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HYPERSCANNING 2.0

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Hyperscanning 2.0 Analyses of Multimodal Neuroimaging Data Concept Methods and...

Hyperscanning 2.0 Analyses of Multimodal Neuroimaging Data Concept Methods and Applications "Classical ""Hyperscanning"" is concerned with determining brain interactions of two subjects by analyzing correlations of their brain signals. We here define ""Hyperscanning 2.0"" as a broader concept, which refers to the analysi... ver más

31/12/2016

TUB

209K€

Presupuesto del proyecto: 209K€

Líder del proyecto

TECHNISCHE UNIVERSITAT BERLIN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2016-12-31 No tenemos la información de la convocatoria

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1 Participantes

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Líder del proyecto

TECHNISCHE UNIVERSITAT BERLIN No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 209K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto "Classical ""Hyperscanning"" is concerned with determining brain interactions of two subjects by analyzing correlations of their brain signals. We here define ""Hyperscanning 2.0"" as a broader concept, which refers to the analysis of (arbitrarily) coupled brain activity in multiple datasets that are temporally synchronized. With this definition, applications of Hyperscanning 2.0 range from the analysis of brain responses to repeated complex stimulation to the determination of interactions between different types of brain signals of multiple subjects in multi-modal recordings. In this research proposal, we will use Hyperscanning 2.0 for detecting specific multi-modal brain signatures of visual attention and attentional shifts during movie viewing, as well as of emotional valence in clinical populations suffering from Major Depressive Disorder (MDD). To this end, we will collect and analyze respective electroencephalography (EEG) and functional magentic resonance imaging (fMRI) data. Many of the computational tools needed for carrying out Hyperscanning 2.0 analyses are yet to be developed. With this project we will provide a blind source separation (BSS) framework for optimally extracting latent (not directly observable) brain processes with well-defined similarities/couplings from multiple neuroimaging datasets. Within this framework we will implement two algorithms, canonical and hyper source power correlation analysis (cSPoC and HyperSPoC), which will for the first time enable the optimal treatment of an important class of neurophysiological features - namely brain oscillations - in a Hyperscanning setting. Since our algorithms will be capable of isolating brain activity of interest in the absense of external trigger information, they will enable the study of attention and emotion in more realistic scenarios than previous approaches and thereby promise to contribute to a better understanding of these cognitive functions in healthy subjects and patients in the future."

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