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a likely possibility, it should be fascinating to explore further the idea that there are classes of neuronal responses delayed and/or prolonged on the order of seconds after a task event.

Given what we know about the physiological and biophysical parameters that lead to variance in current fMRI signal change onset measurements, there are two complimentary approaches to reducing variance in regional onset delay measurements that might be used to measure neuronally evoked delays within or across brain regions with a temporal resolution down to fractions of a second. First, several MRI acquisition techniques are know to be selectively sensitive to physiological perturbations within the microvasculature. Though at a loss of some sensitivity, these data acquisition methods should reduce the intrinsic temporal lags, and hence variation, created by imaging flow downstream into draining venous vessels. A similar reduction in sensitivity to downstream flow should be provided through use of some of the arterial spin labeling techniques recently developed, though again at a loss of sensitivity. The use of higher field strength imaging systems, and more advanced radio frequency receiver technology, should at least, in part, mitigate against these sensitivity losses and make such measurements practical. Second, at least under some circumstances it will be possible to make measurements relative to the baseline hemodynamic delay within regions or voxels. Savoy and colleagues (25) have performed such a normalization to reveal temporal lags on the order of 1/2 sec in visual cortex (Fig. 5). Their observation clearly demonstrates the potential of making temporal neuronal onset maps that have the underlying hemodynamic lag variance removed, even for time scales significantly below the apparent hemodynamic delays.

These data suggest that combining high-speed MRI techniques with event-related task paradigms can be used successfully to map quite rapid hemodynamic changes. “Rapid,” however, is a relative term—although changes on the order of seconds, or even several hundred milliseconds, is certainly fast enough to track changes in mental activity occurring with a broad range of tasks and state changes (for example, in studies of rapidly intermixed trials types, of sleep, and of learning), it is clearly not rapid enough to observe the transient coordination of neuronal activities known to occur across large segments of the cortex on time scales of tens to a few hundred milliseconds. The only noninvasive techniques capable of resolving brain activity at such short time scales are EEG and magnetoencephalography (MEG). Unfortunately, however, these techniques provide relatively coarse spatial resolution. To overcome this limitation, techniques recently have been developed for combining the temporal resolution of EEG and MEG with the spatial resolution of fMRI (52, 53). By using such techniques, it is now becoming possible to study the precise spatiotemporal orchestration of neuronal activity associated with perceptual and cognitive events. One example of MRI/MEG integration is shown in Fig. 6. Event-related fMRI allows a further refinement of such integration by affording the ability to study the same exact paradigms in both fMRI settings and during EEG and MEG sessions.


This paper has briefly reviewed several recent developments in fMRI that promise to significantly expand, in the temporal domain, the manner in which we map human brain function. Two developments should allow the field of fMRI to continue this dramatic growth. First, because of both the drive to ever higher magnetic field strengths and improvements in radio frequency receiver coil technology, MRI signal-to-noise shows no evidence of plateau. Second, new and more sophisticated data analytic methods offer greater understanding of our data’s true sensitivity and specificity and will continue to improve our ability to address increasingly sophisticated hypotheses about the underlying mechanisms of brain action. Thus there is every reason to expect that the next half-decade of activity in this field will show growth at least as fast as the last and carry us into new domains of spatial and temporal resolution in our efforts at human brain mapping.

We thank our many colleagues at the Nuclear Magnetic Resonance Center, Massachusetts General Hospital for discussion and support. Figures were generously provided by Ken Kwong, Robert Savoy, Kathy O’Craven, Peter Bandettini, Vince Clark, Karl Friston, Seiki Konishi, and Daniel Schacter. Nick Szumski provided help with preparation of the manuscript. R.L.B. was supported by National Institutes of Health Grant DC03245–01, the Charles A.Dana Foundation, and the Human Frontiers Science Project. A.M.D. was supported by the Human Frontiers Science Project.

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