Aina Puce - US grants

[unreadable] DESCRIPTION (provided by applicant): The research program in this application is concerned with the neural basis of social cognition. We propose to examine neocortical areas in and near the superior temporal sulcus (STS), a region known for its ability to process the motion of living forms, integrate information from different sense modalities, and respond to agency and perspective taking. The STS region together with the amygdala, several parts of the frontal lobe, and other brain areas are thought to form a brain network dealing with social cognition. We propose to study the neural mechanisms of basic social cognition in humans and macaques by recording unisensory and multisensory responses elicited to social and non-social stimuli. We will study cross-species neural responses to visual, auditory and combined audiovisual stimulation. Apparent motion activation tasks depicting combined facial expressions and associated non-verbal vocalizations will be studied. We will use identical activation tasks to collect neurophysiological and neuroimaging data in human and macaque subjects. Event-related potential (ERP) recordings provide information with excellent time resolution - to millisecond precision, whereas neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), provide accurate spatial information -to millimeter resolution. Combined fMRI and ERP measures in humans will provide an accurate picture of the brain circuits and temporal dynamics of social cognition. Under the identical experimental conditions, combined ERP and action potential recordings in macaques will identify the neuron populations and cellular processes indexed by the ERP measurements. Understanding how the healthy primate brain processes social information is important to understanding the biological bases for the social communication disorders (e.g. Asperger's syndrome, autism, schizophrenia), where severe impairments occur in reading social information from others. By using the same activation tasks and comparable methods in humans and monkeys we will be able to determine important similarities as well as differences in how the brain deals with relevant social information. Further, our multi-technique approach within each species will allow us to visualize where and when the brain activation manifests in the monkey and human brain. [unreadable] [unreadable] [unreadable]

This data sharing proposal between existing collaborators in the USA and France will expand the functionality and also user base of a cloud-based computing platform [brainlife.io] devoted to the storage, curation, analysis, sharing and publication of neuroimaging data. Currently, users of brainlife.io interact and analyze magnetic resonance imaging [MRI] based data on the platform, which is capable of very sophisticated analyses of brain structure and function. Here, our specific goal is to expand the capabilities of this platform to handle human neurophysiological data for the first time ? specifically magneto- encephalographic and electroencephalographic [MEEG] data. The high temporal resolution of MEEG data significantly enhances studies of brain function in ways that MRI-based brain activity data cannot. By adding MEEG data to brainlife.io we believe that we can offer the neuroimaging community a unique open science and data sharing resource that will accelerate scientific discovery in computational, systems, cognitive and social neuroscience. Why? We plan to implement data analysis ?Apps? on brainlife.io that will allow users to perform sophisticated analyses, e.g. structural and functional connectivity ? allowing brain networks to be better studied by integrating MEEG and MRI-based data. We will implement MEEG ?Apps? using 2 widely-used open source MEEG software suites ? FieldTrip [MATLAB-based] and MNE Python [Python-based]. We have the endorsement of the developers of these software packages and, importantly, the expertise within our team to expand the functionality of brainlife.io. We will also make use of our scientific expertise ? proposing 4 projects that will also make scientific gains in the fields of computational, systems and cognitive-social neuroscience. Specific Aim 1 [Project 1] presents basic MEEG preprocessing and processing methods, targeting new users of brainlife.io. Specific Aim 2 [Project 2] provides simulation tools for evaluating the required statistical power in a MEG experiment prior to running the study ? benefitting both entry-level and sophisticated users. Specific Aim 3 [Project 3] provides tools for source modelling of MEEG data, as well as providing multimodal datasets in single subjects [from the PI and 3 Co- PIs] who will be studied in both the USA and French laboratories. Finally, Specific Aim 4 [Project 4] integrates MEEG data with white matter tracts data in the human brain [based on structural MRI and diffusion weighting imaging [DWI] data]. This integrative analysis has been generated using our existing collaboration. Specific Aims 3 and 4 target more mid-level and experienced MEEG scientists. RELEVANCE (See instructions): The development and integration of neuroimaging tools across MEEG and MRI-based techniques such as in this project will directly aid the integrated study of brain functional and structural connectivity across multiple imaging modalities. This is the next step to developing viable in vivo models of both healthy and diseased brain function ? an essential step for preventing, detecting and treating diseases of the central nervous system.