The capacity for using external cues to guide behavior ("cue detection") constitutes an essential aspect of attention and goal-directed behavior. The cortical cholinergic input system, via phasic increases in prefrontal acetylcholine release, plays an essential role in attention by mediating such cue detection. However, the relationship between cholinergic signaling during cue detection and neural activity dynamics in prefrontal networks remains unclear. Here we combined subsecond measures of cholinergic signaling, neurophysiological recordings, and cholinergic receptor blockade to delineate the cholinergic contributions to prefrontal oscillations during cue detection in rats. We first confirmed that detected cues evoke phasic acetylcholine release. These cholinergic signals were coincident with increased neuronal synchrony across several frequency bands and the emergence of theta-gamma coupling. Muscarinic and nicotinic cholinergic receptors both contributed specifically to gamma synchrony evoked by detected cues, but the effects of blocking the two receptor subtypes were dissociable. Blocking nicotinic receptors primarily attenuated high-gamma oscillations occurring during the earliest phases of the cue detection process, while muscarinic (M1) receptor activity was preferentially involved in the transition from high to low gamma power that followed and corresponded to the mobilization of networks involved in cue-guided decision making. Detected cues also promoted coupling between gamma and theta oscillations, and both nicotinic and muscarinic receptor activity contributed to this process. These results indicate that acetylcholine release coordinates neural oscillations during the process of cue detection.

Cortico-basal ganglia-thalamic (CBT) neural circuits are critical modulators of cognitive and motor function. When compromised, these circuits contribute to neurological and psychiatric disorders, such as Parkinson's disease (PD). In PD, motor deficits correlate with the emergence of exaggerated beta frequency (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) oscillations throughout the CBT network. However, little is known about how specific cell types within individual CBT brain regions support the generation, propagation, and interaction of oscillatory dynamics throughout the CBT circuit or how specific oscillatory dynamics are related to motor function. Here, we investigated the role of striatal cholinergic interneurons (SChIs) in generating beta and gamma oscillations in cortical-striatal circuits and in influencing movement behavior. We found that selective stimulation of SChIs via optogenetics in normal mice robustly and reversibly amplified beta and gamma oscillations that are supported by distinct mechanisms within striatal-cortical circuits. Whereas beta oscillations are supported robustly in the striatum and all layers of primary motor cortex (M1) through a muscarinic-receptor mediated mechanism, gamma oscillations are largely restricted to the striatum and the deeper layers of M1. Finally, SChI activation led to parkinsonianlike motor deficits in otherwise normal mice. These results highlight the important role of striatal cholinergic interneurons in supporting oscillations in the CBT network that are closely related to movement and parkinsonian motor symptoms.E xaggerated beta oscillations (15-30 Hz) within the cortico-basal ganglia-thalamic (CBT) neural network are putative electrophysiological correlates of bradykinesia and rigidity in Parkinson's disease (PD) (1-4). Therapies that effectively manage PD motor symptoms, such as dopamine replacement therapy and deep brain stimulation, are associated with a suppression of the exaggerated beta oscillations (4, 5). Beta oscillations are also found in the CBT circuits of patients with other movement-related disorders, such as epilepsy and dystonia (6, 7), and in normal, nonhuman primates (8, 9) and normal rodents (10, 11). Moreover, brief elevations (≤200 ms) of beta oscillations are observed in the basal ganglia of task-performing nonhuman primates and rodents during specific phases of behavioral tasks (10, 12, 13), indicating that beta oscillations may be important for motor and nonmotor functions. In contrast to the regulated temporal variability of beta oscillations in normal motor functions, temporal stability is correlated with the parkinsonian motor symptoms of bradykinesia and rigidity (2). Together, these findings suggest that brief epochs of beta oscillations are a normal aspect of basal ganglia dynamics, their temporal modulation is important for movement regulation, and loss of regulation or uncontrolled expression of beta oscillations may contribute to movement deficits, such as those observed in PD.Despite the clear link bet...

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

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