collaborators

5 papers

q-bio.NC2025

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…

q-bio.NC2025

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…

q-bio.NC2025

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…

q-bio.NC2024

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…

stat.ML2024

What Representational Similarity Measures Imply about Decodable Information

Sarah E. Harvey, David Lipshutz, Alex H. Williams

Neural responses encode information that is useful for a variety of downstream tasks. A common approach to understand these systems is to build regression models or ``decoders'' th…