Cholinergic control of striatal GABAergic microcircuits.

Cholinergic interneurons (CINs) are essential elements of striatal circuits and functions. Although acetylcholine signaling via muscarinic receptors (mAChRs) has been well studied, more recent data indicate that postsynaptic nicotinic receptors (nAChRs) located on striatal GABAergic interneurons (GINs) are equally critical. One example is that CIN stimulation induces large disynaptic inhibition of striatal projection neurons (SPNs) mediated by nAChR activation of GINs. Although these circuits are ideally positioned to modulate striatal output, the neurons involved are not definitively identified because of an incomplete mapping of CINs-GINs interconnections. Here, we show that CINs modulate four GINs populations via an intricate mechanism involving co-activation of presynaptic and postsynaptic mAChRs and nAChRs. Using optogenetics, we demonstrate the participation of tyrosine hydroxylase-expressing GINs in the disynaptic inhibition of SPNs via heterotypic electrical coupling with neurogliaform interneurons. Altogether, our results highlight the importance of CINs in regulating GINs microcircuits via complex synaptic/heterosynaptic mechanisms.

A behavioral paradigm for cortical control of a robotic actuator by freely moving rats in a one-dimensional two-target reaching task.

BACKGROUND: Controlling the trajectory of a neuroprosthesis to reach distant targets is a commonly used brain-machine interface (BMI) task in primates and has not been available for rodents yet. NEW METHOD: Here, we describe a novel, fine-tuned behavioral paradigm and setup which enables this task for rats in one-dimensional space for reaching two distant targets depending on their limited cognitive and visual capabilities compared to those of primates. An online transform was used to convert the activity of a pair of primary motor cortex (M1) units into two robotic actions. The rats were shaped to adapt to the transform and direct the robotic actuator toward the selected target by modulating the activity of the M1 neurons. RESULTS: All three rats involved in the study were capable of achieving randomly selected targets with at least 78% accuracy. A total of 9 out of 16 pairs of units examined were eligible for exceeding this success criterion. Two out of three rats were capable of reversal learning, where the mapping between the activity of the M1 units and the robotic actions were reversed. COMPARISON WITH EXISTING METHODS: The present work is the first demonstration of trajectory-based control of a neuroprosthetic device by rodents to reach two distant targets using visual feedback. CONCLUSION: The behavioral paradigm and setup introduced here can be used as a cost-effective platform for elucidating the information processing principles in the neural circuits related to neuroprosthetic control and for studying the performance of novel BMI technologies using freely moving rats.