BOLD Data Research Articles

An integrative taxonomic and molecular identification of Calvatia holothurioides (Lycoperdaceae): the present status of genus Calvatia in India

Genus Calvatia belongs to a gasteroid fungi which are commonly known as a puffball mushrooms including around 47 species worldwide. Approximately 25 species of the genus Calvatia have been reported previously in India from various forest regions; however, only 15 species of these are accepted on their current taxonomic status because several of them are synonymized with other genera or species. The present study reports the distribution of Calvatia holothurioides which was collected from Jambughoda Wildlife Sanctuary in Gujarat state, India. The identification was carried out based on the morphological characteristics as well as molecular phylogenetic analysis using nuclear rDNA Internal Transcribed Spacer (ITS) and rDNA LSU gene sequences data. Nucleotide sequences of different gene loci (ITS and LSU) were submitted into the BOLD data system for DNA barcoding. Additionally, this study also provides a literature-based checklist for the present status of Calvatia species reported in India so far.

Altered dynamic functional connectivity of insular subdivisions among male cigarette smokers.

Insular subdivisions show distinct patterns of resting state functional connectivity with specific brain regions, each with different functional significance in chronic cigarette smokers. This study aimed to explore the altered dynamic functional connectivity (dFC) of distinct insular subdivisions in smokers. Resting-state BOLD data of 31 smokers with nicotine dependence and 27 age-matched non-smokers were collected. Three bilateral insular regions of interest (dorsal, ventral, and posterior) were set as seeds for analyses. Sliding windows method was used to acquire the dFC metrics of different insular seeds. Support vector machine based on abnormal insular dFC was applied to classify smokers from non-smokers. We found that smokers showed lower dFC variance between the left ventral anterior insula and both the right superior parietal cortex and the left inferior parietal cortex, as well as greater dFC variance the right ventral anterior insula with the right middle cingulum cortex relative to non-smokers. Moreover, compared to non-smokers, it is found that smokers demonstrated altered dFC variance of the right dorsal insula and the right middle temporal gyrus. Correlation analysis showed the higher dFC between the right dorsal insula and the right middle temporal gyrus was associated with longer years of smoking. The altered insular subdivision dFC can classify smokers from non-smokers with an accuracy of 89.66%, a sensitivity of 96.30% and a specify of 83.87%. Our findings highlighted the abnormal patterns of fluctuating connectivity of insular subdivision circuits in smokers and suggested that these abnormalities may play a significant role in the mechanisms underlying nicotine addiction and could potentially serve as a neural biomarker for addiction treatment.

The maintenance of complex visual scenes in working memory may require activation of working memory manipulation circuits in the dlPFC: a preliminary report.

Past research has shown that the bilateral dorsolateral prefrontal cortices (dlPFC) are implicated in both emotional processing as well as cognitive processing,1,2,3 in addition to working memory4, 5. Exactly how these disparate processes interact with one another within the dlPFC is less understood. To explore this, we designed a task that looked at working memory performance during fMRI under both emotional and non-emotional conditions, and tested it in this preliminary report. Participants were asked to complete three tasks (letters, neutral images, emotional images) of the Sternberg Sorting Task under one of two trial conditions (sort or maintain). Regions of interest consisted of the left and right dlPFC as defined by brain masks based on NeuroSynth6. Results showed a significant main effect of the 'sort' condition on reaction speed for all three trial types, as well as a main effect of task type (letters) on accuracy. In addition, a significant interaction was found between trial type (sort) and task type (letters), but not for either of the picture tasks. Although preliminary, these results reveal a discrepancy between BOLD signal and behavioral data, with no significant difference in BOLD activity during image trials being displayed, despite longer response times for every condition. While these initial results show that the dlPFC is implicated in non-emotional cognitive processing, more research is needed to explain the lack of BOLD activation seen here for similar emotionally valanced tasks, possibly indicating involvement of other brain networks.

The cortical representation of language timescales is shared between reading and listening

Language comprehension involves integrating low-level sensory inputs into a hierarchy of increasingly high-level features. Prior work studied brain representations of different levels of the language hierarchy, but has not determined whether these brain representations are shared between written and spoken language. To address this issue, we analyze fMRI BOLD data that were recorded while participants read and listened to the same narratives in each modality. Levels of the language hierarchy are operationalized as timescales, where each timescale refers to a set of spectral components of a language stimulus. Voxelwise encoding models are used to determine where different timescales are represented across the cerebral cortex, for each modality separately. These models reveal that between the two modalities timescale representations are organized similarly across the cortical surface. Our results suggest that, after low-level sensory processing, language integration proceeds similarly regardless of stimulus modality.

MetaZooGene Atlas and Database: Reference Sequences for Marine Ecosystems.

The MetaZooGene Atlas and Database (MZGdb; https://metazoogene.org/mzgdb/ ) is an open-access data and metadata portal synchronized with the NCBI GenBank and BOLD data repositories. The MZGdb includes sequences for genes used for the classification and identification of marine organisms based on DNA barcoding and metabarcoding. The focus of the MZGdb is biodiversity of marine ecosystems, including phytoplankton and microbes, zooplankton and invertebrates, fish, and other marine vertebrates (pinnipeds, cetaceans, and sea turtles). DNA sequences currently included are mitochondrial cytochrome oxidase I (COI), 12S, and 16S rRNA, and nuclear 18S and 28S rRNA. The MZGdb provides data and mapping tools for assembling and downloading compilations of reference sequence data that are specific to selected genes, taxonomic groups, and/or ocean regions. An additional feature of the MZGdb is the Atlas which summarizes data coverage and proportional completeness based on statistics of species with available sequences versus species commonly found in each ocean region.This chapter is a collaborative effort of the Scientific Committee for Ocean Research (SCOR) Working Group WG157: MetaZooGene: Toward a new global view of marine zooplankton biodiversity based on DNA metabarcoding and reference DNA sequence databases ( https://metazoogene.org ).

Improving lives by linking data: Views from groups with complex needs. Commissioned by the cross-government Better Outcomes through Linked Data programme and the Centre for Data Ethics and Innovation, and delivered by the research agency Britain Thinks

Objectives
 
 Improve and refine BOLD's delivery of its four pilot projects via feedback on acceptable uses and forms of analysis of shared data.
 Inform how BOLD communicates its aims and progress for maximum clarity and transparency.
 Understand the impact of BOLD's data management on the level of trust in the program.
 
 MethodsInitial workshops were conducted with expert intermediary organisations, such as charities, who have a deep understanding of each of the audiences’ attitudes and needs. This was to explain the purpose of the project to the intermediary organisations and to gain their feedback on the approach and materials.
 Fieldwork was undertaken with 82 participants from across the four vulnerability audiences, using a combination of methods to ensure full participation from a range of individuals with differing levels of need.
 Participants were presented with information about BOLD's purpose, objectives, and three example scenarios related to their respective pilot to prompt useful discussions.
 Results
 
 Participants in the BOLD program pilots generally support data sharing to improve public services.
 They view the program positively, have similar experiences across pilot areas, and reflect on its relevance to a range of audiences.
 However, some lack experience with issues addressed by BOLD. Concerns exist regarding negative impacts and scepticism towards government.
 BOLD use cases should prioritise four principles: relevance, impact, clarity, and non-stigmatisation.
 Intermediary organisations are crucial for engaging with pilot audiences.
 
 ConclusionBOLD is a three-year cross government pilot project that links social policy datasets to better support individuals with complex needs. It aims to improve outcomes by providing new evidence and insight into how services delivered in one part of government affect outcomes in another. This research was commissioned to inform how to take the BOLD programme forward, by engaging and consulting with relevant audiences in an ethical and transparent way.
 The published findings are informing the delivery of BOLD and improving and enhancing our understanding of the impact of BOLD's data management on trust.

An imaging-based method of mapping multi-echo BOLD intracranial pulsatility.

Cardiac-related intracranial pulsatility may relate to cerebrovascular health, and this information is contained in BOLD MRI data. There is broad interest in methods to isolate BOLD pulsatility, and the current study examines a deep learning approach. Multi-echo BOLD images, respiratory, and cardiac recordings were measured in 55 adults. Ground truth BOLD pulsatility maps were calculated with an established method. BOLD fast Fourier transform magnitude images were used as temporal-frequency image inputs to a U-Net deep learning model. Model performance was evaluated by mean squared error (MSE), mean absolute error (MAE), structural similarity index (SSIM), and mutual information (MI). Experiments evaluated the influence of input channel size, an age group effect during training, dependence on TE, performance without the U-Net architecture, and importance of respiratory preprocessing. The U-Net model generated BOLD pulsatility maps with lower MSE as additionalfast Fourier transform input images were used. There was no age group effect for MSE (P > 0.14). MAE and SSIM metrics did not vary across TE (P > 0.36), whereas MI showed a significant TE dependence (P < 0.05). The U-Net versus no U-Net comparison showed no significant difference for MAE (P=0.059); however, SSIM and MI were significantly different between models (P < 0.001). Within the insula, the cross-correlation values were high (r > 0.90) when comparing the U-Net model trained with/without respiratory preprocessing. Multi-echo BOLD pulsatility maps were synthesized from a U-net model that was trained to use temporal-frequency BOLD image inputs. This work adds to the deep learning methods that characterize BOLD physiological signals.

Poorer sleep health is associated with altered brain activation during cognitive control processing in healthy adults.

This study investigated how proactive and reactive cognitive control processing in the brain was associated with habitual sleep health. BOLD fMRI data were acquired from 81 healthy adults with normal sleep (41 females, age 20.96-39.58years) during a test of cognitive control (Not-X-CPT). Sleep health was assessed in the week before MRI scanning, using both objective (actigraphy) and self-report measures. Multiple measures indicating poorer sleep health-including later/more variable sleep timing, later chronotype preference, more insomnia symptoms, and lower sleep efficiency-were associated with stronger and more widespread BOLD activations in fronto-parietal and subcortical brain regions during cognitive control processing (adjusted for age, sex, education, and fMRI task performance). Most associations were found for reactive cognitive control activation, indicating that poorer sleep health is linked to a "hyper-reactive" brain state. Analysis of time-on-task effects showed that, with longer time on task, poorer sleep health was predominantly associated with increased proactive cognitive control activation, indicating recruitment of additional neural resources over time. Finally, shorter objective sleep duration was associated with lower BOLD activation with time on task and poorer task performance. In conclusion, even in "normal sleepers," relatively poorer sleep health is associated with altered cognitive control processing, possibly reflecting compensatory mechanisms and/or inefficient neural processing.

Molecular and morphological studies on some gasteroid (Basidiomycota) fungi from Western India

The gasteroid fungi are a group of fungi in Basidiomycota that include stinkhorns, earth balls, puffballs, pseudo truffles, earth stars, and bird’s nests. In the present study, six species of gasteroid fungi belonging to four genera were collected from different forest regions in Gujarat state. Identification was carried out based on the morphological features, and molecular phylogenetic analysis using nuclear rDNA Internal Transcribed Spacer (ITS), rDNA LSU and mitochondrial ATP6 gene sequences were used for molecular identification. DNA sequencing data of different gene loci (ITS, LSU, and ATP6) were submitted into the BOLD data system for DNA barcoding. Additionally, this study provides a checklist of available molecular identification data for reported gasteroid fungi from Gujarat state.

PhiPipe: A multi-modal MRI data processing pipeline with test-retest reliability and predicative validity assessments.

Magnetic resonance imaging (MRI) has been one of the primary instruments to measure the properties of the human brain non-invasively in vivo. MRI data generally needs to go through a series of processing steps (i.e., a pipeline) before statistical analysis. Currently, the processing pipelines for multi-modal MRI data are still rare, in contrast to single-modal pipelines. Furthermore, the reliability and validity of the output of the pipelines are critical for the MRI studies. However, the reliability and validity measures are not available or adequate for almost all pipelines. Here, we present PhiPipe, a multi-modal MRI processing pipeline. PhiPipe could process T1-weighted, resting-state BOLD, and diffusion-weighted MRI data and generate commonly used brain features in neuroimaging. We evaluated the test-retest reliability of PhiPipe's brain features by computing intra-class correlations (ICC) in four public datasets with repeated scans. We further evaluated the predictive validity by computing the correlation of brain features with chronological age in three public adult lifespan datasets. The multivariate reliability and predictive validity of the PhiPipe results were also evaluated. The results of PhiPipe were consistent with previous studies, showing comparable or better reliability and validity when compared with two popular single-modality pipelines, namely DPARSF and PANDA. The publicly available PhiPipe provides a simple-to-use solution to multi-modal MRI data processing. The accompanied reliability and validity assessments could help researchers make informed choices in experimental design and statistical analysis. Furthermore, this study provides a framework for evaluating the reliability and validity of image processing pipelines.

Mechanistic model for human brain metabolism and its connection to the neurovascular coupling.

The neurovascular and neurometabolic couplings (NVC and NMC) connect cerebral activity, blood flow, and metabolism. This interconnection is used in for instance functional imaging, which analyses the blood-oxygen-dependent (BOLD) signal. The mechanisms underlying the NVC are complex, which warrants a model-based analysis of data. We have previously developed a mechanistically detailed model for the NVC, and others have proposed detailed models for cerebral metabolism. However, existing metabolic models are still not fully utilizing available magnetic resonance spectroscopy (MRS) data and are not connected to detailed models for NVC. Therefore, we herein present a new model that integrates mechanistic modelling of both MRS and BOLD data. The metabolic model covers central metabolism, using a minimal set of interactions, and can describe time-series data for glucose, lactate, aspartate, and glutamate, measured after visual stimuli. Statistical tests confirm that the model can describe both estimation data and predict independent validation data, not used for model training. The interconnected NVC model can simultaneously describe BOLD data and can be used to predict expected metabolic responses in experiments where metabolism has not been measured. This model is a step towards a useful and mechanistically detailed model for cerebral blood flow and metabolism, with potential applications in both basic research and clinical applications.

HALO: A software tool for real-time head alignment in the MR scanner.

MRI studies in human subjects often require multiple scanning sessions/visits. Changes in a subject's head position across sessions result in different alignment between brain tissues and the magnetic field which leads to changes in magnetic susceptibility. These changes can have considerable impacts on acquired signals. Head ALignment Optimization (HALO), a software tool was developed by the authors for active head alignment between sessions. HALO provides real-time visual feedback of a subject's current head position relative to the position in a previous session. The tool was evaluated in a pilot sample of seven healthy human subjects. HALO was shown to enable subjects to actively align their head positions to the desired position of their initial sessions. The subjects were able to improve their head alignment significantly using HALO and achieved good alignment with their first session meeting stringent criteria similar to that used for within-run head motion (less than 2 mm translation or 2 degrees rotation in any direction from the desired position). Moreover, we found a negative correlation between the post-alignment rotation and similarity in inter-session BOLD patterns around the air-tissue interface near sinus which further highlighted the impact of tissue-field alignment on BOLD data quality. Utilization of HALO in longitudinal studies may help to improve data quality by ensuring the consistency of susceptibility gradients in brain tissues across sessions. HALO has been made publicly available.

Neural mechanisms of background and velocity effects in smooth pursuit eye movements.

Smooth pursuit eye movements (SPEM) are essential to guide behaviour in complex visual environments. SPEM accuracy is known to be degraded by the presence of a structured visual background and at higher target velocities. The aim of this preregistered study was to investigate the neural mechanisms of these robust behavioural effects. N=33 participants performed a SPEM task with two background conditions (present and absent) at two target velocities (0.4 and 0.6Hz). Eye movement and BOLD data were collected simultaneously. Both the presence of a structured background and faster target velocity decreased pursuit gain and increased catch-up saccade rate. Faster targets additionally increased position error. Higher BOLD response with background was found in extensive clusters in visual, parietal, and frontal areas (including the medial frontal eye fields; FEF) partially overlapping with the known SPEM network. Faster targets were associated with higher BOLD response in visual cortex and left lateral FEF. Task-based functional connectivity analyses (psychophysiological interactions; PPI) largely replicated previous results in the basic SPEM network but did not yield additional information regarding the neural underpinnings of the background and velocity effects. The results show that the presentation of visual background stimuli during SPEM induces activity in a widespread visuo-parieto-frontal network including areas contributing to cognitive aspects of oculomotor control such as medial FEF, whereas the response to higher target velocity involves visual and motor areas such as lateral FEF. Therefore, we were able to propose for the first time different functions of the medial and lateral FEF during SPEM.

Cross-sectional use of barcode of life data system and GenBank as DNA barcoding databases for the advancement of museomics

Museomics is an approach to the DNA sequencing of museum specimens that can generate both biodiversity and sequence information. In this study, we surveyed both the biodiversity information-based database BOLD (Barcode of Life System) and the sequence information database GenBank, by using DNA barcoding data as an example, with the aim of integrating the data from these two databases. DNA barcoding is a method of identifying species from DNA sequences by using short genetic markers. We surveyed how many entries had biodiversity information (such as links to BOLD and specimen IDs) by downloading all fish, insect, and flowering plant data available from the GenBank Nucleotide, and BOLD ID was assigned to 26.2% of entries for insects. In the same way, we downloaded the respective BOLD data and checked the status of links to sequence information. We also investigated how many species do these databases cover, and 7,693 species were found to exist only in BOLD. In the future, as museomics develops as a field, the targeted sequences will be extended not only to DNA barcodes, but also to mitochondrial genomes, other genes, and genome sequences. Consequently, the value of the sequence data will increase. In addition, various species will be sequenced and, thus, biodiversity information such as the evidence specimen photographs used as a basis for species identification, will become even more indispensable. This study contributes to the acceleration of museomics-associated research by using databases in a cross-sectional manner.

Single Center to Evaluate and Compare Anisometropic Amblyopia in Adults Using Blood Oxygenation Level-Dependent Functional Magnetic Resonance Imaging and Diffusion Kurtosis Imaging.

BackgroundAnisometropic amblyopia results from the unequal ability to focus between the right and left eyes. Blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) measures the proportion of oxygenated hemoglobin in specific areas. Diffusion kurtosis imaging (DKI) is a method of diffusion tensor imaging that estimates the skewed distribution of water diffusion probability. We aimed to evaluate and compare 11 adult patients with anisometropic amblyopia (AA) with 13 normally sighted healthy controls (HC) using BOLD-fMRI and DKI.Material/MethodsEleven adults with AA (age range 20–49; mean age 29.18±8.089) and 13 HC adults (age range 22–50; mean age 28.00±5.79) were recruited. DKI scanning used a single excitation echo-planar imaging sequence and a region of interest to obtain DKI parameters for optic radiation; the corpus callosum was manually placed, including mean kurtosis (MK), fractional anisotropic (FA), and mean diffusivity (MD) values; and BOLD data used a gradient-echo echo-planar imaging sequence.ResultsThe AA group had lower MK and FA of bilateral optic radiation than the HC group (P=0.008 and P=0.006, respectively) and higher MD than the HC group (P=0.005). The MK of the corpus callosum in the AA group was lower than that of HC group (P=0.012).Compared with the non-dominant eyes of the HC group, the amblyopic eyes in the AA group had less activation range and intensity in Brodmann areas 17, 18, and 19.ConclusionsThe combined use of DKI and BOLD-fMRI detected microstructural changes associated with local visual pathways and identified damage to the visual cortex in patients with amblyopia.

A comprehensive DNA barcode inventory of Austria's fish species.

Austria is inhabited by more than 80 species of native and non-native freshwater fishes. Despite considerable knowledge about Austrian fish species, the latest Red List of threatened species dates back 15 years and a systematic genetic inventory of Austria's fish species does not exist. To fulfill this deficit, we employed DNA barcoding to generate an up-to-date and comprehensive genetic reference database for Austrian fish species. In total, 639 newly generated cytochrome c oxidase subunit 1 (COI) sequences were added to the 377 existing records from the BOLD data base, to compile a near complete reference dataset. Standard sequence similarity analyses resulted in 83 distinct clusters almost perfectly reflecting the expected number of species in Austria. Mean intraspecific distances of 0.22% were significantly lower than distances to closest relatives, resulting in a pronounced barcoding gap and unique Barcode Index Numbers (BINs) for most of the species. Four cases of BIN sharing were detected, pointing to hybridization and/or recent divergence, whereas in Phoxinus spp., Gobio spp. and Barbatula barbatula intraspecific splits, multiple BINs and consequently cryptic diversity were observed. The overall high identification success and clear genetic separation of most of the species confirms the applicability and accuracy of genetic methods for bio-surveillance. Furthermore, the new DNA barcoding data pinpoints cases of taxonomic uncertainty, which need to be addressed in further detail, to more precisely assort genetic lineages and their local distribution ranges in a new National Red-List.

A Comparison of Single- and Multi-Echo Processing of Functional MRI Data During Overt Autobiographical Recall.

Recent years have seen an increase in the use of multi-echo fMRI designs by cognitive neuroscientists. Acquiring multiple echoes allows one to increase contrast-to-noise; reduce signal dropout and thermal noise; and identify nuisance signal components in BOLD data. At the same time, multi-echo acquisitions increase data processing complexity and may incur a cost to the temporal and spatial resolution of the acquired data. Here, we re-examine a multi-echo dataset previously analyzed using multi-echo independent components analysis (ME-ICA) and focused on hippocampal activity during the overtly spoken recall of recent and remote autobiographical memories. The goal of the present series of analyses was to determine if ME-ICA’s theoretical denoising benefits might lead to a practical difference in the overall conclusions reached. Compared to single-echo (SE) data, ME-ICA led to qualitatively different findings regarding hippocampal contributions to autobiographical recall: whereas the SE analysis largely failed to reveal hippocampal activity relative to an active baseline, ME-ICA results supported predictions of the Standard Model of Consolidation and a time limited hippocampal involvement. These data provide a practical example of the benefits multi-echo denoising in a naturalistic memory paradigm and demonstrate how they can be used to address long-standing theoretical questions.

The Cerebrovascular Reactivity-Adjusted Spontaneous Brain Activity Abnormalities in White Matter Hyperintensities Related Cognitive Impairment: A Resting-State Functional MRI Study.

The BOLD signal is regulated by neuronal activity and vascular physiology. The evolution pattern of brain activities after modulating the vascular factors in white matter hyperintensities (WMHs) related cognitive impairment (CI) was unknown. To explore the "pure" low-frequency fluctuation (ALFF) alterations after adjusting the cerebrovascular reactivity (CVR) factor. In this study, 111 WMHs subjects including 55 with CI (WMH-CI) and 56 without CI (WMH-no-CI), and 72 normal controls (NCs) underwent resting-state fMRI. The CVR and ALFF maps were derived using BOLD data. A voxel-wise Pearson analysis was performed to detect the relationship between CVR and ALFF maps. The ANCOVA analysis with and without CVR as a covariate was conducted to explore the effect of CVR on ALFF analysis. Correlation between the ALFF alterations and cognitive performance was conducted in WMH-CI subjects. The receiver operating characteristic curve was constructed to assess the diagnostic performance of ALFF indexes to determine the occurrence of CI. There was a significant widespread correlation between the CVR and ALFF maps. The ALFF alterations between the WMH groups and NC group with CVR as covariate were more than those without CVR as covariate. WMH-CI subjects showed further ALFF alterations when compared with WMH-no-CI subjects. The abnormal ALFF values were significantly associated with poor performance. The combination of inferior frontal gyrus and middle frontal gyrus to PCC provided an incremental contribution to the occurrence of CI. More areas with abnormal ALFF values which were specific to the WMHs related cognitive dysfunction were detected when considering the impact of CVR.

Enhancing cognitive restructuring with concurrent fMRI-guided neurostimulation for emotional dysregulation–A randomized controlled trial

BackgroundTransdiagnostic clinical emotional dysregulation is a key component of many mental health disorders and offers an avenue to address multiple disorders with one transdiagnostic treatment. In the current study, we pilot an intervention that combines a one-time teaching and practice of cognitive restructuring (CR) with repetitive transcranial magnetic stimulation (rTMS), targeted based on functional magnetic resonance imaging (fMRI). MethodsThirty-seven clinical adults who self-reported high emotional dysregulation were enrolled in this randomized, double-blind, placebo-controlled trial. fMRI was collected as participants were reminded of lifetime stressors and asked to downregulate their distress using CR tactics. fMRI BOLD data were analyzed to identify the cluster of voxels within the left dorsolateral prefrontal cortex (dlPFC) with the highest activation when participants attempted to downregulate, versus passively remember, distressing memories. Participants underwent active or sham rTMS (10 Hz) over the left dlPFC target while practicing CR following emotional induction using recent autobiographical stressors. ResultsReceiving active versus sham rTMS led to significantly higher high frequency heart rate variability during regulation, lower regulation duration during the intervention, and higher likelihood to use CR during the week following the intervention. There were no differences between conditions when administering neurostimulation alone without the CR skill and compared to sham. Participants in the sham versus active condition experienced less distress the week after the intervention. There were no differences between conditions at the one-month follow up. ConclusionThis study demonstrated that combining active rTMS with emotion regulation training for one session significantly enhances emotion regulation and augments the impact of training for as long as a week. These findings are a promising step towards a combined intervention for transdiagnostic emotion dysregulation.

Intelligibility of audiovisual sentences drives multivoxel response patterns in human superior temporal cortex

Regions of the human posterior superior temporal gyrus and sulcus (pSTG/S) respond to the visual mouth movements that constitute visual speech and the auditory vocalizations that constitute auditory speech, and neural responses in pSTG/S may underlie the perceptual benefit of visual speech for the comprehension of noisy auditory speech. We examined this possibility through the lens of multivoxel pattern responses in pSTG/S. BOLD fMRI data was collected from 22 participants presented with speech consisting of English sentences presented in five different formats: visual-only; auditory with and without added auditory noise; and audiovisual with and without auditory noise. Participants reported the intelligibility of each sentence with a button press and trials were sorted post-hoc into those that were more or less intelligible. Response patterns were measured in regions of the pSTG/S identified with an independent localizer. Noisy audiovisual sentences with very similar physical properties evoked very different response patterns depending on their intelligibility. When a noisy audiovisual sentence was reported as intelligible, the pattern was nearly identical to that elicited by clear audiovisual sentences. In contrast, an unintelligible noisy audiovisual sentence evoked a pattern like that of visual-only sentences. This effect was less pronounced for noisy auditory-only sentences, which evoked similar response patterns regardless of intelligibility. The successful integration of visual and auditory speech produces a characteristic neural signature in pSTG/S, highlighting the importance of this region in generating the perceptual benefit of visual speech.