Jack Gallant in outdoor setting
Photo: Brittany Hosea-Small

Research Bio

Jack Gallant is a cognitive neuroscientist whose research investigates how the brain represents and processes naturalistic information. He is best known for developing computational models that decode brain activity to reveal how sensory and cognitive information is encoded in the cerbral cortex. Gallant’s research integrates neuroimaging, computational neuroscience, and machine learning to map brain function during perception, language processing, and cognition. His work has advanced understanding of the neural basis of cognition and inspired new methods in brain-computer interfaces and AI.

He is Chancellor’s Professor of Psychology and Neuroscience at UC Berkeley, and co-director of the Henry H. Wheeler Brain Imaging Center. His research has been published in Nature, Science, and Neuron, and it is featured routinely in popular newspapers and magazines. At Berkeley, he teaches systems neuroscience and computational modeling, mentoring graduate students in the areas of neuroimaging, computational modeling of the brain, brain decoding and cognitive neuroscience.

Research Expertise and Interest

computational neuroscience, vision science, attention, fMRI, language, natural scene perception, brain encoding, brain decoding

In the News

New video shows reconstruction of 'brain movies'

UC Berkeley scientists Jack Gallant and Shinji Nishimoto have wowed the world by using brain scans and computer modeling to reconstruct images of what we see when we’re watching movies. UC Berkeley broadcast manager Roxanne Makasdjian has produced a video of how they achieved this breakthrough, and where they’re headed.

Scientists use brain imaging to reveal the movies in our mind

Imagine tapping into the mind of a coma patient, or watching one’s own dream on YouTube. With a cutting-edge blend of brain imaging and computer simulation, UC Berkeley scientists are bringing these futuristic scenarios within reach. Using functional Magnetic Resonance Imaging (fMRI) and computational models, researchers have succeeded in decoding and reconstructing people’s dynamic visual experiences – in this case, watching Hollywood movie trailers.

Teaching

Courses taught during the three most recent terms
2026 Spring
  • Supervised Independent Study  [COMPSCI 199]  

  • Senior Research Thesis  [NEU 191]  

  • Supervised Independent Study  [NEU 199]  

  • Seminars  [NEU 290]  

  • Neuroscience Graduate Research  [NEU 292]  

  • Neuroscience Research Review  [NEU 295]  

  • Supervised Independent Study  [NEU 99]  

  • Honors Research Thesis  [NEU H196A]  

  • Honors Research Thesis  [NEU H196B]  

  • Directed Study  [PSYCH 298]  

  • Research  [PSYCH 299]  

  • Supervised Independent Study and Research  [PSYCH 99]  

  • Research in Vision Science  [VISSCI 299]  

2025 Fall
  • Supervised Independent Study  [COMPSCI 199]  

  • Cognitive Neuroscience  [NEU 128]  

  • Senior Research Thesis  [NEU 191]  

  • Supervised Independent Study  [NEU 199]  

  • Functional MRI Methods  [NEU 271]  

  • Neuroscience Graduate Research  [NEU 292]  

  • Neuroscience Research Review  [NEU 295]  

  • Supervised Independent Study  [NEU 99]  

  • Honors Research Thesis  [NEU H196A]  

  • Honors Research Thesis  [NEU H196B]  

  • Field Study in Psychology  [PSYCH 197]  

  • Supervised Independent Study and Research  [PSYCH 199]  

  • Directed Study  [PSYCH 298]  

  • Research  [PSYCH 299]  

  • Supervised Independent Study and Research  [PSYCH 99]  

  • Research in Vision Science  [VISSCI 299]  

2025 Spring
  • Supervised Independent Study  [COMPSCI 199]  

  • Senior Honors Thesis Research  [COMPSCI H196B]  

  • Supervised Independent Study  [NEU 199]  

  • Neuroscience Graduate Research  [NEU 292]  

  • Neuroscience Research Review  [NEU 295]  

  • Supervised Independent Study  [NEU 99]  

  • Honors Research Thesis  [NEU H196A]  

  • Honors Research Thesis  [NEU H196B]  

  • Directed Study  [PSYCH 298]  

  • Research  [PSYCH 299]  

  • Supervised Independent Study and Research  [PSYCH 99]  

  • Research in Vision Science  [VISSCI 299]