# Visual perception as a window onto prediction anomalies in schizophrenia

> **NIH NIH R01** · MICHIGAN STATE UNIVERSITY · 2022 · $462,574

## Abstract

Abstract
 What are the aberrant brain processes that lead to symptoms of schizophrenia—to the distressing and
disabling hallucinations, delusions, disorganization, and loss of motivation? Answering this question is central
to developing targeted and effective treatments. Prominent mechanistic accounts of schizophrenia hinge on
the notion of the brain as a “prediction machine” that maintains and updates a mental model of the probabilistic
structure of the environment, which it uses in concert with sensory input to make sense of the world.
Schizophrenia has been associated with an abnormality in this interpretative process, leading to abnormal
perceptions, beliefs, and behaviors. What is currently lacking, however, is an empirical basis for delineating the
specific nature of prediction abnormalities in schizophrenia, at the level of both behavior and brain.
 The general aim of the current project is to understand how visual perception is influenced by
experience-based predictions in the schizophrenia. The visual system is a uniquely suited system for
understanding prediction abnormalities in clinical populations for several reasons. First, robust behavioral
paradigms can quantify the influence of predictions on visual perception. Second, parallel neurophysiology and
neuroimaging work provides a basis for interpretation at the level of neuronal populations. Understanding these
abnormalities in vision, then, may provide a scalable framework for understanding symptoms more generally.
Furthermore, visual distortions are observed in schizophrenia before illness onset, and they relate to important
clinical factors. Understanding prediction in the visual system can help explain specific clinical phenomenology.
 The current project proposes to investigate the influence of prior experience on visual processing by
measuring visual aftereffects and their neural concomitants. Aftereffects are illusory perception of the
“opposite” that arises after prolonged viewing of a image. Characterizing visual aftereffects in the
schizophrenia spectrum can provide important insights into the computational and biological underpinnings of
abnormal prediction. The substantial existing literature on the neural and computational origins of aftereffects
means that different aftereffects can reveal at what level of the sensory hierarchy, and in which specific
component processes, prediction abnormalities emerge. Specific study goals are to 1) characterize visual
aftereffects in the schizophrenia spectrum; 2) determine whether they are present across illness stages and in
individuals at-risk for the disorder; 3) evaluate the clinical relevance of altered visual aftereffects; and 4) to
measure neuroimaging concomitants of altered aftereffects and link them to computational model components.
Visual aftereffects can provide a tool with which to empirically test a canonical computational mechanism as
the basis for both altered visual experience and symptom genesis generally, namely a...

## Key facts

- **NIH application ID:** 10376280
- **Project number:** 5R01MH121417-02
- **Recipient organization:** MICHIGAN STATE UNIVERSITY
- **Principal Investigator:** Katharine Natasha Thakkar
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $462,574
- **Award type:** 5
- **Project period:** 2021-04-01 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10376280

## Citation

> US National Institutes of Health, RePORTER application 10376280, Visual perception as a window onto prediction anomalies in schizophrenia (5R01MH121417-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10376280. Licensed CC0.

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