Descrizione del progetto
Uno studio sulle capacità di apprendimento ludico
Da molto tempo gli scienziati studiano il modo per ottimizzare il processo di apprendimento e migliorare le funzioni cerebrali degli esseri umani. Si tratta di una questione che oggi attira sempre maggiore attenzione considerando il numero di persone che trascorrono molto tempo giocando ai videogame in tutto il mondo. Alcuni studi dimostrano che l’attività svolta durante il gioco è potenzialmente in grado di apportare benefici cognitivi inaspettatamente profondi. Per questo motivo, il progetto BrainPlay, finanziato dall’UE, rivolge l’attenzione a uno studio completo e interdisciplinare sui promettenti meccanismi di apprendimento attraverso il gioco, dal livello cellulare alle prestazioni cognitive globali. In particolare, BrainPlay esaminerà i meccanismi alla base delle variazioni sinaptiche interne al cervello durante il processo di autoistruzione ed elaborerà una nuova teoria per i meccanismi neurali in tale processo, ricomprendendo l’elemento ludico e l’autoistruzione negli algoritmi cerebrali di apprendimento.
Obiettivo
Our goal is to uncover the learning algorithms that subserve biological intelligence and to discover how they are implemented in the brain. We take for granted that biological intelligence results from neural information processing, that neural information processing is based on the transmission of action potentials through synapses, and that learning is realized through synaptic plasticity. We are inspired by two key observations: Firstly, we know that biological learning unfolds in ways different from mainstream machine learning that relies on learning from large labeled datasets. Second, we discovered that the engagement of the brain during play can result in unexpected and profound cognitive benefits. This proposal describes an untravelled route to the learning algorithms of the brain that runs through the no-man’s-land between synaptic physiology, systems neuroscience, cognitive neuroscience, theoretical neuroscience and machine learning. Our approach focuses on the self-teaching abilities of the mammalian brain and covers and connects four major topics: (1) the objective functions that govern synaptic plasticity, (2) the teaching signals through which learning is steered, (3) behavioral mechanisms of self-teaching, in particular play behaviors, (4) the brain states that engage self-teaching behaviors, in particular the brain state of play. The BrainPlay grant will study self-teaching abilities from synapses to brains, from computational theory to action video games. As gaming has been shown to be highly beneficial for human brain function, we are intrigued by how little we know about what is going on in playing brains and how the brain state of play shapes learning. Engaging the latest theoretical and technological breakthroughs, BrainPlay will reach far beyond mainstream neuroscience and embrace and elucidate playfulness and self-teaching as important components of the brain's learning algorithms.
Campo scientifico
- natural sciencesbiological sciencesneurobiologycognitive neuroscience
- natural sciencesbiological sciencesneurobiologycomputational neuroscience
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesdata sciencedata processing
- natural sciencescomputer and information sciencessoftwaresoftware applicationsvideo games
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
ERC-SyG - Synergy grantIstituzione ospitante
10117 Berlin
Germania