About 90% of fMRI findings on specific phobias (SP) include analysis of region of interest (ROI). This approach characterized by higher sensitivity may produce inflated results, particularly when findings are aggregated in meta‐analytic maps. Here, we conducted a systematic review and activation likelihood estimation (ALE) meta‐analysis on SP, testing the impact of the inclusion of ROI‐based studies. ALE meta‐analyses were carried out either including ROI‐based results or focusing on whole‐brain voxelwise studies exclusively. To assess the risk of bias in the neuroimaging field, we modified the Newcastle–Ottawa Scale (NOS) and measured the reliability of fMRI findings. Of the 31 selected investigations (564 patients and 485 controls) one‐third did not motivate ROI selection: five studies did not report an explicit rationale, whereas four did not cite any specific reference in this regard. Analyses including ROI‐based studies revealed differences between phobics and healthy subjects in several regions of the limbic circuit. However, when focusing on whole‐brain analysis, only the anterior midcingulate cortex differentiated SP from controls. Notably, 13 studies were labeled with low risk of bias according to the adapted NOS. The inclusion of ROI‐based results artificially inflates group differences in fMRI meta‐analyses. Moreover, a priori, well‐motivated selection of ROIs is desirable to improve quality and reproducibility in SP neuroimaging studies. Lastly, the use of modified NOS may represent a valuable way to assess and evaluate biases in fMRI studies: “low risk” of bias was reported for less than half of the included studies, indicating the need for better practices in fMRI.

Though a plethora of functional magnetic resonance imaging (fMRI) studies explored the neurobiological underpinnings of borderline personality disorder (BPD), findings across different tasks were divergent. We conducted a systematic review and activation likelihood estimation (ALE) meta-analysis on the fMRI studies conducted in BPD patients compared to healthy controls (HC). We systematically searched PubMed and PsychINFO from inception until July 9th 2020 using combinations of database-specific terms like ‘fMRI’, ‘Neuroimaging’, ‘borderline’. Eligible studies employed task-based fMRI of the brain in participants of any age diagnosed with BPD compared to HC, during any behavioral task and providing a direct contrast between the groups. From 762 entries, we inspected 92 reports full-texts and included 52 studies (describing 54 experiments). Across all experiments, the HC > BPD and BPD > HC meta-analyses did not yield any cluster of significant convergence of differences. Analyses restricted to studies of emotion processing revealed two significant clusters of activation in the bilateral hippocampal/amygdala complex and anterior cingulate for the BPD > HC meta-analysis. Fail-safe N and single study sensitivity analysis suggested significant findings were not robust. For the subgroup of emotional processing experiments, on a restricted number of experiments providing results for each group separately, another meta-analysis method (difference of convergence) showed a significant cluster in the insula/inferior frontal gyrus for the HC > BPD contrast. No consistent pattern of alteration in brain activity for BPD was evidenced suggesting substantial heterogeneity of processes and populations studied. A pattern of amygdala dysfunction emerged across emotion processing tasks, indicating a potential pathophysiological mechanism that could be transdiagnostic.

Background Though aberrant face processing is a hallmark of autistic spectrum disorder (ASD), findings on accompanying brain activity are divergent. Therefore, we conducted an activation likelihood estimation (ALE) meta‐analysis of studies examining brain activity during face processing. Methods We searched PubMed and PsycINFO using combinations of terms as ‘fMRI’, ‘Autism Spectrum Disorder’, ‘Face Perception’. Eligible studies reported on DSM‐diagnosed ASD individuals, compared to controls (HC), using face stimuli presented in fMRI and reporting whole‐brain analysis coordinates. We compared two approaches: ‘convergence of differences’ (primary analysis) using study‐level coordinates from ASD vs. HC contrasts, and ‘differences in convergence’ (secondary) pooling coordinates within each group separately, and contrasting the resultant ALE maps. Results Thirty‐five studies (655 ASD and 668 HC) were included. Primary analysis identified a cluster in amygdala/parahippocampus where HC showed greater convergence of activation. Secondary analysis yielded no significant results. Conclusions Results suggest that ASD dysfunction in face processing relies on structures involved in emotional processing rather than perception. We also demonstrate that the two ALE methodologies lead to divergent results.

This paper reports a research conducted to determine the changes in the electrical activity of the contralateral motor cortex of the brain that drives the maximum voluntary contraction (MVC) of right Adductor Pollicis muscle (APM) after fatigue. For this aim, the power changes of EEG signals after muscle fatigue were computed. EEG signals from the left motor cortical area (C3, FC3) in twenty-five subjects, simultaneously with the EMG from right Adductor Pollicis muscle (APM), before and after exercise-induced fatigue were recorded. The Root Mean Square (RMS) of the EEG bands (alpha, beta, and gamma) was calculated to determine the power changes of the EEG signals after right APM fatigue. The mean RMS of EEG bands were increased during MVC of fatigued right APM compared to the RMS value during relaxation before fatigue (p<0.05). The RMS value was seen to be greatest in the beta band, and lowest in the gamma band. The observed increase in the RMS of EEG bands during MVC of fatigued right APM suggest an increase in the EEG signals power, which could reflect an increase in energy needed by the motor cortex to perform MVC in fatigued muscle, which might give an indication of neural fatigue in the motor cortex.