We read and discuss the latest papers in computational neuroscience. The hope is to generate new ideas, foster new collaborations, and keep up-to-date with the literature.
For the spring 2021 semester, we will have four themes (3 weeks per theme). All meetings will be virtual (not recorded). The papers for each theme have been pre-selected to match PNI's interests. The papers reflect authors from a diverse set of backgrounds and from outside of PNI in order to encourage a breadth of perspective.
We encourage participants to spend at least 20 minutes with each paper before coming to club.
If you’d like to be added to the email list, visit our google group, or contact Ben (bcowley [at] princeton.edu) or Iris (istone [at] princeton.edu). If you'd like to present, please also contact Ben and Iris.
Let’s make our journal club the envy of PNI! Please read the paper before choosing, plan for 35 minutes of presenting (expect plenty of questions!), and follow these tips: presentation_checklist.pdf
We use a recurring Zoom link. You can find the Zoom link in our e-mails. If you need the Zoom link, please join our mailing list or contact Ben or Iris.
Current Meetings (Spring 2021)
Special club for PNI Recruitment
|Feb 19||11:30am-12:30pm||David Zoltowski|| Decoding and perturbing decision states in real time.
Peixoto, Verhein, Kiani, ..., Ryu, Shenoy, Newsome (Nature 2021)
Theme 1: Understanding multi-area interactions
|Mar 3||3-4pm||Ben Cowley|| Principles of Corticocortical Communication: Proposed Schemes and Design Considerations.
Kohn, Jasper, Semedo, Gokcen, Machens, Yu (Trends in Neuro 2020)
Statistical methods for dissecting interactions between brain areas.
Semedo, Gokcen, Machens, Kohn, Yu (Current Op in Neuro 2020)
|Mar 10||3-4pm||Rich Pang|| Inferring brain-wide interactions using data-constrained recurrent neural network models.
Perich, Arlt, Soares, ..., Rudebeck, Harvey, Rajan (bioRxiv 2020)
|Mar 17||3-4pm||Orren Karniol-Tambour|| Brain-wide electrical spatiotemporal dynamics encode depression vulnerability.
Hultman, Ulrich, Sachs, ..., Nestler, Carin, Dzirasa (Cell 2018)
Theme 2: Neuroethology: Understanding computation through behavior
|Apr 6||3-4pm||Jess Breda|| Computational neuroethology: a call to action.
Datta, Anderson, Branson, Perona, Leifer (Neuron 2019)
|Apr 13||3-4pm||Jorge Yanar|| Continuous Whole-Body 3D Kinematic recordings across the rodent behavioral repertoire.
Marshall, Aldarondo, Dunn, Wang, Berman, Olveczky (Neuron 2020)
|Apr 20||3-4pm||Iris Stone|| A cortical-hypothalamic circuit decodes social rank and promotes dominance behavior.
Padilla-Coreano, Batra, Patarino, ..., Fiete, Lu, Tye (ResearchSquare 2020)
AlphaTracker: A multi-animal tracking and behavioral analysis tool.
Chen, Zhang, Zhang, ..., Tye, Lu (bioRxiv 2020)
Theme 3: The curious computations of dopamine
|May 6||4-5pm||Rachel Lee|| Neural circuitry of reward prediction error.
Watabe-Uchida, Eshel, Uchida (Ann. Review of Neuro. 2017)
|May 13||4-5pm||Sreejan Kumar|| Evidence for a neural law of effect.
Athalye, Santos, Carmena, Costa (Science 2018)
|May 20||4-5pm||Yoel Sanchez Araujo|| Dopamine enhances signal-to-noise ratio in cortical-brainstem encoding of aversive stimuli.
Vander Weele, Siciliano, Gillian, ..., Wichmann, Wildes, Tye (Nature 2018)
Theme 4: Recording from more neurons than we know what to do with
|June 9||3-4pm||Aditi Jha|| Towards the neural population doctrine.
Saxena and Cunningham (Current Opinion in Neuro. 2019)
|June 16||3-4pm||Daniel Greenidge|| A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex.
de Vries, Lecoq, Buice, ..., Phillips, Reid, Koch (Nat Neuro 2020)
|June 23||3-4pm||Eleni Papadoyannis|| Distributed coding of choice, action and engagement across the mouse brain.
Steinmetz, Zatka-Haas, Carandini, Harris (Nature 2019)
Past Meetings (Fall 2020)
|Jan 30||4-5pm, PNI 230||David Zoltowski||
Stimulus-choice (mis)alignment in primate MT cortex.
Zhao, Yates, Levi, Huk, Park (bioRxiv 2019)
|Feb 6||3-4pm, PNI 130||Zoë Ashwood||
Computational noise in reward-guided learning drives behavioral variability in volatile environments.
Findling, Skvortsova, Dromnelle, Palminteri, Wyart. (Nat Neuro 2019)
|Feb 13||3-4pm, PNI 130||Daniel Greenidge||
Structure in neural population recordings: an expected byproduct of simpler phenomena?
Elsayed and Cunningham. (Nat Neuro 2017)
|Feb 20||11am-12pm, Psych 404||Brian DePasquale||
Engineering recurrent neural networks from task-relevant manifolds and dynamics.
Pollock and Jazayeri. (bioRxiv 2019)
|Feb 27||No club -- COSYNE|
|Mar 5||No club -- Unfilled slot|
|Mar 12||Virtual||Lindsay Willmore||
Deep neuroethology of a virtual rodent.
Merel, Aldarondo, Marshall, Tassa, Wayne, Olveczky. (arXiv 2019)
Past Meetings (Fall 2019)
|Oct 24||Ben Cowley||
High-dimensional geometry of population responses in visual cortex.
Stringer, Pachitariu, Steinmetz, Carandini, Harris. (Nature 2019)
|Oct 31||(not meeting)||
A spooky paper
Fox (Ann. Reviews 1975)
|Nov 7||Ben Cowley||
What makes a good scientific figure?
|Nov 14||Matt Creamer||
Hierarchical recurrent state space models reveal discrete and continuous dynamics of neural activity in C. elegans
Linderman, Nichols, Blei, Zimmer, Paninski. (bioRxiv 2019)
|Nov 21||Sean Bittner (visitor)||
Interrogating theoretical models of neural computation with deep inference
Bittner, Agostina Palmigiano, Piet, Duan, Brody, Miller, Cunningham. (bioRxiv, 2019)
|Dec 5||Matt Panichello||
Bayesian computation through cortical latent dynamics
Sohn, Narain, Meirhaeghe, Jazayeri (Neuron 2019)
|Dec 12||No journal club (PNI holiday party)|
|Dec 19||Kevin Chen||
A quantitative model of conserved macroscopic dynamics predicts future motor commands
Brennan, Proekt. (eLife, 2019)
Past Meetings (Spring 2019)
Past Meetings (Fall 2018)
|Oct 25th, 3PM||Jonathan Pillow||
Efficient coding explains the universal law of generalization in human perception
Chris R. Sims (2018)
|Nov 1st||Anqi Wu||
Uncovering hidden brain state dynamics that regulate performance and decision-making during cognition
Taghia et al. (2018)
|Nov 8th||No Meeting, SFN|
|Nov 15th||Manuel Schottdorf||
Distributed network interactions and their emergence in developing neocortex
Smith et al. (2018)
|Nov 22nd||No Meeting, Thanksgiving|
|Nov 29th||Sue Ann Koay||
Shaping Neural Circuits by High Order Synaptic Interactions
Tannenbaum et al. (2018)
|Dec 6th||No Meeting, NIPS|
Past Meetings (Spring 2018)
Past Meetings (Fall 2017)
|Sep 26||Mike Morais||
Lawful relation between perceptual bias and discriminability
Wei & Stocker (2017)
|Oct 3||Alex Hyafil||
Attention stabilizes the shared gain of V4 populations
Rabinowitz et al. (2015)
|Oct 10||Jamal Williams||
Brains on Beats
Guclu et al. (2016)
|Oct 17||Adam Charles||
Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity
Koyluoglu, et al. eLife (2017)
|Oct 24||Adam Calhoun||
A brain wide circuit model of heat evoked swimming behavior in larval zebrafish
Haesemeyer et al. (2017)
|Oct 31||Michael Berry||
A Theory of Canonical Computations in the Neocortical Microcircuit
|Nov 28||Brian DePasquale||
Optimal degrees of synaptic connectivity
Litwin-Kumar et al. (2017)
Past Meetings (Summer 2017)
|Jun 22||Scott Linderman||
Using computational theory to constrain statistical models of neural data
Linderman & Gershman (2017)
Past Meetings (Spring 2017)
Past Meetings (Fall 2016)
Past Meetings (Summer 2016)
|Jun 14|| Athena Akrami & Adam Charles
Could a neuroscientist understand a
Jonas & Koerding. biorxiv (2016)
|Jun 23||Ben Machta||
Perspective: Sloppiness and Emergent Theories in Physics, Biology, and Beyond
Transtrum, Machta, Brown, Daniels, Myers, and Sethna. J. Chem. Phys. (2015)
|Jun 30||Ahmed Hl Hady||
Cell Types, Network Homeostasis, and Pathological Compensation from a Biologically Plausible Ion Channel Expression Model
O’Leary, Williams, Franci, and Marder. Neuron (2014)
|Jul 7||Leenoy Meshulam||
Sloppiness in Spontaneously Active Neuronal Networks
Panas1, Amin, Maccione, Muthmann1, van Rossum, Berdondini, and Hennig. J. Neurosci. (2015)
|Jul 21||Adam Charles||Assessing the distinguishability of models and the informativeness of data Navarro et al. Cognitive Psychology (2004)|
|Aug 23||Ido Kanter||Low-firing rates, cortical oscillations and neuronal ?s precision stem from neuronal plasticity: Experiment and theory|
|Sep 13||Yonatan Aljadeff||Optimal population coding by mixed-dimensionality neurons|
Past Meetings (Fall-Spring 2015-16)
|Nov 24||Jonathan Pillow
Inferring learning rules from distributions of firing rates in cortical neurons|
Lim, McKee, Woloszyn, Amit, Freedman, Sheinberg, & Brunel.
Nature Neuroscience (2015). [summary]
|Dec 1||Adam Calhoun|| Global Brain Dynamics Embed the Motor Command Sequence of Caenorhabditis elegans.|
Kato, Kaplan, Schrödel, Skora, Lindsay, Yemini, Lockery, & Zimmer.
|Dec 8|| Mark Ioffe
readers: Alex Piet & DJ Strouse
thesaurus for a neural population
Ganmor, Segev, & Schneidman. eLife (2015).
|Dec 15|| DJ Strouse
readers: Mark Ioffe & Mingbo Cai
Bayesian observer model constrained by
efficient coding can explain 'anti-Bayesian'
Wei & Stocker, Nat Neurosci (2015).
|Jan 19|| Mikio Aoi
readers: Adam Calhoun & Jonathan Pillow.
|Cortical activity in the null space: permitting preparation without movement. Kaufman, Churchland, Ryu, & Shenoy, Nat Neurosci 2014.|
| Sina Tafazoli
readers: Adam Charles & Mikio Aoi
|A neural network that finds a naturalistic solution for the production of muscle activity. Sussillo, Churchland, Kaufman, & Shenoy, Nat Neurosci 2015|
|Feb 2|| Mingbo Cai
readers: Becket Ebitz & Nick Roy
|Human representation of visuo-motor uncertainty as mixtures of orthogonal basis distributions. Zhang, Daw, Maloney, Nat Neurosci 2015.|
|Feb 9|| Angela Langdon
readers: Jane Keung, Diksha Gupta, Tyler Boyd-Meredith
|A neural mechanism for sensing and reproducing a time interval. Jazayeri & Shadlen, Current Biology 2015.|
|Feb 23|| Nick Roy
reader: Lea Duncker
|The nature of shared cortical variability. Lin, Okun, Carandini, & Harris, Neuron 2015.|
|Mar 1||( cosyne workshops)|
|Mar 8|| Diksha Gupta
reader: Tyler Boyd-Meredith
|The Inevitability of Probability: Probabilistic Inference in Generic Neural Networks Trained with Non-Probabilistic Feedback A. Emin Orhan & Wei Ji Ma. arxiv 2016.|
|Mar 15||( spring break )|
|Mar 29|| Sam Lewallen
reader: Ahmed El Hady
|Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex. Schottdorf, Wolfgang Keil, Coppola, White, & Wolf. PloS Comp Bio 2015.|
|Apr 5||Adam Charles||Neuronal Circuits Underlying Persistent Representations Despite Time Varying Activity. Druckmann & Chklovskii, Current Biol (2012). [blog summary]|
|Apr 12|| Anqi Wu
readers: Mikio & Nick
|Sensory uncertainty decoded from visual cortex predicts behavior. Bergen, Ma, Pratte, & Jehee, Nat Neurosci (2015).|
|Apr 19|| David Deutsch
readers: Diksha & Jonathan
|Active sensing in the categorization of visual patterns. Yang, Lengyel, & Wolpert. eLIFE 2016.|
|Apr 26|| Lea Duncker
readers: Adam Charles, Matt Panichello
Robust neuronal dynamics in premotor cortex during motor planning.
Li, Daie, Svoboda, & Druckmann. Nature (2016).
|May 3|| Alex Piet
readers: Angela Langdon & Sam Lewallen
Robust timing and motor patterns by taming chaos in
recurrent neural networks.
Rodrigo Laje & Dean V Buonomano, Nature Neurosci (2013).
|May 10|| Tyler Boyd-Meredith
readers: Angela L and Alex P
Cortex Is Required for Optimal Waiting Based
on Decision Confidence.
Lak, Costa, Romberg, Koulakov, Mainen, & Kepecs, Neuron (2014).
Past Meetings (Summer 2015)
|Topic #1: Information theory and the brain (Adam Calhoun)|
|June 9||Jonathan Pillow
|June 16||Adam Calhoun
|June 23||Chris Baldassano||
|June 30||Ida Momennejad||
|Topic #2: Neural Codes in Noisy Cortical Circuits (Alex Piet & Ahmed El Hady)|
|July 14||Leenoy Meshulam||
|July 21||Alex Piet||
|July 28||Sam Lewallen||
|Aug 4||Athena Akrami||
|Aug 11||Ahmed El Hady||
|Aug 18||Sam Lewallen||
Past Meetings (Spring 2015)
|Date||Presenter and readers||Reading|
|Mar 18||Jonathan Pillow
readers: Jason P. & Jamal W.
Goris, Movshon & Simoncelli Nature Neurosci (2014).
|Apr 01|| Michael Berry
readers: Angela L. & Sam L.
coding of dynamical variables in balanced spiking
Boerlin, Machens & Deneve, PLoS Comp Biol (2013).
|Apr 08||DJ Strouse
readers: Jonathan P. & Adam C.
information in a sensory population.
Palmer, Marre, Berry, & Bialek. arXiv:1307.0225
|Apr 15|| Mikio Aoi
readers: Alex P. & Ashley L.
Neural constraints on learning. Sadtler, Quick,
Golub, Chase, Ru, Tyler-Kabara, Yu & Batista.
|Apr 22|| Adrianna Loback
readers: Jonathan P. & DJ S.
|A Simple Model of Optimal Population Coding for Sensory Systems. Doi & Lewicki, PLOS Comp. Biol. (2014)|
|Apr 29|| Chris Baldassano
readers: Jamal W. & Ida M.
|Human-level control through deep reinforcement learning. Mnih et al, Nature (2015).|
|May 06|| Sam Lewallen
reader: Stephanie Chan
|Performance-optimized hierarchical models predict neural responses in higher visual cortex", Yamins, Hong, Cadieu, Solomon, Seibert, & DiCarlo, PNAS (2014).|
|May 13|| Jane Keung
readers: Alex Piet & Mikio Aoi
|Signals in inferotemporal and perirhinal cortex suggest an untangling of visual target information. Pagan, Urban, Wohl, & Rust, Nature Neurosci (2013).|