Mission Statement

This journal club aims to provide a forum for discussing neurons, brains, and behavior among people with diverse quantitative and neurobiology backgrounds. Weekly meetings will focus on a paper relevant to a theoretical understanding of some neuroscientific problem or system. Graduate students and postdocs are especially encouraged to attend and propose/present papers. Appropriate papers present neural data, theoretical models, foundational principles for computation, new statistical, mathematical, or machine learning methods, etc.

Time & Place

Wednesdays @ 1pm

NHB 4.202.


If you’d like to be added to the email list or sign up to present, please contact Rishidev Chaudhuri (rchaudhuri [at] austin   [dot] utexas [dot] edu).


Date Presenter and readers Reading

Rishidev Chaudhuri


Murray JD, et al. (2017). Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex. PNAS 114. [PDF]


Tzuhsuan Ma

Bradde S & Bialek W. (2016). PCA meets RG arXiv:1610.09733


03.08.2017  Kim Houck Lillicrap T, et al. (2016). Random synaptic feedback weights support error backpropagation for deep learning.
03.15.2017  Spring break  
03.22.2017  Ingmar Kanitscheider

Zhang C, et al. (2016). Understanding deep learning requires rethinking generalization. [arXiv:1611.03530]

03.29.2017 Canceled  
04.05.2017 Andrei Khilkevich  Litwin-Kumar A, et al. (2017). Optimal degrees of synaptic connectivity. Neuron 93. [PDF]
04.12.2017 Brian Gereke  
04.19.2017  Berk Gercek






05.10.2017  Julie Charlton