3 citations · 8 across the 14 of their papers we have counts for
12 papers · 1 filter
Modeling Neural Activity with Conditionally Linear Dynamical Systems
Victor Geadah, Amin Nejatbakhsh, David Lipshutz +2
Neural population activity exhibits complex, nonlinear dynamics, varying in time, over trials, and across experimental conditions. Here, we develop Conditionally Linear Dynamical S…
Comparing noisy neural population dynamics using optimal transport distances
Amin Nejatbakhsh, Victor Geadah, Alex H. Williams +1
Biological and artificial neural systems form high-dimensional neural representations that underpin their computational capabilities. Methods for quantifying geometric similarity i…
Discriminating image representations with principal distortions
Jenelle Feather, David Lipshutz, Sarah E. Harvey +2
Image representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have st…
Shaping the distribution of neural responses with interneurons in a recurrent circuit model
David Lipshutz, Eero P. Simoncelli
Efficient coding theory posits that sensory circuits transform natural signals into neural representations that maximize information transmission subject to resource constraints. L…
Neuronal Temporal Filters as Normal Mode Extractors
Siavash Golkar, Jules Berman, David Lipshutz +3
To generate actions in the face of physiological delays, the brain must predict the future. Here we explore how prediction may lie at the core of brain function by considering a ne…
Adaptive whitening with fast gain modulation and slow synaptic plasticity
Lyndon R. Duong, Eero P. Simoncelli, Dmitri B. Chklovskii +1
Neurons in early sensory areas rapidly adapt to changing sensory statistics, both by normalizing the variance of their individual responses and by reducing correlations between the…