Circuit mechanisms of cortical predictive learning
This project aims to investigate the circuit and neuromodulatory mechanisms of sensory prediction learning in the visual cortex, enhancing understanding of self-generated feedback processing and its implications for neurodevelopmental conditions and AI.
Projectdetails
Introduction
To perform sensory guided behaviors, animals need to distinguish self-generated and externally generated sensory inputs. Predictive processing theories propose that the brain does this by learning to predict sensations caused by self-motion. The key signals thought to drive this learning are prediction errors: differences between predicted and actual sensory input.
Previous Work
My previous work shows that neurons in the primary visual cortex (V1) compute visuomotor prediction errors, and that prediction errors activate the locus coeruleus, a brain-wide neuromodulatory system.
Research Objectives
We will now investigate the circuit and neuromodulatory mechanisms underlying the learning of sensory predictions, using V1 as a model. I hypothesize that input to V1 from higher order cortical areas undergoes plasticity during self-generated sensory feedback.
Hypothesis
This plasticity should be driven by prediction errors in V1 activity, modulated by locus coeruleus output, and improve detection of externally generated visual flow during self-motion.
Methodology
We will test this hypothesis using innovative methods, including:
- A multimodal virtual reality system
- A novel object detection task
- In vivo whole cell recordings
- Two-photon imaging
- Optogenetics
Specific Aims
The specific aims are to:
- Investigate how prediction errors are communicated between the locus coeruleus and the cortex.
- Decipher the mechanisms of predictive plasticity within the V1 circuit.
- Assess the behavioral relevance of this plasticity.
Significance
The knowledge gained will have a fundamental impact on our mechanistic understanding of predictive learning in the cortex and the role of neuromodulation in this process. This will have significance for:
- Understanding conditions in which the processing of self-generated sensory feedback is thought to be disrupted (e.g., neurodevelopmental conditions and psychosis).
- Development of AI and brain-machine interfaces that deal with self-generated sensor feedback (e.g., prostheses).
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.941.819 |
Totale projectbegroting | € 1.941.819 |
Tijdlijn
Startdatum | 1-12-2024 |
Einddatum | 30-11-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- THE UNIVERSITY OF EDINBURGHpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Active Inference and the Circuits of Precision and PredictionPREDICTION aims to uncover the neural mechanisms of high-level visual cognition by integrating advanced methods across disciplines to model hierarchical processing in the human brain. | ERC Advanced... | € 2.500.000 | 2025 | Details |
Correcting for self: The impact of head motion on visual processing and behaviour.This project aims to uncover the neuronal circuits connecting the vestibular system to visual processing in mice, enhancing understanding of sensory integration during self-motion. | ERC Starting... | € 1.499.639 | 2024 | Details |
Shaping cortical computations via higher-order feedbackFeedbackCircuits aims to uncover the neural mechanisms of feedback-driven cortical computations in the mouse visual cortex, linking synaptic plasticity to circuit-level processing through a multi-scale theoretical framework. | ERC Consolid... | € 1.818.781 | 2025 | Details |
Mechanisms of memory formation in cortical networks during learning of goal-directed behaviorsThis project aims to map and manipulate causal connectivity in vivo between neurons during memory learning in mice using novel optical methods to understand network dynamics and memory mechanisms. | ERC Starting... | € 2.110.000 | 2024 | Details |
Tracing Visual Computations from the Retina to BehaviorThis project aims to investigate how the superior colliculus integrates retinal signals to drive behavior using imaging, optogenetics, and modeling, revealing mechanisms of visual information processing. | ERC Starting... | € 1.871.465 | 2025 | Details |
Active Inference and the Circuits of Precision and Prediction
PREDICTION aims to uncover the neural mechanisms of high-level visual cognition by integrating advanced methods across disciplines to model hierarchical processing in the human brain.
Correcting for self: The impact of head motion on visual processing and behaviour.
This project aims to uncover the neuronal circuits connecting the vestibular system to visual processing in mice, enhancing understanding of sensory integration during self-motion.
Shaping cortical computations via higher-order feedback
FeedbackCircuits aims to uncover the neural mechanisms of feedback-driven cortical computations in the mouse visual cortex, linking synaptic plasticity to circuit-level processing through a multi-scale theoretical framework.
Mechanisms of memory formation in cortical networks during learning of goal-directed behaviors
This project aims to map and manipulate causal connectivity in vivo between neurons during memory learning in mice using novel optical methods to understand network dynamics and memory mechanisms.
Tracing Visual Computations from the Retina to Behavior
This project aims to investigate how the superior colliculus integrates retinal signals to drive behavior using imaging, optogenetics, and modeling, revealing mechanisms of visual information processing.