Descrizione del progetto
Comprendere la base neurale della socializzazione
Quali sono i calcoli neurali alla base del comportamento sociale nei gruppi? Come si integrano i segnali multimodali per controllare e passare dal corteggiamento all’aggressione? In che modo l’elaborazione sensoriale si adatta nelle grandi folle per orientare il comportamento dei singoli membri del gruppo? Il progetto NeuSoSen, finanziato dall’UE, cerca di rispondere a tali domande, combinando modellazione computazionale e strumenti genetici. L’apprendimento automatico aiuterà il progetto a quantificare e modellare la struttura fine delle interazioni sociali per identificare i segnali che guidano il comportamento. Il progetto si propone infine di svelare i principi e i meccanismi di calcolo attraverso cui le informazioni sensoriali vengono elaborate per guidare il comportamento nel complesso ambiente sensoriale dei gruppi animali.
Obiettivo
Animals often interact in groups. Animal groups constitute complex sensory environments which challenge the brain and engage complex neural computations. This behavioral context is therefore fruitful for understanding how sophisticated neural computations give rise to behavior. However, it is also technically difficult since many of the relevant sensory cues arise from the members of the group and are therefore hard to quantify or control. Consequently, we only incompletely understand how the brain drives complex social behaviors in naturalistic contexts. To uncover the neural computations underlying social behavior in groups, we are using Drosophila, which provides unprecedented experimental access to the nervous system via genetic tools. Drosophila gathers on rotten fruit to feed and mate. Courtship and aggression dominate social interactions and rely on the recognition of sex-specific chemical cues and the production of context-specific acoustic signals. How are these multi-modal cues integrated to control and switch between courtship and aggression? How is unstable and conflicting sensory information resolved to promote stable behavioral strategies? How does sensory processing adapt to socially crowded environments in order to efficiently target behavior at individual members of the group? These issues will be addressed by combining computational modeling and genetic tools. Using machine learning, we will quantify and model the fine structure of social interactions to identify the social cues that drive behavior. Closed-loop optogenetics and calcium imaging in behaving animals will allow us to test the models and to ultimately reveal how the brain integrates, selects and combines social cues to drive social interactions. This multi-disciplinary approach will uncover the computational principles and mechanisms by which sensory information is processed to drive behavior in the complex sensory environment of animal groups.
Campo scientifico
- natural sciencesbiological sciencesneurobiology
- natural scienceschemical sciencesinorganic chemistryalkaline earth metals
- agricultural sciencesagriculture, forestry, and fisheriesagriculturehorticulturefruit growing
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
ERC-STG - Starting GrantIstituzione ospitante
37075 Goettingen
Germania