- All Categories
- Featured Events
- Alumni
- Application Deadline
- Arts
- Campus Discourse
- Careers
- BU Central
- Center for the Humanities
- Charity & Volunteering
- Kilachand Center
- Commencement
- Conferences & Workshops
- Diversity & Inclusion
- Examinations
- Food & Beverage
- Global
- Health & Wellbeing
- Keyword Initiative
- Lectures
- LAW Community
- Meetings
- Orientation
- Other Events
- Religious Services & Activities
- Special Interest to Women
- Sports & Recreation
- Social Events
- Study Abroad
- Weeks of Welcome
- In Wilderness Is the Preservation of the World: Photography by Dan Wells12:00 am
- IS&T RCS Tutorial - Analysis of Large Datasets Using R’s Data.table10:00 am
- Cross-Disability Club Meeting (ONLINE)12:30 pm
- Torn Between the Lover and the Love You Leave Behind: Forced Migration, Human Trafficking and Access to Hell12:30 pm
- IS&T RCS Tutorial - Data Visualization in Python1:00 pm
- IS&T RCS Tutorial - Basics of using ArcGIS Pro2:00 pm
- Metropolitan College Graduate Admissions Webinar2:00 pm
- Provost Workshop: Exploring Opportunities at the Nexus of Computing and Data Sciences3:00 pm
- Create Space3:00 pm
- IS&T RCS Tutorial - Introduction to C++ Programming, Part One3:30 pm
- Descriptive methods and analyses of neural population activity (Mikio Aoi - Princeton University)4:00 pm
- How to talk to Employers4:00 pm
- Quito Tropical Ecology Info Session 4:30 pm
- Global Dinner Club5:00 pm
- Faculty Book Publication Party 5:00 pm
- Visiting Artist: Gala Porras-Kim7:30 pm
Descriptive methods and analyses of neural population activity (Mikio Aoi - Princeton University)
Recent developments in neural recording technologies have dramaticallyincreased the number of neurons that can be simultaneously observedduring behavioral experiments. Concurrently, complexity inexperimental environments, and in the tuning properties of individualneurons, have conspired to make the task of summarizing neuronalpopulation activity both conceptually and computationally oneroususing conventional methods. Despite heroic efforts on the part of boththe systems neuroscience and machine learning communities, littleconsensus has been reached on the best ways to summarize these data.In this talk I will demonstrate new analysis techniques developed tomeet some of these challenges. I will highlight a case of neuralpopulation activity from monkey prefrontal cortex (PFC) during acontext-dependent decision making task. The analysis method decomposespopulation activity into a combination of low-dimensionalrepresentations that carry specific task-related information. Specialcases of this model include standard dimension-reduction techniquessuch as principal components and factor analysis. This decompositionreveals a multi-dimensional, dynamic code for decision, context, andstimulus information. I will describe how these observationssubstantially alter our understanding of decision-related populationactivity in PFC and provide a glimpse of how this basic approach issuited to analysis of neural population activity for other brainareas, tasks, animals, and recording modalities with the goal ofestablishing a suite of methods what will be considered the newstandard for analyzing these data. I will conclude with a few examplesof ongoing work where I am developing a variety of data analysis toolsto better understand brain dynamics.
When | 4:00 pm to 5:00 pm on Tuesday, February 4, 2020 |
---|---|
Location | MCS B39, 111 Cummington Mall |