Consistency and functional specialization in the default mode brain network

Brain extended and closed forms glutathione levels decrease with age and extended glutathione is associated with visuospatial memory

During aging, the brain is subject to greater oxidative stress (OS), which is thought to play a critical role in cognitive impairment. Glutathione (GSH), as a major antioxidant in the brain, can be used to combat OS. However, how brain GSH levels vary with age and their associations with cognitive function is unclear. In this study, we combined point-resolved spectroscopy and edited spectroscopy sequences to investigate extended and closed forms GSH levels in the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and occipital cortex (OC) of 276 healthy participants (extended form, 166 females, age range 20-70 years) and 15 healthy participants (closed form, 7 females, age range 26-56 years), and examined their relationships with age and cognitive function. The results revealed decreased extended form GSH levels with age in the PCC among 276 participants. Notably, the timecourse of extended form GSH level changes in the PCC and ACC differed between males and females. Additionally, positive correlations were observed between extended form GSH levels in the PCC and OC and visuospatial memory. Additionally, a decreased trend of closed form GSH levels with age was also observed in the PCC among 15 participants. Taken together, these findings enhance our understanding of the brain both closed and extended form GSH time course during normal aging and associations with sex and memory, which is an essential first step for understanding the neurochemical underpinnings of healthy aging.

Comparative analysis of resting-state EEG functional connectivity in depression and obsessive-compulsive disorder

Major depressive disorder (MDD) and obsessive-compulsive disorder (OCD) are psychiatric disorders that often co-occur. We aimed to investigate whether their high comorbidity could be traced not only by clinical manifestations, but also at the level of functional brain activity. In this paper, we examined the differences in functional connectivity (FC) at the whole-brain level and within the default mode network (DMN). Resting-state EEG was obtained from 43 controls, 26 OCD patients, and 34 MDD patients. FC was analyzed between 68 cortical sources, and between-group differences in the 4-30 Hz range were assessed via the Network Based Statistic method. The strength of DMN intra-connectivity was compared between groups in the theta, alpha and beta frequency bands. A cluster of 67 connections distinguished the OCD, MDD and control groups. The majority of the connections, 8 of which correlated with depressive symptom severity, were found to be weaker in the clinical groups. Only 3 connections differed between the clinical groups, and one of them correlated with OCD severity. The DMN strength was reduced in the clinical groups in the alpha and beta bands. It can be concluded that the high comorbidity of OCD and MDD can be traced at the level of FC.

Cell-type-specific optogenetic fMRI on basal forebrain reveals functional network basis of behavioral preference

The basal forebrain (BF) is a complex structure that plays key roles in regulating various brain functions. However, it remains unclear how cholinergic and non-cholinergic BF neurons modulate large-scale functional networks and their relevance in intrinsic and extrinsic behaviors. With an optimized awake mouse optogenetic fMRI approach, we revealed that optogenetic stimulation of four BF neuron types evoked distinct cell-type-specific whole-brain BOLD activations, which could be attributed to BF-originated low-dimensional structural networks. Additionally, optogenetic activation of VGLUT2, ChAT, and PV neurons in the BF modulated the preference for locomotion, exploration, and grooming, respectively. Furthermore, we uncovered the functional network basis of the above BF-modulated behavioral preference through a decoding model linking the BF-modulated BOLD activation, low-dimensional structural networks, and behavioral preference. To summarize, we decoded the functional network basis of differential behavioral preferences with cell-type-specific optogenetic fMRI on the BF and provided an avenue for investigating mouse behaviors from a whole-brain view.

Resting-state functional network connectivity underlying conscientiousness in school-aged children

Conscientiousness is a personality trait that matures from early childhood to late adolescence, yet little is known about its underlying brain mechanisms during this period. To investigate this, our study examined the resting-state functional network connectivity (rsFNC) of 69 school-aged children (mean age = 10.12 years, range = 9-12) using a whole-brain region-of-interest (ROI) based analysis, based on functional magnetic resonance imaging (fMRI). The results indicated a positive association between conscientiousness and the rsFNC between the fronto-parietal network (FPN) and two brain networks: the somatosensory motor-hand network (SMHN) and the auditory network (AN). However, conscientiousness was negatively associated with the rsFNC between FPN and two other networks: the salience network (SN); the default mode network (DMN). Moreover, our results suggest that the FPN may play a hub role in the neural performance of children's conscientiousness. Intrinsic brain networks, particularly those involved in higher-order cognitive functions, impact children's conscientiousness. Therefore, FPN plays an important role in the development of children's personality, providing insight into the neural mechanisms underlying children's personality.

Neural substrates of marriage on self-parents processing and the association with a parents-oriented perspective shift in a collectivistic culture

Relationship with parents is a special bond that shapes self-other representations and have an impact on adult-child's marriage, especially in the early stages of marriage. This study sought to investigate the neural mechanisms underlying self-parents processing as well as their relationship with marriage. Seventy-eight premarital Korean participants were scanned in functional MRI while evaluating traits of the self and parents. Then, 21 of them returned after being married to engage in the identical task three years later. The precuneus and temporoparietal junction were identified to activate stronger for parents than self at both marital statuses. The dorsal anterior cingulate cortex, posterior cingulate cortex, parietal operculum, and caudate activated more for self than parents before marriage, but their activities changed during marriage. The activation increase of the parietal operculum between marital statuses in the parents condition was negatively correlated with the level of marital dissatisfaction, and this association only appeared among participants with a child. Self-parents processing may recruit brain regions involved in autobiographical memory and self-other distinction, and marriage has an impact on the way individuals process rewards and multimodal sensory information during this processing. Marriage may lead to changes in brain function that affect the processing of emotions toward parents and a more parents-oriented perspective shift in collectivistic societies.

Brain Functional Connectivity and Anatomical Features as Predictors of Cognitive Behavioral Therapy Outcome for Anxiety in Youths

Background

Because pediatric anxiety disorders precede the onset of many other problems, successful prediction of response to the first-line treatment, cognitive-behavioral therapy (CBT), could have major impact. However, existing clinical models are weakly predictive. The current study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT anxiety symptoms.

Methods

Two datasets were studied: (A) one consisted of n=54 subjects with an anxiety diagnosis, who received 12 weeks of CBT, and (B) one consisted of n=15 subjects treated for 8 weeks. Connectome Predictive Modeling (CPM) was used to predict treatment response, as assessed with the PARS; additionally we investigated models using anatomical features, instead of functional connectivity. The main analysis included network edges positively correlated with treatment outcome, and age, sex, and baseline anxiety severity as predictors. Results from alternative models and analyses also are presented. Model assessments utilized 1000 bootstraps, resulting in a 95% CI for R2, r and mean absolute error (MAE).

Outcomes

The main model showed a mean absolute error of approximately 3.5 (95%CI: [3.1-3.8]) points a R2 of 0.08 [-0.14 - 0.26] and r of 0.38 [0.24 - 0.511]. When testing this model in the left-out sample (B) the results were similar, with a MAE of 3.4 [2.8 - 4.7], R2-0.65 [-2.29 - 0.16] and r of 0.4 [0.24 - 0.54]. The anatomical metrics showed a similar pattern, where models rendered overall low R2.

Interpretation

The analysis showed that models based on earlier promising results failed to predict clinical outcomes. Despite the small sample size, the current study does not support extensive use of CPM to predict outcome in pediatric anxiety.

Design and Implementation of a Brief Digital Mindfulness and Compassion Training App for Health Care Professionals: Cluster Randomized Controlled Trial

BACKGROUND

Several studies show that intense work schedules make health care professionals particularly vulnerable to emotional exhaustion and burnout.

OBJECTIVE

In this scenario, promoting self-compassion and mindfulness may be beneficial for well-being. Notably, scalable, digital app-based methods may have the potential to enhance self-compassion and mindfulness in health care professionals.

METHODS

In this study, we designed and implemented a scalable, digital app-based, brief mindfulness and compassion training program called "WellMind" for health care professionals. A total of 22 adult participants completed up to 60 sessions of WellMind training, 5-10 minutes in duration each, over 3 months. Participants completed behavioral assessments measuring self-compassion and mindfulness at baseline (preintervention), 3 months (postintervention), and 6 months (follow-up). In order to control for practice effects on the repeat assessments and calculate effect sizes, we also studied a no-contact control group of 21 health care professionals who only completed the repeated assessments but were not provided any training. Additionally, we evaluated pre- and postintervention neural activity in core brain networks using electroencephalography source imaging as an objective neurophysiological training outcome.

RESULTS

Findings showed a post- versus preintervention increase in self-compassion (Cohen d=0.57; P=.007) and state-mindfulness (d=0.52; P=.02) only in the WellMind training group, with improvements in self-compassion sustained at follow-up (d=0.8; P=.01). Additionally, WellMind training durations correlated with the magnitude of improvement in self-compassion across human participants (ρ=0.52; P=.01). Training-related neurophysiological results revealed plasticity specific to the default mode network (DMN) that is implicated in mind-wandering and rumination, with DMN network suppression selectively observed at the postintervention time point in the WellMind group (d=-0.87; P=.03). We also found that improvement in self-compassion was directly related to the extent of DMN suppression (ρ=-0.368; P=.04).

CONCLUSIONS

Overall, promising behavioral and neurophysiological findings from this first study demonstrate the benefits of brief digital mindfulness and compassion training for health care professionals and compel the scale-up of the digital intervention.

TRIAL REGISTRATION

Trial Registration: International Standard Randomized Controlled Trial Number Registry ISRCTN94766568, https://www.isrctn.com/ISRCTN94766568.

Brain Networks With Modified Connectivity in Patients With Neuropathic Pain and Spinal Cord Injury

Background. Neuropathic pain (NP) following spinal cord injury (SCI) affects the quality of life of almost 40% of the injured population. The modified brain connectivity was reported under different NP conditions. Therefore, brain connectivity was studied in the SCI population with and without NP with the aim to identify networks that are altered due to injury, pain, or both. Methods. The study cohort is classified into 3 groups, SCI patients with NP, SCI patients without NP, and able-bodied. EEG of each participant was recorded during motor imagery (MI) of paralyzed and painful, and nonparalyzed and nonpainful limbs. Phased locked value was calculated using Hilbert transform to study altered functional connectivity between different regions. Results. The posterior region connectivity with frontal, fronto-central, and temporal regions is strongly decreased mainly during MI of dominant upper limb (nonparalyzed and nonpainful limbs) in SCI no pain group. This modified connectivity is prominent in the alpha and high-frequency bands (beta and gamma). Moreover, oscillatory modified global connectivity is observed in the pain group during MI of painful and paralyzed limb which is more evident between fronto-posterior, frontocentral-posterior, and within posterior and within frontal regions in the theta and SMR frequency bands. Cluster coefficient and local efficiency values are reduced in patients with no reported pain group while increased in the PWP group. Conclusion. The altered theta band connectivity found in the fronto-parietal network along with a global increase in local efficiency is a consequence of pain only, while altered connectivity in the beta and gamma bands along with a decrease in cluster coefficient values observed in the sensory-motor network is dominantly a consequence of injury only. The outcomes of this study may be used as a potential diagnostic biomarker for the NP. Further, the expected insight holds great clinical relevance in the design of neurofeedback-based neurorehabilitation and connectivity-based brain-computer interfaces for SCI patients.

A hybrid spatiotemporal deep belief network and sparse representation-based framework reveals multilevel core functional components in decoding multitask fMRI signals

Decoding human brain activity on various task-based functional brain imaging data is of great significance for uncovering the functioning mechanism of the human mind. Currently, most feature extraction model-based methods for brain state decoding are shallow machine learning models, which may struggle to capture complex and precise spatiotemporal patterns of brain activity from the highly noisy fMRI raw data. Moreover, although decoding models based on deep learning methods benefit from their multilayer structure that could extract spatiotemporal features at multiscale, the relatively large populations of fMRI datasets are indispensable, and the explainability of their results is elusive. To address the above problems, we proposed a computational framework based on hybrid spatiotemporal deep belief network and sparse representations to differentiate multitask fMRI (tfMRI) signals. Using a relatively small cohort of tfMRI data as a test bed, our framework can achieve an average classification accuracy of 97.86% and define the multilevel temporal and spatial patterns of multiple cognitive tasks. Intriguingly, our model can characterize the key components for differentiating the multitask fMRI signals. Overall, the proposed framework can identify the interpretable and discriminative fMRI composition patterns at multiple scales, offering an effective methodology for basic neuroscience and clinical research with relatively small cohorts.

The Study of Ketamine for Youth Depression (SKY-D): study protocol for a randomised controlled trial of low-dose ketamine for young people with major depressive disorder

BACKGROUND

Existing treatments for young people with severe depression have limited effectiveness. The aim of the Study of Ketamine for Youth Depression (SKY-D) trial is to determine whether a 4-week course of low-dose subcutaneous ketamine is an effective adjunct to treatment-as-usual in young people with major depressive disorder (MDD).

METHODS

SKY-D is a double-masked, randomised controlled trial funded by the Australian Government's National Health and Medical Research Council (NHMRC). Participants aged between 16 and 25 years (inclusive) with moderate-to-severe MDD will be randomised to receive either low-dose ketamine (intervention) or midazolam (active control) via subcutaneous injection once per week for 4 weeks. The primary outcome is change in depressive symptoms on the Montgomery-Åsberg Depression Rating Scale (MADRS) after 4 weeks of treatment. Further follow-up assessment will occur at 8 and 26 weeks from treatment commencement to determine whether treatment effects are sustained and to investigate safety outcomes.

DISCUSSION

Results from this trial will be important in determining whether low-dose subcutaneous ketamine is an effective treatment for young people with moderate-to-severe MDD. This will be the largest randomised trial to investigate the effects of ketamine to treat depression in young people.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry ID: ACTRN12619000683134. Registered on May 7, 2019. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377513 .

When shapes are more than shapes: perceptual, developmental, and neurophysiological basis for attributions of animacy and theory of mind

Among a variety of entities in their environment, what do humans consider alive or animate and how does this attribution of animacy promote development of more abstract levels of mentalizing? By decontextualizing the environment of bodily features, we review how physical movements give rise to perceived animacy in Heider-Simmel style animations. We discuss the developmental course of how perceived animacy shapes our interpretation of the social world, and specifically discuss when and how children transition from perceiving actions as goal-directed to attributing behaviors to unobservable mental states. This transition from a teleological stance, asserting a goal-oriented interpretation to an agent's actions, to a mentalistic stance allows older children to reason about more complex actions guided by hidden beliefs. The acquisition of these more complex cognitive behaviors happens developmentally at the same time neural systems for social cognition are coming online in young children. We review perceptual, developmental, and neural evidence to identify the joint cognitive and neural changes associated with when children begin to mentalize and how this ability is instantiated in the brain.

A distinct intra-individual suppression subnetwork in the brain's default mode network across cognitive tasks

Suppression of the brain's default mode network (DMN) during external goal-directed cognitive tasks has been consistently observed in neuroimaging studies. However, emerging insights suggest the DMN is not a monolithic "task-negative" network but is comprised of subsystems that show functional heterogeneity. Despite considerable research interest, no study has investigated the consistency of DMN activity suppression across multiple cognitive tasks within the same individuals. In this study, 85 healthy 15- to 25-year-olds completed three functional magnetic resonance imaging tasks that were designed to reliably map DMN suppression from a resting baseline. Our findings revealed a distinct suppression subnetwork across the three tasks that comprised traditional DMN and adjacent regions. Specifically, common suppression was observed in the medial prefrontal cortex, the dorsal-to-mid posterior cingulate cortex extending to the precuneus, and the posterior insular cortex and parietal operculum. Further, we found the magnitude of suppression of these regions were significantly correlated within participants across tasks. Overall, our findings indicate that externally oriented cognitive tasks elicit common suppression of a distinct subnetwork of the broader DMN. The consistency to which the DMN is suppressed within individuals suggests a domain-general mechanism that may reflect a stable feature of cognitive function that optimizes external goal-directed behavior.

Methylphenidate Enhances Spontaneous Fluctuations in Reward and Cognitive Control Networks in Children With Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Methylphenidate, a first-line treatment for attention-deficit/hyperactivity disorder (ADHD), is thought to influence dopaminergic neurotransmission in the nucleus accumbens (NAc) and its associated brain circuitry, but this hypothesis has yet to be systematically tested.

METHODS

We conducted a randomized, placebo-controlled, double-blind crossover trial including 27 children with ADHD. Children with ADHD were scanned twice with resting-state functional magnetic resonance imaging under methylphenidate and placebo conditions, along with assessment of sustained attention. We examined spontaneous neural activity in the NAc and the salience, frontoparietal, and default mode networks and their links to behavioral changes. Replicability of methylphenidate effects on spontaneous neural activity was examined in a second independent cohort.

RESULTS

Methylphenidate increased spontaneous neural activity in the NAc and the salience and default mode networks. Methylphenidate-induced changes in spontaneous activity patterns in the default mode network were associated with improvements in intraindividual response variability during a sustained attention task. Critically, despite differences in clinical trial protocols and data acquisition parameters, the NAc and the salience and default mode networks showed replicable patterns of methylphenidate-induced changes in spontaneous activity across two independent cohorts.

CONCLUSIONS

We provide reproducible evidence demonstrating that methylphenidate enhances spontaneous neural activity in NAc and cognitive control networks in children with ADHD, resulting in more stable sustained attention. Our findings identified a novel neural mechanism underlying methylphenidate treatment in ADHD to inform the development of clinically useful biomarkers for evaluating treatment outcomes.

A tripartite view of the posterior cingulate cortex

The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.

Neural Basis of Internal Attention in Adults with Pure and Comorbid ADHD

OBJECTIVE

To examine whether putatively atypical neuronal activity during internal attention in ADHD yields insights into processes underlying emotion dysregulation.

METHODS

We used a word processing paradigm to assess neural activations in adults with ADHD (N = 46) compared to controls (N = 43). We measured effects of valence, applied partial-least squares correlation analysis to assess multivariate brainbehavior relationships and ran subgroup analyses to isolate results driven by pure ADHD (N = 18).

RESULTS

During internal attention, ADHD, compared to controls, have (1) increased activation in the right angular gyrus (rAG), which appears driven by pure, not comorbid, ADHD and (2) diminished activation in the insula and fronto-striatal circuitry. Diminished activations were driven by negatively-valenced internal attention and negatively correlated with increased affective lability within the ADHD group.

CONCLUSION

Internal attention in ADHD is associated with increased rAG activation, possibly reflecting difficulty converging external and internal information, and diminished activation within emotion regulation circuitry.

Transcranial Magnetic Stimulation Improves Executive Functioning through Modulation of Social Cognitive Networks in Patients with Mild Cognitive Impairment: Preliminary Results

(1) Background: Patients with mild cognitive impairment (MCI) often present impairment in executive functions (EFs). This study aimed to investigate the effect of high-frequency repetitive transcranial magnetic stimulation (rTMS) on EFs in patients with MCI. (2) Methods: A prospective trial was conducted on 11 patients with MCI. Participants underwent 25 min of 20 Hz rTMS for ten days on the right temporo-parietal junction (RTPJ) and medial prefrontal cortex (MPFC). Before (T0) and after rTMS treatment (T1), global cognitive profile and EFs were investigated using the Montreal cognitive assessment (MoCA), trial making test (TMT) A and B, and frontal assessment battery (FAB). Depression symptoms were assessed using the geriatric depression scale (GDS). Statistical analysis included Wilcoxon signed-rank test. (3) Results: After treatment, patients showed a significant improvement in the MoCA EFs subtask (T0 vs. T1, p = 0.015) and TMT-B (T0 vs. T1, p = 0.028). Five MCI patients with EF impairment showed full recovery of these deficits. No significant changes in the GDS were observed. (4) Conclusions: rTMS stimulation over the TPJ and MPFC induced significant short-term improvements in EFs in MCI patients. These findings suggest that the TPJ and MPFC may be involved in the attention-executive skills to redirect attention toward behaviorally relevant stimuli.

Vision- and touch-dependent brain correlates of body-related mental processing

In humans, the nature of sensory input influences body-related mental processing. For instance, behavioral differences (e.g., response time) can be found between mental spatial transformations (e.g., mental rotation) of viewed and touched body parts. It can thus be hypothesized that distinct brain activation patterns are associated with such sensory-dependent body-related mental processing. However, direct evidence that the neural correlates of body-related mental processing can be modulated by the nature of the sensory stimuli is still missing. We thus analyzed event-related functional magnetic resonance imaging (fMRI) data from thirty-one healthy participants performing mental rotation of visually- (images) and haptically-presented (plastic) hands. We also dissociated the neural activity related to rotation or task-related performance using models that either regressed out or included the variance associated with response time. Haptically-mediated mental rotation recruited mostly the sensorimotor brain network. Visually-mediated mental rotation led to parieto-occipital activations. In addition, faster mental rotation was associated with sensorimotor activity, while slower mental rotation was associated with parieto-occipital activations. The fMRI results indicated that changing the type of sensory inputs modulates the neural correlates of body-related mental processing. These findings suggest that distinct sensorimotor brain dynamics can be exploited to execute similar tasks depending on the available sensory input. The present study can contribute to a better evaluation of body-related mental processing in experimental and clinical settings.

Default mode and fronto-parietal network associations with IQ development across childhood in autism

Background

Intellectual disability affects approximately one third of individuals with autism spectrum disorder (autism). Yet, a major unresolved neurobiological question is what differentiates autistic individuals with and without intellectual disability. Intelligence quotients (IQs) are highly variable during childhood. We previously identified three subgroups of autistic children with different trajectories of intellectual development from early (2–3½ years) to middle childhood (9–12 years): (a) persistently high: individuals whose IQs remained in the normal range; (b) persistently low: individuals whose IQs remained in the range of intellectual disability (IQ < 70); and (c) changers: individuals whose IQs began in the range of intellectual disability but increased to the normal IQ range. The frontoparietal (FPN) and default mode (DMN) networks have established links to intellectual functioning. Here, we tested whether brain regions within the FPN and DMN differed volumetrically between these IQ trajectory groups in early childhood.

Methods

We conducted multivariate distance matrix regression to examine the brain regions within the FPN (11 regions x 2 hemispheres) and the DMN (12 regions x 2 hemispheres) in 48 persistently high (18 female), 108 persistently low (32 female), and 109 changers (39 female) using structural MRI acquired at baseline. FPN and DMN regions were defined using networks identified in Smith et al. (Proc Natl Acad Sci U S A 106:13040–5, 2009). IQ trajectory groups were defined by IQ measurements from up to three time points spanning early to middle childhood (mean age time 1: 3.2 years; time 2: 5.4 years; time 3: 11.3 years).

Results

The changers group exhibited volumetric differences in the DMN compared to both the persistently low and persistently high groups at time 1. However, the persistently high group did not differ from the persistently low group, suggesting that DMN structure may be an early predictor for change in IQ trajectory. In contrast, the persistently high group exhibited differences in the FPN compared to both the persistently low and changers groups, suggesting differences related more to concurrent IQ and the absence of intellectual disability.

Conclusions

Within autism, volumetric differences of brain regions within the DMN in early childhood may differentiate individuals with persistently low IQ from those with low IQ that improves through childhood. Structural differences in brain networks between these three IQ-based subgroups highlight distinct neural underpinnings of these autism sub-phenotypes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-022-09460-y.

Higher reliability and validity of Wavelet-ALFF of resting-state fMRI: From multicenter database and application to rTMS modulation

Amplitude of low-frequency fluctuation (ALFF) has been widely used for localization of abnormal activity at the single-voxel level in resting-state fMRI (RS-fMRI) studies. However, previous ALFF studies were based on fast Fourier transform (FFT-ALFF). Our recent study found that ALFF based on wavelet transform (Wavelet-ALFF) showed better sensitivity and reproducibility than FFT-ALFF. The current study aimed to test the reliability and validity of Wavelet-ALFF, and apply Wavelet-ALFF to investigate the modulation effect of repetitive transcranial magnetic stimulation (rTMS). The reliability and validity were assessed on multicenter RS-fMRI datasets under eyes closed (EC) and eyes open (EO) conditions (248 healthy participants in total). We then detected the sensitivity of Wavelet-ALFF using a rTMS modulation dataset (24 healthy participants). For each dataset, Wavelet-ALFF based on five mother wavelets (i.e., db2, bior4.4, morl, meyr and sym3) and FFT-ALFF were calculated in the conventional band and five frequency sub-bands. The results showed that the reliability of both inter-scanner and intra-scanner was higher with Wavelet-ALFF than with FFT-ALFF across multiple frequency bands, especially db2-ALFF in the higher frequency band slow-2 (0.1992-0.25 Hz). In terms of validity, the multicenter ECEO datasets showed that the effect sizes of Wavelet-ALFF with all mother wavelets (especially for db2-ALFF) were larger than those of FFT-ALFF across multiple frequency bands. Furthermore, Wavelet-ALFF detected a larger modulation effect than FFT-ALFF. Collectively, Wavelet db2-ALFF showed the best reliability and validity, suggesting that db2-ALFF may offer a powerful metric for inspecting regional spontaneous brain activities in future studies.

Understanding cognitive control in aging: A brain network perspective

Cognitive control decline is a major manifestation of brain aging that severely impairs the goal-directed abilities of older adults. Magnetic resonance imaging evidence suggests that cognitive control during aging is associated with altered activation in a range of brain regions, including the frontal, parietal, and occipital lobes. However, focusing on specific regions, while ignoring the structural and functional connectivity between regions, may impede an integrated understanding of cognitive control decline in older adults. Here, we discuss the role of aging-related changes in functional segregation, integration, and antagonism among large-scale networks. We highlight that disrupted spontaneous network organization, impaired information co-processing, and enhanced endogenous interference promote cognitive control declines during aging. Additionally, in older adults, severe damage to structural network can weaken functional connectivity and subsequently trigger cognitive control decline, whereas a relatively intact structural network ensures the compensation of functional connectivity to mitigate cognitive control impairment. Thus, we propose that age-related changes in functional networks may be influenced by structural networks in cognitive control in aging (CCA). This review provided an integrative framework to understand the cognitive control decline in aging by viewing the brain as a multimodal networked system.

Distinct population and single-neuron selectivity for executive and episodic processing in human dorsal posterior cingulate

Posterior cingulate cortex (PCC) is an enigmatic region implicated in psychiatric and neurological disease, yet its role in cognition remains unclear. Human studies link PCC to episodic memory and default mode network (DMN), while findings from the non-human primate emphasize executive processes more associated with the cognitive control network (CCN) in humans. We hypothesized this difference reflects an important functional division between dorsal (executive) and ventral (episodic) PCC. To test this, we utilized human intracranial recordings of population and single unit activity targeting dorsal PCC during an alternated executive/episodic processing task. Dorsal PCC population responses were significantly enhanced for executive, compared to episodic, task conditions, consistent with the CCN. Single unit recordings, however, revealed four distinct functional types with unique executive (CCN) or episodic (DMN) response profiles. Our findings provide critical electrophysiological data from human PCC, bridging incongruent views within and across species, furthering our understanding of PCC function.

The neurobiology of Pavlovian safety learning: Towards an acquisition-expression framework

Safety learning creates associations between conditional stimuli and the absence of threat. Studies of human fear conditioning have accumulated evidence for the neural signatures of safety over various paradigms, aligning on several common brain systems. While these systems are often interpreted as underlying safety learning in a generic sense, they may instead reflect the expression of learned safety, pertaining to processes of fear inhibition, positive affect, and memory. Animal models strongly suggest these can be separable from neural circuits implicated in the conditioning process itself (or safety acquisition). While acquisition-expression distinctions are ubiquitous in behavioural science, this lens has not been applied to safety learning, which remains a novel area in the field. In this mini-review, we overview findings from prevalent safety paradigms in humans, and synthesise these with insights from animal models to propose that the neurobiology of safety learning be conceptualised along an acquisition-expression model, with the aim of stimulating richer brain-based characterisations of this important process.

The salience network is activated during self-recognition from both first-person and third-person perspectives

We usually observe ourselves from two perspectives. One is the first-person perspective, which we perceive directly with our own eyes, and the other is the third-person perspective, which we observe ourselves in a mirror or a picture. However, whether the self-recognition associated with these two perspectives has a common or separate neural basis remains unclear. To address this, we used functional magnetic resonance imaging to examine brain activity while participants viewed pretaped video clips of themselves and others engaged in meal preparation taken from first-person and third-person perspectives. We found that the first-person behavioral videos of the participants and others induced greater activation in the premotor-intraparietal region. In contrast, the third-person behavioral videos induced greater activation in the default mode network compared with the first-person videos. Regardless of the perspective, the videos of the participants induced greater activation in the salience network than the videos of others. On the other hand, the videos of others induced greater activation in the precuneus and lingual gyrus than the videos of the participants. These results suggest that the salience network is commonly involved in self-recognition from both perspectives, even though the brain regions involved in action observation for the two perspectives are distinct.

Effects of aging on functional connectivity in a neurodegenerative risk cohort: resting state versus task measurement using near-infrared spectroscopy

Changes in functional brain organization are considered to be particularly sensitive to age-related effects and may precede structural cognitive decline. Recent research focuses on aging processes determined by resting state (RS) functional connectivity (FC), but little is known about differences in FC during RS and cognitive task conditions in elderly participants. The purpose of this study is to compare FC within and between the cognitive control (CCN) and dorsal attention network (DAN) at RS and during a cognitive task using functional near-infrared spectroscopy (fNIRS). In a matched, neurodegenerative high-risk cohort comprising early (n = 98; 50–65 y) and late (n = 98; 65–85 y) elder subjects, FC was measured at RS and during performance of the Trail Making Test (TMT) via fNIRS. Both, under RS and task conditions our results revealed a main effect for age, characterized by reduced FC for late elder subjects within the left inferior frontal gyrus. During performance of the TMT, negative correlations of age and FC were confirmed in various regions of the CCN and DAN. For the whole sample, FC of within-region connections was elevated, while FC between regions was decreased at RS. The results confirm a reorganization of functional brain connectivity with increasing age and cognitive demands.

Tasks activating the default mode network map multiple functional systems

Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.

Brain Network Changes in Lumbar Disc Herniation Induced Chronic Nerve Roots Compression Syndromes

Lumbar disc herniation (LDH) induced nerve compression syndromes have been a prevalent problem with complex neural mechanisms. Changes in distributed brain areas are involved in the occurrence and persistence of syndromes. The present study aimed to investigate the changes of brain functional network in LDH patients with chronic sciatica using graph theory analysis. A total of thirty LDH adults presenting L4 and/or L5 root (s) compression syndromes (LDH group) and thirty age-, sex-, BMI- and education-matched healthy control (HC group) were recruited for functional MRI scan. Whole-brain functional network was constructed for each participant using Pearson's correlation. Global and nodal properties were calculated and compared between two groups, including small-worldness index, clustering coefficient, characteristic path length, degree centrality (DC), betweenness centrality (BC) and nodal efficiency. Both LDH and HC groups showed small-world architecture in the functional network of brain. However, LDH group showed that nodal centralities (DC, BC and nodal efficiency) increased in opercular part of inferior frontal gyrus; and decreased in orbital part of inferior frontal gyrus, lingual cortex and inferior occipital gyrus. The DC and efficiency in the right inferior occipital gyrus were negatively related with the Oswestry Disability Index in LDH group. In conclusion, the LDH-related chronic sciatica syndromes may induce regional brain alterations involving self-referential, emotional responses and pain regulation functions. But the whole-brain small-world architecture was not significantly disturbed. It may provide new insights into LDH patients with radicular symptoms from new perspectives.

Rostral anterior cingulate network effective connectivity in depressed adolescents and associations with treatment response in a randomized controlled trial

The rostral anterior cingulate cortex (rACC) is consistently implicated in the neurobiology of depression. While the functional connectivity of the rACC has been previously associated with treatment response, there is a paucity of work investigating the specific directional interactions underpinning these associations. We compared the fMRI resting-state effective connectivity of 94 young people with major depressive disorder and 91 healthy controls. Following the fMRI scan, patients were randomized to receive cognitive behavioral therapy for 12 weeks, plus either fluoxetine or a placebo. Using spectral dynamic causal modelling, we examined the effective connectivity of the rACC with eight other regions implicated in depression: the left and right anterior insular cortex (AIC), amygdalae, and dorsolateral prefrontal cortex (dlPFC); and in the midline, the subgenual (sgACC) and dorsal anterior cingulate cortex (dACC). Parametric empirical Bayes was used to compare baseline differences between controls and patients and responders and non-responders to treatment. Depressed patients demonstrated greater inhibitory connectivity from the rACC to the dlPFC, AIC, dACC and left amygdala. Moreover, treatment responders illustrated greater inhibitory connectivity from the rACC to dACC, greater excitatory connectivity from the dACC to sgACC and reduced inhibitory connectivity from the sgACC to amygdalae at baseline. The inhibitory hyperconnectivity of the rACC in depressed patients aligns with hypotheses concerning the dominance of the default mode network over other intrinsic brain networks. Surprisingly, treatment responders did not demonstrate connectivity which was more similar to healthy controls, but rather distinct alterations that may have predicated their enhanced treatment response.

Across the adult lifespan the ipsilateral sensorimotor cortex negative BOLD response exhibits decreases in magnitude and spatial extent suggesting declining inhibitory control

Ipsilateral sensorimotor (iSM1) cortex negative BOLD responses (NBR) are observed to unilateral tasks and are thought to reflect a functionally relevant component of sensorimotor inhibition. Evidence suggests that sensorimotor inhibitory mechanisms degrade with age, along with aspects of motor ability and dexterity. However, understanding of age-related changes to NBR is restricted by limited comparisons between young vs old adults groups with relatively small samples sizes. Here we analysed a BOLD fMRI dataset (obtained from the CamCAN repository) of 581 healthy subjects, gender-balanced, sampled from the whole adult lifespan performing a motor response task to an audio-visual stimulus. We aimed to investigate how sensorimotor and default-mode NBR characteristics of magnitude, spatial extent and response shape alter at every decade of the aging process. A linear decrease in iSM1 NBR magnitude was observed across the whole lifespan whereas the contralateral sensorimotor (cSM1) PBR magnitude was unchanged. An age-related decrease in the spatial extent of NBR and an increase in the ipsilateral positive BOLD response (PBR) was observed. This occurred alongside an increasing negative correlation between subject's iSM1 NBR and cSM1 PBR magnitude, reflecting a change in the balance between cortical excitation and inhibition. Conventional GLM analysis, using a canonical haemodynamic response (HR) function, showed disappearance of iSM1 NBR in subjects over 50 years of age. However, a deconvolution analysis showed that the shape of the iSM1 HR altered throughout the lifespan, with delayed time-to-peak and decreased magnitude. The most significant decreases in iSM1 HR magnitude occurred in older age (>60 years) but the first changes in shape and timing occurred as early as 30 years, suggesting possibility of separate mechanisms underlying these alterations. Reanalysis using data-driven HRs for each decade detected significant sensorimotor NBR into late older age, showing the importance of taking changes in HR morphology into account in fMRI aging studies. These results may reflect fMRI measures of the age-related decreases in transcollosal inhibition exerted upon ipsilateral sensorimotor cortex and alterations to the excitatory-inhibitory balance in the sensorimotor network.

Abnormal Cerebrovascular Reactivity and Functional Connectivity Caused by White Matter Hyperintensity Contribute to Cognitive Decline

Aims

This study aimed to investigate the relationships of impaired cerebrovascular reactivity (CVR) and abnormal functional connectivity (FC) with white matter hyperintensity (WMH)-related cognitive decline.

Methods

A total of 233 WMH subjects were recruited and categorized into WMH-I (n = 106), WMH-II (n = 72), and WMH-III (n = 55) groups according to Fazekas visual rating scale. All participants underwent neuropsychological tests and multimodal MRI scans, including 3D-T1, and resting-state functional magnetic resonance imaging (rs-fMRI). The alterations of CVR maps and FC were further explored.

Results

Subjects with a higher WMH burden displayed a lower CVR in the left medial occipital gyrus (MOG). The FC analysis using MOG as a seed revealed that the FC of the left insula, left inferior parietal lobule, and thalamus changed abnormally as WMH aggravated. After adjusting for age, gender, and education years, the serial mediation analysis revealed that periventricular white matter hyperintensity contributes indirectly to poorer Mini-Mental State Examination (MMSE) scores (indirect effect: β = −0.1248, 95% CI: −0.4689, −0188), poorer Montreal Cognitive Assessment (MoCA) (indirect effect: β = −0.1436, 95% CI: −0.4584, −0.0292) scores, and longer trail making tests A (TMT-A) (indirect effect: β = 0.1837, 95% CI: 0.0069, 0.8273) times, specifically due to the lower CVR of the left MOG and the higher FC of the left insula-MOG.

Conclusion

The CVR decline of the left MOG and the abnormal FC of the left insula-MOG attributed to WMH progression were responsible for the poor general cognition (MMSE and MoCA) and information processing speed (TMT-A). The left MOG may act as a connection, which is involved in the processing of cognitive biases by connecting with the left insula-cortical regions in WMH individuals.

Explanatory pragmatism: a context-sensitive framework for explainable medical AI

Explainable artificial intelligence (XAI) is an emerging, multidisciplinary field of research that seeks to develop methods and tools for making AI systems more explainable or interpretable. XAI researchers increasingly recognise explainability as a context-, audience- and purpose-sensitive phenomenon, rather than a single well-defined property that can be directly measured and optimised. However, since there is currently no overarching definition of explainability, this poses a risk of miscommunication between the many different researchers within this multidisciplinary space. This is the problem we seek to address in this paper. We outline a framework, called Explanatory Pragmatism, which we argue has two attractive features. First, it allows us to conceptualise explainability in explicitly context-, audience- and purpose-relative terms, while retaining a unified underlying definition of explainability. Second, it makes visible any normative disagreements that may underpin conflicting claims about explainability regarding the purposes for which explanations are sought. Third, it allows us to distinguish several dimensions of AI explainability. We illustrate this framework by applying it to a case study involving a machine learning model for predicting whether patients suffering disorders of consciousness were likely to recover consciousness.

Modulation of the brain's core-self network by self-appraisal processes

The 'core' regions of the default mode network (DMN) - the medial prefrontal cortex (MPFC), the posterior cingulate cortex (PCC), and inferior parietal lobules (IPL) - show consistent involvement across mental states that involve self-oriented processing. Precisely how these regions interact in support of such processes remains an important unanswered question. In the current functional magnetic resonance imaging (fMRI) study, we examined dynamic interactions of the 'core-self' DMN regions during two forms of self-referential cognition: direct self-appraisal (thinking about oneself) and reflected self-appraisal (thinking about oneself from a third-person perspective). One-hundred and eleven participants completed our dual self-appraisal task during fMRI, and general linear models were used to characterize common and distinct neural responses to these conditions. Informed by these results, we then applied dynamic causal modelling to examine causal interactions among the 'core-self' regions, and how they were specifically modulated under the influence of direct and reflected self-appraisal. As a primary observation, this network modelling revealed a distinct inhibitory influence of the left IPL on the PCC during reflected compared to direct self-appraisal, which was accompanied by evidence of greater activation in both regions during the reflected self-appraisal condition. We suggest that the greater engagement posterior DMN regions during reflected self-appraisal is a function of the higher-order processing needed for this form of self-appraisal, with the left IPL supporting abstract self-related processes including episodic memory retrieval and shifts of perspective. Overall, we show that core DMN regions interact in functionally unique ways in support of self-referential processes, even when these processes are inter-related. Further characterization of DMN functional interactions across self-related mental states is likely to inform a deeper understanding of how this brain network orchestrates the self.

"Would You Allow Your Wife to Dress in a Miniskirt to the Party"? : Batterers Do Not Activate Default Mode Network During Moral Decisions About Intimate Partner Violence

Moral convictions consist of assessments based on perceptions of morality and immorality, of right and wrong. There are people who, based on morality, commit crimes. For instance, social and moral norms based on inequality appear to play an important role in the batterer's behavior to commit violent acts. Research shows that batterers consider themselves to be moral persons, are defenders of their beliefs, and, if necessary, are self-delusional, enjoying a "feeling" of moral worth. The main aim of this work was to uncover the brain mechanisms underlying moral decision making related to intimate partner violence (IPV) against women. We conducted a functional magnetic resonance imaging (fMRI) study comparing moral decisions related to IPV and general violence (GV) in a sample of convicted Spanish men. The two groups of our sample were recruited from the Center for Social Insertion (CSI; Granada, Spain): batterers (BG, n = 21), people convicted for IPV, and other criminals (OCG, n = 20) convicted of violating other legal norms without violence against people. Greene's classical dilemmas were used to validate IPV and GV dilemmas. First, our results showed that IPV and GV dilemmas activate the same brain areas as those activated by Greene's dilemmas, primarily involving the default mode network (DMN), which suggests that IPV and GV dilemmas are both moral dilemmas. Second, our results showed that other criminals activated the DMN during both types of dilemmas. Nevertheless, batterers activated the DMN during the GV dilemmas but not during the IPV ones, suggesting that decisions about their female partners do not entail moral conflict. Thus, these preliminary results showed that batterers do not activate moral areas during IPV dilemmas specifically, but do so during GV dilemmas. These results suggest that intervention programs for batterers should aim to specifically modify the value system held by the abuser toward his female partner and not toward other people.

The self on its axis: a framework for understanding depression

The self is experienced differently in depression. It is infused with pervasive low mood, and structured by negative self-related thoughts. The concept of the self has been difficult to define-one of the reasons it is now infrequently an object of enquiry for psychiatry-but findings from functional brain imaging and other neuroscience studies have provided new insights. They have elucidated how the self is supported by complex, hierarchical brain processes. Bodily sensations rise through the spinal cord, brainstem, and subcortical regions through to cortical networks, with the default mode network sitting at the apex, integrating interoceptive signals with information about the extended social environment. We discuss how this forms a "self axis", and demonstrate how this axis is set awry by depression. Our self-axis model of depression establishes a new perspective on the disorder. It emphasises the multi-level nature of depression, and how impacts made at different explanatory levels influence others along the axis. It suggests that diverse treatments might be effective for depression, from lifestyle interventions to psychotherapies to medications: they target different aspects of the self, but changes at one level of the self axis can affect others along it. Our framework for depression establishes a central role for the self, which might again become a useful focus of investigation.

Dynamic Subcortical Modulators of Human Default Mode Network Function

The brain’s “default mode network” (DMN) enables flexible switching between internally and externally focused cognition. Precisely how this modulation occurs is not well understood, although it may involve key subcortical mechanisms, including hypothesized influences from the basal forebrain (BF) and mediodorsal thalamus (MD). Here, we used ultra-high field (7 T) functional magnetic resonance imaging to examine the involvement of the BF and MD across states of task-induced DMN activity modulation. Specifically, we mapped DMN activity suppression (“deactivation”) when participants transitioned between rest and externally focused task performance, as well as DMN activity engagement (“activation”) when task performance was internally (i.e., self) focused. Consistent with recent rodent studies, the BF showed overall activity suppression with DMN cortical regions when comparing the rest to external task conditions. Further analyses, including dynamic causal modeling, confirmed that the BF drove changes in DMN cortical activity during these rest-to-task transitions. The MD, by comparison, was specifically engaged during internally focused cognition and demonstrated a broad excitatory influence on DMN cortical activation. These results provide the first direct evidence in humans of distinct BF and thalamic circuit influences on the control of DMN function and suggest novel mechanistic avenues for ongoing translational research.

Suppressed activity of the rostral anterior cingulate cortex as a biomarker for depression remission

BACKGROUND

Suppression of the rostral anterior cingulate cortex (rACC) has shown promise as a prognostic biomarker for depression. We aimed to use machine learning to characterise its ability to predict depression remission.

METHODS

Data were obtained from 81 15- to 25-year-olds with a major depressive disorder who had participated in the YoDA-C trial, in which they had been randomised to receive cognitive behavioural therapy plus either fluoxetine or placebo. Prior to commencing treatment patients performed a functional magnetic resonance imaging (fMRI) task to assess rACC suppression. Support vector machines were trained on the fMRI data using nested cross-validation, and were similarly trained on clinical data. We further tested our fMRI model on data from the YoDA-A trial, in which participants had completed the same fMRI paradigm.

RESULTS

Thirty-six of 81 (44%) participants in the YoDA-C trial achieved remission. Our fMRI model was able to predict remission status (AUC = 0.777 [95% confidence interval (CI) 0.638-0.916], balanced accuracy = 67%, negative predictive value = 74%, p < 0.0001). Clinical models failed to predict remission status at better than chance levels. Testing the model on the alternative YoDA-A dataset confirmed its ability to predict remission (AUC = 0.776, balanced accuracy = 64%, negative predictive value = 70%, p < 0.0001).

CONCLUSIONS

We confirm that rACC activity acts as a prognostic biomarker for depression. The machine learning model can identify patients who are likely to have difficult-to-treat depression, which might direct the earlier provision of enhanced support and more intensive therapies.

Brain Structural Changes in Carpal Tunnel Syndrome Patients: From the Perspectives of Structural Connectivity and Structural Covariance Network

BACKGROUND

Carpal tunnel syndrome (CTS) is a common peripheral entrapment neuropathy. However, CTS-related changes of brain structural covariance and structural covariance networks (SCNs) patterns have not been clearly studied.

OBJECTIVE

To explore CTS-related brain changes from perspectives of structural connectivity and SCNs.

METHODS

Brain structural magnetic resonance images were acquired from 27 CTS patients and 19 healthy controls (HCs). Structural covariance and SCNs were constructed based on gray matter volume. The global network properties including clustering coefficient (Cp), characteristic path length (Lp), small-worldness index, global efficiency (Eglob), and local efficiency (Eloc) and regional network properties including degree, betweenness centrality (BC), and Eloc of a given node were calculated with graph theoretical analysis.

RESULTS

Compared with HCs, the strength of structural connectivity between the dorsal anterior insula and medial prefrontal thalamus decreased (P < .001) in CTS patients. There was no intergroup difference of area under the curve for Cp, Lp¸ Eglob, and Eloc (all P > .05). The real-world SCN of CTS patients showed a small-world topology ranging from 2% to 32%. CTS patients showed lower nodal degrees of the dorsal anterior insula and medial prefrontal thalamus, and higher Eloc of a given node and BC in the lateral occipital cortex (P < .001) and the dorsolateral middle temporal gyrus (P < .001) than HCs, respectively.

CONCLUSION

CTS had a profound impact on brain structures from perspectives of structural connectivity and SCNs.

Childhood urbanicity interacts with polygenic risk for depression to affect stress-related medial prefrontal function

Urbanization is increasing globally, and is associated with stress and increased mental health risks, including for depression. However, it remains unclear, especially at the level of brain function, how urbanicity, social threat stressors, and psychiatric risk may be linked. Here, we aim to define the structural and functional MRI neural correlates of social stress, childhood urbanicity, and their putative mechanistic relevance to depressive illness risk, in terms of behavioral traits and genetics. We studied a sample of healthy adults with divergent urban and rural childhoods. We examined childhood urbanicity effects on brain structure as suggested by MRI, and its functional relevance to depression risk, through interactions between urbanicity and trait anxiety-depression, as well as between urbanicity and polygenic risk for depression, during stress-related medial prefrontal cortex (mPFC) engagement. Subjects with divergent rural and urban childhoods were similar in adult socioeconomic status and were genetically homogeneous. Urban childhood was associated with relatively reduced mPFC gray matter volumes as suggested by MRI. MPFC engagement under social status threat correlated with the higher trait anxiety-depression in subjects with urban childhoods, but not in their rural counterparts, implicating an exaggerated physiological response to the threat context with urbanicity, in association with behavioral risk for depression. Stress-associated mPFC engagement also interacted with polygenic risk for depression, significantly predicting a differential mPFC response in individuals with urban but not rural childhoods. Developmental urbanicity, therefore, appears to interact with genetic and behavioral risk for depression on the mPFC neural response to a threat context.

Modulating medial prefrontal cortex activity using real-time fMRI neurofeedback: Effects on reality monitoring performance and associated functional connectivity

Neuroimaging studies have found ‘reality monitoring’, our ability to distinguish internally generated experiences from those derived from the external world, to be associated with activity in the medial prefrontal cortex (mPFC) of the brain. Here we probe the functional underpinning of this ability using real-time fMRI neurofeedback to investigate the involvement of mPFC in recollection of the source of self-generated information. Thirty-nine healthy individuals underwent neurofeedback training in a between groups study receiving either Active feedback derived from the paracingulate region of the mPFC (21 subjects) or Sham feedback based on a similar level of randomised signal (18 subjects). Compared to those in the Sham group, participants receiving Active signal showed increased mPFC activity over the course of three real-time neurofeedback training runs undertaken in a single scanning session. Analysis of resting state functional connectivity associated with changes in reality monitoring accuracy following Active neurofeedback revealed increased connectivity between dorsolateral frontal regions of the fronto-parietal network (FPN) and the mPFC region of the default mode network (DMN), together with reduced connectivity within ventral regions of the FPN itself. However, only a trend effect was observed in the interaction of the recollection of the source of Imagined information compared with recognition memory between participants receiving Active and Sham neurofeedback, pre- and post- scanning. As such, these findings demonstrate that neurofeedback can be used to modulate mPFC activity and increase cooperation between the FPN and DMN, but the effects on reality monitoring performance are less clear.

Mental fatigue correlates with depression of task-related network and augmented DMN activity but spares the reward circuit

Long-lasting and demanding cognitive activity typically leads to mental fatigue (MF). Indirect evidence suggests that MF may be caused by altered motivational processes. Here, we hypothesized that if MF consists in an alteration of motivational states, brain functional changes induced by MF could specifically affect the brain motivation circuit. In order to test this hypothesis, we devised a functional neuroimaging protocol to detect altered brain activity in reward-related brain regions in relation to cognitively induced mental fatigue. Twenty-five healthy participants underwent a FATIGUE and a CONTROL session on different days. In the FATIGUE session, MF was induced by performing a demanding cognitive task (adapted Stroop task) during 90 min, whereas in the CONTROL session, participants were asked to read magazines for the same period of time. We measured the neural consequences of the MF induction during a working memory task (Missing Number task) while modulating extrinsic motivation with block-wise variations in monetary reward. We also tracked participants' momentary fatigue, anxiety state and intrinsic motivation prior to and following the MF inducement and measurement. Accuracy on the Missing Number Task was lower in the FATIGUE than in the CONTROL condition. Furthermore, subjective MF, but not its behavioral manifestations, was associated with hypoactivity of the task-evoked neural responses. Importantly, activity in regions modulated by reward showed no differences between FATIGUE and CONTROL sessions. In parallel, subjective MF correlated with increased on-task activity and resting-state functional connectivity in the default mode network. These results indicate that subjective mental fatigue is not associated with altered activity in the brain motivation circuit but rather with hypoactivity in task-specific brain regions as well as relative increases of activity and connectivity in the default mode network during and after the task.

Individualized video recommendation modulates functional connectivity between large scale networks

With the emergence of AI‐powered recommender systems and their extensive use in the video streaming service, questions and concerns also arise. Why can recommended video content continuously capture users' attention? What is the impact of long‐term exposure to personalized video content on one's behaviors and brain functions? To address these questions, we designed an fMRI experiment presenting participants with personally recommended videos and generally recommended ones. To examine how large‐scale networks were modulated by personalized video content, graph theory analysis was applied to investigate the interaction between seven networks, including the ventral and dorsal attention networks (VAN, DAN), frontal–parietal network (FPN), salience network (SN), and three subnetworks of default mode network (dorsal medial prefrontal (dMPFC), Core, and medial temporal lobe (MTL)). Our results showed that viewing nonpersonalized video content mainly enhanced the connectivity in the DAN‐FPN‐Core pathway, whereas viewing personalized ones increased not only the connectivity in this pathway but also the DAN‐VAN‐dMPFC pathway. In addition, both personalized and nonpersonalized short videos decreased the couplings between SN and VAN as well as between two DMN subsystems, Core and MTL. Collectively, these findings uncovered distinct patterns of network interactions in response to short videos and provided insights into potential neural mechanisms by which human behaviors are biased by personally recommended content.

Prognostic neuroimaging biomarkers of trauma-related psychopathology: resting-state fMRI shortly after trauma predicts future PTSD and depression symptoms in the AURORA study

Neurobiological markers of future susceptibility to posttraumatic stress disorder (PTSD) may facilitate identification of vulnerable individuals in the early aftermath of trauma. Variability in resting-state networks (RSNs), patterns of intrinsic functional connectivity across the brain, has previously been linked to PTSD, and may thus be informative of PTSD susceptibility. The present data are part of an initial analysis from the AURORA study, a longitudinal, multisite study of adverse neuropsychiatric sequalae. Magnetic resonance imaging (MRI) data from 109 recently (i.e., ~2 weeks) traumatized individuals were collected and PTSD and depression symptoms were assessed at 3 months post trauma. We assessed commonly reported RSNs including the default mode network (DMN), central executive network (CEN), and salience network (SN). We also identified a proposed arousal network (AN) composed of a priori brain regions important for PTSD: the amygdala, hippocampus, mamillary bodies, midbrain, and pons. Primary analyses assessed whether variability in functional connectivity at the 2-week imaging timepoint predicted 3-month PTSD symptom severity. Left dorsolateral prefrontal cortex (DLPFC) to AN connectivity at 2 weeks post trauma was negatively related to 3-month PTSD symptoms. Further, right inferior temporal gyrus (ITG) to DMN connectivity was positively related to 3-month PTSD symptoms. Both DLPFC-AN and ITG-DMN connectivity also predicted depression symptoms at 3 months. Our results suggest that, following trauma exposure, acutely assessed variability in RSN connectivity was associated with PTSD symptom severity approximately two and a half months later. However, these patterns may reflect general susceptibility to posttraumatic dysfunction as the imaging patterns were not linked to specific disorder symptoms, at least in the subacute/early chronic phase. The present data suggest that assessment of RSNs in the early aftermath of trauma may be informative of susceptibility to posttraumatic dysfunction, with future work needed to understand neural markers of long-term (e.g., 12 months post trauma) dysfunction. Furthermore, these findings are consistent with neural models suggesting that decreased top-down cortico-limbic regulation and increased network-mediated fear generalization may contribute to ongoing dysfunction in the aftermath of trauma.

Statistical and Machine Learning Link Selection Methods for Brain Functional Networks: Review and Comparison

Network-based representations have introduced a revolution in neuroscience, expanding the understanding of the brain from the activity of individual regions to the interactions between them. This augmented network view comes at the cost of high dimensionality, which hinders both our capacity of deciphering the main mechanisms behind pathologies, and the significance of any statistical and/or machine learning task used in processing this data. A link selection method, allowing to remove irrelevant connections in a given scenario, is an obvious solution that provides improved utilization of these network representations. In this contribution we review a large set of statistical and machine learning link selection methods and evaluate them on real brain functional networks. Results indicate that most methods perform in a qualitatively similar way, with NBS (Network Based Statistics) winning in terms of quantity of retained information, AnovaNet in terms of stability and ExT (Extra Trees) in terms of lower computational cost. While machine learning methods are conceptually more complex than statistical ones, they do not yield a clear advantage. At the same time, the high heterogeneity in the set of links retained by each method suggests that they are offering complementary views to the data. The implications of these results in neuroscience tasks are finally discussed.

A common genetic variant in fatty acid amide hydrolase is linked to alterations in fear extinction neural circuitry in a racially diverse, nonclinical sample of adults

Poor fear extinction learning and recall are linked to the development of fear-based disorders, like posttraumatic stress disorder, and are associated with aberrant activation of fear-related neural circuitry. This includes greater amygdala activation during extinction learning and lesser hippocampal and ventromedial prefrontal cortex (vmPFC) activation during recall. Emerging data indicate that genetic variation in fatty acid amide hydrolase (FAAH C385A; rs324420) is associated with increased peripheral endocannabinoid (eCB) levels and lesser threat-related amygdala reactivity. Preclinical studies link increased eCB signaling to better extinction learning and recall, thus FAAH C385A may protect against the development of trauma-related psychopathology by facilitating extinction learning. However, how this FAAH variant affects fear extinction neural circuitry remains unknown. In the present study, we used a novel, immersive-reality fear extinction paradigm paired with functional neuroimaging to assess FAAH C385A effects on fear-related neural circuitry and conditioned fear responding (US expectancy ratings, subjective units of distress, and skin conductance responding) in healthy adults from an urban area (Detroit, MI; N = 59; C/C = 35, A-carrier = 24). We found lesser amygdala activation in A-allele carriers, compared to C/C homozygotes, during early extinction recall. Likewise, we found lesser dorsal anterior cingulate cortex and greater hippocampus activation in early extinction learning in A-carriers compared to C/C homozygotes. We found no effects of FAAH C385A on vmPFC activation or behavioral fear indices. These data support and extend previous findings that FAAH genetic variation, associated with increased eCB signaling and subsequent enhanced fear extinction, may predict individual differences in successful fear learning.

Audiovisual working memory and association with resting-state regional homogeneity

Multisensory processing is a prevalent research issue. However, multisensory working memory research has received inadequate attention. The present study aimed to investigate the behavioral performance of an audiovisual working memory task and its association with resting-state functional magnetic resonance imaging (fMRI) regional homogeneity (ReHo). A total of 128 healthy participants were enrolled in this study. The participants completed a modified Sternberg working memory task using complex auditory and visual objects as materials involved in different encoding conditions, including semantically congruent audiovisual, semantically incongruent audiovisual, and single modality of auditory or visual object encoding. Two subgroups received resting-state fMRI scans according to their behavioral performances. The results showed that the semantically congruent audiovisual object encoding sped up the later unisensory memory recognition in this task. Moreover, the high behavioral performance (response time, RT) group showed increased ReHo in the executive control network (ECN) and decreased ReHo in the default mode network (DMN) and saline network (SN). In addition, resting-state ReHo values in the ECN nodes (e.g., middle frontal gyrus and superior frontal gyrus) was correlated with RT. These findings suggested that semantically congruent audiovisual processing in working memory was superior to unisensory memory recognition and may be involved in the different functional networks such as ECN.

Safety learning and the Pavlovian conditioned inhibition of fear in humans: Current state and future directions

Safety learning occurs when an otherwise neutral stimulus comes to signal the absence of threat, allowing organisms to use safety information to inhibit fear and anxiety in nonthreatening environments. Although it continues to emerge as a topic of relevance in biological and clinical psychology, safety learning remains inconsistently defined and under-researched. Here, we analyse the Pavlovian conditioned inhibition paradigm and its application to the study of safety learning in humans. We discuss existing studies; address outstanding theoretical considerations; and identify prospects for its further application. Though Pavlovian conditioned inhibition presents a theoretically sound model of safety learning, it has been investigated infrequently, with decade-long interims between some studies, and notable methodological variability. Consequently, we argue that the full potential of conditioned inhibition as a model for human safety learning remains untapped, and propose that it could be revisited as a framework for addressing timely questions in the behavioural and clinical sciences.

Trait self-control mediates the association between resting-state neural correlates and emotional well-being in late adolescence

Trait self-control (TSC), defined as the capacity to alter predominant response to promote desirable long-term goals, has been found to facilitate emotional well-being (EWB). However, the neural correlates underlying this association remain unclear. The present study estimated resting-state brain activity and connectivity with amplitude of low-frequency fluctuations (ALFFs) and resting-state functional connectivity (rsFC) among late adolescents. Whole-brain correlation analysis showed that higher TSC was associated with increased ALFFs in regions within the executive control network (inferior frontal gyrus, IFG) and the salience network (anterior insula, AI) and decreased ALFF in regions (e.g. medial frontal gyrus, MFG; posterior cingulate, PC) within the default-mode network (DMN). TSC was also linked with the integration (e.g. increased IFG-PC connectivity) and segregation (e.g. decreased AI-MFG connectivity) among brain networks. Mediation analysis indicated that TSC totally mediated the links from the IFG and the precuneus, FC of the AI and regions of the DMN (e.g. bilateral PC and MFG), to EWB. Additionally, ALFF in the IFG and the MFG could predict negative affect in the pandemic through TSC. These findings suggest that TSC is involved in several regions and functional organizations within and between brain networks and mediated the association between neural correlates and emotional wellness in adolescence.

Differences between the child and adult brain in the local functional structure of the cerebral cortex

Imaging studies on neuronal network formation provide relevant information as to how the brain matures during adolescence. We used a novel imaging approach combining well-established MRI measures of local functional connectivity that jointly provide qualitatively different information relating to the functional structure of the cerebral cortex. To investigate the adolescent transition into adulthood, we comparatively assessed 169 preadolescents aged 8-12 years and 121 healthy adults. Whole-brain functional connectivity maps were generated using multi-distance measures of intracortical neural activity coupling defined within iso-distant local areas. Such Iso-Distant Average Correlation (IDAC) measures therefore represent the average temporal correlation of a given brain unit, or voxel, with other units situated at increasingly separated iso-distant intervals. The results indicated that between-group differences in the functional structure of the cerebral cortex are extensive and implicate part of the lateral prefrontal cortex, a medial frontal/anterior cingulate region, the superior parietal lobe extending to the somatosensory strip and posterior cingulate cortex, and local connections within the visual cortex, hippocampus, amygdala and insula. We thus provided detail of the cerebral cortex functional structure maturation during the transition to adulthood, which may serve to establish more accurate links between adolescent performance gains and cerebral cortex maturation. Remarkably, our study provides new information as to the cortical maturation processes in prefrontal areas relevant to executive functioning and rational learning, medial frontal areas playing an active role in the cognitive appraisal of emotion and anxiety, and superior parietal cortices strongly associated with bodily self-consciousness in the context of body image formation.

Largest scale dissociation of brain activity at propofol-induced loss of consciousness

The brain is a functional unit made up of multilevel connected elements showing a pattern of synchronized activity that varies in different states. The wake-sleep cycle is a major variation of brain functional condition that is ultimately regulated by subcortical arousal- and sleep-promoting cell groups. We analyzed the evolution of functional MRI (fMRI) signal in the whole cortex and in a deep region including most sleep- and wake-regulating subcortical nuclei at loss of consciousness induced by the hypnotic agent propofol. Optimal data were obtained in 21 of the 30 healthy participants examined. A dynamic analysis of fMRI time courses on a time-scale of seconds was conducted to characterize consciousness transition, and functional connectivity maps were generated to detail the anatomy of structures showing different dynamics. Inside the magnet, loss of consciousness was marked by the participants ceasing to move their hands. We observed activity synchronization after loss of consciousness within both the cerebral cortex and subcortical structures. However, the evolution of fMRI signal was dissociated, showing a transient reduction of global cortico-subcortical coupling that was restored during the unconscious state. An exception to cortico-subcortical decoupling was a brain network related to self-awareness (i.e. the default mode network) that remained connected to subcortical brain structures. Propofol-induced unconsciousness is thus characterized by an initial, transitory dissociated synchronization at the largest scale of brain activity. Such cortico-subcortical decoupling and subsequent recoupling may allow the brain to detach from waking activity and reorganize into a functionally distinct state.

Differential Modulation of Effective Connectivity in the Brain's Extended Face Processing System by Fearful and Sad Facial Expressions

The processing of emotional facial expressions is underpinned by the integration of information from a distributed network of brain regions. Despite investigations into how different emotional expressions alter the functional relationships within this network, there remains limited research examining which regions drive these interactions. This study investigated effective connectivity during the processing of sad and fearful facial expressions to better understand how these stimuli differentially modulate emotional face processing circuitry. Ninety-eight healthy human adolescents and young adults, aged between 15 and 25 years, underwent an implicit emotional face processing fMRI task. Using dynamic causal modeling (DCM), we examined five brain regions implicated in face processing. These were restricted to the right hemisphere and included the occipital and fusiform face areas, amygdala, and dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC). Processing sad and fearful facial expressions were associated with greater positive connectivity from the amygdala to dlPFC. Only the processing of fearful facial expressions was associated with greater negative connectivity from the vmPFC to amygdala. Compared with processing sad faces, processing fearful faces was associated with significantly greater connectivity from the amygdala to dlPFC. No difference was found between the processing of these expressions and the connectivity from the vmPFC to amygdala. Overall, our findings indicate that connectivity from the amygdala and dlPFC appears to be responding to dimensional features which differ between these expressions, likely those relating to arousal. Further research is necessary to examine whether this relationship is also observable for positively valenced emotions.