Disuse-driven plasticity in the human thalamus and putamen

Abstract

Subcortical plasticity has mainly been studied using invasive electrophysiology in animals. Here, we leverage precision functional mapping (PFM) to study motor plasticity in the human subcortex during 2 weeks of upper-extremity immobilization with daily resting-state and motor task fMRI. We found previously that, in the cortex, limb disuse drastically impacts disused primary motor cortex functional connectivity (FC) and is associated with spontaneous fMRI pulses. It remains unknown whether disuse-driven plasticity pulses and FC changes are cortex specific or whether they could also affect movement-critical nodes in the thalamus and striatum. Tailored analysis methods now show spontaneous disuse pulses and FC changes in the dorsal posterior putamen and central thalamus (centromedian [CM], ventral-intermediate [VIM], and ventroposterior-lateral nuclei), representing a motor circuit-wide plasticity phenomenon. The posterior putamen effects suggest plasticity in stimulus-driven habit circuitry. Importantly, thalamic plasticity effects are focal to nuclei used as deep brain stimulation targets for essential tremor/Parkinson's disease (VIM) and epilepsy/coma (CM).

Keywords: CP: Neuroscience; disused; fMRI; motor plasticity; putamen; resting state; thalamus.

Figure 1.. Disuse-driven changes in FC of the left effector-specific primary somatomotor cortex to the subcortex

For each participant (left to right: Nico, Ashley, and Omar), individual-specific plasticity effect size (Cohen’s d) maps show changes in left SM1_ue FC during right (dominant) arm casting (pre cast). For reference, a Cohen’s d of 0.8 is generally considered a large effect size. Only significant effects after cluster correction at p < 0.05 (STAR Methods) are displayed. Note that Nico’s data were collected using an earlier pulse sequence with a repetition time (TR) that was twice as long (2.2 s) compared to that used for Ashley and Omar (1.1 s). Nico’s effect sizes are about half the size of those of the other participants. The FreeSurfer-based anatomical borders of the putamen and thalamus are shown as white outlines.

Figure 2.. Disuse pulse distribution in the cortex and subcortex

Spontaneous pulses detected in each of the participants (Nico, top; Ashley, center; Omar, bottom) are shown on an inflated rendering of the left cortical hemisphere (left) and subcortical axial slices (center, thalamic and cerebellar views). The color scale spans 2 s bracketing the average left SM1_ue pulse peak. The maps display the voxels with highest pulse detectability (top 20 %; STAR Methods). The participant-specific upper extremity somatomotor region is outlined in black (left). On the right, the individual (thin lines) and average (thick line) pulse time courses are shown (y axes, percent signal change) for the left SM1_ue, the left thalamus, and right cerebellum. The time course of each disuse pulse was modeled using a hemodynamic response function (HRF) (STAR Methods).

Figure 3.. Spatial overlap of FC increases and disuse pulses

The strongest disuse-driven FC increases (orange, cast > pre, cluster corrected) and disuse pulses (purple, top 20% threshold) as well as their overlap (green) are shown on the cortical surface (left) and in the thalamus and putamen (center) and cerebellum (right). Results are displayed on the lateral left hemisphere surface, medial left hemisphere surface, and two axial slices (MNI z = 5 and −21). White borders on axial slices define individual specific FreeSurfer-based anatomical structures (z = 5: putamen, globus pallidus, caudate, and thalamus; z = −21: cerebellum and hippocampus).

Figure 4.. Putaminal disuse-driven FC changes, pulses, and hand movement task fMRI activations

(A) Map of disuse-driven increases in FC with the left SM1_ue region of interest (top 30 % t-statistics). (B) Map of disuse pulses (top 30 % t-statistics). (C) Map of pre-casting task fMRI contrast: right hand movement vs. baseline (top 30% t-statistics). For all three maps, color scales are represented at the bottom of the map with maximum value at 99.5%. (D) Correlation between left putamen t-statistic maps for disuse-driven FC increases, pulse, and activation during hand movement (right hand vs. baseline). Correlations between unthresholded t-statistic maps were tested against individual-specific null distribution effects for each participant (top to bottom: Nico, Ashley, and Omar). Reported significant p < 0.05 corrected for false discovery rate (FDR; black asterisks).

Figure 5.. Thalamic disuse-driven FC changes, pulses, and hand movement task fMRI activations

(A) Map of disuse-driven increases in FC with left SM1_ue region of interest (top 30% t-statistics). (B) Map of disuse pulses (top 30% t-statistics). (C) Map of pre-casting task fMRI contrast: right hand movement vs. baseline (top 30% t-statistics). For all three maps, color scales are represented at the bottom of the map with maximum value at 99.5%. Nucleus borders from the Thalamus Optimized Multi Atlas Segmentation (THOMAS) atlas individual-based segmentation overlapping with the effects are shown in white. Four nuclei are outlined: CM (centromedian), VPL (ventro-posterior lateral), VIM (ventral intermediate), and MD-Pf (medio-dorsal). Average t-statistics values for all thalamic nuclei are represented in bar plots (Figure S12). (D) Correlation between left thalamic t-statistic maps for disuse-driven FC increases, pulses, and activations during hand movement (right hand vs. baseline). Correlations between unthresholded t-statistic maps were tested against individual-specific null distribution effects for each participant (top to bottom: Nico, Ashley, and Omar). Reported significant p < 0.05 corrected for FDR (black asterisks).