Neural Circuits and Systems Neuroscience
Author: Marcos Antonio Coletti | Email: coletti.marcos@gmail.com
Marcos Coletti1°2°, Azul Silva1°2°, Gustavo Murer1°3°, Mariano Belluscio1°2°
1° Universidad de Buenos Aires, CONICET, Instituto de Fisiología y Biofísica Bernardo Houssay, Grupo de Neurociencia de Sistemas, Laboratorio Bases Neuronales del Comportamiento, Buenos Aires, Argentina
2° Universidad de Buenos Aires, Facultad de Medicina, Departamento de Ciencias Fisiológicas, Buenos Aires, Argentina
3° Universidad de Buenos Aires, CONICET, Instituto de Fisiología y Biofísica Bernardo Houssay, Grupo de Neurociencia de Sistemas, Laboratorio de Fisiología de Circuitos Neuronales, Buenos Aires, Argentina
Midbrain dopamine neurons (DAn), especially those in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc), play a crucial role in modulating reward-related behaviors.
While several studies analyze the DAn activity during tasks guided by predictive cues, the dynamics of their activity during self-initiated tasks remain less understood. Addressing this knowledge gap is important since self-initiated actions are a fundamental aspect of adaptive behavior, requiring the integration of internal and external signals to guide decisions without external cues.
In this study we explored DAn activity during a self-paced task where rats autonomously initiated a sequence of actions to obtain a reward. Through in vivo electrophysiological recordings we registered and characterized neuronal activity during different phases of the task, focusing on action initiation, timing, and outcome anticipation.
Preliminary findings suggest that DAn in the VTA encode anticipatory signals linked to task initiation, indicating their critical role in the timing and preparation of self-initiated actions. This activity is modulated by the duration of the waiting period before action initiation and resembles the temporal coding observed in the striatum during similar tasks.
These findings reveal an important role for DAn in integrating temporal information and reward outcomes, providing a deeper understanding of the neural mechanisms underlying decision-making and adaptive behavior.