Intrinsic Disruption of the M1 Cortical Network in a Mouse Model of Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) disrupts motor performance by affecting the basal ganglia system. Yet, despite the critical position of the primary motor cortex in linking basal ganglia computations with motor performance, its contribution to motor disability in PD is largely unknown. The objective of this study was to characterize the role of the primary motor cortex in PD-related motor disability. METHODS: Two-photon calcium imaging and optogenetic stimulation of primary motor cortex neurons was done during performance of a dexterous reach-to-grasp motor task in control and 6-hydroxydopamine-induced PD mice. RESULTS: Experimental PD disrupted performance of the reach-to-grasp motor task and especially initiation of the task, which was partially restored by optogenetic activation of the primary motor cortex. Two-photon calcium imaging during task performance revealed experimental-PD affected the primary motor cortex in a cell-type-specific manner. It suppressed activation of output layer 5 pyramidal tract neurons, with greater effects on freeze versus nonfreeze trials. In contrast, it did not attenuate the initial movement-related activation response of layer 2/3 pyramidal neurons while diminishing the late inhibitory phase of their response. At the network level, experimental PD disrupted movement-related population dynamics of the layer 5 pyramidal tract network while almost not affecting the dynamics of the layer 2/3 neuronal population. It also disrupted short- and long-term robustness and stability of the pyramidal tract subnetwork, with reduced intertrial temporal accuracy and diminished reproducibility of motor parameter encoding and temporal recruitment of the output pyramidal tract neurons over repeated daily sessions. CONCLUSIONS: Experimental PD disrupts both external driving and intrinsic properties of the primary motor cortex. Motor disability in experimental PD results primarily from the inability to generate robust and stable output motor sequences in the parkinsonian primary motor cortex output layer 5 pyramidal tract subnetwork. © 2021 International Parkinson and Movement Disorder Society.

Network Fragility for Seizure Genesis in an Acute in vivo Model of Epilepsy.

Epilepsy affects over 50 million people worldwide and 30% of patients' seizures are medically refractory. The process of localizing and removing the epileptogenic zone is error-prone and ill-posed in part because we do not understand how epilepsy manifests. It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. If the fragility of the cortical network could be computed over a period in which seizure genesis occurs, then it might elucidate network mechanisms correlated to the epileptogenic zone. In this study, we used local field potentials (LFP) from neocortex by implementing an acute model of epilepsy in mice. These recordings were used to develop a dynamical network model that quantifies the fragility of the nodes from LFP epochs of baseline activity, preictal and ictal states. Fragility was quantified by the generation of a linear time-varying model to which we then applied a perturbation to determine the sensitivity of nodes in the network. Spatiotemporal fragility maps showed clear quantifiable changes in the epileptogenic network's properties throughout different states of seizure genesis. We quantified this difference over a baseline, preictal and ictal periods to show that network fragility is modulated in the manifestation of epilepsy.

Cell-Type-Specific Outcome Representation in the Primary Motor Cortex.

Adaptive movements are critical for animal survival. To guide future actions, the brain monitors various outcomes, including achievement of movement and appetitive goals. The nature of these outcome signals and their neuronal and network realization in the motor cortex (M1), which directs skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in the murine forelimb M1. We found two populations of layer 2-3 neurons, termed success- and failure-related neurons, that develop with training, and report end results of trials. In these neurons, prolonged responses were recorded after success or failure trials independent of reward and kinematics. In addition, the initial state of layer 5 pyramidal tract neurons contained a memory trace of the previous trial's outcome. Intertrial cortical activity was needed to learn new task requirements. These M1 layer-specific performance outcome signals may support reinforcement motor learning of skilled behavior.

Layer- and Cell-Specific Recruitment Dynamics during Epileptic Seizures In Vivo.

OBJECTIVE: To investigate the network dynamics mechanisms underlying differential initiation of epileptic interictal spikes and seizures. METHODS: We performed combined in vivo 2-photon calcium imaging from different targeted neuronal subpopulations and extracellular electrophysiological recordings during 4-aminopyridine-induced neocortical spikes and seizures. RESULTS: Both spikes and seizures were associated with intense synchronized activation of excitatory layer 2/3 pyramidal neurons (PNs) and to a lesser degree layer 4 neurons, as well as inhibitory parvalbumin-expressing interneurons (INs). In sharp contrast, layer 5 PNs and somatostatin-expressing INs were gradually and asynchronously recruited into the ictal activity during the course of seizures. Within layer 2/3, the main difference between onset of spikes and seizures lay in the relative recruitment dynamics of excitatory PNs compared to parvalbumin- and somatostatin-expressing inhibitory INs. Whereas spikes exhibited balanced recruitment of PNs and parvalbumin-expressing INs, during seizures IN responses were reduced and less synchronized than in layer 2/3 PNs. Similar imbalance was not observed in layers 4 or 5 of the neocortex. Machine learning-based algorithms we developed were able to distinguish spikes from seizures based solely on activation dynamics of layer 2/3 PNs at discharge onset. INTERPRETATION: During onset of seizures, the recruitment dynamics markedly differed between neuronal subpopulations, with rapid synchronous recruitment of layer 2/3 PNs, layer 4 neurons, and parvalbumin-expressing INs and gradual asynchronous recruitment of layer 5 PNs and somatostatin-expressing INs. Seizures initiated in layer 2/3 due to a dynamic mismatch between local PNs and inhibitory INs, and only later spread to layer 5 by gradually and asynchronously recruiting PNs in this layer. ANN NEUROL 2020;87:97-115.