Monitor Neural Activity

ABSTRACT The non-human primate (NHP) model is critical to the advancement of translational neuroscience, as it allows researchers to link observations regarding macroscale brain dynamics and cognition in the human to underlying meso- and microscale phenomena that cannot be fully investigated in humans. Importantly, the ultimate value of findings from the NHP for informing human models relies on the adequacy of methods for cross-species anatomical and functional alignment.

SUMMARY Brain-mapping initiatives are acquiring increasingly large and comprehensive neuroimaging and multiomic— e.g. genomic and transcriptomic—datasets. Existing analyses of such data in human neuroscience tend to search for links between cognition, behavior or disease on the one hand, and properties of genomes, transcrip- tomes or brain morphology and connectivity on the other. Such valuable analyses have steadily advanced our knowledge of human brain function.

PROJECT SUMMARY/ABSTRACT The growing availability of large functional magnetic resonance imaging (fMRI) datasets has enabled new investigations into functional systems of the human brain. A challenge – but also opportunity – of fMRI arises from the fact that BOLD signal stems from multiple intertwined neural and physiological sources. One major contributor to fMRI signals arises from slow (

This two-year project will advance, integrate, document, and promote the use of the Hierarchical Event Descriptor (HED) system to describe events in human neuroimaging and behavioral data from research experiments and other sources in sufficient detail to support comparative analysis of human brain dynamics across studies. Relating the recorded data dynamics to temporally- specifiable changes in subject experience, action, and cognition is a major goal (and challenge) for both neuroimaging and biomechanical imaging.

ABSTRACT Eating disorders are severe psychiatric conditions with a significant worldwide cost and disability burden. Binge eating (BE) is a behavior that cuts across nearly all eating disorder diagnoses. Unfortunately, psychological treatments for eating disorders/BE are limited, and targeted biological/pharmacological treatments have not yet been effective. In order to develop more effective targeted treatments, it is critical to understand the neural circuit abnormalities that contribute to the onset, expression, and maintenance of BE.

PROJECT SUMMARY Machine-learning-based classification of neuroimaging data (hereafter ML-MRI) to predict clinical diagnoses has increased substantially in the last decade. Despite the promise of ML for clinical classification and prediction, no work has been done to anticipate the ethical obligations and challenges that emerge when ML algorithms predict clinical diagnoses in pre-symptomatic individuals.

Project Summary The mouse posterior parietal cortex (PPC) has emerged as an essential region for decision-making during memory-guided decision-making tasks. Neurons in the PPC typically respond selectively at a single point during a unique behavioral trial type; activity at the population level can be thought of as a choice-specific trajectory through state space.

Project Summary This project’s long-term goal is a fuller understanding of the neurobiological mechanisms of olfactory sensory adaptation that facilitate odor discrimination in the natural world. To confront the wide fluctuations in intensity and temporal variability that are characteristic of natural odor environments, animals have evolved refined neurosensory mechanisms for parsing behaviorally-relevant signals such as pheromones from background nuisance odors.

Project summary Understanding how neural circuits give rise to sensory computation and, ultimately, perception, requires connecting biological features of neural circuits to abstract models of neural computation. In vison, a model of the visual receptive field (RF) describes how a neuron's responses are determined by the visual inputs it encounters. The visual RF can also provide a compact description of a neuron's function, revealing which features of the external environment that neuron is responsible for encoding.

Project Summary A fundamental end-goal of brain-computer interfaces (BCI) is to enable communication in individuals with severe motor paralysis. BCIs decode the neural signals and accomplish the intended goal via an effector, such as a computer cursor or a robotic limb. The BCI user relies on the realtime feedback of the effector's performance to modulate their neural strategy to control the external device. To date, this feedback is predominantly visual.