Biology subjects

Gilat, M.

Publications and source records attributed to Gilat, M..

3 recordsLinked to original sources

bioRxiv2026

No effect of anodal high-definition transcranial direct current stimulation during motor sequence learning in older people

BackgroundTranscranial direct current stimulation (tDCS) targeting the primary motor cortex (M1) has previously been shown to enhance motor learning in older adults. However, findings across studies are inconsistent, which may be partly due to variability in stimulation parameters and montages across experimental protocols. ObjectiveWe aimed to replicate the effect of 1mA conventional anodal tDCS over the M1 hotspot during one session of motor sequence learning on retention (24h) compared to sham stimulation in older adults. In addition, we aimed to compare the effect of high definition (HD tDCS) versus conventional tDCS on motor sequence learning to explore if stimulation montage and according focality affects the effect sizes found. MethodsIn a pre-registered, double-blind, randomized, sham-controlled, parallel study design including 52 older adults, we investigated the effects of conventional and HD tDCS on motor sequence learning in a serial reaction time task (SRTT), using a crossover design for the stimulation montage. ResultsAlthough all groups showed motor sequence learning over time, both during practice sessions (main effect of time: p < 0.0001), as well as across session (main effect of time: p < 0.0001), we observed no significant effects on learning between stimulation groups (main effect of stimulation: p = 0. 68) or montages (main effect of montage: p = 0. 66). For all groups, motor sequence learning improvements were maintained but not further enhanced after 24 hours of consolidation (HD tDCS: p = 0.64; conventional tDCS: p = 0.76; HD sham: p = 0.69; conventional sham: p = 0.57). ConclusionOur findings indicate that neither conventional nor HD tDCS enhanced motor sequence learning in older adults. To better understand potential long-term or cumulative effects, we recommend that future studies investigate the effects of repeated tDCS sessions administered throughout the motor learning process.

neuroscience↗

bioRxiv2024

Impaired online and enhanced offline motor sequence learning in individuals with Parkinson's disease

Whereas memory consolidation research has traditionally focused on longer temporal windows (i.e., hours to days) following an initial learning episode, recent research has also examined the functional significance of the shorter rest epochs commonly interspersed with blocks of task practice (i.e., "micro-offline" intervals on the timescale of seconds to minutes). In the motor sequence learning domain, evidence from young, healthy individuals suggests that micro-offline epochs afford a rapid consolidation process that is supported by the hippocampus. Consistent with these findings, amnesic patients with hippocampal damage were recently found to exhibit degraded micro-offline performance improvements. Interestingly, these offline losses were compensated for by larger performance gains during online practice. Given the known role of the striatum in online motor sequence learning, we hypothesized that individuals with dysfunction of the striatal system would exhibit impaired online, yet enhanced micro-offline, learning (i.e., a pattern of results opposite to those observed in patients with hippocampal lesions). We tested this hypothesis using Parkinsons disease (PD) as a model of striatal dysfunction. Forty-two drug-naive individuals (men and women) with a clinical diagnosis of unilateral PD and 30 healthy control subjects completed a motor sequence learning paradigm. Individuals with PD exhibited deficits during online task practice that were paralleled by greater improvements over micro-offline intervals. This pattern of results could not be explained by disease-related deficits in movement execution. These data suggest that striatal dysfunction disrupts online learning, yet total learning remains unchanged because of greater micro-offline performance improvements that potentially reflect hippocampal-mediated compensatory processes. Significance StatementThe short rest intervals commonly interspersed between periods of active task engagement have traditionally been employed to minimize the build-up of fatigue. There is recent evidence, however, suggesting that these rest epochs may play an active role in motor learning and memory processes and the hippocampus appears to be a critical brain region supporting this rapid "offline" learning. Here, we show that individuals with Parkinsons disease, a movement disorder characterized by dysfunction in the basal ganglia including the striatum, exhibit deficits during active task practice but greater learning over the interspersed offline intervals. Results potentially suggest that the relatively intact hippocampus may help compensate for motor sequence learning deficits linked to a disrupted striatal system in Parkinsons disease.

neuroscience↗

bioRxiv2018

Small effect size leads to reproducibility failure in resting-state fMRI studies

Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric isorders together with healthy individuals have been analyzed. Parkinsons disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named amplitude of low frequency fluctuation (ALFF) showed that the effect size (Hedges g) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t-maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.

neuroscience↗