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
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|
Murray JD, et al. (2017). Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex. PNAS 114. [PDF]
|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.
|04.05.2017||Andrei Khilkevich||Litwin-Kumar A, et al. (2017). Optimal degrees of synaptic connectivity. Neuron 93. [PDF]|