Hostname: page-component-745bb68f8f-b6zl4 Total loading time: 0 Render date: 2025-01-10T15:39:13.605Z Has data issue: false hasContentIssue false
  • English
  • Français

Cross Frequency Modulation and Cognitive Performance

Published online by Cambridge University Press:  15 April 2020

P.L. Marconi ,
R. Tambelli ,
M.P. Penna ,
C. Trentini  and
B. Volpi
P.L. Marconi
Affiliation:
Department of Dynamic and Clinical Psychology, Sapienza University of Rome, Roma, Italy
R. Tambelli
Affiliation:
Department of Dynamic and Clinical Psychology, Faculty of Medicine and Psychology University of Rome Sapienza, Roma, Italy
M.P. Penna
Affiliation:
Department of Pedagogy Psychology and Philosophy, University of Cagliari, Cagliari, Italy
C. Trentini
Affiliation:
Department of Dynamic and Clinical Psychology, Sapienza University of Rome, Rome, Italy
B. Volpi
Affiliation:
Department of Dynamic and Clinical Psychology, Sapienza University of Rome, Rome, Italy

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Background

Cross-frequency modulation (CfM) supports the synchronization and the coordination of the high-frequency activity of large brain areas and it may represent a generalized mode of systems communication and integration (Canolty and Knight, 2010). CfM, therefore, it is likely to be a key element of the brain integration (He et al, 2010), featuring the learning process (Tort et al, 2009), the higher cognitive functions and the healthy thought process (Allen et al, 2011) as well as the emergence of consciousness (Melloni et al, 2007, Tononi, 2010).

Aim of the Study

The present study was focused on the relationship between CfM and cognitive performance compared withother classical neurophysiologic parameters.

Methods

A cognitive task, similar to the WCST, was developed. 71 Channels EEG was recorded by means of EGI Geodesic equipment set to a sample ratio of 250 Hz. Data are processed using the EEGLAB Matlab Package (Delorme and Makeig, 2004). Independent Component Analysis, Cluster Analysis with dipole projection were performed. Cross Frequency Modulation (CfM) indexes between EEG low frequency phase and high frequency amplitude have been computed also.

Results

Present preliminary data are performed on a sample of healthy subjects, aged between 20 and 45 years old. Avarage response time was about 2 sec, and an anticipation of the P3 pick was observed the case of a persistent correct answers. A greater CfM was associated to best performances, in some clusters only.

Conclusions

This preliminary results support the hypothesis that CfM may have a role in brain network integration.

Type
Article: 1230
Information
European Psychiatry , Volume 30 , Issue S1: Abstracts of the 23rd European Congress of Psychiatry , March 2015 , pp. 1
Copyright
Copyright © European Psychiatric Association 2015
Submit a response

Comments

No Comments have been published for this article.