SPATEMP
Financiado
From spatial relationships to temporal correlations New vistas on predictive co...
During active wakefulness, cortical activity organizes itself into highly coherent patterns of gamma waves (30-80Hz). These waves are believed to be essential for cortical communication and synaptic plasticity. Their impairment is...
During active wakefulness, cortical activity organizes itself into highly coherent patterns of gamma waves (30-80Hz). These waves are believed to be essential for cortical communication and synaptic plasticity. Their impairment is a hallmark of neurological and psychiatric disorders. Yet, it remains heavily debated what gamma waves encode, and what their precise role in information transmission is. I have recently proposed a new theory about gamma in visual cortex, building on the predictive coding theory. The predictive coding theory holds that the brain makes active top-down predictions about its own sensory inputs. By comparing these, it generates bottom-up prediction errors to drive learning and the updating of priors. The standard view in predictive coding theories is that gamma waves carry prediction errors. However, I recently hypothesized the opposite: 1) Gamma waves signal a match between predictions and sensory inputs (i.e. predictability), and 2) Columns that predict each other's visual input engage in long-range gamma-synchronization. To test this hypothesis, it is critical to develop a new method to quantify predictions and prediction errors in the context of natural vision. I will solve this by using recently developed deep-learning networks for prediction. By making multi-areal recordings from visual cortex in marmosets and humans (MEG), I will test if predictability indeed determines gamma waves and their synchronization pattern across space. Because stimulus priors have to be acquired through learning, I will further determine whether gamma waves depend on experience and perceptual learning. In marmosets, I will develop an optogenetics approach to test whether gamma waves drive perceptual learning, and test the prediction that V1 gamma waves depend on top-down feedback. In sum, I expect to provide evidence for a new, unified theory about the role of gamma waves in information transmission and the integration of sensory evidence with predictions.
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Duración del proyecto: 60 meses
Fecha Inicio: 2020-01-28
Fecha Fin: 2025-01-31
Fecha Fin: 2025-01-31
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2020-01-28
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2019-STG:
ERC Starting Grant
Cerrada
hace 6 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
ERNST STRUNGMANN INSTITUTE GGMBH
No se ha especificado una descripción o un objeto social para esta compañía.
179.63K€ |
Participante