Summary
Knowing the causal structure of a system enables controlling this system to our benefit. In neuroscience, the brain is widely envisioned as a complex controller whose main role is to help the organism reach and maintain itself into the most desirable states of its environment. However, not all environments are equally controllable and changes in environmental controllability require a permanent adaptation of cognitive and motor processes. Controllability estimation may thus play a key role in the regulation of action in health and disease, but its cognitive and neurobiological underpinnings remain poorly understood. Here, I will leverage a computational framework that I have recently developed to investigate in detail the neural implementation and the downstream consequences of controllability estimation for adaptive and maladaptive behaviours, with a particular focus on the serotonin (5-HT) system. My goal is to demonstrate that 5HT neurons broadcast controllability prediction errors and mediate the behavioural effects of controllability estimation in rodents and humans performing homologous tasks. To do so, I will record and manipulate the activity of genetically defined 5-HT neurons using light-based techniques and pharmacological manipulations. I will further test whether drug-naïve patients diagnosed with depression suffer from downward biases in controllability estimation and whether these biases can be alleviated by the initiation of serotonergic antidepressants. Finally, I will probe the neural mechanisms underlying controllability estimation mechanisms in healthy and depressed participants using functional neuroimaging. The ambition of this translational project is to untangle the complexities of 5-HT signalling and clarify its roles in depression and antidepressant treatments, which are still elusive despite decades of research. As such, it may provide new insights and predictive phenotyping tools for evidence-based approaches in neuropsychiatry.
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| Web resources: | https://cordis.europa.eu/project/id/101078795 |
| Start date: | 01-12-2023 |
| End date: | 30-11-2028 |
| Total budget - Public funding: | 1 483 738,75 Euro - 1 483 738,00 Euro |
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Original description
Knowing the causal structure of a system enables controlling this system to our benefit. In neuroscience, the brain is widely envisioned as a complex controller whose main role is to help the organism reach and maintain itself into the most desirable states of its environment. However, not all environments are equally controllable and changes in environmental controllability require a permanent adaptation of cognitive and motor processes. Controllability estimation may thus play a key role in the regulation of action in health and disease, but its cognitive and neurobiological underpinnings remain poorly understood. Here, I will leverage a computational framework that I have recently developed to investigate in detail the neural implementation and the downstream consequences of controllability estimation for adaptive and maladaptive behaviours, with a particular focus on the serotonin (5-HT) system. My goal is to demonstrate that 5HT neurons broadcast controllability prediction errors and mediate the behavioural effects of controllability estimation in rodents and humans performing homologous tasks. To do so, I will record and manipulate the activity of genetically defined 5-HT neurons using light-based techniques and pharmacological manipulations. I will further test whether drug-naïve patients diagnosed with depression suffer from downward biases in controllability estimation and whether these biases can be alleviated by the initiation of serotonergic antidepressants. Finally, I will probe the neural mechanisms underlying controllability estimation mechanisms in healthy and depressed participants using functional neuroimaging. The ambition of this translational project is to untangle the complexities of 5-HT signalling and clarify its roles in depression and antidepressant treatments, which are still elusive despite decades of research. As such, it may provide new insights and predictive phenotyping tools for evidence-based approaches in neuropsychiatry.Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
12-03-2024
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