Primary objective: To understand the temporal evolution of brain reorganization during recovery from stroke. Research design: A patient who suffered left middle cerebral artery stroke 9 months earlier was studied on three occasions, ∼1 month apart. Methods and procedures: Brain activation was studied using functional Magnetic Resonance Imaging (fMRI). During each session, the patient performed a finger-to-thumb opposition task, which involved one bimanual and two unimanual conditions. Each condition consisted of overt movement of fingers and imagery of the same task. Results: With recovery, greater recruitment was observed of the affected primary motor cortex (M1) and a decrease in activation of the unaffected M1 and supplementary motor area. In addition, the widespread activation of brain areas seen during the initial session changed to a more focused pattern of activation as the patient recovered. Imagery tasks resulted in similar brain activity as overt execution pointing to imagery as a potential tool for rehabilitation.

We measured modulations of neuroelectric gamma-band activity (GBA) as subjects listened to isochronous pure-tone sequences with embedded temporal perturbations. Perturbations occurred every 6-10 tones, and at the locus of the perturbation, tones occurred early, on time, or late. In the absence of perturbations, induced (non-phase-locked) GBA reached maximum power simultaneously with the occurrence of tone onsets, whereas evoked (phase-locked) GBA peaks were observed after onsets. During late perturbation trials, peaks in induced activity tended to precede tone onsets, and during early perturbation trials, induced peaks followed tone onsets. Induced peaks returned to synchrony after both types of perturbations. Early tones resulted in a marked increase in evoked GBA power at the locus of the perturbation. The latency of evoked GBA relative to tone onset, as well as some other features of the response, depended asymmetrically on the direction of the perturbation. The current results provide evidence for the synchronization of GBA during the perception of auditory rhythms, thus supporting the role of GBA in temporal expectancy.

The neural (blood oxygenation level dependent) correlates of executed and imagined finger sequences, both unimanual and bimanual, were studied in adult right-handed volunteers using functional magnetic resonance imaging (fMRI) of the entire brain. The finger to thumb opposition tasks each consisted of three conditions, two unimanual and one bimanual. Each experimental condition consisted of overt movement of the fingers in a prescribed sequence and imagery of the same task. An intricate network consisting of sensorimotor cortex, supplementary motor area (SMA), superior parietal lobule and cerebellum was identified when the tasks involved both planning and execution. During imagery alone, however, cerebellar activity was largely absent. This apparent decoupling of sensorimotor cortical and cerebellar areas during imagined movement sequences, suggests that cortico-cerebellar loops are engaged only when action sequences are both intended and realized. In line with recent models of motor control, the cerebellum may monitor cortical output and feed back corrective information to the motor cortex primarily during actual, not imagined, movements. Although parietal cortex activation occurred during both execution and imagery tasks, it was most consistently present during bimanual action sequences. The engagement of the superior parietal lobule appears to be related to the increased attention and memory resources associated, in the present instance, with coordinating difficult bimanual sequences.

Objective: Whole head magnetoencephalography was used to investigate the spatiotemporal dynamics of neuromagnetic brain activity associated with rhythmic auditory stimulation. Methods: In order to characterize the evolution of the auditory responses we applied a Karhunen-Loève decomposition and k-means cluster analysis to globally compare spatial patterns of brain activity at different latencies and stimulation rates. Tones were presented binaurally at 27 different stimulation rates within a perceptually and behaviorally relevant range from 0.6 to 8.1 Hz. Results: Over this range, we observed a linear increase of the amplitude of the main auditory response at 100 ms latency (N1m) with increasing inter-stimulus interval, and qualitative changes of the overall spatiotemporal dynamics of the auditory response. In particular, a transition occurred between a transient evoked response at low frequencies, and a continuous steady-state response at high frequencies. Conclusions: We show the onset of temporal overlap between responses to successive tones that leads to this transition. Response overlap begins to occur near 2 Hz, marking the onset of a continuous perceptual representation.

Dynamic systems have proven to be well suited to describe a broad spectrum of human coordination behavior such synchronization with auditory stimuli. Simultaneous measurements of the spatiotemporal dynamics of electroencephalographic (EEG) and magnetoencephalographic (MEG) data reveals that the dynamics of the brain signals is highly ordered and also accessible by dynamic systems theory. However, models of EEG and MEG dynamics have typically been formulated only in terms of phenomenological modeling such as fixed-current dipoles or spatial EEG and MEG patterns. In this paper, it is our goal to connect three levels of organization, that is the level of coordination behavior, the level of patterns observed in the EEG and MEG and the level of neuronal network dynamics. To do so, we develop a methodological framework, which defines the spatiotemporal dynamics of neural ensembles, the neural field, on a sphere in three dimensions. Using magnetic resonance imaging we map the neural field dynamics from the sphere onto the folded cortical surface of a hemisphere. The neural field represents the current flow perpendicular to the cortex and, thus, allows for the calculation of the electric potentials on the surface of the skull and the magnetic fields outside the skull to be measured by EEG and MEG, respectively. For demonstration of the dynamics, we present the propagation of activation at a single cortical site resulting from a transient input. Finally, a mapping between finger movement profile and EEG/MEG patterns is obtained using Volterra integrals.

For low rhythmic rates (1.0 to ∼2.0 Hz), subjects are able to successfully coordinate finger flexion with an external metronome in either a syncopated (between the beats) or synchronized (on each beat) fashion. Beyond this rate, however, syncopation becomes unstable and subjects spontaneously switch to synchronization to maintain a 1:1 stimulus/response relationship. We used a whole‐head magnetometer to investigate the spatiotemporal dynamics of neuromagnetic activity (MEG) associated with both coordinative patterns at eight different rates spanning the range 1.0–2.75 Hz. Timing changes in the event‐related fields accompanied transitions from syncopation to synchronization and followed the placement of the motor response within each stimulus/response cycle. Decomposition of event‐related fields into component auditory and motor brain responses revealed that the amplitude of the former decreased with increasing coordination rate whereas the motor contribution remained approximately constant across all rates. Such an interaction may contribute to changes in auditory‐motor integration that cause syncopation to become unstable. Examination of event‐related changes in high frequency bands revealed that MEG signal power in the beta band (15–30 Hz) was significantly lower during syncopated coordination in sensors covering the contralateral sensorimotor area suggesting a dependence of beta rhythm amplitude on task difficulty. Suppression of beta rhythms was also stronger during synchronization preceded by syncopation, e.g., after subjects had switched, when compared with a control condition in which subjects synchronized throughout the entire range of rates. Hum. Brain Mapping 14:65–80, 2001. © 2001 Wiley‐Liss, Inc.

Objective: To investigate how learning induced increases in stability on a syncopation task are manifest in the dynamics of cortical activity.Method: Magnetoencephalography was recorded from 143 sensors (CTF Systems, Inc). A pre-training procedure determined the critical frequency (F-c) for each subject (n = 4). Subjects either syncopated or synchronized to a metronome that increased in frequency from 1.2 to 3.0 Hz in 0.2 Hz steps. The F-c was the point at which subjects spontaneously switched from syncopation to synchronization. Subjects then underwent 100 training trials (with feedback) at F-c. Following the learning phase the pre-training procedure was repeated.Results: An increase in the F-c occurred indicating that practice improved the stability of syncopation. The transition delay was also observed in the phase of the time-averaged signal in sensors over the contralateral sensorimotor area and in power analysis in the 8-12 Hz and 18-24 Hz frequency bands. Initially, reduced power was observed bilaterally during syncopation compared to synchronization. Following training, these differences were reduced or eliminated.Conclusion: Pre-training power differences can be explained by the greater difficulty of the syncopation task. The reduction in power differences following training suggests that at the cortical level, syncopation became more similar to synchronization possibly reflecting a decrease in task and/or attention demands. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.

A full-head 143-channel superconducting quantum interference device was used to study changes occurring in the magnetic activity of the human brain during performance of an auditory–motor coordination task in which the rate of coordination was systematically increased. Previous research using the same task paradigm demonstrated that spontaneous switches in timing behavior that arise with higher coordination rates are accompanied by qualitative changes in spatiotemporal brain activity measured by electro- and magnetoencephalography. Here we show how these patterns can be decomposed into basic physiological events, i.e., evoked brain responses to acoustic tones and self-initiated finger movements. The frequency dependence of the amplitudes of these component responses may shed new light onto why spontaneous timing transitions occur in the first place.

m t c e r o b w m We are grateful to Sanes for his comments on our work, particularly for placing it in the broader context of current neurophysiological and neuroanatomical evidence. For the most part, his remarks are well made and well taken. Here we wish to provide some further perspective and elaboration on some of the issues he raises. These fall into three main categories: strategies of investigation into the relation between the dynamics of the brain and the dynamics of behavior, theoretical development of our neural field theory of cortical function, and analysis and computational methods for extracting key information from human neuroimaging data. Sanes understands that modern neuroimaging studies come with a double-edged sword. While they may provide access to the activity of underlying neural structures for small-amplitude finger movements (as in Kelso et al., 1998), they cannot easily be tailored for ore complicated, everyday actions. Normal reaching ovements, for example, cannot be carried out by a ubject inside a magnet or with a large array of QuIDs around the head for pretty obvious reasons. ovement artifacts alone would drown out the underying brain signals. Yet the issue concerning which ovements are appropriate to study may not revolve round single versus multijoint movements, per se. For s the issue is rather which experimental paradigms or model systems) afford the best entry point for unerstanding brain–behavior relations. For example, he discovery and ongoing study of behavioral phase ransitions and related phenomena have proved useful ecause they have allowed identification of the releant behavioral and neural variables (on a given level f description) and their coordination dynamics (equaions of motion that capture the stability and change of oordination states). Our work on sensorimotor coordiation referred to by Sanes derives from earlier empircal and theoretical studies of interlimb (multijoint!) oordination (e.g., Kelso, 1984; Haken et al., 1985). It urns out that the dynamics which hold for bimanual

w x In their Letter 1 , Daffertshofer, Peper and Beek Ž . referred to in the following as DPB report on findings from an attempt to replicate an experiment Ž . by one of us S.K. in 1989 which demonstrated a Ž . phase transition at both brain MEG and behavioral w x levels of description 3,10,12 . Although DPB reproduce most of the original results, they fail to observe a frequency doubling in the brain signals which occurs across the transition. This apparent absence triggers a lengthy discussion of possible artifacts that may happen in spectral analysis of time series in the presence of noise. Here we show the results of our own replication of the original experiment using a state of the art full-head magnetometer in order to illustrate our point of view with respect to the arguments made in DPB. We find that the results from our earlier and recent experimental studies are in excellent agreement even though they use different subjects. Moreover, our results agree with wellestablished features of evoked auditory and motor fields in the neurophysiological literature whereas it

Earlier research established that spontaneous changes in human sensorimotor coordination are accompanied by qualitative changes in the spatiotemporal dynamics of neural activity measured by multisensor electroencephalography and magnetoencephalography. More recent research has demonstrated that a robust relation exists between brain activity and the movement profile produced. In particular, brain activity has been shown to correlate strongly with movement velocity independent of movement direction and mode of coordination. Using a recently developed field theoretical model of large-scale brain activity itself based on neuroanatomical and neurophysiological constraints we show here how these experimental findings relate to the field theory and how it is possible to reconstruct the movement profile via spatial and temporal integration of the brain signal. There is a unique relation between the quantities in the theory and the experimental data, and fit between the shape of the measured and the reconstructed time series for the movement is remarkably good given that there are no free parameters.

We used a 61-channel electrode array to investigate the spatiotemporal dynamics of electroencephalographic (EEG) activity related to behavioral transitions in rhythmic sensorimotor coordination. Subjects were instructed to maintain a 1:1 relationship between repeated right index finger flexion and a series of periodically delivered tones (metronome) in a syncopated (anti-phase) fashion. Systematic increases in stimulus presentation rate are known to induce a spontaneous switch in behavior from syncopation to synchronization (in-phase coordination). We show that this transition is accompanied by a large-scale reorganization of cortical activity manifested in the spatial distributions of EEG power at the coordination frequency. Significant decreases in power were observed at electrode locations over left central and anterior parietal areas, most likely reflecting reduced activation of left primary sensorimotor cortex. A second condition in which subjects were instructed to synchronize with the metronome controlled for the effects of movement frequency, since synchronization is known to remain stable across a wide range of frequencies. Different, smaller spatial differences were observed between topographic patterns associated with synchronization at low versus high stimulus rates. Our results demonstrate qualitative changes in the spatial dynamics of human brain electrical activity associated with a transition in the timing of sensorimotor coordination and suggest that maintenance of a more difficult anti-phase timing relation is associated with greater activation of primary sensorimotor areas.

For the paradigmatic case of bimanual coordination, we review levels of organization of behavioral dynamics and present a description in terms of modes of behavior. We briefly review a recently developed model of spatiotemporal brain activity that is based on short-and long-range connectivity of neural ensembles. This model is specified for the case of motor and sensorimotor units embedded in the neural sheet. Focusing on the cortical left-right symmetry, we derive a bimodal description of the brain activity that is connected to behavioral dynamics. We make predictions of global features of brain dynamics during coordination tasks and test these against experimental magnetoencephalogram (MEG) results. A key feature of our approach is that phenomenological laws at the behavioral level can be connected to a field-theoretical description of cortical dynamics.

That animals and humans can accomplish the same goal using different effectors and different goals using the same effectors attests to the remarkable flexibility of the central nervous system. This phenomenon has been termed ‘motor equivalence’ 1 , 2 , an example being the writing of a name with a pencil held between the toes or teeth. The idea of motor equivalence has reappeared because single-cell studies in monkeys have shown that parameters of voluntary movement (such as direction) may be specified in the brain, relegating muscle activation to spinal interneuronal systems 3 , 4 . Using a novel experimental paradigm 5 and a full-head SQUID (for superconducting quantum interference device) array to record magnetic fields corresponding to ongoing brain activity, we demonstrate: (1), a robust relationship between time-dependent activity in sensorimotor cortex and movement velocity, independent of explicit task requirements; and (2) neural activations that are specific to task demands alone. It appears, therefore, that signatures of motor equivalence in humans may be found in dynamic patterns of cortical activity.

814 NATURE | VOL 392 | 23 APRIL 1998 9. Yakovlev, P. I. & Lecours, A. in Regional Development of the Brain in Early Life (ed. Minkowski, A.) 3– 70 (Blackwell, Oxford, 1967). 10. Takeuchi, A. H. & Hulse, S. H. Absolute pitch. Psychol. Bull. 113, 345–361 (1993). 11. Barnea, A., Granot, R. & Pratt, H. Absolute pitch-electrophysiological evidence. Int. J. Psychophysiol. 16, 29–38 (1994). 12. Benguerel, A. P. & Westdal, C. Absolute pitch and the perception of sequential music intervals. Music Percept. 9, 105–120 (1991). 13. Williamson, S. J. & Kaufman, L. in Auditory Evoked Magnetic Fields and Electric Potentials (eds Grandori, F., Hoke, M. & Romani, G. L.) 1–39 (Karger, Basel, 1990). 14. Kaas, J. H., Merzenich, M. M. & Killackey, H. P. The reorganization of somatosensory cortex following peripheral nerve damage in adult and developing mammals. Annu. Rev. Neurosci. 6, 325–356 (1983).

The present study aims to understand the neurally based coordination dynamics (multistability, loss of stability, transitions, etc.) of trajectory formation in a simple task. Six subjects produced two spatial patterns of coordination in the xy plane by alternating the abduction-adduction and flexion-extension motions of their right index finger. Each pattern was characterized by a unique temporal ratio between the x and y directions of motion: (1) a figure zero, a 1∶1 temporal pattern; and (2) a figure eight, a 2∶1 temporal pattern. The patterns were produced rhythmically and movement frequency was scaled across ten frequency plateaus, with ten cycles of motion per step. As movement frequency increased, switching from a figure eight to a figure zero was observed at critical cycling frequencies. The switch from pattern (2) to pattern (1) was identified in the spatial trajectory and power spectra of x(t) and y(t). En route to the transition, enhancement of fluctuations was observed in the Fourier amplitudes of x(t) and y(t), specifically at f0 (the metronome frequency) and 2f0 (the first harmonic off0). Interestingly, there was no difference in the spatial variability of the two patterns. Overall, the data demonstrate that spatial patterns of coordination can be characterized in terms of the temporal relationship between the spatial components of the trajectory itself. We discuss the experimental findings in relation to other end-point planning and multijoint control strategies, as well as the much more general problem of temporal synchronization in many interlimb and intralimb coordination tasks.

We study the dynamics of a system of coupled nonlinear oscillators that has been used to model coordinated human movement behavior. In contrast to earlier work we examine the case where the two component oscillators have different eigenfrequencies. Problems related to the decomposition of a time series (from an experiment) into amplitude and phase are discussed. We show that oscillations at multiples of the main frequency of the oscillator system may occur in the phase and amplitude due to the choice of a coordinate system and how these oscillations can be eliminated. We derive an explicit equation for the dynamics of the relative phase of the oscillator system in phase space that enables a direct comparison between theory and experiment.

Using a sensorimotor coordination task in conjunction with an array of SQUIDs (Superconducting QUantum Interference Devices) we demonstrate critical instabilities in human brain activity patterns. Analysis of the dominant spatial pattern of the brain and its time-varying amplitude displays a task-dependent geometry characteristic of Sil'nikov-like chaos, which changes qualitatively at the transition. (c) 1995 American Institute of Physics.

In this article we describe the synergetic approach to pattern recognition and associative memory as well as its extension to the modelling of phenomena observed in human perception. These are two examples of the application of phenomenological synergetics. In general, natural systems which show spontaneous self-organization can be divided into two classes: Systems for which the interaction at a microscopic level can be derived from first principles (like the laser or hydrodynamical systems), and systems where only the macroscopic phenomena are known. Examples of this class of systems which are treated with the methods of synergetics are the dynamics of spatio-temporal EEG patterns [2] and the so-called synergetic computers [1]. Synergetic computers are systems which we want to fulfill a special task, i.e. to act as an associative memory or to learn patterns which are offered from outside. Such systems can also be used to model phenomena in human perception, especially psychological experiments with ambiguous patterns as we shall describe below.