Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in alleviating movement disability in patients with Parkinson's disease (PD). However, its therapeutic mechanism of action is unknown. The healthy striatum exhibits rich dynamics resulting from an interaction of beta, gamma, and theta oscillations. These rhythms are essential to selection and execution of motor programs, and their loss or exaggeration due to dopamine (DA) depletion in PD is a major source of behavioral deficits. Restoring the natural rhythms may then be instrumental in the therapeutic action of DBS. We develop a biophysical networked model of a BG pathway to study how abnormal beta oscillations can emerge throughout the BG in PD and how DBS can restore normal beta, gamma, and theta striatal rhythms. Our model incorporates STN projections to the striatum, long known but understudied, found to preferentially target fast-spiking interneurons (FSI). We find that DBS in STN can normalize striatal medium spiny neuron activity by recruiting FSI dynamics and restoring the inhibitory potency of FSIs observed in normal conditions. We also find that DBS allows the reexpression of gamma and theta rhythms, thought to be dependent on high DA levels and thus lost in PD, through cortical noise control. Our study highlights that DBS effects can go beyond regularizing BG output dynamics to restoring normal internal BG dynamics and the ability to regulate them. It also suggests how gamma and theta oscillations can be leveraged to supplement DBS treatment and enhance its effectiveness.

Algebraic approach for subspace decomposition and clustering of neural activity.

We developed an approach to decompose neuronal signals into disjoint components, corresponding to task- or event-based epochs. This protocol describes how to project behavioral templates onto a low-dimensional subspace of neuronal responses to derive neuronal templates, then how to decompose and cluster neuronal responses using these derived templates. We outline these steps on complementary datasets of calcium imaging and spiking activity. Our approach relies on fundamental, linear algebraic principles and is adaptive to the temporal structure of the neural data. For complete details on the use and execution of this protocol, please refer to Adam et al. (2022).1.

Dynamic control of visually guided locomotion through corticosubthalamic projections.

Goal-directed locomotion requires control signals that propagate from higher order areas to regulate spinal mechanisms. The corticosubthalamic hyperdirect pathway offers a short route for cortical information to reach locomotor centers in the brainstem. We developed a task in which head-fixed mice run to a visual landmark and then stop and wait to collect the reward and examined the role of secondary motor cortex (M2) projections to the subthalamic nucleus (STN) in controlling locomotion. Our behavioral modeling, calcium imaging, and optogenetics manipulation results suggest that the M2-STN pathway can be recruited during visually guided locomotion to rapidly and precisely control the pedunculopontine nucleus (PPN) of the mesencephalic locomotor region through the basal ganglia. By capturing the physiological dynamics through a feedback control model and analyzing neuronal signals in M2, PPN, and STN, we find that the corticosubthalamic projections potentially control PPN activity by differentiating an M2 error signal to ensure fast input-output dynamics.