http://www.cognitiveneuroscience.it/wp-content/uploads/2015/11/Woods_et_al_clinph_tES_2016.pdf

A technical guide to tDCS, and related non-invasive brain stimulation tools

Low intensity transcranial electric stimulation: Safety, ethical, legal regulatory and application guidelines

Adverse events of tDCS and tACS: A review

Functional role of frontal alpha oscillations in creativity

Perception, cognition and consciousness can be modulated as a function of oscillating neural activity, while ongoing neuronal dynamics are influenced by synaptic activity and membrane potential. Consequently, transcranial alternating current stimulation (tACS) may be used for neurological intervention. The advantageous features of tACS include the biphasic and sinusoidal tACS currents, the ability to entrain large neuronal populations, and subtle control over somatic effects. Through neuromodulation of phasic, neural activity, tACS is a powerful tool to investigate the neural correlates of cognition. The rapid development in this area requires clarity about best practices. Here we briefly introduce tACS and review the most compelling findings in the literature to provide a starting point for using tACS. We suggest that tACS protocols be based on functional brain mechanisms and appropriate control experiments, including active sham and condition blinding.

/pdf/transcranial-alternating-current-stimulation-tacs-mechanisms-14xhcuni6b.pdf

Transcranial Alternating Current Stimulation (tACS) Mechanisms and Protocols

Neurosensory Effects of Transcranial Alternating Current Stimulation

Excitability changes triggered by white noise exposure revealed by whole head MEG

ABSTRACT We introduce a new touchscreen-based method measuring aspects of cognitive control and memory, in children and young people with neurodevelopmental difficulties, including intellectual disability (ID). FarmApp is a gamified, tablet-based assessment tool measuring go/no-go response speed, response inhibition, visuospatial short-term memory span, and long-term memory. Here, we assessed the feasibility, validity, and utility of the method, including the benefits of measuring change in performance over two weeks. We observed that: 1) a higher proportion of participants completed FarmApp than traditional psychometric tests; 2) this proportion increased when participants had opportunity for two weeks of self-paced testing at home; 3) ADHD-relevant behavioral difficulties were associated with average go/no-go performance across all attempts, and change in go/no-go performance over time, indicating sensitivity of the method to cognitive differences with real-world relevance. We also addressed the potential utility of the FarmApp for exploring links between ID etiology and cognitive processes. We observed differences in go/no-go task between two groups of ID participants stratified by the physiological functions of associated genetic variants (chromatin-related and synaptic-related). Moreover, the synaptic group demonstrated higher degree of improvement in go/no-go performance over time. This outcome is potentially informative of dynamic mechanisms contributing to cognitive difficulties within this group. In sum, FarmApp is a feasible, valid, and useful tool increasing access to cognitive assessment for individuals with neurodevelopmental difficulties of variable severity, with an added opportunity to monitor variation in performance over time and determine capacity to acquire task competence.

https://www.tandfonline.com/doi/pdf/10.1080/09297049.2022.2054968?needAccess=true

FarmApp: a new assessment of cognitive control and memory for children and young people with neurodevelopmental difficulties

Magnetoencephalography and electroencephalography (M/EEG) seed-based connectivity analysis requires the extraction of measures from regions of interest (ROI). M/EEG ROI-derived source activity can be treated in different ways. It is possible, for instance, to average each ROI’s time series prior to calculating connectivity measures. Alternatively, one can compute connectivity maps for each element of the ROI prior to dimensionality reduction to obtain a single map. The impact of these different strategies on connectivity results is still unclear. Here, we address this question within a large MEG resting state cohort (N=113) and within simulated data. We consider 68 ROIs (Desikan-Kiliany atlas), two measures of connectivity (phase locking value-PLV, and its imaginary counterpart- ciPLV), three frequency bands (theta 4-8 Hz, alpha 9-12 Hz, beta 15-30 Hz). We compare four extraction methods: (i) mean, or (ii) PCA of the activity within the seed or ROI before computing connectivity, map of the (iii) average, or (iv) maximum connectivity after computing connectivity for each element of the seed. Hierarchical clustering in then applied to compare connectivity outputs across multiple strategies, followed by direct contrasts across extraction methods. Finally, the results are validated by using a set of realistic simulations. We show that ROI-based connectivity maps vary remarkably across strategies in terms of connectivity magnitude and spatial distribution. Dimensionality reduction procedures conducted after computing connectivity are more similar to each-other, while PCA before approach is the most dissimilar to other approaches. Although differences across methods are consistent across frequency bands, they are influenced by the connectivity metric and ROI size. Greater differences were observed for ciPLV than PLV, and in larger ROIs. Realistic simulations confirmed that after aggregation procedures are generally more accurate but have lower specificity (higher rate of false positive connections). Though computationally demanding, after dimensionality reduction strategies should be preferred when higher sensitivity is desired. Given the remarkable differences across aggregation procedures, caution is warranted in comparing results across studies applying different methods.

/pdf/the-impact-of-roi-extraction-method-for-meg-connectivity-2zktna3a.pdf

Diandra Brkic

Papers

Neurosensory Effects of Transcranial Alternating Current Stimulation

Excitability changes triggered by white noise exposure revealed by whole head MEG

FarmApp: a new assessment of cognitive control and memory for children and young people with neurodevelopmental difficulties

The impact of ROI extraction method for MEG connectivity estimation: practical recommendations for the study of resting state data