Theory & Data Analysis Tools

Decision making is a fundamental cognitive process, and many decisions are based on gradually accumulated evidence. Thus, it is critical to understand the mechanistic basis underlying this accumulation process. Traditional models of evidence accumulation are based on low-dimensional attractors where individual neurons show ramping activity throughout a trial. However, an increasing number of studies have observed choice-selective sequences in their neural recordings, in which neurons fire transiently and sequentially with the subset of neurons that fires indicative of the animal’s choice.

PROJECT SUMMARY Animals can exhibit goal-directed behaviors in novel environments, despite limited experience with them. How does the brain make and use inferences about the underlying statistics and generative structure of environments to guide behavior? The field of reinforcement learning refers to this capacity as “model-based” reasoning, meaning that it relies on an internal model of the structure of the world. Critically, this internal model can be used to flexibly estimate the best actions by mental simulation or planning, without direct experience.

TITLE: IDENTIFYING THE NEURAL MECHANISMS OF GOAL-DIRECTED DECISION-MAKING IN PARKINSON’S DISEASE USING CLOSED-LOOP DEEP BRAIN STIMULATION PROJECT SUMMARY People with Parkinson’s disease commonly suffer from non-motor symptoms, including motivation deficits, that impact quality of life more than classical

Electrophysiology is a critical technology in neuroscience as a direct measure of neuronal functions. It has become routine for scientists to record and stimulate neuron populations in different brain regions in awake behaving animals, correlating activity with behavior. However, it has been insurmountable for the same electrophysiology to perform well in the spinal cord of behaving animals.

Project Summary Aggression is an evolutionarily conserved behavior that controls social hierarchies and protects valuable resources like mates, food, and territory. In most cases, aggression is a necessary, adaptive component of social behavior. In humans, however, some forms of aggression are considered pathological when they threaten lives, increase the risk of psychiatric impairment in victims, and incur economic burdens on society. Considerable evidence indicates that aggression is associated with aberrant facial perception in humans.

Project Summary/Abstract Mental disorders that affect the hippocampus disrupt people’s ability to form one-shot memories. My goal is to lead an independent lab, linking biological properties of hippocampal neurons to the ability to perform memory- guided cognitive behaviors. To map cognitive behaviors to their underlying neural mechanisms, my lab will perform theoretical analyses and simulation of state-space models of cognitive behaviors, implementing these models in a recurrent network architecture with learning rules that match biological plasticity rules (Aims 3a, c).

Summary The goal of this proposal is to develop DDALAB, a software platform that will make it possible for researchers to identify latent cortical states and analyze the flow of information in large populations of neurons using Delay Differential Analysis (DDA). Although DDA can be used to analyze any time series data, we will initially focus on EEG recordings from the scalp and iEEG data recordings directly from the brain.

PROJECT SUMMARY / ABSTRACT The BRAIN Initiative’s -omics data archive NeMO contains all the BICCN single cell single cell data, more than one million files at the time of writing.

cloudSLEAP – PROJECT SUMMARY/ABSTRACT Understanding how the brain produces complex behavior is a central goal of neuroscience, but quantifying behavior is technically challenging, particularly in unrestrained and naturalistic settings. Tools that are able to overcome these limitations leverage deep learning to achieve robust markerless motion capture, enabling characterization of behavior through precise positional tracking of body parts from standard videos of behavior.

Summary: Behavioral data is central to biomedical research, including both synchronous measures (e.g. brain activation and button-presses from a reading task in an fMRI scan), and those performed independently (e.g. a literacy questionnaire.) Compared to neurophysiology and brain imaging data, behavioral data is often relatively small, with file sizes in the megabytes rather than terabytes for both experimental scripts and resulting datasets.