Key Highlights Discussed by Individual Participants
- Effective collaboration among disparate disciplines is critical (e.g., molecular biology and bioengineering or electrophysiology and physics); in this space innovation will arise and there are opportunities to train scientists to work toward a sum greater than the collected parts and spur innovation (Federoff, Sejnowski, and Steward).
- There is a distinction between training of neuroscientists and training in neuroscience, and several participants raised the question of whether graduate programs should focus on one or the other (Steward).
- As neuroscience expands in scope, adding various tracks might be beneficial (Landis, Litt, Raman, Sejnowski, and Steward).
- Forming successful transdisciplinary collaborations requires time and involves a considerable amount of risk, and can be encouraged with increased incentives with regard to grant review and hiring/promotion decisions (Sejnowski).
- Opportunities for transdisciplinary training come from a variety of sources, including National Science Foundation grants and BRAIN Initiative short courses (Ferrini-Mundy and Litt).
NOTE: The items in this list were addressed by individual participants and were identified and summarized for this report by the rapporteurs. This is not intended to reflect a consensus among workshop participants.
As neuroscience has evolved as a discipline and incorporated many types of science—microbiology, genetics, statistics, animal behavior, optics, engineering, computational biology, etc.—it has become increas-
ingly less likely that any one individual or laboratory will have all the expertise needed to tackle higher-level problems. Many workshop participants noted that teams of scientists from disparate disciplines are necessary for improving fundamental neuroscience knowledge, developing new treatments, building the next powerful tool, and revolutionizing imaging technology. But it is not a matter of getting out a checklist and making sure each team has a biologist, a physicist, a mathematician, an engineer, and a chemist. Rather, each of these disciplines needs to learn how to work effectively with the others. According to several workshop participants, in this space innovation will arise and there are opportunities to train scientists to work toward a sum greater than the collected parts.
Oswald Steward, director of the Reeve-Irvine Research Center at the University of California Irvine School of Medicine, enumerated several decision points for graduate programs to consider when training students to engage in transdisciplinary research. Terry Sejnowski emphasized the need for better incentives to encourage scientists to collaborate on transdisciplinary projects. Howard Federoff, executive dean of the Georgetown University School of Medicine, provided an overview of how best to enable transdisciplinary teams to do translational science. Finally, Dennis Choi, director of the Neurosciences Institute at Stony Brook University, called for improving collaboration between basic neuroscientists and clinicians.
DEFINING TRANSDISCIPLINARY NEUROSCIENCE
Steward challenged participants to think about the requirements for successful transdisciplinary collaborations and what impact those requirements can have on training students. In his opinion, a transdisciplinary team should be composed of specialists, not people with a general knowledge of their discipline. For example, if a team requires a neuroscientist, he noted that this person needs to be a card-carrying neuroscientist, that is, someone with a Ph.D. in neuroscience who regularly does neuroscience research. Similarly, if a neuroscientist were putting together a team requiring a mathematician, the neuroscientist would want a card-carrying mathematician, not a neuroscientist with some knowledge of math. Although several participants had differing opinions on the type of neuroscientist needed for such transdisciplinary collaboration—particularly given that most individuals engaged in the neuroscience workforce would not be
considered a card-carrying neuroscientist—Steward noted that there is still a need for experts in the discipline of neuroscience.
Related to the question of specialization versus generalization, Steward discussed the differences between the training of neuroscientists—training in the core knowledge of a discipline that qualifies one to be called a neuroscientist—and training in neuroscience—training for individuals in other disciplines that would allow them to be partners in the greater enterprise of neuroscience research. Steward’s opinion was that a single graduate program probably could not effectively accommodate both of these needs. Instead, programs should carefully consider these differences when developing their training goals and either define themselves as institutes, which are cross-disciplinary, or departments, which have a specialized focus.
As for the training of neuroscientists, a number of participants asked, what does every card-carrying neuroscientist need to know? While there were no clear answers, many participants agreed there should be a limit to how many additional courses should be required of students given the already long average time to earn a degree, even if that limit means sacrificing breadth of knowledge. According to a few workshop participants, one way around this class time limit is to offer micro- or nano-courses, rather than semester-long courses, to give students a chance to sample relevant topics. In addition, several workshop participants suggested that many neuroscience courses could be more effective as a series of coordinated hands-on exercises or demonstrations rather than traditional didactic lectures. More importantly, graduate students need to be trained in how to do rigorous science (as noted in Chapter 3) and establish effective transdisciplinary collaborations.
Another potential training-related choice that Steward pointed out is training students to be Renaissance scientists or goal-directed scientists. The former operate in a mode of pure exploration and discovery, while the latter can be plugged into teams to solve specific problems and develop treatments for disorders. Again, Steward suggested that different tracks are needed to train each type of scientist.
Reconsidering the One-Size-Fits-All Approach to Training
Several workshop participants also expressed the need for separate tracks in neuroscience training, although the dimensions along which to separate varied. A comment by Landis captured a common sentiment expressed throughout the workshop: “There’s too much neuroscience, it’s not one thing anymore.” She asked how much cellular and molecular
neuroscience training is necessary for someone who is doing brain mapping at the macro level? How much magnetic resonance imaging information does someone who is working at the cellular and molecular level need to have? Does a neuroscientist 10 years from now need to be fully articulate in all of the areas of neuroscience? Chesselet noted training programs should be designed in a way in which there is a balance between trainees being aware of a topic compared to having the knowledge (often best acquired in a laboratory setting) to apply it to a research project. Landis suggested that one solution to narrowing students’ focus was to look for lessons from the field of neurology, where there is a core residency program, followed by subspecialty training. Several workshop participants stated that separate tracks might allow for more focused courses—and possibly less overall class time for trainees—and might encourage the development of mini-courses that address particular problems in a certain subspecialty. Potential tracks that could be created in graduate neuroscience programs include electrophysiology, optical imaging, fMRI, cellular and molecular neuroscience, translational neuroscience, neuroengineering, theory and modeling, and systems neuroscience. Trainees could also be split into theoretical or experimental tracks, suggested Litt. Such tracks could potentially be organized around current faculty expertise and available core resources and infrastructure at each institution. Several workshop participants noted that these subspecialty tracks might serve as the basis of tight-knit communities among students and alumni that might be advantageous when seeking internships and employment opportunities. Indira Raman suggested stratifying trainees according to their interested career pathway as well (i.e., academia and non-academic careers).
Finally, Sejnowski and Steward suggested that questions about specialization and the formation of graduate school tracks may ultimately be dictated by outside forces; what kind of workforce do employers need, and, to a lesser degree, what kind of training will funding agencies support? Will there be more jobs in goal-directed science? Is the workforce trending toward large teams? Will these teams need a certain ratio of specialists to generalists (who might be in a better position to support or manage all the moving pieces in a lab)? Will workforce needs vary across subfields of neuroscience? Understanding these needs will be critical for optimizing graduate neuroscience training, said Steward.
Challenges to Cooperative Science
Sejnowski mentioned two primary challenges to overcome to encourage more collaborative science: trust and acknowledgment. Forming collaborations with scientists in other fields is similar to getting married, he noted. You have to have trust, get to know the person, and work together long enough to develop a common language. According to Sejnowski, seeking out scientists from other fields to collaborate and be on the same page on large, complex problems can take such a considerable amount of time and risk that collaboration may not be viewed as worth the effort. These factors could especially dissuade new faculty, who are eager to publish high-impact articles and obtain grant funding in order to secure tenure. The field needs a better way, according to Sejnowski, to reward scientists for building cooperative, transdisciplinary teams. One way to do this is to convince academic departments and funding agencies to assign collaborative projects more weight when making decisions about promotions and grants, akin to the suggestion for the sharing index and the data citation mentioned in Chapter 2. NIH, for its part, has begun to recognize the importance of taking risks to encourage interdisciplinary research with the advent of its Common Fund High Risk, High Reward program,1 which supports the Early Independence Award,2 the New Innovator Award,3 the Pioneer Award,4 and the Trans-formative Research Award.5
Initiatives for Cooperative Science
Transdisciplinary collaboration was a vital part of the discussion among the NIH BRAIN Initiative Working Group, according to Sejnowski, a member of the working group. One of the seven core principles of the initiative that is listed in the BRAIN 2025 report6 is cross boundaries in interdisciplinary collaborations (NIH, 2014). Within the report, potential collaboration scenarios to facilitate the BRAIN Initiative’s goals were discussed:
6BRAIN 2025: A Scientific Vision. See http://www.braininitiative.nih.gov/2025/BRAIN2025.pdf (accessed October 28, 2014).
- “The physicists and engineers who develop optical hardware should partner with the biologists and chemists who develop new molecular sensors.
- The tool builders who design new molecules for sensing or regulating neurons should partner with neuroscientists who will rigorously examine their validity in neurons and brains.
- The theorists who develop models for understanding neuronal dynamics should partner with experimentalists, from initial experimental design to execution to interpretation.
- The clinicians and neuroscientists who develop sophisticated imaging methods in humans should partner with scientists working in animal models who can relate imaging signals to the underlying cellular mechanisms with great precision” (p. 51).
Finally, Sejnowski mentioned the imperative for transdisciplinary research held by another science initiative of which he is also an organizing member, the National Academies Keck Futures Initiative (NAKFI). NAKFI brings together scientists from disparate fields to work intensively over 2 days in small teams to address issues related to important science problems. A few years ago, NAKFI conducted a survey of 600 stakeholders to examine how research could be more innovative. The survey asked individuals to rate the importance and ubiquity of several factors that are integral to interdisciplinary collaborations, including data accessibility, institutional support, responsive funding, ingenuity/risk taking, incentives, and education/training (see Figure 4-1). The results revealed that the more critical gaps—those factors rated high in importance and low in ubiquity—were responsive funding, incentives, and ingenuity/risk taking (see Figure 4-2). Katja Brose, editor of Neuron, cautioned workshop participants about moving into the direction where it is all about team science. In her opinion, what makes neuroscience special is the diversity of topics and approaches. There are instances in which collaboration at the investigator level or between laboratories is more desired than team science, in which several experts come together for a common goal.
FIGURE 4-1 A conceptual model of the various factors that contribute to enhancing innovative research.
SOURCE: Terry Sejnowski presentation, Salk Institute for Biological Studies, October 28, 2014.
OPPORTUNITIES FOR TRANSDISCIPLINARY TRAINING
Throughout the workshop, several participants discussed a number of opportunities to support transdisciplinary training, to include incorporating courses about collaboration in neuroscience graduate programs. Descriptions of a few of these funding opportunities and courses are provided below. Akil and Chesselet stressed that education about transdisciplinary research should not stop in graduate school, but rather should be modeled after continuing medical education courses for physicians, in which education is incorporated throughout the trainee’s lifespan.
FIGURE 4-2 Results from a survey of scientists across many disciplines responding to questions about the importance of a variety of factors (and their prevalence) for increasing innovation in science.
SOURCE: Terry Sejnowski presentation, Salk Institute for Biological Studies, October 28, 2014.
NSF Research Traineeships
NRT7 supports the development of innovative training programs for teams of graduate students within a single university or institution around a cross-disciplinary theme related to national research priorities. NRT replaces NSF’s IGERT grants, the last of which were issued in 2013. Joan Ferrini-Mundy, assistant director of the Directorate for Education and Human Resources at NSF, noted that between 1998 and 2013, 278 IGERT awards were issued to 100 lead universities in support of 6,500 graduate students. Neuroscience projects accounted for 15 percent of the IGERT awards. Previous neuroscience-related IGERT awards focused on themes such as neuroimaging of non-human primates, neuroprostheses,
7See http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505015 (accessed October 28, 2014).
and computational neurobiology. The initial priority research theme of the new NRT program is Data-Enabled Science and Engineering. However, proposals are encouraged on any other crosscutting, interdisciplinary theme.
Ferrini-Mundy added that time to degree was not slowed for students doing interdisciplinary research on IGERT grants. She also mentioned that students would report anecdotally that their ability to communicate and to get other people excited about their science improved as a result of their IGERT experience.
Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS)
The NSF-NSC grants8 support transformative science and engineering efforts to accelerate knowledge of neural and cognitive systems. Because the complexities of the brain and behavior touch on many aspects of science and engineering, these grants will cut across NSF’s various directorates. For 2015, the NSF-NSC grants are organized around two research themes: (1) Neuroengineering and Brain-Inspired Concepts and Designs and (2) Individuality and Variation. Within each theme, projects will address general advances in theory and methods, technological innovations, educational approaches, enabling research infrastructure, and workforce development.
BRAIN Initiative Short Courses
In recognition of the critical role cross-disciplinary research will play in developing the next generation of tools and computational approaches for studying the brain, the NIH BRAIN Initiative plans to sponsor short courses9 for training graduate students, medical students, postdoctoral scholars, medical residents, and/or early-career faculty. Courses will be offered to neuroscientists as well as to scientists from other disciplines. One course will focus on tools to classify cell types, reconstruct neural pathways, and record from and manipulate neural circuits using electrical
8See http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505132 (accessed October 24, 2014).
9BRAIN Initiative short course about data analysis/handling. See http://grants.nih.gov/grants/guide/notice-files/NOT-MH-15-005.html (accessed October 28, 2014). BRAIN Initiative short course about innovative tools. See http://grants.nih.gov/grants/guide/notice-files/NOT-MH-15-006.html (accessed October 28, 2014).
and optical techniques. The other course will focus on quantitative methods for analyzing high-dimensional imaging, electrophysiological, anatomical, and behavioral datasets. Aside from using these relatively low-cost short courses as a training tool, the staff organizing the NIH BRAIN Initiative hopes the courses will expose physical and information scientists to the projects in the initiative and help foster cross-discipline collaborations.
National Academies Keck Futures Initiative Seed Grant Program10
NAKFI has hosted an annual meeting over the past 10 years on how to push forward innovations through interdisciplinary interactions among many different fields of science and engineering. Previous meetings with a strong neuroscience focus include signaling, complex systems, imaging science, the digital brain, and collective behavior. Participants are invited to self-organize into cross-disciplinary teams to apply for seed grants to further pursue ideas stimulated by conversations and breakout sessions that occur over the course of the 2-day meetings.
University of Pennsylvania’s Brain-Computer Interface Course
One challenge in bringing multiple disciplines together to work on a neuroscience problem is communication, said Litt. Every field has its own special language, and to some extent, its own worldview. Litt described his “Brain-Computer Interface” course, which brings together students in neuroscience, physical science, and engineering, as a model for training disparate groups to communicate and collaborate with one another. In addition to classroom lectures on topics such as modeling and simulation, the students work in interdisciplinary teams on 10 hands-on programming projects. Project examples include modeling visual cortex orientation tuning columns, controlling robot arms driven by motor units, classifying speech, and designing cochlear implants.
CROSS-TRAINING IN CLINICAL NEUROSCIENCE
Despite the historic intersection between neuroscience and clinical science, there is little cross-training between the two disciplines, said Choi. The clinical interface is central to neuroscience for at least two rea-
sons, he added: (1) the potential for medical benefit is a key source of inspiration, purpose, funding, and public support; and (2) the interface represents the necessary experimental platform for investigating, and ultimately understanding, the human mind. Although the clinical dimension in neuroscience training has been around longer than more novel and emerging dimensions, such as genetics, engineering, and informatics, Choi noted that basic neuroscience training typically provides limited exposure to principles of clinical medicine, clinical research, and overall disease biology. The converse is true as well; clinical training typically provides scant exposure to the scientific method.
Choi cited four primary consequences of the lack of cross-training in these areas. First, neuroscientists without clinical training are vulnerable to what Landis referred to as “pseudo-translation”—studies that combine disease models of uncertain value with interventions unlikely to ever be applicable to patients. These ideas can gain inappropriate traction and lead to dilution of resources and disappointment for myriad stakeholders, said Choi. Second, he noted that clinicians without basic neuroscience knowledge are vulnerable to unsubstantiated claims about the brain and are prone to adopting dogmatic approaches based on anecdotes rather than available evidence. Third, without cross-training and collaboration, opportunities to exploit the clinical setting for studies in basic neuroscience can be missed. Choi used work by Edward Chang at the University of California, San Francisco, as an example of such research. Chang took advantage of intraoperative electrocorticography for patients about to undergo epilepsy surgery to test theories about how speech is perceived and generated by the brain. Choi added that as new tools and technologies provide answers to research questions the neuroscience enterprise cannot afford the divide between basic and clinical science. Fourth, the lack of exposure to, and appreciation of, the clinical method creates situations where researchers might not truly understand clinical data. There are fundamental risks, Choi said, for bias in clinicians taking clinical history and in performing examinations of the nervous system. Once those biases are incorporated into databases where phenotype is linked with genetic and imaging information, Choi stated that they become intractable and can greatly affect study outcomes.
Another obstacle to maximizing the potential of the clinical interface is the historical balkanization in the way patients and diseases are managed in medical centers today, noted Choi. The primary example of these long-standing divisions is between neurology and psychiatry. Despite the fact that the distinctions between their missions are blurring, they remain
separate departments and their cultures and associated training programs remain fully segregated. Balkanization occurs throughout clinical science, Choi continued. Diseases of the nervous system are typically managed by disparate clinical departments and not just psychiatry, neurology, and neurosurgery:
- Medicine (Alzheimer’s disease, fibromyalgia, sleep disorders)
- Pediatrics (cerebral palsy, genetic/metabolic disorders)
- Radiology (stroke)
- Anesthesia (pain)
- Ophthalmology (macular degeneration)
- Otolaryngology (tinnitus, hearing loss)
- Orthopedics (stroke, traumatic brain injury)
- Obstetrics (hot flashes, seizures, hyperemesis)
- Rehabilitation (stroke, traumatic brain injury)
- Emergency medicine (stroke, traumatic brain injury)
- Oncology (central nervous systems cancers, radiation encephalopathy)
- Surgery (neurological intensive care)
Because of this balkanization, Choi said opportunities for collaboration are challenging, but offered several suggestions for improving cross-training between neuroscience and clinical science (see Box 4-1). In addition, a few workshop participants discussed unique challenges for physician-scientists. For example, several speakers noted that M.D./Ph.D. students often accelerate through their Ph.D. coursework to go into their clinical training. Landis asked whether there was a special role for them, given that in principle they could speak to both communities (neuroscience and clinical science).
Challenges and Opportunities for Improving Cross-Training Between Neuroscience and Clinical Science
- The interface between basic research and clinical science provides both a key source of inspiration, purpose, funding, and public support as well as the necessary experimental platform for investigating and ultimately understanding the human mind.
- Neuroscience training typically provides limited exposure to principles of clinical medicine, clinical research, and overall disease biology, while clinical training typically provides scant exposure to the scientific method.
- Opportunities for improving cross-training between neuroscience and clinical science include increased availability of neurobiology of disease courses and clinical rotations for neuroscience trainees, and completion of research projects and journal clubs for clinical trainees.
- For neuroscience graduate students:
- Increase the availability and strength of neurobiology of disease (NBD) courses. This type of course could have a greater impact if delivered online due to the labor-intensive steps of bringing in patients and performing all of the clinical interventions (e.g., Society for Neuroscience NBD workshop, National Institute of Neurological Disorders and Stroke/Child Neurology NBD in Children website).
- Augmented online clinical courses (e.g., Stanford Online, HarvardX) with readings and discussions with faculty—even tests and recognition of achievement.
- Increase the availability of clinical courses (pathophysiology, clinical research) for neuroscience graduate students.
- Increase the availability of clinical rotations to neuroscience Medical Engineering and Medical Physics (HST MEMP) program.
- For clinical students:
- Increase opportunities for exposure to basic neuroscience, as well as physics, informatics, and engineering, for selected medical students (e.g., HST MEMP program)
- Increase graduate students along the lines of those implemented by the Harvard-Massachusetts Institute of Technology Health Sciences and Technology requirements for the training of clinical residents in core scientific methods, focusing on skills needed to read the clinical literature with a critical eye.
- Require completion of a research project.
- Journal clubs focusing on the critical analysis of key papers.
- For both neuroscience and clinical students:
- Build interdisciplinary and interdepartmental teams around shared clinical research or clinical care goals, involving both M.D.s and Ph.D.s (e.g., Parkinson’s disease centers).
- Merge neurology and psychiatry training—and eventually, departments.
SOURCE: Dennis Choi presentation, Stony Brook University, October 29, 2014.