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Narratives & Naturalistic Contexts

In 2018 we explored narratives and natural contexts focusing on analyses, experiments, and models that capture the rich spatiotemporal structure of the “real world.” There has been renewed interest in moving the study of neural and psychological processes from highly controlled laboratory studies to more naturalistic contexts. However, this requires developing new methods to develop experiments and analyze data. We are excited to incorporate some of the latest theoretical, methodological, and experimental advances that are advancing progress towards this goal. Our program will feature a mix of expertise at a broad range of spatiotemporal scales and domains (e.g. behavioral, cognitive, social; circuit, whole-brain, and social networks; etc.).

Participants

Claire Chang, Vassiki Chauhan, Robert Chavez, Hung-Tu Chen, Andy Chen, Damien Crone, Josh Davis, Halle Dimsdale-Zucker, Thomas Donoghue, Justin Drake Shin, Andy Dykstra, Emily Finn, Linda Geerligs, Ariel Goldstein, Jarrod Hicks, Hongmi Lee, Feilong Ma, David Maisson, Judith Mildner, Nils Nyberg, Temidayo Orederu, Lucy Owen, Prateekshit Pandey, Kumar Pankaj Gupta, Athula Pudhiyidath, Angela Radulescu, Touran Rahimi-Moghaddam, Shawn Rhoads, Megan Speer, Mark Straccia, Emma Templeton, Weizhen Xie, Asieh Zadbood

Faculty

Luke Chang

Dartmouth College

Janice Chen

Johns Hopkins University

Michale Fee

Massachusetts Institute of Technology

Yaroslav Halchenko

Dartmouth College

James Haxby

Dartmouth College

Christopher Honey

Johns Hopkins University

Alex Huth

University of Texas Austin

Caleb Kemere

Rice University

Jeremy Manning

Dartmouth College

Ida Momennejad

Columbia University

Emily Mower-Provost

University of Michigan

Carolyn Parkinson

University of California Los Angeles

Alireza Soltani

Dartmouth College

Mark Thornton

Princeton University

Matthijs van der Meer

Dartmouth College

Thalia Wheatley

Dartmouth College

Tutorials

Scientific Computing

by: Luke Chang

Containers

by: Lucy Owens

Github

by: Eshin Jolly

Jupyter Notebooks

by: Eshin Jolly

Science Hacking 101

by: Jeremy Manning

Tools from the Center for Open Neuroscience

by: Yarik Halchenko

Modeling fine-scale cortical topographies

by: Jim Haxby

Endogenous variation in emotional experiences

by: Luke Chang

Internally generated activity in rodent hippocampus

by: Matt van der Meer

Contextual Dynamics

by: Jeremy Manning

Computational modeling at different levels

by: Alireza Soltani

Encoding models for natural stimuli

by: Alex Huth

Speech model tutorial

by: Alex Huth

The cortical map during ripples

by: Caleb Kemere

Hippocampal analysis with nelpy

by: Caleb Kemere

Hierarchical timescales of perception and memory

by: Chris Honey

Timescales tutorial

by: Chris Honey

The songbird as a model system for complex learned behaviors

by: Michaele Fee

Shared Perception & Memory

by: Janice Chen

ROI-Level Pattern Similarity Analyses Tutorial

by: Janice Chen

Sculpting cognitive maps

by: Ida Momennejad

Successor Representations

by: Ida Momennejad

Conversation

by: Thalia Wheatley

Human centered computing and the complexity of emotion

by: Emily Mower Provost

The brain in the social world

by: Carolyn Parkinson

Social network tutorial

by: Carolyn Parkinson

Gaussian Process Regression with SuperEEG

by: Jeremy Manning

The neural representation of social knowledge

by: Mark Thornton

Representational Similarity Analysis

by: Mark Thornton