Actor's and observer's primary motor cortices stabilize similarly after seen or heard motor actions Gina Caetano*, Veikko Jousmäki*, and Riitta Hari*,, *Brain Research Unit, Low Temperature Laboratory, Helsinki University of Technology, P.O. Box 2200, FIN-02015 HUT, Espoo, Finland; and Department of Clinical Neurophysiology, Helsinki University Central Hospital, FIN-00290, Helsinki, Finland Contributed by Riitta Hari, March 15, 2007 (received for review July 3, 2006) We quantified rhythmic brain activity, recorded with whole-scalp magnetoencephalography (MEG), of 13 healthy subjects who were performing, seeing, or hearing the tapping of a drum membrane with the right index finger. In the actor's primary motor (M1) cortex, the level of the 20-Hz brain rhythms started to decrease, as a sign of M1 activation, 2 s before the action and then increased, with a clear rebound 0.6 s after the tapping, as a sign of M1 stabilization. A very similar time course occurred in the M1 cortex of the observer: the activation, although less vigorous than in the actor, started 0.8 s before the action and was followed by a rebound. When the subject just heard the tapping sound, no preaction activation was visible, but a rebound followed the sound. The 10-Hz somatosensory rhythm, which also started to decrease before own and viewed actions, returned to the baseline level 0.6 s later after own actions than observed actions. This delay likely reflects proprioceptive input to the cortex, available only during own actions, and therefore could be related to the brain signature of the sense of agency. The strikingly similar motor cortex reactivity during the first and third person actions expands previous data on brain mechanisms of intersubjective understanding. Besides motor cortex activation before own and observed (predicted) actions, the M1 cortex of both the viewer and the listener stabilized in a very similar manner after brisk motor actions. brain rhythms | intersubjectivity | magnetoencephalography | mirror neurons | motor cortex -------------------------------------------------------------------------------- Freely available online through the PNAS open access option. Author contributions: G.C., V.J., and R.H. designed research; G.C. performed research; V.J. contributed new nonmagnetic drum tools; G.C. and R.H. analyzed data; and G.C., V.J., and R.H. wrote the paper. The authors declare no conflict of interest. See Commentary on page 8683. This article contains supporting information online at www.pnas.org/cgi/content/full/0702453104/DC1. To whom correspondence should be addressed. E-mail: hari@neuro.hut.fi

We used magnetoencephalography (MEG) to map the spatiotemporal evolution of cortical activity for visual word recognition. We show that for five-letter words, activity in the left hemisphere (LH) fusiform gyrus expands systematically in both the posterior-anterior and medial-lateral directions over the course of the first 500 ms after stimulus presentation. Contrary to what would be expected from cognitive models and hemodynamic studies, the component of this activity that spatially coincides with the visual word form area (VWFA) is not active until around 200 ms post-stimulus, and critically, this activity is preceded by and co-active with activity in parts of the inferior frontal gyrus (IFG, BA44/6). The spread of activity in the VWFA for words does not appear in isolation but is co-active in parallel with spread of activity in anterior middle temporal gyrus (aMTG, BA 21 and 38), posterior middle temporal gyrus (pMTG, BA37/39), and IFG.

Partial least squares (PLS) analysis has been used to characterize distributed signals measured by neuroimaging methods like positron emission tomography (PET), functional magnetic resonance imaging (fMRI), event-related potentials (ERP) and magnetoencephalography (MEG). In the application to PET, it has been used to extract activity patterns differentiating cognitive tasks, patterns relating distributed activity to behavior, and to describe large-scale interregional interactions or functional connections. This paper reviews the more recent extension of PLS to the analysis of spatiotemporal patterns present in fMRI, ERP, and MEG data. We present a basic mathematical description of PLS and discuss the statistical assessment using permutation testing and bootstrap resampling. These two resampling methods provide complementary information of the statistical strength of the extracted activity patterns (permutation test) and the reliability of regional contributions to the patterns (bootstrap resampling). Simulated ERP data are used to guide the basic interpretation of spatiotemporal PLS results, and examples from empirical ERP and fMRI data sets are used for further illustration. We conclude with a discussion of some caveats in the use of PLS, including nonlinearities, nonorthogonality, and interpretation difficulties. We further discuss its role as an important tool in a pluralistic analytic approach to neuroimaging.

DA - 20050829 IS - 1097-6256 LA - eng PT - Journal Article SB - IM

Times Cited: 17 Article English Krumbholz, K KFA Julich GmbH, Forschungszentrum, IME, AG Kognit Neurol, D-52425 Julich, Germany Cited References Count: 27 695NG JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA CARY

Results from several recent studies suggest that neuronal processing of sound content and its spatial location may be dissociated. The use of modern neuroimaging techniques has allowed for the determination that different brain structures may be specifically activated during working memory processing of pitch and location of sound. The time course of these task-related differences, however, remains uncertain. In the present study, we performed simultaneous whole-head electroencephalogram and magnetoencephalogram recordings, using a new behavioral paradigm, to investigate the dynamics of differences between "what" and "where" evoked responses in the auditory system as a function of memory load. In the location task the latency of the N1m was shorter and its generator was situated more inferiorly than in the pitch task. Working memory processing of the tonal frequency enhanced the amplitude of the N2 component, as well as the negative-going deflection at a latency around 400 ms. A memory-load-dependent task-related difference was found in the positive slow wave which was higher during the location than pitch task at the low load. Late slow waves were affected by memory load but not type of task. These results suggest that separate neuronal networks are involved in the attribute-specific analysis of auditory stimuli and their encoding into working memory, whereas the maintenance of auditory information is accomplished by a common, nonspecific neuronal network.

OBJECTIVE: Slow evoked responses have been extensively studied using electrophysiological and neuroimaging methods, but there is no consensus regarding their generators. We investigated the generators of the P3 and positive slow wave (PSW) in the evoked responses to probes recorded during auditory working memory tasks to find out whether there is dissociation between functional networks involved in the generation of the P3 and PSW and between spatial and nonspatial auditory processing within this time window. METHODS: Whole-head magneto-(MEG) and electroencephalography (EEG); analysis of MEG data using minimum-norm current estimates. RESULTS: The associative temporal, occipito-temporal and parietal areas contributed to the generation of the slow evoked responses. The temporal source increased while the occipito-temporal source diminished activity during transition from the P3 to PSW. The occipito-temporal generator of the P3 was activated more during the spatial than nonspatial task, and the left temporal generator of the PSW tended to be more strongly activated during the nonspatial task. CONCLUSIONS: These findings indicate that partially distinct functional networks generate the P3 and PSW and provide evidence for segregation of spatial and nonspatial auditory information processing in associative areas beyond the supratemporal auditory cortex. SIGNIFICANCE: The present results support the dual-stream model for auditory information processing.