Literature DB >> 7833694

Neurophysiological differences between perception and imagery.

H T Schupp1, W Lutzenberger, N Birbaumer, W Miltner, C Braun.   

Abstract

The present study was designed to examine brain activity underlying mental imagery is conceptualized as behavior guided by internal representation only, the activity of the prefrontal lobes was assumed to be a measure of differentiation of imagery from perception. Twenty-one subjects were requested to observe and imagine a swinging pendulum and to touch and imagine a coshball in separate trials. The EEG was recorded from 15 standard electrode sites and analyzed with (1) traditional alpha power and (2) an estimation of dimensional complexity (a measure derived from nonlinear dynamics). Both EEG measures revealed expected object-related differences during perception as well as during imagery. The visual pendulum showed relative to the tactile coshball increased dimensional complexity and less alpha power at parietal and frontal sites. However, only the EEG dimension supported the main hypothesis: Imagery resulted in increased prefrontal dimensional complexity in comparison to perception independent of the modality of the image. In contrast, for alpha power the difference between imagery and perception was due to stimulus modality.

Mesh:

Year:  1994        PMID: 7833694     DOI: 10.1016/0926-6410(94)90004-3

Source DB:  PubMed          Journal:  Brain Res Cogn Brain Res        ISSN: 0926-6410


  7 in total

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2.  Drawing on mind's canvas: differences in cortical integration patterns between artists and non-artists.

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4.  Competitive Frontoparietal Interactions Mediate Implicit Inferences.

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5.  Nonlinear Analysis of Eye-Tracking Information for Motor Imagery Assessments.

Authors:  Antonio Lanata; Laura Sebastiani; Francesco Di Gruttola; Stefano Di Modica; Enzo Pasquale Scilingo; Alberto Greco
Journal:  Front Neurosci       Date:  2020-01-15       Impact factor: 4.677

6.  Attending to Visual Stimuli versus Performing Visual Imagery as a Control Strategy for EEG-based Brain-Computer Interfaces.

Authors:  Nataliya Kosmyna; Jussi T Lindgren; Anatole Lécuyer
Journal:  Sci Rep       Date:  2018-09-05       Impact factor: 4.379

7.  Visual Modulation of Resting State α Oscillations.

Authors:  Kelly Webster; Tony Ro
Journal:  eNeuro       Date:  2020-01-03
  7 in total

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