Large-scale analysis of neuronal population activity

Informations projet

NEUROPOP

N° de convention de subvention: 694401

DOI

10.3030/694401

Projet clôturé

Date de signature de la CE 2 Août 2016

Date de début 1 Octobre 2016

Date de fin 31 Mars 2023

Financé au titre de

• EXCELLENT SCIENCE - European Research Council (ERC)

Coût total

€ 2 499 131,00

Contribution de l’UE

€ 2 499 131,00

Coordonné par

UNIVERSITY COLLEGE LONDON
United Kingdom

Periodic Reporting for period 5 - NEUROPOP (Large-scale analysis of neuronal population activity)

Période du rapport: 2022-10-01 au 2023-03-31

Résumé du contexte et des objectifs généraux du projet

What is the problem/issue being addressed?

This project is addressing the way large populations of neurons across the brain work together to process information.


Why is it important for society?

In the same way that a deep understanding of cell biology led to today’s rapid advances in treatment of cancer, a deep understanding how the brain functions will be essential to develop effective treatments for currently intractable disorders such as Alzheimer’s disease. This project tackles the question of how neuronal populations compute information, one of the key questions that must be solved to achieve this objective. Additionally, discoveries made in how neurons process information will continue to inform design of artificially intelligent systems such as deep neural networks.


What are the overall objectives?

To characterize how large neuronal populations across the brain encode visual information, and the decisions that subjects make based on them.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

1. Overturning the textbook view that primary sensory cortex encodes primarily sensory information (Stringer et al Science 2019)
2. Demonstrating an quantitative regularity in neural population activity, revealing unexpected connections to pure mathematics (Stringer et al Nature 2019).
3. Characterizing the brain-wide correlates of vision, choice, action, and engagement (Steinmetz et al Nature 2018).
4. Understanding the relationships between activity in the striatum and cortex during behavior (Peters et al Nature 2021)
5. Characterizing how frontal cortex nonlinearly integrates stimuli, choices, and outcomes (Wool et al Wellcome Open Research 2023)
6. Characterizing how frontal cortex linearly integrates auditory and visual stimulus information (Coen et al, Neuron 2023)
7. Showing that one of the commonly used mouse models of the time showed aberrant cortical activity so should not be used (Steinmetz et al Eneuro 2017)
8. Characterizing how infraslow cortical activity relates to fast activity (Okun et al Cerebral Cortex 2019)
9. Understanding the basis of perseverative behavior in dorsal prefrontal cortex (Lebedeva et al 2024)
10. Relating the cortex-wide correlates of sensation and decision seen with electrophysiology to those observed with calcium imaging (Zatka-Haas et al eLife 2021)

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

Leveraging new experimental technologies, these studies have recorded from larger neuronal populations that previously possible. This has led to revision of the textbook view of the function of visual cortex, and to unexpected connections with pure mathematics that may have important implications for the design of artificially intelligent systems.

Brain networks found by Steinmetz et al 2019