Computational insights on asymmetrical and receptor-mediated chunking: implications for OCD and Schizophrenia

Area of Science:

• Neuroscience
• Computational Psychiatry
• Computational Neuroscience

Background:

• Repetitive thoughts and motor perseveration are hallmark symptoms of obsessive-compulsive disorder (OCD) and schizophrenia.
• These conditions involve altered dopamine D1 and D2 receptor function, impacting sequence learning and recall.
• Identifying start and stop points in cognitive and motor behaviors is crucial for understanding these disorders.

Purpose of the Study:

• To investigate how neural and striatal circuit parameters influence start/stop signaling in learned sequences.
• To extend a computational model simulating D1 and D2 striatal neuronal populations.

Main Methods:

• Utilized a published computational model within a reservoir computing framework.
• Simulated two distinct neuronal populations representing D1 and D2 striatal neurons.
• Analyzed the impact of asymmetric intra-network connection probabilities, synaptic weights, and differential time constants.

Main Results:

• Asymmetric intra-network connections and differential time constants contribute to signaling start/stop elements.
• Asymmetric coupling between D1 and D2 striatal populations proved beneficial for sequence boundary signaling.
• Dynamical differences and interactions between dopaminergic striatal populations play complementary roles in chunk boundary signaling.

Conclusions:

• Striatal D1 and D2 receptor dynamics and their interactions are critical for signaling sequence boundaries.
• Start and stop dichotomies can emerge from broader circuit dynamics, not solely from specialized neural connections.
• Computational modeling provides insights into the neural mechanisms underlying sequence processing deficits in psychiatric disorders.