More and More Neurons

Friday, February 24, 2023

9:30 am — 4:00 pm

Hybrid (see description for details)

Open to the Public

Center for the Physics of Biological Function symposium featuring guest speakers Braden Brinkman (Stony Brook University), Andrew Leifer (Princeton University), and Carsen Stringer (Janelia Research Campus, HHMI).

Admission Price



Please register here.


In-Person: CUNY Graduate Center, Skylight Room (9100)
Online: Via Zoom (link sent upon registration)


9:30 a.m. 


10:00 AM - 11:30 AM

Structure, Function, and Dynamics of the C. elegans Nervous System
Andrew Leifer, Princeton University

11:30 a.m.


12:00 p.m. - 1:30 p.m.

Making Sense of Large - Scale Neural and Behavioral Data
Carsen Stringer, Janelia Research Campus, HHMI

Advances in protein engineering and microscopy have enabled routine recordings of over 50,000 neurons simultaneously in the mouse cortex at a sampling rate of 3Hz, or ~8,000 neurons at a rate of 30Hz. What properties does this large-scale activity have? One popular hypothesis is that this neural activity is “simple” and low-dimensional, and we can summarize even 50,000 neuron recordings with just a few numbers at any one time. Many analytical tools and theories have been developed based on this assumption. However, in our large-scale recordings we found that neural responses to visual stimuli were high-dimensional, exploring many diverse patterns of activity that could not be reduced to a few numbers.  This high-dimensional structure that cannot be easily captured by existing data visualization methods. We therefore developed an embedding algorithm called Rastermap, which captures complex temporal and highly nonlinear relationships between neurons, and provides useful visualizations by assigning each neuron to a location in the embedding space. We found within neural datasets from virtual reality tasks unique subpopulations of neurons encoding abstract elements of decision-making, the environment and behavioral states. Further, we found that ongoing “spontaneous” activity in cortex was high-dimensional, representing the moment-to-moment behaviors of the mouse. To interrogate behavioral representations in the mouse brain, we developed the fast Facemap network for tracking 13 distinct points on the mouse face recorded from arbitrary camera angles. We used Facemap to find that the neuronal activity clusters which were highly driven by behaviors were more spatially spread-out across cortex. We also found that the deep keypoint features inferred by the model had time-asymmetrical state dynamics that were not apparent in the raw keypoint data. In summary, Facemap provides a stepping stone towards understanding the function of the brainwide neural signals and their relation to behavior.

1:30 p.m. - 2:30 p.m.


2:30 p.m. - 4:00 p.m.

Non-Perturbative Renormalization Group Analysis of Collective Behavior in Networks of Spiking Neurons
Braden Brinkman, Stony Brook University

The critical brain hypothesis posits that neural circuits may operate close to critical points of a phase transition, which has been argued to have functional benefits for neural computation. In physics, our modern understanding of the collective behavior that emerges near such phase transitions is provided by the renormalization group. However, the all-or-nothing nature of neural spikes transmitted across a web of synaptic connections make it difficult to apply the ideas of the renormalization group directly to models of leaky integrate-and-fire networks commonly used in neuroscience. In this talk I will discuss recent work adapting the non-perturbative renormalization group (NPRG) method to network models of stochastic spiking neurons, providing a means of investigating the nature of different types of collective behavior in neural circuitry. In particular, I will highlight possible differences between phase transitions in slice tissue and cortical networks.

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CUNY attendees must show proof of vaccination by presenting a valid CUNY Access Pass through the CLEARED4 health validation platform upon entry. Non-CUNY visitors will need to show proof of ID by presenting a valid government-issued photo document. See the full Building Entry Policy for more information.