Epidural cerebellar stimulation drives widespread neural synchrony in the intact and stroke perilesional cortex

Abstract

Background: Cerebellar electrical stimulation has shown promise in improving motor recovery post-stroke in both rodent and human studies. Past studies have used motor evoked potentials (MEPs) to evaluate how cerebellar stimulation modulates ongoing activity in the cortex, but the underlying mechanisms are incompletely understood. Here we used invasive electrophysiological recordings from the intact and stroke-injured rodent primary motor cortex (M1) to assess how epidural cerebellar stimulation modulates neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics.

Methods: We recorded single unit spiking and local field potentials (LFPs) in both the intact and acutely stroke-injured M1 contralateral to the stimulated cerebellum in adult Long-Evans rats under anesthesia. We analyzed changes in the firing rates of single units, the extent of synchronous spiking and power spectral density (PSD) changes in LFPs during and post-stimulation.

Results: Our results show that post-stimulation, the firing rates of a majority of M1 neurons changed significantly with respect to their baseline rates. These firing rate changes were diverse in character, as the firing rate of some neurons increased while others decreased. Additionally, these changes started to set in during stimulation. Furthermore, cross-correlation analysis showed a significant increase in coincident firing amongst neuronal pairs. Interestingly, this increase in synchrony was unrelated to the direction of firing rate change. We also found that neuronal ensembles derived through principal component analysis were more active post-stimulation. Lastly, these changes occurred without a significant change in the overall spectral power of LFPs post-stimulation.

Conclusions: Our results show that cerebellar stimulation caused significant, long-lasting changes in the activity patterns of M1 neurons by altering firing rates, boosting neural synchrony and increasing neuronal assemblies' activation strength. Our study provides evidence that cerebellar stimulation can directly modulate cortical dynamics. Since these results are present in the perilesional cortex, our data might also help explain the facilitatory effects of cerebellar stimulation post-stroke.

Keywords: Cerebellum; Epidural direct current stimulation; Motor cortex; Neural plasticity.

Fig. 1

Diversity in firing rate response of M1 units after cerebellar stimulation. a Direct current stimulation was applied to the cerebellum while neural activity of contralateral M1 was recorded using an electrode array. b Example of either a significant increase (orange) or decrease (purple) in firing rate after cerebellar stimulation (p < 0.05). Top panel shows waveforms and the distribution of inter-spike interval of respective units (100 representative waveforms are plotted for each unit and the inter-spike interval is from full recording period). The dotted lines represent the mean from Stim_pre. c Violin plot showing the change in firing rate from Stim_pre to Stim_post across all neurons. d Percentage of positively (M⁺) or negatively (M⁻), and non-modulated (NM) units across all animals

Fig. 2

M1 coincident firing is strengthened post cerebellar stimulation. a Raster plots depicting changes in correlated activity among M1 units from Stim_pre to Stim_post. b Representative cross-correlogram of a pair of M1 units, before and after cerebellar stimulation. c Mean changes in Δ_CCH are shown as mean ± s.e.m. across four animals. *p < 1 × 10^–67

Fig. 3

Changes in neural synchrony are unrelated to firing rate changes. Regression analysis of the mean ΔCCH change from Stim_pre to Stim_post for a neuron with all other neurons with similar modulation in a rat (labeled Mean (ΔCCH_post − ΔCCH_pre)) compared to the same neuron’s firing rate change from Stim_pre to Stim_post is shown. a Regression for M⁺ neurons firing rate change and correlation change. b Similar regression for M⁻ neurons and c for NM neurons are shown

Fig. 4

Activation of M1 ensembles before and after cerebellar stimulation. a Correlation matrix eigenvalues calculated from spontaneous activity prior to cerebellar stimulation. The dashed line is the signal threshold (λ_max), defined as the theoretical upper bound for a randomized spike train. Three PCs have eigenvalues greater than λ_max. b The weight of each neuron contributing to the first principal component (or ensemble) in a. c Example of activation events of an M1 ensemble prior to and after cerebellar stimulation (i.e., Stim_pre and Stim_post). d Across all animals, there was a significantly stronger activation of M1 ensembles post stimulation (average of top 20th percentile activation events in Stim_pre and Stim_post blocks, *p < 10^–115)

Fig. 5

Power spectrum analyses of M1 LFP. a An example of LFP traces from three channels in an animal. b An example LFP power from a single animal, before and after cerebellar stimulation. Grey shaded area shows the slow frequency band (0.3–4 Hz). Inset, the average LFP power in the slow frequency band across animals. No significant changes were observed in this frequency band (p = 0.69)

Fig. 6

M1 activity during epidural cerebellar stimulation. a An example M1 unit showing modulation during stimulation (left). Its waveform and inter-spike interval histogram is shown (right). b Violin plot showing firing rate change between Stim_pre and Stim_dur across all high-amplitude M1 units. c Representative cross-correlogram of a pair of M1 units, before and during cerebellar stimulation (left). Mean change in the Δ_CCH is shown as mean ± s.e.m., across 4 animals (right). d Change in LFP power from a single animal before and during cerebellar stimulation (left). Grey shaded area shows the slow frequency band (0.3–4 Hz). On the right is the average LFP power in the slow frequency band across all animals (right, *p < 1 × 10^–2; Stim_pre power is same in Fig. 5 but y-axis scale is adjusted to accommodate Stim_dur power)

Fig. 7

Activity in post-stroke peri-infarct M1 during cerebellar stimulation. a A schematic of electrophysiological recordings in stroke peri-infarct M1 and cerebellar stimulation (left). A histology image with Fluoro-Jade C staining showing the sagittal view of stroke area and the site of electrophysiologcal recordings. b Mean Stim_pre firing rate of intact and stroke animals is shown as mean ± s.e.m. (Str: stroke; **p < 5 × 10^-8). c An example peri-infarct M1 unit showing modulation during stimulation (bottom). Its waveform and inter-spike interval histogram is also shown. d Violin plot showing firing rate change between Stim_pre and Stim_dur across all high-SNR peri-infarct M1 units. e Representative cross-correlogram of a pair of peri-infarct M1 units, before and during cerebellar stimulation (left). Mean change in Δ_CCH is shown as mean ± s.e.m., across four animals (right). f An example LFP power from a single animal before and during cerebellar stimulation (left). Grey shaded area shows the slow frequency band (0.3–4 Hz). The average LFP power in the slow frequency band across four animals is shown on the right side, *p < 1 × 10^–2

Fig. 8

Activity in post-stroke peri-infarct M1 after cerebellar stimulation. a An example peri-infarct M1 unit showing modulation after cerebellar stimulation (bottom). Its waveform and inter-spike interval histogram is also shown (top). b Violin plot showing firing rate change between Stim_pre and Stim_post across all peri-infarct M1 units (left) and percentage of M⁺, M⁻ and NM units across all stroke animals (right). c Representative cross-correlogram of a pair of peri-infarct M1 units, before and during cerebellar stimulation (left). Mean change in Δ_CCH is shown as mean ± s.e.m., across four animals (right). *p < 5 × 10^–2. d An example LFP power from a single animal before and after cerebellar stimulation (left). Grey shaded area shows the slow frequency band (0.3–4 Hz). The average LFP power in the slow frequency band across four animals is shown in the inset (Stim_pre power is same as the Fig. 7 but y-axis is adjusted)