Oscillations in sensorimotor cortex in movement disorders: an electrocorticography study

Abstract

Movement disorders of basal ganglia origin may arise from abnormalities in synchronized oscillatory activity in a network that includes the basal ganglia, thalamus and motor cortices. In humans, much has been learned from the study of basal ganglia local field potentials recorded from temporarily externalized deep brain stimulator electrodes. These studies have led to the theory that Parkinson's disease has characteristic alterations in the beta frequency band (13-30 Hz) in the basal ganglia-thalamocortical network. However, different disorders have rarely been compared using recordings in the same structure under the same behavioural conditions, limiting straightforward assessment of current hypotheses. To address this, we utilized subdural electrocorticography to study cortical oscillations in the three most common movement disorders: Parkinson's disease, primary dystonia and essential tremor. We recorded local field potentials from the arm area of primary motor and sensory cortices in 31 subjects using strip electrodes placed temporarily during routine surgery for deep brain stimulator placement. We show that: (i) primary motor cortex broadband gamma power is increased in Parkinson's disease compared with the other conditions, both at rest and during a movement task; (ii) primary motor cortex high beta (20-30 Hz) power is increased in Parkinson's disease during the 'stop' phase of a movement task; (iii) the alpha-beta peaks in the motor and sensory cortical power spectra occur at higher frequencies in Parkinson's disease than in the other two disorders; and (iv) patients with dystonia have impaired movement-related beta band desynchronization in primary motor and sensory cortices. The findings support the emerging hypothesis that disease states reflect abnormalities in synchronized oscillatory activity. This is the first study of sensorimotor cortex local field potentials in the three most common movement disorders.

Figures

Figure 1

Method of localization of subdural recording electrodes (from Subject PD-7). (A and B) Intended location of middle of 6-contact recording strip (white arrows) over presumed M1, 3 cm from the midline, on axial (A) and parasagittal (B) images from the preoperative planning MRI. (C and D) Actual location of the recording strip, shown on intra-operative CT, computationally fused to preoperative MRI and reformatted in a parasagittal plane through the recording strip. Images are windowed to optimize visualization of bone and metal contacts (C) or to show the contacts blended onto the preoperative MRI (D). Contacts C1 and C5 are labelled in C (contact C6 is out-of-plane and not visible). White arrows indicate presumed M1 as in A and B. (E) Alternative means of confirming anatomic location of recording strip, using intra-operative two-dimensional lateral X-ray. A radio-opaque marker (black arrow) is sutured to the scalp along a trajectory (dotted black line) that passes through anatomic M1 and terminates at the intended deep brain stimulator electrode tip location. Intersection of the trajectory with the subdural recording strip shows the anteroposterior localization of the contacts with respect to the preoperative MRI. (F) Somatosensory-evoked potentials used to physiologically localize the contacts with respect to the central sulcus. Stimulation of the median nerve is performed at time zero (black arrow). Bipolar somatosensory-evoked potential recordings are stacked from anterior (top trace) to posterior (bottom trace). The downward direction is negative. For each bipolar pair, the posterior contact of the pair is ‘active’ while the anterior contact is ‘reference’. The most posterior contact pair with a negative N20 waveform in this example is the 3–4 pair, localizing contact 3 to M1, immediately anterior to central sulcus.

Figure 2

M1 local field potential recordings and their power spectra in the resting state. (A) Examples of 1-s recordings from M1 in each disease state. (B) Log power spectral density 4–100 Hz for each example in A, from a 30-s recording. (C) Log power spectral density 5–35 Hz for each example in A, with the frequency corresponding to alpha–beta peak power indicated with an arrow. (D) Box plot of frequencies at which the alpha–beta peak occurred across 10 subjects in each disease group. Horizontal line = median, box = 25th and 75th percentiles, ‘whiskers’ = range of values. Dys = Dystonia; ET = essential tremor; PD = Parkinson's disease.

Figure 3

Cortical resting state power spectral density grouped over all subjects in each disease state. (A) Schematic drawing of the relation of the cortical bipolar recording pairs to the underlying frontal and parietal gyri and sulci. (B) Method of comparing spectral power across disease states. For each individual subject, the mean log power in each of four frequency bands (low beta, high beta = blue; low gamma, high gamma = orange) was calculated, and grouped data were compared statistically. (C) Mean (±SEM) log power 4–100 Hz for the three disease states, for the four bipolar pairs covering primary sensory, primary motor and premotor cortices as illustrated in A. The yellow bars indicate frequency bands for which mean log power in Parkinson's disease (PD) was significantly different from both dystonia (Dys) and essential tremor (ET) disease groups, and the P-value corresponds to a one-way ANOVA for overall difference in mean log power in the relevant bands. Only contact pairs that included M1 showed a significant difference (PD > Dys and PD > ET), and only low gamma and high gamma bands showed this difference. (D) Lack of a ‘stun effect’ of lead insertion on resting state cortical power in subjects with Parkinson's disease. Thick red line = mean log power spectral density prior to lead insertion; thin black line = mean log power spectral density following insertion of 1.2 mm diameter deep brain stimulator lead through the motor territory of subthalamic nucleus.

Figure 4

(A) Example local field potential (LFP) recordings from individual subjects with Parkinson's disease (PD, left), dystonia (centre) and essential tremor (ET, right). The local field potential (top row) is shown with simultaneously recorded forearm EMG (bottom row). Recording duration is 4 s, centred on the start of movement. (B) Time varying log power spectral density for the same subjects as in A, averaged over five stop/move epochs. The colour scale represents the change in power spectral density from the baseline period, defined as 2 to 1 s prior to onset of EMG activity. Vertical dotted line indicates the start of movement. (C) Time-varying power spectral density during the elbow movement task, showing data pooled across all subjects in each disease group (nine subjects per group) and represented as a Z-score. For visual clarity, the Z-scores are thresholded so that Z-scores between −1 and 1 are all assigned the neutral (grey) colour. (D) Movement related change in power (log power move phase-log power stop phase), over the 4–100 Hz range, utilizing the 2 s epochs beginning 0.5 s after the start of the move or stop phases. The red, blue and green lines show the mean log power change in subjects with Parkinson's disease, dystonia and essential tremor, respectively. The dotted lines (and colour shading) indicate ±SEM. The asterisks indicate the frequencies at which the disease groups differed, at a significance threshold of P = 0.002 (corresponding to an uncorrected threshold of 0.05, with Bonferroni correction). (E) Mean power 13–30 Hz normalized to baseline (2 to 1 s prior to the EMG-defined start of movement) as a function of time (time resolution of 50 ms), in an individual subject with Parkinson's disease. The onset of beta band power decrease (vertical arrow) was defined as the time at which mean beta power crossed the threshold of 3 SD of the mean power during the reference period (horizontal red-dotted lines). (F) Mean (±SEM) time of onset of movement-related beta decrease, relative to start of EMG activity, did not differ between groups (one-way ANOVA P = 0.909). NS = not significant.

Figure 5

Movement-related change in M1 (top) and S1 (bottom) local field potential log power over all subjects, for each of the five movement tasks (hand, elbow, shoulder, jaw and foot) for mean beta band (13–30 Hz) log power (left column) and mean gamma band (76–100 Hz) log power (right column). Error bars represent ±SEM. Statistical details are provided in the ‘Results’ section.

Figure 6

Cortical power spectral density grouped over all subjects in each disease state, during the stop (left column) and move (right column) phases of the motor task (illustrated here for elbow movement). The lines in each plot show mean (±SEM) log power over 4–100 Hz for the three disease states, for the four bipolar pairs covering primary sensory, primary motor and premotor cortices. The coloured bars indicate frequency bands for which mean log power in Parkinson's disease (PD) was significantly different from both dystonia (Dys) and essential tremor (ET) disease groups (yellow bars = low and high gamma bands, blue bars = high beta band), and the P-value corresponds to a one-way ANOVA for overall difference in mean log power in the relevant bands. Only contact pairs that included M1 showed a significant difference (PD > Dys and PD > ET). Details similar to Fig. 3A–C.