User:Mintjulie/sandbox
Jennifer L. Raymond | |
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Born | 24 January 1997 |
Nationality | American |
Alma mater | Williams College |
Known for | Advocating Diversity in STEM |
Awards |
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Scientific career | |
Fields | Neuroscience |
Jennifer L. Raymond is an American neuroscientist and associate professor of neurobiology at Stanford University School of Medicine.[1] Her research focuses on using cerebellar and vestibular circuitry to understand the logic of neural learning algorithms.[2] In addition to her research and professorship, Raymond has been committed to promoting diversity in STEM academia and served the neuroscience community in numerous capacities.
Raymond completed a B.A. with a major in mathematics at Williams College (1987). After graduating, she acquired her Ph.D. in neuroscience at the University of Texas Health Science Center at Houston, working in Jack Byrne's lab (1993). She then completed postdoctoral training with Steve Lisberger at University of California, San Francisco. Raymond is currently an associate professor of neurobiology at Stanford University School of Medicine. In the academic year 2018-2019, she taught courses including graduate/undergraduate research studies, senior honors tutorial, medical scholars research, and other independent studies. In prior years, she taught neuroscience systems core. She is an affiliated faculty member of Bio-X and Wu Tsai Neurosciences Institute, both of which are Stanford's biosciences research institutes. Raymond is also an active member of Society for Neuroscience, serving in the Education Committee and the Committee on Neuroscience Departments and Programs.[4]
The Raymond Lab studies how local synaptic decisions are coordinated throughout a neural circuit to yield an algorithm for learning. Neural circuits are shaped by patterns of dynamic synaptic connections, which are elicited by our experiences. Depending on the pattern of input, specific synaptic connections in a neural circuit can be strengthened or weakened, constantly changing to support our sensation, action, and cognition. Such ability of synapses to change continuously depending on the activity of neurons is called synaptic plasticity. The Raymond Lab analyzes the neural learning rules governing these local decisions on a moment-by-moment basis. Their ultimate goal is to understand how these local decisions are coordinated throughout a neural circuit to yield an algorithm for the adaptive regulation of the circuit's function.
The Raymond Lab uses electrophysiological, behavioral, computational, and molecular-genetic tools for precise manipulation of specific neurons in vivo for investigating the circuit architecture in the cerebellum. They have developed behavioral paradigms in mice for studying the vestibular control of behavior and its adaptive regulation by the cerebellum, including learned changes in the amplitude and timing of movements, the generalization of learning, and factors influencing the persistence of memory.
Acquiring an understanding of the algorithms used by neural circuits can potentially help design machines with computing and learning capacity more closely approximating humans. In addition, such studies could be applied to help optimize learning in neural circuits damaged by injury or disease.
- Depressed by Learning-Heterogeneity of the Plasticity Rules at Parallel Fiber Synapses onto Purkinje Cells (The Cerebellum, 2018)
- Computational Principles of Supervised Learning in the Cerebellum (Annual Review of Neuroscience, 2018)
- Yet another reason to walk instead of drive (Nature Neuroscience, 2018)
- Magnetic eye tracking in mice (eLife, 2017)
- A saturation hypothesis to explain both enhanced and impaired learning with enhanced plasticity (eLife, 2017)
- Timing Rules for Synaptic Plasticity Matched to Behavioral Function (Neuron, 2016)
- Purkinje cell responses during visually and vestibularly driven smooth eye movements in mice (Brain and Behavior, 2015)
- Signals and learning rules guiding oculomotor plasticity (Journal of Neuroscience, 2014)
- Cerebellar encoding of multiple candidate error cues in the service of motor learning (Journal of Neuroscience, 2014)
Advocacy for Diversity in STEM Academia
[edit]Jennifer Raymond is an active advocate for women and underrepresented minorities in STEM and is committed to bringing diversity into academia. She has been actively involved in advocating diversity at both her home institution and at external affiliations. At Stanford, Raymond served as the Associate Dean (2012-2014) at Office of Diversity and Leadership and during this time, she redesigned faculty career track to attract next-generation scientists into the workforce. As a member of Society for Neuroscience, Raymond has given lectures about diversity in STEM academia. Some of her lectures include "Change the Formula to Change the System," "Where is the Drop Off?," "Why Underrepresented Minorities Leave Academia," and "What is Diversity Double-Blind."[7]
- Funders should evaluate projects, not people. (Lancet, 2019)
- An Integrated Career Coaching and Time Banking System Promoting Flexibility, Wellness, and Success: A Pilot Program at Stanford University School of Medicine (Academic Medicine, 2018)
- Obscuring Gender Bias with "Choice" (Science, 2014)
- Sexist attitudes: Most of us are biased. (Nature, 2013)
In Research
[edit]- Sloan Fellow, Alfred P. Sloan Foundation (1999)
- McKnight Scholar, McKnight Endowment Fund for Neuroscience (1999)
- Klingenstein Fellow, Klingenstein Foundation (1999)
- Terman Fellow, Stanford University (1999)
- EJLB Foundation Scholar, EJLB Foundation (2004)
- Graduate Teaching Award, Stanford School of Medicine
- Stanford Biosciences Excellence in Diversity Award
External Links
[edit]- How Challenges Can Bring Change, Society for Neuroscience
- Building a Circuit-Diagram for the Brain, Stanford University
- Unconscious Bias: Where It Comes From and What You Can Do About It, Report from Santa Fe
References
[edit]- ^ "Jennifer Raymond: Bio". Stanford Profiles. Retrieved 12 May 2019.
- ^ "Research: Using the cerebellar and vestibular circuitry to understand the logic of neural learning algorithms". The Raymond Lab. Retrieved 12 May 2019.
- ^ "Jennifer Raymond Profile". Stanford Profiles. Retrieved 12 May 2019.
- ^ "SfN: Diversity". Society for Neuroscience. Retrieved 12 May 2019.
- ^ "Research: Using the cerebellar and vestibular circuitry to understand the logic of neural learning algorithms". The Raymond Lab. Retrieved 12 May 2019.
- ^ "Jennifer Raymond: All Publications". Stanford Profiles. Retrieved 12 May 2019.
- ^ "SfN: Diversity". Society for Neuroscience. Retrieved 12 May 2019.
- ^ "Jennifer Raymond: All Publications". Stanford Profiles. Retrieved 12 May 2019.
- ^ "Jennifer Raymond: Bio". Stanford Profiles. Retrieved 12 May 2019.
- ^ "SfN: Diversity". Society for Neuroscience. Retrieved 12 May 2019.
- ^ https://www.simonsfoundation.org/team/jennifer-raymond/