Colloquium Series 2019-2019

Colloquium Series 2019-2019

Colloquia are generally on Tuesdays at 3:30 p.m., once per month. They are usually held in E5-6111 (exceptions will be noted). Abstracts are posted as available. If you'd like to be on the mailing list announcing these events, please sign up here.

Here is a list of our upcoming speakers for the 2019 and 2020 academic year:

September 17, 2019 - Mayzar Fallah

October 8, 2019 - Wilten Nicola

November 20, 2019 - Xaq Pitkow

November 26, 2019 - Morris Moscovitch

January 25, 2020 - Randy McIntosh

Tuesday, September 27, 2019 - 3:30 pm
EC5, 2004

Mayzar Fallah
York University

Cortical Interactions in the Oculomotor System

Abstract: 
Previous neurophysiological studies have demonstrated that saccade curvatures are the result of excitatory and competitive interactions between potential saccade goals in the intermediate layers of the superior colliculus (SCi) and frontal eye field (FEF), whereby the resulting saccade curvature is proportional to the level of unresolved activity encoding a competing saccade vector. This suggests that the magnitudes of saccade curvature vary continuously along a gradient of oculomotor excitation and inhibition. Given that top-down factors like task relevance are encoded by the visuomotor neurons of the oculomotor system (reviewed by Fecteau & Munoz, 2006), this predicts a functional relationship between saccade curvature and cortical visual processing. I will be presenting a series of studies that investigates the featural and temporal factors affecting saccadic encoding, as measured by saccade curvatures. These studies provide increasing evidence that visual processing can be read out of saccade metrics.

Tuesday, October 8, 2019 - 3:30pm
E5 - 2004

Wilten Nicola
University of Calgary

Fast, Compressible Learning in the Hippocampus using Interneuron Sequences

Abstract:
The hippocampus is able to rapidly learn incoming information, even if that information is only observed once. Furthermore, this information can be replayed in a compressed format in either forward or reverse modes during sharp wave–ripples (SPW–Rs). We leveraged state-of-the-art techniques in training recurrent spiking networks to demonstrate how primarily interneuron networks can achieve the following: (1) generate internal theta sequences to bind externally elicited spikes in the presence of inhibition from the medial septum; (2) compress learned spike sequences in the form of a SPW–R when septal inhibition is removed; (3) generate and refine high-frequency assemblies during SPW–R-mediated compression; and (4) regulate the inter-SPW interval timing between SPW–Rs in ripple clusters. From the fast timescale of neurons to the slow timescale of behaviors, interneuron networks serve as the scaffolding for one-shot learning by replaying, reversing, refining, and regulating spike sequences.

Wednesday, November 20, 2019 - 3:30 pm
E7, 7363

Xaq Pitkow
Rice University 

Rational Thoughts in Neural Codes

Abstract:
Complex behaviors are often driven by an internal model, which integrates sensory information over time and facilitates long-term planning to reach subjective goals. We interpret behavioral data by assuming an agent behaves rationally — that is, they take actions that optimize their subjective reward according to their understanding of the task and its relevant causal variables. We apply a new method, Inverse Rational Control (IRC), to learn an agent’s internal model and reward function by maximizing the likelihood of its measured sensory observations and actions. This thereby extracts rational and interpretable thoughts of the agent from its behavior. We also provide a framework for interpreting encoding, recoding and decoding of neural data in light of this rational model for behavior. When applied to behavioral and neural data from simulated agents performing suboptimally on a naturalistic foraging task, this method successfully recovers their internal model and reward function, as well as the computational dynamics within the neural manifold that represents the task. This work lays a foundation for discovering how the brain represents and computes with dynamic beliefs.

Tuesday, November 26, 2019 - 3:30 pm

Morris Moscovitch
University of Toronto

The Cognitive Neuroscience of Recent Remote Event and Spatial Memory

Abstract:
Memories are dynamic and interactive. Their representations are influenced by time and experience. I will present evidence on the nature of the changing representations and their neural correlates, show how event and spatial memory interact with one another,  and propose a neurocognitive model of hippocampal-neocortical interactions that may account for the evidence.

Tuesday, January 21, 2020 - 3:30 pm

Randy McIntosh
Baycrest Centre

Flow and Manifolds in Cognition and Neural Networks

Abstract:
Our experience is elaborate, where our perceptions are embellished by memories and emotions, and driven by predictions. We have developed a quantitative framework that makes the explicit link between the elaborate temporal evolution of the brain networks and the accompanying evolution of the mental streams. We posit that the coordination underlying experience can be understood by considering neural processes as flows depicting system interactions. The flows occur on relatively low-dimensional manifolds, which constrain the landscape of possible functional configurations – Structured Flows on Manifolds (SFM). The attraction of the SFM framework is that the same mathematical formulation can be used to quantify the flows and manifolds for the cognitive architecture as for the neural dynamics. The potential for new configurations reflects the adaptive nature of the brain and higher cognitive function. This “hidden repertoire” is at the heart of what makes our experiences special, where the richness comes precisely because of what is happening and also of what possibly could happen.