Night Vision: Current Research and Future Directions, Symposium Proceedings (1987)

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HUMAN PERFORCE I SSUES l

INTRODUCTI ON Jo Ann Kinney I believe that I represent for this conference the personification of institutional memory, and I am taking my position seriously by pre- senting a brief review of night vision testing over the past 25 years. In 1961, I was asked to do a review of the literature on night vision testing for the Committee on Vision (Kinney, l962~. There was extensive material to review, since the years during and following World War II produced a large number of different tests of night vision and a great deal of research on their reliability and validity. Fortun- ately, William Berry summarized this work in 1949. However, from his assessment he took a rather dim view of night vision testing, and I quote some of his conclusions (Berry, 1949~: One generalization is unfortunately that tests of night vision are not very reliable. Visual acuity, contrast sensitivity, absolute sensitivity etc. have not been convincingly demonstrated as co-varying. Is night vision ability of any sort sufficiently important to the Armed Forces to warrant night vision testing efforts? Two new tests appeared in the 1950s: the Naval Medical Research Laboratory Night Vision Sensitivity Test, for which I was primarily responsible for the Navy, and the Army Night Seeing Tester, done by the Personnel Research Branch of the Adjutant General's Office, which was actually a test of mesopic acuity. My assessment in 1961 was much more upbeat: that night vision testing rested upon a firmer foundation of knowledge than did the war- time tests; that, one by one, important variables were being identified and understood; and that, in general, to answer one of Dr. Berry's questions, night vision testing was feasible. In 1968, I was again asked to assess the measurement of night vision for a meeting of the Committee on Vision; at that time I could find no organized program of night vision testing. In the armed forces, essen- tially nothing was going on; interestingly, the Navy test was on loan to the Army and the Army test to the National Aeronautics and Space Administration. In order to have something to say, I did some new 237

238 research on the correlations among mesopic acuities and scotopic sensitivity, and my review of the literature consisted of that (Kinney, 1968). These data are included in Appendix A. My experience exemplifies night vision testing over the years. Regularly the necessity for night vision testing was disparaged r as each new electronic aid or superior sensing system emerged. And just as regularly it was revitalized as some new combat need surfaced. This cycle was repeated every 5 to 10 years, with the result that very little progress in testing occurred. In the meantime, basic knowledge advanced by leaps and bounds. In 1961, I thought we had learned a lot--if I could have foreseen 1985' In the papers that follow the reader will find not only a wealth of new knowledge but also a very effective and complete summary. Andre Sanders covers the broad topic of visual search, including the major determiners of search effectiveness: structural or display factors and strategic factors. His analysis, which is based upon data obtained primarily from photopic levels of illumination, emphasizes the research needed to apply these results to search at low levels of illu · ~ m~nat~on. Chris Johnson provides an overview of peripheral function, organ- ized under topics of detection sensitivity, temporal contrast sensi- tivity, motion sensitivity, and a variety of suprathreshold functions. This summary provides an excellent example of our new knowledge: for example, spatial and temporal contrast sensitivity were virtually un- known 25 years ago. Dr. Johnson also adds a section on the equipment that would be needed to measure these functions and the areas for which additional research is needed. Cynthia Owsley presents a survey of current knowledge on the effects of aging on night vision which includes senile miosis, increased lenti- cular density, elevated dark adaptation functions, loss of acuity, and increased sensitivity to glare. Dr. Owsley notes that much of our know- ledge on aging and vision comes from investigations conducted at pho- topic levels and that there is a great need for better determinations of the losses at low levels of illumination. Andrew Watson illustrates the advantages of modeling for the study of vision with a number of examples, such as temporal sensitivity, con- trast sensitivity, and motion sensing. He suggests that modeling might also be used effectively in the study of night vision and includes a discussion of the equipment that would be needed to attempt this. Throughout these papers, one is impressed by both the amount of new knowledge of vision and the recurring themes of gaps in this knowledge. Particularly evident among the latter, in all of the summaries, is the sparsity of information on the size of individual differences in the various night vision functions and the fact that we know, in each area, so much more about photopic vision than scotopic vision. The challenges will now be to effectively utilize the knowledge to test night vision, to determine the areas crucial to further understanding, and to pursue these goals despite cyclical variation in the apparent need for night vision testing.

239 REFERENCE S Ber ry, W. 1949 Review of Wartime Studies of Dark Adaptation, Night Vision Tests, and Related Topics. Armed Forces, National Research Council Vision Committee. Washington, D.C.: National Academy of Sc fences . K inney, J .A. S . 1962 Review of literature on night vision testing. Pp. 3-11 in M.A. Whitcomb, ea., Visual Problems of the Armed Forces. l Washington, D.C.: National Research Council. 1968 Clinical measurement of night vision. Pp. 139-152 in M.A. Whitcomb, ea., Visual Problems of the Armed Forces. - tiashington, D .C .: National Research Council.

VI SUAL SEARCH IN VIG I LANT PERK ORMANCE A.F. Sanders In a recent summary of the literature Monk (1984) has correctly noted that the term visual search appears as a loose label for a variety of phenomena and experimental paradigms that certainly do not share a common denominator. In this summary I will follow Monk's sug- gestion to limit the discussion to situations that are characterized by "spatial uncertainty reduction and target uncertainty to a greater or lesser extent" (Monk, 1984, p. 294~. The first property is self- evident. The second property is meant to imply that subjects may either know or not know whether a target is present during a certain time period. In the case of a brief time period--usually defined as the duration of a discrete trial--certainty about the presence of a target leads to an experimental paradigm in which a subject searches for the target until it is actually found. heisser's (1963) classical studies on target search in a letter matrix are prototypical for this paradigm. When subjects are uncertain about the presence of a target, the experimental paradigm becomes one of target search in tachistosco- pic recognition (e.g., Rabbitt, 1967), with probability of detection or detection time as a measure. Rabbitt's studies on ignoring irrelevant information in target search and later work by Shiffrin and Gardner (1972), Shiffrin (1975), and Shiffrin and Schneider (1977) on visual search for predefined targets with a display size between one and four elements are again among the prototypical studies. Alternatively, if the task does not consist of discrete trials but is open-ended and continues for a longer period of time, there is con- tinuing search, resulting in successes and failures of target detection on those occasions that a target is visible. The latter situation con- tains the characteristics of the traditional vigilance situation, as first studied by Mackworth (1950~. Yet it is not limited to situations where targets are relatively rare. For instance, when driving a car there is a continuous search for relevant information which may vary from a monotonous infrequent target situation on an empty motorway to the overload of information in busy city traffic (e.g., Naetanen and Summula, 1975~. In the last case there are almost always targets, and the subjects are faced with the problem of deciding which targets have the priorities for action. It could be argued that the latter situa- tion does not require visual search in the proper sense of the word. Yet, when faced with several targets at once (e.g., Yntema and 240

241 TABLE 1 Major Distinctions of Categories of Visual Search Tests Task type Signal Presence Discrete Trial Openended Trial Certain Searching lists for a Keeping track of several target (Neisser, 1963) several things at once (Yntema, 1962) Uncertain Target detection in Vigilant search for limited search infrequent targets (Rabbitt, 1967) (Mackworth, 1950) Schulm.an, 1967) there can be a visual search problem in that targets at certain positions may be favored in comparison with targets at other positions. Apart from this subdivision (see Table 1) there are various other major distinctions between categories of visual search tests. One important distinction concerns the continuous versus discrete character of the search display. Prototypical examples of the first case are car driving and sonar display inspection, which are characterized by the fact that targets may be found anywhere (e.~., Baker, 19581. An example of the second case is the discrete display inspection, as exemplified in the work of Senders (1984~. A second distinction concerns the size of the display field, where possibly relevant signals may appear. Although the usual visual search studies have dealt with fairly limited displays--as applied to sonar (Vallerie and Link, 1968) or to aerial maps (e.g., Enoch, 1959--there are various other conditions where the search can extend beyond the eye field (Sanders, 19701; this includes head and body movements. A third distinction concerns the extent to which a display is filled with confusing nontargets or, in other words, the extent of clutter. Usually the effects of clutter are more impor- tant in continuous than in discrete displays but they need not be absent in discrete displays, in particular not as the number of alternative signal sources is larger. A final distinction is not so much concerned with the type of search but rather what kind of search modes are per- mitted in the actual experiment. On the one extreme-there are strict instructions to fixate the eye in an attempt to construct the lobe, a probability contour concerned with target detection under conditions of spatial uncertainty at various eccentricities. On the other extreme there are free search conditions usually characterized by analysis of eye movements. The first type of experiment starts from the reasonable assumption that visual search is guided by the limiting conditions of the visual system, and in particular by the properties of peripheral vision. The common f inding that intake of information is limited to f ixations and that there is no useful vision during saccadic eye move- ments--e.~. , Matin (1974--is at the basis of visual studies with the f ixated eye.

242 The studies with fixated eyes have usually centered around issues of structural constraints, while the free search studies have been predom- inantly concerned with questions about visual search strategies. Thus, there is either a relative emphasis on bottom-up type of constraints or on top-down type of analysis. It is interesting to note this difference in emphasis when comparing the proceedings of a symposium on search and the human observer (Clare and Sinclair, 1979) with Rabbitt's (1984) re- cent account (Parasuraman and Davies, 1984~. It may be clear from this attempt toward classification of issues on visual search that this paper would be faced with an impossible task when aiming at a detailed review of the results on each cross-section and discussion. I will limit myself , therefore, to a marginal discus- sion of the issues that are treated in more detail in various recent reviews (e.g., Monk, 1984; Rabbitt, 1984; Wiener, 1984; Megaw and Bellamy, 1979; Bouma, 1978~. In addition I will elaborate some issues that might be relatively neglected in these papers. I will follow a fairly arbitrary distinction between structural-display-related and strategic-related factors in visual search, although a strict separa- tion is hard to maintain. Attentional and cognitive factors can be shown to play an important role in situations that, at first sight, may seem to be largely determined by stimulus. Alternatively, visual search strategies are, of course, never free but always subject to cer- tain display-determined constraints. I will conclude the paper with a brief summary of what I consider to be some relevant future research issues. STRUCTURAL AND DI SPLAY FACTORS A structural analysis of visual search starts with the observation that in all visual scanning the eyes are steady for relatively brief periods of time--200 to 400 ms, perhaps extending to 800 ms under ex- treme conditions--after which there is a rapid shift to a new position. Oculomotor factors appear to require a minimum 200 ms to stop and start (Salthouse and Ellis, 1980), while processing demands constitute a second determining factor. Both components may operate in parallel so that effects of processing demands are only found when the minimal dura- tion is exceeded (Vaughan and Graefe, 19771. In support of this view Sanders and Reitsma (1982) found that stimulus processing starts imme- diately upon fixation--even in the case of a combined eye-head shift where the initial part of the fixation consists of a compensatory eye movement. The most relevant question with regard to visual search is related to the determination of the next fixation during the preceding one. The excellent accuracy in aiming at the next fixation, together with the limited saccadic movement times--about 100 ms for a 40-degree movement (e.g., Sanders, 1963--render a closed-loop explanation of saccadic eye movements quite unlikely. Hence, the new aiming point is supposed to be preprogrammed during the previous fixation, or in other words, the "where to look" of the next fixation is decided during the previous one. Consequently, the properties of peripheral viewing have

243 ~ m sti mulus response stimulus response FIGURE 1 Measurement of the inspection time of the let t signal, the saccadic movement time, and the inspection of the right signal. received a good deal of interest in the visual search literature. This starts with visual acuity prof lies of the common Landolt ring type in conditions without either temporal or spatial uncertainty, which is then extended to conditions with spatial uncertainty (e.g., Michon and Kirk, 1962a; Corbin et al., 1958~. Recent research in this direction concerns covert orientation of attention, which has shown convincing evidence that visual attention can be shifted to a position other than the line of sight. Reaction times are shorter and the probability of detection is improved when a signal occurs at an expected as compared with an unexpected position (Posner, 1980~. Some studies (Poaner et al., 1980; Shulman et al., 1979) suggest that covert orientation can be conceived of as an internal spotlight moving in an analog fashion across the visual field. Presumably there are relations between the intake of peripheral information and the determination of the next saccade. Evidence about peripheral acquisition of information comes from studies like those of Edwards and Goolkasian (1974 ~ and Antes and Edwards (1973 ~ which sug- gest that information load in the per iphery is the most important factor in determining visual performance. Another example concerns work on the functional visual field (Sanders, 1963, 19;0) in which a nonlinear relation was observed between performance and the display angle at which a visual task is carried out. In a typical experiment two signals are presented at equal distances to the left and the right of the subject's meridian. At the start of a trial the left signal is always fixated, followed by a shift to the right signal and a same or a different reaction. This setup enables separate measurement of the inspection time of the left signal (tl), the saccadic movement time (tm), and the inspection of the right signal (tr) (see Figure 1~. In a number of studies (Sanders, 1963; Sanders and Reitsma, 1982; Houtmans and Sanders, 1984), it was consistently found that tr was considerably shorter when signals constitute an eye field rather than a head field display. In the eye f ield an eye movement is suff icient to cover the angle between the left and the right signal, while a supplementary head movement is needed in the head f ield. The interpretation of the

244 reduced tr in the eye field--which was recently confirmed in a number of additional studies (e.g., Sanders and Houtmans, 1984)--is that, while fixating the left signal, subjects acquire a hypothesis about the right signal, as long as the visual angle does not exceed the eye f ield. This hypothesis is checked during the subsequent fixation of the right signal--an activity that takes less time than when a full new percept needs to be formed, which is supposed to occur in the head field. The implication of these results is that as long as search is lim- ited to the eye field, more or less pronounced hypotheses are obtained about all signals that are present in the eye field. me hypotheses would allow direct shifts of the eye to the most relevant signal for additional close inspection. In the head field the processing mode undergoes a basic change since no parallel hypotheses about all pre- sent signals are obtained. In line with the work on covert attention, Houtmans and Sanders (1984) found evidence that the acquisition of peripheral hypotheses does not run off automatically but involves controlled processing. Yet, it should be fully clear that these considerations are at best a small part of the visual search story. One of the main limitations is that the work discussed so far is concerned with a largely empty visual field, while, as mentioned above, more structured visual dis- plays are more common. In a review Bouma (1978) has discussed several structural constraints of more cluttered visual fields, including the effects of lateral inhibition of surrounding items. Although the effect of lateral inhibition has been known for a long time, systematic inves- tigations have not been carried out before the 1970s. Figure 2 shows the pronounced effects of lateral inhibition on visual performance in the periphery. At present there is much more detailed knowledge about various parameters affecting the size of the effect, including angular distances between target and noise letters, the extent of eccentricity, the number of noise letters, the right versus left visual field, and shape differences between target and noise. Engel (1977) has put for- ward the idea that subjects carry out about random saccadic shifts until the target is in the area where it can be peripherally detected. Subsequently, a rapidly directed accede brings the target into foveal vision and, hence, to detection. This was tested by presenting sub- jects with a background of identical disks, except for two disks which deviated in size. First the lobe--the area of display around the cen- ter of fixation, within which a target can be detected with some proba- bil~ty--was determined for each individual subject by tachistoscopic recognition, "hereafter they searched for targets in a search study during which saccades were recorded. The functions did not fully coin- cide, but they still had a fair degree of common variance, to suggest that this type of model has promise. It is doubtful whether the pre- detection search is really random or continuously tests the most likely hypothesis available (e.g., Bloomfield, 1972, 1975; see also Cohen's model, 1981~. In addition to the factors mentioned above that affect lateral interference, the size of the lobe is affected by a range of display variables. Display density; display size; the number of nontargets (e.s., Drury and Clement, 1978~; the degree of homogeneity of

JO ~8 245 ~j ~ ~T ~1 I' ~ /a/ 0 O 2 ~ cocontrldty (degrees) \,0` _I 6 8 10 12° FIGURE 2 The pronounced effects of lateral inhibition on visual perfor- mance in the per iphery. nontargets; shape, size, and color; and the regularity of the display (Bloo~r.f ield, 1972) are factors that are discussed in more detail by Monk (1984). Color effects have received the most interest (Green and Anderson, 1956; Von Wright, 1970; Noble and Sanders, 1981) and turn out to be the most powerful cue in visual search. It should be noted, though, that to be effective, the targets should always have the same color. If targets have another color, their detection is either impoverished or the color cue becomes ineffective as a means of Sating information (Posner, 1964; Noble and Sanders, 1980). The properties of the nontargets are quite relevant in determining the efficiency of visual search. The effect of physical similarity between nontargets and targets was convincingly shown in the classical studies of Neisser (1963). Effects of clustering of nontargets have been found by Banks and Prinzmetal (1976), while Rabbitt (1967) was the first to demonstrate the effect of the constancy of nontarget patterns. Subjects do not only learn how to search for targets they also learn how to ignore irrelevant information, and this is most easily achieved when the nontarget items are characterized by constancy in spatial loca- tion and content in relation to the targets (see also Prinz, 1979). In other words targets, as defined at some trials, should preferably not appear as nontargets at later trials and vice versa. This principle is also at the basis of the work of Shiffrin and Schneider (1977) on auto- matic and controlled processing. In the case of consistent mapping of targets and nontargets, automatic detection responses to targets develop in a parallel processing mode of all items in the display set. Alter- natively, in the case of variable mapping of targets and nontargets, Schneider and Shiffrin (1977) found evidence for a sequential controlled search through the items of the display set.

246 A separate class of factors in determining whether a target is suc- cessfully detected and recognized concerns the size of target set--or the number of alternative targets to be searched for. Although an early paper by Neisser et al. (1965) had suggested that searching for ten tsr- gets at once was about equally effective as searching for one target only, most recent research has consistently found effects brought about by the size of the target set, although constant categorical and dimen- sional properties can moderate the size of the effect. The greater part of Rabbitt's (1984) paper is devoted to the question of what to look for. STRATEGIC FACTORS Various strategic elements were briefly discussed in the previous section, among the most prominent of which are the attentional bias in covert orienting (Poster, 1980), controlled processing in the acqui- sition of peripheral hypotheses (Sanders and Houtmans, 1984), and con- trolled processing in the question of what to look for (Schneider and Shiffrin, 1977~. Another interesting example stems from the work of Moraal (1975) on signal detection during either dynamic or static in- spection of large noisy visual displays. A considerably lower d' value was obtained with dynamic presentation, where 1 x 1 m displays moved across the visual field. This is in agreement with results suggesting a reduced dynamic vision compared with static vision (e.g., Ludvigh and Miller, 1958; Erickson, 1~64~. Yet, the condition of static presenta-' tion proved to be more sensitive to the effect of night sleep depriva- tion (Figure 3~. This result suggests that certain mechanisms that are involved in static presentation--presumably a readiness to scan the static display as efficiently as possible within the allocated viewing time--play less of a role in dynamic inspection. This agrees with the conclusion of Erickson (1964) that, in dynamic presentation, subjects give up scanning and merely fixate on the center of the visual display in an attempt to detect the targets. This latter strategy would seem to be more passive than active scanning and, therefore, would be less liable to sleep loss. Yet, the really strategic factors in visual search have' usually been related to more or less cognitive scanning patterns and their changes as related to environmental and organismic factors. A convenient starting point for this discussion is the work on inspection strategies of a lime ited number of displays, as initiated by Senders (1964, 1967, 198~), which, however, can be easily extended to freer search conditions, for example, automobile driving (Senders et al., 19671. This is also the area in which considerable effort has been devoted to mathematical modeling of visual search behavior, an excellent discussion of which can be found in Moray (1984~. Much of the work in this area derives from inspection of displays, as observed by pilots. Senders' (1984) original models were in the information theory tradition, which were current in the 1950s and which sought to describe inspection behavior in terms of reconstruction of the temporal course of the signals that appeared on the displays. Later models started from the idea that

247 2.2 1 ~ , ~ :_ Sol_ / - ~\ ~ i\ ~\\ , 1~ - - ~ 1 E 1 - Q1~ 1.0 0.8 OHS ~ _ ~ ., ./ first day second day I 1 2 3 4 S test ses s ion . dyn.sleeping .__ dyn.waking ~ ~ stat. sleeping 0~4 stat.wak ing FIGURE 3 Effect of night sleep depr ivation. Abbreviations : dye., dynamic; stat., static. inspection of a certain instrument is conditional on the probability that a certain critical value is exceeded. Apart from the time elate sing since the last inspection, this probability depends, of course, on the speed and the rate of change of the signal, while some personal fac- tor of forgetting is also thought to play a role. In addition, Moray (1984) describes various models that add elements of decision making by assuming that there are costs for each observation and missed signal an~a benefits for each correctly detected signal in determining the critical value of the interval between successive f fixations. It should be noted that, in comparison with the mathematical sophis- tication of the models, the empirical evidence is extremely meager. For example, according to the conditional sampling models, the next fixation is supposed to depend on the state of the observed signal at the previ- ous fixation. If that state was close to the critical limit, the next fixation should be sooner than if it was far away from the critical limit--depending, of course, on speed and rate of change. Moray (1984) notes that obtaining the necessary eye movement records "is a task that even today is beset with formidable technical problems" (p. 502). This is especially valid with regard to obtaining proper combinations of the states of the instruments and the moments of fixation. Yet, the tine is about ripe to carry out the relevant studies, given the steady

248 progress in data-processing techniques of eye movements and the pos- sible links to computer-controlled stimulus processes. In addition Senders et al. (1967) already have suggested a visual occlusion technique for evaluating the environmental information load-- particularly in everyday life situations, like car driving, in which the signal situation is not easily defined. Today, more sophisticated versions of this idea are available which should allow rapid progress in this area. In the absence of systematic data on dynamic display eye movement relations, research on the strategic aspects of search has mainly cen- tered around (1) scan path analysis of static displays and (2) infer- ences about search strategies from general performance data. With respect to scan paths, various authors have emphasized the notion that, in scanning a visual display, the observer uses visual schemata of the environment to guide his or her exploratory behavior (Stark and Ellis, 1981~. In addition the goals of the search process and the knowledge about ongoing processes affect the scan path. This was clearly demonstrated in the now classical studies by Yarbus (1967), who showed that scan paths of a painting depend on the type of probe questions that are asked before the start of the scan. Despite the ample evidence in favor of effects of strategic factors on scanning, a major question remains: to what extent are scan paths fixed by the oculomotor system or by prepared programs that run oft automatically-- e.g., scanning from left to right as in reading--and to what extent can flexible and adjustable strateg ies be employed? Where strateg ies pre- vail the question immediately follows, what are the controlling agents (Levy-Schoen, 1981~? It is probably fair to say that the microstruc- ture of scan paths is probably quite auto~natic--like in the succession of f ixations and saccades in reading--while the microstructure, e.g., biasing certain areas of the visual f ield, is more under cognitive con- trol. So far little is known about the actual interrelations between automatic and controlled aspects of visual search and about the condi- tions under which either mode predominates. This is a good point to br ief ly mention the of ten observed (Mackworth and Mackworth, 1958; Stark and Ellis, 1981) but little unaer- stood phenomenon of looking without seeing, i.e., the finding that, at least on occasion, a target is f ixated but not detected. Although f ixa- tion seems to be a necessary condition for detection, it is not suffici- ent. The circumstances under which looking without seeing are found are little researched. I t is not implausible to suppose that the phenomenon occurs not when f ixation on the target is directed by earlier per ipheral information but when, instead, the gaze hits the target position unin- tentionally. With regard to inference of search strategies from performance data, there are several lines of search largely i n the context of effects cuff long-term performance, inspection behavior, and environmental stressors. For instance, in vigilance tasks, many studies indicate a reduction of correct detections and slowing of reaction speed when spatial uncer- tainty is introduced (e.g., Bergum and Lehr, lg63; Adams and Boulter, 1964~. More importantly, there is the long-stanaing notion of funneling of attention to Snore centrally located signals as the watch continues

249 over time. Bartlett (1953) has even suggested the funneling effect as a criterion for fatigue. Funneling suggests a change in search stra- tegy as time goes on in monotonous situations. Perhaps because of its strategic nature, the effect is not particularly stable and can easily be overcome by motivation or instruction. For example Baker (1958), while observing a funneling effect in vigilant performance on a simu- lated radar screen, was able to show that the funneling effect can be easily changed by biasing attention toward the periphery of the screen. The funneling effect is also implicit in the work of Michon and Kirk (1962b) who found fewer eye fixations in the periphery of the screen at the end of a work shift. Sanders (1963) reported results on a vigilance task where subjects had to detect an increase in brightness in any of 16 light sources that were grouped in one centrally located subset of 8 lights and two peripheral subsets of 4 lights each. When the total dis- play did not exceed the eye field, reaction times to outer light signals were considerably longer than the central light signals--suggesting a stronger emphasis on the central lights. In contrast, when the total display exceeded the eye field, reaction times to central light signals were even longer than those to outer light signals--suggesting that subjects turn their head from the peripheral group of lights located at the left, to the peripheral group of lights located at the right, and vice versa, while neglecting the central lights. This changed at the end of the 2 h watch--suggesting that subjects got satiated to shifting their attention all the time; instead, they turned to a more passive strategy of fixating the central group of lights while neglecting the peripheral group of lights. It is likely, therefore, that the funneling effect corresponds to a change from a more active orientation to a more passive reception of data from the outside world. If this is the case, funneling will be only observed under conditions where more passive processing leads to less emphasis on the peripheral field of view. Evidence in favor of changes of visual sampling strategies can also be found in the literature on effects of environmental stressors such as noise and sleep loss. For example, Jerison (1957, 1959) failed to find an effect of noise on a simple clock test vigilance task but found a pronounced impairment of performance when subjects monitored three clocks at the same time. This result fits more recent evidence that noise has the effect of increased visual selectivity, i.e., greater concentration on a specific part of a display at the neglect of other parts (Hockey, 1970, 1973~. Similarly, sleep loss can have the effect of a more diffuse cue utilization and less attentional selectivity (Hockey, 1970~. It should be noted, though, that, as with funneling, these effects are not extremely stable (Loeb and Jones, 1978~. There is a clear need to investigate more systematically strategic effects on visual search and scanning, including measures that go beyond the most simple performance measures of time and signal detection.

250 CONCLUSION With regard to the efficiency of signal detection, it is probably fair to say that the conclusion of Corbin et al. (1958) that "the best search method is no search at alla still holds in the sense of a recomb mendation to create situations permitting direct detection of signals. Conditions where this seems to be possible include (a) easily visible targets on an empty or clearly discriminable background (e.g., deter- ministic color differences) and (b) consistent mapping conditions allowing for automatic detection responses. In all other cases search times increase about linearly as a function of a whole score of vari- ables, as briefly outlined in this paper. Depending on the organiza- tion of the display, search either proceeds in the very regular way of reading from left to right and from top to bottom, or in a more random scan through the display, with the restriction that the next fixation is likely to be at least partly determined by information gathered during the previous fixation. Although the display constraints are known to interact with top- down type of visual search strategies, which are liable to effects of fatigue and stress, little is known either about the more precise rela- tions between strategies and display constraints or about the set of possible search strategies that are actually used. The most pressing research needs in the field of visual search seem to center around these interactions. This requires (1) hypotheses about the possible search strategies at various levels of conscious control, with accom- panying tests about the possibility of their implementation by instruc- tion; and (2) systematic variation of instructed strategies, together with various display characteristics, to determine the relative effici- ency of the strategies under these various conditions. Interesting questions in this respect include the relative weight of peripheral information compared with strategic rules in determining the position of the next fixation pause in free search and the effect of cognitive factors (forgetting, expectancy, hearing, and so on) in determining where to look next. More specificially, the time is ripe to carry out the relevant empir ical studies aimed at the evaluation of existing mathematical inspection models; again, current display tech- niques enable changes of the display during saccadic eye shifts to study the effect of stable versus changing backgrounds on performance in search tasks. In the literature this approach has already led to interesting results, the scope of which should be further determined (e.g., Rayner et al., 1981~. REFERENCES Adams, J.A., and L.R. Boulter 1964 Spatial and temporal uncertainty as determinants of vigilance performance. Journal of Experimental Psychology 67: 127-131. Antes, J .R., and D.C . Edwards 1973 Information processing in the visual per iphery. Bulletin of the Psychonomic Society 1:351-353.

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PERIPHERAL VISUAL FUNCTION AT VARIOUS ADAPTATION LEVELS Chr is A. Johnson OVERVIEW OF PERIPHERAL VI SION FUNCTION Visual performance is often evaluated with respect to the func- tiona~ properties of the fovea. However, extrafoveal response characteristics play an important role in orientation and mobility skills (Marron and Bailey, 1982; Verriest et al., 1985J, driving performance (Johnson and Keltner, 1983; Verriest et al., 1985), initiation of eye and head movements to fixate objects of interest (Verriest et al., 1983), and related visual tasks. The peripheral visual field differs from the fovea in terms of the optical quality of the retinal image (Ferree et al., 1931; Jennings and Charman, 1981, 1978), anatomical and physiological properties of underlying visual mechanisms (Cohen, 1975; Fukuda and Stone, 1974), as well as other factors. It is therefore interesting to compare the functional pro- perties of foveal and peripheral vision and to evaluate their signi- ficance for different visual tasks. This paper will provide an over- view of selected peripheral visual functions (detection sensitivity, visual acuity, spatial and temporal summation, spatial and temporal contrast sensitivity, and motion sensitivity) at different levels of illumination. Considerations for testing the peripheral visual field and a discussion of several peculiarities of peripheral vision will also be presented. At photopic background luminances, detection sensitivity is highest at the fovea and declines with increasing visual field eccentricity. Reductions in background luminance increase detection sensitivity, but to a greater extent for visual field locations beyond 5 degrees than for the fovea. This produces an isosensitivity plateau over the central 30-degree visual field at mesopic background luminances and a foveal scotoma (localized area of reduced sensitivity) in the center of the isosensitivity plateau at scotopic background luminances (Figure 1~. These characteristics of peripheral visual field sensitivity have been reported by many investigators (Aulhorn and Harms, 1972; Harvey and Poppel, 1972; Johnson et al., 1981~. Figure 1 presents the mean and standard deviation of visual field sensitivity profiles obtained in 10 normal observers at seven different background luminances ranging from low-photopic to scotopic levels. These data indicate that inter individual var iation increases as a 256

257 ~ L nave l temporal 0,0 0,1 L,~ 0~_~ AL Ash Aground l | luminance | ,0~' 1 ~L, ~ ~ coo 50° 40° 30. 20. 10° 0° 10° 20° 30. LO° 50° 60° 70. 80° 90° FIGURE 1 Detection sensitivity profiles of the visual field as a func- tion of different background luminance levels. Source: E. Aulhorn and H. Harms (1972) Visual perimetry, in Handbook of Sensory Physiology Vol. VII/4. Berlin: Springer-Verlag. function of both increasing visual field eccentricity and decreasing background luminance. Intraindividual variation exhibits similar characteristics for different visual field locations and background luminances (Aulhorn and Harms, 1972~. Because other visual functions in the periphery also display these large inter- and intraindividual differences, they may represent an important factor in predicting performance skills for tasks that depend on peripheral vision. Visual acuity at photopic luminance levels exhibits an approximately linear decrease from the fovea out to the periphery, when the data are plotted according to the log minimum angle of resolution (Kerr, 1971; Johnson et al., 1978~. In addition to large inter- and intraindividual variations in peripheral visual acuity, there are also significant dif- ferences in the peripheral visual acuity measurements that have been reported by various investigators (see Johnson et al., 1978~. These differences can be attributed to the use of trained versus naive observers, the type of acuity target employed, the methodology used to obtain visual acuity measurements, and related factors. Figure 2 presents peripheral visual acuity- measurements from seven different investigators. All of the curves depicting visual acuity as a function of eccentricity have a similar shape, but there are considerable dif- ferences in the absolute acuity values repor tee by each of the studies. With reductions in background luminance, there are decreases in visual acuity at all visual field locations. However, the influence of lumi- nance on visual acuity becomes smaller with increasing visual field eccentricity (Mandelbaum and Sloan, 1947~.

258 05 00 - to ~ _ _ Oe 5 :~- _ cat of: _ ~ -1.0 -1-51 Q \ jiL`~% \\ \: '` -~-Millodot et al. ( 1976) ---I-- Fick ( 1898) . ~.Kerr ( 1971) · Present results -- ~ --Wertheim (1894) - --o---Low (1951) -- · --Mandelbaum and Sloan (19471 -.,:` hNN ": ~% >~ PRESENT ~` a';; ,` RESULTS , . I ~ I , I ~ 0 10 20 30 Visuel Field Eccentricity (deg.) FIGURE 2 Peripheral visual acuity measurements obtained by seven  different investigators. It is difficult to directly compare detection and resolution pro- perties of the peripheral visual field, because different dependent variables are measured for each function. Visual detection thresholds are specified by a minimum stimulus luminance, whereas visual acuity is denoted by a minimum angle of resolution for stimulus detail. Aulhorn

259 and Harms (1972), in their design of the Tubinger perimeter, devised a procedure for measuring detection and resolution properties at any visu- al field location using the same stimuli and the same dependent measure (luminance) . The stimuli consist of circle and square target pairs of varying size. For each pair, the area of the circle and square targets is nearly the same (less than 7 percent difference) and luminance detec- tion thresholds for the two targets are usually within 0.1 log unit of each other. Resolution discriminations are made by the observer on the basis of whether or not there are corners present on the target from one trial to the next. The distance between the outer edge of the circle and the corner of the square is 0.15 times the diameter of the circle, which defines the critical detail for the minimum angle of resolution. Although this type of acuity determination differs from conventional approaches, it has been shown that visual acuity measurements using the Aulhorn and Harms procedure compare favorably with standard acuity measurement techniques (Aulhorn and Harms, 1972; Johnson et al., 1978~. The Aulhorn and Harms procedure allows luminance thresholds to be ob- tained for both detection and resolution tasks using the same stimuli, thereby permitting direct comparisons of the two visual functions. Seven target pairs are available on the Tubinger perimeter, with circle diameters of 7 (20/20), 10 (20/30), 17 (20/50), 26 (20/80), 42 (20/12S), 66 (20/200), and 12 (20/333~. Other details of the stimulus attributes and methodology can be found in Aulhorn and Harms (1972) and Johnson et al.~1978, 1981) . Figure 3 presents a comparison of detection and resolution thresh- olds for five target sizes (10 min arc, 20/30 through 66, 20/200) in the central 30-degree visual field at a low photopic background level. Both detection and resolution sensitivity profiles become flatter (toward isosensitivity) for larger stimulus targets, although the effect is much more prominent for resolution than for detection. For all target sizes, the resolution profiles show a more rapid decline with eccentricity than the detection profiles. The resolution cutoffs (visual field locations corresponding to the resolution threshold at maximum stimulus luminance) are consistent with peripheral visual acuity measurements using conventional acuity measurement techniques, as indicated by the curve labeled "Present Results" in Figure 2. The relationship between detection and resolution sensitivity prow files is altered by lowering the background luminance (Johnson et al., 1981) . Figure 4 presents detection and resolution sensitivity profiles for the 10 min arc (20/30) target at five background luminances from low-photopic to scotopic levels. For detection sensitivity, reductions in background luminance produced typical changes in the sensitivity prof lie from a photopic g radient to a mesopic isosensitivity plateau to a scotopic foveal scotoma. Resolution sensitivity profiles, however, did not vary appreciably with changes in background luminance. Similar detection and resolution data were obtained for the 17 min arc (20/50) target (Figure 5) and the 28 min arc (20/80) target (Figure 6), with the exception of two new findings. First, the isosensitivity plateau and the foveal scotoma for the detection sensitivity profiles are pre- sent at higher background levels than for the 10 min arc (20/30) target. Second, the resolution cutoff is at greater visual field eccentricities for the larger targets.

o.o 1.0 2.0 0.0 I.C 2.C _ 9 °0.0 I cr. LO con ~ 1 0 Z , Lo cn cut 'A ~ 2.0 to J 0.0 .0 0.0 1.0 2.0 10' _ ' ~ - it ~ ~ ~ ~ ~ I . 1, . . . . . 17 JO WfJ; ,6 . . . 6, . . . 1 -a' ', , , 1, 26. - , , , .1, . , , . ~ . . , )~ ~ a ff ~ ~ ~ - 30 20 10 0 10 20 30 ' TEMPORAL NASAL- ~ VISUAL FIELD ECCENTRICITY(deg.)  o.o 1.0 2.0 0.0 1.0 2.0 - C~ an ~ V.V - - ~n · 0 1.0 it, to 2 0 'A I 0.0 1.0 ' , 0.0 '.0 2.0 FIGURE 3 Static (detection sensitivity) and acuity (resolution sensi- tivity) profiles of the visual field for 10', 17', 26', 42', and 66' target sizes at photopic background luminances.

261 -3.0: -2.0t -1.0 0.0 - ._ - ._ c in l.0 cr. J C) O 2.0 in -3.0 - - I, - 2.0 c' . _ J Cot o -1.0 0.0 1.0 2.0 10 (20/30) Target STAT I C PRO Fl LE N ~ I. ~ ~ In. off Background Luminance ~[~ · · 3.18 cd/m 0 0 0.32 cd/m 0.032 cd/m or 0.0032 cd/m2 · 0.00032 cd/m2 ACUITY PROFILE 30 20 10 0 10 20 30 ~ Nasal VISUAL FIELD ECCENTRICITY(De9) Temporal ~  FIGURE 4 Static (detection sensitivity) and acuity (resolution sensi- tivity) prof lies of the visual f ield for 10' target size at 5 different background luminances.

262 -2.0 30 17 (20/SO)Target ~ `~_ IN ~ _,, I_ ~- -1.0 0.0 1.0 g J 2.0 -3.0 - ~ -2.0 c c' ._ J 1.0 _ 1 o.o 1.0 2.0 0~ toe - tr~-~, 1~ Background Luminonce | . . ~ ~ 3.18 cd/m2 to 0.32 cd/m2 ~ ~ 0.032 cd/m2 onto 0.0032 cd/m2 ~ 1 · · 0 00032 cd/m2 1 , . . . ACU ITY PROFI L E 30 20 10 0 10 20 30 · Nasal VISUAL FIELD ECCENTRICITY(Deg) Temporal ~ FIGURE 5 Static (detection sensitivity) and acuity ~ resolution sensi-  tivity) prof lies of the visual f ield for a 17' target size at S cliff er- ent bac Aground luminance s.

263 -3.0 -2.0 -1.0 1 Do - ._ . - c ~ 1.0 _ 9 2.0 Go I in I -3.0 -1.0 0.0 1.0 2.0 26' (20/80) Target S T AT I C P R O F I L E a' __ Background Luminance ~- ~ ~ 3.18cd/m2 C 0 0.32 cd/m2 0.032 cd/m2 0.0032 cd/m2 · · 0.00032 cd/m2 ACUITY PROFILE loo , ,  30 20 10 0 10 20 30-- --- -- Nasal VISUAL FIELD ECCENTRICITY(Deg) Temporal-- FIGURE 6 Static (detection sensitivity) and acuity (resolutior~ sensi- tivity) profiles of the visual field for a 26' target size at 5 differ- ent bac Aground luminances.

264 m e 42 min arc (20/125) target shows a similar trend for the detec- tion sensitivity profiles (Figure 71. The resolution sensitivity pro- files, however, demonstrate changes associated with reductions in the background luminance. An isosensitivity plateau and a foveal scotoma are present for the resolution sensitivity profiles at low background luminances. However, these features appear on the resolution sensitiv- ity profiles at background luminances that are about 1 log unit lower than their occurrence on the detection sensitivity profiles. A similar pattern can be observed for the 66 min arc (20/200) target (Figure 8~. The detection and resolution sensitivity results can be summarized as follows: (1) resolution luminance thresholds are affected by target size and eccentricity by a greater amount than detection luminance thresholds; (2) resolution sensitivity profiles for small targets {20/80 or less) are minimally affected by changes in background lumi- nance, whereas resolution sensitivity profiles for larger targets (20/125 or greater) and detection sensitivity profiles for all target sizes display distinct changes in their visual f ield sensitivity that correspond to photopic, mesopic, and scotopic profiles; (3) the reso- lution limit of scotopic mechanisms appears to be between 20/80 and 20/125, based on the present findings; (4) the background luminance associated with a photopic gradient profile, a mesopic isosensitivity plateau, and a scotopic foveal scotoma varied with both the target size and the type of visual task (detection versus resolution) Spatial summation properties of the peripheral visual field have been evaluated by Wilson (1970), who reported that the basic charac- teristics of spatial summation curves from the fovea out to 55 degrees eccentricity were similar. The size of the summation region increased and overall sensitivity decreased for greater visual field eccentrici- ties, but translation of the spatial summation curves for all visual field locations along the log dI/I (Intensity) axis, log area axis, or both produced a superimposition of all the curves. Wilson concluded that spatial summation properties are invariant across the visual field. m e spatial contrast sensitivity function has been thoroughly evaluated from the fovea to 50 degrees eccentricity by Koenderink and colleagues (1978a,b,c,d). At photopic background luminances, contrast sensitivity for all spatial frequencies exhibited a progressive decrease from the fovea out to greater visual field eccentricities. High spatial frequencies were not detected in the periphery, and the spatial frequency cutoffs at various eccentricities were consistent with the decline in visual acuity and resolution in the periphery. The general form of the contrast sensitivity function was highly similar for all visual field locations. When mesopic and scotopic background levels were employed, only low and middle spatial frequencies could be detected, and midperipheral target locations displayed greater contrast sensitivity for these targets than the fovea. These results are there- fore in general agreement with the luminance threshold data for resolution of the circle-square target pairs. Temporal contrast sensitivity and temporal summation characteristics of the peripheral visual field have been evaluated by Dunn and Massof (1983~. m ey measured temporal summation properties for increment

265 -2.0 42't20/~25) Targe! ST AT ~ C P R O F ~ ~ -3.0 ~,-_~ ~ ~ -~L -1.0 0.0 1.0 -3.0 -I .0 0.0 1 ~ 7~, sf~<' ·~ of Background Lum,nonce · · 3.18 cd/m2 ° 0 0.32 cd/m2 G 0.032 cd/m2 to 0.0032 cd/m2 · · 0.00032 cd/m2 ACUITY PROFILE at' 111' I_ . _ ~ Nasal VISUAL FIELD ECCENTRICITY(Deg) Temporal --- FIGURE 7 Static (detection sensitivity) and acuity (resolution sensi- tivity) prof lies of the visual f ield for a 42' target size at 5 dif fer- ent background luminances.

266 -3.0 -2.0 -1 .0 loo - c in 1.0 Cat 2.0 -3.0 - 4,, - 2.0 A C, ._ 3. Cal -I .0 668(20/200)Targe~TAT I C PROFI -N; to _ - . ,~ ~1 Background Luminance ~ ~ 3.18cd/m2 ° o 0.32 cd/m2 ~ 0.032 cd/m2 _ to 0.0032 cd/m2 · · 0.00052 cd/m2 , . . , . ACUITY PROFIT ¢; - rem _ -hi E 30 20 10 0 10 20 30 ~ Nesal VISUAL FIELD ECCENTRICITY(Deg) Temporal- FIGURE 8 Static (detection sensitivity) and acuity (resolution sensi- tivity) profiles of the visual field for a 66' target size at 5 differ- ent background luminances.

267 thresholds at photopic background levels from the fovea out to 50 degrees eccentricity and found that temporal summation did not vary across the visual field. Temporal contrast sensitivity functions were also measured and found to be constant for all visual field locations. A similar invariance of the temporal contrast sensitivity function throughout the visual field was reported by Ronchi and Molesini (1974) for scotopic background levels. Ronchi and Molesini also measured temporal summation characteristics of the peripheral visual field at scotopic levels, using two different methods to define the temporal summation limit. With one method the summation limit appeared to be invariant with visual field eccentricity, whereas the other method indicated a modest increase with increasing visual field eccentricity. Motion sensitivity at photopic background levels exhibits a system atic decrease from the fovea out to 60 degrees eccentricity (Johnson and Leibowitz, 1974; McColgin, 1960J. Various parameters such as target size, luminance, type of stimulus motion, duration of movement, the presence of reference lines, and other features have been reported to influence motion thresholds (Johnson and Scobey, 1980, 1982; Post et al., 1984; Scobey and Johnson, 1981a,b). However, these effects are generally similar for both foveal and peripheral motion sensitivity. Few studies have been performed for motion sensitivity at mesopic and scotopic levels. Gordon (1947) evaluated motion, form, and displace- ment thresholds at scotopic luminance levels for visual field eccen- tricities out to 50 degrees. Gordon reported that the thresholds for form, motion, and displacement were linearly related for all background luminances and visual field eccentricities examined. At all visual f ield locations, motion sensitivity at scotopic background levels was poorer than for photopic backs round luminances. There was a smaller effect of luminance on peripheral motion thresholds than for the fovea; this is similar to the results reported for peripheral visual acuity and background luminance. The majority of the literature pertaining to spatial and temporal properties of peripheral visual function at different background levels supports the following summary statements. (1) Spatial and temporal properties of visual function at all adaptation levels are invariant across the visual field, with the exception of high-spatial-frequency cutoffs for greater peripheral visual field eccentricities. (2) Changes in background luminance have a larger effect on foveal visual functions than on peripheral visual functions, except for increment thresholds. (3) As the background luminance drops to scotopic levels, the midperi- phery becomes more sensitive than the fovea. However, at photopic and mesopic adaptation levels, the fovea is equal to or better than the periphery for all spatial and temporal visual functions. (4) Most of the differences between the fovea and periphery for spatial and temporal functions are quantitative rather than qualitative. PECULIARITIES OF PERIPHERAL VISION The visual functions discussed to this point have been concerned with the threshold characteristics of visual field locations for various

268 spatial and temporal parameters of visual function. In general) these characteristics are quite similar for the fovea and periphery. The appearance of suprathreshold objects in the periphery, however, can often be considerably different than for foveal viewing. This section will describe several peculiarities associated with the appearance of objects in the peripheral visual field. It is well known that with steady fixation, a stationary object in the periphery will fade or disappear within a brief period of time (the Troxler effect). A related phenomenon has been reported by a number of authors for slowly moving objects in the peripheral visual field (Campbell and Maffei, 1979, 1981; Cohen, 1965; Day, 1973; Enoch et al., 1976; Hunzelmann and Spillman, 1984; MacKay, 1982; Tynan and Sekuler, 1982~. The various perceptual effects that have been reported for this phenomenon include a reduction in the apparent velocity of the moving object, a total cessation of movement, disappearance of all or part of the moving object, fragmentation of the object, and pulsations or wave- like motion of the object. These effects occur within a very short time period (typically 10 to 80 s), with the onset of the effect being more rapid for greater visual field eccentricities. These effects seem to be more robust for the temporal retina than for the nasal retina and have been reported to display intraocular transfer. It has also been noted that a motion aftereffect is generated by the object, even if it perceptually appears to be stationary. A variety of parameters have been reported to influence the magni- tude and latency of this effect: (1) greater visual field eccentrici- ties have a shorter latency and a greater magnitude than locations closer to the fovea; (2) slow stimulus velocities (less than 2 degrees/s for rotary movement, less than 4 degrees/s for linear movement) produce larger effects than fast velocities; (3) the number of elements or spa- tial frequency of the stimulus affects the magnitude of the effects; (4) the more spatially and temporally periodic the stimulus, the larger the effect; (5j reduced contrast and luminance decrease the latency and increase the magnitude of the effect. To account for the reduction in apparent velocity and disappearance of moving objects in the periphery, various authors have proposed that rapid adaptation of movement-selective mechanisms is responsible for the effect. Other possible interpretations include backward masking, a balance between antagonistic mechanisms sensitive to movement, and dif- ferences in the central and peripheral distribution of motion-sensitive and position-sensitive mechanisms. However, a completely satisfactory explanation of these phenomena has not been presented to date. A related phenomenon has been reported by Frome et al. (1981) for dark-adapted increment thresholds obtained with a temporally periodic presentation method. Within a period of several minutes to half an hour, sensitivity to a peripheral target decreased by as much as 1.2 log units when the stimulus was presented in a rhythmic sequence. The sensitivity loss persisted for a considerable period of time after ces- sation of the stimulus pattern, was present for both the rod and cone systems (and exhibited transfer between the rod and cone systems), and was specific to the size and spatial frequency of the stimulus. How- ever, there was no orientation specificity to the effect, nor did it

269 transfer interocularly. The authors interpreted these findings in terms of habituation of size- and frequency-selective mechanisms in the mono- cular visual pathways. The apparent brightness of objects in the periphery is also an interesting phenomenon. Although detection sensitivity declines with increasing visual field eccentricity, Poppel and Harvey (1973) have re- ported that the subjective brightness of suprathreshold targets remains constant across the visual field for a fixed stimulus luminance. Thus, at threshold targets appear to be brighter in the periphery than at the fovea. At all eccentricities they examined, there was a monotonic rela- tionship between stimulus luminance and apparent brightness. The apparent size of objects in the periphery is also different from that in the fovea. As described by Bedell and Johnson (1984), various investigators have reported that objects in the periphery appear larger than with foveal viewing, whereas others have reported the opposite effect (Newsome, 1972~. In the Bedell and Johnson study, there was an increase in the apparent size of objects in the periphery as their luminance was increased. A stimulus in the periphery could appear to be either larger or smaller than a foveal reference, depending on the luminance of the peripheral target. The effect of luminance on appar- ent size in the periphery was more pronounced for small targets than for larger ones. A model was proposed to account for the changes in apparent size with variations in luminance in the periphery, based on the optical properties of the central and peripheral visual field (Jennings and Charman, 1978, 1981) and the distribution of activity within overlapping receptive fields. The results of studies evaluating apparent brightness, apparent size, and the fading and disappearance of slowly moving or temporally periodic stimuli in the periphery indicate that the appearance of ob- jects at nonfoveal locations can vary considerably. The influence of these perceptual phenomena on other visual skills such as judgments of distance, visual search, vigilance, and related performance tasks is not known at present. Further research is needed to understand these perceptual effects in the peripheral visual fields and their relation- ship to performance of tasks that rely on peripheral vision. RECOMMENDED RESEARCH PROJ ECI S Previous studies have shown that peripheral visual function is an important factor in or ientation and mobility tasks (Marron and Bailey, 1982), driving performance (Johnson and Keltner, 1983), and related skills (Verriest et al., 1985~. However, these investigations examined decrements in performance that were associated with the loss of visual function in various portions of the visual field due to ocular or neur- ologic disorders. The relationship between peripheral visual function and task performance in observers with normal visual fields has not been systematically evaluated. In view of the large individual differ- ences that are present for peripheral visual function, especially at low luminances, it would be valuable to determine the relationship between peripheral visual function and task performance for the normal population.

270 There are many investigations of peripheral visual function that could be performed by a night vision laboratory. The simplest approach might include the measurement of visual sensitivity to light throughout the visual field (increment or detection thresholds) at low photopic and mesopic luminance levels. Scotopic visual field sensitivity could also be measured, but this would require a much longer preadaptation time. These visual field sensitivity measures could then be correlated with skills displayed on job-related tasks for each individual. This approach would only require an automated perimeter capable of per- forming quantitative visual field sensitivity measurements, a method of adjusting the background adaptation luminance of the device, and a method of storing results to be able to follow participants over an extended period of time. A more elaborate approach might consist of the measurement of visual sensitivity, visual resolution, temporal contrast sensitivity and spatial contrast sensitivity at various locations throughout the visual field at photopic, mesopic, and scotopic adaptation levels. A subset of representative job-related skills could be identified and implemented in a field study environment in which quantitative measures of performance (reaction time, errors, etc.) could be determined for various luminance levels. Alternatively, a flight simulator might be used to assess performance. Psychophysical measurement in the peri- phery could then be correlated with performance measures to determine their relationships for various luminance levels. A third area of research might include the study of strange per- ceptual phenomena that occur in the periphery, such as the disappear- ance of slowly moving objects and the apparent brightness, size, and distance of peripheral targets. At the present time, these perceptual effects are not well understood. It is very likely, however, that these effects play an important role in tasks that are dependent on peripheral visual function. The visual environment outside of the cockpit during flight mainly consists of slowly moving stimuli. It would therefore be worthwhile to determine the conditions under which visual sensitivity to such targets is reduced and to define methods to minimize or eliminate this loss of sensitivity. RECOMMENDED INSTRUMENTAT I ON One desirable clinical instrument for a night vision laboratory is an automated perimeter. For screening of peripheral vision to detect ocular or necrologic disorders, an automated suprathreshold static peri- meter would be sufficient. These devices permit rapid screening of the visual field (2-5 min/eye under standardized conditions). The Field- master 101-PR (Bausch and Lomb/Synemed Inc.) has had the most extensive clinical performance trials to date, although the Dicon 2000 (Cooper Vision), Digilab 750 (Bio-Rad), and several other devices have undergone clinical trials that have documented their clinical efficacy. Keltner and Johnson (1985) have reviewed the various features and clinical eval- uation studies that are associated with existing automated perimeters. The cost of automated suprathreshold static perimeters is between $5,000 and S8, 000.

271 Quantitative measurements of increment (detection) thresholds require the use of an automated threshold static perimeter. There are several commercially available devices that can perform such measures: the Octopus 500 (Cilco, Inc.), the Humphrey Field Analyzer "Humphrey Instruments), the Fieldmaster 275 (Bausch and Lomb/Synemed Inc.), and the Digilab 750 (Bio-Rad). The Octopus 500 is probably not an appro- priate choice for a night vision laboratory because of its lack of flexibility and difficulties related to maintenance and hardware and software support. Both the Humphrey Field Analyzer and the Fieldmaster 275 would be good choices because of their flexibility and the willing- ness of the manufacturers to accommodate specific needs of individual customers (e.g., low background luminances). The cost of these devices is between $10,000 and S25,000. For a night vision laboratory, it would be desirable to have the capability of evaluating a variety of visual functions throughout the visual field at many background luminances. To measure visual func- tions other than sensitivity to light, a versatile perimetry system is required. The Tubinger perimeter (Oculus, Inc., Tubingen, Federal Republic of Germany) is the only commercial device that is able to measure a number of visual functions throughout the visual field. Detection sensitivity, resolution sensitivity, flicker sensitivity, spatial summation, temporal summation, dark adaptation, and glare sensitivity can all be evaluated with the TObinger perimeter at any location in the visual field. Background luminances f rom low-photopic to scotopic (a 6-log-unit range) can be established for testing . I t is uncertain as to whether the Tubinger perimeter is still availab~ e from the manufacturer. However, it is likely that a good, used Tubinger perimeter could be obtained (the advent of automated perimeters has drastically reduced the popularity of the T6binger perimeter for clini- cal ophthalmic use) or that a similar device could be fabricated. It would also be very useful to modify the T6binger perimeter so that it could be interfaced to a microcomputer system to automatically control the testing procedures and acquire data. REFERENCES Aulhorn, E., and H. Harms 1972 Visual perimetry. In D. Jameson and L. Hurvich, eds., Handbook of Sensory Physiology, Vol. VII/4 (Visual Psychophysics). Berlin: Springer-Verlag. Bedell, H.E., and C.A. Johnson 1984 The perceived size of targets in the peripheral and central visual fields. Ophthalmic and Physiological Optics 4 :123-131. Carrpbell, F.W., and L. Maffei 1979 Stopped visual motion. Nature 278:192 . 1981 The inf luence of spatial f requency and contrast on the perce~ tion of moving patterns. Vision Research 21: 713-721. Cohen, A. 1975 The r~tina and optic nerve. In R. Moses, ea., Adler's Phys iology of the Eye . S t . Lou i s: Mosby .

272 Cohen, R.L. 1985 Adaptation effects and aftereffects of moving patterns viewed in the periphery of the visual field. Scandinavian Journal of Psychology 6:257-264. Day, R.H. 1973 Apparent contraction and disappearance of moving objects in the peripheral visual field. Vision Research 13:959-975. Dunn, P.M., and R.W. Massof 1983 Temporal resolution in the peripheral visual field. Doc. Ophthalmology Proceedings Series 35:433-438. Enoch, J.M., J. Lazarus, and C.A. Johnson 1976 Human psychophysical analysis of receptive field-like proper- ties. 1. A new transient-like visual response using a moving windmill (Werblin-type) target. Sensory Processes 1:14-32. Ferree, C.E., G. Rand, and C. Hardy 1931 Refraction of the peripheral field of vision. Archives of Ophthalmology 5:717-731. Frome, F.S., D.I.A. MacLeod, S.L. Buck, and D.R. Williams 1981 Large loss of visual sensitivity to flashed peripheral targets. Vision Research 21:1323-1328. Fukoda, Y., and J. Stone 1974 Retinal distribution and central projections of Y-, X- and W-cells of the cat's retina. Journal of Neurophysiology 37:749-772. Gordon, D.A. 1947 The relation between the thresholds of form, motion and dis- placement in parafoveal and peripheral vision at a scotopic level of illumination. American Journal of Psychology 60:202-225. Harvey, L.O., and E. Poppel 1972 Contrast sensitivity of the human retina. American Journal of Optometry 49:748-753. Hunzelmann, N., and L. Spillman 1984 Movement adaptation in the per ipheral retina. Vision Research 24:1785-1788. Jennings, J.A.M., and W.N. Charman 1978 Optical image quality in the peripheral retina. American Journal of Optometry and Physiological Optics 55:582-590. 1981 Off-axis image quality in the human eye. Vision Research 21:445-455. Johnson, C.A., and J.L. Keltner 1983 Incidence of visual field loss in 20,000 eyes and its rela- tionship to driving performance. Archives of Ophthalmology 101:371-375. Johnson, C.A., J.L. Keltner, and F.G. Balestrery 1978 Effects of target size and eccentricity on visual detection and resolution. Vision Research 18:1217-1222. 1981 Static and acuity profile perimetry at various adaptation levels. Doc. Ophthalmology 50:371-388.

273 Johnson, C.A., and H.W. Leibowitz 1974 Practice, refractive error and feedback as factors influencing peripheral motion thresholds. Perception and Psychopysics 15:278-280. Johnson, C.A., and R.F. Scobey 1980 Foveal and peripheral displacement thresholds as a function of stimulus luminance, line length and duration of movement. Vision Research 20:709-716. 1982 Effects of reference lines on displacement thresholds at various durations of movement. Vision Research 22:819-821 Keltner, J.L., and C.A. Johnson 1985 Comparative material on automated and semi-automated peri- meters--1985. Ophthalmology (Instrument and Book Supplement) 92:34-57. Kerr, J.L. 1971 Visual resolution in the periphery. Perception end Psycho- phys~cs 9:375-378. Xoenderink, J.J., M.A. Bouman, A.E. Bueno de Mesquita, and S. Slappendel 1978a Perimetry of contrast detection thresholds of moving spatial sine wave patterns. I. The near peripheral visual field. Journal of the Optical Society of America 68:845-849. 1978b Perimetry of contrast detection thresholds of moving spatial sine wave patterns. II. The far peripheral visual field. Journal of the Optical Society of America 68:850-854. - 1978c Perimetry of contrast detection thresholds of moving spatial sine wave patterns. III. The target extent as a sensitivity controlling parameter. Journal of the Optical Society of America 68:8S5-860. 1978d Perimetry of contrast detection thresholds of moving spatial sine wave patterns. IV. The influence of mean retinal illuminance. Journal of the Optical Society of America 68:861-865. MacKay, D.M. 1982 Anomalous perception of extrafoveal motion. Perception 11:359-380. Mandelbaum, J., and L.L. Sloan 1947 Peripheral visual acuity. American Journal of Ophthalmology 30:581-588. Marron, J.A., and I.L. Bailey 1982 Visual factors and orientation and mobility performance. American Journal of Optometry and Physiological Optics 59:413, 426. McColgin, F.H. 1960 Movement thresholds in peripheral vision. Journal of the Optical Society of America 50:774-779. Newsome, L.R. 1972 Visual angle and apparent size of objects in peripheral vision. Perception and Psychophy-s-ics 12:300-304. Poppel, E., and L.O. Harvey 1973 Light-difference threshold and subjective brightness in the periphery of the visual field. Psychologie Forschung 36:145-181.

274 Post, R.B., R.P. Scobey, and C.A. Johnson 1984 Effects of retinal eccentricity on displacement thresholds for unidirectional and Oscillatory stimuli. Vision Research 24:835-838. Ronchi, L., and G. Molesini 1974 Tome resolution at extremely low scotopic luminance. Journal of the Optical Society of America 84:887-88y. Scobey, R.F., and C.A. Johnson 1981a Psychophysical properties of displacement thresholds for moving targets. Acta Psychologica 48:49-55. 1981b Displacement thresholds for unidirectional and oscillatory movement. Vision Research 21:1297-1302. Tynan, P.D., and R. Sekuler 1982 Motion processing in peripheral vision: reaction time and perceived velocity. Vision Research 22:61-88. Verriest, G., L. Barca, A. Dubois-Foulsen, M.J.M. Houtmans, B. Inditsky, C.A. Johnson, I. Overington, L. Ronchi, and S. Villani 1983 The occupational visual field. I. Theoretical aspects, the normal functional visual field. Proceedings Series 35:165-185. Doc. Ophthalmology Verriest, G., I.L. Bailey, G. Calabria, E. Campos, R.P. Crick, J.M. Enoch, B. Esterman, A.C. Friedmann, M. Ikeda, C.A. Johnson, I. Overington, L. Ronchi, S. Saida, A. Serra, S. Villani, R.A. Weale, M.L. Wolbarsht, and M. Zingirian 1985 The occupational visual field. II. Practical aspects: The functional visual field in abnormal conditions and its relationship to visual ergonomics, visual impairment and job fitness. Doc. Ophthalmology Proceedings Series 42:281-326. Wilson, M.E. 1970 Invariant features of spatial summation with changing locus in the visual field. Journal of Physiology 207: 611-822.

AGING AND NIGHT VISICN Cynthia Owsley The effect of the aging process on human visual function has been studied sporadically throughout the twentieth century, but it has only been in the past few years that there has been a concentrated effort to understand visual function in older adults. Most of this recent work has been devoted to older adults' visual capacities under photopic luminance conditions (see Sekuler et al., 1982; Peale, 1982a; Kline and Schieber, 1985, for a review of this literature). In contrast, relatively little is known about the visual performance capabilities of older adults at night. What follows is a review of the existing knowledge in this field, with a subsequent discussion of issues which demand our further attention. AGING RELATED CHANGES Senile Miosis A well-documented accompaniment of the aging process is senile mio- sis, which refers to a decrease in the pupil diameter with increasing age during adulthood. Figure 1 illustrates this life span phenomenon, showing that for both light- and dark-adapted eyes, the pupil decreases in diameter throughout adulthood (Kornzweig, 1954~. As can be noted, by age 80 the pupil has almost an identical size under radically differ- ent luminance conditions. Although there is a significant age-related decline in pupil size, there is a great deal of individual variability and overlap between individuals in different decades of life. This wide variability is illustrated in Figure 2 from Loewenfeld (1979~. Several different explanations have been advanced to account for senile miosis, such as damage to the iris, deficits in the pupil's sympathetic innervation, and defective central inhibition of the papillary sphinc- tor. The functional implication is that as a result of a smaller pupil, less light reaches the older adult's retina than that of the younger adult. Weale (1963, p. 168-170) has estimated that the 60-year-old retina receives approximately one-third the amount of light as the 20- year-old retina, regardless of the level of adaptation. This estimate also takes into account the increased absorption of the aged crystalline lens (to be discussed below). 275

s FIGURE 1 Pupil diameter in millimeters (ordinate) as a function of age. Top function is for the dark-adapted eye; bottom functin is for the light-adapted eye. Source: Kornzweig (1954~. Some data from Woodhouse (1975) (Figure 3) demonstrate how pupil size affects an observer's spatial resolution (see also Woodhouse and Campbell, 1975; Campbell and Gregory, 1960~. These data are from a young adult, but they will serve to illustrate an important point. At the highest luminance tested (40 ft.-Lamberts) in the Woodhouse (1975) experiment, adults in their 60s typically have about a 3-mm-diameter pupil, and adults in their 20s typically have about a 5-mm~aiameter pupil. As the top function in Figure 3 shows, both of these pupil sizes would yield about the same resolution, suggesting that the older adult's small pupil does not actually put them at a disadvantage in resolving detail at high luminances. This is because the optimum pupil diameter for resolution is a compromise between the retinal illumina- tion requirements and optical aberration. But the situation is quite different at lower luminances. As lumi- nance drops, the younger adult's pupil dilates and optimizes resolution. As Figure 3 also indicates, however, the older adult's pupil, which is small and relatively fixed in size, hampers resolution, keeping acuity at a rather low level compared with the acuity of younger adults under the same luminance conditions. Thus, although senile miosis is unlikely to pose a serious threat to resolution at higher light levels, it can produce a significant acuity loss in older adults at lower luminances. Increased Lenticular Density Another change in the older eye that contributes to reducing the light level reaching the retina is the increased density of the crys- talline lens during later adulthood. Said and Peale (1959) have made measurements on the optical density of the human lens as a function

8 7 6 s 4 3 hi, ~0 O ~IO 15 20 25 30 35 90 95 50 S5 60 t5 70 75 tO 85 tO FIGURE 2 Pupil diameter in darkness as a function of age for 1,263 sub jects. Note the wide individual variability. Source: Lowenfeld (1979) . 36 28 26 ce 24 22 1B s 14 ~2 lo ; 8 Z , C i : . . . . . . . C=1t~QS. 097 Sat ~ ,~m ~ · . ,Y,-~ ·~-~4O ~2 1{ ·26 . 1/ _-001245 ~_0~4 _ --00004 ~a=2q . . O 12 3 4 5 6 ? e 9 lO pupil deom~er non FIGURE 3 Maximum spatial f requency resolved as a function of pupil diameter. Each function represents a different luminance level ~ ft.-Lamberts) . Source: Woodhouse ( 1975) .

IF 05t c - .Y At, Cal in, ~ 1 W., o 1 . 1 . I . 500 coo X)O Weecle~th In - e FIGURE 4 Optical density of human crystalline lenses as a function of wavelength. Each curve represents a different age (as indicated). Source: Said and Weale (1959~. Of wavelength for adults ranging in age from 21 to 63 years; these data are depicted in Figure 4. Each curve represents a subject of a differ- ent age. It can be seen that density increases with increasing age, but also notable is that this density increase is greater at shorter wavelengths. This density-by-wavelength interaction is more apparent in Figure 5, where each wavelength is plotted separately. The increase in density with increasing age is quite slight at 680 nm, while it is much more dramatic at the shorter wavelengths. The rate of these changes seems to be quite negligible or minimal in childhood and early adulthood, but it then accelerates at about 20 to 30 years of age. Thus, it can be seen that in addition to the pupil, the crystalline lens attenuates the amount of light reaching the older retina, as compared with the younger retina. The amount of this attenuation is wavelength specific, thereby affecting color perception and spectral sensitivity. Dark Adaptation Dark adaptation has historically been one of the most popular topics of interest to researchers of aging and vision. Most of the studies presented in the literature are rather old, but they are quite numerous and for the most part well executed (e.g., Robertson and Yudkin, 1944; Steven, 1946; Birren et al., 1948; Birren and Shock,

279 °F o ~ - o. - . C ~ C'S ~ - o c . `-396~. I' . ~ "- We . ~ / I. I . 1- 500 I , ~, ~ , I . ~. I . ~ 0 10 20 30 ·0 SO ~·0 Atc In rcore SO .0 FIGURE 5 Optical density of human crystalline lenses as a function of age. Each function represents a different wavelength (as indicated). Source: Said and Weale (1959~. 1950; McFarland and Fisher, 1955; McFarland and Domey, 1958; McFarland et al., 1958, 1960; Luria, 1960; Domey and McFarland, 1960, 1961; Domey, 1964~. There have been two recent, comprehensive reviews of this liter- ature by Pitts ( 1982 ~ wh ich can aid the interested reader in sorting through this rather large body of work. A study by }McFarland et al. (1960) can be used to summarize these studies; the results are illustrated in F igure 6. They tested 240 sub- jects ranging in age from the teens to the 80s using a liecht-Schlaer Adaptometer . The test 1 ig ht was 1 deg ree and was v iolet ~ 4 0 5 nm) . One of the most obvious points to note from Figure 6 is that the dark adap- tation curves are elevated with increasing age. The final threshold for the 80 year olds is about 2 .2 log units higher than that for the 20 year olds. For each age group the cone-rod transition occurs between the fifth and sixth minutes. There is also a highly signif icant correl- ation between age and threshold at each point dur ing the dark adaptation process, i .e., older adults tend to have higher thresholds at each time interval tested . These curves ind icate that target luminance must be doubled every 13 years to be seen by the dark-adapted eye throughout life (Pitts, 1982). I t is important to point out that these data have not taken into consideration the two signif icant ag ing changes in the eye discussed earlier, namely, senile miosis and increased lenticular density. with

z 6 me o o on o o 2 280 - S ~ \\ ~ ~80-89 3 Am_ ~~~-- ~40-49 __=_____ 30-39 ~--____ ~20-29 16-19 1 ~ ~ 0 10 20 30 40 SO 60 TIMES, MINUTES FIGURE 6 Dark adaptation as a function of age. Source: McFarland et al. (1960). regard to senile changes in pupil size, the young adult's pupil normally dilates during the dark adaptation process, but for the older adult the pupil remains at a rather small, relatively fixed size. Pitts (1982) has calculated that senile miosis for people in their 70s accounts for about 0.6 log units of older adults' threshold elevation. The differ- ence between the young and old adultst threshold level is further mini- mized when increased lenticular density is taken into account. Pitts goes on to point out that although most of older adults' threshold ele- vation is accounted for by these preretinal factors, there is still about a 0.5-log-unit elevation in older adults' thresholds. At this point it is uncertain as to what is precisely responsible for this threshold elevation in older adults, but mechanisms that have been suggested are metabolic problems in the aged retina (McFarland and Fisher, 1955) and neural deterioration in the visual pathways (Peale, 1982b). Acuity One of the most common clinical measures of visual function is acu- ity, the smallest visual detail that an observer can resolve. There have been many studies on how acuity changes during adulthood, and in general, it has been found that acuity tends to decline after middle adulthood (see summary by Pitts, 1982~. One problem encountered in comparing these studies is that the studies vary quite widely in their

281 use of important methodological controls. For example, not all studies refracted subjects for the test distance, which is important in avoid- ing the confounding effects of blur; subjects with significant ocular disease were not necessarily screened out of the test sample; and the method of measuring acuity was not always precisely specified. How- ever, a few recent studies (Frisen and Prisen, 1981; Owsley et al., 1983) have instituted these methodological safeguards and have found that even under optimal conditions where subjects are refracted for the test distance and are in good ocular health, letter acuity does tend to decline after middle adulthood. The studies just described assessed acuity under photopic viewing conditions. The relevant question for the present discussion is how does aging affect acuity in a lower luminance environment? It can be expected on the basis of senile miosis that older adults' acuity is selectively impaired at lower luminances relative to that of younger adults. Unfortunately, there have only been a few studies that have specifically examined this issue. Richards (1977) measured letter acuity in a large sample of adults ranging in age from 16 to 90 years. Acuity was measured at several chart luminances, from 10 to 0.01 ft.-Lamberts, and at several different letter contrast levels. The data for 10 and 0.01 ft.-Lamberts are displayed in Figure 7. All age groups had reduced acuity at the lower luminance level, but older adults, particularly those in their 70s and Bus, seemed to have greater acuity reductions relative to those of young adults at the lower lumi- nance. In fact, their acuity was so poor that it was worse than that at the largest target size presented in the study. Thus, these data seem to suggest that at reduced light levels, older adults undergo more significant acuity reductions than do younger adults. One problem in interpreting the results of this study is that Richards did not evalu- ate the subjects' eyes for ocular media opacities; therefore, it is difficult to know whether the age-related acuity reduction at low lumi- nance is due to a few subjects with clinically significant cataracts, or whether the acuity reduction is a representative problem for most elderly individuals. In a related study, Sivak et al. (1981) conducted a field study to investigate nighttime legibility of highway signs for young (under 25) and older (over 61) adults. They found that the legibility distances for the older adults were 65 to 77 percent of those for the younger adults, implying that older adults required larger visual angles to dis- cern the signs. They further showed that the age-associated legibility difference, while unrelated to high-luminance acuity, disappeared when young and old subjects were equated on low-luminance acuity (Sivak and Olson, 1982~. This study not only underscores the acuity problem that older adults have at night but also questions the relevance of using high-luminance "cuity tests to predict nighttime visual performance. A study by Bentivegna et al. (1981) examined the accuracy of accord modation in darkness for adults of various ages. Previous research had indicated that when visual stimulation is degraded, the amplitude of accommodation is reduced as accommodation is biased toward the person's dark focus, a condition often referred to as night myopia (Leibowitz

282 1~= o 20 Ho 60 80 loo TEST LETTER CONTRAST (%) 20 255 en 2 20 ~ r r rim z so to Z lo - 20 o Hi 7 Ql[L 1\\ \ Ct 20 100 . 1 1 1 . ~ 1 ~ 1 ~ 1 1 1 20 o20 co 60 so loo20 TEST LETTER CONTRAST (%) FIGURE 7 Left panel: Letter acuity as a function of letter contrast. Each function represents a different age group (as indicated). Chart luminance was 10 ft.-Lamberts. Right panel: Same as for the left panel, except chart luminance was set at 0.1 ft.-Lamberts. Source: Richards (19777. a r 20 r to Z. and Owens, 1978; see also the paper by Owens in this volume). Bentivegna et al. (19 81) found that the dark focus was between the near and far points for all age groups, indicating that an intermediate dark focus is characteristic of accommodation regardless of the observer's age during adulthood. Glare Because intraocular light scatter is typically increased in the aged eye, it might be expected that glare would pose a more serious visual problem for older adults (see also the chapter by Blackwell and Blackwell in this volume). One of the classic studies demonstrating

I ! V O On _ ~ l Cal . ~ - Q. D o . _ = . _ t _ m 2 cr' J ~ . . 1 . L: ~ A. Act, ;~- , , ~ At/: 1 3 _ _l- LIZ 1.97 108 1.91 L~ l J l It 10 20 30 40 50 60 70 80 90 age FIGURE 8 Long threshold luminance for target recognition in relation to log glare luminance, as a function of age. Each function represents a different glare level. Source: Wolf (1960~. this aging-related problem is by Wolf (1960), who studied glare sensi- tivity in a large sample of people ranging in age from 5 to 85 years. Subjects were asked to identify the orientations of Landolt ring tar- gets, which were positioned at various distances from a glare source. Screen luminance was varied until the subject could make the determin- ations. Figure 8 illustrates how target screen luminance varied as a function of age; each function represents a different glare level. It is obvious that screen luminance had to be increased as the observer's age increased. Thus it appears that glare hampers target sensitivity more so for older than for younger adults. Wolf and Gardner (1965)  further note in a related report that the increase in the slopes of these functions at age 40 corresponds to an increase in intraocular light scatter which occurs at about the same age, suggesting that glare sensitivity is systematically related to media changes in the eye (see also Reading, 1968~. It would be interesting, however, to examine whether this relationship between glare sensitivity and ocular media changes is observed when both the threshold measurements and the intraocular scatter measurements are done on the same individuals. A situation in which glare can be particularly disabling is during night driving when the headlights of oncoming cars appear in the field

284 92.5 o en 2.0 w I.S 0 - ~· 0 20 · . . · e e e e · ·te at_ e ~a' ~e e ~e I- e e · e e e e ~ e e e ·N e S e:\ - . \ · ·\ . ·\ - I ~· t 40 60 80 AGE FIGURE 9 Physiological glare threshold ~ see text) as a function of age. Source: Pulling et al. ( 1980~ . Of view. Headlight glare resistance was studied as a function of age by Pulling et al. (1980) . They used Wolf~s technique (1960), described earlier, to measure glare thresholds in a large sample of subjects ranging in age f rom 5 to 91 years. They obtained what they refer to as a physiological glare threshold, wh ich was def ined as the logar ithm of the ratio, at the threshold for target recognition, between the illumi- nance of the glare source and the illuminance of the background screen; thus, higher thresholds correspond to greater glare resistance. Figure 9 displays how this physiological glare threshold changes as a function of age. Glare thresholds do not signif icantly change dur ing early adulthood, but do drop off quite rapidly beginning at about age 40, which is also the age when <glare thresholds began to change in Wolf' s work (1960) .  DI RECTI ONS FOR FETUS RESEARCH I t should be fairly obvious from this review that there is a clear need for more psychophysical research on aging and night vision. Although preretinal factors in the aged eye, such as senile miosis and increased lenticular density, are fairly well understood, knowledge is qu ite sparse concerning how visual function in older adults is at f ected by a low-luminance environment. I t is interesting, for example, that despite the fact that there have been several studies on ag ing and spa- tial contrast sensitivity (Derefeldt and McFarland, 1979; Owsley et al., 1983 ; Higgens et al., 1983), none of these experiments has addressed

285 how older adults' contrast sensitivity loss may be exacerbated by lower luminance conditions. With the possible exception of dark adaptation, most visual functions (e.g., contrast sensitivity, flicker, acuity, peripheral vision) still have not been systematically examined with respect to older adults' visual capacities at night. Throughout all stages of adulthood there is individual variability in visual capacities and performance, but this variability tends to increase during later adulthood. Therefore, it is very important that studies on aging and vision incorporate large enough sample sizes, so that results more accurately reflect the breadth of performance vari- ation found in older people. Many studies comparing psychophysical performance in young versus old adults have found that many older adults perform well within the range of the younger group, despite the fact that statistically significant age effects exist in the data. Finally, it is important to point out that the study of aging is not simply a matter of comparing very young adults with very old adults. Aging is a gradual process, and thus researchers must routinely look at the transitional phases of development by studying middle-aged adults as well as adults at the extreme ages. This type of life span approach may prove the most fruitful in uncovering the mechanisms underlying the visual problems faced by older adults and flay ultimately lead to their solution. REFERENCES Bentivegna, J., D.A. Owens, and K. Messner 1981 Aging, cyclopedia, and accommodation. Investigative Ophthal- mology and Visual Science 20tSuppl.~:21. - Birren, J.E ., M.W. Bick, and C. Fox 1948 Age changes in rate and level of the dark adapted eye. Journal of Gerontology 3:267-271. Birren, J.E., and N.W. Shock 1950 Age changes in rate and level of dark adaptation. Journal of Applied Physiology 2:407-411. Campbell, F.W., and A.H. Gregory 1960 Effect of size of pupil on visual acuity. Nature (London) 229:1121-1123. Derefeldt, G., and R.A. McFarland 1979 Age variations in normal human contrast sensitivity. Acta Ophthalmolog ice 57: 679-69 0 . Domey, R .G . 1964 Statistical properties of foveal CFF as a function of age, light/dark ratio, and surroundings. Journal of the Optical Society of America 54: 394-398. Domey, R .G . , and ~ .A . McEa r land 1960 Threshold and rate of dark adaptation as functions of age and time. Human Factors 2 :109-119. 1961 Dark adaptation as a function of age : Individual prediction. American Journal of Ophthalmology 51:1262-1268.

286 Fr isen, L., and M. Fr isen 1981 How good is normal visual acuity? Klin Ophthalmolog ie 215: 149-15 7 . Higgens, K.E., M.J. Jaffe, R.C. Caruso, F. deMonasterio, and C. Simon 1983 Normal aging and spatial contrast sensitivity. Ophthalmology Supplement :109. Kline, D.W., and F . Schieber 1985 Vision and aging. Pp. 296-331 in J.E. Birren and K.W. Schaie, eds., Handbook of the Psychology of Aging. New York: Van Nostrand Reinhold. Kor nzwe ig, A .L . 1954 Physiological effects on age on the visual process. S. ight Saving Review 24 :130-138. Leibowitz, H.W., and D.A. Owens 1978 New evidence for the intermediate position of relaxed accommo- dation. Documenta Ophthalmolog ice 46 :133-14 7. Loewenfeld, I .E. 1979 Pupillary changes related to age. Pp. 124-150 in G.S. Thompson, ea., Topics in Neuro-ophthalmology. Baltimore: Williams and Wilkins. Luria, S.M. 1960 Absolute visual threshold and age. Journal of the Optical Society of Amer ice 50: 86-8 7. McFarland, R.A., and R.G. Domey 1958 Exper imental studies of night vision as a function of age and changes in illumination. Highway Research Board Bulletin 191 :17-32. McFarland, R.A., R.C. Domey, A.B. Warren, and D.C. Ward 1960 Dark adaptation as a function of age. I. A statistical analysis. Journal of Gerontology 15 :149-154 . McFarland, R.A., and M.B. Fisher 1955 Alternation in dark adaptation as a function of age. Journal of Gerontology 10: 424-428. McFarland, R.A., A.B. Warren, and C. Karis 1958 Alternations in critical flicker frequency as a function of age and light: Dark ratio. Journal of Experimental Psychology 56 :529-538. Owsley, C., R. Sekuler, and D. Siemsen 1983 Contrast sensitivity throughout adulthood. Vision Research 23: 689-699 Pitts, D .G . 1982 The effects of aging on selected visual functions: Dark aaa~ tation, visual acuity, stereopsis, and brightness contrast. - Pp. 131-159 in R. Sekuler, D. Kline, and K. Dismokes, eds., Aging and Human Visual Function. New York: Alan R. Liss. Pulling, N.H., E. Wolf, S.P. Sturgis, D.R. Vaillancourt, and J .J . Doll iver 1980 Headlight glare resistance and driver age. Human Factors 22 :103-112. Albrecht von Craetes Archiv

287 Reading, V. 1968 Disability glare and age. Vision Research 8:207-214. Richards, O.W. 1977 Effects of luminance and contrast on visual acuity, ages 16 to 90 years. American Journal of Optometry and Physiological Optics 54:178-184 . Robertson, G.W., and J. Yudkin 1944 Effect of age upon dark adaptation. Journal of Physiology 103:1-8. Said, F.S., and R.A. Weale 1959 The variation with age of the spectral transmissivity of the living crystalline lens. Gerontologia 3:213-231. Sekuler, R., D. Kline, and K. Dismukes 1982 Aging and Human Visual Function. New York: Alan R. Liss. Sivak, M., and P.L. Olson 1982 Nighttime legibility of traffic signs: Conditions eliminating the effects of driver age and disability glare. Accident Analysis and Prevention 14:87-93. Sivak, M., P.L. Olson, and L.A. Pastalan 1981 Effect of driver's age on nighttime legibility of highway signs. Human Factors 23:59-64. Steven, D.M. 1946 Relation between dark adaptation and age. Nature (London) 157:376-377. Weale, R.A. 1963 The Aging Eye. London: H.K. Lewis. 1982a A Biography of the Eye. London: H.K. Lewis. 198~b Senile ocular changes, cell death, and vision. Pp. 161-172 in R. Sekuler, D. Kline, and K. Dismukes, eds., Aging and Human Visual Function. New York: Alan R. Liss. Wolf, E.W. 1960 Glare and age. Archives of Ophthalmology 64:502-514. Wolf, E., and J.S. Gardner 1965 Studies on the scatter of light in the dioptric media of the eye as a basis of visual glare. Archives of Ophthalmology 74:338-345. Woodhouse, J.M. 1975 The effect of pupil size on grating detection at various contrast levels e Vision Research 15:645-648 Woodhouse, J.M., and F.W. Campbell 1975 The role of the pupil light reflex in aiding adaptation to the dark. Vision Research 15:649-653.

THE ROLE OF VI SI ON MODELS IN HUMAN E ACTORS Andrew B. Watson Other authors of papers in this volume have described some of the facts of night vision and some of the outstanding questions in that area. I will discuss a methodological issue, namely, the role of models as an integral part of vision and human factors research. I will make some general remarks about this role, give some examples of models developed in our laboratory, and show and example of how they can be applied to important practical problems. Figure 1 illustrates the central role that models do play, or should play, in the application of scientific knowledge to applied problems. Take the case of the designer of a display in an aircraft cockpit. Empirical data provide the inspiration for and constraints on the creation of a model. The model then generates predictions of interest to the application, and these predictions guide the design of the display. The model then serves a second role as a means of evalu- ating the design. If I were the owner of an artificial intelligence company, I would argue that the whole process could be automated and that the model could directly generate the optimal design. Even though this prospect is immeasurably beyond present capabilities, it is worth noting as an ultimate goal. While this ideal process is rarely followed in the area of human factors, it should be noted that it is completely obvious and standard in more advanced areas of engineering. What I am advocating is a form of computer-aided design, in which the models are not of finite element analyses of load-bearing beams but of human sensitivity to contrast, color, and motion. The main point to be made here, however r is the central role that models play in this process. To do without them would be like trying to design a television set by trial and error, without the fundamental laws of electrical circuit theory. DI~KSI ONS OF P~DICTI ON Niels Bohr, whose birthday centennial was in 1985, was famous for his theory of complementary variables: that is, two quantities whose magnitudes vary inversely and which cannot therefore be simultaneously minimized. After one of his talks he was asked what variable was 288

289 data evaluaLion~ ~ ; . . ... , ... ~: Actions 1- ; r r _ models ~ _ ~ resign FIGURE 1 The central role of models in human factors design. 1 complementary to truth. His immediate reply was, "clarity." This rule no doubt applies to this talk (which I hope will be perfectly clear), but it certainly applies to models. In Figure 2, I have illustrated some of the decisions a modeler must make. Models vary in their depth, the sense of how many different levels of the visual system they encompass, their breadth, the sense of how many of the parallel processes at the same level are included, and of course, their accuracy. The complexity of the model is primarily determined by how much of this space it attempts to cover. My own modeling work lies toward the middle of each range. At the outset a working model of visual sensitivity has been provided. IMPORTANT ASPECTS OF VISUAL SENSITIVITY Before I describe specific models, the most important aspects of visual sensitivity are worth considering. A reasonable plan would be to list them in order of significance (measured, perhaps, by the amount of variance accounted for) and work down the list. Everyone probably has a somewhat different list, but I offer the following as an example:

290 Dimensions of Prediction actions Depth optics ~ accuracy ~ foci Breadth all receptors FIGURE 2 Dimensions of prediction for models of vision. Spatial contrast sensitivity* 2. Temporal contrast sensitivity* 3. Light adaptation 4. Motion sensitivity* 5. 6. 7. 8. 9. Spatial inhomogeneity* Color sensitivity Masking Decision mechanism* Spatial channels* An asterisk has been placed next to each topic that has been worked on in my laboratory to date, so the plan that I suggested has not been followed exactly. Although the topics listed are all n low level" and deal primarily with sensitivity, rather than coding or analyzing the visual input, there is no question that a model that captures the essence of all these properties of human vision would be an enormous

291 leap for human factors. Although this goal has not been reached, some progress has been made; some examples are given below. Temporal Sensitivity As with most models, temporal sensitivity is not really new. It is an amalgam of good ideas from various sources, notably from de Lange, Fourtes and Hodgkin, Don Kelly, and George Sperling "Watson, 1986b). It is an attempt to provide in a compact, usable form a model that is capable of predicting sensitivity to an arbitrary temporal fluctuation in image contrast. It consists of a linear temporal filter followed by a decision stage which incorporates probability summation. It is cur- rently implemented in digital form as a recursive finite impulse res- ponse (FIR) filter. Figure 3 illustrates the impulse response, amplitude response, and phase response of the model. Also plotted are some of Robson's data (1966) for sensitivity to a grating flickering at various rates. This model has been tested by comparing its predictions with data for a wide range of waveforms, including pulses, double pulses, sinusoids, and random noise, all with good results (Watson, 1986a; Watson and Miller, 1986~. While not perfect, it can now serve as a building block for more complex models of temporal and spatiotemporal sensitivity. Spatial Model The second model is one that has been under development since 1982 (Watson, 1983~. It describes the sensitivity of the human observer to arbitrary spatial patterns of contrast. The visual input is sampled by a large array of spatial sensors, each with a receptive field tuned to in no ·_I ~ _ O \ / C O o 0 40 80 120 160 Time (msec) ~ ~ ~AT au, < 1 us ~8 N O 1 om "C 1 Q . ~4 \ \ . . . ~ . _ . . . ~ 1 5 10 50 1 1 5 10 50 Frequency (Hz) Frequency (Hz) FIGURE 3 Model of human temporal sensitivity. The impulse response (A), amplitude response (B), and phase response (C) of a linear filter are shown. The amplitude response in panel B has been fit to sensitiv-  ities to temporal modulation of a 0.5-c/degree grating, as measured by Robson (19661.

292 a particular location, spatial frequency, orientation, and spatial phase. These samples are then examined by an ideal observer to deter- mine whether a stimulus was present, or which of several stimuli was present. The sensors incorporate three of the aspects of visual sensi- tivity noted above: spatial contrast sensitivity, spatial inhomogene- ity, and spatial channels. First, the channel aspect is implicit in the spatial tuning of each sensor, which responds to a one octave band of two-dimensional spatial frequency. Figure 4 shows at the top the receptive field of a sensor tuned to a particular spatial frequency and orientation; below this is shown its two-dimensional frequency spectrum. Second, the sensors scale in size with distance from the fovea, which gives rise to the proper variation in contrast sensitivity with eccentricity. Finally, the gain of each sensor is set by an overall contrast sensitivity function that is unique to each observer. With this simple structure it has been found that many of the outstanding features of spatial sensitivity and discrimination can be explained. There are also some cases where it fails abysmally, but these are of great value, because they can provide guidance toward new and better models. Generally, the failures are for fairly complex dis- criminations rather than for predictions of sensitivity (Nielsen et al., 1985~. Lately work has been done on making the model more general, com- pact, portable, and easy to use (Watson, 1985~. Motion Model Another prominent item on the list is motion. Motion sensitivity involves both spatial and temporal dimensions, hence the motion model used has borrowed heavily from the preceding models of temporal and spatial sensitivity. In fact, each of the individual motion sensors that make up the model is constructed from the building blocks provided by those models. The spatial tuning of each sensor is given by the spatial sensor, and the temporal tuning is provided by the linear fil- ter of the temporal model. A few components are added to endow the sensor with direction selectivity, and a second processing stage is introduced to compute actual image velocities from the sensor outputs. The result is a model that can both predict whether the observer will detect a moving target, and which way it appears to move (Watson and Ahumada, 19851. The model accepts any visual input that can be repre- sented as a sequence of digitized images. Thus one can present iden- tical stimuli to human and model observers. AN APPLICATION: SYMBOL DESIGE Although I have only briefly discussed these examples, my purpose is to convey the spirit rather than the details of these models. How- ever, I will present here at least one example of how such models might be applied. Andrew Fitzhugh and I are now engaged in one project, which we call SYMBOL, that is an attempt to create a system for automatic

FIGURE 4 Receptive f ield weighting function of a spatial sensor and its f requency spectrum. evaluation of the legibility of alphabetic fonts, or~ more generally, the discriminability of arbitrary sets of visual symbols. The basis of the system consists of a simplif fed version of the spatial model. The out- put can be either a prediction for the target application, for exan~ple, determination of the probabil ity that these two symbols will be confused when presented at this viewing distance, or a simpler distance measure, which relates to the perceptual distance between any pair of symbols. The project has only just begun, so I cannot tell you whether it will succeed, but the type of ca1 culations that are performed can be des- cr ibed .

294 At the top of Figure 5 are shown three characters. The next line shows the characters after they have been passed through a spatial fil- ter that mimics human contrast sensitivity. The third line shows the autocorrelations, and the last line shows the cross-correlations between each pair. These are used in the computation of a perceptual distance between any two characters. Figure 6 shows a distance matrix for an entire font of 26 uppercase letters. Each cell depicts the distance measure between the two letters indicated by row and column. The key runs from zero or very small distances, such as between a letter and itself (along the diagonal), to very large distances. Figure 6 shows a very small distance, or highly confusable pair, which is in fact the I-T shown in Figure 5. Finally, the histogram of interpair distance can be compared for complete fonts. Figure 7 shows examples for three fonts, and it is clear that one font generates generally larger perceptual distances, and hence higher legibility. This illustrates one example of how it is hoped that models of human visual sensitivity will be used to optimize the design of visual displays. A NOTE ON TOOLS One of the purposes of the papers presented in this volume is to give suggestions for the design of a night vision laboratory. Since I am promoting the notion of model and theory as an integral part of such a laboratory, the question arises as to what tools will best serve the vision theorist. First, since so much of visual theory can and should be cast in the language of digital image processing, the scientist should be provided with a personal workstation capable of processing and displaying images in color at high resolution. The workstation (perhaps it should be called a theory station) should be served by massive amounts of f ile space (on the order of 0.1-1 gigabyte/user). The workstation should be capable of very fast floating point operations and should, if possible, be equipped with a fast (15 millions of floating point operations per second) array processor. It would be helpful to have a data link to a supercomputer, such as a GRAY, for models that are beyond the computa- tional capacity of the local workstation. Also useful would be a video camera and framegrabber for digitizing images to serve as model input. An ideal would be a workstation that is also capable of conducting psychophysical experiments, that is, of generating displays and collecting responses. As important as the hardware, however, is the need for appropriate software. This should include extensive libraries of mathematical sub- routines, image-processing routines, and statistical procedures. Also essential are graphics routines for the interactive study of complex data structures. As is well known, all of this is hard to find in a single package.

295 s U2 s I: U2 ~ o 3 ~ · - O : S O eQ ~ ~ a) 3 G. O S al O o S ED X Z .,, In S X ~ O L. · - S U] 3 O ~ S O In o 3 O :D O S ED ~ - U] H 3 _ o S A) U] 3 O ~ O - o · - ~ · - U] S · - ED no, so . I: · - : ~ O · -  U] · - U) ~ >~ ·-1 AS U] ~ U] 0 3 o S U] 3 3 C: U] H Jo U] A' 3 a) Q - ~ O S · - ~ - In ·rl _ C~ O _ o :^ · - · - · - U] o o . - Q~ o O · - O · - U] o 1 ~n U] o S~ U) o ·_1 S" o 1 U] U] o 3 O

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297 . no_. - . ~ . . ~ :{ .~. ..... . FIGURE 7 Histograms of letter pair distances for the three different fonts illustrated in enlarged form. The rightmost histogram should correspond to the most legible font. It is also hoped that vision models will be developed that adhere to certain standards that enhance portability and ease of use. This will promote the sharing of models among scientists, which will greatly increase the productivity, as well as the reliability, of individual models. Perhaps most critical is the need for someone, other than the sci- entist, to purchase, integrate, and perhaps program the theory station. Scientists are curious by nature, and there are few things more arous- ing of curiosity than a fancy computer, and just as curiosity killed the cat, so may the challenge of building the theory station consume the energy and time of the vision scientist. REFERENCES Nielsen, K.R.K., A.B. Watson, and A.J. Ahumada, Jr. 1985 Application of a computable model of human spatial vision to phase discrimination. Journal of the Optical Society of America A 2:1600-1606. Robson, J. 1966 Spatial and temporal contrast sensitivity functions of the visual system. Journal of the Optical Society of America 56:1141-1142. Watson, AeBe 1983 Detection and recognition of simple spatial fortes. In O.J. Braddick and A.C. Sleigh, eds., Physical and Biolog ical Processing of Images. New York: Springer-Verlag.

298 1985 Image transforms for visual modeling. Investigative Ophthal malogy and Visual Science 26~3) (Suppl.) :83. 1986a Window of visibility: Psychophysical theory of fidelity in Journal of the Opt ical - time-sampled visual motion displays. Journal of the Optical Society of America A 3 (3) :300-307. 1986b Temporal sensitivity. In R. Boff, L. Kaufman, and J. myomas, eds., Handbook of Perception and Human Performance. New York: John Wiley & Sons. Watson, A. B., and A .J. Ahumada, Jr. 1985 Model of human visual-motion sensing. Journal of Optical Society of America A 2: 322-342. Watson, A.B., and L. Miller 1986 Tests of a working model of temporal sensitivity. Unpublished pape r .

GENERAL D I SCUSSI ON KINNEY: I'm going to take the chairman's prerogative and ask the first question. Before I do that, I want to give you a little back- ground for my question. Some of you may not be aware that there were dozens of tests of night vision developed during World War II. Refer- ring back to my introductory remarks concerning my reviews of the early literature on night vision testing, two points stand out in my mind. For my first review, there was a wealth of material to evaluate from the wartime studies; however, the tests turned out to be not very reli- able, the validity scores were poor, and the many tests did not even correlate with one another. The second strong impression is of the lack of new data that I found to review a few years later. This epitomizes what has been going on in night vision testing ever since: a flurry of interest followed by a period of complete inactivity. The result is that, while there has been a 9 reat deal of basic research on night vision, there has been very little new in the applied aspects of testing. So my question, f inally, to the panelists is this: What factors f rom the basic work would you now include in a test of night vision--factors that you believe would improve on our past performance in the testing of night vision? SANDERS: Spatial and temporal uncertainty--with the traditional psychophysical methods, but without the subject's knowing where and when the signal will appear. The uncertainty factor is a very essen- tial aspect of functioning at night. I realize that this is a depar- ture f rom testing sensory functions ~ n its purest sense, but I think you approach more reality. The more you extend the tests with essen- tially nonsensory functions, the more you get to add effects of cogni- tion. The beauty of pu re sensory systems--most of you who are in sensory psychology or sensory physiology will recognize this-- is that you are working with a well-clef ined anatomical and physiolog ical substrate. I t is very tempting, therefore, to study sensory functions in i solation. In the 1960s, I came across a metatheoretical psychology book about the relationship between real life and testing of performance. The author defended laboratory research by saying, "Suppose you want to test visual ecu ity, and you ask 'Does the result of the Landolt r ing test really transform to real life? ' Where are we interested in visual acuity in 299

300 real life?" Well, perhaps in the dark we are interested that we don't hit a lantern pole when we are walking on the street. No one will then defend a so-called Lantern pole test" where you bring people into a f ield study in the street and register the probability of them hitting a lantern pole while making a stroll. No, we'll go in the laboratory, test the visual acuity, and if needed, prescribe glasses. You presume that that will lower the probability of hitting a lantern pole while walking on the street, although that has not been proven. In the 1960s, we thought we could develop similar simple and small paradigms that would extend to real life as measures of higher cognitive processes and skilled performances. This belief has been considerably shaken in the 1970s and the 1980s. m erefore, the better you simulate reality, the better you are. If you say well, in night vision functioning in reality there is always spatial and temporal uncertainty--so we'll introduce spatial and temporal uncertainty. There is considerable probability that if you don't, your measures do not predict real-life functioning as well as you might expect. MASSOF: I think it might be premature to even ask that question. It's not clear to me, even after 2 days of listening to the talks, what the problem is that needs to be solved. I think it would be important first to determine what you want to do with the data before you collect it. What is it that needs to be known? What are you screening for? Obviously screening for night vision pathology is well worked out, it's easy to do, and night vision disorders are sufficiently rare that the discovery of undiagnosed pathology is not going to happen that often. But In terms of discriminating among people who are Normal and find- ing the "supernormals," I think that what you're going to have to focus on is not sensory equipment but, as Dr. Sanders pointed out, the task. What are we asking them to do? Cognitive factors may be a lot more important than the sensory factors. JOHNSON: I think there are a couple of things that have emerged since 1961 which are worth looking at. One of them is oculomotor func- tion under low illumination. Even though it was reported in the 1800s, the bulk of research on the dark focus of accommodation and dark conver- gence has been obtained within the past 20 years. Contrast sensitivity is another new approach that has emerged since 1961. Neither of these topics represents a panacea for night vision problems, but they are certainly new areas that are worthy of further investigation. With regard to Dr. Sandersl comment about spatial uncertainty' I would like to mention that several clinical automated devices for evaluating peripheral visual function (automated perimeters) are now designed to perform tests with a high degree of spatial uncertainty. They minimize the likelihood that people will be able to predict where or when a target will appear in the peripheral visual field by random- izing target presentation. m is is done for two reasons: (1) to re- duce the number of spurious responses, and (2) to minimize the occur- rence of eye movements. Spatial uncertainty in terms of automated visual field testing has been developed and is used quite widely. By implementing modest alterations to these test procedures, appropriate night visual search tasks or related tests incorporating spatial un- certainty could be readily accomplished.

301 OWSLEY: I just want to emphasize a point that Bob Massof made, and then add something. I think that we would probably be more helpful as basic researchers in coming up with this battery if we understoca better the task requirements of the military. Not only from a standpoint of the cognitive factors but also it would be helpful to know a lot more about the visual requirements of these tasks along the lines that Ralph Haber was talking about. TREDICI: In your experience, Chris [Johnson], do you think the sensitivity of the size of the central 30-degree field is different enough in individuals to be worth studying that in normals? JOHNSON: There's considerable individual variation in the normal population, especially for the over-60 age groups. But even in the younger population there are large individual differences. I certainly feel that these individual differences in the normal population should be investigated, especially with regard to task performance and the effects of practice and training. MASSOF: About the idea of individual variability of test perfor- mance--I think from classic high-threshold theory there's a tendency to assume that these individual differences can be attributed to individual differences in the sensory apparatus, and from detection theory princi- ples we would argue that a large source of the individual difference could be simply due to performance variables. That is, they can be attributed to criterion shifts or criterion differences among observers.