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Terrence J. Sejnowski

Computational Neurobiology Laboratory, Salk Institute / UC San Diego

Functionalist What matters is the organisation of the processing, not the material

Terrence J. Sejnowski is the Francis Crick Chair and Professor at the Salk Institute for Biological Studies and Distinguished Professor of Neurobiology at the University of California, San Diego. He is one of the foundational pioneers of computational neuroscience, connectionism, and machine learning, and a member of all three US National Academies (Sciences, Engineering, and Medicine).

In the 1980s, Sejnowski co-invented the Boltzmann machine and NETtalk with Geoffrey Hinton, demonstrating that distributed neural networks could learn complex statistical representations. In The Computational Brain (MIT Press, 1992, with Patricia Churchland) and The Deep Learning Revolution (MIT Press, 2018), he formalized the computational principles governing cortical oscillations, spike-timing-dependent plasticity, and sleep-dependent synaptic consolidation.

Sejnowski’s research bridges artificial neural network scaling with biological cortical microcircuits, arguing that higher-order cognitive flexibility and conscious deliberation emerge from the coordinated interaction of recurrent feedback connections, thalamocortical loops, and continuous predictive temporal coding.

He is a co-author of the wave papers that anchor the traveling-wave literature. His name appears on the Davis Nature 2020 study showing wave phase gating perception in behaving primates, on the 2021 Nature Communications paper where waves emerge from horizontal fiber time delays in spiking models, and on the 2018 Nature Reviews Neuroscience review that framed the field (the site’s analysis of the 2026 review). The experimental lead on those recordings is Zachary Davis (his profile), and the review’s senior voice is Lyle Muller (his profile).

Known for. Co-inventor of the Boltzmann Machine, The Computational Brain (1992), Independent Component Analysis (ICA), The Deep Learning Revolution (MIT Press, 2018)

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