The brain's default network: anatomy, function, and relevance to disease

The primacy of experience in language processing: Semantic priming is driven primarily by experiential similarity

The organization of semantic memory, including memory for word meanings, has long been a central question in cognitive science. Although there is general agreement that word meaning representations must make contact with sensory-motor and affective experiences in a non-arbitrary fashion, the nature of this relationship remains controversial. One prominent view proposes that word meanings are represented directly in terms of their experiential content (i.e., sensory-motor and affective representations). Opponents of this view argue that the representation of word meanings reflects primarily taxonomic structure, that is, their relationships to natural categories. In addition, the recent success of language models based on word co-occurrence (i.e., distributional) information in emulating human linguistic behavior has led to proposals that this kind of information may play an important role in the representation of lexical concepts. We used a semantic priming paradigm designed for representational similarity analysis (RSA) to quantitatively assess how well each of these theories explains the representational similarity pattern for a large set of words. Crucially, we used partial correlation RSA to account for intercorrelations between model predictions, which allowed us to assess, for the first time, the unique effect of each model. Semantic priming was driven primarily by experiential similarity between prime and target, with no evidence of an independent effect of distributional or taxonomic similarity. Furthermore, only the experiential models accounted for unique variance in priming after partialling out explicit similarity ratings. These results support experiential accounts of semantic representation and indicate that, despite their good performance at some linguistic tasks, the distributional models evaluated here do not encode the same kind of information used by the human semantic system.

Differential brainstem connectivity according to sex and menopausal status in healthy men and women

Background Brainstem nuclei play a critical role in both ascending monoaminergic modulation of cortical function and arousal, and in descending bulbospinal pain modulation. Even though sex-related differences in the function of both systems have been reported in animal models, a complete understanding of sex differences, as well as menopausal effects, in brainstem connectivity in humans is lacking. This study evaluated resting-state connectivity of the dorsal raphe nucleus (DRN), right and left locus coeruleus complex (LCC), and periaqueductal gray (PAG) according to sex and menopausal status in healthy individuals. In addition, relationships between systemic estrogen levels and brainstem-network connectivity were examined in a subset of participants. Methods Resting-state fMRI was performed in 50 healthy men (age, 31.2 ± 8.0 years), 53 healthy premenopausal women (age, 24.7 ± 7.3 years; 22 in the follicular phase, 31 in the luteal phase), and 20 postmenopausal women (age, 54.6 ± 7.2 years). Permutation Analysis of Linear Models (5000 permutations) was used to evaluate differences in brainstem-network connectivity according to sex and menopausal status, controlling for age. In 10 men and 17 women (9 premenopausal; 8 postmenopausal), estrogen and estrogen metabolite levels in plasma and stool were determined by liquid chromatography-mass spectrometry/mass spectrometry. Relationships between estrogen levels and brainstem-network connectivity were evaluated by partial least squares analysis. Results Left LCC-executive control network (ECN) connectivity showed an overall sex difference (p = 0.02), with higher connectivity in women than in men; however, this was mainly due to differences between men and pre-menopausal women (p = 0.008). Additional sex differences were dependent on menopausal status: PAG-default mode network (DMN) connectivity was higher in postmenopausal women than in men (p = 0.04), and PAG-sensorimotor network (SMN) connectivity was higher in premenopausal women than in men (p = 0.03) and postmenopausal women (p = 0.007). Notably, higher free 2-hydroxyestrone levels in stool were associated with higher PAG-SMN and PAG-DMN connectivity in premenopausal women (p < 0.01). Conclusions Healthy women show higher brainstem-network connectivity involved in cognitive control, sensorimotor function, and self-relevant processes than men, dependent on their menopausal status. Further, 2-hydroxyestrone, implicated in pain, may modulate PAG connectivity in premenopausal women. These findings may relate to differential vulnerabilities to chronic stress-sensitive disorders at different life stages.

Neural signatures of default mode network subsystems in first-episode, drug-naive patients with major depressive disorder after 6-week thought induction psychotherapy treatment

Evidence indicates that the default mode network (DMN) plays a crucial role in the neuropathology of major depressive disorder (MDD). However, the neural signatures of DMN subsystems in MDD after low resistance Thought Induction Psychotherapy (TIP) remain incompletely understood. We collected functional magnetic resonance imaging data from 20 first-episode, drug-naive MDD and 20 healthy controls (HCs). The DMN was segmented into three subsystems and seed-based functional connectivity (FC) was computed. After 6-week treatment, the significantly reduced FCs with the medial temporal lobe memory subsystem in MDD at baseline were enhanced and were comparable to that in HCs. Changed Hamilton Depression Rating Scale scores were significantly related with changed FC between the posterior cingulate cortex (PCC) and the right precuneus (PCUN). Further, changed serotonin 5-hydroxytryptamine levels were significantly correlated with changed FCs between the PCC and the left PCUN, between the posterior inferior parietal lobule and the left inferior temporal gyrus, and between the retrosplenial cortex and the right inferior frontal gyrus, opercular part. Finally, the support vector machine obtained an accuracy of 67.5% to distinguish between MDD at baseline and HCs. These findings may deepen our understanding of the neural basis of the effects of TIP on DMN subsystems in MDD.

Static and dynamic interactions within the triple-network model in stroke patients with multidomain cognitive impairments

BACKGROUND

Internal capsule strokes often result in multidomain cognitive impairments across memory, attention, and executive function, typically due to disruptions in brain network connectivity. Our study examines these impairments by analyzing interactions within the triple-network model, focusing on both static and dynamic aspects.

METHODS

We collected resting-state fMRI data from 62 left (CI_L) and 56 right (CI_R) internal capsule stroke patients, along with 57 healthy controls (HC). Using independent component analysis to extract the default mode (DMN), executive control (ECN), and salience networks (SAN), we conducted static and dynamic functional network connectivity analyses (DFNC) to identify differences between stroke patients and controls. For DFNC, we used k-means clustering to focus on temporal properties and multilayer network analysis to examine integration and modularity Q, where integration represents dynamic interactions between networks, and modularity Q measures how well the network is divided into distinct modules. We then calculated the correlations between SFNC/DFNC properties with significant inter-group differences and cognitive scales.

RESULTS

Compared to HC, both CI_L and CI_R patients showed increased static FCs between SAN and DMN and decreased dynamic interactions between ECN and other networks. CI_R patients also had heightened static FCs between SAN and ECN and maintained a state with strongly positive FNCs across all networks in the triple-network model. Additionally, CI_R patients displayed decreased modularity Q.

CONCLUSION

These findings highlight that stroke can result in the disruption of static and dynamic interactions in the triple network model, aiding our understanding of the neuropathological basis for multidomain cognitive deficits after internal capsule stroke.

Frequency-specific static and dynamic neural activity indices in children with different attention deficit hyperactivity disorder subtypes: a resting-state fMRI study

Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood. Numerous resting-state functional magnetic resonance imaging (rs-fMRI) studies in ADHD have been performed using traditional low-frequency bands (0.01-0.08 Hz). However, the neural activity patterns of frequency subbands in ADHD still require further investigation. The purpose of this study is to explore the frequency-dependent characteristics and neural activity patterns of ADHD subtypes. We selected the ADHD combined type (ADHD-C, N = 25), ADHD inattentive type (ADHD-I, N = 26) and typically developing (TD, N = 28) children from the ADHD-200 Consortium. Based on the slow-5 band (0.01-0.027 Hz) and slow-4 band (0.027-0.073 Hz), we generated static and dynamic fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) maps for each participant. A flexible-factorial analysis of variance model was performed on static and temporal dynamic rs-fMRI measurements within two subbands. Results revealed that the orbital-frontal gyrus, precuneus, superior temporal gyrus and angular gyrus were found to have obvious frequency band and group interaction effects. The intrinsic neural activity differences among three groups were more prominent in the slow-5 frequency band compared to the slow-4 band. In addition, the indices of significant interaction regions showed correlations with the progression of the disease and the features in slow-5 showed an advantageous diagnostic performance compared with those in slow-4. The results suggested the intrinsic neural activities of ADHD subtypes were frequency-dependent. The frequency-specific analysis of static and dynamic brain activity may provide a deeper understanding of neurophysiological dysfunction patterns in ADHD subtypes and provide supplementary information for assessing ADHD subtypes.

Altered dynamic neural activities in individuals with obsessive-compulsive disorder and comorbid depressive symptoms

Objectives

Depressive symptoms are the most prevalent comorbidity in individuals with obsessive-compulsive disorder (OCD). The objective of this study was to investigate the dynamic characteristics of resting-state neural activities in OCD patients with depressive symptoms.

Methods

We recruited 29 OCD patients with depressive symptoms, 21 OCD patients without depressive symptoms, and 27 healthy controls, and collected data via structural and functional magnetic resonance imaging (fMRI). We analyzed the fMRI results using the dynamic amplitude of low-frequency fluctuation (dALFF) and support vector machine (SVM) techniques.

Results

Compared with OCD patients without depressive symptoms, OCD patients with depressive symptoms exhibited an increased dALFF in the left precuneus and decreased dALFF in the right medial frontal gyrus. The SVM indicated that the integration of aberrant dALFF values in the left precuneus and right medial frontal gyrus led to an overall accuracy of 80%, a sensitivity of 79%, and a specificity of 100% in detecting depressive symptoms among OCD patients.

Conclusion

Therefore, our study reveals that OCD patients with depressive symptoms display neural activities with unique dynamic characteristics in the resting state. Accordingly, abnormal dALFF values in the left precuneus and right medial frontal gyrus could be used to identify depressive symptoms in OCD patients.

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.

Cross-regional coordination of activity in the human brain during autobiographical self-referential processing

For the human brain to operate, populations of neurons across anatomical structures must coordinate their activity within milliseconds. To date, our understanding of such interactions has remained limited. We recorded directly from the hippocampus (HPC), posteromedial cortex (PMC), ventromedial/orbital prefrontal cortex (OFC), and the anterior nuclei of the thalamus (ANT) during two experiments of autobiographical memory processing that are known from decades of neuroimaging work to coactivate these regions. In 31 patients implanted with intracranial electrodes, we found that the presentation of memory retrieval cues elicited a significant increase of low frequency (LF < 6 Hz) activity followed by cross-regional phase coherence of this LF activity before select populations of neurons within each of the four regions increased high-frequency (HF > 70 Hz) activity. The power of HF activity was modulated by memory content, and its onset followed a specific temporal order of ANT→HPC/PMC→OFC. Further, we probed cross-regional causal effective interactions with repeated electrical pulses and found that HPC stimulations cause the greatest increase in LF-phase coherence across all regions, whereas the stimulation of any region caused the greatest LF-phase coherence between that particular region and ANT. These observations support the role of the ANT in gating, and the HPC in synchronizing, the activity of cortical midline structures when humans retrieve self-relevant memories of their past. Our findings offer a fresh perspective, with high temporal fidelity, about the dynamic signaling and underlying causal connections among distant regions when the brain is actively involved in retrieving self-referential memories from the past.

Precision mapping of the default network reveals common and distinct (inter) activity for autobiographical memory and theory of mind

The default network is widely implicated as a common neural substrate for self-generated thought, such as remembering one's past (autobiographical memory) and imagining the thoughts and feelings of others (theory of mind). Findings that the default network comprises subnetworks of regions, some commonly and some distinctly involved across processes, suggest that one's own experiences inform their understanding of others. With the advent of precision functional MRI (fMRI) methods, however, it is unclear if this shared substrate is observed instead due to traditional group analysis methods. We investigated this possibility using a novel combination of methodological strategies. Twenty-three participants underwent multi-echo resting-state and task fMRI. We used their resting-state scans to conduct cortical parcellation sensitive to individual variation while preserving our ability to conduct group analysis. Using multivariate analyses, we assessed the functional activation and connectivity profiles of default network regions while participants engaged in autobiographical memory, theory of mind, or a sensorimotor control condition. Across the default network, we observed stronger activity associated with both autobiographical memory and theory of mind compared to the control condition. Nonetheless, we also observed that some regions showed preferential activity to either experimental condition, in line with past work. The connectivity results similarly indicated shared and distinct functional profiles. Our results support that autobiographical memory and theory of mind, two theoretically important and widely studied domains of social cognition, evoke common and distinct aspects of the default network even when ensuring high fidelity to individual-specific characteristics.NEW & NOTEWORTHY We used cutting-edge precision functional MRI (fMRI) methods such as multi-echo fMRI acquisition and denoising, a robust experimental paradigm, and individualized cortical parcellation across 23 participants to provide evidence that remembering one's past experiences and imagining the thoughts and feelings of others share a common neural substrate. Evidence from activation and connectivity analyses indicate overlapping and distinct functional profiles of these widely studied episodic and social processes.

Higher substance use is associated with low executive control neural activity and higher inflammation

Individuals with substance use problems show lower executive control and alterations in prefrontal brain systems supporting emotion regulation and impulse control. A separate literature suggests that heightened inflammation also increases risk for substance use, in part, through targeting brain systems involved in executive control. Research on neural and inflammatory signaling in substance use, however, has occurred in parallel. Drawing on recent neuroimmune network models, we used fMRI to examine the relationships between executive control-related brain activity (as elicited by an n-back working memory task), peripheral inflammation, as quantified by inflammatory cytokines and C-reactive protein (CRP), and substance use for the past month in 93 participants [mean age = 24.4 (SD = 0.6)]. We operationalized low executive control as a neural inefficiency during the n-back task to achieve normative performance, as reflected in higher working memory-related brain activity and lower activity in the default mode network (DMN). Consistent with prediction, individuals with low executive control and high inflammation reported more substance use over the past month, controlling for behavioral performance on the n-back, sex, time between assessments, body-mass-index (BMI), and personal socioeconomic status (SES) (interaction between inflammation and working memory-related brain activity, b = 0.210, p = 0.005; interaction between inflammation and DMN, b = -0.219, p < 0.001). Findings suggest that low executive control and high inflammation may be associated with higher substance use. This has implications for understanding psychological, neural, and immunological risk for substance use problems and the development of interventions to target each of these components.

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

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

Predicting treatment outcomes in patients with panic disorder: Cross-sectional and two-year longitudinal structural connectome analysis using machine learning methods

PURPOSE

This study examined the relationship between structural brain networks and long-term treatment outcomes in patients with panic disorder (PD) using machine learning methods.

METHOD

The study involved 80 participants (53 PD patients and 27 healthy controls) and included clinical assessments and MRI scans at baseline and after two years (160 MRIs). Patients were categorized based on their response to two-year pharmacotherapy. Brain networks were analyzed using white matter tractography and network-based statistics.

RESULTS

Results showed structural network changes in PD patients, particularly in the extended fear network, including frontal regions, thalamus, and cingulate gyrus. Longitudinal analysis revealed that increased connections to the amygdala, hippocampus, and insula were associated with better treatment response. Conversely, overconnectivity in the amygdala and insula at baseline was associated with poor response, and similar patterns were found in the insula and parieto-occipital cortex related to non-remission. This study found that SVM and CPM could effectively predict treatment outcomes based on network pattern changes in PD.

CONCLUSIONS

These findings suggest that monitoring structural connectome changes in limbic and paralimbic regions is critical for understanding PD and tailoring treatment. The study highlights the potential of using personalized biomarkers to develop individualized treatment strategies for PD.

Association between patent foramen ovale and migraine: evidence from a resting-state fMRI study

A relationship between migraine without aura (MO) and patent foramen ovale (PFO) has been observed, but the neural basis underlying this relationship remains elusive. Utilizing independent component analysis via functional magnetic resonance imaging, we examined functional connectivity (FC) within and across networks in 146 patients with MO (75 patients with and 71 patients without PFO) and 70 healthy controls (35 patients each with and without PFO) to elucidate the individual effects of MO and PFO, as well as their interaction, on brain functional networks. The main effect of PFO manifested exclusively in the FC among the visual, auditory, default mode, dorsal attention and salience networks. Furthermore, the interaction effect between MO and PFO was discerned in brain clusters of the left frontoparietal network and lingual gyrus network, as well as the internetwork FC between the left frontoparietal network and the default mode network (DMN), the occipital pole and medial visual networks, and the dorsal attention and salience networks. Our findings suggest that the presence of a PFO shunt in patients with MO is accompanied by various FC changes within and across networks. These changes elucidate the intricate mechanisms linked to PFO-associated migraines and provide a basis for identifying novel noninvasive biomarkers.

Impacts of early deprivation on behavioral and neural measures of executive function in early adolescence

Children reared in institutional settings experience early deprivation that has lasting implications for multiple aspects of neurocognitive functioning, including executive function (EF). Changes in brain development are thought to contribute to these persistent EF challenges, but little research has used fMRI to investigate EF-related brain activity in children with a history of early deprivation. This study examined behavioral and neural data from a response conflict task in 12-14-year-olds who spent varying lengths of time in institutional care prior to adoption (N = 84; age at adoption - mean: 15.85 months, median: 12 months, range: 4-60 months). In initial analyses, earlier- and later-adopted (EA, LA) youth were compared to a group of children raised in their biological families (non-adopted, NA). NA youth performed significantly more accurately than LA youth, with EA youth falling in between. Imaging data suggested that previously institutionalized (PI) youth activated additional frontoparietal regions, including dorsolateral prefrontal cortex, as compared to NA youth. In addition, EA youth uniquely activated medial prefrontal regions, and LA uniquely activated parietal regions during this task. A separate analysis in a larger group of PI youth examined whether behavioral or brain measures of EF varied with the duration of deprivation experienced. Duration of deprivation was negatively associated with activation of default mode network (DMN) regions. Overall, results suggest that there are lasting effects of deprivation on EF, but that those who are removed from institutional care earlier may be able to recruit additional neural resources as a compensatory mechanism.

Age-related differences in functional connectivity associated with pain modulation

Growing evidence suggests that aging is associated with impaired endogenous pain modulation, and that this likely underlies the increased transition from acute to chronic pain in older individuals. Resting-state functional connectivity (rsFC) offers a valuable tool to examine the neural mechanisms behind these age-related changes in pain modulation. RsFC studies generally observe decreased within-network connectivity due to aging, but its relevance for pain modulation remains unknown. We compared rsFC within a set of brain regions involved in pain modulation between young and older adults and explored the relationship with the efficacy of distraction from pain. This revealed several age-related increases and decreases in connectivity strength. Importantly, we found a significant association between lower pain relief and decreased strength of three connections in older adults, namely between the periaqueductal gray and right insula, between the anterior cingulate cortex (ACC) and right insula, and between the ACC and left amygdala. These findings suggest that the functional integrity of the pain control system is critical for effective pain modulation, and that its function is compromised by aging.

Exploring the transformative potential of out-of-body experiences: A pathway to enhanced empathy

Out-of-body experiences (OBEs) are subjective phenomena during which individuals feel disembodied or perceive themselves as outside of their physical bodies, often resulting in profound and transformative effects. In particular, experiencers report greater heightened pro-social behavior, including more peaceful relationships, tolerance, and empathy. Drawing parallels with the phenomenon of ego dissolution induced by certain psychedelic substances, we explore the notion that OBEs may engender these changes through ego dissolution, which fosters a deep-seated sense of unity and interconnectedness with others. We then assess potential brain mechanisms underlying the link between OBEs and empathy, considering the involvement of the temporoparietal junction and the Default Mode Network. This manuscript offers an examination of the potential pathways through which OBEs catalyze empathic enhancement, shedding light on the intricate interplay between altered states of consciousness and human empathy.

Alterations in amygdala subregions-Default mode network connectivity after treatment in patients with schizophrenia

Disrupted connectivity in the default mode network (DMN) during resting-state functional MRI (rs-fMRI) is well-documented in schizophrenia (SCZ). The amygdala, a key component in the neurobiology of SCZ, comprises distinct subregions that may exert varying effects on the disorder. This study aimed to investigate variations in functional connectivity (FC) between distinct amygdala subregions and the DMN in SCZ individuals and explore the effects of treatment on these connections. Fifty-six SCZ patients and 51 healthy controls underwent FC analysis and questionnaire surveys during resting state. The amygdala was selected as the region of interest (ROI) and subdivided into four parts. Changes in FC were examined, and correlations between questionnaire scores and brain activity were explored. Pre-treatment, SCZ patients exhibited reduced FC between the amygdala and DMN compared to HCs. After treatment, significant differences persisted in the right medial amygdala, while other regions did not differ significantly from controls. In addition, PANSS scores positively correlated with FC between the Right Medial Amygdala and the left SMFC (r = .347, p = .009), while RBANS5A scores showed a positive correlation with FC between the Left Lateral Amygdala and the right MTG (rho = -.347, p = .009). The rsFC between the amygdala and the DMN plays a crucial role in the treatment mechanisms of SCZ. This could provide a promising predictive indicator for understanding the neural mechanisms behind treatment and symptomatic improvement.

Structural and functional neural patterns among sub-threshold bulimia nervosa: Abnormalities in dorsolateral prefrontal cortex and orbitofrontal cortex

BACKGROUND

Disordered eating behaviors are prevalent among youngsters and highly associated with dysfunction in neurocognitive systems. We aimed to identify the potential changes in individuals with bulimia symptoms (sub-BN) to generate insights to understand developmental pathophysiology of bulimia nervosa.

METHODS

We investigated group differences in terms of degree centrality (DC) and gray matter volume (GMV) among 145 undergraduates with bulimia symptoms and 140 matched control undergraduates, with the secondary analysis of the whole brain connectivity in these regions of interest showing differences in static functional connectivity (FC).

RESULTS

The sub-BN group exhibited abnormalities of the right dorsolateral prefrontal cortex and right orbitofrontal cortex in both GMV and DC, and displayed decreased FC between these regions and the precuneus. We also observed that sub-BN presented with reduced FC between the calcarine and superior temporal gyrus, middle temporal gyrus and inferior parietal gyrus. Additionally, brain-behavioral associations suggest a distinct relationship between these FCs and psychopathological symptoms in sub-BN group.

CONCLUSIONS

Our study demonstrated that individuals with bulimia symptoms present with aberrant neural patterns that mainly involved in cognitive control and reward processing, as well as attentional and self-referential processing, which could provide important insights into the pathology of BN.

Neuroticism and openness exhibit an anti-correlation pattern to dissociable default mode network: using resting connectivity and structural equation modeling analysis

The default mode network (DMN) can be subdivided into ventral and dorsal subsystems, which serve affective cognition and mental sense construction, respectively. An internally dissociated pattern of anti-correlations was observed between these two subsystems. Although numerous studies on neuroticism and openness have demonstrated the neurological functions of the DMN, little is known about whether different subsystems and hubs regions within the network are engaged in different functions in response to the two traits. We recruited 223 healthy volunteers in this study and collected their resting-state functional magnetic resonance imaging (fMRI) and NEO Five-Factor Inventory scores. We used independent component analysis (ICA) to obtain the DMN, before further decomposing it into the ventral and dorsal subsystems. Then, the network coherence of hubs regions within subsystems was extracted to construct two structural equation models (SEM) to explore the relationship between neuroticism and openness traits and DMN. We observed that the ventral DMN could significantly predict positive openness and negative neuroticism. The dorsal DMN was diametrically opposed. Additionally, the medial prefrontal cortex (mPFC) and middle temporal gyrus (MTG), both of which are core hubs of the subnetworks within the DMN, are significantly positively correlated with neuroticism and openness. These findings may point to a biological basis that neuroticism and openness are engaged in opposite mechanisms and support the hypothesis about the functional dissociation of the DMN.

Exploring functional connectivity in large-scale brain networks in obsessive-compulsive disorder: a systematic review of EEG and fMRI studies

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition that is difficult to treat due to our limited understanding of its pathophysiology. Functional connectivity in brain networks, as evaluated through neuroimaging studies, plays a pivotal role in understanding OCD. While both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been extensively employed in OCD research, few have fully synthesized their findings. To bridge this gap, we reviewed 166 studies (10 EEG, 156 fMRI) published up to December 2023. In EEG studies, OCD exhibited lower connectivity in delta and alpha bands, with inconsistent findings in other frequency bands. Resting-state fMRI studies reported conflicting connectivity patterns within the default mode network (DMN) and sensorimotor cortico-striato-thalamo-cortical (CSTC) circuitry. Many studies observed decreased resting-state connectivity between the DMN and salience network (SN), implicating the 'triple network model' in OCD. Task-related hyperconnectivity within the DMN-SN and hypoconnectivity between the SN and frontoparietal network suggest OCD-related cognitive inflexibility, potentially due to triple network dysfunction. In conclusion, our review highlights diverse connectivity differences in OCD, revealing complex brain network interplay that contributes to symptom manifestation. However, the presence of conflicting findings underscores the necessity for targeted research to achieve a comprehensive understanding of the pathophysiology of OCD.

An Exploratory Study of Large-Scale Brain Networks during Gambling Using SEEG

Decision-making is a cognitive process involving working memory, executive function, and attention. However, the connectivity of large-scale brain networks during decision-making is not well understood. This is because gaining access to large-scale brain networks in humans is still a novel process. Here, we used SEEG (stereoelectroencephalography) to record neural activity from the default mode network (DMN), dorsal attention network (DAN), and frontoparietal network (FN) in ten humans while they performed a gambling task in the form of the card game, "War". By observing these networks during a decision-making period, we related the activity of and connectivity between these networks. In particular, we found that gamma band activity was directly related to a participant's ability to bet logically, deciding what betting amount would result in the highest monetary gain or lowest monetary loss throughout a session of the game. We also found connectivity between the DAN and the relation to a participant's performance. Specifically, participants with higher connectivity between and within these networks had higher earnings. Our preliminary findings suggest that connectivity and activity between these networks are essential during decision-making.

A mediation approach in resting-state connectivity between the medial prefrontal cortex and anterior cingulate in mild cognitive impairment

Mild cognitive impairment (MCI) is recognized as the prodromal phase of dementia, a condition that can be either maintained or reversed through timely medical interventions to prevent cognitive decline. Considerable studies using functional magnetic resonance imaging (fMRI) have indicated that altered activity in the medial prefrontal cortex (mPFC) serves as an indicator of various cognitive stages of aging. However, the impacts of intrinsic functional connectivity in the mPFC as a mediator on cognitive performance in individuals with and without MCI have not been fully understood. In this study, we recruited 42 MCI patients and 57 healthy controls, assessing their cognitive abilities and functional brain connectivity patterns through neuropsychological evaluations and resting-state fMRI, respectively. The MCI patients exhibited poorer performance on multiple neuropsychological tests compared to the healthy controls. At the neural level, functional connectivity between the mPFC and the anterior cingulate cortex (ACC) was significantly weaker in the MCI group and correlated with multiple neuropsychological test scores. The result of the mediation analysis further demonstrated that functional connectivity between the mPFC and ACC notably mediated the relationship between the MCI and semantic fluency performance. These findings suggest that altered mPFC-ACC connectivity may have a plausible causal influence on cognitive decline and provide implications for early identifications of neurodegenerative diseases and precise monitoring of disease progression.

The Brain Salience Network at the Intersection of Pain and Substance use Disorders: Insights from Functional Neuroimaging Research

Purpose of Review

The brain's salience network (SN), primarily comprising the anterior insula and anterior cingulate cortex, plays a key role in detecting salient stimuli and processing physical and socioemotional pain (e.g., social rejection). Mounting evidence underscores an altered SN in the etiology and maintenance of substance use disorders (SUDs). This paper aims to synthesize recent functional neuroimaging research emphasizing the SN's involvement in SUDs and physical/socioemotional pain and explore the therapeutic prospects of targeting the SN for SUD treatment.

Recent Findings

The SN is repeatedly activated during the experience of both physical and socioemotional pain. Altered activation within the SN is associated with both SUDs and chronic pain conditions, characterized by aberrant activity and connectivity patterns as well as structural changes. Among individuals with SUDs, functional and structural alterations in the SN have been linked to abnormal salience attribution (e.g., heightened responsiveness to drug-related cues), impaired cognitive control (e.g., impulsivity), and compromised decision-making processes. The high prevalence of physical and socioemotional pain in the SUD population may further exacerbate SN alterations, thus contributing to hindered recovery progress and treatment failure. Interventions targeting the restoration of SN functioning, such as real-time functional MRI feedback, neuromodulation, and psychotherapeutic approaches, hold promise as innovative SUD treatments.

Summary

The review highlights the significance of alterations in the structure and function of the SN as potential mechanisms underlying the co-occurrence of SUDs and physical/socioemotional pain. Future work that integrates neuroimaging with other research methodologies will provide novel insights into the mechanistic role of the SN in SUDs and inform the development of next-generation treatment modalities.

Overlapping neural correlates underpin theory of mind and semantic cognition: Evidence from a meta-analysis of 344 functional neuroimaging studies

Key unanswered questions for cognitive neuroscience include whether social cognition is underpinned by specialised brain regions and to what extent it simultaneously depends on more domain-general systems. Until we glean a better understanding of the full set of contributions made by various systems, theories of social cognition will remain fundamentally limited. In the present study, we evaluate a recent proposal that semantic cognition plays a crucial role in supporting social cognition. While previous brain-based investigations have focused on dissociating these two systems, our primary aim was to assess the degree to which the neural correlates are overlapping, particularly within two key regions, the anterior temporal lobe (ATL) and the temporoparietal junction (TPJ). We focus on activation associated with theory of mind (ToM) and adopt a meta-analytic activation likelihood approach to synthesise a large set of functional neuroimaging studies and compare their results with studies of semantic cognition. As a key consideration, we sought to account for methodological differences across the two sets of studies, including the fact that ToM studies tend to use nonverbal stimuli while the semantics literature is dominated by language-based tasks. Overall, we observed consistent overlap between the two sets of brain regions, especially in the ATL and TPJ. This supports the claim that tasks involving ToM draw upon more general semantic retrieval processes. We also identified activation specific to ToM in the right TPJ, bilateral anterior mPFC, and right precuneus. This is consistent with the view that, nested amongst more domain-general systems, there is specialised circuitry that is tuned to social processes.

Contrasting topologies of synchronous and asynchronous functional brain networks

We generated asynchronous functional networks (aFNs) using a novel method called optimal causation entropy (oCSE) and compared aFN topology to the correlation-based synchronous functional networks (sFNs) which are commonly used in network neuroscience studies. Functional magnetic resonance imaging (fMRI) time series from 212 participants of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study were used to generate aFNs and sFNs. As a demonstration of how aFNs and sFNs can be used in tandem, we used multivariate mixed effects models to determine whether age interacted with node efficiency to influence connection probabilities in the two networks. After adjusting for differences in network density, aFNs had higher global efficiency but lower local efficiency than the sFNs. In the aFNs, nodes with the highest outgoing global efficiency tended to be in the brainstem and orbitofrontal cortex. aFN nodes with the highest incoming global efficiency tended to be members of the Default Mode Network (DMN) in sFNs. Age interacted with node global efficiency in aFNs and node local efficiency in sFNs to influence connection probability. We conclude that the sFN and aFN both offer information about functional brain connectivity which the other type of network does not.

Predicting performance in attention by measuring key metabolites in the PCC with 7T MRS

The posterior cingulate cortex (PCC) is a key hub of the default mode network and is known to play an important role in attention. Using ultra-high field 7 Tesla magnetic resonance spectroscopy (MRS) to quantify neurometabolite concentrations, this exploratory study investigated the effect of the concentrations of myo-inositol (Myo-Ins), glutamate (Glu), glutamine (Gln), aspartate or aspartic acid (Asp) and gamma-amino-butyric acid (GABA) in the PCC on attention in forty-six healthy participants. Each participant underwent an MRS scan and cognitive testing, consisting of a trail-making test (TMT A/B) and a test of attentional performance. After a multiple regression analysis and bootstrapping for correction, the findings show that Myo-Ins and Asp significantly influence (p < 0.05) attentional tasks. On one hand, Myo-Ins shows it can improve the completion times of both TMT A and TMT B. On the other hand, an increase in aspartate leads to more mistakes in Go/No-go tasks and shows a trend towards enhancing reaction time in Go/No-go tasks and stability of alertness without signal. No significant (p > 0.05) influence of Glu, Gln and GABA was observed.

Static and Temporal Dynamic in Functional Connectivity of Large-scale Brain Networks During Acute Stress Regulate Stress Resilience Differently: The Promotion Role of Trait Resilience

Stress resilience has been largely regarded as a process in which individuals actively cope with and recover from stress. Over the past decade, the emergence of large-scale brain networks has provided a new perspective for the study of the neural mechanisms of stress. However, the role of inter-network functional-connectivity (FC) and its temporal fluctuations in stress resilience is still unclear. To bridge this knowledge gap, seventy-seven participants (age, 17-22 years, 37 women) were recruited for a ScanSTRESS brain imaging study. A static perspective was initially adopted, using changes in FC that obtained from stress vs. control condition during the entire stress induction phase as a static indicator. Further, changes in FC between different stress runs were analyzed as an index of temporal dynamics. Stress resilience was gauged using salivary cortisol levels, while trait resilience was measured via behavioral-activation-system (BAS) sensitivity. Results found that, for the static index, enhanced FC between the salience-network (SN), default-mode-network (DMN) and limbic-network (LBN) during acute stress could negatively signal stress resilience. For the temporal dynamics index, FC among the dorsal-attention-network (DAN), central-executive-network (CEN) and visual-network (VN) decreased significantly during repeated stress induction. Moreover, the decline of FC positively signaled stress resilience, and this relationship only exist in people with high BAS. The current research elucidates the intricate neural underpinnings of stress resilience, offering insights into the adaptive mechanisms underlying effective stress responses.

Functional network reorganization after endovascular thrombectomy in patients with anterior circulation stroke

BACKGROUND

Endovascular thrombectomy has been confirmed to be an effective therapy for acute ischemic stroke (AIS). However, how functional brain networks reorganize after restoration of blood supply in AIS patients, and whether the degree of reperfusion associates with functional network changes remains unclear.

METHODS

Resting-state fMRI data were collected from 43 AIS patients with anterior circulation occlusion after thrombectomy and 37 healthy controls (HCs). Both static and dynamic functional connectivity (FC) within four advanced functional networks including dorsal attention network (DAN), ventral attention network (VAN), executive control network (ECN) and default mode network (DMN), were calculated and compared between post-thrombectomy patients and HCs, and between two subgroups of post-thrombectomy patients with different reperfusion conditions.

RESULTS

As compared to HCs, patients showed significant differences in static FC of four functional networks, and in dynamic FC of DAN, ECN and DMN. Furthermore, patients with better reperfusion conditions exhibited increased static FC with precuneus, and altered dynamic FC within precuneus. Moreover, these alterations were associated with clinical assessments of stroke severity and functional recovery in post-thrombectomy patients.

CONCLUSIONS

Collectively, these findings may provide the potential imaging markers for assessment of thrombectomy efficacy and help establish the specific rehabilitation treatments for post-thrombectomy patients.

Mechanisms of Neuronal Reactivation in Memory Consolidation: A Perspective from Pathological Conditions

Memory consolidation refers to a process by which labile newly formed memory traces are progressively strengthened into long term memories and become more resistant to interference. Recent work has revealed that spontaneous hippocampal activity during rest, commonly referred to as "offline" activity, plays a critical role in the process of memory consolidation. Hippocampal reactivation occurs during sharp-wave ripples (SWRs), which are events associated with highly synchronous neural firing in the hippocampus and modulation of neural activity in distributed brain regions. Memory consolidation occurs primarily through a coordinated communication between hippocampus and neocortex. Cortical slow oscillations drive the repeated reactivation of hippocampal memory representations together with SWRs and thalamo-cortical spindles, inducing long-lasting cellular and network modifications responsible for memory stabilization.In this review, we aim to comprehensively cover the field of "reactivation and memory consolidation" research by detailing the physiological mechanisms of neuronal reactivation and firing patterns during SWRs and providing a discussion of more recent key findings. Several mechanistic explanations of neuropsychiatric diseases propose that impaired neural replay may underlie some of the symptoms of the disorders. Abnormalities in neuronal reactivation are a common phenomenon and cause pathological impairment in several diseases, such as Alzheimer's disease (AD), epilepsy and schizophrenia. However, the specific pathological changes and mechanisms of reactivation in each disease are different. Recent work has also enlightened some of the underlying pathological mechanisms of neuronal reactivation in these diseases. In this review, we further describe how SWRs, ripples and slow oscillations are affected in Alzheimer's disease, epilepsy, and schizophrenia. We then compare the differences of neuronal reactivation and discuss how different reactivation abnormalities cause pathological changes in these diseases. Aberrant neural reactivation provides insights into disease pathogenesis and may even serve as biomarkers for early disease progression and treatment response.

Mediodorsal thalamus and ventral pallidum contribute to subcortical regulation of the default mode network

Humans and other animals readily transition from externally to internally focused attention, and these transitions are accompanied by activation of the default mode network (DMN). The DMN was considered a cortical network, yet recent evidence suggests subcortical structures are also involved. We investigated the role of ventral pallidum (VP) and mediodorsal thalamus (MD) in DMN regulation in tree shrew, a close relative of primates. Electrophysiology and deep learning-based classification of behavioral states revealed gamma oscillations in VP and MD coordinated with gamma in anterior cingulate (AC) cortex during DMN states. Cross-frequency coupling between gamma and delta oscillations was higher during DMN than other behaviors, underscoring the engagement of MD, VP and AC. Our findings highlight the importance of VP and MD in DMN regulation, extend homologies in DMN regulation among mammals, and underline the importance of thalamus and basal forebrain to the regulation of DMN.

A review of the application of exercise intervention on improving cognition in patients with Alzheimer's disease: mechanisms and clinical studies

Alzheimer's disease (AD) is the most common form of dementia, leading to sustained cognitive decline. An increasing number of studies suggest that exercise is an effective strategy to promote the improvement of cognition in AD. Mechanisms of the benefits of exercise intervention on cognitive function may include modulation of vascular factors by affecting cardiovascular risk factors, regulating cardiorespiratory health, and enhancing cerebral blood flow. Exercise also promotes neurogenesis by stimulating neurotrophic factors, affecting neuroplasticity in the brain. Additionally, regular exercise improves the neuropathological characteristics of AD by improving mitochondrial function, and the brain redox status. More and more attention has been paid to the effect of Aβ and tau pathology as well as sleep disorders on cognitive function in persons diagnosed with AD. Besides, there are various forms of exercise intervention in cognitive improvement in patients with AD, including aerobic exercise, resistance exercise, and multi-component exercise. Consequently, the purpose of this review is to summarize the findings of the mechanisms of exercise intervention on cognitive function in patients with AD, and also discuss the application of different exercise interventions in cognitive impairment in AD to provide a theoretical basis and reference for the selection of exercise intervention in cognitive rehabilitation in AD.

Functional connectivity associations with menstrual pain characteristics in adolescents: an investigation of the triple network model

ABSTRACT

Menstrual pain is associated with deficits in central pain processing, yet neuroimaging studies to date have all been limited by focusing on group comparisons of adult women with vs without menstrual pain. This study aimed to investigate the role of the triple network model (TNM) of brain networks in adolescent girls with varied menstrual pain severity ratings. One hundred participants (ages 13-19 years) completed a 6-min resting state functional magnetic resonance imaging (fMRI) scan and rated menstrual pain severity, menstrual pain interference, and cumulative menstrual pain exposure. Imaging analyses included age and gynecological age (years since menarche) as covariates. Menstrual pain severity was positively associated with functional connectivity between the cingulo-opercular salience network (cSN) and the sensory processing regions, limbic regions, and insula, and was also positively associated with connectivity between the left central executive network (CEN) and posterior regions. Menstrual pain interference was positively associated with connectivity between the cSN and widespread brain areas. In addition, menstrual pain interference was positively associated with connectivity within the left CEN, whereas connectivity both within the right CEN and between the right CEN and cortical areas outside the network (including the insula) were negatively associated with menstrual pain interference. Cumulative menstrual pain exposure shared a strong negative association with connectivity between the default mode network and other widespread regions associated with large-scale brain networks. These findings support a key role for the involvement of TNM brain networks in menstrual pain characteristics and suggest that alterations in pain processing exist in adolescents with varying levels of menstrual pain.

A synergistic workspace for human consciousness revealed by Integrated Information Decomposition

How is the information-processing architecture of the human brain organised, and how does its organisation support consciousness? Here, we combine network science and a rigorous information-theoretic notion of synergy to delineate a 'synergistic global workspace', comprising gateway regions that gather synergistic information from specialised modules across the human brain. This information is then integrated within the workspace and widely distributed via broadcaster regions. Through functional MRI analysis, we show that gateway regions of the synergistic workspace correspond to the human brain's default mode network, whereas broadcasters coincide with the executive control network. We find that loss of consciousness due to general anaesthesia or disorders of consciousness corresponds to diminished ability of the synergistic workspace to integrate information, which is restored upon recovery. Thus, loss of consciousness coincides with a breakdown of information integration within the synergistic workspace of the human brain. This work contributes to conceptual and empirical reconciliation between two prominent scientific theories of consciousness, the Global Neuronal Workspace and Integrated Information Theory, while also advancing our understanding of how the human brain supports consciousness through the synergistic integration of information.

Associations between tinnitus and body composition: a cross-sectional study

The relationship between tinnitus and body composition in specific regions has not been extensively investigated. This study aimed to identify associations between tinnitus and body composition. Individuals with data on physical and otological examination findings, and bioelectrical impedance analysis were included from the ninth Korea National Health and Nutritional Examination Survey. They were divided into a tinnitus group and a non-tinnitus group. Participants with tinnitus were further classified into acute or chronic tinnitus group. The tinnitus group showed significantly higher body fat percentages in each region (arms: P = 0.014; legs: P = 0.029; trunk: P = 0.008; whole body: P = 0.010) and waist circumference (P = 0.007) than the non-tinnitus group, and exhibited lower leg muscle percentage (P = 0.038), total body fluid percentage (P = 0.010), and intracellular fluid percentage (P = 0.009) than the non-tinnitus group in men. Furthermore, men with chronic tinnitus showed a significantly higher trunk fat percentage (P = 0.015) and waist circumference (P = 0.043), and lower intracellular fluid percentage (P = 0.042) than their counterparts without tinnitus. No significant differences in body composition were observed among the groups in the female population. In men, body composition may be associated with tinnitus.

Callousness, exploitativeness, and tracking of cooperation incentives in the human default network

Human cognitive capacities that enable flexible cooperation may have evolved in parallel with the expansion of frontoparietal cortical networks, particularly the default network. Conversely, human antisocial behavior and trait antagonism are broadly associated with reduced activity, impaired connectivity, and altered structure of the default network. Yet, behaviors like interpersonal manipulation and exploitation may require intact or even superior social cognition. Using a reinforcement learning model of decision-making on a modified trust game, we examined how individuals adjusted their cooperation rate based on a counterpart's cooperation and social reputation. We observed that learning signals in the default network updated the predicted utility of cooperation or defection and scaled with reciprocal cooperation. These signals were weaker in callous (vs. compassionate) individuals but stronger in those who were more exploitative (vs. honest and humble). Further, they accounted for associations between exploitativeness, callousness, and reciprocal cooperation. Separately, behavioral sensitivity to prior reputation was reduced in callous but not exploitative individuals and selectively scaled with responses of the medial temporal subsystem of the default network. Overall, callousness was characterized by blunted behavioral and default network sensitivity to cooperation incentives. Exploitativeness predicted heightened sensitivity to others' cooperation but not social reputation. We speculate that both compassion and exploitativeness may reflect cognitive adaptations to social living, enabled by expansion of the default network in anthropogenesis.

Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain

While the hippocampus is key for human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, which shows anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species followed an anterior-posterior axis, we observed a marked reconfiguration in the latter across species, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Here we show that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding within heteromodal association networks.

Comprehension of English for-adverbials: The Nature of Lexical Meanings and the Neurocognitive Architecture of Language

What is the nature of lexical meanings such that they can both compose with others and also appear boundless? We investigate this question by examining the compositional properties of for-time adverbial as in "Ana jumped for an hour." At issue is the source of the associated iterative reading which lacks overt morphophonological support, yet, the iteration is not disconnected from the lexical meanings in the sentence. This suggests an analysis whereby the iterative reading is the result of the interaction between lexical meanings under a specific compositional configuration. We test the predictions of two competing accounts: Mismatch-and-Repair and Partition-Measure. They differ in their assumptions about lexical meanings: assumptions that have implications for the possible compositional mechanisms that each can invoke. Mismatch-and-Repair assumes that lexical meaning representations are discrete, separate from the conceptual system from which they originally emerged and brought into sentence meaning through syntactic composition. Partition-Measure assumes that lexical meanings are contextually salient conceptual structures substantially indistinguishable from the conceptual system that they inhabit. During comprehension, lexical meanings construe a conceptual representation, in parallel, morphosyntactic and morphophonological composition as determined by the lexical items involved in the sentence. Whereas both hypotheses capture the observed cost in the punctual predicate plus for-time adverbial composition (e.g., jump (vs. swim) for an hour), their predictions differ regarding iteration with durative predicates; for example, swim for a year (vs. for an hour). Mismatch-and-Repair predicts contrasting processing profiles and nonoverlapping activation patterns along punctuality differences. Partition-Measure predicts overlapping processing and cortical distribution profiles, along the presence of iterativity. Results from a self-paced reading and an functional Magnetic Resonance Imaging (fMRI) studies bear out the predictions of the Partition-Measure account, supporting a view of linguistic meaning composition in line with an architecture of language whereby combinatoriality and generativity are distributed, carried out in parallel across linguistic and nonlinguistic subsystems.

Brain state dynamics differ between eyes open and eyes closed rest

The human brain exhibits spatio-temporally complex activity even in the absence of external stimuli, cycling through recurring patterns of activity known as brain states. Thus far, brain state analysis has primarily been restricted to unimodal neuroimaging data sets, resulting in a limited definition of state and a poor understanding of the spatial and temporal relationships between states identified from different modalities. Here, we applied hidden Markov model (HMM) to concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI) eyes open (EO) and eyes closed (EC) resting-state data, training models on the EEG and fMRI data separately, and evaluated the models' ability to distinguish dynamics between the two rest conditions. Additionally, we employed a general linear model approach to identify the BOLD correlates of the EEG-defined states to investigate whether the fMRI data could be used to improve the spatial definition of the EEG states. Finally, we performed a sliding window-based analysis on the state time courses to identify slower changes in the temporal dynamics, and then correlated these time courses across modalities. We found that both models could identify expected changes during EC rest compared to EO rest, with the fMRI model identifying changes in the activity and functional connectivity of visual and attention resting-state networks, while the EEG model correctly identified the canonical increase in alpha upon eye closure. In addition, by using the fMRI data, it was possible to infer the spatial properties of the EEG states, resulting in BOLD correlation maps resembling canonical alpha-BOLD correlations. Finally, the sliding window analysis revealed unique fractional occupancy dynamics for states from both models, with a selection of states showing strong temporal correlations across modalities. Overall, this study highlights the efficacy of using HMMs for brain state analysis, confirms that multimodal data can be used to provide more in-depth definitions of state and demonstrates that states defined across different modalities show similar temporal dynamics.

Atypical intrinsic neural timescale in the left angular gyrus in Alzheimer's disease

Alzheimer's disease is characterized by cognitive impairment and progressive brain atrophy. Recent human neuroimaging studies reported atypical anatomical and functional changes in some regions in the default mode network in patients with Alzheimer's disease, but which brain area of the default mode network is the key region whose atrophy disturbs the entire network activity and consequently contributes to the symptoms of the disease remains unidentified. Here, in this case-control study, we aimed to identify crucial neural regions that mediated the phenotype of Alzheimer's disease, and as such, we examined the intrinsic neural timescales-a functional metric to evaluate the capacity to integrate diverse neural information-and grey matter volume of the regions in the default mode network using resting-state functional MRI images and structural MRI data obtained from individuals with Alzheimer's disease and cognitively typical people. After confirming the atypically short neural timescale of the entire default mode network in Alzheimer's disease and its link with the symptoms of the disease, we found that the shortened neural timescale of the default mode network was associated with the aberrantly short neural timescale of the left angular gyrus. Moreover, we revealed that the shortened neural timescale of the angular gyrus was correlated with the atypically reduced grey matter volume of this parietal region. Furthermore, we identified an association between the neural structure, brain function and symptoms and proposed a model in which the reduced grey matter volume of the left angular gyrus shortened the intrinsic neural time of the region, which then destabilized the entire neural timescale of the default mode network and resultantly contributed to cognitive decline in Alzheimer's disease. These findings highlight the key role of the left angular gyrus in the anatomical and functional aetiology of Alzheimer's disease.

Disrupted Brain Network Measures in Parkinson's Disease Patients with Severe Hyposmia and Cognitively Normal Ability

Neuroscience has revolved around brain structural changes, functional activity, and connectivity alteration in Parkinson's Disease (PD); however, how the network topology organization becomes altered is still unclear, specifically in Parkinson's patients with severe hyposmia. In this study, we have examined the functional network topological alteration in patients affected by Parkinson's Disease with normal cognitive ability (ODN), Parkinson's Disease with severe hyposmia (ODP), and healthy controls (HCs) using resting-state functional magnetic resonance imaging (rsfMRI) data. We have analyzed brain topological organization using popular graph measures such as network segregation (clustering coefficient, modularity), network integration (participation coefficient, path length), small-worldness, efficiency, centrality, and assortativity. Then, we used a feature ranking approach based on the diagonal adaptation of neighborhood component analysis, aiming to determine a graph measure that is sensitive enough to distinguish between these three different groups. We noted significantly lower segregation and local efficiency and small-worldness in ODP compared to ODN and HCs. On the contrary, we did not find differences in network integration in ODP compared to ODN and HCs, which indicates that the brain network becomes fragmented in ODP. At the brain network level, a progressive increase in the DMN (Default Mode Network) was observed from healthy controls to ODN to ODP, and a continuous decrease in the cingulo-opercular network was observed from healthy controls to ODN to ODP. Further, the feature ranking approach has shown that the whole-brain clustering coefficient and small-worldness are sensitive measures to classify ODP vs. ODN, as well as HCs. Looking at the brain regional network segregation, we have found that the cerebellum and limbic, fronto-parietal, and occipital lobes have higher ODP reductions than ODN and HCs. Our results suggest network topological measures, specifically whole-brain segregation and small-worldness decreases. At the network level, an increase in DMN and a decrease in the cingulo-opercular network could be used as biomarkers to characterize ODN and ODP.

Network mechanisms of ongoing brain activity's influence on conscious visual perception

Sensory inputs enter a constantly active brain, whose state is always changing from one moment to the next. Currently, little is known about how ongoing, spontaneous brain activity participates in online task processing. We employed 7 Tesla fMRI and a threshold-level visual perception task to probe the effects of prestimulus ongoing brain activity on perceptual decision-making and conscious recognition. Prestimulus activity originating from distributed brain regions, including visual cortices and regions of the default-mode and cingulo-opercular networks, exerted a diverse set of effects on the sensitivity and criterion of conscious recognition, and categorization performance. We further elucidate the mechanisms underlying these behavioral effects, revealing how prestimulus activity modulates multiple aspects of stimulus processing in highly specific and network-dependent manners. These findings reveal heretofore unknown network mechanisms underlying ongoing brain activity's influence on conscious perception, and may hold implications for understanding the precise roles of spontaneous activity in other brain functions.

What makes an event significant: an fMRI study on self-defining memories

Self-defining memories are highly significant personal memories that contribute to an individual's life story and identity. Previous research has identified 4 key subcomponents of self-defining memories: content, affect, specificity, and self-reflection. However, these components were not tested under functional neuroimaging. In this study, we first explored how self-defining memories distinguish themselves from everyday memories (non-self-defining) through their associated brain activity. Next, we evaluated the different self-defining memory subcomponents through their activity in the underlying brain system. Participants recalled both self-defining and non-self-defining memories under functional MRI and evaluated the 4 subcomponents for each memory. Multivoxel pattern analysis uncovered a brain system closely related to the default mode network to discriminate between self-defining and non-self-defining memories. Representational similarity analysis revealed the neural coding of each subcomponent. Self-reflection was coded mainly in the precuneus, middle and inferior frontal gyri, and cingulate, lateral occipital, and insular cortices. To a much lesser extent, content coding was primarily in the left angular gyrus and fusiform gyrus. No region was found to represent information on affect and specificity. Our findings highlight the marked difference in brain processing between significant and non-significant memories, and underscore self-reflection as a predominant factor in the formation and maintenance of self-defining memories, inviting a reassessment of what constitutes significant memories.

Frequency-specific directed connectivity between the hippocampus and parietal cortex during verbal and spatial episodic memory: an intracranial EEG replication

Hippocampus-parietal cortex circuits are thought to play a crucial role in memory and attention, but their neural basis remains poorly understood. We employed intracranial intracranial electroencephalography (iEEG) to investigate the neurophysiological underpinning of these circuits across three memory tasks spanning verbal and spatial domains. We uncovered a consistent pattern of higher causal directed connectivity from the hippocampus to both lateral parietal cortex (supramarginal and angular gyrus) and medial parietal cortex (posterior cingulate cortex) in the delta-theta band during memory encoding and recall. This connectivity was independent of activation or suppression states in the hippocampus or parietal cortex. Crucially, directed connectivity from the supramarginal gyrus to the hippocampus was enhanced in participants with higher memory recall, highlighting its behavioral significance. Our findings align with the attention-to-memory model, which posits that attention directs cognitive resources toward pertinent information during memory formation. The robustness of these results was demonstrated through Bayesian replication analysis of the memory encoding and recall periods across the three tasks. Our study sheds light on the neural basis of casual signaling within hippocampus-parietal circuits, broadening our understanding of their critical roles in human cognition.

Auditory cortical regions show resting-state functional connectivity with the default mode-like network in echolocating bats

Echolocating bats are among the most social and vocal of all mammals. These animals are ideal subjects for functional MRI (fMRI) studies of auditory social communication given their relatively hypertrophic limbic and auditory neural structures and their reduced ability to hear MRI gradient noise. Yet, no resting-state networks relevant to social cognition (e.g., default mode-like networks or DMLNs) have been identified in bats since there are few, if any, fMRI studies in the chiropteran order. Here, we acquired fMRI data at 7 Tesla from nine lightly anesthetized pale spear-nosed bats (Phyllostomus discolor). We applied independent components analysis (ICA) to reveal resting-state networks and measured neural activity elicited by noise ripples (on: 10 ms; off: 10 ms) that span this species' ultrasonic hearing range (20 to 130 kHz). Resting-state networks pervaded auditory, parietal, and occipital cortices, along with the hippocampus, cerebellum, basal ganglia, and auditory brainstem. Two midline networks formed an apparent DMLN. Additionally, we found four predominantly auditory/parietal cortical networks, of which two were left-lateralized and two right-lateralized. Regions within four auditory/parietal cortical networks are known to respond to social calls. Along with the auditory brainstem, regions within these four cortical networks responded to ultrasonic noise ripples. Iterative analyses revealed consistent, significant functional connectivity between the left, but not right, auditory/parietal cortical networks and DMLN nodes, especially the anterior-most cingulate cortex. Thus, a resting-state network implicated in social cognition displays more distributed functional connectivity across left, relative to right, hemispheric cortical substrates of audition and communication in this highly social and vocal species.

Evaluating the Effect of Alzheimer's Disease-Related Biomarker Change in Corticobasal Syndrome and Progressive Supranuclear Palsy

OBJECTIVES

To evaluate the effect of Alzheimer's disease (AD) -related biomarker change on clinical features, brain atrophy and functional connectivity of patients with corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP).

METHODS

Data from patients with a clinical diagnosis of CBS, PSP, and AD and healthy controls were obtained from the 4-R-Tauopathy Neuroimaging Initiative 1 and 2, the Alzheimer's Disease Neuroimaging Initiative, and a local cohort from the Toronto Western Hospital. Patients with CBS and PSP were divided into AD-positive (CBS/PSP-AD) and AD-negative (CBS/PSP-noAD) groups based on fluid biomarkers and amyloid PET scans. Cognitive, motor, and depression scores; AD fluid biomarkers (cerebrospinal p-tau, t-tau, and amyloid-beta, and plasma ptau-217); and neuroimaging data (amyloid PET, MRI and fMRI) were collected. Clinical features, whole-brain gray matter volume and functional networks connectivity were compared across groups.

RESULTS

Data were analyzed from 87 CBS/PSP-noAD and 23 CBS/PSP-AD, 18 AD, and 30 healthy controls. CBS/PSP-noAD showed worse performance in comparison to CBS/PSP-AD in the PSPRS [mean(SD): 34.8(15.8) vs 23.3(11.6)] and the UPDRS scores [mean(SD): 34.2(17.0) vs 21.8(13.3)]. CBS/PSP-AD demonstrated atrophy in AD signature areas and brainstem, while CBS/PSP-noAD patients displayed atrophy in frontal and temporal areas, globus pallidus, and brainstem compared to healthy controls. The default mode network showed greatest disconnection in CBS/PSP-AD compared with CBS/PSP-no AD and controls. The thalamic network connectivity was most affected in CBS/PSP-noAD.

INTERPRETATION

AD biomarker positivity may modulate the clinical presentation of CBS/PSP, with evidence of distinctive structural and functional brain changes associated with the AD pathology/co-pathology. ANN NEUROL 2024;96:99-109.

The crucial role of the cerebellum in autism spectrum disorder: Neuroimaging, neurobiological, and anatomical insights

Background and Aims

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by a wide range of symptoms and challenges. While ASD is primarily associated with atypical social and communicative behaviors, increasing research has pointed towards the involvement of various brain regions, including the cerebellum. This review article aims to provide a comprehensive overview of the role of cerebellar lobules in ASD, highlighting recent findings and potential therapeutic implications.

Methods

Using published articles found in PubMed, Scopus, and Google Scholar, we extracted pertinent data to complete this review work. We have searched for terms including anatomical insights, neuroimaging, neurobiological, and autism spectrum disorder.

Results

The intricate relationship between the cerebellum and other brain regions linked to ASD has been highlighted by neurobiological research, which has shown abnormalities in neurotransmitter systems and cerebellar circuitry. The relevance of the cerebellum in the pathophysiology of ASD has been further highlighted by anatomical studies that have revealed evidence of cerebellar abnormalities, including changes in volume, morphology, and connectivity.

Conclusion

Thorough knowledge of the cerebellum's function in ASD may lead to new understandings of the underlying mechanisms of the condition and make it easier to create interventions and treatments that are more specifically targeted at treating cerebellar dysfunction in ASD patients.

Deep Brain Stimulation Modulates the Visual Pathway to Improve Freezing of Gait in Parkinson's Disease Patients

OBJECTIVE

To investigate the involvement of the visual cortex in improving freezing of gait (FoG) after subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD) patients using whole-brain seed-based functional connectivity.

METHODS

A total of 66 PD patients with FoG who underwent bilateral STN-DBS were included in our study. Patients were divided into a FoG responder group and an FoG nonresponder group according to whether FoG improved 1 year after DBS. We compared the differences in clinical characteristics, brain structural imaging, and seed-based functional connectivity between the 2 groups. The locations of active contacts were further analyzed.

RESULTS

All PD patients benefited from STN-DBS. No significant differences in the baseline characteristics or brain structures were found between the 2 groups. Seed-based functional connectivity analysis revealed that better connectivity in bilateral primary visual areas was associated with better clinical improvement in FoG (P < 0.05 familywise error corrected). Further analysis revealed that this disparity was associated with the location of the active contacts within the rostral region of the sensorimotor subregion in the FoG responder group, in contrast to the findings in the FoG nonresponder group.

CONCLUSIONS

This study suggested that DBS in the rostral region of the STN sensorimotor subregion may alleviate FoG by strengthening functional connectivity in primary visual areas, which has significant implications for guiding surgical strategies for FoG in the future.

Gradient synchronization for multivariate functional data, with application to brain connectivity

Quantifying the association between components of multivariate random curves is of general interest and is a ubiquitous and basic problem that can be addressed with functional data analysis. An important application is the problem of assessing functional connectivity based on functional magnetic resonance imaging (fMRI), where one aims to determine the similarity of fMRI time courses that are recorded on anatomically separated brain regions. In the functional brain connectivity literature, the static temporal Pearson correlation has been the prevailing measure for functional connectivity. However, recent research has revealed temporally changing patterns of functional connectivity, leading to the study of dynamic functional connectivity. This motivates new similarity measures for pairs of random curves that reflect the dynamic features of functional similarity. Specifically, we introduce gradient synchronization measures in a general setting. These similarity measures are based on the concordance and discordance of the gradients between paired smooth random functions. Asymptotic normality of the proposed estimates is obtained under regularity conditions. We illustrate the proposed synchronization measures via simulations and an application to resting-state fMRI signals from the Alzheimer's Disease Neuroimaging Initiative and they are found to improve discrimination between subjects with different disease status.

Global Effect on Cortical Activity in Young Indian Males in Response to "OM" Chanting: A High-Density Quantitative Electro-Encephalography Study

Background

Meditation using the "OM" mantra is the most widely used practice in India. Though reports have been published about the relaxation effect during both verbal "OM" chanting and listening to "OM" chanting, there is a paucity of literature concerning the cortical areas activated/deactivated after verbal "OM" chanting and listening to "OM" chanting using quantitative electro-encephalography (qEEG).

Purpose

The objective of this study was to compare the effects of verbal "OM" chanting and listening to "OM" chanting on cortical sources as compared to baseline, as assessed by qEEG.

Method

Twenty adult male subjects with a mean age of 27.5 ± 7.5 years and no past or present history of psychiatric, neurological, or auditory disorders or previous exposure to yoga and meditation were recruited from the undergraduate and postgraduate student population of AIIMS, New Delhi. Subjects were given a paradigm designed using E-prime for both verbal and listening to "OM" chanting of 5 min each and a 5-min relaxation period in between the tasks. Electroencephalography recording was done using a 128-channel geodesic sensor net with band-pass filtered at 1-70 Hz, and 20-sec data of eyes-closed condition, post-verbal "OM", and post-listening to "OM" chanting were segmented and pre-processed. Further, source analysis was performed on the data using standardized low-resolution electromagnetic tomography.

Result

The pre (baseline) versus post-verbal "OM" (p < .05) and post-listening to "OM" (p < .05) chanting showed significant differences in similar cortical areas in both verbal "OM" and listening to "OM" chanting except the three areas, that is, the orbital gyrus, the rectal gyrus, and the sub-callosal gyrus, which were additionally activated post-listening to "OM" chanting. Both verbal and listening to "OM" chanting induced activation of similar cortical areas, which were classified as the nodes/hubs of specific resting-state networks (RSNs) such as the attentional network, frontoparietal control network, and default mode network.

Conclusion

The study results suggest that "OM" chanting could facilitate flexible switching between various RSNs to induce a relaxed state and could improve attention simultaneously.Both verbal and listening to "OM" chanting induced common activated areas that are classified into frontoparietal, dorsal attention, and default mode network areas. And it is hypothesized that flexible switching between these RSNs could induce a relaxed state and improve attention simultaneously with the possible role of the frontoparietal network.

Time, valence, and imagination: a comparative study of thoughts in restricted and unrestricted mind wandering

William James' "stream of thought" is a key component of human cognition. Such thoughts arise in both restricted and unrestricted contexts, either with or without the presence of a secondary task. This study examines the similarities and differences in thoughts produced in these two contexts, which we call restricted and unrestricted mind wandering. Participants performed a mindfulness task representing restricted mind wandering and an unrestricted thought task where they spontaneously explored thoughts, reporting them as they arose. Participants then self-rated their thoughts based on valence, temporal orientation (past/present/future), and reality orientation (imaginary vs. real). Participants' emotional states were also evaluated using the Emotion Recall Task (ERT) and the PANAS questionnaire. Unrestricted mind wandering generated more thoughts, which were more positive and future-oriented than those in restricted mind wandering. Additionally, participants' thought valence correlated with their PANAS and ERT scores. Approximately 1 out of 4 thoughts in both restricted and unrestricted mind wandering were imaginary, with increased future orientation linked to more imaginative thought. Despite the statistical differences separating restricted and unrestricted thought, effect sizes were predominantly small, indicating that the thoughts arise during these two types of mind wandering are largely of the same kind.