2023 Computational Neuroscience Next Generation Symposium
September 11, 2023
The Computational Neuroscience Next Generation (CNNG) Symposium @ WashU was held September 11, 2023. This event featured an exciting day of talks and poster presentations at the School of Medicine and Danforth campuses.
CNNG Symposium @ WashU is a prestigious symposium sponsored by the newly established Center for Theoretical and Computational Neuroscience (CTCN) at Washington University in St. Louis. Eight selected senior graduate students from the US and Europe, who are using primarily theoretical and computational techniques to study the principles of brain organization and function, come to WashU to share their thesis work, learn about WashU’s stellar research environment, and expand their scientific network.
Program of events
Moore Auditorium (Medical School North Building, adjacent to FLTC)
8:55 a.m.
Opening remarks
Geoff Goodhill, PhD
Professor of Neuroscience and Developmental Biology
Washington University
CTCN Director
9 a.m.
Complex computation from developmental priors
Daniel Barabasi
Biophysics PhD Program
Harvard University
Graduate advisor: Florian Engert
9:30 a.m.
The nature-nurture transform underlying the emergence of reliable cortical representations
Sigrid Trägenap
International Max-Planck Research School for Neural
Circuits
Graduate advisor: Matthias Kaschube
10 a.m.
Understanding the influences of context on efficient sensory coding
Gaia Tavoni, PhD
Assistant Professor, Department of Neuroscience
Washington University
10:15 a.m.
Tea break
10:45 a.m.
Flow-field inference from neural data using deep recurrent networks
Tim Kim
Neuroscience Program
Princeton Neuroscience Institute
Graduate advisor: Carlos Brody
11:15 a.m.
Large-scale neural state dynamics of ongoing cognition and attention
Hayoung Song
Integrative Neuroscience Program
Department of Psychology
University of Chicago
Graduate advisor: Monica D. Rosenberg
11:45 a.m.
Data-driven identification of multi-scale neural dynamics for understanding and enhancing cognitive function
ShiNung Ching, PhD
Associate Professor of Electrical & Systems Engineering
Washington University
12 p.m.
Lunch
1 p.m.
Predictive sequence learning in the hippocampal formation
Yusi Chen
Biology
University of California, San Diego
Graduate advisor: Terrence Sejnowski
1:30 p.m.
Cerebellar-driven strategies for brain-wide learning
Joseph Pemberton
Computational Neuroscience and Machine Learning
University of Bristol
Graduate advisor: Rui Ponte Costa
2 p.m.
Synaptic credit assignment in the octopus vertical lobe
Naoki Hiratani, PhD
Assistant Professor, Department of Neuroscience
Washington University
2:15 p.m.
Coffee break
2:45 p.m.
Geometry of neural representations for optimal inference
Jacob Zavatone-Veth
Department of Physics
Harvard University
Graduate advisor: Cengiz Pehlevan
3:15 p.m.
Task-driven neural network models predict neural dynamics of proprioception
Alessandro Marin-Vargas
Neuroscience
Ecole Polytechnique Fédérale de Lausanne (EPFL)
Graduate advisor: Alexander Mathis
4 p.m.
Train to Danforth Campus
Poster session in Forum at Hillman Hall on the Danforth Campus
4:30 – 6 p.m.
Poster session
Refreshments will be served.