scholarly journals Linking normative models for natural tasks and subunit models of neural response

2017 ◽  
Vol 17 (10) ◽  
pp. 411
Author(s):  
Johannes Burge ◽  
Priyank Jaini
Keyword(s):  
Neural Response ◽  
Normative Models ◽  
Natural Tasks

scholarly journals Linking Normative Models of Natural Tasks to Descriptive Models of Neural Response

2017 ◽  
Author(s):  
Priyank Jaini ◽  
Johannes Burge
Keyword(s):  
Latent Variables ◽  
Receptive Fields ◽  
Neural Response ◽  
Energy Model ◽  
Disparity Estimation ◽  
Quadratic Model ◽  
Sensory Stimuli ◽  
Visual Tasks ◽  
Natural Tasks ◽  
Descriptive Models

AbstractUnderstanding how nervous systems exploit task relevant properties of sensory stimuli to perform natural tasks is fundamental to the study of perceptual systems. However, there are few formal methods for determining which stimulus properties are most useful for a given task. As a consequence, it is difficult to develop principled models for how to compute task-relevant latent variables from natural signals, and it is difficult to evaluate descriptive models fit to neural response. Accuracy Maxmization Analysis (AMA) is a recently developed Bayesian method for finding the optimal task-specific filters (receptive fields). Here, we introduce AMA-Gauss, a new faster form of AMA that incorporates the assumption that the class-conditional filter responses are Gaussian distributed. Next, we use AMA-Gauss to show that its assumptions are justified for two fundamental visual tasks: retinal speed estimation and binocular disparity estimation. Then, we show that AMA-Gauss has striking formal similarities to popular quadratic models of neural response: the energy model and the Generalized Quadratic Model (GQM). Together, these developments deepen our understanding of why the energy model of neural response have proven useful, improve our ability to evaluate results from subunit model fits to neural data, and should help accelerate psychophysics and neuroscience research with natural stimuli.

Allometry of Neural Response to Threat in Chickadees is Learned

2011 ◽  
Author(s):  
Christopher B. Sturdy ◽  
Marc T. Avey ◽  
Marisa Hoeschele ◽  
Michele K. Moscicki ◽  
Laurie L. Bloomfield
Keyword(s):  
Neural Response

Visual Attention and Neural Response to Faces in Children With Autism

2011 ◽  
Author(s):  
James Mcpartland ◽  
Danielle Perszyk ◽  
Michael Crowley ◽  
Adam Naples ◽  
Linda C. Mayes
Keyword(s):  
Visual Attention ◽  
Children With Autism ◽  
Neural Response

Psychology and the New Private Law

2020 ◽  
pp. 124-142
Author(s):  
Tess Wilkinson-Ryan
Keyword(s):  
Social Psychology ◽  
Decision Making ◽  
Law And Economics ◽  
Mental States ◽  
Psychological Research ◽  
Private Law ◽  
Legal Decision ◽  
Psychological Analysis ◽  
Legal Decision Making ◽  
Normative Models

This chapter presents a framework for understanding the most promising contributions of psychological methods and insights for private law. It focuses on two related domains of psychological research: cognitive and social psychology. Cognitive psychology is the study of mental processes, which one might shorthand as “thinking.” Social psychology asks about the role of other people—actual, implied, or imagined—on mental states and human behavior. The chapter is oriented around five core psychological insights: calculation, motivation, emotion, social influence, and moral values. Legal scholarship by turns tries to explain legal decision-making, tries to calibrate incentives, and tries to justify its values and its means. Psychology speaks to these descriptive, prescriptive, and normative models of decision-making. The chapter then argues that psychological analysis of legal decision-making challenges the work that the idea of choice and preference is doing in private law, especially in the wake of the law and economics movement.

Sign in / Sign up

Export Citation Format

Share Document