Multimodal EEG analysis in man suggests impairment-specific changes in movement-related electric brain activity after stroke

Transcription

1 Brain (2000), 123, Multimodal EEG analysis in man suggests impairment-specific changes in movement-related electric brain activity after stroke T. Platz, 1 I. H. Kim, 1 H. Pintschovius, 1 T. Winter, 1 A. Kieselbach, 1 K. Villringer, 2 R. Kurth 2 and K.-H. Mauritz 1 1 Klinik Berlin, Department of Neurological Rehabilitation, Correspondence to: Dr T. Platz, Klinik Berlin, Kladower Freie Universität and 2 Department of Radiology, Damm 223, Berlin, Germany Universitätsklinikum Benjamin Franklin, Freie Universität Berlin, Germany Summary Movement-related slow cortical potentials and eventrelated desynchronization of alpha (alpha-erd) and beta (beta-erd) activity after self-paced voluntary triangular finger movements were studied in 13 ischaemic supratentorial stroke patients and 10 age-matched control subjects during movement preparation and actual performance. The stroke patients suffered from central arm paresis (n 8), somatosensory deficits (n 3) or ideomotor apraxia (n 2). The multimodal EEG analysis suggested impairment-specific changes in the movementrelated electrical activity of the brain. The readiness potential of paretic subjects was centred more anteriorly and laterally; during movement, they showed increased beta-erd at left lateral frontal recording sites. Patients with somatosensory deficits showed reduced alpha-erd and beta-erd during both movement preparation and actual performance. Patients with ideomotor apraxia showed more lateralized frontal movement-related slow cortical potentials during both movement preparation and performance, and reduced left parietal beta-erd during movement preparation. We conclude that (i) disturbed motor efference is associated with an increased need for excitatory drive of pyramidal cells in motor and premotor areas or an attempt to drive movements through projections from these areas to brainstem motor systems during movement preparation; (ii) an undisturbed somatosensory afference might contribute to the release of relevant cortical areas from their idling state when movements are prepared and performed; and (iii) apraxic patients have a relative lack of activity of the mesial frontal motor system and the left parietal cortex, which is believed to be part of a network subserving ideomotor praxis. Keywords: event-related desynchronization; arm; apraxia; hemiparesis; deafferentation Abbreviations: alpha-erd event-related desynchronization of alpha activity; beta-erd event-related desynchronization of beta activity; HEOG horizontal electrooculogram; MRP movement-related DC potentials; PCA principal components analysis; VEOG vertical electrooculogram Introduction Stroke in man can result in different impairments affecting motor control, such as central paresis, deafferentation, apraxia, visuoconstructional deficits and neglect. Even simple movements indicate different behavioural disturbances for each of these impairments. For example, hemiparesis results, even after clinical recovery, in reduced efficiency of various basic motor abilities, such as aiming, dexterity and steadiness (Platz et al., 1999); while these patients are able to perform most motor tasks, they still show an increased demand for time and corrections (Platz et al., 1994). It seems that the final efferent pathway that is affected (the pyramidal tract) causes behavioural deficiencies in different aspects of basic Oxford University Press 2000 motor control. Deafferentation, on the other hand, seems to affect especially the feedback-guided aspects of basic motor control, e.g. the homing-in phase of aimed movements, which guarantees final precision (Platz and Mauritz, 1997), and the ability to maintain a constant force with static motor tasks (Rothwell et al., 1982). Ideomotor apraxia affects motor behaviour at a higher level of organization. The spatiotemporal characteristics of the movements of ideomotor apraxic patients are altered qualitatively; for example, they are unable to reproduce the characteristic features of gestures flawlessly (Poizner et al., 1990; Platz and Mauritz, 1995). In addition to learning about the behavioural consequences

2 2476 T. Platz et al. of stroke, it is of interest to assess any related changes in the functional activity of the brain. Activation studies with imaging techniques have indicated functional cortical reorganization after motor stroke (Brion et al., 1989; Chollet et al., 1991; Weiller et al., 1992; Cramer et al., 1997; Cao et al., 1998; Seitz et al., 1999); movements of the recovered, formerly paretic hand after stroke were shown to be associated with bilateral activation of the motor and non-motor association cortex and the contralateral cerebellum, in addition to areas symmetrical to those activated by movements of the unaffected hand, i.e. the primary sensorimotor cortex. The aim of the present study was to describe the electrophysiological correlates of changed cerebral motor control in different clinical impairments after stroke, namely hemiparesis, deafferentation and ideomotor apraxia, by means of multimodal EEG. The high temporal resolution of this technique a few milliseconds allows the separate assessment of brain activity related to movement preparation and movement execution. In addition, different electrical activities of the brain can be analysed from a given data set: slow movement-related DC potentials (MRPs) and event-related desynchronization (ERD) of rhythmic brain activity, at frequencies in both the alpha band (alpha-erd) and beta band (beta-erd). These different analyses reveal different patterns of spatiotemporal cerebral activation related to movement, and might therefore reflect different neural mechanisms related to motor control. Movement-related slow cortical potentials are generated by the coherent synaptic activity of cortical neurones; excitatory postsynaptic potentials at the apical dendrites of pyramidal cells with their source in deeper layers near or at the soma are the most likely candidates for the generation of these slow cortical potentials (Bierbaumer et al., 1990). Shifts in slow negative MRPs start ~1.5 s before movement onset [negativity of Bereitschaft (readiness)], with a fairly wide bilateral distribution and a maximum at the midline close to the vertex, at least with self-paced, consciously performed finger movements. They become more lateralized shortly before and during movement, with maxima at recording sites overlying the sensorimotor cortex contralateral to the moving hand (negativity of performance). MRPs have been shown to be modified in amplitude and distribution in relation to specific task demands (Kornhuber and Deecke, 1965; Lang et al., 1994). Apart from these slow potential changes, rhythmic sensorimotor activity in the alpha and beta bands becomes desynchronized as early as 2 s before movement onset; desynchronization continues during movement. Early alpha- and beta-erd in the preparatory period before movement onset has been described as more lateralized than ERD during movement or MRPs during movement preparation (Pfurtscheller and Berghold, 1989; Pfurtscheller and Neuper, 1994; Stancák and Pfurtscheller, 1996). The central beta rhythm has a slightly more anterior focus than the central alpha rhythm, indicating different expression of these rhythmic brain activities in the motor and somatosensory cortex (Pfurtscheller et al., 1994; Salmelin et al., 1995). Characteristic of rhythms within the alpha and lower beta band, occurring not only over the sensorimotor area but also over visual and auditory cortex, is their blockade (or ERD) when the corresponding area becomes activated. This might indicate a shift from an idling to an active state of cortical areas involved in a given task (Pfurtscheller and Neuper, 1994). Neurally, desynchronized alpha-band activity is believed to be a correlate of increased cellular excitability in interconnected thalamocortical systems (Steriade and Llinas, 1988). Thus, it might be assumed that ERD reflects changes in local interactions between pyramidal neurones and interneurones controlling the frequency components of the EEG, while slow movement-related potentials would represent the response of cortical neurones to afferent signals (Pfurtscheller and Lopes da Silva, 1999). In the present study, two approaches were combined: (i) the assessment of different subgroups of stroke patients with clinically distinct impairments; and (ii) the multimodal EEG analysis of movement-related brain activity with high time resolution, providing comprehensive information about the electrical activity of the brain before and during movement. This combination was chosen to explore the possibility of impairment-specific changes in movement-related electrical activity of the brain after stroke. The study should answer the question whether any changes in the electrical activity of the brain (MRP, alpha-erd and/or beta-erd) occur in stroke patients immediately before and/or during simple movements, and whether any of these changes are associated with a particular impairment of interest (hemiparesis, deafferentation, ideomotor apraxia). Material and methods Subjects Ten healthy subjects (five female and five male; mean age 54.3 years, SD 5.1 years) served as a reference group. They had no history of brain disease, no clinical signs of central or peripheral nervous system disorder, and no orthopaedic conditions relevant to upper extremity movements. Between 1996 and 1999, we recruited 13 patients after a first unilateral supratentorial ischaemic stroke in the subacute to early chronic phase during inpatient rehabilitation treatment at the department of neurological rehabilitation of the Freie Universität, Berlin (for patient details, see Table 1). The patients mean age was 54.9 years (SD 6.5 years) and, on average, they were investigated 8.8 weeks (SD 7.3 weeks) after stroke. Patients were selected if they belonged to any of three groups of interest at the time of the investigation, i.e. if they presented with (i) mild to moderate central arm paresis without somatosensory deficits [referred to here as the hemiparesis (HE) group]; (ii) somatosensory deficits of the arm (reduced sensation to light touch and/or positional change) but without signs of overt paresis ( deafferentation (SE) group]; or (iii) ideomotor apraxia, as ascertained by

3 Movement-related brain activity after stroke 2477 Table 1 Characteristics of stroke patients Patient Age Gender Time after Cerebral lesion Group Clinical presentation (years) stroke (weeks) P.E. 57 M 6 L posterior limb of internal capsule, HE-R Mild to moderate paresis, putamen, extending laterally normal sensation G.U. 53 F 20 L anterior and posterior limb of internal HE-R Moderate paresis, normal capsule, extending laterally sensation M.U. 50 M 9 L posterior limb of internal capsule HE-R Mild to moderate paresis, normal sensation B.E. 58 M 6 Incomplete L MCA stroke, affecting frontal HE-R Mild to moderate paresis, areas normal sensation G.R. 66 M 4 R posterior limb of internal capsule, HE-L Mild to moderate paresis, putamen, white matter under precentral gyrus normal sensation S.T.A. 61 F 12 R putamen and head of caudate, anterior HE-L Mild to moderate paresis, limb of internal capsule normal sensation M.O. 49 M 4 R posterior limb of internal capsule HE-L Mild hemiparesis, normal sensation G.A. 58 M 3 R posterior limb of internal capsule HE-L Mild hemiparesis, normal sensation P.A. 47 M 7 R inferior frontal and postcentral gyrus SE-L Moderate reduction of LT, TH and ST H.E. 59 M 6 R posterior part of posterior limb of internal SE-L Mild reduction of LT and TH capsule S.T.E. 55 M 5 R thalamus SE-L Moderate reduction of LT, TH, PS and ST K.L. 59 M 28 Incomplete L MCA stroke, predominantly IM Mild ideomotor apraxia, nontemporal and lower frontal and parietal areas fluent aphasia, mild sensorimotor paresis S.A. 42 F 5 Incomplete L MCA stroke, predominantly IM Moderate ideomotor apraxia, temporal and lower frontal and parietal areas global aphasia, mild sensorimotor paresis F female; M male; R right hand affected; L left hand affected; HE hemiparesis; SE somatosensory deficits; IM ideomotor apraxia; LT sense of light touch; TH thermal sense; PS position sense; ST stereognosis. typical parapraxic performance errors with symbolic and non-symbolic gestures after verbal command and with imitation (Platz and Mauritz, 1995) when the non-paretic ipsilesional arm was tested [ ideomotor apraxia (IM) group]. The patients had to be able to perform the experimental task (see below) in order to be included in the study. All subjects gave informed consent to participation in the study, which had received approval from the Ethics Committee of the Freie Universität Berlin. Procedure Motor tasks A triangular trajectory movement was performed by the subject s index finger. This movement was chosen because it has been shown previously to be sensitive to motor control deficits in both hemiparetic and apraxic patients, i.e. it reflects both motor execution and cognitive motor aspects of motor control (Platz et al., 1994; Platz and Mauritz, 1995). The triangular movement consisted of a movement from the resting position upwards and outwards to a position that represented the tip of a triangle; from there downwards and outwards to the outer angle; and then back to the starting position, which represented the inner angle of an imagined triangle. The triangular movement was performed twice in sequence with a target rate of 1 Hz for single movement elements, resulting in a movement time of ~6 s. Only one finger was moved at any time, all other fingers resting on the plate. Movements were self-initiated, and the interval between movement sequences was intended to range from 8 to 16 s. Subjects were requested not to move their eyes before and during movements, but to look at a fixation point. Five blocks of movements, each with 30 task repetitions, were recorded (for control subjects there were five blocks for each hand, the hands being alternated after each block). Hemiparetic patients and deafferented patients performed the motor task with their affected hand, i.e. the hand contralateral to the affected half of the brain. Ideomotor apraxic patients performed the task with their ipsilesional (left) hand to avoid any confounding by paresis or somatosensory deficits affecting the contralesional hand. The healthy control subjects performed the task with either hand. The motor tasks were performed with the subject s moving hand positioned on a plate; an integrated touch-switch underneath the index finger generated an 8 bit electrical impulse when it was lifted. These impulses were recorded simultaneously with the surface EMG over the extensor digitorum communis muscle and the EEG. In addition, data from a 2D miniature accelerometer (model EGAXT2-C-5; Entran, Fairfield, NJ, USA), fixed to the tip of the index

4 2478 T. Platz et al. Fig. 1 Electrode positions on a standardized realistic head model reconstructed from an MRI when viewed from above. The same view is used in Figs 2 5. The electrodes are positioned according to the extended international system. finger, was recorded with a 500 Hz analogue digital (AD) conversion rate. These data were analysed off-line. We recorded the intra-individual mean and coefficient of variation for the duration of the triangular movements, and the maximal tangential acceleration during each movement segment of a triangle. EEG recording and primary data analysis The subject was seated in a semi-reclining chair. Movementrelated potentials were recorded using a multichannel EEG device (SynAmps amplifier and Scan software (NeuroScan, Sterling, Va., USA). Skin preparation with Abralyt Light (Falk Minow Services, Munich, Germany) resulted in impedance 3 kω at all recording sites. Twenty-seven Ag AgCl sinter electrodes were spaced on the scalp in a montage modified from the international system (FP1, FP2, F7, F3, FZ, F4, F8, FC5, FC1, FC2, FC6, T3, C3, CZ, C4, T4, CP5, CP1, CP2, CP6, T5, P3, PZ, P4, T6, O1, O2) (Fig. 1) (Jasper 1958; Herrmann et al., 1989). Vertical (VEOG) and horizontal (HEOG) electrooculograms were recorded separately. Data were recorded continuously with DC filtering to 100 Hz and an AD conversion rate of 500 Hz, with either A1 or A2 as the reference electrode (ipsilateral to the moving hand). Movement onset was marked off-line according to a rectified surface EMG recording of the extensor digitorum communis muscle. Data sweeps were generated for a period from 5 s before until 18 s after movement onset. Baseline correction was performed using the interval from 2500 to 2000 ms before movement onset. Blink artefacts were removed from raw data using VEOG data and the artefact-reduction Scan software algorithm (NeuroScan). Individual sweeps were inspected off-line and were rejected from the analysis if one of the following conditions was fulfilled: (i) the resting period before movement onset was shorter than 8 s; (ii) the EEG signals were greater than 50 µv or less than 50 µv; (iii) HEOG indicated horizontal eye movements; (iv) one or more electrodes showed any other artefact. For the analysis of DC potentials, intra-individual averaging of sweeps was performed; on average 53 accepted sweeps were averaged (patients, 52 sweeps; controls, 54 sweeps; t-test, P 0.793). Averaged sweeps were corrected for residual drifts by a linear detrend algorithm (followed by a second baseline correction), transformed to a common average reference (based on 19 electrodes of the system), and reduced in size to the period of interest from 3 s before movement onset to 5 s after movement onset. All further analyses of DC potentials were based on common average reference data. For the analysis of ERD in the alpha band, data were baseline-corrected to a baseline period from 3500 to 2500 ms before movement onset and transformed to a common average reference (based on 19 electrodes of the system). The alpha frequency with the largest movement-related change of power at C3 or C4 (contralateral to the moving limb) was considered the individual s µ frequency; this most reactive frequency was determined by comparing a period of 4 s before movement onset (5000 to 1000 ms before movement onset) with a period of 4 s during movement ( ms after movement onset); a distinct responsive peak in the alpha band was usually present; the mean µ frequency for control subjects was 10.2 Hz (SD 1.1 Hz) and for patients it was 9.5 Hz (SD 0.9 Hz) (t-test, P 0.060). Data were then bandpass-filtered from 1 Hz below to 1 Hz above the individual µ frequency, and were rectified. Intra-individual averaging of sweeps was then performed. For the analysis of ERD in the beta band, a broader and standardized bandpass digital filter was used from 14.5 to 24.5 Hz, because the distribution of the power of beta-band activity was broader than the distribution of the power of alpha-band activity and was usually without a discernible and distinct peak. After filtering, the data were rectified, and intra-individual averaging of sweeps was performed. These bandpassed intraindividual averages (for the alpha and beta bands) were transformed to ERD data by dividing each data point for any electrode by the mean of the baseline data ( s before movement) for that electrode; this resulted in relative scores for each electrode and data point indicating the degree of either event-related synchronization (score 1.0) or ERD (score 1.0). Advanced and statistical data analysis Movement-related time periods of interest For each individual, electrode and data aspect (DC, alpha- ERD, beta-erd) scores for dependent variables were

5 Movement-related brain activity after stroke 2479 calculated as mean scores for prespecified time periods: NB1, early negativity of Bereitschaft (readiness) from 750 to 500 ms before movement onset; NB2, late negativity of Bereitschaft from 250 to 0 ms (immediately before movement onset); NP1, negativity of performance during the first second of movement; NP2, negativity of performance during the second and third seconds of movement. The distinction between early and late negativity of Bereitschaft was based on published data showing that an early negativity of Bereitschaft, starting up to 2 s before movement onset, evolves more gradually than a late negativity of Bereitschaft immediately before movement onset with a steeper slope (Tamas and Shibasaki, 1985). The selection of periods was confirmed post hoc; i.e. modelling a moving dipole revealed a relatively stable localization of the equivalent dipole during both NB1 and NP1, whereas there was a gradual shift from the first to the second position during NB2. Negativity of performance was divided into two phases in order to assess the temporal evolution of MRPs during performance. Later during movement (NP2), the data were more variable than the data relating to the first second of movement, and thus the statistical analysis rarely revealed any significant intergroup effects; consequently, these data (NP2) are not presented in detail. The main analyses were therefore based on the two phases of relatively stable electrocortical activity distributions, namely NB1 and NP1. Data reduction EEG analysis as described above included 27 electrodes, two time periods of interest and three types of analysis (DC, alpha-erd, beta-erd), giving 162 parameters per person. Accordingly, data reduction was warranted. Rather than any self-selected data reduction, more formal (and presumably more meaningful) procedures for data reduction were performed. For DC potentials, the equivalent dipole reconstruction was performed using the Advanced Source Analysis (ASA) software (ANT Software, Enschede, The Netherlands). The small number of electrodes and the wide distribution of task-related surface negativity (DC potentials) (Fig. 2) excluded the possibility of accurate localization of the centres of activity in every single subject. However, by means of meaningful data reduction, dipole reconstruction should facilitate the detection of significant differences in generator configuration between subjects. The volume conductor effects were accounted for by a spherical head model with three shells representing the inner and outer surfaces of the skull and the skin surface. A single fixed dipole was fitted; this dipole model assumed that the surface electric field could be explained by a single equivalent dipole with constant position and orientation over the entire time window of interest (i.e. NB1, NP1) and varying source strength; information from 27 electrodes was then represented by seven dipole parameters (x, y and z positions; x, y and z normalized orientation moments; and average dipole strength); three normalized orientation moments (with scores ranging from 1 to 1) were chosen as opposed to two orientation angles because of their ease of interpretation. The fit was carried out separately for every subject and period of interest (NB1, NP1). Starting with a dipole positioned in the centre of the spherical head model, the free parameters of the dipoles were repeatedly adjusted in such a way that the residual variance (RV), i.e. the squared sum of the differences between the measured and simulated EEG field data, became minimal. The individual fitting process continued until all predetermined stopping criteria were reached. These were (i) reduction of RV to below 0.1%; (ii) position shift smaller than 0.1 mm; and (iii) orientation changes smaller than 1. The goodness of fit of the model was assessed by the amount of the variance that was explained, i.e. the proportion of the signal variance that was explained by the dipole (1 RV). The seven estimated dipole parameters for each individual and period of interest were then used for further statistical analysis. For ERD data, equivalent dipole reconstruction (with ASA software) is not possible. Principal components analysis (PCA) was therefore used. The purpose of PCA is to explain as much as possible of the total variation in the data with as few factors (the principal components) as possible. Because data reduction was our primary interest, and in view of the signal-to-noise ratio in the ERD data for the individuals in our study, we considered it appropriate to explain approximately 75% of the variance in the data set and to enter no principal component that explained less than 5% of the total variance. To help in the interpretation of the principal components, an orthogonal (varimax) rotation was applied. PCA was performed separately for alpha-erd and beta- ERD, based on the data set consisting of the data for 10 healthy subjects, both hands, all 27 electrodes and the time periods of primary interest (NB1, NP1). Estimated factor weights for the PCA were then used to estimate factor scores for each individual (healthy subjects and patients) and time period of interest; these factor scores were then used for further statistical analysis. Statistical analysis Data for the 10 healthy subjects served as a reference. Data for each patient group (hemiparesis, deafferentation and ideomotor apraxia) were compared with data for healthy individuals; t-tests for independent groups and unequal variances were performed. Data for hemiparetic subjects (eight data sets: four patients with right hemiparesis and four patients with left hemiparesis) were compared with pooled data for either hand of healthy subjects (20 data sets); data for other patient groups (left hand assessed) were compared with corresponding data for healthy subjects (10 data sets with the left hand assessed). Results Motor performance For each individual, we recorded the duration of the triangular movements and the maximal tangential acceleration of each

6 2480 T. Platz et al. movement segment of a triangle. The groups were similar with regard to movement duration (P 0.20). Only the hemiparetic patients showed a tendency to have a somewhat shorter movement duration and showed greater variability of movement duration with repeated movements (mean, control subjects 2.90 s, hemiparetic subjects 2.75 s, P ; coefficient of variation, control subjects 0.12, hemiparetic subjects 0.23, P ). In addition, for all three segments of the triangular movement the hemiparetic subjects had lower maximal acceleration scores than control subjects (maximal acceleration of first segment: control subjects 6.2 U, hemiparetic subjects 3.2 U, P ). Patients with ideomotor apraxia had a reduced maximal acceleration for the first movement segment only; a less pronounced tendency was observed in patients with somatosensory deficits (control subjects, left hand 6.1 U; ideomotor apraxic subjects 1.8 U, P ; deafferented patients 4.2 U, P ). Dipole analysis of movement-related DC potentials Goodness of fit Overall, modelling a single fixed dipole for each individual for the readiness period (from 750 to 500 ms before movement onset) resulted in a mean goodness of fit (proportion of variance explained) of 0.65 (95% confidence interval ); modelling a single fixed dipole during the first second of movement resulted in a mean goodness of fit of 0.74 (95% confidence interval ). This indicates a considerable degree of variance explained by the individual models; equally, overfitting seems unlikely. Although single fixed dipoles cannot be regarded as accurate localizing information for focal brain activity in a given experiment, they do represent valid descriptors of more widely distributed MRPs and are thus suitable for numerical comparisons of groups. Dipole analysis data for subgroups are presented in Table 2. Hemiparetic patients Comparing the dipole analysis data for eight hemiparetic subjects with 20 data sets for control subjects (10 right arm, 10 left arm) revealed differences, especially during the readiness potential period. On average, the dipole during the readiness period was at a higher location (z position: hemiparesis 57.7 mm, controls 23.2 mm, P ) and the dipole was more anteriorly (y) and more laterally (x) oriented (y orientation: hemiparesis 0.29, controls 0.03, P ; x orientation: hemiparesis 0.25, controls 0.02, P ), while its strength was reduced (magnitude: hemiparesis 30.2 nam, controls 46.8 nam, P ). This corresponds to a more anteriorly centred and more lateralized map of MRPs (Fig. 2, HE, Readiness). During movement, only a tendency towards a more posterior localization of the dipole among hemiparetic patients was noted (y position: hemiparesis 0.5 mm, controls 7.8 mm, P ). Patients with somatosensory deficits Dipole analysis among patients with left-sided somatosensory deficits did not reveal significant differences compared with controls subjects (left arm). Numerically, the dipole was, on average, positioned less laterally and more posteriorly. Equally, the MRP map suggests a more posteriorly centred and less lateralized distribution of DC potentials (Fig. 2, SE, Readiness and Performance). Patients with ideomotor apraxia For two ideomotor apraxic patients performing the task with their left, non-paretic limb, dipole analysis indicated for both the readiness period and the first second of movement a more lateral position of the single fixed dipole (x position: readiness, ideomotor apraxia 20.7 mm, controls (left arm) 0.3 mm, P ; performance, ideomotor apraxia 33.1 mm, controls 21.6 mm, P ). In addition, the dipole was oriented more anteriorly during movement (y orientation: ideomotor apraxia 0.30, controls 0.06, P ). The MRP map similarly indicates a more anteriorly centred and more lateralized distribution of movement-related negativity, with a lack of negativity at left lateral recording sites (Fig. 2, IM, Readiness and Performance). Principal components analysis of ERD in the alpha band Principal components analysis in the alpha band Three factors accounted for 74% of the standardized variance (a fourth factor would have accounted for less than an additional 5%). Factors 1, 2 and 3 explained (after varimax rotation) 8.4, 6.4 and 5.1 of the variance, respectively. We preferred to retain relatively few components because our primary purpose was data reduction for statistical analysis. Factor 1 correlated highly with the frontocentral and posterior electrodes [correlation ranged from 0.52 to 0.88 (O1)], which showed little or no movement-related desynchronization, or even a movement-related increase in alpha activity (synchronization) among healthy subjects (Figs 3 and 4, CO). Factor 2 correlated highly with bilateral central and right centroparietal electrodes [C3, CZ, C4, CP2, CP6, P4; correlation ranged from 0.63 to 0.88 (C4)]; these electrodes showed the most prominent task-related alpha-erd. Factor 3 correlated especially with the left frontal and lateral electrodes [FP1, F7, FC5, T3, CP5, F8; correlation ranged from 0.57 to 0.87 (F7)]; at these recording sites a minor degree of alpha-erd was observed. By the use of standardized scoring coefficients for the three components and each electrode derived from data for the control subjects,

7 Movement-related brain activity after stroke 2481 Table 2 Dipole analysis of movement-related DC potentials of 13 stroke patients and 10 control subjects Variable Control Hemiparesis Deafferentation Apraxia L(n 3) L (n 2) L(n 10) R (n 10) L (n 4) R (n 4) Readiness Position x 0.3 (31.2) 1.0 (16.3) 4.7 (12.3) 10.5 (36.5) 1.3 (8.6) 20.7 (3.1) y 15.3 (20.5) 12.6 (10.4) 6.6 (9.5) 19.3 (32.0) 9.8 (23.0) 7.8 (2.4) z 25.8 (30.0) 20.5 (42.8) 53.3 (19.3) 62.1 (23.4) 25.3 (18.6) 26.8 (55.5) Orientation x 0.03 (0.23) 0.0 (0.20) 0.03 (0.15) 0.46 (0.27) 0.01 (0.17) 0.20 (0.24) y 0.08 (0.17) 0.02 (0.28) 0.31 (0.42) 0.28 (0.45) 0.12 (0.47) 0.34 (0.24) z 0.96 (0.04) 0.74 (0.61) 0.83 (0.30) 0.63 (0.39) 0.42 (0.98) 0.88 (0.15) Magnitude 47.1 (23.5) 46.5 (11.7) 35.9 (10.3) 24.5 (12.4) 37.0 (12.4) 69.8 (39.7) Performance Position x 21.6 (15.1) 14.5 (7.2) 14.1 (8.2) 16.6 (7.9) 6.2 (12.6) 33.1 (3.0) y 7.1 (13.3) 8.5 (11.8) 4.7 (4.0) 5.6 (7.3) 3.6 (13.9) 9.1 (0.30) z 34.3 (17.5) 31.5 (14.4) 31.7 (16.4) 36.3 (24.0) 31.7 (5.1) 28.7 (20.3) Orientation x 0.01 (0.16) 0.06 (0.11) 0.06 (0.13) 0.14 (0.11) 0.05 (0.12) 0.13 (0.08) y 0.06 (0.18) 0.03 (0.24) 0.18 (0.34) 0.10 (0.31) 0.30 (0.57) 0.30 (0.06) z 0.79 (0.59) 0.96 (0.05) 0.92 (0.16) 0.94 (0.04) 0.53 (0.78) 0.94 (0.03) Magnitude (60.7) (130.5) (10.5) (44.0) (45.8) 80.7 (17.8) Data are subgroup averages (SD) of dipole parameters. Single dipoles were characterized by seven parameters of a 3D vector reflecting their position within the head model (x, lateral distance; y, anterior posterior distance; z, vertical distance from the centre of the spherical head model in mm), their normalized orientation moments (expressed in the same coordinate system; scores range from 1 to 1), and their average strength in nam (Magnitude). L left; R right. individual factor scores were calculated; subgroup mean values are given in Table 3. Hemiparetic patients Statistical analysis of group differences between eight hemiparetic patients and 20 data sets for 10 control subjects (left and right arms) confirmed a negative increase in factor 3 among hemiparetic subjects during the first second of movement (factor 3: hemiparesis 1.32, controls 0.00, P ). The effect was similar for left and right hemiparetic patients (factor 3: left hemiparesis 1.15, right hemiparesis 1.48). As already noted, factor 3 was especially correlated with scores for predominantly left frontal and lateral electrodes. Hemiparetic subjects had a pronounced alpha- ERD at these recording sites (mean alpha-erd at FP1, F7, FC5, T3, CP5, F8: control subjects 0.95, hemiparetic subjects 0.81) (Fig. 4, CO and HE, Performance). Patients with somatosensory deficits These patients had higher positive values of factor 2 both during movement preparation and during performance (factor 2: readiness, deafferentation 1.45, controls 0.15, P ; performance, deafferentation 0.68, controls 0.41, P ). This effect continued during the later stages of performance (factor 2, 1 3 s after movement onset: deafferentation 0.90, controls 0.25, P ). Factor 2 was highly correlated with scores for central electrodes and right centroparietal electrodes. Accordingly, alpha-erd was reduced for deafferented patients at recording sites where movement-related alpha-erd can be expected typically [mean alpha-erd at C3, C4, CP2, CP6: control subjects (left arm), readiness 0.88, performance 0.80; deafferented subjects, readiness 1.12, performance 0.97] (Fig. 4, CO and SE, Readiness and Performance). Patients with ideomotor apraxia No statistically significant differences were found between the two ideomotor apraxic patients and the 10 control subjects (left arm), even though the topographical map indicated a reduced alpha-erd at left centroparietal recording sites (Fig. 4, CO and IM, Readiness and Performance). Principal components analysis of ERD in the beta band Principal components analysis in the beta band Six components were necessary to account for 77% of the standardized variance (any further component would have accounted for 4% of additional variance); the variance explained by the six factors (after varimax rotation) was 5.6, 3.7, 3.6, 3.3, 2.8 and 2.0, respectively. Factor 1 was highly correlated with mesiocentral electrodes (FC1, FC2, FC5, CZ, CP1, CP2; correlation ranged from 0.69 to 0.89), factor 2 with left lateral centroparietal electrodes (FC5, C3, T3, CP5, P3; correlation ranged from 0.62 to 0.76), factor 3 (among others) with occipital electrodes (O1, O2; correlation 0.69 and 0.86, respectively), factor 4 with frontopolar-frontal electrodes (FP1, FP2, F3, F4, F8; correlation ), factor 5 with right lateral-central electrodes (FC6, C4, CP6; correlation 0.62, 0.71 and 0.82, respectively) and factor 6

8 2482 T. Platz et al. Fig. 2 Movement-related DC potentials. Evoked potentials are time-locked to the onset of triangular finger movements performed with the left hand. Group average activities for the period from 750 to 500 ms before movement onset (Readiness) and for the period from movement onset to 1000 ms after movement onset (Performance) are plotted as 27-channel topographical EEG maps. Blue denotes movement-related positive drifts and red denotes movement-related negative shifts of slow cortical potentials, based on common average reference data. Isoelectric lines are separated by 0.4 µv. CO grand average of 10 control subjects; HE grand average for four left hemiparetic patients; SE grand average for three patients with somatosensory deficits; IM grand average for two patients with ideomotor apraxia.

9 Movement-related brain activity after stroke 2483 patient groups. Therefore, detailed results are presented only for these three factors in Table 4. Hemiparetic patients Statistical analysis of group differences between the eight hemiparetic patients and the 20 data sets for the 10 control subjects (left and right arms) confirmed a reversal of sign with a considerable positive value for factor 3 among the hemiparetic subjects during movement preparation (factor 3: readiness, hemiparesis 0.45, controls 0.19; P ). This indicates a movement-related increase in beta activity (event-related synchronization, ERS) at occipital recording sites for hemiparetic patients [mean beta-erd at O1 and O2: control subjects and 0.962, respectively ( ERD), hemiparetic subjects 1.03 and 1.02 ( ERS)] (Fig. 5, CO and HE, Readiness). The hemiparetic patients beta-erd during movement was not significantly different from that of the control subject. Fig. 3 For alpha-erd and beta-erd, principle components analysis (PCA) revealed three and six factors, respectively, that accounted for ~75% of the variance within each data set. For each electrode, the figure shows the factor with which the electrode has the highest correlation (all correlations 0.50). Factors 1 3 in the PCAs of both alpha-erd and beta-erd revealed significant group differences; no significant group differences were observed for factors 4 6 in the PCA for beta- ERD. with temporoparietal electrodes (T5, PZ, P4; correlation 0.80, 0.59 and 0.49, respectively) (Fig. 3). Factors 1, 2, 5 and 6 represented information related to movement-related desynchronization at frontal, central and parietal recording sites, while factors 3 and 4 represented information related to the paucity of movement-related desynchronization at prefrontal and occipital recording sites (Fig. 5, CO). Only factors 1 3 could differentiate between control subjects and Patients with somatosensory deficits These patients had higher positive values for factor 1 during movement preparation compared with control subjects (left arm), indicating a lack of beta-erd at mesiocentral recording sites [factor 1: readiness, deafferentation 2.25, controls 0.72, P ; mean beta-erd for FC1, FC2, FC5, CZ, CP1, CP2 during readiness: control subjects (left arm) 0.88; deafferented subjects 0.98] (Fig. 5, CO and SE, Readiness). In addition, values for factor 3 had a reversed sign, negative values during movement indicating a minor degree of desynchronization at occipital recording sites among deafferented patients, which was not present in control subjects [factor 3: performance, deafferentation 0.35, controls 0.17, P ; mean beta-erd at O1 and O2 during performance: control subjects (left arm) 0.99; deafferented subjects 0.97]; this effect was found even during the later stages of performance (factor 3, 1 3 s after movement onset: deafferentation 0.39, controls 0.13, P ) (Fig. 5, CO and SE, Performance). Patients with ideomotor apraxia ERD of the two ideomotor apraxic patients and 10 control subjects (left arm) differed significantly during movement preparation (only); apraxic patients had higher positive values for factor 2 and more negative scores for factor 3 (readiness: factor 2, apraxia 1.03, controls 0.20, P ; factor 3, apraxia 0.67, controls 0.02, P ). This indicates that the apraxic patients lacked beta-erd at left lateral centroparietal recording sites, whereas their ERD was somewhat pronounced at occipital recording sites [mean beta- ERD at FC5, C3, T3, CP5 and P3 during readiness: control subjects (left arm) 0.95, ideomotor apraxic patients 1.00; mean beta-erd at O1 and O2 during readiness: control

10 2484 T. Platz et al. Fig. 4 Movement-related desynchronization of alpha-band activity (alpha-erd). Relative changes in alpha-band activity are time-locked to the onset of triangular finger movements performed with the left hand. Group average activities for the period from 750 to 500 ms before movement onset (Readiness) and for the period from movement onset to 1000 ms after movement onset (Performance) are plotted as 27-channel topographical EEG maps of proportional mean alpha activity compared with the baseline interval from 3.5 to 2.5 s before movement onset. Blue denotes movement-related synchronization, and thus a proportional increase in alpha activity (values 1.0); red denotes movement-related desynchronization, and thus a proportional decrease in alpha-band activity (values 1.0) compared with baseline alpha activity. Colour steps and lines are separated by proportional differences of For abbreviations, see caption of Fig. 2.

11 Movement-related brain activity after stroke 2485 Table 3 Alpha-ERD in 13 stroke patients and 10 control subjects Variable Control Hemiparesis Deafferentation Apraxia L(n 3) L (n 2) L(n 10) R (n 10) L (n 4) R (n 4) Readiness Factor (0.79) 0.12 (0.71) 0.47 (0.43) 0.43 (0.35) 0.90 (0.63) 0.24 (0.09) Factor (0.73) 0.46 (0.68) 0.26 (0.05) 0.88 (0.12) 1.45 (0.69) 0.26 (0.80) Factor (0.85) 0.02 (1.09) 0.30 (0.66) 0.16 (1.32) 0.73 (0.82) 0.04 (0.45) Performance Factor (1.45) 0.22 (1.24) 0.45 (0.38) 0.31 (0.54) 1.30 (1.47) 0.63 (0.11) Factor (1.06) 0.13 (1.30) 1.26 (0.60) 0.18 (0.51) 0.68 (0.68) 1.26 (1.04) Factor (1.01) 0.06 (1.26) 1.15 (1.51) 1.48 (1.93) 0.34 (1.11) 0.24 (0.67) Data are subgroup averages (SD) of factor scores. subjects (left arm) 0.98, ideomotor apraxic patients 0.95] (Fig. 5, CO and IM, Readiness). Baseline differences in alpha and beta EEG activity Event-related desynchronization was calculated relative to baseline data. Thus, changes between groups could partially reflect differences in baseline EEG activity (as opposed to differences in EEG before and during movement). Therefore, it seemed important to include a comparison of baseline activities in the different groups. Mean amplitudes of alpha and beta activity during baseline ( ms before movement onset) differed from the control subjects data only for patients with somatosensory deficits (alpha: control subjects 1.87 µv, deafferentation 0.88 µv, P ; beta: control subjects 1.21 µv, deafferentation 0.84 µv, P ). Next, we sought to determine whether the effects demonstrated for ERD in patients with somatosensory deficits would still be present when these baseline differences were accounted for. For this purpose, a subgroup of control subjects with similar (P 0.40) baseline amplitudes of alpha (n 6) and beta (n 7) activity was chosen and their ERD was compared with that of patients with somatosensory deficits. The pattern of altered alpha-erd and beta-erd, as described in the sections headed Patients with somatosensory deficits, was still present in these comparisons; P values were reduced because of the smaller number of subjects (alpha-erd: factor 2: readiness, deafferentation 1.45, controls 0.33, P ; performance, deafferentation 0.68, controls 0.26, P ; beta-erd: factor 1: readiness, deafferentation 2.25, controls 1.04, P ; factor 3: performance, deafferentation 0.35, controls 0.36, P ). Effect of motor performance on EEG activity Patients differed from control subjects with regard to maximal acceleration during movement. We therefore sought to investigate the degree to which motor behaviour among control subjects influenced EEG activity and thus whether differences in motor behaviour, independently of any clinical impairment, could explain differences in EEG activity. Simple regression models for control subjects maximal acceleration when using their right hand revealed no influence on EEG parameters during performance (dipole parameters, factors 1 3 for alpha-erd, factors 1 3 for beta-erd; for all univariate regression models P 0.25). Thus, at least within the intended low range of movement variation of the experiment and with regard to the EEG parameter analysed, no major influence of movement variation on EEG parameters was found among the control subjects. Discussion General considerations Both clinical experience and previous research support the notion of impairment-specific behavioural motor deficits; by classifying patients according to their clinical presentation it is possible to demonstrate various patterns of associated changes in motor behaviour (Platz et al., 1994; Platz and Mauritz, 1995, 1997). It was, therefore, of interest to investigate whether this clinically oriented functional classification of stroke patients was associated with a differential pattern of movement-related electrical activity of the brain, and thus with a differential pattern of functional cerebral reorganization. The strength of the method is its high temporal resolution, which allows the separate assessment of movement preparation and movement execution and makes it possible to distinguish slowly evolving movement-related potentials and sensorimotor rhythms, and thereby different types of electric brain activity that are closely related to neural function. In line with the available literature (for review, see Lang et al., 1994; Pfurtscheller and Lopes da Silva, 1999), different spatiotemporal patterns of electrical activity of the brain were found in the present study, on the basis of the same raw EEG data (Figs 2, 4 and 5): in healthy subjects, slow cortical movement-related potentials were widespread, with a midline centre at the vertex during movement preparation, and became more lateralized during movement execution. ERD in the alpha and beta bands, however, was expressed bilaterally, with centres over the

12 2486 T. Platz et al. Fig. 5 Movement-related desynchronization of beta-band activity (beta-erd). Relative changes of betaband activity are time-locked to the onset of triangular finger movements performed with the left hand. Group average activities for the period from 750 to 500 ms before movement onset (Readiness) and for the period from movement onset to 1000 ms after movement onset (Performance) are plotted as 27-channel topographical EEG maps of proportional mean beta activity compared with the baseline interval from 3.5 to 2.5 s before movement onset. Blue denotes movement-related synchronization, and thus a proportional increase in beta activity (values 1.0); red denotes movement-related desynchronization, and thus a proportional decrease in beta-band activity (values 1.0) compared with baseline beta activity. Colour steps and lines are separated by proportional differences of For abbreviations, see caption of Fig. 2.

13 Movement-related brain activity after stroke 2487 Table 4 Beta-ERD in three stroke patients and 10 control subjects Variable Control Hemiparesis Deafferentation Apraxia L(n 3) L (n 2) L(n 10) R (n 10) L (n 4) R (n 4) Readiness Factor (0.94) 0.77 (0.67) 0.19 (0.56) 0.84 (0.88) 2.25(0.57) 0.67 (0.09) Factor (1.00) 0.52 (1.02) 0.01 (0.52) 0.01 (0.68) 0.39 (0.45) 1.03 (0.20) Factor (0.80) 0.39 (0.92) 0.47 (0.71) 0.42 (0.32) 0.70 (0.70) 0.67 (0.26) Performance Factor (1.08) 0.45 (1.02) 1.18 (0.74) 0.04 (1.24) 0.20 (0.32) 0.51 (0.47) Factor (0.98) 0.15 (1.10) 0.12 (1.44) 0.13 (0.71) 0.36 (0.40) 0.99 (0.55) Factor (0.78) 0.10 (1.50) 0.26 (1.01) 0.29 (1.07) 0.35 (0.19) 0.35 (0.43) Data are subgroup averages (SD) of factor scores. sensorimotor cortices already apparent during movement preparation. Furthermore, while alpha desynchronization was recorded primarily at central and parietal electrodes, beta synchronization was also recorded simultaneously at frontomesial recording sites. The results obtained also demonstrate that this type of investigation can be performed with stroke patients who show deviations from the pattern documented for age-matched healthy subjects, as we have described above. More interestingly, the results support the hypothesis that changes in the electrical activity of the brain differ according to the specific impairments that occur after a stroke. Groups of hemiparetic, deafferented and ideomotor apraxic patients showed different patterns of changes in the electrical activity of the brain compared with healthy subjects. Each of these groups showed its own picture of changes in either preparatory or execution-related electrical activity in the brain. We will summarize these patterns and propose possible functional interpretations. While they are encouraging, these results and interpretations must be considered to be preliminary and subject to confirmation because they are based on a limited number of patients; however, as previously shown for Parkinson s disease (i.e. Jahanshahi et al., 1995; Pfurtscheller et al., 1998), these results firmly indicate the potential of a non-invasive method, with high temporal resolution, for the investigation of specific aspects of altered motor control after stroke. Impairment-specific changes Motor performance While movement duration was largely similar across groups, the patients especially those with hemiparesis had lower maximal acceleration scores for their triangular movements. It could therefore be argued that differences in the electrical activity of the brain observed between the groups might be explained by differences in motor behaviour. This, however, seems unlikely, as among the control subjects no systematic effect of variation of maximal acceleration during finger movements on EEG parameters could be substantiated within the set of experimental data. Accordingly, the alternative hypothesis is more likely that differences in the electrical activity of the brain between groups reflect more fundamental changes in cortical motor control. Hemiparesis Patients with hemiparesis showed differences from control subjects mostly during movement preparation. Since movement-related slow DC potentials generally showed a wide unipolar distribution, dipole analysis cannot be considered to be a descriptor of a small activated area, but rather a descriptor of a more global field. Accordingly, it was used for the statistical confirmation of topographical differences in MRPs between groups. In hemiparetic subjects, the MRP map (Fig. 2, HE, Readiness) and dipole analysis indicated a more laterally (contralateral to the moving limb) and frontally centred distribution of the Bereitschaftspotential (readiness potential). This might indicate increased importance of the motor and premotor cortex in movement preparation in this patient group. More specifically, hemiparetic subjects may have an increased need for excitatory postsynaptic drive of pyramidal cells (Bierbaumer et al., 1990) and thus need an increased neural effort (Rösler et al., 1993) in motor areas during movement preparation. Alternatively, these changes in the electrical activity of the brain might reflect compensatory measures that are recruited in order to drive movement through projections from these areas to brainstem motor systems. Such mechanisms in motor areas might resemble a neural attempt to compensate for reduced ability to produce highly selective and efficient force impulses via the primary motor cortex and the pyramidal system, as reflected in the reduced maximal acceleration scores of the hemiparetic patients index finger movements. Another effect discriminated between the hemiparetic patients and control subjects during movement preparation: while control subjects had, on average, a minor beta-erd also at occipital recording sites, the hemiparetic patients showed a rather slight event-related synchronization (increase in beta activity) at these sites. This may indicate an accentuated idling state in visual areas during movement preparation in hemiparetic subjects.