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Seminars in Hearing Research (09/05/24) - Edward Bartlett and Brandon Coventry

Seminars in Hearing Research (09/05/24) - Edward Bartlett and Brandon Coventry

Author: M. Heinz
Event Date: September 5, 2024
Hosted By: Maureen Shader
Time: 1030-1120
Location: NLSN 1215
Contact Name: Shader, Maureen J
Contact Email: mshader@purdue.edu
Open To: All
Priority: No
School or Program: Non-Engineering
College Calendar: Show
Edward Bartlett (Assoc. Dean for Undergraduate Affairs, College of Science & Professor, Depts. Biological Sciences and Biomedical Engineering) and Brandon Coventry (Post Doctoral Fellow at the Wisconsin Institute for Translational Neuroengineering) will present "Practical Bayesian Inference in Neuroscience: Or How I Learned to Stop Worrying and Embrace the Distribution" at our next Seminars in Hearing Research at Purdue (SHRP) on September 5th at 12-1 in NLSN 1215.

Seminars in Hearing Research

Date: Thursday, Septmebr 5th, 2024

Location: Nelson Hall, Room 1215

Time: 12:00-1:00pm

 

Speakers:
Edward Bartlett, Associate Dean for Undergraduate Affairs, College of Science & Professor, Depts. Biological Sciences and Biomedical Engineering

Brandon Coventry, Post Doctoral Fellow at the Wisconsin Institute for Translational Neuroengineering

Title: Practical Bayesian Inference in Neuroscience: Or How I Learned to Stop Worrying and Embrace the Distribution

Abstract: Typical statistical practices in the biological sciences have been increasingly called into question due to difficulties in the replication of an increasing number of studies, many of which are confounded by the relative difficulty of null significance hypothesis testing designs and interpretation of p-values. Bayesian inference, representing a fundamentally different approach to hypothesis testing, is receiving renewed interest as a potential alternative or complement to traditional null significance hypothesis testing due to its ease of interpretation and explicit declarations of prior assumptions. Bayesian models are more mathematically complex than equivalent frequentist approaches, which have historically limited applications to simplified analysis cases. However, the advent of probability distribution sampling tools with exponential increases in computational power now allows for quick and robust inference under any distribution of data. Here we present a practical tutorial on the use of Bayesian inference in the context of neuroscientific studies in both rat electrophysiological and computational modeling data. We first start with an intuitive discussion of Bayes' rule and inference followed by the formulation of Bayesian-based regression and ANOVA models using data from a variety of neuroscientific studies. We show how Bayesian inference leads to easily interpretable analysis of data while providing an open-source toolbox to facilitate the use of Bayesian tools.

 

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The working schedule is available here: https://purdue.edu/TPAN/hearing/shrp_schedule

 

The titles and abstracts of the talks will be added here: https://purdue.edu/TPAN/hearing/shrp_abstracts