An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings

Novelty-Related fMRI Responses of Precuneus and Medial Temporal Regions in Individuals at Risk for Alzheimer Disease

Background and Objectives

We assessed whether novelty-related fMRI activity in medial temporal lobe regions and the precuneus follows an inverted U-shaped pattern across the clinical spectrum of increased Alzheimer disease (AD) risk as previously suggested. Specifically, we tested for potentially increased activity in individuals with a higher AD risk due to subjective cognitive decline (SCD) or mild cognitive impairment (MCI). We further tested whether activity differences related to diagnostic groups were accounted for by CSF markers of AD or brain atrophy.

Methods

We studied 499 participants aged 60–88 years from the German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study (DELCODE) who underwent task-fMRI. Participants included 163 cognitively normal (healthy control, HC) individuals, 222 SCD, 82 MCI, and 32 patients with clinical diagnosis of mild AD. CSF levels of β-amyloid 42/40 ratio and phosphorylated-tau181 were available from 232 participants. We used region-based analyses to assess novelty-related activity (novel > highly familiar scenes) in entorhinal cortex, hippocampus, and precuneus as well as whole-brain voxel-wise analyses. First, general linear models tested differences in fMRI activity between participant groups. Complementary regression models tested quadratic relationships between memory impairment and activity. Second, relationships of activity with AD CSF biomarkers and brain volume were analyzed. Analyses were controlled for age, sex, study site, and education.

Results

In the precuneus, we observed an inverted U-shaped pattern of novelty-related activity across groups, with higher activity in SCD and MCI compared with HC, but not in patients with AD who showed relatively lower activity than MCI. This nonlinear pattern was confirmed by a quadratic relationship between memory impairment and precuneus activity. Precuneus activity was not related to AD biomarkers or brain volume. In contrast to the precuneus, hippocampal activity was reduced in AD dementia compared with all other groups and related to AD biomarkers.

Discussion

Novelty-related activity in the precuneus follows a nonlinear pattern across the clinical spectrum of increased AD risk. Although the underlying mechanism remains unclear, increased precuneus activity might represent an early signature of memory impairment. Our results highlight the nonlinearity of activity alterations that should be considered in clinical trials using functional outcome measures or targeting hyperactivity.

Basal forebrain magnocellular cholinergic systems are damaged in mice following neonatal hypoxia-ischemia

Neonatal hypoxic-ischemic encephalopathy (HIE) causes lifelong neurologic disability. Despite the use of therapeutic hypothermia, memory deficits and executive functions remain severely affected. Cholinergic neurotransmission from the basal forebrain to neocortex and hippocampus is central to higher cortical functions. We examined the basal forebrain by light microscopy and reported loss of choline acetyltransferase-positive (ChAT)+ neurons, at postnatal day (P) 40, in the ipsilateral medial septal nucleus (MSN) after neonatal hypoxia-ischemia (HI) in mice. There was no loss of ChAT+ neurons in the ipsilateral nucleus basalis of Meynert (nbM) and striatum. Ipsilateral striatal and nbM ChAT+ neurons were abnormal with altered immunoreactivity for ChAT, shrunken and crenated somas, and dysmorphic appearing dendrites. Using confocal images with 3D reconstruction, nbM ChAT+ dendrites in HI mice were shorter than sham (p = .0001). Loss of ChAT+ neurons in the MSN directly correlated with loss of ipsilateral hippocampal area. In the nbM and striatum, percentage of abnormal ChAT+ neurons correlated with loss of ipsilateral cerebral cortical and striatal area, respectively. Acetylcholinesterase (AChE) activity increased in adjacent ipsilateral cerebral cortex and hippocampus and the increase was linearly related to loss of cortical and hippocampal area. Numbers and size of cathepsin D+ lysosomes increased in large neurons in the ipsilateral nbM. After neonatal HI, abnormalities were found throughout the major cholinergic systems in relationship to amount of forebrain area loss. There was also an upregulation of cathepsin D+ particles within the nbM. Cholinergic neuropathology may underlie the permanent dysfunction in learning, memory, and executive function after neonatal brain injury.

Effects of Methylphenidate on Somatic Symptoms and Brain Functional Connectivity in Adolescents with Attention Deficit Hyperactivity Disorder: A Pilot Study

Objective

This study aimed to evaluate whether somatic symptoms in adolescents with attention deficit hyperactivity disorder (ADHD) are associated with a dissociative pattern of functional connectivity (FC) within the default mode network (DMN) and whether methylphenidate administration can improve clinical and somatic symptoms. We also evaluated whether the improvement of somatic symptoms is associated with increased FC within the DMN in response to methylphenidate treatment.

Methods

Fifteen male adolescents with somatic symptoms of ADHD and 15 male adolescents with ADHD without somatic symptoms were included. At baseline and after 6 months of methylphenidate treatment, all adolescents were asked to complete questionnaires for the Korean version of the Dupaul’s ADHD rating scale, the symptom checklist-90- revised-somatization subscales, the Beck Depression Inventory, and the Beck Anxiety Inventory. Additionally, a resting-state functional magnetic resonance imaging scan was conducted.

Results

Methylphenidate treatment improved clinical and somatic symptoms in adolescents with ADHD. In addition, it increased brain FC within the DMN from the posterior cingulate cortex (posterior DMN) to the middle prefrontal cortex (anterior DMN). The improvement of somatic symptoms was associated with FC within the DMN from the posterior cingulate cortex to the middle prefrontal cortex in ADHD adolescents with somatic symptoms.

Conclusion

Methylphenidate increased brain FC between the anterior and posterior DMN. The improvement of somatic symptoms in adolescents with ADHD was associated with FC within the DMN. The DMN in adolescents with ADHD seems to be associated with the severity of the clinical and somatic symptoms of ADHD.

Use of Novel Concussion Protocol With Infralow Frequency Neuromodulation Demonstrates Significant Treatment Response in Patients With Persistent Postconcussion Symptoms, a Retrospective Study

Introduction

Concussion is a growing public health concern. No uniformly established therapy exists; neurofeedback studies report treatment value. We use infralow frequency neuromodulation (ILF) to remediate disabling neurological symptoms caused by traumatic brain injury (TBI) and noted improved outcomes with a novel concussion protocol. Postconcussion symptoms (PCS) and persistent postconcussion symptoms (PPCS; >3 months post head injury) are designated timelines for protracted neurological complaints following TBI. We performed a retrospective study to explore effectiveness of ILF in PCS/PPCS and investigated the value of using this concussion protocol.

Method

Patients with PCS/PPCS seen for their first neurology office visit or received their first neurofeedback session between 1 August 2018 and 31 January 2021 were entered. Outcomes were compared following treatment as usual (TAU) vs. TAU with ILF neurotherapy (TAU+ILF). The study cohort was limited to PPCS patients; the TAU+ILF group was restricted further to PPCS patients receiving at least 10 neurotherapy sessions. Within the TAU+ILF group, comparisons were made between those who trained at least 10 sessions using concussion protocol (TAU+ILF+CP) and those who trained for at least 10 sessions of ILF regardless of protocol (TAU+ILF-CP).

Results

Among our resultant PPCS cohort (n = 59) leading persistent neurological complaints were headache (67.8%), memory impairment (57.6%), and brain fog (50.8%). PPCS patients in TAU+ILF+CP (n = 25) demonstrated greater net (p = 0.004) and percent (p = 0.026) improvement of symptoms compared to PPCS subjects in TAU (n = 26). PPCS patients in TAU+ILF-CP (n = 8) trended toward significant symptom improvements compared to TAU, and TAU+ILF+CP trended toward greater efficacy than TAU+ILF-CP.

Conclusion

PPCS patients who received TAU+ILF+CP demonstrated significantly greater improvement as a group when compared to TAU. When used as an integrative modality to treatment as usual in managing patients with PPCS, ILF neuromodulation with use of concussion protocol provided significant symptom improvements.

Episodic Past, Future, and counterfactual thinking in Relapsing-Remitting Multiple sclerosis

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Performance in episodic past, future or counterfactual thinking in relapsing-remitting MS and controls was explored.

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Behavioral and diffusion weighted imaging were used to evaluate associations between white matter integrity and group differences in performance.

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Relative to controls, MS patients showed reductions in episodic details across all three simulations.

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Reduced white matter integrity in three association tracts predicted this reduction in episodic details during counterfactual simulations.

Multiple sclerosis (MS) is a progressive disease characterized by widespread white matter lesions in the brain and spinal cord. In addition to well-characterized motor deficits, MS results in cognitive impairments in several domains, notably in episodic autobiographical memory. Recent studies have also revealed that patients with MS exhibit deficits in episodic future thinking, i.e., our capacity to imagine possible events that may occur in our personal future. Both episodic memory and episodic future thinking have been shown to share cognitive and neural mechanisms with a related kind of hypothetical simulation known as episodic counterfactual thinking: our capacity to imagine alternative ways in which past personal events could have occurred but did not. However, the extent to which episodic counterfactual thinking is affected in MS is still unknown. The current study sought to explore this issue by comparing performance in mental simulation tasks involving either past, future or counterfactual thoughts in relapsing-remitting MS. Diffusion weighted imaging (DWI) measures were also extracted to determine whether changes in structural pathways connecting the brain’s default mode network (DMN) would be associated with group differences in task performance. Relative to controls, patients showed marked reductions in the number of internal details across all mental simulations, but no differences in the number of external and semantic-based details. It was also found that, relative to controls, patients with relapsing-remitting MS reported reduced composition ratings for episodic simulations depicting counterfactual events, but not so for actual past or possible future episodes. Additionally, three DWI measures of white matter integrity—fractional anisotropy, radial diffusivity and streamline counts—showed reliable differences between patients with relapsing-remitting MS and matched healthy controls. Importantly, DWI measures associated with reduced white matter integrity in three association tracts on the DMN—the right superior longitudinal fasciculus, the left hippocampal portion of the cingulum and the left inferior longitudinal fasciculus—predicted reductions in the number of internal details during episodic counterfactual simulations. Taken together, these results help to illuminate impairments in episodic simulation in relapsing-remitting MS and show, for the first time, a differential association between white matter integrity and deficits in episodic counterfactual thinking in individuals with relapsing-remitting MS.

Network communication models narrow the gap between the modular organization of structural and functional brain networks

Structural and functional brain networks are modular. Canonical functional systems, such as the default mode network, are well-known modules of the human brain and have been implicated in a large number of cognitive, behavioral and clinical processes. However, modules delineated in structural brain networks inferred from tractography generally do not recapitulate canonical functional systems. Neuroimaging evidence suggests that functional connectivity between regions in the same systems is not always underpinned by anatomical connections. As such, direct structural connectivity alone would be insufficient to characterize the functional modular organization of the brain. Here, we demonstrate that augmenting structural brain networks with models of indirect (polysynaptic) communication unveils a modular network architecture that more closely resembles the brain's established functional systems. We find that diffusion models of polysynaptic connectivity, particularly communicability, narrow the gap between the modular organization of structural and functional brain networks by 20-60%, whereas routing models based on single efficient paths do not improve mesoscopic structure-function correspondence. This suggests that functional modules emerge from the constraints imposed by local network structure that facilitates diffusive neural communication. Our work establishes the importance of modeling polysynaptic communication to understand the structural basis of functional systems.

Neuroanatomical markers of psychotic experiences in adolescents: A machine-learning approach in a longitudinal population-based sample

It is important to identify accurate markers of psychiatric illness to aid early prediction of disease course. Subclinical psychotic experiences (PEs) are important risk factors for later mental ill-health and suicidal behaviour. This study used machine learning to investigate neuroanatomical markers of PEs in early and later stages of adolescence. Machine learning using logistic regression using Elastic Net regularization was applied to T1-weighted and diffusion MRI data to classify adolescents with subclinical psychotic experiences vs. controls across 3 timepoints (Time 1:11-13 years, n = 77; Time 2:14-16 years, n = 56; Time 3:18-20 years, n = 40). Neuroimaging data classified adolescents aged 11-13 years with current PEs vs. controls returning an AROC of 0.62, significantly better than a null model, p = 1.73^e-29. Neuroimaging data also classified those with PEs at 18-20 years (AROC = 0.59;P = 7.19^e-10) but performance was at chance level at 14-16 years (AROC = 0.50). Left hemisphere frontal regions were top discriminant classifiers for 11-13 years-old adolescents with PEs, particularly pars opercularis. Those with future PEs at 18-20 years-old were best distinguished from controls based on left frontal regions, right-hemisphere medial lemniscus, cingulum bundle, precuneus and genu of the corpus callosum (CC). Deviations from normal adolescent brain development in young people with PEs included an acceleration in the typical pattern of reduction in left frontal thickness and right parietal curvature, and accelerated progression of microstructural changes in right white matter and corpus callosum. These results emphasise the importance of multi-modal analysis for understanding adolescent PEs and provide important new insights into early phenotypes for psychotic experiences.

Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI

The relationship between age-related changes in brain structural connectivity (SC) and functional connectivity (FC) with cognition is not well understood. Furthermore, it is not clear whether cognition is represented via a similar spatial pattern of FC and SC or instead is mapped by distinct sets of distributed connectivity patterns. To this end, we used a longitudinal, within-subject, multimodal approach aiming to combine brain data from diffusion-weighted MRI (DW-MRI), and functional MRI (fMRI) with behavioral evaluation, to better understand how changes in FC and SC correlate with changes in cognition in a sample of older adults. FC and SC measures were derived from the multimodal scans acquired at two time points. Change in FC and SC was correlated with 13 behavioral measures of cognitive function using Partial Least Squares Correlation (PLSC). Two of the measures indicate an age-related change in cognition and the rest indicate baseline cognitive performance. FC and SC—cognition correlations were expressed across several cognitive measures, and numerous structural and functional cortical connections, mainly cingulo-opercular, dorsolateral prefrontal, somatosensory and motor, and temporo-parieto-occipital, contributed both positively and negatively to the brain-behavior relationship. Whole-brain FC and SC captured distinct and independent connections related to the cognitive measures. Overall, we examined age-related function-structure associations of the brain in a comprehensive and integrated manner, using a multimodal approach. We pointed out the behavioral relevance of age-related changes in FC and SC. Taken together, our results highlight that the heterogeneity in distributed FC and SC connectivity patterns provide unique information about the variable nature of healthy cognitive aging.

Resting-State Functional Connectivity Differences in College Students with and without Food Insecurity

We used functional magnetic resonance imaging (fMRI) to investigate cross-sectional differences in functional connectivity across cognitive networks at rest among age and sex matched college students with very low food security [food insecurity (FI); n = 20] and with high food security (n = 20). The participants completed the Behavior Rating Inventory of Executive Function-2 (BRIEF-2) and Adverse Childhood Experiences (ACEs) questionnaires. Seven-minute resting-state fMRI scans were collected. Independent Component Analysis assessed group connectivity differences in three large-scale networks: the default-mode network (DMN), the frontoparietal network (FPN), and the salience network (SN). FI was associated with poorer Global BRIEF scores (adjusted β = 8.36; 95% CI: 2.32, 14.40) and five BRIEF subscales: Inhibit, Initiate, Working Memory, Plan, and Organize (p-values < 0.05). The students with FI had greater functional connectivity between the FPN and left middle temporal gyrus (cluster size p-FWE = 0.029), the SN and precuneus (cluster size p-FWE < 0.001), and the SN and right middle frontal gyrus (cluster size p-FWE = 0.016) compared to the students with high food security. Exploratory correlations revealed that greater connectivity between the SN and right middle frontal gyrus was associated with poorer BRIEF Inhibit scores (p = 0.038), and greater connectivity between the FPN and left middle temporal gyrus was associated with poorer BRIEF Organize scores (p = 0.024) for the students with FI. Greater functional connectivity between the FPN, DMN, and SN at rest may contribute to executive function difficulties for college students with FI.

Subcortical control of the default mode network: Role of the basal forebrain and implications for neuropsychiatric disorders

The precise interplay between large-scale functional neural systems throughout the brain is essential for performance of cognitive processes. In this review we focus on the default mode network (DMN), one such functional network that is active during periods of quiet wakefulness and believed to be involved in introspection and planning. Abnormalities in DMN functional connectivity and activation appear across many neuropsychiatric disorders, including schizophrenia. Recent evidence suggests subcortical regions including the basal forebrain are functionally and structurally important for regulation of DMN activity. Within the basal forebrain, subregions like the ventral pallidum may influence DMN activity and the nucleus basalis of Meynert can inhibit switching between brain networks. Interactions between DMN and other functional networks including the medial frontoparietal network (default), lateral frontoparietal network (control), midcingulo-insular network (salience), and dorsal frontoparietal network (attention) are also discussed in the context of neuropsychiatric disorders. Several subtypes of basal forebrain neurons have been identified including basal forebrain parvalbumin-containing or somatostatin-containing neurons which can regulate cortical gamma band oscillations and DMN-like behaviors, and basal forebrain cholinergic neurons which might gate access to sensory information during reinforcement learning. In this review, we explore this evidence, discuss the clinical implications on neuropsychiatric disorders, and compare neuroanatomy in the human vs rodent DMN. Finally, we address technological advancements which could help provide a more complete understanding of modulation of DMN function and describe newly identified BF therapeutic targets that could potentially help restore DMN-associated functional deficits in patients with a variety of neuropsychiatric disorders.

Relationship between plasma clozapine/N-desmethylclozapine and changes in basal forebrain-dorsolateral prefrontal cortex coupling in treatment-resistant schizophrenia

Clozapine (CLZ) demonstrates a unique clinical efficacy relative to other antipsychotic drugs. Previous work has linked the plasma ratio of CLZ and its major metabolite, N-desmethylclozapine (NDMC), to an inverse relationship with cognition via putative action on the cholinergic system. However, neuroimaging correlates of CLZ/NDMC remain unknown. Here, we examined changes in basal forebrain functional connectivity with the dorsolateral prefrontal cortex, and secondly, cognition in relation to the CLZ/NDMC ratio. A cohort of nineteen chronically ill participants with treatment-resistant schizophrenia (TRS) undergoing 12 weeks of CLZ treatment were included. Measures of cognition and plasma CLZ/NDMC ratios were obtained in addition to resting-state functional neuroimaging scans, captured at baseline and after 12 weeks of CLZ treatment. We observed a significant correlation between basal forebrain-DLPFC connectivity and CLZ/NDMC ratios across CLZ treatment (p = 0.02). Consistent with previous findings, we also demonstrate a positive relationship between CLZ/NDMC ratio and working memory (p = 0.03). These findings may reflect the action of CLZ and NDMC on the muscarinic cholinergic system, highlighting a possible neural correlate of cognition across treatment.

The anterior thalamic nuclei: core components of a tripartite episodic memory system

Standard models of episodic memory focus on hippocampal-parahippocampal interactions, with the neocortex supplying sensory information and providing a final repository of mnemonic representations. However, recent advances have shown that other regions make distinct and equally critical contributions to memory. In particular, there is growing evidence that the anterior thalamic nuclei have a number of key cognitive functions that support episodic memory. In this article, we describe these findings and argue for a core, tripartite memory system, comprising a 'temporal lobe' stream (centred on the hippocampus) and a 'medial diencephalic' stream (centred on the anterior thalamic nuclei) that together act on shared cortical areas. We demonstrate how these distributed brain regions form complementary and necessary partnerships in episodic memory formation.

Sustained attention alterations in major depressive disorder: A review of fMRI studies employing Go/No-Go and CPT tasks

BACKGROUND

Major depressive disorder (MDD) is a severe psychiatric condition characterized by selective cognitive dysfunctions. In this regard, functional Magnetic Resonance Imaging (fMRI) studies showed, both at resting state and during tasks, alterations in the brain functional networks involved in cognitive processes in MDD patients compared to controls. Among those, it seems that the attention network may have a role in the disease pathophysiology. Therefore, in this review we aim at summarizing the current fMRI evidence investigating sustained attention in MDD patients.

METHODS

We conducted a search on PubMed on case-control studies on MDD employing fMRI acquisitions during Go/No-Go and continuous performance tasks. A total of 12 studies have been included in the review.

RESULTS

Overall, the majority of fMRI studies reported quantitative alterations in the response to attentive tasks in selective brain regions, including the prefrontal cortex, the cingulate cortex, the temporal and parietal lobes, the insula and the precuneus, which are key nodes of the attention, the executive, and the default mode networks.

LIMITATIONS

The heterogeneity in the study designs, fMRI acquisition techniques and processing methods have limited the generalizability of the results.

CONCLUSIONS

The results from the included studies showed the presence of alterations in the activation patterns of regions involved in sustained attention in MDD, which are in line with current evidence and seemed to explain some of the key symptoms of depression. However, given the paucity and heterogeneity of studies available, it may be worthwhile to continue investigating the attentional domain in MDD with ad-hoc study designs to retrieve more robust evidence.

Subregions of DLPFC Display Graded yet Distinct Structural and Functional Connectivity

The human dorsolateral prefrontal cortex (DLPFC; approximately corresponding to Brodmann areas 9 and 46) has demonstrable roles in diverse executive functions such as working memory, cognitive flexibility, planning, inhibition, and abstract reasoning. However, it remains unclear whether this is the result of one functionally homogeneous region or whether there are functional subdivisions within the DLPFC. Here, we divided the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically and explored their respective patterns of structural and functional connectivity. In vivo probabilistic tractography (11 females and 13 males) and resting-state functional magnetic resonance imaging (fMRI; 57 females and 21 males) were employed to map out the patterns of connectivity from each DLPFC subregion. Structural connectivity demonstrated graded intraregional connectivity within the DLPFC. The patterns of structural connectivity between the DLPFC subregions and other cortical areas revealed that the dorsal-rostral subregions connections were restricted to other frontal and limbic areas, whereas the ventral-caudal region was widely connected to frontal, parietal, and limbic cortex. Functional connectivity analyses demonstrated that subregions of DLPFC were strongly interconnected to each other. The dorsal subregions were associated with the default mode network (DMN), while middle dorsal-rostral subregions were linked with the multiple demand network (MDN). The ventral-caudal subregion showed increased functional coupling with both DMN and MDN. Our results suggest that the connectivity of the DLPFC may be subdivided along a dorsorostral-ventrocaudal axis with differing (albeit graded) patterns of connectivity reflecting the integrative executive function of the DLPFC.SIGNIFICANCE STATEMENT Research has shown that the dorsolateral prefrontal cortex (DLPFC) plays a role in various executive functions. By dividing the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically, we explored their patterns of structural and functional connectivity. The patterns of connectivity within DLPFC subregions demonstrated graded intraregional connectivity. There were distinctive patterns of connectivity with other cortical areas in dorsal-rostral and ventral-caudal DLPFC subregions. Divisions across DLPFC subregions seem to align with their structural and functional connectivity. Our results suggest that DLPFC may be subdivided by the diagonal axis of the dorsal-ventral axis and rostral-caudal axis, supporting the framework of a functional organization along the anterior-posterior axis in the lateral PFC.

Reappraisal and empathic perspective-taking - More alike than meets the eyes

Emotion regulation and empathy represent highly intertwined psychological processes sharing common conceptual ground. Despite the wealth of research in these fields, the joint and distinct functional nature and topological features of these constructs have not yet been investigated using the same experimental approach. This study investigated the common and distinct neural correlates of emotion regulation and empathy using a meta-analytic approach. The regions that were jointly activated were then characterized using meta-analytic connectivity modeling and functional decoding of metadata terms. The results revealed convergent activity within the ventrolateral and dorsomedial prefrontal cortex as well as temporal regions. The functional decoding analysis demonstrated that emotion regulation and empathy were related to highly similar executive and internally oriented processes. This synthesis underlining strong functional and neuronal correspondence between emotion regulation and empathy could (i) facilitate greater integration of these two separate lines of literature, (ii) accelerate progress toward elucidating the neural mechanisms that support social cognition, and (iii) push forward the development of a common theoretical framework for these psychological processes essential to human social interactions.

Grey matter correlates of affective and somatic symptoms of premenstrual dysphoric disorder

Ovarian hormones fluctuations across the menstrual cycle are experienced by about 58% of women in their fertile age. Maladaptive brain sensitivity to these changes likely leads to the severe psychological, cognitive, and physical symptoms repeatedly experienced by women with Premenstrual Dysphoric Disorder (PMDD) during the late luteal phase of the menstrual cycle. However, the neuroanatomical correlates of these symptoms are unknown. The relationship between grey matter structure and PMDD symptom severity was delineated using structural magnetic resonance imaging during the late luteal phase of fifty-one women diagnosed with PMDD, combined with Voxel- and Surface-Based Morphometry, as well as subcortical volumetric analyses. A negative correlation was found between depression-related symptoms and grey matter volume of the bilateral amygdala. Moreover, the severity of affective and somatic PMDD symptoms correlated with cortical thickness, gyrification, sulcal depth, and complexity metrics, particularly in the prefrontal, cingulate, and parahippocampal gyri. The present findings provide the first evidence of grey matter morphological characteristics associated with PMDD symptomatology in brain regions expressing ovarian hormone receptors and of relevance to cognitive-affective functions, thus potentially having important implications for understanding how structural brain characteristics relate to PMDD symptomatology.

Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs

Deep brain stimulation is a treatment option for patients with drug-resistant epilepsy. The precise mechanism of neuromodulation in epilepsy is unknown, and biomarkers are needed for optimizing treatment. The aim of this study was to describe the neural network associated with deep brain stimulation targets for epilepsy and to explore its potential application as a novel biomarker for neuromodulation. Using seed-to-voxel functional connectivity maps, weighted by seizure outcomes, brain areas associated with stimulation were identified in normative resting state functional scans of 1000 individuals. To pinpoint specific regions in the normative epilepsy deep brain stimulation network, we examined overlapping areas of functional connectivity between the anterior thalamic nucleus, centromedian thalamic nucleus, hippocampus and less studied epilepsy deep brain stimulation targets. Graph network analysis was used to describe the relationship between regions in the identified network. Furthermore, we examined the associations of the epilepsy deep brain stimulation network with disease pathophysiology, canonical resting state networks and findings from a systematic review of resting state functional MRI studies in epilepsy deep brain stimulation patients. Cortical nodes identified in the normative epilepsy deep brain stimulation network were in the anterior and posterior cingulate, medial frontal and sensorimotor cortices, frontal operculum and bilateral insulae. Subcortical nodes of the network were in the basal ganglia, mesencephalon, basal forebrain and cerebellum. Anterior thalamic nucleus was identified as a central hub in the network with the highest betweenness and closeness values, while centromedian thalamic nucleus and hippocampus showed average centrality values. The caudate nucleus and mammillothalamic tract also displayed high centrality values. The anterior cingulate cortex was identified as an important cortical hub associated with the effect of deep brain stimulation in epilepsy. The neural network of deep brain stimulation targets shared hubs with known epileptic networks and brain regions involved in seizure propagation and generalization. Two cortical clusters identified in the epilepsy deep brain stimulation network included regions corresponding to resting state networks, mainly the default mode and salience networks. Our results were concordant with findings from a systematic review of resting state functional MRI studies in patients with deep brain stimulation for epilepsy. Our findings suggest that the various epilepsy deep brain stimulation targets share a common cortico-subcortical network, which might in part underpin the antiseizure effects of stimulation. Interindividual differences in this network functional connectivity could potentially be used as biomarkers in selection of patients, stimulation parameters and neuromodulation targets.

A Multivariate Functional Connectivity Approach to Mapping Brain Networks and Imputing Neural Activity in Mice

Temporal correlation analysis of spontaneous brain activity (e.g., Pearson "functional connectivity," FC) has provided insights into the functional organization of the human brain. However, bivariate analysis techniques such as this are often susceptible to confounding physiological processes (e.g., sleep, Mayer-waves, breathing, motion), which makes it difficult to accurately map connectivity in health and disease as these physiological processes affect FC. In contrast, a multivariate approach to imputing individual neural networks from spontaneous neuroimaging data could be influential to our conceptual understanding of FC and provide performance advantages. Therefore, we analyzed neural calcium imaging data from Thy1-GCaMP6f mice while either awake, asleep, anesthetized, during low and high bouts of motion, or before and after photothrombotic stroke. A linear support vector regression approach was used to determine the optimal weights for integrating the signals from the remaining pixels to accurately predict neural activity in a region of interest (ROI). The resultant weight maps for each ROI were interpreted as multivariate functional connectivity (MFC), resembled anatomical connectivity, and demonstrated a sparser set of strong focused positive connections than traditional FC. While global variations in data have large effects on standard correlation FC analysis, the MFC mapping methods were mostly impervious. Lastly, MFC analysis provided a more powerful connectivity deficit detection following stroke compared to traditional FC.

Ghani ARIG, Wan Mohamad WNA, Mohamed Mustafar MF, Hanafi MH, Reza MF, Umar H, Mohd Zulkifly MF, Ang SY, Zakaria Z, Musa KI, Othman A, Embong Z, Sapiai NA, Kandasamy R, Ibrahim H, Abdullah MZ, Amaruchkul K, Valdes-Sosa P, Luisa-Bringas M, Biswal B, Songsiri J, Yaacob HS, Sumari P, Jamir Singh PS, Azman A, Abdullah JM. Alteration in the Functional Organization of the Default Mode Network Following Closed Non-severe Traumatic Brain Injury

The debilitating effect of traumatic brain injury (TBI) extends years after the initial injury and hampers the recovery process and quality of life. In this study, we explore the functional reorganization of the default mode network (DMN) of those affected with non-severe TBI. Traumatic brain injury (TBI) is a wide-spectrum disease that has heterogeneous effects on its victims and impacts everyday functioning. The functional disruption of the default mode network (DMN) after TBI has been established, but its link to causal effective connectivity remains to be explored. This study investigated the differences in the DMN between healthy participants and mild and moderate TBI, in terms of functional and effective connectivity using resting-state functional magnetic resonance imaging (fMRI). Nineteen non-severe TBI (mean age 30.84 ± 14.56) and twenty-two healthy (HC; mean age 27.23 ± 6.32) participants were recruited for this study. Resting-state fMRI data were obtained at the subacute phase (mean days 40.63 ± 10.14) and analyzed for functional activation and connectivity, independent component analysis, and effective connectivity within and between the DMN. Neuropsychological tests were also performed to assess the cognitive and memory domains. Compared to the HC, the TBI group exhibited lower activation in the thalamus, as well as significant functional hypoconnectivity between DMN and LN. Within the DMN nodes, decreased activations were detected in the left inferior parietal lobule, precuneus, and right superior frontal gyrus. Altered effective connectivities were also observed in the TBI group and were linked to the diminished activation in the left parietal region and precuneus. With regard to intra-DMN connectivity within the TBI group, positive correlations were found in verbal and visual memory with the language network, while a negative correlation was found in the cognitive domain with the visual network. Our results suggested that aberrant activities and functional connectivities within the DMN and with other RSNs were accompanied by the altered effective connectivities in the TBI group. These alterations were associated with impaired cognitive and memory domains in the TBI group, in particular within the language domain. These findings may provide insight for future TBI observational and interventional research.

Portable Neuroimaging-Guided Noninvasive Brain Stimulation of the Cortico-Cerebello-Thalamo-Cortical Loop—Hypothesis and Theory in Cannabis Use Disorder

Background: Maladaptive neuroplasticity-related learned response in substance use disorder (SUD) can be ameliorated using noninvasive brain stimulation (NIBS); however, inter-individual variability needs to be addressed for clinical translation. Objective: Our first objective was to develop a hypothesis for NIBS for learned response in SUD based on a competing neurobehavioral decision systems model. The next objective was to develop the theory by conducting a computational simulation of NIBS of the cortico-cerebello-thalamo-cortical (CCTC) loop in cannabis use disorder (CUD)-related dysfunctional “cue-reactivity”—a construct closely related to “craving”—that is a core symptom. Our third objective was to test the feasibility of a neuroimaging-guided rational NIBS approach in healthy humans. Methods: “Cue-reactivity” can be measured using behavioral paradigms and portable neuroimaging, including functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) metrics of sensorimotor gating. Therefore, we conducted a computational simulation of NIBS, including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS) of the cerebellar cortex and deep cerebellar nuclei (DCN) of the CCTC loop for its postulated effects on fNIRS and EEG metrics. We also developed a rational neuroimaging-guided NIBS approach for the cerebellar lobule (VII) and prefrontal cortex based on a healthy human study. Results: Simulation of cerebellar tDCS induced gamma oscillations in the cerebral cortex, while transcranial temporal interference stimulation induced a gamma-to-beta frequency shift. A preliminary healthy human study (N = 10) found that 2 mA cerebellar tDCS evoked similar oxyhemoglobin (HbO) response in the range of 5 × 10⁻⁶ M across the cerebellum and PFC brain regions (α = 0.01); however, infra-slow (0.01–0.10 Hz) prefrontal cortex HbO-driven phase–amplitude-coupled (PAC; 4 Hz, ±2 mA (max)) cerebellar tACS evoked HbO levels in the range of 10⁻⁷ M that were statistically different (α = 0.01) across these brain regions. Conclusion: Our healthy human study showed the feasibility of fNIRS of cerebellum and PFC and closed-loop fNIRS-driven ctACS at 4 Hz, which may facilitate cerebellar cognitive function via the frontoparietal network. Future work needs to combine fNIRS with EEG for multi-modal imaging for closed-loop NIBS during operant conditioning.

Whole-brain white matter correlates of personality profiles predictive of subjective well-being

We investigated the white matter correlates of personality profiles predictive of subjective well-being. Using principal component analysis to first determine the possible personality profiles onto which core personality measures would load, we subsequently searched for whole-brain white matter correlations with these profiles. We found three personality profiles that correlated with the integrity of white matter tracts. The correlates of an “optimistic” personality profile suggest (a) an intricate network for self-referential processing that helps regulate negative affect and maintain a positive outlook on life, (b) a sustained capacity for visually tracking rewards in the environment and (c) a motor readiness to act upon the conviction that desired rewards are imminent. The correlates of a “short-term approach behavior” profile was indicative of minimal loss of integrity in white matter tracts supportive of lifting certain behavioral barriers, possibly allowing individuals to act more outgoing and carefree in approaching people and rewards. Lastly, a “long-term approach behavior” profile’s association with white matter tracts suggests lowered sensitivity to transient updates of stimulus-based associations of rewards and setbacks, thus facilitating the successful long-term pursuit of goals. Together, our findings yield convincing evidence that subjective well-being has its manifestations in the brain.

White matter microstructure in children and adolescents with ADHD

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A systematic review of diffusion MRI studies in children and adolescents with ADHD.

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46 studies included, encompassing multiple diffusion MRI techniques.

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Reduced white matter microstructure was reported in several studies.

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Mixed evidence linking white matter differences with specific cognitive processes.

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Common limitations included sample size, head motion and medication status.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Advances in diffusion magnetic resonance imaging (MRI) acquisition sequences and analytic techniques have led to growing body of evidence that abnormal white matter microstructure is a core pathophysiological feature of ADHD. This systematic review provides a qualitative assessment of research investigating microstructural organisation of white matter amongst children and adolescents with ADHD. This review included 46 studies in total, encompassing multiple diffusion MRI imaging techniques and analytic approaches, including whole-brain, region of interest and connectomic analyses. Whole-brain and region of interest analyses described atypical organisation of white matter microstructure in several white matter tracts: most notably in frontostriatal tracts, corpus callosum, superior longitudinal fasciculus, cingulum bundle, thalamic radiations, internal capsule and corona radiata. Connectomic analyses, including graph theory approaches, demonstrated global underconnectivity in connections between functionally specialised networks. Although some studies reported significant correlations between atypical white matter microstructure and ADHD symptoms or other behavioural measures there was no clear pattern of results. Interestingly however, many of the findings of disrupted white matter microstructure were in neural networks associated with key neuropsychological functions that are atypical in ADHD. Limitations to the extant research are outlined in this review and future studies in this area should carefully consider factors such as sample size, sex balance, head motion and medication status.

White Matter Hyperintensities after Five-Year Follow-Up and a Cross-Sectional FA Decrease in Bipolar I and Major Depressive Patients

INTRODUCTION

An increase in brain white matter hyperintensities (WMHs) and a decrease in white matter fractional anisotrophy (FA) have been detected in bipolar I (BPI), II (BPII), and major depressive disorder (MDD) patients. Their relationship, and differences in diagnostic groups are obscure. Longitudinal studies are rare.

OBJECTIVE

After 5-year follow-up, we evaluated WMHs in BPI, BPII, and MDD patients as compared with controls, and studied the effects of clinical variables. We also explored the associations of clinical variables with cross-sectional whole brain FA.

METHODS

Eight BPI, 8 BPII, 6 MDD patients, and 19 controls participated in magnetic resonance imaging at baseline and follow-up. Diffusion weighted imaging was included at follow-up. WMHs were rated by the Coffey scale, and a tract-based spatial statistics method was used for diffusion data. The general linear model, ANOVA, Fisher's exact, Wilcoxon sign, and Kruskal-Wallis tests were used for statistical analyses.

RESULTS

Periventricular WMHs were increased in BPI patients (p = 0.047) and associated with the duration of disorder and lifetime occurrence of substance use disorder (p = 0.018). FA decrease was found in the corpus callosum of BPI patients (p < 0.01). MDD patients showed FA decrease in the right cerebellar middle peduncle (RCMP) (p < 0.01). In BPI patients, the duration of disorder associated with FA increase in RCMP (p < 0.05). No FA decrease was detected in patients with WMHs as compared with those without.

CONCLUSIONS

Preceding illness burden associated modestly with WMHs, and FA increase in RCMP in BPI patients. MDD patients had FA decrease in RCMP. No association with FA decrease and WMHs was found.

Altered Interplay Among Large-Scale Brain Functional Networks Modulates Multi-Domain Anosognosia in Early Alzheimer’s Disease

Decline in self-awareness is a prevalent symptom in Alzheimer’s disease (AD). Current data suggest that an early breakdown in the brain’s default mode network (DMN) is closely associated with the main symptomatic features in AD patients. In parallel, the integrity of the DMN has been shown to be heavily implicated in retained self-awareness abilities in healthy individuals and AD patients. However, the global contribution to awareness skills of other large-scale networks is still poorly understood. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were acquired and pre-processed from 53 early-stage AD individuals. A group-level independent component analysis was run to isolate and reconstruct four intrinsic connectivity large-scale brain functional networks, namely left and right central executive fronto-parietal networks (FPN), salience network, and anterior and posterior DMN. Hypothesis-driven seed-based connectivity analyses were run to clarify the region-specific underpinnings of multi-domain anosognosia. Multiple regression models were run on large-scale network- and seed-based connectivity maps, including scores of memory, non-memory and total anosognosia obtained via the Measurement of Anosognosia Questionnaire. Memory anosognosia scores were associated with selective lower fronto-temporal connectivity and higher parieto-temporal connectivity. Non-memory anosognosia scores were associated with higher connectivity between the anterior DMN and the cerebellum, between the left medial prefrontal seeds and the contralateral prefrontal cortex, and between the left hippocampal seed and the left insula; lower connectivity was observed between the right prefrontal cortex and the right lingual seed. Lastly, total anosognosia scores were associated with large-scale network alterations, namely reduced left-FPN expression in the left posterior cingulate, reduced right-FPN expression in the left inferior lingual gyrus and adjacent inferior occipital cortex, and increased right-FPN expression in the right anterior cingulate. Seed-based analyses yielded significant connectivity differences only in the connectivity pattern associated with the left hippocampal seed by displaying lower intercommunication with the right prefrontal cortex, but higher connectivity with the left caudate nucleus. These findings support the hypothesis that alterations in functional connectivity of frontal lobe regions involved in executive-related mechanisms represent the neural correlates of domain-specific anosognosia in early AD. Up-regulated connectivity with subcortical structures appears to contribute to changes in the network dynamics interplay and fosters the appearance of anosognosia.

Mapping brain structural differences and neuroreceptor correlates in Parkinson's disease visual hallucinations

Parkinson's psychosis (PDP) describes a spectrum of symptoms that may arise in Parkinson's disease (PD) including visual hallucinations (VH). Imaging studies investigating the neural correlates of PDP have been inconsistent in their findings, due to differences in study design and limitations of scale. Here we use empirical Bayes harmonisation to pool together structural imaging data from multiple research groups into a large-scale mega-analysis, allowing us to identify cortical regions and networks involved in VH and their relation to receptor binding. Differences of morphometrics analysed show a wider cortical involvement underlying VH than previously recognised, including primary visual cortex and surrounding regions, and the hippocampus, independent of its role in cognitive decline. Structural covariance analyses point to the involvement of the attentional control networks in PD-VH, while associations with receptor density maps suggest neurotransmitter loss may be linked to the cortical changes.

Catching Wandering Minds with Tapping Fingers: Neural and Behavioral Insights into Task-unrelated Cognition

When the human mind wanders, it engages in episodes during which attention is focused on self-generated thoughts rather than on external task demands. Although the sustained attention to response task is commonly used to examine relationships between mind wandering and executive functions, limited executive resources are required for optimal task performance. In the current study, we aimed to investigate the relationship between mind wandering and executive functions more closely by employing a recently developed finger-tapping task to monitor fluctuations in attention and executive control through task performance and periodical experience sampling during concurrent functional magnetic resonance imaging (fMRI) and pupillometry. Our results show that mind wandering was preceded by increases in finger-tapping variability, which was correlated with activity in dorsal and ventral attention networks. The entropy of random finger-tapping sequences was related to activity in frontoparietal regions associated with executive control, demonstrating the suitability of this paradigm for studying executive functioning. The neural correlates of behavioral performance, pupillary dynamics, and self-reported attentional state diverged, thus indicating a dissociation between direct and indirect markers of mind wandering. Together, the investigation of these relationships at both the behavioral and neural level provided novel insights into the identification of underlying mechanisms of mind wandering.

ANKK1 and TH gene variants in combination with paternal maltreatment increase susceptibility to both cognitive and attentive impulsivity

Recent scientific findings suggest that dopamine exerts a central role on impulsivity, as well as that aversive life experiences may promote the high levels of impulsivity that often underlie violent behavior. To deepen our understanding of the complex gene by environment interplay on impulsive behavior, we genotyped six dopaminergic allelic variants (ANKK1-rs1800497, TH-rs6356, DRD4-rs1800955, DRD4-exonIII-VNTR, SLC6A3-VNTR and COMT-rs4680) in 655 US White male inmates convicted for violent crimes, whose impulsivity was assessed by BIS-11 (Barratt Impulsiveness Scale). Furthermore, in a subsample of 216 inmates from the whole group, we also explored the potential interplay between the genotyped dopaminergic variants and parental maltreatment measured by MOPS (Measure of Parental Style) in promoting impulsivity. We found a significant interaction among paternal MOPS scores, ANKK1-rs1800497-T allele and TH-rs6356-A allele, which increased the variance of BIS-11 cognitive/attentive scores explained by paternal maltreatment from 1.8 up to 20.5%. No direct association between any of the individual genetic variants and impulsivity was observed. Our data suggest that paternal maltreatment increases the risk of attentive/cognitive impulsivity and that this risk is higher in carriers of specific dopaminergic alleles that potentiate the dopaminergic neurotransmission. These findings add further evidence to the mutual role that genetics and early environmental factors exert in modulating human behavior and highlight the importance of childhood care interventions.

A thalamo-centric neural signature for restructuring negative self-beliefs

Negative self-beliefs are a core feature of psychopathology. Despite this, we have a limited understanding of the brain mechanisms by which negative self-beliefs are cognitively restructured. Using a novel paradigm, we had participants use Socratic questioning techniques to restructure negative beliefs during ultra-high resolution 7-Tesla functional magnetic resonance imaging (UHF 7 T fMRI) scanning. Cognitive restructuring elicited prominent activation in a fronto-striato-thalamic circuit, including the mediodorsal thalamus (MD), a group of deep subcortical nuclei believed to synchronize and integrate prefrontal cortex activity, but which has seldom been directly examined with fMRI due to its small size. Increased activity was also identified in the medial prefrontal cortex (MPFC), a region consistently activated by internally focused mental processing, as well as in lateral prefrontal regions associated with regulating emotional reactivity. Using Dynamic Causal Modelling (DCM), evidence was found to support the MD as having a strong excitatory effect on the activity of regions within the broader network mediating cognitive restructuring. Moreover, the degree to which participants modulated MPFC-to-MD effective connectivity during cognitive restructuring predicted their individual tendency to engage in repetitive negative thinking. Our findings represent a major shift from a cortico-centric framework of cognition and provide important mechanistic insights into how the MD facilitates key processes in cognitive interventions for common psychiatric disorders. In addition to relaying integrative information across basal ganglia and the cortex, we propose a multifaceted role for the MD whose broad excitatory pathways act to increase synchrony between cortical regions to sustain complex mental representations, including the self.

In vivo tractography of human locus coeruleus-relation to 7T resting state fMRI, psychological measures and single subject validity

The locus coeruleus (LC) in the brainstem as the main regulator of brain noradrenaline gains increasing attention because of its involvement in neurologic and psychiatric diseases and its relevance in general to brain function. In this study, we created a structural connectome of the LC nerve fibers based on in vivo MRI tractography to gain an understanding into LC connectivity and its impact on LC-related psychological measures. We combined our structural results with ultra-high field resting-state functional MRI to learn about the relationship between in vivo LC structural and functional connections. Importantly, we reveal that LC brain fibers are strongly associated with psychological measures of anxiety and alertness indicating that LC-noradrenergic connectivity may have an important role on brain function. Lastly, since we analyzed all our data in subject-specific space, we point out the potential of structural LC connectivity to reveal individual characteristics of LC-noradrenergic function on the single-subject level.

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.

Mapping the subcortical connectivity of the human default mode network

The default mode network (DMN) mediates self-awareness and introspection, core components of human consciousness. Therapies to restore consciousness in patients with severe brain injuries have historically targeted subcortical sites in the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia, with the goal of reactivating cortical DMN nodes. However, the subcortical connectivity of the DMN has not been fully mapped, and optimal subcortical targets for therapeutic neuromodulation of consciousness have not been identified. In this work, we created a comprehensive map of DMN subcortical connectivity by combining high-resolution functional and structural datasets with advanced signal processing methods. We analyzed 7 Tesla resting-state functional MRI (rs-fMRI) data from 168 healthy volunteers acquired in the Human Connectome Project. The rs-fMRI blood-oxygen-level-dependent (BOLD) data were temporally synchronized across subjects using the BrainSync algorithm. Cortical and subcortical DMN nodes were jointly analyzed and identified at the group level by applying a novel Nadam-Accelerated SCAlable and Robust (NASCAR) tensor decomposition method to the synchronized dataset. The subcortical connectivity map was then overlaid on a 7 Tesla 100 µm ex vivo MRI dataset for neuroanatomic analysis using automated segmentation of nuclei within the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia. We further compared the NASCAR subcortical connectivity map with its counterpart generated from canonical seed-based correlation analyses. The NASCAR method revealed that BOLD signal in the central lateral nucleus of the thalamus and ventral tegmental area of the midbrain is strongly correlated with that of the DMN. In an exploratory analysis, additional subcortical sites in the median and dorsal raphe, lateral hypothalamus, and caudate nuclei were correlated with the cortical DMN. We also found that the putamen and globus pallidus are negatively correlated (i.e., anti-correlated) with the DMN, providing rs-fMRI evidence for the mesocircuit hypothesis of human consciousness, whereby a striatopallidal feedback system modulates anterior forebrain function via disinhibition of the central thalamus. Seed-based analyses yielded similar subcortical DMN connectivity, but the NASCAR result showed stronger contrast and better spatial alignment with dopamine immunostaining data. The DMN subcortical connectivity map identified here advances understanding of the subcortical regions that contribute to human consciousness and can be used to inform the selection of therapeutic targets in clinical trials for patients with disorders of consciousness.

The neurobiology of treatment-resistant depression: A systematic review of neuroimaging studies

Treatment-resistant depression (TRD) is a debilitating condition associated with higher medical costs, increased illness burden, and reduced quality of life compared to non-treatment-resistant major depressive disorder (MDD). The question arises whether TRD can be considered a distinct MDD sub-type based on neurobiological features. To answer this question we conducted a systematic review of neuroimaging studies investigating the neurobiological differences between TRD and non-TRD. Our main findings are that patients with TRD show 1) reduced functional connectivity (FC) within the default mode network (DMN), 2) reduced FC between components of the DMN and other brain areas, and 3) hyperactivity of DMN regions. In addition, aberrant activity and FC in the occipital lobe may play a role in TRD. The main limitations of most studies were related to inherent confounding factors for comparing TRD with non-TRD, such as differences in disease chronicity/severity and medication history. Future studies may use prospective longitudinal neuroimaging designs to delineate which effects are present in treatment-naive patients and which effects are the result of disease progression.

Dopaminergic pathways and resting-state functional connectivity in Parkinson's disease with freezing of gait

Freezing of gait is a common phenomenon of advanced Parkinson's disease. Besides locomotor function per se, a role of cognitive deficits has been suggested. Limited evidence of associated dopaminergic deficits points to caudatal denervation. Further, altered functional connectivity within resting-state networks with importance for cognitive functions has been described in freezers. A potential pathophysiological link between both imaging findings has not yet been addressed. The current study sought to investigate the association between dopaminergic pathway dysintegrity and functional dysconnectivity in relation to FOG severity and cognitive performance in a well-characterized PD cohort undergoing high-resolution 6-[18F]fluoro-L-Dopa PET and functional MRI. The freezing of gait questionnaire was applied to categorize patients (n = 59) into freezers and non-freezers. A voxel-wise group comparison of 6-[18F]fluoro-L-Dopa PET scans with focus on striatum was performed between both well-matched and neuropsychologically characterized patient groups. Seed-to-voxel resting-state functional connectivity maps of the resulting dopamine depleted structures and dopaminergic midbrain regions were created and compared between both groups. For a direct between-group comparison of dopaminergic pathway integrity, a molecular connectivity approach was conducted on 6-[18F]fluoro-L-Dopa scans. With respect to striatal regions, freezers showed significant dopaminergic deficits in the left caudate nucleus, which exhibited altered functional connectivity with regions of the visual network. Regarding midbrain structures, the bilateral ventral tegmental area showed altered functional coupling to regions of the default mode network. An explorative examination of the integrity of dopaminergic pathways by molecular connectivity analysis revealed freezing-associated impairments in mesolimbic and mesocortical pathways. This study represents the first characterization of a link between dopaminergic pathway dysintegrity and altered functional connectivity in Parkinson's disease with freezing of gait and hints at a specific involvement of striatocortical and mesocorticolimbic pathways in freezers.

Decomposing MRI phenotypic heterogeneity in epilepsy: a step towards personalized classification

In drug-resistant temporal lobe epilepsy (TLE), precise predictions of drug response, surgical outcome, and cognitive dysfunction at an individual level remain challenging. A possible explanation may lie in the dominant "one-size-fits-all" group-level analytical approaches that does not allow parsing inter-individual variations along the disease spectrum. Conversely, analyzing inter-patient heterogeneity is increasingly recognized as a step towards person-centered care. Here, we utilized unsupervised machine learning to estimate latent relations (or disease factors) from 3 T multimodal MRI features (cortical thickness, hippocampal volume, FLAIR, T1/FLAIR, diffusion parameters) representing whole-brain patterns of structural pathology in 82 TLE patients. We assessed the specificity of our approach against age- and sex-matched healthy individuals and a cohort of frontal lobe epilepsy patients with histologically-verified focal cortical dysplasia. We identified four latent disease factors variably co-expressed within each patient and characterized by ipsilateral hippocampal microstructural alterations, loss of myelin and atrophy (Factor-1), bilateral paralimbic and hippocampal gliosis (Factor-2), bilateral neocortical atrophy (Factor-3), bilateral white matter microstructural alterations (Factor-4). Bootstrap analysis and parameter variations supported high stability and robustness of these factors. Moreover, they were not expressed in healthy controls and only negligibly in disease controls, supporting specificity. Supervised classifiers trained on latent disease factors could predict patient-specific drug-response in 76 ± 3% and postsurgical seizure outcome in 88 ± 2%, outperforming classifiers that did not operate on latent factor information. Latent factor models predicted inter-patient variability in cognitive dysfunction (verbal IQ: r = 0.40 ± 0.03; memory: r = 0.35 ± 0.03; sequential motor tapping: r = 0.36 ± 0.04), again outperforming baseline learners. Data-driven analysis of disease factors provides a novel appraisal of the continuum of interindividual variability, which is likely determined by multiple interacting pathological processes. Incorporating interindividual variability is likely to improve clinical prognostics.

Body-mind relaxation meditation modulates the thalamocortical functional connectivity in major depressive disorder: a preliminary resting-state fMRI study

Mindfulness-based interventions such as meditation have increasingly been utilized for the treatment of psychological disorders and have been shown to be effective in the treatment of depression and relapse prevention. However, it remains largely unclear the neural mechanism of the therapeutic effects of meditation among depressed individuals. In this study, we investigated how body-mind relaxation meditation (BMRM) can modulate the thalamocortical functional connectivity (FC) in major depressive disorder patients and healthy controls. In the present study, we recruited 21 medication-naive adolescents with major depressive disorder (MDDs) and 24 matched healthy controls (HCs). We designed an audio recording to induce body-mind relaxation meditation. Resting-state fMRI (rs-fMRI) scans were collected before and after the BMRM intervention in both groups. The thalamus subregions were defined according to the Human Brainnetome Atlas, and functional connectivity (FC) was measured and compared to find brain regions that were affected by the BMRM intervention. Before the BMRM intervention, MDDs showed reduced FC of the bilateral precuneus/post cingulate cortex with the left posterior parietal thalamus and left caudal temporal thalamus, as well as an increased FC of the left occipital thalamus with the left medial frontal cortex. Moreover, aberrant FCs in MDDs at baseline were normalized following the BMRM intervention. After the BMRM intervention, both MDDs and HCs showed decreased FC between the left rostral temporal thalamus and the left inferior occipital. Given the small sample used in this study, future studies are warranted to evaluate the generalizability of these findings. Our findings suggest that BMRM is associated with changes in thalamocortical functional connectivity in MDDs. BMRM may act by strengthening connections between the thalamus and the default mode network, which are involved in a variety of high-level functioning, such as attention and self-related processes.

Bridging large-scale cortical networks: Integrative and function-specific hubs in the thalamus

The thalamus is critical for the brain's integrative hub functions; however, the localization and characterization of the different thalamic hubs remain unclear. Using a voxel-level network measure called functional connectivity overlap ratio (FCOR), we examined the thalamus' association with large-scale resting-state networks (RSNs) to elucidate its connector hub roles. Connections to the core-neurocognitive networks were localized in the anterior and medial parts, such as the anteroventral and mediodorsal nuclei areas. Regions functionally connected to the sensorimotor network were distinctively located around the lateral pulvinar nucleus but to a limited extent. Prominent connector hubs include the anteroventral, ventral lateral, and mediodorsal nuclei with functional connections to multiple RSNs. These findings suggest that the thalamus, with extensive connections to most of the RSNs, is well placed as a critical integrative functional hub and could play an important role for functional integration facilitating brain functions associated with primary processing and higher cognition.

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Multiple large-scale cortical networks converged in the thalamus

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Neurocognitive associated hub existed in the anterior and medial region

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Control-processing hub localized in the intermediate thalamus

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Sensorimotor network was located around the lateral pulvinar nucleus

Flexible brain transitions between hierarchical network segregation and integration associated with cognitive performance during a multisource interference task

Cognition involves locally segregated and globally integrated processing. This process is hierarchically organized and linked to evidence from hierarchical modules in brain networks. However, researchers have not clearly determined how flexible transitions between these hierarchical processes are associated with cognitive behavior. Here, we designed a multisource interference task (MSIT) and introduced the nested-spectral partition (NSP) method to detect hierarchical modules in brain functional networks. By defining hierarchical segregation and integration across multiple levels, we showed that the MSIT requires higher network segregation in the whole brain and most functional systems but generates higher integration in the control system. Meanwhile, brain networks have more flexible transitions between segregated and integrated configurations in the task state. Crucially, higher functional flexibility in the resting state, less flexibility in the task state and more efficient switching of the brain from resting to task states were associated with better task performance. Our hierarchical modular analysis was more effective at detecting alterations in functional organization and the phenotype of cognitive performance than graph-based network measures at a single level.

Acute Brain Activation Patterns of High- Versus Low-Frequency Stimulation of the Anterior Nucleus of the Thalamus During Deep Brain Stimulation for Epilepsy

BACKGROUND

Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is an increasingly utilized treatment of drug-resistant epilepsy. To date, the effect of high-frequency stimulation (HFS) vs low-frequency stimulation (LFS) in ANT DBS is poorly understood.

OBJECTIVE

To assess differences in the acute effect of LFS vs HFS in ANT DBS utilizing blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI).

METHODS

In this prospective study of 5 patients with ANT DBS for epilepsy, BOLD activation and deactivation were modeled for 145-Hz and 30-Hz ANT stimulation using an fMRI block design. Data were analyzed with a general linear model and combined via 2-stage mixed-effects analysis. Z-score difference maps were nonparametrically thresholded using cluster threshold of z > 3.1 and a (corrected) cluster significance threshold of P = .05.

RESULTS

HFS produced significantly greater activation within multiple regions, in particular the limbic and default mode network (DMN). LFS produced minimal activation and failed to produce significant activation within these same networks. HFS produced widespread cortical and subcortical deactivation sparing most of the limbic and DMN regions. Meanwhile, LFS produced deactivation in most DMN and limbic structures.

CONCLUSION

Our results show that HFS and LFS produce substantial variability in both local and downstream network effects. In particular, largely opposing effects were identified within the limbic network and DMN. These findings may serve as a mechanistic basis for understanding the potential of HFS vs LFS in various epilepsy syndromes.

Alterations in Resting-State Functional MRI Connectivity Related to Cognitive Changes in Intracranial Dural Arteriovenous Fistulas Before and After Embolization Treatment

BACKGROUND

Cognitive decline is a non-hemorrhagic, major complication of intracranial dural arteriovenous fistula (DAVF), thought to be primarily related to venous hypertension. However, imaging features to predict cognitive decline are scanty in the literature.

PURPOSE

To evaluate functional connectivity (FC) changes of resting-state networks (RSNs) in DAVF before and after treatment and its relation to cognitive impairment.

STUDY TYPE

Prospective.

SUBJECTS

DAVF subjects were screened for inclusion. Pre-embolization (N = 33, mean age 45.9 years, 29 males), 1 month post-embolization (N = 20, mean age 42.7 years, 19 males), and healthy controls (HC, N = 33, mean age 45.09 years, 27 males).

FIELD STRENGTH/SEQUENCE

3.0 T, resting-state functional magnetic resonance imaging (MRI), three-dimensional (3D) T1, T₂ fast spin echo (FSE), diffusion weighted imaging (DWI), susceptibility weighted imaging (SWI), fluid-attenuated inversion recovery, and time of flight.

ASSESSMENT

Data quality assessment was performed. FC analysis was done using group independent component analysis (ICA) and seed to voxel analysis. Neuropsychology (NP) scores of patients were compared with HC and correlated with FC changes.

STATISTICAL TESTS

Voxel-wise parametric T-statistics for F-test was executed in FC analysis (p-FDR corrected <0.05). NP scores between DAVF group and HC group were compared using one-way analysis of variance with post hoc Bonferroni correction (P < 0.05).

RESULTS

Both RSNs analysis methods showed reduced FC at the precuneus-posterior cingulate cortex (PC-PCC) of default mode network (DMN), anterior cingulate cortex (ACC) of the salience network (SN), and possible compensatory increased connectivity at the frontoparietal (FPN) and dorsal attention (DAN) networks. DAVF with low NP scores showed reduced FC at DMN and SN and minimal to absent connectivity at FPN and DAN. At post-embolization 1-month follow-up, improvement in FC at PC-PCC of DMN and ACC of SN were noted.

DATA CONCLUSION

RS-fMRI in DAVF displayed FC changes that may be related to cognitive decline and its subsequent reversibility after treatment. FC changes at DMN, SN, FPN, and DAN were linked to cognitive decline and the corresponding NP scores.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Global hippocampal and selective thalamic nuclei atrophy differentiate chronic TBI from Non-TBI

Traumatic brain injury (TBI) may increase susceptibility to neurodegenerative diseases later in life. One neurobiological parallel between chronic TBI and neurodegeneration may be accelerated aging and the nature of atrophy across subcortical gray matter structures. The main aim of the present investigation is to evaluate and rank the degree that subcortical gray matter atrophy differentiates chronic moderate-severe TBI from non-TBI participants by evaluating morphometric differences between groups. Forty individuals with moderate-severe chronic TBI (9.23 yrs from injury) and 33 healthy controls (HC) underwent high resolution 3D T1-weighted structural magnetic resonance imaging. Whole brain volume was classified into white matter, cortical and subcortical gray matter structures with hippocampi and thalami further segmented into subfields and nuclei, respectively. Extensive atrophy was observed across nearly all brain regions for chronic TBI participants. A series of multivariate logistic regression models identified subcortical gray matter structures of the hippocampus and thalamus as the most sensitive to differentiating chronic TBI from non-TBI participants (McFadden R² = .36, p < .001). Further analyses revealed the pattern of hippocampal atrophy to be global, occurring across nearly all subfields. The pattern of thalamic atrophy appeared to be much more selective and non-uniform, with largest between-group differences evident for nuclei bordering the ventricles. Subcortical gray matter was negatively correlated with time since injury (r = -.31, p = .054), while white matter and cortical gray matter were not. Cognitive ability was lower in the chronic TBI group (Cohen's d = .97, p = .003) and correlated with subcortical structures including the pallidum (r² = .23, p = .038), thalamus (r² = .36, p = .007) and ventral diencephalon (r² = .23, p = .036). These data may support an accelerated aging hypothesis in chronic moderate-severe TBI that coincides with a similar neuropathological profile found in neurodegenerative diseases.

Cortical Morphology and White Matter Tractography of Three Phylogenetically Distant Primates: Evidence for a Simian Elaboration

Comparative neuroimaging has been used to identify changes in white matter architecture across primate species phylogenetically close to humans, but few have compared the phylogenetically distant species. Here, we acquired postmortem diffusion imaging data from ring-tailed lemurs (Lemur catta), black-capped squirrel monkeys (Saimiri boliviensis), and rhesus macaques (Macaca mulatta). We were able to establish templates and surfaces allowing us to investigate sulcal, cortical, and white matter anatomy. The results demonstrate an expansion of the frontal projections of the superior longitudinal fasciculus complex in squirrel monkeys and rhesus macaques compared to ring-tailed lemurs, which correlates with sulcal anatomy and the lemur’s smaller prefrontal granular cortex. The connectivity of the ventral pathway in the parietal region is also comparatively reduced in ring-tailed lemurs, with the posterior projections of the inferior longitudinal fasciculus not extending toward parietal cortical areas as in the other species. In the squirrel monkeys we note a very specific occipito-parietal anatomy that is apparent in their surface anatomy and the expansion of the posterior projections of the optical radiation. Our study supports the hypothesis that the connectivity of the prefrontal-parietal regions became relatively elaborated in the simian lineage after divergence from the prosimian lineage.

Ventral pallidum regulates the default mode network, controlling transitions between internally and externally guided behavior

Daily life requires transitions between performance of well-practiced, automatized behaviors reliant upon internalized representations and behaviors requiring external focus. Such transitions involve differential activation of the default mode network (DMN), a group of brain areas associated with inward focus. We asked how optogenetic modulation of the ventral pallidum (VP), a subcortical DMN node, impacts task switching between internally to externally guided lever-pressing behavior in the rat. Excitation of the VP dramatically compromised acquisition of an auditory discrimination task, trapping animals in a DMN state of automatized internally focused behavior and impairing their ability to direct attention to external sensory stimuli. VP inhibition, on the other hand, facilitated task acquisition, expediting escape from the DMN brain state, thereby allowing rats to incorporate the contingency changes associated with the auditory stimuli. We suggest that VP, instant by instant, regulates the DMN and plays a deterministic role in transitions between internally and externally guided behaviors.

Structural and Functional Default Mode Network Connectivity and Antipsychotic Treatment Response in Medication-Naïve First Episode Psychosis Patients

Introduction

Only a few studies have comprehensively characterized default mode network (DMN) pathology on a structural and functional level, and definite conclusions cannot be drawn due to antipsychotic medication exposure and illness chronicity. The objective of this study was to characterize DMN pathology in medication-naïve first episode psychosis (FEP) patients, and determine if DMN structural and functional connectivity (FC) have potential utility as a predictor for subsequent antipsychotic treatment response.

Methods

Diffusion imaging and resting state FC data from 42 controls and 52 FEP were analyzed. Patients then received 16 weeks of antipsychotic treatment. Using region of interest analyses, we quantified FC of the DMN and structural integrity of the white matter tracts supporting DMN function. We then did linear regressions between DMN structural and FC indices and antipsychotic treatment response.

Results

We detected reduced DMN fractional anisotropy and axial diffusivity in FEP compared to controls. No DMN FC abnormalities nor correlations between DMN structural and FC were found. Finally, DMN fractional anisotropy and radial diffusivity were associated with response to treatment.

Conclusion

Our study highlights the critical role of the DMN in the pathophysiology suggesting that axonal damage may already be present in FEP patients. We also demonstrated that DMN pathology is clinically relevant, as greater structural DMN alterations were associated with a less favorable clinical response to antipsychotic medications.

Frontocerebellar gray matter plasticity in alcohol use disorder linked to abstinence

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GM loss in frontocerebellar circuit predicts relapse.

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GM recovery in AUD involves distinct neural processes.

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Recovery is not a reversal of any AUD-related GM damage.

Alcohol use disorder (AUD) is associated with brain-wide gray matter (GM) reduction, but the frontocerebellar circuit seems specifically affected by chronic alcohol consumption. T1 weighted MRI data from 38 AUD patients at one month of sobriety and three months later and from 25 controls were analyzed using voxel-based morphometry (VBM) and a graph theory approach (GTA). We investigated the degree to which the frontocerebellar circuit’s integration within the brain’s GM network architecture was altered by AUD-related GM volume loss. The VBM analyses did not reveal significant GM volume differences between relapsers and abstainers at either timepoint, but future relapsers at both timepoints had significantly less GM than controls in the frontocerebellar circuit. Abstainers, who at baseline also showed the most pronounced GM loss in the thalamus, showed a significant circuit-wide GM increase with inter-scan abstinence. The post-hoc GTAs revealed a persistent diffuse global atrophy in both AUD groups at follow-up relative to controls and different recovery patterns in the two AUD groups. Our findings suggest that future relapsers do not just present with a more severe expression of the same AUD consequences than abstainers, but that AUD affects the frontocerebellar circuit differently in relapsers and abstainers.

The role of the medial prefrontal cortex in cognition, ageing and dementia

Humans require a plethora of higher cognitive skills to perform executive functions, such as reasoning, planning, language and social interactions, which are regulated predominantly by the prefrontal cortex. The prefrontal cortex comprises the lateral, medial and orbitofrontal regions. In higher primates, the lateral prefrontal cortex is further separated into the respective dorsal and ventral subregions. However, all these regions have variably been implicated in several fronto-subcortical circuits. Dysfunction of these circuits has been highlighted in vascular and other neurocognitive disorders. Recent advances suggest the medial prefrontal cortex plays an important regulatory role in numerous cognitive functions, including attention, inhibitory control, habit formation and working, spatial or long-term memory. The medial prefrontal cortex appears highly interconnected with subcortical regions (thalamus, amygdala and hippocampus) and exerts top-down executive control over various cognitive domains and stimuli. Much of our knowledge comes from rodent models using precise lesions and electrophysiology readouts from specific medial prefrontal cortex locations. Although, anatomical disparities of the rodent medial prefrontal cortex compared to the primate homologue are apparent, current rodent models have effectively implicated the medial prefrontal cortex as a neural substrate of cognitive decline within ageing and dementia. Human brain connectivity-based neuroimaging has demonstrated that large-scale medial prefrontal cortex networks, such as the default mode network, are equally important for cognition. However, there is little consensus on how medial prefrontal cortex functional connectivity specifically changes during brain pathological states. In context with previous work in rodents and non-human primates, we attempt to convey a consensus on the current understanding of the role of predominantly the medial prefrontal cortex and its functional connectivity measured by resting-state functional MRI in ageing associated disorders, including prodromal dementia states, Alzheimer's disease, post-ischaemic stroke, Parkinsonism and frontotemporal dementia. Previous cross-sectional studies suggest that medial prefrontal cortex functional connectivity abnormalities are consistently found in the default mode network across both ageing and neurocognitive disorders such as Alzheimer's disease and vascular cognitive impairment. Distinct disease-specific patterns of medial prefrontal cortex functional connectivity alterations within specific large-scale networks appear to consistently feature in the default mode network, whilst detrimental connectivity alterations are associated with cognitive impairments independently from structural pathological aberrations, such as grey matter atrophy. These disease-specific patterns of medial prefrontal cortex functional connectivity also precede structural pathological changes and may be driven by ageing-related vascular mechanisms. The default mode network supports utility as a potential biomarker and therapeutic target for dementia-associated conditions. Yet, these associations still require validation in longitudinal studies using larger sample sizes.

Determinants and modulators of human social decisions

Social decision making is a highly complex process that involves diverse cognitive mechanisms, and it is driven by the precise processing of information from both the environment and from the internal state. On the one hand, successful social decisions require close monitoring of others' behavior, in order to track their intentions; this can guide not only decisions involving other people, but also one's own choices and preferences. On the other hand, internal states such as own reward or changes in hormonal and neurotransmitter states shape social decisions and their underlying neural function. Here, we review the current literature on modulators and determinants of human social decisions.

The squirrel monkey model in clinical neuroscience

Clinical neuroscience research relying on animal models brought valuable translational insights into the function and pathologies of the human brain. The anatomical, physiological, and behavioural similarities between humans and mammals have prompted researchers to study cerebral mechanisms at different levels to develop and test new treatments. The vast majority of biomedical research uses rodent models, which are easily manipulable and have a broadly resembling organisation to the human nervous system but cannot satisfactorily mimic some disorders. For these disorders, macaque monkeys have been used as they have a more comparable central nervous system. Still, this research has been hampered by limitations, including high costs and reduced samples. This review argues that a squirrel monkey model might bridge the gap by complementing translational research from rodents, macaque, and humans. With the advent of promising new methods such as ultrasound imaging, tool miniaturisation, and a shift towards open science, the squirrel monkey model represents a window of opportunity that will potentially fuel new translational discoveries in the diagnosis and treatment of brain pathologies.

Longitudinal change in hippocampal and dorsal anterior insulae functional connectivity in subjective cognitive decline

BACKGROUND

Subjective cognitive decline, perceived worsening of cognitive ability without apparent performance issues on clinical assessment, may be an important precursor to dementia. While previous cross-sectional research has demonstrated aberrant brain functional connectivity in subjective cognitive decline, longitudinal evaluation remains limited.

METHODS

Here, we examined trajectories of functional connectivity over three measurement occasions ~18 months apart, using voxelwise latent growth models in cognitively unimpaired older adults with varying self-report of subjective cognitive decline (N = 69).

RESULTS

We found that individuals who reported a greater degree of subjective cognitive decline showed a larger subsequent decrease in connectivity between components of the default mode network and increase in connectivity between salience and default mode network components. The change in functional connectivity was observed in the absence of change in cognitive performance.

CONCLUSION

The results indicate that functional brain changes may underly the experience of cognitive decline before deterioration reaches a level detected by formal cognitive assessment.

Estimating Gender and Age from Brain Structural MRI of Children and Adolescents: A 3D Convolutional Neural Network Multitask Learning Model

Despite recent advances, assessing biological measurements for neuropsychiatric disorders is still a challenge, where confounding variables such as gender and age (as a proxy for neurodevelopment) play an important role. This study explores brain structural magnetic resonance imaging (sMRI) from two public data sets (ABIDE-II and ADHD-200) with healthy control (HC, N = 894), autism spectrum disorder (ASD, N = 251), and attention deficit hyperactivity disorder (ADHD, N = 357) individuals. We used gray and white matter preprocessed via voxel-based morphometry (VBM) to train a 3D convolutional neural network with a multitask learning strategy to estimate gender, age, and mental health status from structural brain differences. Gradient-based methods were employed to generate attention maps, providing clinically relevant identification of most representative brain regions for models' decision-making. This approach resulted in satisfactory predictions for gender and age. ADHD-200-trained models, evaluated in 10-fold cross-validation procedures on test set, obtained a mean absolute error (MAE) of 1.43 years (±0.22 SD) for age prediction and an area under the curve (AUC) of 0.85 (±0.04 SD) for gender classification. In out-of-sample validation, the best-performing ADHD-200 models satisfactorily predicted age (MAE = 1.57 years) and gender (AUC = 0.89) in the ABIDE-II data set. The models' accuracy was in line with the current state-of-the-art machine learning applications in neuroimaging. Key regions for models' accuracy were presented as a meaningful graphical output. New implementations, such as the use of VBM along with a 3D convolutional neural network multitask learning model and a brain imaging graphical output, reinforce the relevance of the proposed workflow.