Activity In Brain Regions Research Articles

Real-time motion-enabling positron emission tomography of the brain of upright ambulatory humans

BackgroundMobile upright PET devices have the potential to enable previously impossible neuroimaging studies. Currently available options are imagers with deep brain coverage that severely limit head/body movements or imagers with upright/motion enabling properties that are limited to only covering the brain surface.MethodsIn this study, we test the feasibility of an upright, motion-compatible brain imager, our Ambulatory Motion-enabling Positron Emission Tomography (AMPET) helmet prototype, for use as a neuroscience tool by replicating a variant of a published PET/fMRI study of the neurocorrelates of human walking. We validate our AMPET prototype by conducting a walking movement paradigm to determine motion tolerance and assess for appropriate task related activity in motor-related brain regions. Human participants (n = 11 patients) performed a walking-in-place task with simultaneous AMPET imaging, receiving a bolus delivery of F18-Fluorodeoxyglucose.ResultsHere we validate three pre-determined measure criteria, including brain alignment motion artifact of less than <2 mm and functional neuroimaging outcomes consistent with existing walking movement literature.ConclusionsThe study extends the potential and utility for use of mobile, upright, and motion-tolerant neuroimaging devices in real-world, ecologically-valid paradigms. Our approach accounts for the real-world logistics of an actual human participant study and can be used to inform experimental physicists, engineers and imaging instrumentation developers undertaking similar future studies. The technical advances described herein help set new priorities for facilitating future neuroimaging devices and research of the human brain in health and disease.

Brain regions supporting retrieval of words drawn at encoding: fMRI evidence for multimodal reactivation.

Memory for words that are drawn or sketched by the participant, rather than written, during encoding is typically superior. While this drawing benefit has been reliably demonstrated in recent years, there has yet to be an investigation of its neural basis. Here, we asked participants to either create drawings, repeatedly write, or list physical characteristics depicting each target word during encoding. Participants then completed a recognition memory test for target words while undergoing functional magnetic resonance imaging (fMRI). Behavioural results showed memory was significantly higher for words drawn than written, replicating the typical drawing effect. Memory for words whose physical characteristics were listed at encoding was also higher than for those written repeatedly, but lower than for those drawn. Voxel-wise analyses of fMRI data revealed two distributed sets of brain regions more active for items drawn relative to written, the left angular gyrus (BA 39) and bilateral frontal (BA 10) regions, suggesting integration and self-referential processing during retrieval of drawn words. Brain-behaviour correlation analyses showed that the size of one's memory benefit for words drawn relative to written at encoding was positively correlated with activation in brain regions linked to visual representation and imagery (BA 17 and cuneus) and motor planning (premotor and supplementary motor areas; BA 6). This study suggests that drawing benefits memory by coactivating multiple sensory traces. Target words drawn during encoding are subsequently remembered by re-engaging visual, motoric, and semantic representations.

Central autonomic network dysfunction and plasma Alzheimer’s disease biomarkers in older adults

BackgroundHigher order regulation of autonomic function is maintained by the coordinated activity of specific cortical and subcortical brain regions, collectively referred to as the central autonomic network (CAN). Autonomic changes are frequently observed in Alzheimer’s disease (AD) and dementia, but no studies to date have investigated whether plasma AD biomarkers are associated with CAN functional connectivity changes in at risk older adults.MethodsIndependently living older adults (N = 122) without major neurological or psychiatric disorder were recruited from the community. Participants underwent resting-state brain fMRI and a CAN network derived from a voxel-based meta-analysis was applied for overall, sympathetic, and parasympathetic CAN connectivity using the CONN Functional Toolbox. Sensorimotor network connectivity was studied as a negative control. Plasma levels of amyloid (Aβ42, Aβ40), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were assessed using digital immunoassay. The relationship between plasma AD biomarkers and within-network functional connectivity was studied using multiple linear regression adjusted for demographic covariates and Apolipoprotein E (APOE) genotype. Interactive effects with APOE4 carrier status were also assessed.ResultsAll autonomic networks were positively associated with Aβ42/40 ratio and remained so after adjustment for age, sex, and APOE4 carrier status. Overall and parasympathetic networks were negatively associated with GFAP. The relationship between the parasympathetic CAN and GFAP was moderated by APOE4 carrier status, wherein APOE4 carriers with low parasympathetic CAN connectivity displayed the highest plasma GFAP concentrations (B = 910.00, P = .004). Sensorimotor connectivity was not associated with any plasma AD biomarkers, as expected.ConclusionThe present study findings suggest that CAN function is associated with plasma AD biomarker levels. Specifically, lower CAN functional connectivity is associated with decreased plasma Aβ42/40, indicative of cerebral amyloidosis, and increased plasma GFAP in APOE4 carriers at risk for AD. These findings could suggest higher order autonomic and parasympathetic dysfunction in very early-stage AD, which may have clinical implications.

Time-varying functional connectivity as Wishart processes

Abstract We investigate the utility of Wishart processes (WPs) for estimating time-varying functional connectivity (TVFC), which is a measure of changes in functional coupling as the correlation between brain region activity in functional magnetic resonance imaging (fMRI). The WP is a stochastic process on covariance matrices that can model dynamic covariances between time series, which makes it a natural fit to this task. Recent advances in scalable approximate inference techniques and the availability of robust open-source libraries have rendered the WP practically viable for fMRI applications. We introduce a comprehensive benchmarking framework to assess WP performance compared with a selection of established TVFC estimation methods. The framework comprises simulations with specified ground-truth covariance structures, a subject phenotype prediction task, a test-retest study, a brain state analysis, an external stimulus prediction task, and a novel data-driven imputation benchmark. The WP performed competitively across all the benchmarks. It outperformed a sliding window (SW) approach with adaptive cross-validated window lengths and a dynamic conditional correlation (DCC)-multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) baseline on the external stimulus prediction task, while being less prone to false positives in the TVFC null models.

Effects of motor imagery using virtual reality on pain sensitivity and affect in healthy individuals: a prospective randomized crossover study.

Exercise induces a hypoalgesic response and improves affect. However, some individuals are unable to exercise for various reasons. Motor imagery, involving kinesthetic and visual imagery without physical movement, activates brain regions associated with these benefits and could be an alternative for those unable to exercise. Virtual reality also enhances motor imagery performance because of its illusion and embodiment. Therefore, we examined the effects of motor imagery combined with virtual reality on pain sensitivity and affect in healthy individuals. Randomized crossover study. Laboratory. Thirty-six participants (women: 18) were included. Each participant completed three 10-min experimental sessions, comprising actual exercise, motor imagery only, and motor imagery combined with virtual reality. Hypoalgesic responses and affective improvement were assessed using the pressure-pain threshold and the Positive and Negative Affect Schedule, respectively. All interventions significantly increased the pressure-pain threshold at the thigh (P < .001). Motor imagery combined with virtual reality increased the pressure-pain threshold more than motor imagery alone, but the threshold was similar to that of actual exercise (both P ≥ .05). All interventions significantly decreased the negative affect of the Positive and Negative Affect Schedule (all P < .05). Motor imagery combined with virtual reality exerted hypoalgesic and affective-improvement effects similar to those of actual exercise. The study was enrolled in the UMIN Clinical Trials Registry (registration number: UMIN000046095). The website for registration information is https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000052614.

Alterations in dynamic regional homogeneity within default mode network in patients with thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO) is a significant autoimmune eye disease known for causing exophthalmos and substantial optic nerve damage. Prior investigations have solely focused on static functional MRI (fMRI) scans of the brain in TAO patients, neglecting the assessment of temporal variations in local brain activity. This study aimed to characterize alterations in dynamic regional homogeneity (dReHo) in TAO patients and differentiate between TAO patients and healthy controls using support vector machine (SVM) classification. Thirty-two patients with TAO and 32 healthy controls underwent resting-state fMRI scans. We calculated dReHo using sliding-window methods to evaluate changes in regional brain activity and compared these findings between the two groups. Subsequently, we employed SVM, a machine learning algorithm, to investigate the potential use of dReHo maps as diagnostic markers for TAO. Compared to healthy controls, individuals with active TAO demonstrated significantly higher dReHo values in the right angular gyrus, left precuneus, right inferior parietal as well as the left superior parietal gyrus. The SVM model demonstrated an accuracy ranging from 65.62 to 68.75% in distinguishing between TAO patients and healthy controls based on dReHo variability in these identified brain regions, with an area under the curve of 0.70 to 0.76. TAO patients showed increased dReHo in default mode network-related brain regions. The accuracy of classifying TAO patients and healthy controls based on dReHo was notably high. These results offer new insights for investigating the pathogenesis and clinical diagnostic classification of individuals with TAO.

Neural basis of reward expectancy inducing proactive aggression.

Proactive aggression refers to deliberate and unprovoked behavior, typically motivated by personal gain or expected reward. Reward expectancy is generally recognized as a critical factor that may influence proactive aggression, but its neural mechanisms remain unknown. We conducted a task-based functional magnetic resonance imaging (fMRI) experiment to investigate the relationship between reward expectancy and proactive aggression. 37 participants (20 females, mean age = 20.8 ± 1.42, age range = 18-23 years) completed a reward-harm task. In the experiment, reward valence expectancy and reward possibility expectancy were manipulated respectively by varying amounts (low: 0.5-1.5 yuan; high: 10.5-11.5 yuan) and possibilities (low: 10%-30%; high: 70%-90%) of money that participants could obtain by choosing to aggress. Participants received fMRI scans throughout the experiment. Brain activation regions associated with reward expectancy mainly involve the middle frontal gyrus, lingual gyrus, inferior temporal gyrus, anterior cuneus, caudate nucleus, inferior frontal gyrus, cingulate gyrus, anterior central gyrus, and posterior central gyrus. Associations between brain activation and reward expectancy in the left insula, left middle frontal gyrus, left thalamus, and right middle frontal gyrus were found to be related to proactive aggression. Furthermore, the brain activation regions primarily involved in proactive aggression induced by reward expectancy were the insula, inferior frontal gyrus, inferior temporal gyrus, pallidum, and caudate nucleus. Under conditions of high reward expectancy, participants engage in more proactive aggressive behavior. Reward expectancy involves the activation of reward- and social-cognition-related brain regions, and these associations are instrumental in proactive aggressive decisions.

Decision-related activity and movement selection in primate visual cortex.

Fluctuations in the activity of sensory neurons often predict perceptual decisions. This connection can be quantified with a metric called choice probability (CP), and there is a longstanding debate about whether CP reflects a causal influence on decisions or an echo of decision-making activity elsewhere in the brain. Here, we show that CP can reflect a third variable, namely, the movement used to indicate the decision. In a standard visual motion discrimination task, neurons in the middle temporal (MT) area of primate cortex responded more strongly during trials that involved a saccade toward their receptive fields. This variability accounted for much of the CP observed across the neuronal population, and it arose through training. Moreover, pharmacological inactivation of MT biased behavioral responses away from the corresponding visual field locations. These results demonstrate that training on a task with fixed sensorimotor contingencies introduces movement-related activity in sensory brain regions and that this plasticity can shape the neural circuitry of perceptual decision-making.

Temporal interference stimulation disrupts spike timing in the primate brain

Electrical stimulation can regulate brain activity, producing clear clinical benefits, but focal and effective neuromodulation often requires surgically implanted electrodes. Recent studies argue that temporal interference (TI) stimulation may provide similar outcomes non-invasively. During TI, scalp electrodes generate multiple electrical fields in the brain, modulating neural activity only at their intersection. Despite considerable enthusiasm for this approach, little empirical evidence demonstrates its effectiveness, especially under conditions suitable for human use. Here, using single-neuron recordings in non-human primates, we establish that TI reliably alters the timing, but not the rate, of spiking activity. However, we show that TI requires strategies—high carrier frequencies, multiple electrodes, and amplitude-modulated waveforms—that also limit its effectiveness. Combined, these factors make TI 80 % weaker than other forms of non-invasive brain stimulation. Although unlikely to cause widespread neuronal entrainment, TI may be ideal for disrupting pathological oscillatory activity, a hallmark of many neurological disorders.

Evaluation of Rural Healing Landscape DESIGN Based on Virtual Reality and Electroencephalography

From the user’s perspective, emotional elements are increasingly being used in design. Researchers have indicated that healing landscapes in rural areas play a positive role in soothing human emotions. In this study, a landscape with healing functions was designed, and 32 subjects experienced emotions in a virtual reality (VR) scene while their 32-channel electroencephalography (EEG) signals were collected. This study compared the brain responses with and without the presence of healing landscape elements and conducted correlation coefficient analysis using eight different regression prediction models to examine the relationship between security, comfort, positivity, and corresponding healing landscape elements. The results show significant improvements in emotions of security, comfort, and positivity post-exposure to the landscape design, especially with certain elements, such as seating, shrubs, and tree pools. EEG data indicate enhanced emotional and cognitive states, particularly relaxation, with increased activity in specific brain regions. The decision tree regression model is the most suitable for our data. It reveals strong correlations between specific healing landscape elements and emotional responses. In the comfort category, “shrubs” show the highest correlation (R² = 0.82), while in the security category, “trees” have the highest correlation (R² = 0.77). Similarly, in the positivity category, “trees” again exhibit the highest correlation (R² = 0.71) with EEG data, indicating their significant impact on these emotional dimensions. This study demonstrates the importance of using scientific methods, such as EEG technology, to validate the principles of emotional design and also underscores the role of green environments in enhancing psychological health and emotional comfort.

Gossypetin targets the liver-brain axis to alleviate pre-existing liver fibrosis and hippocampal neuroinflammation in mice.

Liver fibrosis occurs in response to chronic damage and inflammation to the liver. Leaving untreated, it can lead to decreased liver function and can eventually progress to cirrhosis, a more advanced and irreversible state of liver damage. Clinical investigations showed that chronic liver disease associated with neurological symptoms including anxiety, depression, and cognitive decline. However, few therapeutic options are available for treating liver and related brain pathologies simultaneously. In this study, we aim to find therapeutic candidates that target the liver-brain axis. Gossypetin, a flavonoid from sedum, shows promising capability in treating liver and brain pathologies in CCl4-induced mouse model. Short term of gossypetin administration is sufficient to ameliorate impaired liver function and pre-existing liver fibrosis, suppress MKK3/6-p38 MAPK and p53 activation, and abolish the activation of hepatic stellate cells and Kupffer cells. Although we observe no neuronal loss in the brain of mice with liver fibrosis, we do observe astrogliosis and microglial activation in certain brain regions, especially the hippocampus. Brief gossypetin administration also shows potential in alleviating neuroinflammation in these regions. These results suggest that gossypetin can target the liver-brain axis and be a promising candidate for treating chronic liver fibrosis patients with neurological symptoms.

F.1 Oscillatory network markers of subcallosal cingulate deep brain stimulation for depression

Background: Identifying functional biomarkers related to treatment success can aid in optimizing therapy and provide a better understanding of the neural mechanisms of treatment-resistant depression (TRD) and subcallosal cingulate deep brain stimulation (SCC-DBS). Methods: Magnetoencephalography data were obtained from 16 individuals with SCC-DBS for TRD and 25 healthy subjects. We identified region-specific oscillatory modulations that both (i) discriminate individuals with TRD (SCC-DBS OFF) from healthy controls and (ii) discriminate responders from non-responders (SCC-DBS ON). The effects of stimulation intensity and frequency were also explored. Results: Discriminative regions that differentiated responders from non-responders based on modulations of increased alpha (8-12 Hz) and decreased gamma (32-116 Hz) power included nodes of the default mode, central executive, and somatomotor networks, Broca’s area, and lingual gyrus. Furthermore, low stimulation frequency had stronger effects on oscillatory modulation. Conclusions: The identified functional biomarkers implicate modulations of TRD-related activity in brain regions involved in emotional control/processing, motor control, and interactions between speech, vision, and memory – all implicated in depression. These electrophysiological biomarkers have the potential to be used as functional proxies for therapy optimization. Additional stimulation parameter analyses revealed that oscillatory modulations are strengthened by increasing stimulation intensity or reducing frequency, which may benefit SCC-DBS non-responders.

Polygenic architecture of brain structure and function, behaviors, and psychopathologies in children.

The human brain undergoes structural and functional changes during childhood, a critical period in cognitive and behavioral development. Understanding the genetic architecture of the brain development in children can offer valuable insights into the development of the brain, cognition, and behaviors. Here, we integrated brain imaging-genetic-phenotype data from over 8,600 preadolescent children of diverse ethnic backgrounds using multivariate statistical techniques. We found a low-to-moderate level of SNP-based heritability in most IDPs, which is lower compared to the adult brain. Using sparse generalized canonical correlation analysis (SGCCA), we identified several covariation patterns among genome-wide polygenic scores (GPSs) of 29 traits, 7 different modalities of brain imaging-derived phenotypes (IDPs), and 266 cognitive and psychological phenotype data. In structural MRI, significant positive associations were observed between total grey matter volume, left ventral diencephalon volume, surface area of right accumbens and the GPSs of cognition-related traits. Conversely, negative associations were found with the GPSs of ADHD, depression and neuroticism. Additionally, we identified a significant positive association between educational attainment GPS and regional brain activation during the N-back task. The BMI GPS showed a positive association with fractional anisotropy (FA) of connectivity between the cerebellum cortex and amygdala in diffusion MRI, while the GPSs for educational attainment and cannabis use were negatively associated with the same IDPs. Our GPS-based prediction models revealed substantial genetic contributions to cognitive variability, while the genetic basis for many mental and behavioral phenotypes remained elusive. This study delivers a comprehensive map of the relationships between genetic profiles, neuroanatomical diversity, and the spectrum of cognitive and behavioral traits in preadolescence.

Effects of long-term antipsychotic medication on brain instability in first-episode schizophrenia patients: a resting-state fMRI study

Early initiation of antipsychotic treatment plays a crucial role in the management of first-episode schizophrenia (FES) patients, significantly improving their prognosis. However, limited attention has been given to the long-term effects of antipsychotic drug therapy on FES patients. In this research, we examined the changes in abnormal brain regions among FES patients undergoing long-term treatment using a dynamic perspective. A total of 98 participants were included in the data analysis, comprising 48 FES patients, 50 healthy controls, 22 patients completed a follow-up period of more than 6 months with qualified data. We processed resting-state fMRI data to calculate coefficient of variation of fractional amplitude of low-frequency fluctuations (CVfALFF), which reflects the brain regional activity stability. Data analysis was performed at baseline and after long-term treatment. We observed that compared with HCs, patients at baseline showed an elevated CVfALFF in the supramarginal gyrus (SMG), parahippocampal gyrus (PHG), caudate, orbital part of inferior frontal gyrus (IOG), insula, and inferior frontal gyrus (IFG). After long-term treatment, the instability in SMG, PHG, caudate, IOG, insula and inferior IFG have ameliorated. Additionally, there was a positive correlation between the decrease in dfALFF in the SMG and the reduction in the SANS total score following long-term treatment. In conclusion, FES patients exhibit unstable regional activity in widespread brain regions at baseline, which can be ameliorated with long-term treatment. Moreover, the extent of amelioration in SMG instability is associated with the amelioration of negative symptoms.

Impulse control disorders due to cocaine and synthetic stimulants use: a systematic review

The introduction of ICD-11 has opened up new horizons in understanding the impact of modern narcotic substances on mental health, in particular, it has increased the list of possible mental disorders associated with drug use. The purpose of the work is to conduct a systematic review of the literature and describe the features of the pathogenesis, clinical picture, and effectiveness of various types of therapy for impulse control disorders associated with use of cocaine and synthetic stimulants. A systematic analysis of scientific publications was performed in the eLibrary, PubMed, CNKI, and Google Scholar databases according to PRISMA recommendations. 41 publications were selected from the initially found 4,953 articles. The pathogenesis of induced impulse control disorders is associated with the direct effect of stimulant drugs on the brain and consists in the activation of D3 and 5‑HT1A receptors, as well as activation of limbic brain regions and a lack of inhibitory effects of the frontal lobe. Increased impulsivity in users of cocaine and synthetic stimulants has been proven in a large number of neurophysiological and neuroimaging studies. The frequency of occurrence, clinical features, and approaches to therapy of impulse control disorders resulting from the use of drugs with dopaminergic action (drugs for the treatment of Parkinson's disease and hyperprolactinemia, third-generation antipsychotics, and venlafaxine in high doses) have been described in details. At the same time, there is indirect evidence that cocaine and synthetic stimulants should cause impulse control disorders, since they have similar neurotransmitter activity. In addition, there are descriptions of the predominance of individual symptoms of impulse control disorders in this group of drug users. However, at the time of the review, no detailed description of these drug-induced disorders has been found. These are the prospects for further research. The use of fluoxetine and oxcarbazepine (for intermittent explosive disorder) and naltrexone (for kleptomania), as well as comprehensive prevention of drug use relapse and psychotherapy, has the highest degree of evidence as a therapy for impulse control disorders.

Social interactions and olfactory cues are required for contagious itch in mice

The phenomenon of contagious itch, observed in both humans and rodents, remains a topic of ongoing debate concerning its modulators and underlying pathways. This study delves into the relationship between contagious itch and familiar olfactory cues, a non-visual factor contributing to this intriguing behavior. Our findings showed that contagious itch in observer mice occurs during physical interaction with the cagemate itch-demonstrator but not with a stranger demonstrator or in a non-physical encounter condition. Notably, itch-experienced observer mice displayed an increased contagious itch behavior, highlighting the relevance of itch-associated memory in this phenomenon. Furthermore, anosmic observer mice, whether itch-naïve or itch-experienced, displayed no contagious itch behavior. These results demonstrate that the familiar olfactory cues, specifically cagemate body odors, are required for contagious itch behaviors in mice. In line with these behavioral findings, our study reveals increased activity in brain regions associated with olfaction, emotion, and memory during contagious itch, including the olfactory bulb, the amygdala, the hypothalamus, and the hippocampus, with this activity diminished in anosmic mice. In conclusion, our study unveils the critical role of familiar olfactory cues in driving contagious itch in mice, shedding light on the interplay between social factors, sensory perception, and memory in this phenomenon.

Right thalamic volume mediates impact of the dopamine beta-hydroxylase gene on the endowment effect

The endowment effect is a tendency that individuals overvalue items belonging to them relative to those items that do not. Previous studies showed a strong relation between the dopamine beta-hydroxylase (DBH) gene and the endowment effect (EE), and a link between EE and task-based functional MRI activation in multiple brain regions. However, the role of brain structure on EE remains unclear. In this study, we have explored whether regional brain volume mediate the effect of the DBH gene on EE. Results showed that rs1611115, single-nucleotide polymorphisms (SNPs) at DBH loci, were significantly associated with right thalamus volume and the endowment effect in males but not in female participants. Specifically, male DBH rs1611115 T-carriers had larger right thalamus volume compared to carriers of CC genotype and exhibited a greater endowment effect. Importantly, we found that right thalamus volume mediated the effect of rs1611115 on the endowment effect in male participants. This study demonstrated how thalamic volume plays an important mediating role between genetics and decision-making in humans.

Classification of motor imagery using chaotic entropy based on sub-band EEG source localization

Objective. Electroencephalography (EEG) has been widely used in motor imagery (MI) research by virtue of its high temporal resolution and low cost, but its low spatial resolution is still a major criticism. The EEG source localization (ESL) algorithm effectively improves the spatial resolution of the signal by inverting the scalp EEG to extrapolate the cortical source signal, thus enhancing the classification accuracy. Approach. To address the problem of poor spatial resolution of EEG signals, this paper proposed a sub-band source chaotic entropy feature extraction method based on sub-band ESL. Firstly, the preprocessed EEG signals were filtered into 8 sub-bands. Each sub-band signal was source localized respectively to reveal the activation patterns of specific frequency bands of the EEG signals and the activities of specific brain regions in the MI task. Then, approximate entropy, fuzzy entropy and permutation entropy were extracted from the source signal as features to quantify the complexity and randomness of the signal. Finally, the classification of different MI tasks was achieved using support vector machine. Main result. The proposed method was validated on two MI public datasets (brain–computer interface (BCI) competition III IVa, BCI competition IV 2a) and the results showed that the classification accuracies were higher than the existing methods. Significance. The spatial resolution of the signal was improved by sub-band EEG localization in the paper, which provided a new idea for EEG MI research.

Women and men with distressing low sexual desire exhibit sexually dimorphic brain processing

Distressing low sexual desire, termed Hypoactive Sexual Desire Disorder (HSDD), affects approximately 10% of women and 8% of men. In women, the ‘top-down’ theory of HSDD describes hyperactivity in higher-level cognitive brain regions, suppressing lower-level emotional/sexual brain areas. However, it is unknown how this neurofunctional disturbance compares to HSDD in men. To investigate this, we employed task-based functional MRI in 32 women and 32 men with HSDD to measure sexual-brain processing during sexual versus non-sexual videos, as well as psychometric questionnaires to assess sexual desire/arousal. We demonstrate that women had greater activation in higher-level and lower-level brain regions, compared to men. Indeed, women who had greater hypothalamic activation in response to sexual videos, reported higher psychometric scores in the evaluative (r = 0.55, P = 0.001), motivational (r = 0.56, P = 0.003), and physiological (r = 0.57, P = 0.0006) domains of sexual desire and arousal after watching the sexual videos in the scanner. By contrast, no similar correlations were observed in men. Taken together, this is the first direct comparison of the neural correlates of distressing low sexual desire between women and men. The data supports the ‘top-down’ theory of HSDD in women, whereas in men HSDD appears to be associated with different neurofunctional processes.

ADHD diagnosis guided by functional brain networks combined with domain knowledge

Utilizing functional magnetic resonance imaging (fMRI) to model functional brain networks (FBNs) is increasingly prominent in attention-deficit/hyperactivity disorder (ADHD) research, revealing neural impact and mechanisms through the exploration of activated brain regions. However, current FBNs-based methods face two major challenges. The primary challenge stems from the limitations of existing modeling methods in accurately capturing both regional correlations and long-distance dependencies (LDDs) within the dynamic brain, thereby affecting the diagnostic accuracy of FBNs as biomarkers. Additionally, limited sample size and class imbalance also pose a challenge to the learning performance of the model. To address the issues, we propose an automated diagnostic framework, which integrates modeling, multimodal fusion, and classification into a unified process. It aims to extract representative FBNs and efficiently incorporate domain knowledge to guide ADHD classification. Our work mainly includes three-fold: 1) A multi-head attention-based region-enhancement module (MAREM) is designed to simultaneously capture regional correlations and LDDs across the entire sequence of brain activity, which facilitates the construction of representative FBNs. 2) The multimodal supplementary learning module (MSLM) is proposed to integrate domain knowledge from phenotype data with FBNs from neuroimaging data, achieving information complementarity and alleviating the problems of insufficient medical data and unbalanced sample categories. 3) An ADHD automatic diagnosis framework guided by FBNs and domain knowledge (ADF-FAD) is proposed to help doctors make more accurate decisions, which is applied to the ADHD-200 dataset to confirm its effectiveness. The results indicate that the FBNs extracted by MAREM perform well in modeling and classification. After with MSLM, the model achieves accuracy of 92.4%, 74.4%, and 80% at NYU, PU, and KKI, respectively, demonstrating its ability to effectively capture crucial information related to ADHD diagnosis. Codes are available at https://github.com/zhuimengxuebao/ADF-FAD.