Cortical functional connectivity is associated with the valence of affective states

Wyczesany, Mirosław; Ferdek, Magdalena A.; Grzybowski, Szczepan J.

doi:10.1016/j.bandc.2014.06.001

Cited by 22 publications

(18 citation statements)

References 55 publications

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“…It is worth reflection that in practice results of DTF analysis correspond very well with known neuroimaging, intracranial and electrophysiological evidence including topographic accuracy (Ginter et al, 2001; Kuś et al, 2006; Blinowska et al, 2010, 2013; Brzezicka et al, 2010; Wyczesany et al, 2014, 2015; Ligeza et al, 2016). As an example may serve the finger movement task.…”

supporting

confidence: 65%

The Influence of Volume Conduction on DTF Estimate and the Problem of Its Mitigation

Kamiński

Blinowska

2017

Front. Comput. Neurosci.

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supporting

confidence: 65%

The Influence of Volume Conduction on DTF Estimate and the Problem of Its Mitigation

Kamiński

Blinowska

2017

Front. Comput. Neurosci.

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“…Based on EEG montage brain atlases (Kaiser 2007; Okamoto et al 2004), electrodes corresponding to our regions of interest were selected as follows: left DLPFC (LDLPFC: F3); right DLPFC (RDLPFC: F4), ACC (Fz); left temporal area (LTmp: T7, TP7); and right temporal area (RTmp: T8, TP8). The DTF values were calculated for the whole beta band, as this frequency window covers an important part of middle- and long-range cortical communication (Kuś, Blinowska, Kamiński, & Basińska-Starzycka, 2008; Wyczesany et al, 2014a). Group and valence differences in effective connectivity were examined for the following ROIs in both directions separately: LDLPFC↔LTmp; RDLPFCR↔RTmp; LDLPFC↔RTmp; RDLPFC↔LTmp; LDLPFC↔ACC; RDLPFC↔ACC; (repeated-measures MANOVA).…”

Section: Methodsmentioning

confidence: 99%

“…Despite the fact that many diverse strategies of emotional control exist, all of them seem to depend on a similar emotional control circuit, which comprises the regulatory loop between the prefrontal cortex, limbic cortex, and other limbic regions such as the amygdala and hippocampus (Ochsner, Bunge, Gross, & Gabrieli, 2002). Within this circuit, effective emotional control (down-regulation of negative emotional states) is manifested by higher activation of the prefrontal cortex and decreased activation of the limbic structures (Taylor & Liberzon, 2007), as well as increased connectivity of the prefrontal cortex, which possibly initiates the modulating actions (Wyczesany, Ferdek & Grzybowski, 2014; Wyczesany, Ligeza & Grzybowski, 2014). Supporting this assertion, it was found by Banks et al (2007) that the fronto-limbic coupling may be a predictor of the successful top-down cognitive modulation of the negative affect.…”

Section: Introductionmentioning

confidence: 99%

Depressive rumination and the emotional control circuit: An EEG localization and effective connectivity study

Ferdek

Rijn

Wyczesany

2016

Cogn Affect Behav Neurosci

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Ruminations are repetitive thoughts associated with symptoms, causes, and consequences of one’s negative feelings. The objective of this study was to explore the neuronal basis of depressive rumination in a non-clinical population within the context of emotional control. Participants scoring high or low on the tendency to ruminate scale took part in the EEG experiment. Their EEG data were collected during a state of induced depressive ruminations and compared with positive and neutral conditions. We hypothesized that both groups would differ according to the level of activation and effective connectivity among the structures involved in the emotional control circuit. Clustering of independent components, together with effective connectivity (Directed Transfer Function), was performed using the EEG signal. The main findings involved decreased activation of the left dorsolateral prefrontal cortex (DLPFC) and increased activation of the left temporal lobe structures in the highly ruminating group. The latter result was most pronounced during the ruminative condition. Decreased information from the left DLPFC to the left temporal lobe structures was also found, leading to the conclusion that hypoactivation of the left DLPFC and its inability to modulate the activation of the left temporal lobe structures is crucial for the ruminative tendencies.

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“…The first approach is to perform causal connectivity analysis as described in Sect. 2.2 directly on the available sensor time series Y(t) (Kaminski and Blinowska 2014;Wyczesany et al 2014;. This implies considering the MVAR model ( ) = 2 5 6 ( ) ( − ) + 6 7 ( ) ,…”

Section: Assessment Of Causal Connectivity For Eeg Time Seriesmentioning

confidence: 99%

Critical Comments on EEG Sensor Space Dynamical Connectivity Analysis

et al. 2016

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Many different analysis techniques have been developed and applied to EEG recordings that allow one to investigate how different brain areas interact. One particular class of methods, based on the linear parametric representation of multiple interacting time series, is widely used to study causal connectivity in the brain. However, the results obtained by these methods should be interpreted with great care. The goal of this paper is to show, both theoretically and using simulations, that results obtained by applying causal connectivity measures on the sensor (scalp) time series do not allow interpretation in terms of interacting brain sources. This is because 1) the channel locations cannot be seen as an approximation of a source's anatomical location and 2) spurious connectivity can occur between sensors. Although many measures of causal connectivity derived from EEG sensor time series are affected by the latter, here we will focus on the well-known time domain index of Granger causality (GC) and on the frequency domain directed transfer function (DTF). Using the state-space framework and designing two simulation studies we show that mixing effects caused by volume conduction can lead to spurious connections, detected either by time domain GC or by DTF. Therefore, GC/DTF causal connectivity measures should be computed at the source level, or derived within analysis frameworks that model the effects of volume conduction. Since mixing effects can also occur in the source space, it is advised to combine source space analysis with connectivity measures that are robust to mixing.

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Cortical functional connectivity is associated with the valence of affective states

Cited by 22 publications

References 55 publications

The Influence of Volume Conduction on DTF Estimate and the Problem of Its Mitigation

The Influence of Volume Conduction on DTF Estimate and the Problem of Its Mitigation

Depressive rumination and the emotional control circuit: An EEG localization and effective connectivity study

Critical Comments on EEG Sensor Space Dynamical Connectivity Analysis

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