A Proposed Circuit Computation in Basal Ganglia: History-Dependent Gain

Abstract

In this Scientific Perspectives we first review the recent advances in our understanding of the functional architecture of basal ganglia circuits. Then we argue that these data can best be explained by a model in which basal ganglia act to control the gain of movement kinematics to shape performance based on prior experience, which we refer to as a history-dependent gain computation. Finally, we discuss how insights from the history-dependent gain model might translate from the bench to the bedside, primarily the implications for the design of adaptive deep brain stimulation. Thus, we explicate the key empirical and conceptual support for a normative, computational model with substantial explanatory power for the broad role of basal ganglia circuits in health and disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Keywords: basal ganglia; bradykinesia; dopamine; mouse models; neural circuits.

Figure 1

Proposed functional architecture of basal ganglia. (a) Schematic of basal ganglia organization highlighting the parallel organization of both reentrant loop architecture (as in eference101 and the feed‐forward, convergent pathways discussed in this article. Whereas the reentrant loop circuits flow through the ascending basal ganglia output to thalamus (TH), the feed‐forward, convergent pathways flow through specific premotor (PM) structures in the midbrain and brain stem (more akin to the feed‐forward pathways in lower vertebrates102. (b) Detailed anatomical evidence for convergence of feed‐forward pathways. A rendering of a single corticofugal neuron in the anterior sensorimotor cortex and its axonal arborization through the entire mouse brain reconstructed using the method in reference36 and rendered with software developed by the MouseLight project (https://www.janelia.org/project-team/mouselight). Important brain regions discussed in the text are indicated. Striatum is cyan, deep layers of superior colliculus are pink, and the basal pontine nuclei are orange. (c) Fluorescent images in (i) and the front panel obtained from injection of a retrograde virus expressing fluorescent proteins in the dorsal striatum reveal cortical inputs and clearly illuminate the corticofugal pathway (intermingled axon bundles below thalamus). Modified from reference 29. Corticofugal axons can be followed in to the superior colliculus in a more posterior section (i). Comparison with tissue in which the substantia nigra pars reticulata was infected with an anterograde virus (ii) reveals convergent termination zones (indicated by arrows; image modified from data in reference 63). (d) Schematic diagram of cortical‐BG circuitry described in the text and focusing on the convergent pathways relevant to movements of the forelimb in mice (similar to recent proposals19. Labels on individual pathways represent terms in computation depicted in (e) and in the main text. r and r* describe the cortical output (eg, vector of firing rates) providing excitatory input to subcortical premotor structures (broadly defined) and striatum, respectively. As mentioned in the text, r and r* are correlated but not identical. The output of the direct and indirect pathway striatal projection neurons are expressed as an input‐output function (θ^i/d) of the cortical input (r*) multiplied by the synaptic strengths of corticostriatal inputs (W^i/d). The net output (R_out) — a motor command — reflects integration of basal ganglia output and direct cortical output (see main text for details). (e) Here we plot the predicted change in observed movement kinematics — a consequence of R _out — as a function of the cortical output, r. The shape of the curve is drawn for different ratios of average strength of the direct (W^d) and indirect (Wⁱ) corticostriatal synaptic strengths. When this becomes dramatically altered (ie, following dopamine depletion), the slope of the curves is dramatically reduced (dark red, dashed lines). We also annotate the specific changes in this computation that map to the clinically observed symptoms of bradykinesia (reduction in average speed) and akinesia (a paucity of movement; assuming R_out ≤ 0 results in an absence of movement). We note that the shape of the curves depends on nonlinearities in input‐output functions θ; for simplicity, here we assume the same nonlinearity modifies r* and r. Example simulations of models implementing this function can be found in references 56 and 63.

Figure 2

Regulation of movement vigor by opponent BG pathways. (a) Dopamine depletion from Parkinson's disease in patients (unmedicated patients with chronic DBS stimulators inactivate during the experiment) produces a robust slowing of movement across a broad range of movement vigor relative to control subjects (Ctrl). Modified from reference 9. Parkinsonian patients and controls were instructed to move a joystick to several distances indicated by an LED illuminated at the target eccentricity (example of a human VAO task). (b) Mice were required to perform a similar VAO task, moving a joystick to increasing amplitudes. Dopamine depletion in the MitoPark103 murine model of PD (“parkinsonian”) spares the ability to select and initiate the proper action, but reduces the speed of movement across a range of movement vigor. (c, d) Selective, closed‐loop optogenetic stimulation (pulsed for 450 milliseconds, < 10 milliseconds after movement onset) of direct pathway dSPNs (blue) or indirect pathway iSPNs (red) during the fastest‐reaching movements induces a cumulative shift in peak reach speed compared with control sessions (zero). Changes were a form of learning that persisted for tens of trials of the no‐stimulation recovery period. This effect extends to all reaches, not only those reaches during which stimulation occurred (as evidenced by a lack of change in in the width of the SEM bars throughout the session). The converse was observed when stimulation occurred during the slowest movements — direct pathway stimulation induced a slowing of movement, whereas indirect pathway stimulation induced a speeding of movement. Modified from reference 56.