44 citations · 181 across the 20 of their papers we have counts for
8 papers · 1 filter
Reduced rank regression for neural communication: a tutorial for neuroscientists
Bichan Wu, Jonathan Pillow
Reduced rank regression (RRR) is a statistical method for finding a low-dimensional linear mapping between a set of high-dimensional inputs and outputs. In recent years, RRR has fo…
State-switching navigation strategies in C. elegans are beneficial for chemotaxis
Kevin S. Chen, Andrew M. Leifer, Jonathan W. Pillow
Animals employ different strategies for relating sensory input to behavioral output to navigate sensory environments, but what strategy to use, when to switch and why remain unclea…
Olfactory learning alters navigation strategies and behavioral variability in C. elegans
Kevin S. Chen, Anuj K. Sharma, Jonathan W. Pillow +1
Animals adjust their behavioral response to sensory input adaptively depending on past experiences. The flexible brain computation is crucial for survival and is of great interest…
Correcting motion induced fluorescence artifacts in two-channel neural imaging
Matthew S. Creamer, Kevin S. Chen, Andrew M. Leifer +1
Imaging neural activity in a behaving animal presents unique challenges in part because motion from an animal's movement creates artifacts in fluorescence intensity time-series tha…
Probing the relationship between linear dynamical systems and low-rank recurrent neural network models
Adrian Valente, Srdjan Ostojic, Jonathan Pillow
A large body of work has suggested that neural populations exhibit low-dimensional dynamics during behavior. However, there are a variety of different approaches for modeling low-d…
Unifying and generalizing models of neural dynamics during decision-making
David M. Zoltowski, Jonathan W. Pillow, Scott W. Linderman
An open question in systems and computational neuroscience is how neural circuits accumulate evidence towards a decision. Fitting models of decision-making theory to neural activit…
Capturing the dynamical repertoire of single neurons with generalized linear models
Alison I. Weber, Jonathan W. Pillow
A key problem in computational neuroscience is to find simple, tractable models that are nevertheless flexible enough to capture the response properties of real neurons. Here we ex…
The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction
Ross S. Williamson, Maneesh Sahani, Jonathan W. Pillow
Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular m…