Neuroscience Training for the 21st Century

Abstract

The field of neuroscience is enjoying a rapid expansion in scope, coupled with a remarkable broadening of conceptual approaches, scientific tools, and clinical applications. This growth poses new challenges for academic training programs as they prepare young neuroscientists for a more complex, competitive, and diverse career landscape. Multiple stakeholders, including academia, federal funding agencies, industry, scientific societies, private foundations, and other public and private sector contributors, need to be actively engaged in supporting this broad training effort. A renewed commitment to a more forward-looking, flexible yet integrative training vision offers opportunities for a bright future for young neuroscientists as they assume the role of vanguard of the enterprise that enriches our understanding of the brain.

Intellectual Synthesis in Mentorship Determines Success in Academic Careers

“…We grouped the data into two categories, tight-knit mentorships with mentor graph distance less than 4 and out-of-nest mentorships with mentor graph greater than or equal to 4. In this case, we do see a different distribution of tight-knit and out-of-nest mentorship groups for the two different outcomes ( p=0.0072 , Pearson’s χ 2 test using 100,000 Monte Carlo permutations). Thus trainees of advisors that are closely connected in the mentoring graph may be at a disadvantage in acquiring independent research positions, although a larger dataset will confirm that this effect is a confound with other features, in particular the high publication similarity associated with closely related mentors.…”

“…2E is larger than this trend. This difference may reflect the substantial recent growth of the well-represented field of neuroscience ( 2 , Fig. 7), but it may also reflect a sampling bias in the database favoring more recent graduate students and postdocs.…”

Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience

“…Similarly, as noted above, the richness and complexity of available experimental data is beginning to outstrip the sophistication of the theory that we need to guide new experiments and the development of new analysis approaches. This is becoming a critical bottleneck (Akil et al 2016); increased investment in neural data science and neurotheory training will pay rich dividends in improving our understanding of neural systems over the next decade. * Introduces useful methodology for analyzing and testing orthogonality of various signals in population-level data; uses these methods to advance understanding of preparation and execution of movement.…”

Circuitry-Based Human Neuroanatomy for the Next Generation in Psychiatry and Neuroscience

“…Nevertheless, they are not sufficient to make people imagine a particular circuitry when they observe behavioral phenotypes. This kind of neuroanatomical understanding is beneficial not only in medical training but also to trainees in other neuroscientific areas such as systems neuroscience, human and animal brain imaging, animal studies of cognitive function, and computational neuroscience, whose contribution is crucial to the success of the next generation of neurosciences [38,39]. Currently, these young, talented people are either still taught in traditional human neuroanatomy courses or studying on their own, which sometimes is difficult and makes them lose sight of the big picture of the human brain.…”