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Best of both worlds: promise of combining brain stimulation and brain connectome.

Luft CD, Pereda E, Banissy MJ, Bhattacharya J - Front Syst Neurosci (2014)

Bottom Line: Transcranial current brain stimulation (tCS) is becoming increasingly popular as a non-pharmacological non-invasive neuromodulatory method that alters cortical excitability by applying weak electrical currents to the scalp via a pair of electrodes.In these applications, similarly to lesion studies, tCS was used to provide a causal link between a function or behavior and a specific brain region (e.g., primary motor cortex).Nonetheless, complex cognitive functions are known to rely on functionally connected multitude of brain regions with dynamically changing patterns of information flow rather than on isolated areas, which are most commonly targeted in typical tCS experiments.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Goldsmiths, University of London London, UK.

ABSTRACT
Transcranial current brain stimulation (tCS) is becoming increasingly popular as a non-pharmacological non-invasive neuromodulatory method that alters cortical excitability by applying weak electrical currents to the scalp via a pair of electrodes. Most applications of this technique have focused on enhancing motor and learning skills, as well as a therapeutic agent in neurological and psychiatric disorders. In these applications, similarly to lesion studies, tCS was used to provide a causal link between a function or behavior and a specific brain region (e.g., primary motor cortex). Nonetheless, complex cognitive functions are known to rely on functionally connected multitude of brain regions with dynamically changing patterns of information flow rather than on isolated areas, which are most commonly targeted in typical tCS experiments. In this review article, we argue in favor of combining tCS method with other neuroimaging techniques (e.g., fMRI, EEG) and by employing state-of-the-art connectivity data analysis techniques (e.g., graph theory) to obtain a deeper understanding of the underlying spatiotemporal dynamics of functional connectivity patterns and cognitive performance. Finally, we discuss the possibilities of using these combined techniques to investigate the neural correlates of human creativity and to enhance creativity.

No MeSH data available.


Related in: MedlinePlus

Schematic representation of the possible combination of tCS and functional (EEG) brain connectivity to enhance creativity. An array of scalp electrodes, a subset of which is depicted in (A), is recorded. In (B) is possible to identify ROIs which are highly connected (yellow) and the ones that are flexible hubs (red) or less connected areas (blue) during a solution vs. non-solution RAT task. This helps identifying the target electrodes to stimulate as in (C). Stimulating these electrodes may not only eliminate the differences for the corresponding nodes, but also reduce them for areas in the same network, which are not stimulated but functionally connected to the targeted ones as depicted in (D). It is worth noting that the labels and the networks drawn in the figure are only for demonstration, as they are not precisely equivalent to their anatomical locations (they are only approximate locations on a surface, the areas in yellow are located in the medial area of the brain, which cannot be seen in a cortical mesh). The areas are abbreviated as follows: PCC, posterior cingulate cortex; PPC, posterior parietal cortex; M1, primary motor cortex; mPFC, medial prefrontal cortex; ACC, anterior cingulate cortex; DLPFC, dorsolateral prefrontal cortex; ATL, anterior temporal lobe.
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Figure 2: Schematic representation of the possible combination of tCS and functional (EEG) brain connectivity to enhance creativity. An array of scalp electrodes, a subset of which is depicted in (A), is recorded. In (B) is possible to identify ROIs which are highly connected (yellow) and the ones that are flexible hubs (red) or less connected areas (blue) during a solution vs. non-solution RAT task. This helps identifying the target electrodes to stimulate as in (C). Stimulating these electrodes may not only eliminate the differences for the corresponding nodes, but also reduce them for areas in the same network, which are not stimulated but functionally connected to the targeted ones as depicted in (D). It is worth noting that the labels and the networks drawn in the figure are only for demonstration, as they are not precisely equivalent to their anatomical locations (they are only approximate locations on a surface, the areas in yellow are located in the medial area of the brain, which cannot be seen in a cortical mesh). The areas are abbreviated as follows: PCC, posterior cingulate cortex; PPC, posterior parietal cortex; M1, primary motor cortex; mPFC, medial prefrontal cortex; ACC, anterior cingulate cortex; DLPFC, dorsolateral prefrontal cortex; ATL, anterior temporal lobe.

Mentions: Based on the previous discussions, we propose a hypothetical approach for combining neuroimaging, connectivity and brain stimulation for improving creativity (Figure 2). In this approach, the research starts with the graph theoretical analysis of the connectivity between the regions involved in a certain process (e.g., convergent thinking—insight) as in Figure 2A. Using the discovered cognitive connections (Figure 2B), a protocol for stimulation is determined (Figure 2C). In Figure 2A, we showed a couple of regions involved in creativity. Immediately after the stimulation, the connectivity patterns (in identical conditions of the analyzed patterns in Figures 2A,B) are analyzed against control stimulation protocol, e.g., sham stimulation. The results are presented as a map, with the edges linking the nodes representing here the strength of the difference in connectivity between active and sham stimulation (or any other control or contrast of the experiment), as in Figure 2D. In Figure 2 hypothetical example, the connectivity changed after stimulation of the left DLPFC during a RAT paradigm, especially among the temporal and frontal areas (Figure 2D). In the hypothetical example, there was an increase in communication between ATL and DLPFC and between the DLPFC and the ACC, which could represent coordinated (DLPFC) search of the solution in memory (ATL) and the recognition of the correct solution (ACC), from DLPFC to ACC. Note that this approach does not account for the direction of the interactions, which could be also tested using effective connectivity analysis techniques such as dynamic causal modeling or Granger causality. In divergent thinking, the approach would probably result in a higher change over the posterior rather than anterior regions.


Best of both worlds: promise of combining brain stimulation and brain connectome.

Luft CD, Pereda E, Banissy MJ, Bhattacharya J - Front Syst Neurosci (2014)

Schematic representation of the possible combination of tCS and functional (EEG) brain connectivity to enhance creativity. An array of scalp electrodes, a subset of which is depicted in (A), is recorded. In (B) is possible to identify ROIs which are highly connected (yellow) and the ones that are flexible hubs (red) or less connected areas (blue) during a solution vs. non-solution RAT task. This helps identifying the target electrodes to stimulate as in (C). Stimulating these electrodes may not only eliminate the differences for the corresponding nodes, but also reduce them for areas in the same network, which are not stimulated but functionally connected to the targeted ones as depicted in (D). It is worth noting that the labels and the networks drawn in the figure are only for demonstration, as they are not precisely equivalent to their anatomical locations (they are only approximate locations on a surface, the areas in yellow are located in the medial area of the brain, which cannot be seen in a cortical mesh). The areas are abbreviated as follows: PCC, posterior cingulate cortex; PPC, posterior parietal cortex; M1, primary motor cortex; mPFC, medial prefrontal cortex; ACC, anterior cingulate cortex; DLPFC, dorsolateral prefrontal cortex; ATL, anterior temporal lobe.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4115621&req=5

Figure 2: Schematic representation of the possible combination of tCS and functional (EEG) brain connectivity to enhance creativity. An array of scalp electrodes, a subset of which is depicted in (A), is recorded. In (B) is possible to identify ROIs which are highly connected (yellow) and the ones that are flexible hubs (red) or less connected areas (blue) during a solution vs. non-solution RAT task. This helps identifying the target electrodes to stimulate as in (C). Stimulating these electrodes may not only eliminate the differences for the corresponding nodes, but also reduce them for areas in the same network, which are not stimulated but functionally connected to the targeted ones as depicted in (D). It is worth noting that the labels and the networks drawn in the figure are only for demonstration, as they are not precisely equivalent to their anatomical locations (they are only approximate locations on a surface, the areas in yellow are located in the medial area of the brain, which cannot be seen in a cortical mesh). The areas are abbreviated as follows: PCC, posterior cingulate cortex; PPC, posterior parietal cortex; M1, primary motor cortex; mPFC, medial prefrontal cortex; ACC, anterior cingulate cortex; DLPFC, dorsolateral prefrontal cortex; ATL, anterior temporal lobe.
Mentions: Based on the previous discussions, we propose a hypothetical approach for combining neuroimaging, connectivity and brain stimulation for improving creativity (Figure 2). In this approach, the research starts with the graph theoretical analysis of the connectivity between the regions involved in a certain process (e.g., convergent thinking—insight) as in Figure 2A. Using the discovered cognitive connections (Figure 2B), a protocol for stimulation is determined (Figure 2C). In Figure 2A, we showed a couple of regions involved in creativity. Immediately after the stimulation, the connectivity patterns (in identical conditions of the analyzed patterns in Figures 2A,B) are analyzed against control stimulation protocol, e.g., sham stimulation. The results are presented as a map, with the edges linking the nodes representing here the strength of the difference in connectivity between active and sham stimulation (or any other control or contrast of the experiment), as in Figure 2D. In Figure 2 hypothetical example, the connectivity changed after stimulation of the left DLPFC during a RAT paradigm, especially among the temporal and frontal areas (Figure 2D). In the hypothetical example, there was an increase in communication between ATL and DLPFC and between the DLPFC and the ACC, which could represent coordinated (DLPFC) search of the solution in memory (ATL) and the recognition of the correct solution (ACC), from DLPFC to ACC. Note that this approach does not account for the direction of the interactions, which could be also tested using effective connectivity analysis techniques such as dynamic causal modeling or Granger causality. In divergent thinking, the approach would probably result in a higher change over the posterior rather than anterior regions.

Bottom Line: Transcranial current brain stimulation (tCS) is becoming increasingly popular as a non-pharmacological non-invasive neuromodulatory method that alters cortical excitability by applying weak electrical currents to the scalp via a pair of electrodes.In these applications, similarly to lesion studies, tCS was used to provide a causal link between a function or behavior and a specific brain region (e.g., primary motor cortex).Nonetheless, complex cognitive functions are known to rely on functionally connected multitude of brain regions with dynamically changing patterns of information flow rather than on isolated areas, which are most commonly targeted in typical tCS experiments.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Goldsmiths, University of London London, UK.

ABSTRACT
Transcranial current brain stimulation (tCS) is becoming increasingly popular as a non-pharmacological non-invasive neuromodulatory method that alters cortical excitability by applying weak electrical currents to the scalp via a pair of electrodes. Most applications of this technique have focused on enhancing motor and learning skills, as well as a therapeutic agent in neurological and psychiatric disorders. In these applications, similarly to lesion studies, tCS was used to provide a causal link between a function or behavior and a specific brain region (e.g., primary motor cortex). Nonetheless, complex cognitive functions are known to rely on functionally connected multitude of brain regions with dynamically changing patterns of information flow rather than on isolated areas, which are most commonly targeted in typical tCS experiments. In this review article, we argue in favor of combining tCS method with other neuroimaging techniques (e.g., fMRI, EEG) and by employing state-of-the-art connectivity data analysis techniques (e.g., graph theory) to obtain a deeper understanding of the underlying spatiotemporal dynamics of functional connectivity patterns and cognitive performance. Finally, we discuss the possibilities of using these combined techniques to investigate the neural correlates of human creativity and to enhance creativity.

No MeSH data available.


Related in: MedlinePlus