Summary
Detecting surprising events, such as the sudden approach of a predator or an unexpected touch, is crucial for the survival of all species. We aim to study neuronal mechanisms underlying surprising events. In order to predict upcoming events, mental models of future actions are essential. Where in the brain are such predictions and mental models created? The somatosensory cortex might contain a body model, in which superficial layers provide context and sensory memories, and inputs from deeper layers allow for simulating body movements. In rats, the somatosensory cortex is activated by tickling, which is a special form of unexpected touch containing elements of both sensory and social surprise. However, self-touch induces signals which prevent activation of the somatosensory cortex and prevent self-tickle. Where do these self-touch induced inhibitory signals come from? We hypothesize that the cerebellum is the source of self-touch induced signals. The cerebellum has reciprocal connections with key forebrain areas, including the somatosensory cortex. Combined with its known role in adapting action to sensory and internally generated events, the cerebellum seems well placed to aid in the processing of surprising events. We will test in mice and rats the hypothesis that the cerebellum plays a key role in processing unexpected events to modulate representations in somatosensory cortex. By combining the applicant’s experience in recordings from awake behaving mice, the expertise of the lab of Prof. Wang at Princeton University in cerebellar research with a focus on motor and non-motor function, and the expertise of the lab of Prof. Michael Häusser at University College London in naturalistic systems neuroscience, we are well placed to study the cerebellar signals for sensory prediction. This study can help us to understand how we make sense of the complex environment around us by combining different inputs to form predictions and signal unexpected events during surprising situations.
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Web resources: | https://cordis.europa.eu/project/id/844318 |
Start date: | 01-09-2019 |
End date: | 31-08-2022 |
Total budget - Public funding: | 246 669,61 Euro - 246 669,00 Euro |
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Original description
Detecting surprising events, such as the sudden approach of a predator or an unexpected touch, is crucial for the survival of all species. We aim to study neuronal mechanisms underlying surprising events. In order to predict upcoming events, mental models of future actions are essential. Where in the brain are such predictions and mental models created? The somatosensory cortex might contain a body model, in which superficial layers provide context and sensory memories, and inputs from deeper layers allow for simulating body movements. In rats, the somatosensory cortex is activated by tickling, which is a special form of unexpected touch containing elements of both sensory and social surprise. However, self-touch induces signals which prevent activation of the somatosensory cortex and prevent self-tickle. Where do these self-touch induced inhibitory signals come from? We hypothesize that the cerebellum is the source of self-touch induced signals. The cerebellum has reciprocal connections with key forebrain areas, including the somatosensory cortex. Combined with its known role in adapting action to sensory and internally generated events, the cerebellum seems well placed to aid in the processing of surprising events. We will test in mice and rats the hypothesis that the cerebellum plays a key role in processing unexpected events to modulate representations in somatosensory cortex. By combining the applicant’s experience in recordings from awake behaving mice, the expertise of the lab of Prof. Wang at Princeton University in cerebellar research with a focus on motor and non-motor function, and the expertise of the lab of Prof. Michael Häusser at University College London in naturalistic systems neuroscience, we are well placed to study the cerebellar signals for sensory prediction. This study can help us to understand how we make sense of the complex environment around us by combining different inputs to form predictions and signal unexpected events during surprising situations.Status
CLOSEDCall topic
MSCA-IF-2018Update Date
28-04-2024
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