Local circuit and projection based prefrontal response diversity for action control in rats

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Decisions about when to act are depend on external and internal factors. External factors relate to cues from the environment, while internal factors relate to a diverse set of previous experiences and resulting motivational or physical states. Subjects have to integrate these factors and flexibly adapt their behavior accordingly in order to maximize their success rate. These decisions are partially made in the prefrontal cortex (PFC) and have to be translated into action plans in motor cortical areas which directly send output signals to the spinal cord. Several pathways are candidates for the information transfer from PFC to motor cortical areas. In this project, we will focus on prefrontal-thalamic projections with a differentiation between the projections to the mediodorsal and the ventromedial thalamic nucleus (MD and VM). We aim to define whether there is a distinction between the information quality which is sent out from the medial PFC (mPFC) via these two routes and how this relates to the flexible formation of task-dependent and output-dependent ensembles in mPFC. For this we will conduct electrophysiological recordings in the prelimbic (PL) portion of the mPFC, and in the MD and VM during a motor preparation/inhibition task in rats. In this task, rats have to respond to an auditory signal with a lever release. By varying the required holding time and the reward scheme, we will probe which parameters are essential for the rats’ decision when to release. This will be modelled via a reinforcement learning approach to identify the rules according to which the rats act and which factors relate to neuronal responses and pathways. In order to elucidate circuit specific effects, we will selectively manipulate the pathways between the two structures by either blocking the PL-MD or PL-VM pathway. The data will be fed into a recurrent neural network (RNN) model to reveal neuronal activity rules which narrow down the complexity of neuronal responses and help explaining the neuronal flexibility of the mPFC. In line with the core hypothesis 1, we will investigate how patterns of temporal coordination (i.e. oscillatory bursts) dynamically organize prefrontal ensembles across the task in a decision and state dependent manner. We hypothesize that neuronal activity can be identified as neuronal ensembles defined by temporally organized spiking activity. In line with core hypothesis 2, we hypothesize that these prefrontal ensembles are at least partially defined through outputs to MD and VM.