Bradley Voytek

Bradley Voytek is an Associate Professor in the Department of Cognitive Science, the Halıcıoğlu Data Science Institute, and the Neurosciences Graduate Program at UC San Diego. He is an Alfred P. Sloan Neuroscience Research Fellow and National Academies Kavli Fellow, as well as a founding faculty member of the UC San Diego Halıcıoğlu Data Science Institute and its undergraduate Data Science program, where he serves as Vice-chair.

His research program uses neural modeling and simulation, along with large-scale data mining and machine learning techniques, to understand the physiological basis of human cognition and age-related cognitive decline. To do this, we collect electrophysiological data from people, including invasive recordings from patients undergoing brain surgery. We also have extensive collaborations with colleagues who collect data from human iPSC-derived cortical organoids. Rather than asking, "What brain regions are associated with working memory?" we ask, "Given the computational properties and physiology of neurons and neural systems, how can they give rise to cognitive phenomena that look like 'working memory', and what are the behavioral and cognitive limitations and consequences of these constraints?"

He is a longtime advocate for promoting science to the public, and volunteers extensively to talk to students at all grade levels about the joys of scientific research. In addition to his academic publications, his outreach work has appeared in outlets ranging from Scientific American and NPR to the San Diego Comic-Con. He is also known for his zombie brain “research” and book, with friend and fellow neuroscientist Tim Verstynen, "Do Zombies Dream of Undead Sheep?", by Princeton University Press.

• Donoghue T*, Haller M*, Peterson EJ*, Varma P, Sebastian P, Gao R, Noto T, Knight RT, Shestyuk A¶, Voytek B¶ (2020). Parameterizing neural power spectra into periodic and aperiodic components. Nature Neurosci. (paper)
• Gao R, van den Brink RL, Pfeffer T, Voytek B (2020). Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture. eLife. (paper)
• Donoghue T, Dominguez J, Voytek B. Electrophysiological frequency band ratio measures conflate periodic and aperiodic neural activity. eNeuro. (paper)
• Peterson EJ & Voytek B. Homeostatic mechanisms may shape the type and duration of oscillatory modulation. J Neurophysiol. (paper).
• Tran TT, Rolle CE, Gazzaley A, Voytek B. Linked sources of neural noise contribute to age-related cognitive decline. J Cogn Neurosci. (paper).
• Trujillo CA*, Gao R*, Negraes PD*, Chaim IA, Domissy A, Vandenberghe M, Devor A, Yeo GW, Voytek B¶, Muotri AR¶ (2019). Complex Oscillatory Waves Emerging from Cortical Organoids Model Early Human Brain Network Development. Cell Stem Cell. (paper)
• Cole SR & Voytek B (2019). Cycle-by-cycle analysis of neural oscillations. J Neurophysiol. (paper)
• Gao R, Peterson EJ, Voytek B (2017). Inferring synaptic excitation/inhibition balance from field potentials. NeuroImage. (paper)
• Cole SR, van der Meij R, Peterson EJ, de Hemptinne C, Starr PA, Voytek B (2017). Nonsinusoidal beta oscillations reflect cortical pathophysiology in Parkinson's disease. J Neurosci. (paper)
• Cole SR & Voytek B (2017). Brain oscillations and the importance of waveform shape. Trends Cogn Sci. (paper)
• Tran T, Hoffner NC, LaHue SC, Tseng L, Voytek B (2016). Alpha phase dynamics predict age-related visual working memory decline. NeuroImage. (paper)
• Voytek B, Kayser AS, Badre D, Fegen D, Chang EF, Crone NE, Parvizi J, Knight RT, D’Esposito M (2015). Oscillatory dynamics coordinating human frontal networks in support of goal maintenance. Nature Neurosci. (paper)
• Voytek B, Kramer MA, Case J, Lepage KQ, Tempesta ZR, Knight RT, Gazzaley A (2015). Age-related Changes in 1/f Neural Electrophysiological Noise. J Neurosci. (paper)
• Voytek B & Knight RT (2015). Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease. Biol Psychiatry. (paper)
• Voytek JB & Voytek B (2012). Automated cognome construction and semi-automated hypothesis generation. J Neurosci Methods 208(1), 92-100. (paper)