Literature DB >> 10561425

Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI.

S P Ahlfors1, G V Simpson, A M Dale, J W Belliveau, A K Liu, A Korvenoja, J Virtanen, M Huotilainen, R B Tootell, H J Aronen, R J Ilmoniemi.   

Abstract

A sudden change in the direction of motion is a particularly salient and relevant feature of visual information. Extensive research has identified cortical areas responsive to visual motion and characterized their sensitivity to different features of motion, such as directional specificity. However, relatively little is known about responses to sudden changes in direction. Electrophysiological data from animals and functional imaging data from humans suggest a number of brain areas responsive to motion, presumably working as a network. Temporal patterns of activity allow the same network to process information in different ways. The present study in humans sought to determine which motion-sensitive areas are involved in processing changes in the direction of motion and to characterize the temporal patterns of processing within this network of brain regions. To accomplish this, we used both magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). The fMRI data were used as supplementary information in the localization of MEG sources. The change in the direction of visual motion was found to activate a number of areas, each displaying a different temporal behavior. The fMRI revealed motion-related activity in areas MT+ (the human homologue of monkey middle temporal area and possibly also other motion sensitive areas next to MT), a region near the posterior end of the superior temporal sulcus (pSTS), V3A, and V1/V2. The MEG data suggested additional frontal sources. An equivalent dipole model for the generators of MEG signals indicated activity in MT+, starting at 130 ms and peaking at 170 ms after the reversal of the direction of motion, and then again at approximately 260 ms. Frontal activity began 0-20 ms later than in MT+, and peaked approximately 180 ms. Both pSTS and FEF+ showed long-duration activity continuing over the latency range of 200-400 ms. MEG responses in the region of V3A and V1/V2 were relatively small, and peaked at longer latencies than the initial peak in MT+. These data revealed characteristic patterns of activity in this cortical network for processing sudden changes in the direction of visual motion.

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Year:  1999        PMID: 10561425     DOI: 10.1152/jn.1999.82.5.2545

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  49 in total

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2.  An approach to probe some neural systems interaction by functional MRI at neural time scale down to milliseconds.

Authors:  S Ogawa; T M Lee; R Stepnoski; W Chen; X H Zhu; K Ugurbil
Journal:  Proc Natl Acad Sci U S A       Date:  2000-09-26       Impact factor: 11.205

3.  Spatiotemporal activation of the two visual pathways in form discrimination and spatial location: a brain mapping study.

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Journal:  Hum Brain Mapp       Date:  2003-02       Impact factor: 5.038

Review 4.  How can EEG/MEG and fMRI/PET data be combined?

Authors:  Barry Horwitz; David Poeppel
Journal:  Hum Brain Mapp       Date:  2002-09       Impact factor: 5.038

5.  Multimodal integration of EEG and MEG data: a simulation study with variable signal-to-noise ratio and number of sensors.

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Journal:  Hum Brain Mapp       Date:  2004-05       Impact factor: 5.038

6.  Attentional modulation of neuromagnetic evoked responses in early human visual cortex and parietal lobe following a rank-order rule.

Authors:  Therese Lennert; Roberto Cipriani; Pierre Jolicoeur; Douglas Cheyne; Julio C Martinez-Trujillo
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7.  Spatiotemporal dynamics of feature-based attention spread: evidence from combined electroencephalographic and magnetoencephalographic recordings.

Authors:  Christian Michael Stoppel; Carsten Nicolas Boehler; Hendrik Strumpf; Ruth Marie Krebs; Hans-Jochen Heinze; Jens-Max Hopf; Mircea Ariel Schoenfeld
Journal:  J Neurosci       Date:  2012-07-11       Impact factor: 6.167

8.  fMRI functional networks for EEG source imaging.

Authors:  Xu Lei; Peng Xu; Cheng Luo; Jinping Zhao; Dong Zhou; Dezhong Yao
Journal:  Hum Brain Mapp       Date:  2010-09-02       Impact factor: 5.038

9.  fMRI-constrained MEG source imaging and consideration of fMRI invisible sources.

Authors:  Chang-Hwan Im; Hyun-Kyo Jung; Norio Fujimaki
Journal:  Hum Brain Mapp       Date:  2005-10       Impact factor: 5.038

10.  Combining fMRI with EEG and MEG in order to relate patterns of brain activity to cognition.

Authors:  Walter J Freeman; Seppo P Ahlfors; Vinod Menon
Journal:  Int J Psychophysiol       Date:  2009-02-20       Impact factor: 2.997

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