Descrizione del progetto
Svelare il cervello dei pesci con immaginografia ottica in vivo e modellizzazione matematica avanzata
Comprendere il comportamento di organismi come noi che integrano segnali ambientali e stimoli neurali con l’elaborazione cognitiva è un compito molto complesso. Sfruttare il potere di organismi modello semplici come il pesce zebra, nonché il potere dei metodi analitici computazionali, potrebbe consentire la caratterizzazione di complesse interazioni cervello-corpo-ambiente negli organismi viventi. I pesci zebra condividono molti organi e tessuti principali con gli esseri umani, e allo stadio larvale sono trasparenti all’occhio, agevolando l’immaginografia in vivo delle dinamiche del calcio durante l’attivazione del sistema nervoso. Il progetto DIMENSIVE, finanziato dall’UE, sta registrando l’attività neurale dei pesci zebra in attività e sta utilizzando i dati per sviluppare modelli generativi di comportamento su larga scala. I modelli statistici avanzati consentiranno agli scienziati di creare nuove istanze di dati, fornendo importanti informazioni sul modo in cui il comportamento sorge a partire dall’interazione dinamica del sistema nervoso di un organismo, del suo corpo e dell’ambiente.
Obiettivo
A major challenge in cognitive neuroscience is to understand how behaviour arises from the dynamical interaction of an organism’s nervous system, its body, and its environment. Understanding embodied neural activity involves the resolution of various conceptual, technical and methodological issues in explaining how living organisms self-organize at many levels (from neural bio-chemistry to behaviour and learning). Currently, two important obstacles hinder this endeavour: the difficulties in recording neural activity in behaving animals, and the lack of mathematical tools to characterize the complex brain-body-environment interactions in living organisms. In this project we will address current limits by implementing an interdisciplinary combination of novel animal behaviour neuroimaging setups and large-scale statistical methods, with the goal of recording and modelling whole-brain activity of locomoting vertebrates. We will study fictively swimming larval zebrafish during active behaviour in a pioneering experimental setup, recording neural activity utilizing light-sheet microscopy for calcium imaging in different virtual reality scenarios involving sensorimotor manipulations. In this setup, we will collect data from the distributed neural circuits that integrate sensory signals from the environment (exafferent input) and their own movements (reafferent input), as well as plastic processes of habituation to new sensorimotor contingencies. From this data, we will infer large-scale generative models (i.e. models capable of yielding synthetic data resembling the studied phenomena) of embodied neural circuits by complementing dynamical models and techniques from statistical mechanics with innovative information theoretic and Bayesian inference methods and approximations for very large systems in non-equilibrium and non-stationary conditions.
Campo scientifico
- natural sciencesbiological sciencesneurobiologycognitive neuroscience
- natural sciencesmathematicsapplied mathematicsstatistics and probabilitybayesian statistics
- natural sciencesphysical sciencesclassical mechanicsstatistical mechanics
- natural sciencescomputer and information sciencessoftwaresoftware applicationsvirtual reality
- natural sciencesbiological sciencesbiological behavioural sciencesethology
Programma(i)
Argomento(i)
Meccanismo di finanziamento
MSCA-IF-EF-ST - Standard EFCoordinatore
BN1 9RH Brighton
Regno Unito