Bimanual coordination and interhemispheric interaction

Abstract

Bimanual coordination of skilled finger movements requires intense functional coupling of the motor areas of both cerebral hemispheres. This coupling can be measured non-invasively in humans with task-related coherence analysis of multi-channel surface electroencephalography. Since bimanual coordination is a high-level capability that virtually always requires training, this review is focused on changes of interhemispheric coupling associated with different stages of bimanual learning. Evidence is provided that the interaction between hemispheres is of particular importance in the early phase of command integration during acquisition of a novel bimanual task. It is proposed that the dynamic changes in interhemispheric interaction reflect the establishment of efficient bimanual `motor routines'. The effects of callosal damage on bimanual coordination and learning are reviewed as well as functional imaging studies related to bimanual movement. There is evidence for an extended cortical network involved in bimanual motor activities which comprises the bilateral primary sensorimotor cortex (SM1), supplementary motor area, cingulate motor area, dorsal premotor cortex and posterior parietal cortex. Current concepts about the functions of these structures in bimanual motor behavior are reviewed.

Introduction

Bimanual coordination of skilled finger movements is an outstanding capability of the human motor system. Not only the activation of particular regions such as the supplementary motor area (SMA) and the lateral premotor cortex (Sadato, Yonekura, Waki, Yamada, & Ishii, 1997; Toyokura, Muro, Komiya, & Obara, 1999), but also the functional coupling between the premotor and sensorimotor areas of the two hemispheres is important for the precise timing and execution of bimanual movements. Lesion studies strongly suggest that interhemispheric exchange of premotor and sensorimotor commands plays a major role in bimanual activities (Geffen, Jones, & Geffen, 1994; Jeeves, Silver, & Jacobson, 1988; Leonard, Milner, & Jones, 1988; Preilowski, 1972; Sperry, 1968). Which role do interhemispheric interactions in the sensorimotor system play in the implementation of bimanuality? How do interhemispheric interactions change during bimanual skill acquisition? Another question relates to the point that, in real life, unimanual and bimanual activities alternate frequently. How does the brain switch from the unimanual to the bimanual mode of operation? Some recent papers have shed light on these questions.

The present review focuses on interhemispheric interactions in the course of bimanual skill acquisition. This is of particular importance, since dynamic changes of interhemispheric communication (in the following referred to as `interhemispheric coupling') are expected to provide us with information as to how the brain acquires and implements bimanuality (Section 2).

In Section 3, the functional relevance of interhemispheric communication is discussed in the light of lesion studies describing the effects of callosal damage on interhemispheric coupling and bimanual coordination.

Finally, recent evidence from functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) research in favor of an extended network of cortical areas involved in bimanual motor activities is reviewed with emphasis on the regional activation rather than interregional interaction (Section 4).

Interregional functional coupling can be assessed non-invasively with task-related coherence (TRCoh) analysis of oscillatory activities in different brain regions. Changes in interregionally correlated oscillations in animals can reflect behavioral measures (Bressler, 1995, Bressler, 1996; deCharms & Merzenich, 1996; Engel, Konig, & Singer, 1991; Laurent, Wehr, & Davidowitz, 1996; Murthy & Fetz, 1992; Roelfsema, Engel, Konig, & Singer, 1997; Sanes & Donoghue, 1993; Singer, 1993, Singer, 1994, Singer, 1999). This technique has also proven to be useful when applied to surface EEG data (Andrew & Pfurtscheller, 1996; Classen, Gerloff, Honda, & Hallett, 1998; Gerloff, Hadley, et al., 1998; Manganotti et al., 1998; Rappelsberger & Petsche, 1988; Rappelsberger, Pfurtscheller, & Filz, 1994), and is thus available as an instrument for non-invasive studies in humans. Classen et al. (1998) demonstrated significant TRCoh between the visual and motor cortex in a visuomotor tracking task; Gerloff, Hadley, et al. (1998) identified different amounts of network-like activation of human cortical motor areas during internal and external pacing of movement. In both studies, coherence changes in the beta band (13–30 Hz) were most sensitive to changes of the motor aspects of the task. This is further substantiated by the demonstration of functional coupling of primary motor cortex (M1) and muscle (EEG–EMG (electromyography, EMG) or MEG–EMG (magnetoencephalography, MEG) coherence) which also has its maximal amplitude in the beta frequency range (Conway et al., 1995; Halliday, Conway, Farmer, & Rosenberg, 1998; Kilner, Baker, Salenius, Hari, & Lemon, 2000; Kilner et al., 1999; Mima & Matsuoka, 2000). Preliminary data on the functional coupling of visual and somatosensory areas in a task, in which visual and tactile information had to be matched, suggest that high coherence is related to high behavioral efficacy (Hummel & Gerloff, in press). In this predominantly sensory task, the effects were prominent in the alpha frequency range. This is consistent with the view that dynamic modulation of alpha frequencies is more sensitive to variation of somatosensory parameters, while changes in the beta band are more representative of aspects of actual motor control (Salmelin & Hari, 1994). Changes in the gamma band may be particularly involved in sensory awareness (Engel & Singer, 2001).