Investigating The Role of Noise Correlations in Learning
Completed · Not applicable
Conditions studied: Noise Correlations, Learning Quality
In brief
A fundamental problem in neuroscience is how the brain computes with noisy neurons. An advantage of population codes is that downstream neurons can pool across multiple neurons to reduce the impact of noise. However, this benefit depends on the noise associated with each neuron being independent. Noise correlations refer to the covariance of noise between pairs of neurons, and such correlations can limit the advantages gained from pooling across large neural populations. Indeed, a large body of theoretical work argues that positive noise correlations between similarly tuned neurons reduce the representational capacity of neural populations and are thus detrimental to neural computation. Despite this apparent disadvantage, such noise correlations are observed across many different brain regions, persist even in well-trained subjects, and are dynamically altered in complex tasks. The investigators have advanced the hypothesis that noise correlations may be a neural mechanism for reducing the dimensionality of learning problems. The viability of this hypothesis has been demonstrated in neural network simulations where noise correlations, when embedded in populations with fixed signal-to-noise ratio, enhance the speed and robustness of learning. Here the investigators aim to empirically test this hypothesis, using a combination of computational modeling, fMRI and pupillometry. Establishing a link between noise correlations and learning would open the door to an investigation into how brains navigate a tradeoff between representational capacity and the speed of learning.
Key facts
- Study ID
- NCT06673303
- Run by
- Brown University
- People needed
- 47
- Starts
- 2024-12-14
- Expected to finish
- 2025-09-01
- Last updated by the study team
- 2026-05-26
Who can join
Age: 18 and older. Sex: any. Healthy volunteers: accepted.
You may qualify if…
- Age above 18
- Normal or correctable vision
You may not qualify if…
- Age under 18
- Claustrophobia
- Color blindness
- Neuroleptics medications
- History of drug abuse and/or alcoholism
- Conditions contraindicated for MRI such as:
- Surgical implant that is not MRI compatible
- Metal fragments in the body
- Tattoo with metallic ink
- Eye diseases / impairment:
- Cataracts
- Macular degeneration
- Retinopathies
- Partial vision loss
- Medical history:
- Stroke
- Traumatic brain injury
- Epilepsy
- Schizophrenia
- Manic depression with symptoms including but not limited to psychosis, mania, delusional thinking, and audio/visual hallucinations.
Where it is running
- Brown University — Providence, Rhode Island, United States
Full record on ClinicalTrials.gov
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