Speaker: Vivienne Chi, Brown University

Title: Human-Robot Trust during Interactive Teaching

Abstract: Building and maintaining trust is critically important for continued human-robot interaction and the prospect of robots learning social skills from social environments. While prior work explored ways for artificial agents to learn norms from human users, a psychological analysis of the human teacher has been largely overlooked. To gain insight into how humans would teach robots to master social and moral norms and update their trust, I will present a novel paradigm in which participants interactively teach a simulated robot to behave appropriately in a healthcare setting. In this talk, I will show that human teachers are highly responsive to the robot’s local and cumulative performance. I will discuss my efforts to measure trust dynamics as teaching and learning progress and to examine how human teachers’ choice of teaching method and their perceived contribution to the robot’s learning play a role in these trust dynamics.

ShiNung Ching,Associate Professor Electrical & Systems Engineering,
Washington University in St. Louis

A fundamental challenge in computational neuroscience has been the translation of multimodal data into formal mathematical and computational models that can reveal biophysical mechanisms in neural circuits and their connection to behavior. In this presentation, I will describe our recent efforts in this domain, focusing on extracting from data the generative dynamics that give rise to overt observations of brain activity. Specifically, I will describe how we have adapted tools from Bayesian filtering and algorithmic optimization toward the problem of parametrically learning high-dimensional, biophysically interpretable models of network interactions involving hundreds to thousands of neural populations. These techniques place a particular emphasis on model-building at the level of individuals, which in turn provides leverage on revealing idiosyncrasies in brain mechanisms. In this regard, I will highlight two ways in which we are leveraging the obtained models. First, I will discuss our newly developed methods to directly interrogate the intrinsic dynamics within models, toward assessing topological similarity across individual (brain) dynamics and the functional salience thereof. Second, I will describe how we are using models to predict input-output relationships within brain networks and their responses to exogenous, causal perturbations. In addition to basic mechanistic insights, these approaches enable us to design brain stimulation protocols that are tailored to individuals and defined in terms of dynamical targets that can be linked to specific functional endpoints; to conclude I will briefly describe ongoing work to validate this latter premise.

Opposing Roles of VTA Co-Transmitters in Reward and Aversion

Shelley Warlow
University of California, San Diego

The ventral tegmental area (VTA) controls motivation most notably through its dense dopaminergic projections to various limbic and forebrain sites. However, the VTA is heterogeneous and some VTA neurons have the surprising capacity to co-release multiple neurotransmitters when activated. For example, a subset of VTA glutamate neurons co-release dopamine in the nucleus accumbens medial shell (NAc), and a separate subset co-release GABA in sites such as lateral habenula (LHb) and ventral pallidum. Optogenetic stimulation of VTA glutamate projections promotes positive reinforcement in mice in some assays, yet in other assays can promote aversion, making it difficult to reconcile how the same neurons can promote opposing motivations. Here, I present findings from experiments that dissect the distinct contribution that individual co-transmitters from VTA glutamate neurons make to reinforcement and avoidance behaviors. Overall, our results suggest that distinct neurotransmitters co-released from VTA contribute to motivation in an opposing manner, and highlight mesolimbic contributions to reinforcement that are dopamine-independent.

The Neural Mechanisms and Circuits for Flexible Decision-Making

NaYoung So
Colombia University

A hallmark of cognition lies in the ability to process and combine information in a flexible manner. To identify the mechanisms and circuits underlying this computation, I study the neurobiology of decision-making. Humans and other primates predominantly use vision to gather information, and therefore, I use nonhuman primates as a model for studying the neural correlates of decisions communicated by eye movements. I designed novel tasks that deconstruct the decision process to understand (i) how the decision can be paused and resumed after interruptions and (ii) how the decision can be terminated to be reported later. While the monkey was engaged in these tasks, I recorded tens to hundreds of neurons simultaneously from the parietal cortex. When a decision is interrupted by intervening eye movements and needs to be updated, I demonstrated the population of parietal neurons represents the decision continuously without interruption—by transferring decision-related activity from neuron to neuron across intervening eye movements.
Furthermore, I showed that if the termination of a decision is separate from the expression of the decision, different groups of parietal neurons represent the When and What of the decision. Yet, these representations are correlated on single trials, suggesting the When and What of a decision remain coupled via a single evidence accumulation process. Together, my results reveal the building blocks of the decision process and how these units are put together to guide flexible behavior. Based on my findings, I hypothesize that behavioral flexibility can be explained by the many ways neurons can communicate within and across brain areas to cater to various task demands. My future research will test this hypothesis by probing hundreds of neurons simultaneously from the parietal and frontal areas while the monkey makes decisions under varying task demands:
1. Different information types (i.e., value and sensory).
2. Different rules or contexts.
3. Different ways to gather information.
My research benefits from the latest innovation in neurotechnology for probing neural populations and the set of sophisticated analyses and models to identify neural mechanisms and circuits for decision-making. Through this approach, my research aims to uncover the general principles governing cognition.

Speaker: Mary Hegarty (UCSB)

Title: TBA

Abstract: TBA

Join The Carney Institute for Brain Science as we host The Center for the Neurobiology of Cells and Circuits Special Seminar with Sam Reiter, Ph.D., where he will discuss the Cephalopod skin patterns as windows into brain dynamics.

Dr. Reiter is currently an assistant professor and leader of the computational neuroethology unit at Okinawa Institute of Science and Technology. His background is in experimental neuroscience, where he has studied diverse topics in a range of model organisms. After studying neuroscience at Brown University, he continued graduate school in neuroscience at Brown and the US. National Institutes of Health, and most recently worked as a postdoc at the Max Planck Institute for Brain Research.

Speaker: Linda Zou, University of Maryland

Title:

Abstract:

Join the Carney Institute for Brain Science for a Career Conversation with Sam Reiter, Ph.D., as he shares his personal academic journey and career trajectory. The event will be followed by a discussion and Q&A session, moderated by Kristin Webster, the Carney Institute’s Associate Director for Training and Development.

Dr. Reiter will also be presenting a Center for the Neurobiology of Cells and Circuits Special Seminar discussing the Cephalopod skin patterns as windows into brain dynamics on April 26 at 12:00 p.m. in the Carney Innovation Zone. 

Sam Reiter is currently an assistant professor and leader of the Computational Neuroethology Unit at Okinawa Institute of Science and Technology. His background is in experimental neuroscience, where he has studied diverse topics in a range of model organisms. After studying neuroscience at Brown University as an undergraduate, he continued graduate school in neuroscience at Brown and the US National Institutes of Health and trained as a postdoc at the Max Planck Institute for Brain Research.

Please RSVP by April 24 and reach out to [email protected] with any questions.

Brown University’s Fluid Biomarkers Laboratory & Meso Scale Discovery invite you to join us for a lunch and learn to explore:

MSD Solutions for:

• Personalized Multiplexing
• Ultrasensitive Detection
• Assay Development

Focus: Biomarker detection in blood, CSF, exosomes, + extracellular vesicles (EVs)

Speaker: Justin Parent, Brown/URI

Title:

Abstract:

John Mislow Memorial Lecture

Stanislas Dehaene, Professor, Collège de France

“Understanding the neural code for conscious symbolic thought:
A challenge for human cognitive neuroscience”

Tuesday, April 30, 2024 | 4:00 p.m.
Reception to follow

According to the global neural workspace hypothesis, the mechanisms of conscious access are similar in human and non-human species. Wherein, then, lies the singularity of the human brain? In this talk, I will propose that the contents of consciousness became markedly richer in humans as our brains acquired a capacity for compositional thought using discrete symbols. Recent comparative data from my lab show that humans possess unique abilities for symbolic learning and a mathematical “language of thought”. Even the mere perception of a square or a zig-zag involves a short mental program that captures the observed data in an internal language of geometry. Behavioral and brain- imaging experiments indicate that the perception of geometric shapes is poorly captured by current convolutional neural network models of the ventral visual pathway, but involves a symbolic geometrical description within the dorsal parieto-prefrontal network. I will argue that existing connectionist models do not suffice to account for even elementary human perceptual data, and that neural codes for symbols and syntax remain to be discovered.

Clinical Psychology Training Programs at Brown: A Consortium of the Providence VA Medical Center, Lifespan,
and Care New England
Cultural Adaptation of Evidence-Based Interventions
Melanie M. Domenech Rodríguez, PhD, ABPP
Department of Psychology
Utah State University

Wednesday, May 1, 2024◊ 11:00 am - 12:30 pm
• PRE-REGISTRATION REQUIRED: https://cme-learning.brown.edu/DPHB-23-24
Objectives: At the conclusion of this presentation, participants should be better able to:
• Define cultural adaptation
• Differentiate cultural adaptation from cultural competence
• Identify multiple models of cultural adaptation
• Explain the effects of cultural adaptation on treatment outcomes
• Describe specific examples of cultural adaptations

Financial Relationship Disclosure: Dr. Domenech has no financial relationships to disclose.

This is an Intro Into Networking Workshop and Social Event for Graduate Students and Postdocs in biology-related fields.

Speaker: Miranda Scolari (Texas Tech University)

Title: TBA

Abstract: TBA

Speaker: Semir Tatlidil, Brown University
Title: TBA
Abstract: TBA

We are pleased to invite you to a virtual workshop on the Human Neocortical Neurosolver (HNN), jointly organized by the Stephanie Jones Lab and MetaCell, scheduled for May 8th. The workshop is aimed at researchers and clinicians with an interest in neuroscience but without formal computational modeling or coding experience. It will offer a detailed exploration of HNN, a tool designed to interpret the neural origins of human MEG/EEG data.

Workshop Highlights:

• Comprehensive Overview: The workshop will begin with a didactic presentation on the background and development of HNN, providing a foundation for its application in neuroscience research.
• Practical Application: Participants will learn how to utilize the HNN graphical user interface (GUI) to investigate the circuit origins of commonly measured signals, including event-related potentials (ERPs) and low-frequency brain rhythms.
• Advanced Interface Training: Discover how to use the HNN-core Python interface.

Workshops Hosts:

• Stephanie Jones, PhD
• Mainak Jas, PhD
• Nicholas Tolley
• Ryan Thorpe
• Dylan Daniels

About the Workshop Content:

MEG/EEG signals are correlated with several healthy and pathological brain functions. However, it is still extremely difficult to infer their underlying cellular and circuit level origins. This limits the translation of MEG/EEG signals into novel principles of information processing, or into new treatment methods for pathologies. To address this limitation, we have built the Human Neocortical Neurosolver (HNN): an open-source software tool to help researchers and clinicians without formal computational modeling or coding experience interpret the neural origin of their human MEG/EEG data.

HNN provides a graphical user interface (GUI) and a programmable Python interface to an anatomically and biophysically detailed model of a neocortical circuit, with layer specific thalamocortical and cortical-cortical drives. Tutorials are provided to teach users how to begin to study the cell and circuit level origin of sensory event related potentials (ERPs) and low frequency rhythms in the alpha, beta and gamma band, based on our prior publications.

Unique to HNN is an underlying neural model that accounts for the biophysics generating the primary electric currents underlying EEG/MEG signals, enabling visual and statistical comparison of model output to source localized data from a single brain area (in nAm). Users can change model parameters in the GUI for testing hypotheses on signal differences under varied experimental conditions. Further, visualizations are shown of detailed circuit activity including layer-specific responses, cell spiking activity, and membrane voltages.

We look forward to introducing you to our one-of-a-kind tool for cell and circuit interpretation of MEG/EEG!

Registration Information:

The workshop will take place online on Wednesday, May 8th from 9am to noon ET. It is limited to 20 participants to ensure a productive learning environment. Given the specialized nature of this workshop, we anticipate high interest. To secure your participation, we recommend registering as soon as possible. A registration fee of $25.00 is required to help us cover the costs of organizing the event.

Scaling Single Session Interventions to Bridge Gaps in Mental Health Ecosystems
Jessica L. Schleider, Ph.D.
Associate Professor, Departments of Medical Social Sciences, Pediatrics and Psychology
Northwestern University
Wednesday, May 8, 2024◊ 11:00 am - 12:00 pm
• PRE-REGISTRATION REQUIRED: https://cme-learning.brown.edu/2023-2024-Child-Adolescent
Objectives: At the conclusion of this presentation, participants should be better able to:
• Understand the concept of ‘single-session interventions’ (SSIs) for youth mental health
• Describe state-of-the-art research on how, why, and for whom SSIs can reduce mental health problems
• Identify tools and create an implementation plan for using evidence-based SSIs in real-world practice
Financial Relationship Disclosure: Dr. Schleider has the following financial relationships to disclose: Research Funding: Kooth LLC, Founder: Single Session Support Solutions 

Speaker: Sabine Kastner (Princeton)

Title: TBA

Abstract: TBA