EEG Microstate Correlates of Fluid Intelligence and Response to Cognitive Training

Santarnecchi, Emiliano; Khanna, Arjun; Musaeus, Christian Sandøe; Benwell, Christopher S. Y.; Davila, Paula; Farzan, Faranak; Matham, Santosh; Pascual‐Leone, Álvaro; Shafi, Mouhsin M.

doi:10.1007/s10548-017-0565-z

Cited by 67 publications

(51 citation statements)

References 105 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The synergy between WM and other functions such as attention has been postulated (Shipstead, Harrison, & Engle, ). A similar overlap has been recently identified for fluid intelligence (Santarnecchi, Emmendorfer, & Pascual‐Leone, , Santarnecchi, Khanna, Musaeus, et al, ), a function highly correlated with WM (Friedman et al, ).…”

Section: Discussionsupporting

confidence: 79%

See 1 more Smart Citation

Stimuli, presentation modality, and load‐specific brain activity patterns during n‐back task

Mencarelli

Neri

Momi

et al. 2019

Human Brain Mapping

Self Cite

View full text Add to dashboard Cite

Working memory (WM) refers to a set of cognitive processes that allows for the temporary storage and manipulation of information, crucial for everyday life skills. WM deficits are present in several neurological, psychiatric, and neurodevelopmental disorders, thus making the full understanding of its neural correlates a key aspect for the implementation of cognitive training interventions. Here, we present a quantitative meta‐analysis focusing on the underlying neural substrates upon which the n‐back, one of the most commonly used tasks for WM assessment, is believed to rely on, as highlighted by functional magnetic resonance imaging and positron emission tomography findings. Relevant published work was scrutinized through the activation likelihood estimate (ALE) statistical framework in order to generate a set of task‐specific activation maps, according to n‐back difficulty. Our results confirm the known involvement of frontoparietal areas across different types of n‐back tasks, as well as the recruitment of subcortical structures, cerebellum and precuneus. Specific activations maps for four stimuli types, six presentation modalities, three WM loads and their combination are provided and discussed. Moreover, functional overlap with resting‐state networks highlighted a strong similarity between n‐back nodes and the Dorsal Attention Network, with less overlap with other networks like Salience, Language, and Sensorimotor ones. Additionally, neural deactivations during n‐back tasks and their functional connectivity profile were examined. Clinical and functional implications are discussed in the context of potential noninvasive brain stimulation and cognitive enhancement/rehabilitation programs.

show abstract

Section: Discussionsupporting

confidence: 79%

“…From the first fMRI study aimed at analyzing brain activation dur- (Shipstead, Harrison, & Engle, 2015). A similar overlap has been recently identified for fluid intelligence , Santarnecchi, Khanna, Musaeus, et al, 2017, a function highly correlated with WM (Friedman et al, 2006).…”

Section: Overlap Between N-back Task Network and Rsnmentioning

confidence: 62%

Stimuli, presentation modality, and load‐specific brain activity patterns during n‐back task

Mencarelli

Neri

Momi

et al. 2019

Human Brain Mapping

Self Cite

View full text Add to dashboard Cite

show abstract

“…Such an interpretation was also put forward in a study describing negative correlations of microstate C occurrence and fluid intelligence (Santarnecchi et al, 2017). Tomescu and colleagues (Tomescu et al, 2015;Tomescu et al, 2014) examined patients with 22q11 deletion syndrome, who have a 30% increase in the risk of developing schizophrenia relative to healthy controls.…”

Section: A C C E P T E D Accepted Manuscriptmentioning

confidence: 96%

“…conditions or groups (Nishida et al, 2013;Santarnecchi et al, 2017;Zappasodi et al, 2017). The boxplot in Figure 4 illustrates the different steps of microstate analysis.…”

Section: Determining Microstates: Fitting the Cluster Maps To The Datamentioning

confidence: 99%

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

2018

View full text Add to dashboard Cite

SummaryThe present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of largescale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales.The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates.

show abstract

“…Zappasodi et al (2019) also found that the microstates related to visual (MS2) and default-mode network (MS3) were modulated by visuospatial tasks, which reflect that the contribution of MS2 was significantly increased under visuospatial tasks, while the contribution of MS2 was significantly decreased. Moreover, Santarnecchi et al (2017) found that the RS-EEG microstates of MS2 and MS3 were related to fluid intelligence, where they found that the occurrences of MS2 and MS3 were significantly negatively related to fluid intelligence, and the contribution of MS2 was negatively associated with the increase of fluid intelligence after training it.…”

Section: Introductionmentioning

confidence: 99%

The Relationships Between Trait Creativity and Resting-State EEG Microstates Were Modulated by Self-Esteem

Guo

Wang

et al. 2020

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Numerous studies find that creativity is not only associated with low effort and flexible processes but also associated with high effort and persistent processes especially when defensive behavior is induced by negative emotions. The important role of self-esteem is to buffer negative emotions, and individuals with low self-esteem are prone to instigating various forms of defensive behaviors. Thus, we thought that the relationships between trait creativity and executive control brain networks might be modulated by self-esteem. The resting-state electroencephalogram (RS-EEG) microstates can be divided into four classical types (MS1, MS2, MS3, and MS4), which can reflect the brain networks as well as their dynamic characteristic. Thus, the Williams Creative Tendency Scale (WCTS) and Rosenberg Self-esteem Scale (RSES) were used to investigate the modulating role of self-esteem on the relationships between trait creativity and the RS-EEG microstates. As our results showed, self-esteem consistently modulated the relationships between creativity and the duration and contribution of MS2 related to visual or imagery processing, the occurrence of MS3 related to cingulo-opercular networks, and transitions between MS2 and MS4, which were related to frontoparietal control networks. Based on these results, we thought that trait creativity was related to the executive control of bottom-up processing for individuals with low self-esteem, while the bottom-up information from vision or visual imagery might be related to trait creativity for individuals with high self-esteem.

show abstract

EEG Microstate Correlates of Fluid Intelligence and Response to Cognitive Training

Cited by 67 publications

References 105 publications

Stimuli, presentation modality, and load‐specific brain activity patterns during n‐back task

Stimuli, presentation modality, and load‐specific brain activity patterns during n‐back task

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

The Relationships Between Trait Creativity and Resting-State EEG Microstates Were Modulated by Self-Esteem

Contact Info

Product

Resources

About