Neuroscience Graduate Training at Brandeis

Research image from the Avital Rodal lab

Image Source: Avital Rodal, Associate Professor of Biology

The human brain has roughly as many neurons as there are stars in our galaxy, making it an enormously complex adaptive system.   Making sense of this complexity increasingly requires neuroscientists who are both broadly trained critical and creative thinkers, and who have extensive analytic and computational skills. The Interdepartmental Neuroscience graduate program at Brandeis comprises a comprehensive training program designed to give the next generation of outstanding neuroscientists the cognitive and technical skills they need to make important breakthroughs in understanding nervous system function and health.

Our program is characterized by a diverse and highly collaborative set of internationally renowned faculty, with research programs that incorporate all the major subdisciplines of the field. Collaboration is part of the air we breathe:  being a vibrant program embedded in a small and intimate research university naturally encourages interactions across model systems and at the interfaces between disciplines. During laboratory rotations students are encouraged to explore intellectual frameworks and acquire a range of skills, and throughout their PhD will interact with and receive mentoring from a diverse group of faculty, as well as near-peer mentoring from a strong cohort of interdisciplinary graduate students and postdocs. Our trainees are highly successful in a range of pursuits after graduation, including academic and industrial science, science policy, and science communication.

Shared publications from faculty collaborations

Research labs at Brandeis frequently publish peer-reviewed research together. Some of the publications are listed here:

  • Garrity, P. A., Goodman, M. B., Samuel, A. D., and Sengupta, P. (2010) Running hot and cold: behavioral strategies, neural circuits, and the molecular machinery for thermotaxis in C. elegans and DrosophilaGenes Dev 24, 2365-2382

  • Kang, K., Pulver, S. R., Panzano, V. C., Chang, E. C., Griffith, L. C., Theobald, D. L., and Garrity, P. A. (2010) Analysis of Drosophila TRPA1 reveals an ancient origin for human chemical nociception. Nature 464, 597-600

  • Miller, P., and Katz, D. B. (2010) Stochastic transitions between neural states in taste processing and decision-making. J Neurosci 30, 2559-2570

  • Miller, P., and Wingfield, A. (2010) Distinct effects of perceptual quality on auditory word recognition, memory formation and recall in a neural model of sequential memory. Front Syst Neurosci 4, 14

  • Nagoshi, E., Sugino, K., Kula, E., Okazaki, E., Tachibana, T., Nelson, S., and Rosbash, M. (2010) Dissecting differential gene expression within the circadian neuronal circuit of DrosophilaNat Neurosci 13, 60-68

  • Piquado, T., Cousins, K. A., Wingfield, A., and Miller, P. (2010) Effects of degraded sensory input on memory for speech: behavioral data and a test of biologically constrained computational models. Brain Res 1365, 48-65

  • van der Linden, A. M., Beverly, M., Kadener, S., Rodriguez, J., Wasserman, S., Rosbash, M., and Sengupta, P. (2010) Genome-wide analysis of light- and temperature-entrained circadian transcripts in Caenorhabditis elegansPLoS Biol 8, e1000503

  • Neseliler, S., Narayanan, D., Fortis-Santiago, Y., Katz, D. B., and Birren, S. J. (2011) Genetically induced cholinergic hyper-innervation enhances taste learning. Front Syst Neurosci 5, 97

  • Shang, Y., Haynes, P., Pirez, N., Harrington, K. I., Guo, F., Pollack, J., Hong, P., Griffith, L. C., and Rosbash, M. (2011) Imaging analysis of clock neurons reveals light buffers the wake-promoting effect of dopamine. Nat Neurosci 14, 889-895

  • Blackman, M. P., Djukic, B., Nelson, S. B., and Turrigiano, G. G. (2012) A critical and cell-autonomous role for MeCP2 in synaptic scaling up. J Neurosci 32, 13529-13536

  • Birren, S. J., and Marder, E. (2013) Neuroscience. Plasticity in the neurotransmitter repertoire. Science 340, 436-437

  • Hengen, K. B., Lambo, M. E., Van Hooser, S. D., Katz, D. B., and Turrigiano, G. G. (2013) Firing rate homeostasis in visual cortex of freely behaving rodents. Neuron 80, 335-342

  • Miller, P., and Katz, D. B. (2013) Accuracy and response-time distributions for decision-making: linear perfect integrators versus nonlinear attractor-based neural circuits.J Comput Neurosci 35, 261-294

  • Ni, L., Bronk, P., Chang, E. C., Lowell, A. M., Flam, J. O., Panzano, V. C., Theobald, D. L., Griffith, L. C., and Garrity, P. A. (2013) A gustatory receptor paralogue controls rapid warmth avoidance in DrosophilaNature 500, 580-584

  • Sengupta, P., and Garrity, P. (2013) Sensing temperature. Curr Biol 23, R304-307

  • Shang, Y., Donelson, N. C., Vecsey, C. G., Guo, F., Rosbash, M., and Griffith, L. C. (2013) Short neuropeptide F is a sleep-promoting inhibitory modulator. Neuron 80, 171-183

  • Cousins, K. A., Dar, H., Wingfield, A., and Miller, P. (2014) Acoustic masking disrupts time-dependent mechanisms of memory encoding in word-list recall. Mem Cognit 42, 622-638

  • Ghiretti, A. E., Moore, A. R., Brenner, R. G., Chen, L. F., West, A. E., Lau, N. C., Van Hooser, S. D., and Paradis, S. (2014) Rem2 is an activity-dependent negative regulator of dendritic complexity in vivoJ Neurosci 34, 392-407

  • Van Hooser, S. D., Escobar, G. M., Maffei, A., and Miller, P. (2014) Emerging feed-forward inhibition allows the robust formation of direction selectivity in the developing ferret visual cortex. J Neurophysiol 111, 2355-2373

  • Yu, Y. V., Bell, H. W., Glauser, D., Van Hooser, S. D., Goodman, M. B., and Sengupta, P. (2014) CaMKI-dependent regulation of sensory gene expression mediates experience-dependent plasticity in the operating range of a thermosensory neuron. Neuron 84, 919-926

  • Guo, F., Yu, J., Jung, H. J., Abruzzi, K. C., Luo, W., Griffith, L. C., and Rosbash, M. (2016) Circadian neuron feedback controls the Drosophila sleep--activity profile. Nature 536, 292-297

  • Hengen, K. B., Torrado Pacheco, A., McGregor, J. N., Van Hooser, S. D., and Turrigiano, G. G. (2016) Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake. Cell 165, 180-191

  • Sadacca, B. F., Mukherjee, N., Vladusich, T., Li, J. X., Katz, D. B., and Miller, P. (2016) The Behavioral Relevance of Cortical Neural Ensemble Responses Emerges Suddenly. J Neurosci 36, 655-669

  • Steinmetz, C. C., Tatavarty, V., Sugino, K., Shima, Y., Joseph, A., Lin, H., Rutlin, M., Lambo, M., Hempel, C. M., Okaty, B. W., Paradis, S., Nelson, S. B., and Turrigiano, G. G. (2016) Upregulation of mu3A Drives Homeostatic Plasticity by Rerouting AMPAR into the Recycling Endosomal Pathway. Cell Rep 16, 2711-2722

  • Christie, I. K., Miller, P., and Van Hooser, S. D. (2017) Cortical amplification models of experience-dependent development of selective columns and response sparsification. J Neurophysiol 118, 874-893

  • Herzog, J. J., Deshpande, M., Shapiro, L., Rodal, A. A., and Paradis, S. (2017) TDP-43 misexpression causes defects in dendritic growth. Sci Rep 7, 15656

  • Bronk, P., Kuklin, E. A., Gorur-Shandilya, S., Liu, C., Wiggin, T. D., Reed, M. L., Marder, E., and Griffith, L. C. (2018) Regulation of Eag by Ca(2+)/calmodulin controls presynaptic excitability in DrosophilaJ Neurophysiol 119, 1665-1680

  • Moore, A. R., Richards, S. E., Kenny, K., Royer, L., Chan, U., Flavahan, K., Van Hooser, S. D., and Paradis, S. (2018) Rem2 stabilizes intrinsic excitability and spontaneous firing in visual circuits. Elife 7

Neuroscience faculty members listed in bold.