Large-scale analysis of neuronal population activity

Información del proyecto

NEUROPOP

Identificador del acuerdo de subvención: 694401

DOI

10.3030/694401

Proyecto cerrado

Fecha de la firma de la CE 2 Agosto 2016

Fecha de inicio 1 Octubre 2016

Fecha de finalización 31 Marzo 2023

Financiado con arreglo a

• EXCELLENT SCIENCE - European Research Council (ERC)

Coste total

€ 2 499 131,00

Aportación de la UE

€ 2 499 131,00

Coordinado por

UNIVERSITY COLLEGE LONDON
United Kingdom

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

Período documentado: 2022-10-01 hasta 2023-03-31

Resumen del contexto y de los objetivos generales del proyecto

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.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

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)

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

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