Modelling large motion events in fMRI studies of patients with epilepsy

Altered domain-specific striatal functional connectivity in patients with Parkinson's disease and urinary symptoms

BACKGROUND

In this study, we aimed at investigating the possible association of urinary symptoms with whole-brain MRI resting-state functional connectivity (FC) alterations from distinct striatal subregions in a large cohort of early PD patients.

METHODS

Seventy-nine drug-naive PD patients (45 PD-urinary+/34 PD-urinary-) and 38 healthy controls (HCs) were consecutively enrolled. Presence/absence of urinary symptoms were assessed by means of the Nonmotor Symptom Scale - domain 7. Using an a priori connectivity-based domain-specific parcellation, we defined three ROIs (per each hemisphere) for different striatal functional subregions (sensorimotor, limbic and cognitive) from which seed-based FC voxel-wise analyses were conducted over the whole brain.

RESULTS

Compared to PD-urinary-, PD-urinary+ patients showed increased FC between striatal regions and motor and premotor/supplementary motor areas as well as insula/anterior dorsolateral PFC. Compared to HC, PD-urinary+ patients presented decreased FC between striatal regions and parietal, insular and cingulate cortices.

CONCLUSIONS

Our findings revealed a specific pattern of striatal FC alteration in PD patients with urinary symptoms, potentially associated to altered stimuli perception and sensorimotor integration even in the early stages. These results may potentially help clinicians to design more effective and tailored rehabilitation and neuromodulation protocols for PD patients.

Thalamocortical functional connectivity and rapid antidepressant and antisuicidal effects of low-dose ketamine infusion among patients with treatment-resistant depression

Previous studies have shown an association between the thalamocortical dysconnectivity and treatment-resistant depression (TRD). Whether a single subanesthetic dose of ketamine may change thalamocortical connectivity among patients with TRD is unclear. Whether these changes in thalamocortical connectivity is associated with the antidepressant and antisuicidal effects of ketamine treatment is also unclear. Two resting-state functional MRIs were collected in two clinical trials of 48 patients with TRD (clinical trial 1; 32 receiving ketamine, 16 receiving a normal saline placebo) and 48 patients with TRD and strong suicidal ideation (clinical trial 2; 24 receiving ketamine, 24 receiving midazolam), respectively. All participants underwent rs-fMRI before and 3 days after infusion. Seed-based functional connectivity (FC) was analyzed in the left/right thalamus. FCs between the bilateral thalamus and right middle frontal cortex (BA46) and between the left thalamus and left anterior paracingulate gyrus (BA8) increased among patients in the ketamine group in clinical trials 1 and 2, respectively. FCs between the right thalamus and bilateral frontal pole (BA9) and between the right thalamus and left rostral paracingulate gyrus (BA10) decreased among patients in the ketamine group in clinical trials 1 and 2, respectively. However, the associations between those FC changes and clinical symptom changes did not survive statistical significance after multiple comparison corrections. Whether ketamine-related changes in thalamocortical connectivity may be associated with ketamine's antidepressant and antisuicidal effects would need further investigation. Clinical trials registration: UMIN Clinical Trials Registry (UMIN-CTR): Registration number: UMIN000016985 and UMIN000033916.

Interictal Electroencephalography and Functional Magnetic Resonance Imaging Reveals Involvement of Mesial Anterior Frontal Structures in Patients With Hyperkinetic Semiology Type I

PURPOSE

This work investigates the presence of common anatomic regions associated with interictal activity in patients with hyperkinetic seizures type I by means of concurrent electroencephalography and functional magnetic resonance imaging.

METHODS

Six patients with hyperkinetic seizures type I were evaluated with video-EEG and electroencephalography and functional magnetic resonance imaging in the context of their presurgical evaluation. Statistical Parametric Mapping was used to perform a correlation study between the occurrence of interictal spikes on EEG and suprathreshold blood oxygen level-dependent changes in the whole-brain volume.

RESULTS

In all patients, Statistical Parametric Mapping revealed suprathreshold blood oxygen level-dependent clusters in the mesial anterior frontal areas, including the rostral mesial superior frontal gyrus and the anterior cingulate, associated with the patients' typical interictal activity.

CONCLUSIONS

The electroencephalography and functional magnetic resonance imaging findings contribute to our understanding of hyperkinetic seizures type I semiology generation and can inform stereo-EEG targeting for surgical planning in refractory cases.

Aberrant connectivity in the hippocampus, bilateral insula and temporal poles precedes treatment resistance in first-episode psychosis: a prospective resting-state functional magnetic resonance imaging study with connectivity concordance mapping

Functional connectivity resting-state functional magnetic resonance imaging has been proposed to predict antipsychotic treatment response in schizophrenia. However, only a few prospective studies have examined baseline resting-state functional magnetic resonance imaging data in drug-naïve first-episode schizophrenia patients with regard to subsequent treatment response. Data-driven approaches to conceptualize and measure functional connectivity patterns vary broadly, and model-free, voxel-wise, whole-brain analysis techniques are scarce. Here, we apply such a method, called connectivity concordance mapping to resting-state functional magnetic resonance imaging data acquired from an Asian sample (n = 60) with first-episode psychosis, prior to pharmaceutical treatment. Using a longitudinal design, 12 months after the resting-state functional magnetic resonance imaging, we measured and classified patients into two groups based on psychometric testing: treatment responsive and treatment resistant. Next, we compared the two groups' connectivity concordance maps that were derived from the resting-state functional magnetic resonance imaging data at baseline. We have identified consistently higher functional connectivity in the treatment-resistant group in a network including the left hippocampus, bilateral insula and temporal poles. These data-driven novel findings can help researchers to consider new regions of interest and facilitate biomarker development in order to identify treatment-resistant schizophrenia patients early, in advance of treatment and at the time of their first psychotic episode.

Neuroimaging Methods for MRI Analysis in CSF Biomarkers Studies

Among others, the existence of pathophysiological biomarkers such as cerebrospinal fluid (CSF) Aβ-42, t-tau, and p-tau preceding the onset of Alzheimer's disease (AD) symptomatology has shifted the conceptualization of AD as a continuum. In addition, magnetic resonance imaging (MRI) enables the study of structural and functional cross-sectional correlates and longitudinal changes in vivo, and therefore, the combination of CSF data and imaging analyses emerges as a synergistic approach to understand the structural correlates related with specific AD-related biomarkers. In this chapter, we describe the methods used in neuroimaging that will allow researchers to combine data on CSF metabolites with imaging analyses.

How embodied is cognition? fMRI and behavioral evidence for common neural resources underlying motor planning and mental rotation of bodily stimuli

Functional neuroimaging shows that dorsal frontoparietal regions exhibit conjoint activity during various motor and cognitive tasks. However, it is unclear whether these regions serve several, computationally independent functions, or underlie a motor "core process" that is reused to serve higher-order functions. We hypothesized that mental rotation capacity relies on a phylogenetically older motor process that is rooted within these areas. This hypothesis entails that neural and cognitive resources recruited during motor planning predict performance in seemingly unrelated mental rotation tasks. To test this hypothesis, we first identified brain regions associated with motor planning by measuring functional activations to internally-triggered vs externally-triggered finger presses in 30 healthy participants. Internally-triggered finger presses yielded significant activations in parietal, premotor, and occipitotemporal regions. We then asked participants to perform two mental rotation tasks outside the scanner, consisting of hands or letters as stimuli. Parietal and premotor activations were significant predictors of individual reaction times when mental rotation involved hands. We found no association between motor planning and performance in mental rotation of letters. Our results indicate that neural resources in parietal and premotor cortex recruited during motor planning also contribute to mental rotation of bodily stimuli, suggesting a common core component underlying both capacities.

Effect of Alzheimer's Pathology on Task-Related Brain Network Reconfiguration in Aging

Large-scale brain networks undergo widespread changes with older age and in neurodegenerative diseases such as Alzheimer's disease (AD). Research in young adults (YA) suggest that the underlying functional architecture of brain networks remains relatively consistent between rest and task states. However, it remains unclear whether the same is true in aging and to what extent any changes may be related to accumulation of AD pathology such as β-amyloid (Aβ) and tau. Here, we examined age-related differences in functional connectivity (FC) between rest and an object-scene mnemonic discrimination task using fMRI in young and older adults (OA; both females and males). We used an a priori episodic memory network (EMN) parcellation scheme associated with object and scene processing, that included anterior-temporal regions and posterior-medial regions. We also used positron emission topography to measure Aβ and tau in older adults. The correlation between rest and task FC (i.e., FC similarity) was reduced in older compared with younger adults. Older adults with lower FC similarity in EMN had higher levels of tau in the same EMN regions and performed worse during object, but not scene, trials during the fMRI task. These findings link AD pathology, particularly tau, to a less stable functional architecture in memory networks. They also suggest that smaller changes in FC organization between rest and task states may facilitate better performance in older age. Interpretations are limited by methodological factors related to different acquisition directions and durations between rest and task scans.SIGNIFICANCE STATEMENT The brain's large-scale network organization is relatively consistent between rest and task states in young adults (YA). We found that memory networks in older adults (OA) were less correlated between rest and (memory) task states compared with young adults. Older adults with less correlated brain networks also had higher levels of Alzheimer's disease (AD) pathology in the same regions, suggesting that a less stable network architecture may reflect the early evolution of AD. Older adults with less correlated brain networks also performed worse during the memory task suggesting that more similar network organization between rest and task states may facilitate better performance in older age.

Real-time feedback reduces participant motion during task-based fMRI

The potential negative impact of head movement during fMRI has long been appreciated. Although a variety of prospective and retrospective approaches have been developed to help mitigate these effects, reducing head movement in the first place remains the most appealing strategy for optimizing data quality. Real-time interventions, in which participants are provided feedback regarding their scan-to-scan motion, have recently shown promise in reducing motion during resting state fMRI. However, whether feedback might similarly reduce motion during task-based fMRI is an open question. In particular, it is unclear whether participants can effectively monitor motion feedback while attending to task-related demands. Here we assessed whether a combination of real-time and between-run feedback could reduce head motion during task-based fMRI. During an auditory word repetition task, 78 adult participants (aged 19-81) were pseudorandomly assigned to receive feedback or not. Feedback was provided FIRMM software that used real-time calculation of realignment parameters to estimate participant motion. We quantified movement using framewise displacement (FD). We found that motion feedback resulted in a statistically significant reduction in participant head motion, with a small-to-moderate effect size (reducing average FD from 0.347 to 0.282). Reductions were most apparent in high-motion events. We conclude that under some circumstances real-time feedback may reduce head motion during task-based fMRI, although its effectiveness may depend on the specific participant population and task demands of a given study.

Functional network structure supports resilience to memory deficits in cognitively normal older adults with amyloid-β pathology

Older adults may harbor large amounts of amyloid-β (Aβ) pathology, yet still perform at age-normal levels on memory assessments. We tested whether functional brain networks confer resilience or compensatory mechanisms to support memory in the face of Aβ pathology. Sixty-five cognitively normal older adults received high-resolution resting state fMRI to assess functional networks, 18F-florbetapir-PET to measure Aβ, and a memory assessment. We characterized functional networks with graph metrics of local efficiency (information transfer), modularity (specialization of functional modules), and small worldness (balance of integration and segregation). There was no difference in functional network measures between older adults with high Aβ (Aβ+) compared to those with no/low Aβ (Aβ-). However, in Aβ+ older adults, increased local efficiency, modularity, and small worldness were associated with better memory performance, while this relationship did not occur Aβ- older adults. Further, the association between increased local efficiency and better memory performance in Aβ+ older adults was localized to local efficiency of the default mode network and hippocampus, regions vulnerable to Aβ and involved in memory processing. Our results suggest functional networks with modular and efficient structures are associated with resilience to Aβ pathology, providing a functional target for intervention.

Continuous Evaluation of Denoising Strategies in Resting-State fMRI Connectivity Using fMRIPrep and Nilearn

Reducing contributions from non-neuronal sources is a crucial step in functional magnetic resonance imaging (fMRI) connectivity analyses. Many viable strategies for denoising fMRI are used in the literature, and practitioners rely on denoising benchmarks for guidance in the selection of an appropriate choice for their study. However, fMRI denoising software is an ever-evolving field, and the benchmarks can quickly become obsolete as the techniques or implementations change. In this work, we present a denoising benchmark featuring a range of denoising strategies, datasets and evaluation metrics for connectivity analyses, based on the popular fMRIprep software. The benchmark is implemented in a fully reproducible framework, where the provided research objects enable readers to reproduce or modify core computations, as well as the figures of the article using the Jupyter Book project and the Neurolibre reproducible preprint server (https://neurolibre.org/). We demonstrate how such a reproducible benchmark can be used for continuous evaluation of research software, by comparing two versions of the fMRIprep software package. The majority of benchmark results were consistent with prior literature. Scrubbing, a technique which excludes time points with excessive motion, combined with global signal regression, is generally effective at noise removal. Scrubbing however disrupts the continuous sampling of brain images and is incompatible with some statistical analyses, e.g. auto-regressive modeling. In this case, a simple strategy using motion parameters, average activity in select brain compartments, and global signal regression should be preferred. Importantly, we found that certain denoising strategies behave inconsistently across datasets and/or versions of fMRIPrep, or had a different behavior than in previously published benchmarks. This work will hopefully provide useful guidelines for the fMRIprep users community, and highlight the importance of continuous evaluation of research methods. Our reproducible benchmark infrastructure will facilitate such continuous evaluation in the future, and may also be applied broadly to different tools or even research fields.

Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States

BACKGROUND

EEG-fMRI is a useful additional test to localize the epileptogenic zone (EZ) particularly in MRI negative cases. However subject motion presents a particular challenge owing to its large effects on both MRI and EEG signal. Traditionally it is assumed that prospective motion correction (PMC) of fMRI precludes EEG artifact correction.

METHODS

Children undergoing presurgical assessment at Great Ormond Street Hospital were included into the study. PMC of fMRI was done using a commercial system with a Moiré Phase Tracking marker and MR-compatible camera. For retrospective EEG correction both a standard and a motion educated EEG artefact correction (REEGMAS) were compared to each other.

RESULTS

Ten children underwent simultaneous EEG-fMRI. Overall head movement was high (mean RMS velocity < 1.5 mm/s) and showed high inter- and intra-individual variability. Comparing motion measured by the PMC camera and the (uncorrected residual) motion detected by realignment of fMRI images, there was a five-fold reduction in motion from its prospective correction. Retrospective EEG correction using both standard approaches and REEGMAS allowed the visualization and identification of physiological noise and epileptiform discharges. Seven of 10 children had significant maps, which were concordant with the clinical EZ hypothesis in 6 of these 7.

CONCLUSION

To our knowledge this is the first application of camera-based PMC for MRI in a pediatric clinical setting. Despite large amount of movement PMC in combination with retrospective EEG correction recovered data and obtained clinically meaningful results during high levels of subject motion. Practical limitations may currently limit the widespread use of this technology.

Task-based functional connectivity identifies two segregated networks underlying intentional action

While much of motor behavior is automatic, intentional action is necessary for the selection and initiation of controlled motor acts and is thus an essential part of goal-directed behavior. Neuroimaging studies have shown that self-generated action implicates several dorsal and ventral frontoparietal areas. However, knowledge of the functional coupling between these brain regions during intentional action remains limited. We here studied brain activations and functional connectivity (FC) of thirty right-handed healthy participants performing a finger pressing task instructed to use a specific finger (externally-triggered action) or to select one of four fingers randomly (internally-generated action). Participants performed the task in alternating order either with their dominant right hand or the left hand. Consistent with previous studies, we observed stronger involvement of posterior parietal cortex and premotor regions when contrasting internally-generated with externally-triggered action. Interestingly, this contrast also revealed significant engagement of medial occipitotemporal regions including the left lingual and right fusiform gyrus. Task-based FC analysis identified increased functional coupling among frontoparietal regions as well as increased and decreased coupling between occipitotemporal regions, thus differentiating between two segregated networks. When comparing results of the dominant and nondominant hand we found less activation, but stronger connectivity for the former, suggesting increased neural efficiency when participants use their dominant hand. Taken together, our results reveal that two segregated networks that encompass the frontoparietal and occipitotemporal cortex contribute independently to intentional action.

Optimizing multivariate pattern classification in rapid event-related designs

BACKGROUND

Multivariate pattern analysis (MVPA or pattern decoding) has attracted considerable attention as a sensitive analytic tool for investigations using functional magnetic resonance imaging (fMRI) data. With the introduction of MVPA, however, has come a proliferation of methodological choices confronting the researcher, with few studies to date offering guidance from the vantage point of controlled datasets detached from specific experimental hypotheses.

NEW METHOD

We investigated the impact of four data processing steps on support vector machine (SVM) classification performance aimed at maximizing information capture in the presence of common noise sources. The four techniques included: trial averaging (classifying on separate trial estimates versus condition-based averages), within-run mean centering (centering the data or not), method of cost selection (using a fixed or tuned cost value), and motion-related denoising approach (comparing no denoising versus a variety of nuisance regressions capturing motion-related reference signals). The impact of these approaches was evaluated on real fMRI data from two control ROIs, as well as on simulated pattern data constructed with carefully controlled voxel- and trial-level noise components.

RESULTS

We find significant improvements in classification performance across both real and simulated datasets with run-wise trial averaging and mean centering. When averaging trials within conditions of each run, we note a simultaneous increase in the between-subject variability of SVM classification accuracies which we attribute to the reduced size of the test set used to assess the classifier's prediction error. Therefore, we propose a hybrid technique whereby randomly sampled subsets of trials are averaged per run and demonstrate that it helps mitigate the tradeoff between improving signal-to-noise ratio by averaging and losing exemplars in the test set.

COMPARISON WITH EXISTING METHODS

Though a handful of empirical studies have employed run-based trial averaging, mean centering, or their combination, such studies have done so without theoretical justification or rigorous testing using control ROIs.

CONCLUSIONS

Therefore, we intend this study to serve as a practical guide for researchers wishing to optimize pattern decoding without risk of introducing spurious results.

Long-range functional connections mirror and link microarchitectural and cognitive hierarchies in the human brain

BACKGROUND

Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry.

METHODS

We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections.

RESULTS

Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture.

CONCLUSIONS

By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.

Entorhinal-Hippocampal Circuit Integrity Is Related to Mnemonic Discrimination and Amyloid-β Pathology in Older Adults

Mnemonic discrimination, a cognitive process that relies on hippocampal pattern separation, is one of the first memory domains to decline in aging and preclinical Alzheimer's disease. We tested whether functional connectivity (FC) within the entorhinal-hippocampal circuit, measured with high-resolution resting state fMRI, is associated with mnemonic discrimination and amyloid-β (Aβ) pathology in a sample of 64 cognitively normal human older adults (mean age, 71.3 ± 6.4 years; 67% female). FC was measured between entorhinal-hippocampal circuit nodes with known anatomical connectivity, as well as within cortical memory networks. Aβ pathology was measured with 18F-florbetapir-PET, and neurodegeneration was assessed with subregional volume from structural MRI. Participants performed both object and spatial versions of a mnemonic discrimination task outside of the scanner and were classified into low-performing and high-performing groups on each task using a median split. Low object mnemonic discrimination performance was specifically associated with increased FC between anterolateral entorhinal cortex (alEC) and dentate gyrus (DG)/CA3, supporting the importance of this connection to object memory. This hyperconnectivity between alEC and DG/CA3 was related to Aβ pathology and decreased entorhinal cortex volume. In contrast, spatial mnemonic discrimination was not associated with altered FC. Aβ was further associated with dysfunction within hippocampal subfields, particularly with decreased FC between CA1 and subiculum as well as reduced volume in these regions. Our findings suggest that Aβ may indirectly lead to memory impairment through entorhinal-hippocampal circuit dysfunction and neurodegeneration and provide a mechanism for increased vulnerability of object mnemonic discrimination.SIGNIFICANCE STATEMENT Mnemonic discrimination is a critical episodic memory process that is performed in the dentate gyrus (DG) and CA3 subfield of the hippocampus, relying on input from entorhinal cortex. Mnemonic discrimination is particularly vulnerable to decline in older adults; however, the mechanisms behind this vulnerability are still unknown. We demonstrate that object mnemonic discrimination impairment is related to hyperconnectivity between the anterolateral entorhinal cortex and DG/CA3. This hyperconnectivity was associated with amyloid-β pathology and neurodegeneration in entorhinal cortex, suggesting aberrantly increased network activity is a pathological process. Our findings provide a mechanistic explanation of the vulnerability of object compared to spatial mnemonic discrimination in older adults and has translational implications for choice of outcome measures in clinical trials for Alzheimer's disease.

Dynamic spectral signatures of mirror movements in the sensorimotor functional connectivity network of patients with Kallmann syndrome

In Kallmann syndrome (KS), the peculiar phenomenon of bimanual synkinesis or mirror movement (MM) has been associated with a spectral shift, from lower to higher frequencies, of the resting-state fMRI signal of the large-scale sensorimotor brain network (SMN). To possibly determine whether a similar frequency specificity exists across different functional connectivity SMN states, and to capture spontaneous transitions between them, we investigated the dynamic spectral changes of the SMN functional connectivity in KS patients with and without MM symptom. Brain MRI data were acquired at 3 Tesla in 39 KS patients (32 without MM, KSMM-, seven with MM, KSMM+) and 26 age- and sex-matched healthy control (HC) individuals. The imaging protocol included 20-min rs-fMRI scans enabling detailed spectro-temporal analyses of large-scale functional connectivity brain networks. Group independent component analysis was used to extract the SMN. A sliding window approach was used to extract the dynamic spectral power of the SMN functional connectivity within the canonical physiological frequency range of slow rs-fMRI signal fluctuations (0.01–0.25 Hz). K-means clustering was used to determine (and count) the most recurrent dynamic states of the SMN and detect the number of transitions between them. Two most recurrent states were identified, for which the spectral power peaked at a relatively lower (state 1) and higher (state 2) frequency. Compared to KS patients without MM and HC subjects, the SMN of KS patients with MM displayed significantly larger spectral power changes in the slow 3 canonical sub-band (0.073–0.198 Hz) and significantly fewer transitions between state 1 (less recurrent) and state 2 (more recurrent). These findings demonstrate that the presence of MM in KS patients is associated with reduced spontaneous transitions of the SMN between dynamic functional connectivity states and a higher recurrence and an increased spectral power change of the high-frequency state. These results provide novel information about the large-scale brain functional dynamics that could help to understand the pathologic mechanisms of bimanual synkinesis in KS syndrome and, potentially, other neurological disorders where MM may also occur.

Regional homogeneity of adolescents with high-functioning autism spectrum disorder and its association with symptom severity

BACKGROUND AND PURPOSE

Previous studies have revealed abnormal regional homogeneity (ReHo) in individuals with autism spectrum disorder (ASD); however, there is little consistency across the findings within these studies, partly due to small sample size and great heterogeneity among participants between studies. Additionally, few studies have explored the association between ReHo aberrance and clinical symptoms in individuals with ASD.

METHODS

Forty-eight adolescents with high-functioning ASD and 63 group-matched typically developing (TD) controls received functional magnetic resonance imaging at rest. Group-level analysis was performed to detect differences in ReHo between ASD and TD. Evaluation of symptom severity in individuals with ASD was based on the Autism Behavior Checklist (ABC). Voxel-wise correlation analysis was undergone to examine the correlations between the symptom severity and ReHo map in individuals with ASD within brain areas with ReHo abnormalities.

RESULTS

Compared with the TD controls, individuals with ASD exhibited increased ReHo in the bilateral anterior cingulate cortex, left caudate, right posterior cerebellum (cerebellar tonsil), and bilateral brainstem and decreased ReHo in the left precentral gyrus, left inferior parietal lobule, bilateral postcentral gyrus, and right anterior cerebellum (culmen). The correlation analysis indicated that the ReHo value in the brainstem was negatively associated with the ABC total scores and the scores of Relating factor, respectively.

CONCLUSIONS

Our findings indicated that widespread ReHo abnormalities occurred in ASD, shedding light on the underlying neurobiology of pathogenesis and symptomatology of ASD.

Repetitive Transcranial Magnetic Stimulation (rTMS) of Dorsolateral Prefrontal Cortex May Influence Semantic Fluency and Functional Connectivity in Fronto-Parietal Network in Mild Cognitive Impairment (MCI)

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique that is increasingly used as a nonpharmacological intervention against cognitive impairment in Alzheimer’s disease (AD) and other dementias. Although rTMS has been shown to modify cognitive performances and brain functional connectivity (FC) in many neurological and psychiatric diseases, there is still no evidence about the possible relationship between executive performances and resting-state brain FC following rTMS in patients with mild cognitive impairment (MCI). In this preliminary study, we aimed to evaluate the possible effects of rTMS of the bilateral dorsolateral prefrontal cortex (DLPFC) in 27 MCI patients randomly assigned to two groups: one group received high-frequency (10 Hz) rTMS (HF-rTMS) for four weeks (n = 11), and the other received sham stimulation (n = 16). Cognitive and psycho-behavior scores, based on the Repeatable Battery for the Assessment of Neuropsychological Status, Beck Depression Inventory-II, Beck Anxiety Inventory, Apathy Evaluation Scale, and brain FC, evaluated by independent component analysis of resting state functional MRI (RS-fMRI) networks, together with the assessment of regional atrophy measures, evaluated by whole-brain voxel-based morphometry (VBM), were measured at baseline, after five weeks, and six months after rTMS stimulation. Our results showed significantly increased semantic fluency (p = 0.026) and visuo-spatial (p = 0.014) performances and increased FC within the salience network (p ≤ 0.05, cluster-level corrected) at the short-term timepoint, and increased FC within the left fronto-parietal network (p ≤ 0.05, cluster-level corrected) at the long-term timepoint, in the treated group but not in the sham group. Conversely, regional atrophy measures did not show significant longitudinal changes between the two groups across six months. Our preliminary findings suggest that targeting DLPFC by rTMS application may lead to a significant long-term increase in FC in MCI patients in a RS network associated with executive functions, and this process might counteract the progressive cortical dysfunction affecting this domain.

Predicting response time variability from task and resting-state functional connectivity in the aging brain

Aging is associated with declines in a host of cognitive functions, including attentional control, inhibitory control, episodic memory, processing speed, and executive functioning. Theoretical models attribute the age-related decline in cognitive functioning to deficits in goal maintenance and attentional inhibition. Despite these well-documented declines in executive control resources, older adults endorse fewer episodes of mind-wandering when assessed using task-embedded thought probes. Furthermore, previous work on the neural basis of mind-wandering has mostly focused on young adults with studies predominantly focusing on the activity and connectivity of a select few canonical networks. However, whole-brain functional networks associated with mind-wandering in aging have not yet been characterized. In this study, using response time variability-the trial-to-trial fluctuations in behavioral responses-as an indirect marker of mind-wandering or an "out-of-the-zone" attentional state representing suboptimal behavioral performance, we show that brain-based predictive models of response time variability can be derived from whole-brain task functional connectivity. In contrast, models derived from resting-state functional connectivity alone did not predict individual response time variability. Finally, we show that despite successful within-sample prediction of response time variability, our models did not generalize to predict response time variability in independent cohorts of older adults with resting-state connectivity. Overall, our findings provide evidence for the utility of task-based functional connectivity in predicting individual response time variability in aging. Future research is needed to derive more robust and generalizable models.

Deep Attentive Spatio-Temporal Feature Learning for Automatic Resting-State fMRI Denoising

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive functional neuroimaging modality that has been widely used to investigate functional connectomes in the brain. Since noise and artifacts generated by non-neuronal physiological activities are predominant in raw rs-fMRI data, effective noise removal is one of the most important preprocessing steps prior to any subsequent analysis. For rs-fMRI denoising, a common trend is to decompose rs-fMRI data into multiple components and then regress out noise-related components. Therefore, various machine learning techniques have been used in such analyses with predefined procedures and manually engineered features. However, the lack of a universal definition of a noise-related source or artifact complicates manual feature engineering. Manual feature selection can result in the failure to capture unknown types of noise. Furthermore, the possibility that the hand-crafted features will only work for the broader population (e.g., healthy adults) but not for "outliers" (e.g., infants or subjects that belong to a disease cohort) is quite high. In practice, we have limited knowledge of which features should be extracted; thus, multi-classifier assembly must be implemented to improve performance, although this process is quite time-consuming. However, in real rs-fMRI applications, fast and accurate automatic identification of noise-related components on different datasets is critical. To solve this problem, we propose a novel, automatic, and end-to-end deep learning framework dedicated to noise-related component identification via a faster and more effective multi-layer feature extraction strategy that learns deeply embedded spatio-temporal features of the components. In this study, we achieved remarkable performance on various rs-fMRI datasets, including multiple adult rs-fMRI datasets from different rs-fMRI studies and an infant rs-fMRI dataset, which is quite heterogeneous and differs from that of adults. Our proposed framework also dramatically increases the noise detection speed owing to its inherent ability for deep learning (< 1s for single-component classification). It can be easily integrated into any preprocessing pipeline, even those that do not use standard procedures but depend on alternative toolboxes.

Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film

Intracranial human recordings are a valuable and rare resource of information about the brain. Making such data publicly available not only helps tackle reproducibility issues in science, it helps make more use of these valuable data. This is especially true for data collected using naturalistic tasks. Here, we describe a dataset collected from a large group of human subjects while they watched a short audiovisual film. The dataset has several unique features. First, it includes a large amount of intracranial electroencephalography (iEEG) data (51 participants, age range of 5-55 years, who all performed the same task). Second, it includes functional magnetic resonance imaging (fMRI) recordings (30 participants, age range of 7-47) during the same task. Eighteen participants performed both iEEG and fMRI versions of the task, non-simultaneously. Third, the data were acquired using a rich audiovisual stimulus, for which we provide detailed speech and video annotations. This dataset can be used to study neural mechanisms of multimodal perception and language comprehension, and similarity of neural signals across brain recording modalities.

Tormenting thoughts: The posterior cingulate sulcus of the default mode network regulates valence of thoughts and activity in the brain's pain network during music listening

Many individuals spend a significant amount of their time "mind-wandering". Mind-wandering often includes spontaneous, nonintentional thought, and a neural correlate of this kind of thought is the default mode network (DMN). Thoughts during mind-wandering can have positive or negative valence, but only little is known about the neural correlates of positive or negative thoughts. We used resting-state functional magnetic resonance imaging (fMRI) and music to evoke mind-wandering in n = 33 participants, with positive-sounding music eliciting thoughts with more positive valence and negative-sounding music eliciting thoughts with more negative valence. Applying purely data-driven analysis methods, we show that medial orbitofrontal cortex (mOFC, part of the ventromedial prefrontal cortex) and the posterior cingulate sulcus (likely area 23c of the posterior cingulate cortex), two sub-regions of the DMN, modulate the valence of thought-contents during mind-wandering. In addition, across two independent experiments, we observed that the posterior cingulate sulcus, a region involved in pain, shows valence-specific functional connectivity with core regions of the brain's putative pain network. Our results suggest that two DMN regions (mOFC and posterior cingulate sulcus) support the formation of negative spontaneous, nonintentional thoughts, and that the interplay between these structures with regions of the putative pain network forms a neural mechanism by which thoughts can become painful.

Increased Connectivity among Sensory and Motor Regions during Visual and Audiovisual Speech Perception

In everyday conversation, we usually process the talker's face as well as the sound of the talker's voice. Access to visual speech information is particularly useful when the auditory signal is degraded. Here, we used fMRI to monitor brain activity while adult humans (n = 60) were presented with visual-only, auditory-only, and audiovisual words. The audiovisual words were presented in quiet and in several signal-to-noise ratios. As expected, audiovisual speech perception recruited both auditory and visual cortex, with some evidence for increased recruitment of premotor cortex in some conditions (including in substantial background noise). We then investigated neural connectivity using psychophysiological interaction analysis with seed regions in both primary auditory cortex and primary visual cortex. Connectivity between auditory and visual cortices was stronger in audiovisual conditions than in unimodal conditions, including a wide network of regions in posterior temporal cortex and prefrontal cortex. In addition to whole-brain analyses, we also conducted a region-of-interest analysis on the left posterior superior temporal sulcus (pSTS), implicated in many previous studies of audiovisual speech perception. We found evidence for both activity and effective connectivity in pSTS for visual-only and audiovisual speech, although these were not significant in whole-brain analyses. Together, our results suggest a prominent role for cross-region synchronization in understanding both visual-only and audiovisual speech that complements activity in integrative brain regions like pSTS.SIGNIFICANCE STATEMENT In everyday conversation, we usually process the talker's face as well as the sound of the talker's voice. Access to visual speech information is particularly useful when the auditory signal is hard to understand (e.g., background noise). Prior work has suggested that specialized regions of the brain may play a critical role in integrating information from visual and auditory speech. Here, we show a complementary mechanism relying on synchronized brain activity among sensory and motor regions may also play a critical role. These findings encourage reconceptualizing audiovisual integration in the context of coordinated network activity.

Sex differences in the taste-evoked functional connectivity network

The central gustatory pathway encompasses multiple subcortical and cortical regions whose neural functional connectivity can be modulated by taste stimulation. While gustatory perception has been previously linked to sex, whether and how the gustatory network differently responds to basic tastes between men and women is unclear. Here, we defined the regions of the central gustatory network by a meta-analysis of 35 fMRI taste activation studies and then analyzed the taste-evoked functional connectivity between these regions in 44 subjects (19 women) in a separate 3 Tesla activation study where sweet and bitter solutions, at five concentrations each, were administered during scanning. From the meta-analysis, a network model was set up, including bilateral anterior, middle and inferior insula, thalamus, precentral gyrus, left amygdala, caudate and dorsolateral prefrontal cortex. Higher functional connectivity than in women was observed in men between the right middle insula and bilateral thalami for bitter taste. Men exhibited higher connectivity than women at low bitter concentrations and middle-high sweet concentrations between bilateral thalamus and insula. A graph-based analysis expressed similar results in terms of nodal characteristics of strength and centrality. Our findings add new insights into the mechanisms of taste processing by highlighting sex differences in the functional connectivity of the gustatory network as modulated by the perception of sweet and bitter tastes. These results shed more light on the neural origin of sex-related differences in gustatory perception and may guide future research on the pathophysiology of taste perception in humans.

Evaluating the Performance of Machine Learning Models for Automatic Diagnosis of Patients with Schizophrenia Based on a Single Site Dataset of 440 Participants

Background

Methods

Results

Conclusions

Cross-modal connectivity effects in age-related hearing loss

Age-related sensorineural hearing loss (HL) leads to localized brain changes in the primary auditory cortex, long-range functional alterations, and is considered a risk factor for dementia. Nonhuman studies have repeatedly highlighted cross-modal brain plasticity in sensorial brain networks other than those primarily involved in the peripheral damage, thus in this study, the possible cortical alterations associated with HL have been analyzed using a whole-brain multimodal connectomic approach. Fifty-two HL and 30 normal hearing participants were examined in a 3T MRI study along with audiological and neurological assessments. Between-regions functional connectivity and whole-brain probabilistic tractography were calculated in a connectome-based manner and graph theory was used to obtain low-dimensional features for the analysis of brain connectivity at global and local levels. The HL condition was associated with a different functional organization of the visual subnetwork as revealed by a significant increase in global efficiency, density, and clustering coefficient. These functional effects were mirrored by similar (but more subtle) structural effects suggesting that a functional repurposing of visual cortical centers occurs to compensate for age-related loss of hearing abilities.

A multi-measure approach for assessing the performance of fMRI preprocessing strategies in resting-state functional connectivity

It is well established that head motion and physiological processes (e.g. cardiac and breathing activity) should be taken into consideration when analyzing and interpreting results in fMRI studies. However, even though recent studies aimed to evaluate the performance of different preprocessing pipelines there is still no consensus on the optimal strategy. This is partly due to the fact that the quality control (QC) metrics used to evaluate differences in performance across pipelines have often yielded contradictory results. Furthermore, preprocessing techniques based on physiological recordings or data decomposition techniques (e.g. aCompCor) have not been comprehensively examined. Here, to address the aforementioned issues, we propose a framework that summarizes the scores from eight previously proposed and novel QC metrics to a reduced set of two QC metrics that reflect the signal-to-noise ratio and the reduction in motion artifacts and biases in the preprocessed fMRI data. Using this framework, we evaluate the performance of three commonly used practices on the quality of data: 1) Removal of nuisance regressors from fMRI data, 2) discarding motion-contaminated volumes (i.e., scrubbing) before regression, and 3) low-pass filtering the data and the nuisance regressors before their removal. Using resting-state fMRI data from the Human Connectome Project, we show that the scores of the examined QC metrics improve the most when the global signal (GS) and about 17% of principal components from white matter (WM) are removed from the data. Finally, we observe a small further improvement with low-pass filtering at 0.20 Hz and milder variants of WM denoising, but not with scrubbing.

Soundtrack of life: An fMRI study

Most people have a soundtrack of life, a set of special musical pieces closely linked to certain biographical experiences. Autobiographical memories (AM) and music listening (ML) involve complex mental processes ruled by differentiate brain networks. The aim of the paper was to determine the way both networks interact in linked occurrences. We performed an fMRI experiment on 31 healthy participants (age: 32.4 ± 7.6, 11 men, 4 left-handers). Participants had to recall AMs prompted by music they reported to be associated with personal biographical events (LMM: linked AM-ML events). In the main control task, participants were prompted to recall emotional AMs while listening known tracks from a pool of popular music (UMM: unlinked AM-ML events). We wanted to investigate to what extent LMM network exceeded the overlap of AM and ML networks by contrasting the activation obtained in LMM versus UMM. The contrast LMM>UMM showed the areas (at P < 0.05 FWE corrected at voxel level and cluster size>20): right frontal inferior operculum, frontal middle gyrus, pars triangularis of inferior frontal gyrus, occipital superior gyrus and bilateral basal ganglia (caudate, putamen and pallidum), occipital (middle and inferior), parietal (inferior and superior), precentral and cerebellum (6, 7 L, 8 and vermis 6 and 7). Complementary results were obtained from additional control tasks. Provided part of tLMM>UMM areas might not be related to ML-AM linkage, we assessed LMM brain network by an independent component analysis (ICA) on contrast images. Results from ICA suggest the existence of a cortico-ponto-cerebellar network including left precuneus, bilateral anterior cingulum, parahippocampal gyri, frontal inferior operculum, ventral anterior part of the insula, frontal medial orbital gyri, caudate nuclei, cerebellum 6 and vermis, which might rule the ML-induced retrieval of AM in closely linked AM-ML events. This topography may suggest that the pathway by which ML is linked to AM is attentional and directly related to perceptual processing, involving salience network, instead of the natural way of remembering typically associated with default mode network.

[Imaging in the presurgical evaluation of epilepsy]

Während zwei Drittel der PatientInnen mit Epilepsie durch Medikamente anfallsfrei werden, ist die Erkrankung bei 30 % pharmakoresistent. Bei pharmakoresistenter fokaler Epilepsie bietet die Epilepsiechirurgie eine etwa 65 %ige Chance auf Anfallsfreiheit. Vorab muss der Anfallsfokus exakt eingegrenzt werden, wofür bildgebende Methoden unverzichtbar sind. In den letzten Jahren hat sich in der Prächirurgie der Anteil von PatientInnen mit unauffälliger konventioneller Magnetresonanztomographie (MRT) erhöht. Allerdings konnte die Sensitivität der MRT durch spezielle Aufnahmesequenzen und Techniken der Postprozessierung gesteigert werden. Die Quellenlokalisation des Signals von Elektro- und Magnetenzephalographie (EEG und MEG) verortet den Ursprung iktaler und interiktaler epileptischer Aktivität im Gehirn. Nuklearmedizinische Untersuchungen wie die interiktale Positronen-Emissions-Tomographie (PET) und die iktale Einzelphotonen-Emissionscomputertomographie (SPECT) detektieren chronische oder akute anfallsbezogene Veränderungen des Hirnmetabolismus und können auch bei nichtlokalisierendem MRT auf den epileptogenen Fokus hinweisen. Alle Befunde zusammengenommen werden zur Planung eventueller invasiver EEG-Ableitungen und letztlich der chirurgischen Operation eingesetzt. Konkordante Befunde sind mit besseren chirurgischen Ergebnissen assoziiert und zeigen auch im Langzeitverlauf signifikant höhere Anfallsfreiheitsraten.

Alzheimer's Pathology Is Associated with Dedifferentiation of Intrinsic Functional Memory Networks in Aging

In presymptomatic Alzheimer's disease (AD), beta-amyloid plaques (Aβ) and tau tangles accumulate in distinct spatiotemporal patterns within the brain, tracking closely with episodic memory decline. Here, we tested whether age-related changes in the segregation of the brain's intrinsic functional episodic memory networks-anterior-temporal (AT) and posterior-medial (PM) networks-are associated with the accumulation of Aβ, tau, and memory decline using fMRI and PET. We found that AT and PM networks were less segregated in older than that in younger adults and this reduced specialization was associated with more tau and Aβ in the same regions. The effect of network dedifferentiation on memory depended on the amount of Aβ and tau, with low segregation and pathology associated with better performance at baseline and low segregation and high pathology related to worse performance over time. This pattern suggests a compensation phase followed by a degenerative phase in the early, preclinical phase of AD.

Efficient Brain Connectivity Reconfiguration Predicts Higher Marital Quality and Lower Depression

Social-information processing is important for successful romantic relationships and protecting against depression, and depends on functional connectivity (FC) within and between large-scale networks. Functional architecture evident at rest is adaptively reconfigured during task and there were two possible associations between brain reconfiguration and behavioral performance during neurocognitive tasks (efficiency effect and distraction-based effect). This study examined relationships between brain reconfiguration during social-information processing and relationship-specific and more general social outcomes in marriage. Resting-state FC was compared with FC during social-information processing (watching relationship-specific and general emotional stimuli) of 29 heterosexual couples, and the FC similarity (reconfiguration efficiency) was examined in relation to marital quality and depression 13 months later. The results indicated wives' reconfiguration efficiency (globally and in visual association network) during relationship-specific stimuli processing was related to their own marital quality. Higher reconfiguration efficiency (globally and in medial frontal, frontal-parietal, default mode, motor/sensory and salience networks) in wives during general emotional stimuli processing was related to their lower depression. These findings suggest efficiency effects on social outcomes during social cognition, especially among married women. The efficiency effects on relationship-specific and more general outcome are respectively higher during relationship-specific stimuli or general emotional stimuli processing.

Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep

Current state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a method to reveal the low dimensional intrinsic manifold underlying human brain dynamics, which is invariant of the high dimensional spatio-temporal representation of the neuroimaging technology. By applying this intrinsic manifold framework to fMRI data acquired in wakefulness and sleep, we reveal the nonlinear differences between wakefulness and three different sleep stages, and successfully decode these different brain states with a mean accuracy across participants of 96%. Remarkably, a further group analysis shows that the intrinsic manifolds of all participants share a common topology. Overall, our results reveal the intrinsic manifold underlying the spatiotemporal dynamics of brain activity and demonstrate how this manifold enables the decoding of different brain states such as wakefulness and various sleep stages.

Brain correlates of urban environmental exposures in cognitively unimpaired individuals at increased risk for Alzheimer's disease: A study on Barcelona's population

INTRODUCTION

Urban environmental exposures might contribute to the incidence of Alzheimer's disease (AD). Our aim was to identify structural brain imaging correlates of urban environmental exposures in cognitively unimpaired individuals at increased risk of AD.

METHODS

Two hundred twelve participants with brain scans and residing in Barcelona, Spain, were included. Land use regression models were used to estimate residential exposure to air pollutants. The daily average noise level was obtained from noise maps. Residential green exposure indicators were also generated. A cerebral 3D-T1 was acquired to obtain information on brain morphology. Voxel-based morphometry statistical analyses were conducted to determine the areas of the brain in which regional gray matter (GM) and white matter (WM) volumes were associated with environmental exposures.

RESULTS

Exposure to nitrogen dioxide was associated with lower GM volume in the precuneus and greater WM volume in the splenium of the corpus callosum and inferior longitudinal fasciculus. In contrast, exposure to fine particulate matter was associated with greater GM in cerebellum and WM in the splenium of corpus callosum, the superior longitudinal fasciculus, and cingulum cingulate gyrus. Noise was positively associated with WM volume in the body of the corpus callosum. Exposure to greenness was associated with greater GM volume in the middle frontal, precentral, and the temporal pole.

DISCUSSION

In cognitively unimpaired adults with increased risk of AD, exposure to air pollution, noise, and green areas are associated with GM and WM volumes of specific brain areas known to be affected in AD, thus potentially conferring a higher vulnerability to the disease.

Altered Relationship Between Heart Rate Variability and fMRI-Based Functional Connectivity in People With Epilepsy

Background: Disruptions in central autonomic processes in people with epilepsy have been studied through evaluation of heart rate variability (HRV). Decreased HRV appears in epilepsy compared to healthy controls, suggesting a shift in autonomic balance toward sympathetic dominance; recent studies have associated HRV changes with seizure severity and outcome of interventions. However, the processes underlying these autonomic changes remain unclear. We examined the nature of these changes by assessing alterations in whole-brain functional connectivity, and relating those alterations to HRV. Methods: We examined regional brain activity and functional organization in 28 drug-resistant epilepsy patients and 16 healthy controls using resting-state functional magnetic resonance imaging (fMRI). We employed an HRV state-dependent functional connectivity (FC) framework with low and high HRV states derived from the following four cardiac-related variables: 1. RR interval, 2. root mean square of successive differences (RMSSD), 4. low-frequency HRV (0.04-0.15 Hz; LF-HRV) and high-frequency HRV (0.15-0.40 Hz; HF-HRV). The effect of group (epilepsy vs. controls), HRV state (low vs. high) and the interactions of group and state were assessed using a mixed analysis of variance (ANOVA). We assessed FC within and between 7 large-scale functional networks consisting of cortical regions and 4 subcortical networks, the amygdala, hippocampus, basal ganglia and thalamus networks. Results: Consistent with previous studies, decreased RR interval (increased heart rate) and decreased HF-HRV appeared in people with epilepsy compared to healthy controls. For both groups, fluctuations in heart rate were positively correlated with BOLD activity in bilateral thalamus and regions of the cerebellum, and negatively correlated with BOLD activity in the insula, putamen, superior temporal gyrus and inferior frontal gyrus. Connectivity strength in patients between right thalamus and ventral attention network (mainly insula) increased in the high LF-HRV state compared to low LF-HRV; the opposite trend appeared in healthy controls. A similar pattern emerged for connectivity between the thalamus and basal ganglia. Conclusion: The findings suggest that resting connectivity patterns between the thalamus and other structures underlying HRV expression are modified in people with drug-resistant epilepsy compared to healthy controls.

An Effect of Education on Memory-Encoding Activation in Subjective Cognitive Decline

BACKGROUND

Subjective cognitive decline (SCD) may be an early manifestation of pre-clinical Alzheimer's disease. Elevated amyloid-β (Aβ) is a correlate of SCD symptoms in some individuals. The underlying neural correlates of SCD symptoms and their association with Aβ is unknown. SCD is a heterogeneous condition, and cognitive reserve may explain individual differences in its neural correlates.

OBJECTIVE

We investigated the association between brain activation during memory encoding and SCD symptoms, as well as with Aβ, among older individuals. We also tested the moderating role of education (an index of cognitive reserve) on the associations.

METHODS

We measured brain activation during the "face-name" memory-encoding fMRI task and Aβ deposition with Pittsburgh Compound-B (PiB)-PET among cognitively normal older individuals (n = 63, mean age 73.1 ± 7.4 years). We tested associations between activation and SCD symptoms by self-report measures, Aβ, and interactions with education.

RESULTS

Activation was not directly associated with SCD symptoms or Aβ. However, education moderated the association between activation and SCD symptoms in the executive control network, salience network, and subcortical regions. Greater SCD symptoms were associated with greater activation in those with higher education, but with lower activation in those with lower education.

CONCLUSION

SCD symptoms were associated with different patterns of brain activation in the extended memory system depending on level of cognitive reserve. Greater SCD symptoms may represent a saturation of neural compensation in individuals with greater cognitive reserve, while it may reflect diminishing neural resources in individuals with lower cognitive reserve.

Effect of blast-related mTBI on the working memory system: a resting state fMRI study

Reduced working memory is frequently reported by Veterans with a history of blast-related mild traumatic brain injury (mTBI), but can be difficult to quantify on neuropsychological measures. This study aimed to improve our understanding of the impact of blast-related mTBI on the working memory system by using resting state functional magnetic resonance imaging (fMRI) to explore differences in functional connectivity between OEF/OIF/OND Veterans with and without a history of mTBI. Participants were twenty-four Veterans with a history of blast-related mTBI and 17 Veterans who were deployed but had no lifetime history of TBI. Working memory ability was evaluated with the Auditory Consonants Trigrams (ACT) task. Resting state fMRI was used to evaluate intrinsic functional connectivity from frontal seed regions that are known components of the working memory network. No significant group differences were found on the ACT, but the imaging analyses revealed widespread hyper-connectivity from the frontal seed regions in the Veterans with a history of mTBI relative to the deployed control group. Further, within the mTBI group, but not the control group, better performance on the ACT was associated with increased functional connectivity to multiple brain regions, including cerebellar components of the working memory network. These results were present after controlling for age, PTSD symptoms, and estimated premorbid IQ, and suggest that long-term alterations in the functional connectivity of the working memory network following blast-related mTBI may reflect a compensatory change that contributes to intact performance on an objective measure of working memory.

Altered orbitofrontal activation in preterm-born young adolescents during performance of a reality filtering task

Preterm birth is one of the main causes for neurodevelopmental problems, and has been associated with a wide range of impairments in cognitive functions including executive functions and memory. One of the factors contributing to these adverse outcomes is the intrinsic vulnerability of the premature brain. Neuroimaging studies have highlighted structural and functional alterations in several brain regions in preterm individuals across lifetime. The orbitofrontal cortex (OFC) is crucial for a multitude of complex and adaptive behaviours, and its structure is particularly affected by premature birth. Nevertheless, studies on the functional impact of prematurity on the OFC are still missing. Orbitofrontal Reality filtering (ORFi) refers to the ability to distinguish if a thought is relevant to present reality or not. It can be tested using a continuous recognition task and is mediated by the OFC in adults and typically developing young adolescents. Therefore, the ORFi task was used to investigate whether OFC functioning is affected by prematurity. We compared the neural correlates of ORFi in 35 young adolescents born preterm (below 32 weeks of gestation) and aged 10 to 14 years with 25 full term-born controls. Our findings indicate that OFC activation was required only in the full-term group, whereas preterm young adolescents did not involve OFC in processing the ORFi task, despite being able to correctly perform it.

Reduced Repetition Suppression in Aging is Driven by Tau-Related Hyperactivity in Medial Temporal Lobe

Tau deposition begins in the medial temporal lobe (MTL) in aging and Alzheimer's disease (AD), and MTL neural dysfunction is commonly observed in these groups. However, the association between tau and MTL neural activity has not been fully characterized. We investigated the effects of tau on repetition suppression, the reduction of activity for repeated stimulus presentations compared to novel stimuli. We used task-based functional MRI (fMRI) to assess MTL subregional activity in 21 young adults (YA) and 45 cognitively normal human older adults (OA; total sample: 37 females, 29 males). AD pathology was measured with position emission tomography (PET), using ¹⁸F-Flortaucipir for tau and ¹¹C-Pittsburgh compound B (PiB) for amyloid-β (Aβ). The MTL was segmented into six subregions using high-resolution structural images. We compared the effects of low tau pathology, restricted to entorhinal cortex and hippocampus (Tau- OA), to high tau pathology, also occurring in temporal and limbic regions (Tau+ OA). Low levels of tau (Tau- OA vs YA) were associated with reduced repetition suppression activity specifically in anterolateral entorhinal cortex (alEC) and hippocampus, the first regions to accumulate tau. High tau pathology (Tau+ vs Tau- OA) was associated with widespread reductions in repetition suppression across MTL. Further analyses indicated that reduced repetition suppression was driven by hyperactivity to repeated stimuli, rather than decreased activity to novel stimuli. Increased activation was associated with entorhinal tau, but not Aβ. These findings reveal a link between tau deposition and neural dysfunction in MTL, in which tau-related hyperactivity prevents deactivation to repeated stimuli, leading to reduced repetition suppression.SIGNIFICANCE STATEMENT Abnormal neural activity occurs in the medial temporal lobe (MTL) in aging and Alzheimer's disease (AD). Because tau pathology first deposits in the MTL in aging, this altered activity may be due to local tau pathology, and distinct MTL subregions may be differentially vulnerable. We demonstrate that in older adults (OAs) with low tau pathology, there are focal alterations in activity in MTL subregions that first develop tau pathology, while OAs with high tau pathology have aberrant activity throughout MTL. Tau was associated with hyperactivity to repeated stimulus presentations, leading to reduced repetition suppression, the discrimination between novel and repeated stimuli. Our data suggest that tau deposition is related to abnormal activity in MTL before the onset of cognitive decline.

Systematically disrupted functional gradient of the cortical connectome in generalized epilepsy: Initial discovery and independent sample replication

Genetic generalized epilepsy is a network disorder typically involving distributed areas identified by classical neuroanatomy. However, the finer topological relationships in terms of continuous spatial arrangement between these systems are still ambiguous. Connectome gradients provide the topological representations of human macroscale hierarchy in an abstract low-dimensional space by embedding the functional connectome into a set of axes. Leveraging connectome gradients, we systematically scrutinized abnormalities of functional connectome gradient in patients with genetic generalized epilepsy with tonic-clonic seizure (GGE-GTCS, n = 78) compared to healthy controls (HC, n = 85), and further examined the reproducibility across multiple processing configurations and in an independent validation sample (patients with GGE-GTCS, n = 28; HC, n = 31). Our findings demonstrated an extended principal gradient at different spatial scales, network-level and vertex-level, in patients with GGE-GTCS. We found consistent results across processing parameters and in validation sample. The extended principal gradient revealed the excessive functional segregation between unimodal and transmodal systems associated with duration of epilepsy and age at seizure onset in patients. Furthermore, the connectivity profile of regions with abnormal principal gradients verified the disrupted functional hierarchy revealed by gradients. Together, our findings provided a novel view of functional system hierarchy alterations, which facilitated a continuous spatial arrangement of macroscale networks, to increase our understanding of the functional connectome hierarchy in generalized epilepsy.

Identification of common neural substrates with connectomic abnormalities in four major psychiatric disorders: A connectome-wide association study

Background

Recent imaging studies of large datasets suggested that psychiatric disorders have common biological substrates. This study aimed to identify all the common neural substrates with connectomic abnormalities across four major psychiatric disorders by using the data-driven connectome-wide association method of multivariate distance matrix regression (MDMR).

Methods

This study analyzed a resting functional magnetic resonance imaging dataset of 100 patients with schizophrenia, 100 patients with bipolar I disorder, 100 patients with bipolar II disorder, 100 patients with major depressive disorder, and 100 healthy controls (HCs). We calculated a voxel-wise 4,330 × 4,330 matrix of whole-brain functional connectivity (FC) with 8-mm isotropic resolution for each participant and then performed MDMR to identify structures where the overall multivariate pattern of FC was significantly different between each patient group and the HC group. A conjunction analysis was performed to identify common neural regions with FC abnormalities across these four psychiatric disorders.

Results

The conjunction of the MDMR maps revealed that the four groups of patients shared connectomic abnormalities in distributed cortical and subcortical structures, which included bilateral thalamus, cerebellum, frontal pole, supramarginal gyrus, postcentral gyrus, lingual gyrus, lateral occipital cortex, and parahippocampus. The follow-up analysis based on pair-wise FC of these regions demonstrated that these psychiatric disorders also shared similar patterns of FC abnormalities characterized by sensory/subcortical hyperconnectivity, association/subcortical hypoconnectivity, and sensory/association hyperconnectivity.

Conclusions

These findings suggest that major psychiatric disorders share common connectomic abnormalities in distributed cortical and subcortical regions and provide crucial support for the common network hypothesis of major psychiatric disorders.

A multi-scale cortical wiring space links cellular architecture and functional dynamics in the human brain

The vast net of fibres within and underneath the cortex is optimised to support the convergence of different levels of brain organisation. Here, we propose a novel coordinate system of the human cortex based on an advanced model of its connectivity. Our approach is inspired by seminal, but so far largely neglected models of cortico-cortical wiring established by postmortem anatomical studies and capitalises on cutting-edge in vivo neuroimaging and machine learning. The new model expands the currently prevailing diffusion magnetic resonance imaging (MRI) tractography approach by incorporation of additional features of cortical microstructure and cortico-cortical proximity. Studying several datasets and different parcellation schemes, we could show that our coordinate system robustly recapitulates established sensory-limbic and anterior-posterior dimensions of brain organisation. A series of validation experiments showed that the new wiring space reflects cortical microcircuit features (including pyramidal neuron depth and glial expression) and allowed for competitive simulations of functional connectivity and dynamics based on resting-state functional magnetic resonance imaging (rs-fMRI) and human intracranial electroencephalography (EEG) coherence. Our results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation. Our evaluations demonstrate the cortical wiring space bridges across scales of neural organisation and can be easily translated to single individuals.

Neural correlates of working memory training: Evidence for plasticity in older adults

Brain activity typically increases with increasing working memory (WM) load, regardless of age, before reaching an apparent ceiling. However, older adults exhibit greater brain activity and reach ceiling at lower loads than younger adults, possibly reflecting compensation at lower loads and dysfunction at higher loads. We hypothesized that WM training would bolster neural efficiency, such that the activation peak would shift towards higher memory loads after training. Pre-training, older adults showed greater recruitment of the WM network than younger adults across all loads, with decline at the highest load. Ten days of adaptive training on a verbal WM task improved performance and led to greater brain responsiveness at higher loads for both groups. For older adults the activation peak shifted rightward towards higher loads. Finally, training increased task-related functional connectivity in older adults, both within the WM network and between this task-positive network and the task-negative/default-mode network. These results provide new evidence for functional plasticity with training in older adults and identify a potential signature of improvement at the neural level.

Earliest amyloid and tau deposition modulate the influence of limbic networks during closed-loop hippocampal downregulation

Research into hippocampal self-regulation abilities may help determine the clinical significance of hippocampal hyperactivity throughout the pathophysiological continuum of Alzheimer's disease. In this study, we aimed to identify the effects of amyloid-β peptide 42 (amyloid-β42) and phosphorylated tau on the patterns of functional connectomics involved in hippocampal downregulation. We identified 48 cognitively unimpaired participants (22 with elevated CSF amyloid-β peptide 42 levels, 15 with elevated CSF phosphorylated tau levels, mean age of 62.705 ± 4.628 years), from the population-based 'Alzheimer's and Families' study, with baseline MRI, CSF biomarkers, APOE genotyping and neuropsychological evaluation. We developed a closed-loop, real-time functional MRI neurofeedback task with virtual reality and tailored it for training downregulation of hippocampal subfield cornu ammonis 1 (CA1). Neurofeedback performance score, cognitive reserve score, hippocampal volume, number of apolipoprotein ε4 alleles and sex were controlled for as confounds in all cross-sectional analyses. First, using voxel-wise multiple regression analysis and controlling for CSF biomarkers, we identified the effect of healthy ageing on eigenvector centrality, a measure of each voxel's overall influence based on iterative whole-brain connectomics, during hippocampal CA1 downregulation. Then, controlling for age, we identified the effects of abnormal CSF amyloid-β42 and phosphorylated tau levels on eigenvector centrality during hippocampal CA1 downregulation. Across subjects, our main findings during hippocampal downregulation were: (i) in the absence of abnormal biomarkers, age correlated with eigenvector centrality negatively in the insula and midcingulate cortex, and positively in the inferior temporal gyrus; (ii) abnormal CSF amyloid-β42 (<1098) correlated negatively with eigenvector centrality in the anterior cingulate cortex and primary motor cortex; and (iii) abnormal CSF phosphorylated tau levels (>19.2) correlated with eigenvector centrality positively in the ventral striatum, anterior cingulate and somatosensory cortex, and negatively in the precuneus and orbitofrontal cortex. During resting state functional MRI, similar eigenvector centrality patterns in the cingulate had previously been associated to CSF biomarkers in mild cognitive impairment and dementia patients. Using the developed closed-loop paradigm, we observed such patterns, which are characteristic of advanced disease stages, during a much earlier presymptomatic phase. In the absence of CSF biomarkers, our non-invasive, interactive, adaptive and gamified neuroimaging procedure may provide important information for clinical prognosis and monitoring of therapeutic efficacy. We have released the developed paradigm and analysis pipeline as open-source software to facilitate replication studies.

Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR

Independent Component Analysis-based Automatic Removal of Motion Artifacts (ICA-AROMA; Pruim et al., 2015) is a robust approach to remove brain activity related to head motion within functional magnetic resonance imaging (fMRI) datasets. However, ICA-AROMA requires command line implementation and customized code to batch process large datasets. We developed a cross-platform, open-source graphical user Interface for Batch processing fMRI datasets using ICA-AROMA (INFOBAR). INFOBAR allows a user to search directories, identify appropriate datasets, and batch execute ICA-AROMA. INFOBAR also has additional data processing options and visualization features to support all researchers interested in mitigating head motion artifact in post-processing using ICA-AROMA.

Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy

Drug-resistant focal epilepsy is a large-scale brain networks disorder characterized by altered spatiotemporal patterns of functional connectivity (FC), even during interictal resting state (RS). Although RS-FC-based metrics can detect these changes, results from RS functional magnetic resonance imaging (RS-fMRI) studies are unclear and difficult to interpret, and the underlying dynamical mechanisms are still largely unknown. To better capture the RS dynamics, we phenomenologically extended the neural mass model of partial seizures, the Epileptor, by including two neuron subpopulations of epileptogenic and nonepileptogenic type, making it capable of producing physiological oscillations in addition to the epileptiform activity. Using the neuroinformatics platform The Virtual Brain, we reconstructed 14 epileptic and 5 healthy human (of either sex) brain network models (BNMs), based on individual anatomical connectivity and clinically defined epileptogenic heatmaps. Through systematic parameter exploration and fitting to neuroimaging data, we demonstrated that epileptic brains during interictal RS are associated with lower global excitability induced by a shift in the working point of the model, indicating that epileptic brains operate closer to a stable equilibrium point than healthy brains. Moreover, we showed that functional networks are unaffected by interictal spikes, corroborating previous experimental findings; additionally, we observed higher excitability in epileptogenic regions, in agreement with the data. We shed light on new dynamical mechanisms responsible for altered RS-FC in epilepsy, involving the following two key factors: (1) a shift of excitability of the whole brain leading to increased stability; and (2) a locally increased excitability in the epileptogenic regions supporting the mixture of hyperconnectivity and hypoconnectivity in these areas.

SIGNIFICANCE STATEMENT Advances in functional neuroimaging provide compelling evidence for epilepsy-related brain network alterations, even during the interictal resting state (RS). However, the dynamical mechanisms underlying these changes are still elusive. To identify local and network processes behind the RS-functional connectivity (FC) spatiotemporal patterns, we systematically manipulated the local excitability and the global coupling in the virtual human epileptic patient brain network models (BNMs), complemented by the analysis of the impact of interictal spikes and fitting to the neuroimaging data. Our results suggest that a global shift of the dynamic working point of the brain model, coupled with locally hyperexcitable node dynamics of the epileptogenic networks, provides a mechanistic explanation of the epileptic processes during the interictal RS period. These, in turn, are associated with the changes in FC.

Activity or connectivity? A randomized controlled feasibility study evaluating neurofeedback training in Huntington's disease

Non-invasive methods, such as neurofeedback training, could support cognitive symptom management in Huntington’s disease by targeting brain regions whose function is impaired. The aim of our single-blind, sham-controlled study was to collect rigorous evidence regarding the feasibility of neurofeedback training in Huntington’s disease by examining two different methods, activity and connectivity real-time functional MRI neurofeedback training. Thirty-two Huntington’s disease gene-carriers completed 16 runs of neurofeedback training, using an optimized real-time functional MRI protocol. Participants were randomized into four groups, two treatment groups, one receiving neurofeedback derived from the activity of the supplementary motor area, and another receiving neurofeedback based on the correlation of supplementary motor area and left striatum activity (connectivity neurofeedback training), and two sham control groups, matched to each of the treatment groups. We examined differences between the groups during neurofeedback training sessions and after training at follow-up sessions. Transfer of training was measured by measuring the participants’ ability to upregulate neurofeedback training target levels without feedback (near transfer), as well as by examining change in objective, a priori defined, behavioural measures of cognitive and psychomotor function (far transfer) before and at 2 months after training. We found that the treatment group had significantly higher neurofeedback training target levels during the training sessions compared to the control group. However, we did not find robust evidence of better transfer in the treatment group compared to controls, or a difference between the two neurofeedback training methods. We also did not find evidence in support of a relationship between change in cognitive and psychomotor function and learning success. We conclude that although there is evidence that neurofeedback training can be used to guide participants to regulate the activity and connectivity of specific regions in the brain, evidence regarding transfer of learning and clinical benefit was not robust.

Get real: Orbitofrontal cortex mediates the ability to sense reality in early adolescents

INTRODUCTION

Orbitofrontal reality filtering (ORFi) is a memory mechanism that distinguishes whether a thought is relevant to present reality or not. In adults, it is mediated by the orbitofrontal cortex (OFC). This region is still not fully developed in preteenagers, but ORFi is already active from age 7. Here, we probe the neural correlates of ORFi in early adolescents, hypothesizing that OFC mediates the sense of reality in this population.

METHODS

Functional magnetic resonance images (fMRI) were acquired in 22 early adolescents during a task composed of two runs: run 1 measuring recognition capacity; run 2 measuring ORFi; each containing two types of images (conditions): distractors (D: images seen for the first time in the current run) and targets (T: images seen for the second time in the current run). Group region of interest (ROI) analysis was performed in a flexible factorial design with two factors (run and condition) using SPM12.

RESULTS

We found significant main effects for the experimental run and condition. The bilateral OFC activation was higher during ORFi than during the first run. Additionally, the OFC was more active while processing distractors than targets.

CONCLUSION

These results confirm, for the first time, the role of OFC in reality filtering in early adolescents.

Prospective motion correction of fMRI: Improving the quality of resting state data affected by large head motion

The quality of functional MRI (fMRI) data is affected by head motion. It has been shown that fMRI data quality can be improved by prospectively updating the gradients and radio-frequency pulses in response to head motion during image acquisition by using an MR-compatible optical tracking system (prospective motion correction, or PMC). Recent studies showed that PMC improves the temporal Signal to Noise Ratio (tSNR) of resting state fMRI data (rs-fMRI) acquired from subjects not moving intentionally. Besides that, the time courses of Independent Components (ICs), resulting from Independent Component Analysis (ICA), were found to present significant temporal correlation with the motion parameters recorded by the camera. However, the benefits of applying PMC for improving the quality of rs-fMRI acquired under large head movements and its effects on resting state networks (RSN) and connectivity matrices are still unknown. In this study, subjects were instructed to cross their legs at will while rs-fMRI data with and without PMC were acquired, which generated head motion velocities ranging from 4 to 30 ​mm/s. We also acquired fMRI data without intentional motion. Independent component analysis of rs-fMRI was performed to evaluate IC maps and time courses of RSNs. We also calculated the temporal correlation among different brain regions and generated connectivity matrices for the different motion and PMC conditions. In our results we verified that the crossing leg movements reduced the tSNR of sessions without and with PMC by 45 and 20%, respectively, when compared to sessions without intentional movements. We have verified an interaction between head motion speed and PMC status, showing stronger attenuation of tSNR for acquisitions without PMC than for those with PMC. Additionally, the spatial definition of major RSNs, such as default mode, visual, left and right central executive networks, was improved when PMC was enabled. Furthermore, motion altered IC-time courses by decreasing power at low frequencies and increasing power at higher frequencies (typically associated with artefacts). PMC partially reversed these alterations of the power spectra. Finally, we showed that PMC provides temporal correlation matrices for data acquired under motion conditions more comparable to those obtained by fMRI sessions where subjects were instructed not to move.

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

A rapidly growing number of studies on autism spectrum disorder (ASD) have used resting‐state fMRI to identify alterations of functional connectivity, with the hope of identifying clinical biomarkers or underlying neural mechanisms. However, results have been largely inconsistent across studies, and there remains a pressing need to determine the primary factors influencing replicability. Here, we used resting‐state fMRI data from the Autism Brain Imaging Data Exchange to investigate two potential factors: denoising strategy and data site (which differ in terms of sample, data acquisition, etc.). We examined the similarity of both group‐averaged functional connectomes and group‐level differences (ASD vs. control) across 33 denoising pipelines and four independently‐acquired datasets. The group‐averaged connectomes were highly consistent across pipelines (r = 0.92 ± 0.06) and sites (r = 0.88 ± 0.02). However, the group differences, while still consistent within site across pipelines (r = 0.76 ± 0.12), were highly inconsistent across sites regardless of choice of denoising strategies (r = 0.07 ± 0.04), suggesting lack of replication may be strongly influenced by site and/or cohort differences. Across‐site similarity remained low even when considering the data at a large‐scale network level or when considering only the most significant edges. We further show through an extensive literature survey that the parameters chosen in the current study (i.e., sample size, age range, preprocessing methods) are quite representative of the published literature. These results highlight the importance of examining replicability in future studies of ASD, and, more generally, call for extra caution when interpreting alterations in functional connectivity across groups of individuals.

Testosterone effects on functional amygdala lateralization: A study in adolescent transgender boys and cisgender boys and girls

The influence of testosterone on the development of human brain lateralization has been subject of debate for a long time, partly because studies investigating this are necessarily mostly correlational. In the present study we used a quasi-experimental approach by assessing functional brain lateralization in trans boys (female sex assigned at birth, diagnosed with Gender Dysphoria, n = 21) before and after testosterone treatment, and compared these results to the functional lateralization of age-matched control groups of cisgender boys (n = 20) and girls (n = 21) around 16 years of age. The lateralization index of the amygdala was determined with functional magnetic resonance imaging (fMRI) during an emotional face matching task with angry and fearful faces, as the literature indicates that boys show more activation in the right amygdala than girls during the perception of emotional faces. As expected, the lateralization index in trans boys shifted towards the right amygdala after testosterone treatment, and the cumulative dose of testosterone treatment correlated significantly with amygdala lateralization after treatment. However, we did not find any significant group differences in lateralization and endogenous testosterone concentrations predicted rightward amygdala lateralization only in the cis boys, but not in cis girls or trans boys. These inconsistencies may be due to sex differences in sensitivity to testosterone or its metabolites, which would be a worthwhile course for future studies.