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AbstractNoninvasive brain stimulation (NIBS) modifies corticospinal excitability (CSE) historically in a predictable manner dependent on stimulation parameters. Researchers, however, discuss high degrees of variability between individuals, either responding as expected or not responding as expected. The explanation for this interindividual variability remains unknown with suggested interplay between stimulation parameters and variations in biological, anatomical, and physiological factors. This systematic review and meta-analysis aimed to investigate the effect of variation in inherent factors within an individual (biological and anatomical factors) on CSE in response to NIBS of the primary motor cortex. Twenty-two studies were included investigating genetic variation (n=7), age variation (n=4), gender variation (n=7), and anatomical variation (n=5). The results indicate that variation in brain-derived neurotrophic factor genotypes may have an effect on CSE after NIBS. Variation between younger and older adults also affects CSE after NIBS. Variation between age-matched males and females does not affect CSE after NIBS, but variation across the menstrual cycle does. Variation between skull thickness and brain tissue morphology influences the electric field magnitude that ultimately reaches the primary motor cortex. These findings indicate that biological and anatomical variations may in part account for interindividual variability in CSE in response to NIBS of the primary motor cortex, categorizing individuals as responding as expected (responders) or not responding as expected (nonresponders).

Cluster analysis and other subgrouping techniques have risen in popularity in recent years in non-invasive brain stimulation research in the attempt to investigate the issue of inter-individual variability - the issue of why some individuals respond, as traditionally expected, to non-invasive brain stimulation protocols and others do not. Cluster analysis and subgrouping techniques have been used to categorise individuals, based on their response patterns, as responder or non-responders. There is, however, a lack of consensus and consistency on the most appropriate technique to use. This systematic review aimed to provide a systematic summary of the cluster analysis and subgrouping techniques used to date and suggest recommendations moving forward. Twenty studies were included that utilised subgrouping techniques, while seven of these additionally utilised cluster analysis techniques. The results of this systematic review appear to indicate that statistical cluster analysis techniques are effective in identifying subgroups of individuals based on response patterns to non-invasive brain stimulation. This systematic review also reports a lack of consensus amongst researchers on the most effective subgrouping technique and the criteria used to determine whether an individual is categorised as a responder or a non-responder. This systematic review provides a step-by-step guide to carrying out statistical cluster analyses and subgrouping techniques to provide a framework for analysis when developing further insights into the contributing factors of inter-individual variability in response to non-invasive brain stimulation.

Response variability following transcranial direct current stimulation (tDCS) highlights need for exploring different tDCS electrode montages. This study compared corticospinal excitability (CSE), cortico-cortical excitability and intra-individual variability following conventional and HD anodal (a-tDCS) and cathodal (c-tDCS) tDCS. Fifteen healthy young males attended four sessions at least one-week apart: conventional a-tDCS, conventional c-tDCS, HD-a-tDCS, HD-c-tDCS. TDCS was administered (1mA, 10-minutes) over the primary motor cortex (M1), via 6x4cm active and 7x5cm return electrodes (conventional tDCS) and 4x1 ring-electrodes 3.5cm apart in ring formation around M1 (HD-tDCS). For CSE, twenty-five single-pulse transcranial magnetic stimulation (TMS) peakto-peak motor evoked potentials (MEP) were recorded at baseline, 0-minutes and 30-minutes post-tDCS. For cortico-cortical excitability, twenty-five paired-pulse MEPs with 3-millisecond (ms) inter-pulse interval (IPI) and twenty-five at 10ms assessed short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) respectively. MEP standardised z-values standard deviations represented intra-individual variability. No significant differences were reported in CSE between conventional and HD a-tDCS, but significant differences between conventional and HD c-tDCS 0-minutes post-tDCS. Intra-individual variability was significantly reduced in conventional tDCS compared to HD-tDCS for a-tDCS (0-minutes) and c-tDCS (30-minutes). No significant changes were reported in SICI and ICF. These novel findings highlight current technical issues with HD-tDCS, suggesting future tDCS studies should utilise conventional tDCS to minimise intraindividual variability, ensuring tDCS after-effects are true changes in CSE and cortico-cortical excitability.

Genetic mediation of cortical plasticity and the role genetic variants play in previously observed response variability to transcranial direct current stimulation (tDCS) have become important issues in the tDCS literature in recent years. This study investigated whether inter‐individual variability to tDCS was in‐part genetically mediated. In 61 healthy males, anodal‐tDCS (a‐tDCS) and sham‐tDCS were administered to the primary motor cortex at 1 mA for 10‐min via 6 × 4 cm active and 7 × 5 cm return electrodes. Twenty‐five single‐pulse transcranial magnetic stimulation (TMS) motor evoked potentials (MEP) were recorded to represent corticospinal excitability (CSE). Twenty‐five paired‐pulse MEPs were recorded with 3 ms inter‐stimulus interval (ISI) to assess intracortical inhibition (ICI) via short‐interval intracranial inhibition (SICI) and 10 ms ISI for intracortical facilitation (ICF). Saliva samples were tested for specific genetic polymorphisms in genes encoding for excitatory and inhibitory neuroreceptors. Individuals were sub‐grouped based on a pre‐determined threshold and via statistical cluster analysis. Two distinct subgroups were identified, increases in CSE following a‐tDCS (i.e. Responders) and no increase or even reductions in CSE (i.e. Non‐responders). No changes in ICI or ICF were reported. No relationships were reported between genetic polymorphisms in excitatory receptor genes and a‐tDCS responders. An association was reported between a‐tDCS responders and GABRA3 gene polymorphisms encoding for GABA‐A receptors suggesting potential relationships between GABA‐A receptor variations and capacity to undergo tDCS‐induced cortical plasticity. In the largest tDCS study of its kind, this study presents an important step forward in determining the contribution genetic factors play in previously observed inter‐individual variability to tDCS.