Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease

Reconstruction and application of multilayer brain network for juvenile myoclonic epilepsy based on link prediction

Juvenile myoclonic epilepsy (JME) exhibits abnormal functional connectivity of brain networks at multiple frequencies. We used the multilayer network model to address the heterogeneous features at different frequencies and assess the mechanisms of functional integration and segregation of brain networks in JME patients. To address the possibility of false edges or missing edges during network construction, we combined multilayer networks with link prediction techniques. Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 40 JME patients and 40 healthy controls. The Multilayer Network framework is utilized to integrate information from different frequency bands and to fuse similarity metrics for link prediction. Finally, calculate the entropy of the multiplex degree and multilayer clustering coefficient of the reconfigured multilayer frequency network. The results showed that the multilayer brain network of JME patients had significantly reduced ability to integrate and separate information and significantly correlated with severity of JME symptoms. This difference was particularly evident in default mode network (DMN), motor and somatosensory network (SMN), and auditory network (AN). In addition, significant differences were found in the precuneus, suboccipital gyrus, middle temporal gyrus, thalamus, and insula. Results suggest that JME patients have abnormal brain function and reduced cross-frequency interactions. This may be due to changes in the distribution of connections within and between the DMN, SMN, and AN in multiple frequency bands, resulting in unstable connectivity patterns. The generation of these changes is related to the pathological mechanisms of JME and may exacerbate cognitive and behavioral problems in patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10191-0.

Structural Network Hubs as Potential Organs at Risk in Glioma Patients After Radiation Therapy

PURPOSE

Cognitive sequelae are a concern in glioma patients postradiation therapy. As there is uncertainty regarding which brain regions to spare during radiation therapy to preserve cognition, we explored structural brain network hubs as potential organs at risk.

METHODS AND MATERIALS

We conducted a cross-sectional study, involving 39 irradiated adult WHO grade 2 and 3 gliomas along with 50 healthy controls. Cognitive domains (language, memory, attention, motor-, and executive functioning) were assessed ≥1 year postradiation therapy. Using multishell diffusion-weighted imaging, weighted structural graphs were constructed, and graph measures calculated to define hubs. The association between mean radiation therapy (RT) dose in each region and nodal strength and cognitive domains were tested with a linear regression model and Spearman's rho correlations, respectively.

RESULTS

Lower nodal strength was significantly associated with increasing RT dose in 9 brain regions, significantly (McNemar test, P < .01) impacting hubs more often than nonhubs (58% vs 7%). Executive performance (r(37) ≥ -.474, PFDR ≤ .045) and attention (r(37) ≥ -.471, PFDR ≤ .045) were significantly correlated with RT doses to the left pre- and postcentral gyrus and right posterior cingulate cortex, whereas poorer language outcomes were observed in patients receiving higher doses to the left insula, superior frontal, and precentral gyrus (r(37) ≥ -.460, PFDR ≤ .045). These correlations were more prevalent in hubs than nonhubs (P = .33), and higher than those between memory and left (r(37) = -.359) and right (r(37) = .059) hippocampal dose.

CONCLUSIONS

Higher RT doses to specific brain regions, particularly left-sided hubs, were associated with reduced nodal strength (ie, lower network centrality) and poorer cognitive performance. Although baseline cognitive testing is unavailable and cognitive functioning is influenced by multiple factors, this study highlights the potential value of network- or hub-sparing RT dose planning. Future longitudinal studies are needed to validate these findings before clinical implementation.

Understanding the complex interplay between tau, amyloid and the network in the spatiotemporal progression of Alzheimer's disease

INTRODUCTION

The interaction of amyloid and tau in neurodegenerative diseases is a central feature of AD pathophysiology. While experimental studies point to various interaction mechanisms, their causal direction and mode (local, remote or network-mediated) remain unknown in human subjects. The aim of this study was to compare mathematical reaction-diffusion models encoding distinct cross-species couplings to identify which interactions were key to model success.

METHODS

We tested competing mathematical models of network spread, aggregation, and amyloid-tau interactions on publicly available data from ADNI.

RESULTS

Although network spread models captured the spatiotemporal evolution of tau and amyloid in human subjects, the model including a one-way amyloid-to-tau aggregation interaction performed best.

DISCUSSION

This mathematical exposition of the "pas de deux" of co-evolving proteins provides quantitative, whole-brain support to the concept of amyloid-facilitated-tauopathy rather than the classic amyloid-cascade or pure-tau hypotheses, and helps explain certain known but poorly understood aspects of AD.

Neural correlates of psychotherapy in mental disorders: A meta-analysis of longitudinal resting-state fMRI studies

BACKGROUND

Psychotherapy is a crucial approach in the treatment of mental disorders. However, how psychotherapy modulate spontaneous brain activity and finally take therapeutic effects remain unknown. Among countless number of analytic methods of resting-state functional magnetic resonance imaging (rs-fMRI), Regional Homogeneity (ReHo), Degree Centrality (DC), and Amplitude of Low Frequency Fluctuation (ALFF), are commonly used voxel-wise whole-brain (VWWB) metrics, and these studies could be used for coordinate-based meta-analysis. In order to reveal the underlying neural mechanisms of psychotherapy in patients with mental disorders, serving for future precise targeting intervention, we conducted a systematic review and meta-analysis based on rs-fMRI studies at VWWB level.

MATERIAL AND METHODS

A systematic literature search was conducted in PubMed, PsycINFO, and Web of Science following PRISMA criteria (registration number CRD42023432388) to investigate the differences between pre- and post-psychotherapy. To investigate whether changes in spontaneous brain activity differ across different metrics, distinct psychotherapy approaches or specific patient populations, subgroup analyses were performed.

RESULTS

Nine studies involving a total of 192 patients were included. We observed a significant decrease in spontaneous activity within the left insular after treatment with psychotherapy. Moreover, the subgroup analysis revealed significantly decreased ReHo in the right inferior frontal gyrus.

CONCLUSIONS

The current study indicates that the clinical efficacy of psychotherapy may be modulated by insular and right inferior frontal gyrus through neurological perspective. This contributes to our understanding of the neurobiological mechanisms of psychotherapy and provides valuable insights into improving precise targeting interventions for individuals with mental disorders.

Repeatability and reliability of cerebrovascular reactivity in young adults using multi-echo, multi-contrast MRI

Cerebrovascular reactivity (CVR) shows promise as a biomarker of vascular integrity and may benefit from a repeatable, reliable, and microvasculature-sensitive acquisition. A combined spin- and gradient-echo (SAGE) functional MRI (fMRI) acquisition may improve repeatability and reliability compared to single spin- (SE) and gradient-echo (GRE) fMRI and provide a microvascular-weighted analysis. The most repeatable and reliable MRI acquisition CVR maps were compared across three CVR paradigms: a breath-hold task, a breath modulation task, and a resting state acquisition. SAGE-fMRI data was acquired in fifteen young adults at two timepoints. Mean gray matter (GM) within-subject coefficient of variation (wCV) and intraclass correlation coefficient (ICC) were compared within the quantitative and weighted SAGE-fMRI CVR maps and single GRE- and SE-fMRI CVR. Total and microvascular MRI inputs with lowest wCV and highest ICC were used to compare three CVR paradigms. Total and microvascular weighted SAGE-fMRI CVR had the lowest wCV and highest ICC across paradigms. The breath-hold paradigm produced significantly higher GM CVR estimates. SAGE repeatably and reliably measures CVR and offers a simultaneous, complementary analysis on total and microvascular scales. The breath-hold paradigm showed significantly higher CVR estimates, but less compliance-dependent protocols may be ideal for applications in patient populations.

Neural mechanisms of disease pathology and cognition in young-onset Alzheimer's disease variants

BackgroundLate-onset Alzheimer's disease is consistently associated with alterations in the default-mode network (DMN)-a large-scale brain network associated with self-related processing and memory. However, the functional organization of DMN is far less clear in young-onset Alzheimer's disease (YOAD).ObjectiveThe current study aimed to identify effective connectivity changes in the core DMN nodes between YOAD variants and healthy controls.MethodsWe assessed resting-state DMN effective connectivity in two common YOAD variants (i.e., amnestic variant (n = 26) and posterior cortical atrophy (n = 13) and healthy participants (n = 24) to identify disease- and variant-specific connectivity differences using spectral dynamic causal modelling.ResultsPatients with the amnestic variant showed increased connectivity from prefrontal cortex to posterior DMN nodes relative to healthy controls, whereas patients with posterior cortical atrophy exhibited decreased posterior DMN connectivity. Right hippocampus connectivity differentiated the two patient groups. Furthermore, disease-related connectivity alterations were also predictive of group membership and cognitive performance.ConclusionsThese findings suggest that resting-state DMN effective connectivity provides a new understanding of neural mechanisms underlying the disease pathology and cognition in YOAD.

Brain activity dynamics after traumatic brain injury indicate increased state transition energy and preference of lower order states

Traumatic Brain Injury (TBI) can cause structural damage to the neural tissue and white matter connections in the brain, disrupting its functional coactivation patterns. Although there are a wealth of studies investigating TBI-related changes in the brain's structural and functional connectomes, fewer studies have investigated TBI-related changes to the brain's dynamic landscape. Network control theory is a framework that integrates structural connectomes and functional time-series to quantify brain dynamics. Using this approach, we analyzed longitudinal trajectories of brain dynamics from acute to chronic injury phases in two cohorts of individuals with mild and moderate to severe TBI, and compared them to non-brain-injured, age- and sex-matched control individuals' trajectories. Our analyses suggest individuals with mild TBI initially have brain activity dynamics similar to controls but then shift in the subacute and chronic stages of the injury (1 month and 12 months post-injury) to favor lower-order visual-dominant states compared to higher-order default mode dominant states. We further find that, compared to controls, individuals with mild TBI have overall decreased entropy and increased transition energy demand in the sub-acute and chronic stages that correlates with poorer attention performance. Finally, we found that the asymmetry in top-down to bottom-up transition energies increased in subacute and chronic stages of mild TBI, possibly indicating decreased efficacy of top-down inhibition. We replicate most findings with the moderate to severe TBI dataset, indicating their robustness, with the notable exception of finding the opposite correlation between global transition energy and mean reaction time (MRT). We attribute differences to the cohorts' varied injury severity, with perhaps a stronger compensatory mechanism in moderate to severe TBI. Overall, our findings reveal shifting brain dynamics after mild to severe TBI that relate to behavioral measures of attention, shedding light on post-injury mechanisms of recovery.

Temporal Dynamics of Intrinsic Brain Activity in Older Women With Subclinical Depression

Subclinical depression is common in older adults, especially in females, and may correlate with a higher likelihood of health events and poor prognosis. However, the underlying neurobiology remains unclear. This study, employing resting-state functional magnetic resonance imaging (rs-fMRI), identified alterations in temporal dynamics of intrinsic brain activity in older women with subthreshold depression (OWSD) and their potential relationships to depressive symptoms. The sliding window approach was applied to evaluate the temporal variations of the rs-fMRI indices, including the amplitude of low-frequency fluctuation (ALFF), the fractional amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality in 50 OWSD and 52 healthy older women controls. We then calculated the dynamic voxel-wise concordance index of the rs-fMRI indices. The correlational analyses were used to assess the correlations between the dynamic indices and depressive symptoms. We found that OWSD showed a significant increase in dynamic ALFF in the left dorsolateral prefrontal cortex relative to healthy older women controls. With respect to regional brain function integration, OWSD showed a significantly lower dynamic voxel-wise concordance index in the right parietal lobe, mainly including the precuneus and superior parietal lobule extending to the postcentral gyrus. The regional dynamic ALFF and dynamic concordance index alterations were correlated with depressive symptoms. In conclusion, OWSD showed depression-correlated alterations in temporal variability of intrinsic brain activity, along with regional deficits in brain function integration. The findings reinforce our understanding of subthreshold depression psychopathology in older women.

Knowledge and practice of healthy behaviors for dementia and stroke prevention in a United States cohort

At least 45% of dementia and 60% of stroke cases are due to modifiable risk factors and could in part be prevented through healthy behavior. This cross-sectional study clustered and characterized a U.S. cohort's knowledge and practice of healthy behavior associated with dementia and stroke. A total of 1,478 participants (mean age: 45.5 years, 51.8% female) were included. A hierarchical cluster analysis was performed to identify clusters based on the level of knowledge and practice of healthy behavior. We defined knowledge as recognizing eight modifiable risk factors (alcohol, diet, smoking, physical activity, sleep, stress, social relationships, and purpose in life) as important. We defined practice as complying with validated recommendations for each healthy behavior. Three clusters emerged: (I) high knowledge and poor practice (II) high knowledge and good practice, and (III) lower knowledge and poor practice. Participants in the high knowledge and good practice cluster were statistically significantly older, more educated, perceived fewer barriers (financial and time limitations), and more facilitators (motivation or knowing someone with dementia or stroke) compared to the other clusters. Our findings could assist in tailoring preventative strategies to enhance knowledge, translating knowledge into practice, and addressing particular facilitators and barriers per identified cluster.

Abnormalities of regional brain activity in patients with asymptomatic internal carotid artery occlusion: a resting-state fMRI study

BACKGROUND

Asymptomatic internal carotid artery occlusion (aICAO) disrupts cerebral blood flow and can impair brain function. While previous research has primarily focused on abnormal functional connectivity between brain networks or regions in aICAO patients, less is known about specific regional brain activity alterations. This study investigated changes in local brain activity and their associations with cognitive function in patients with aICAO.

METHODS

A total of 26 unilateral patients with aICAO without MRI lesions and 25 matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging and neuropsychological assessment. Local brain activity in patients with aICAO was investigated using percentage amplitude of fluctuation (PerAF) and degree centrality (DC). The association between the abnormal regional brain activity in patients with aICAO and cognitive function was also explored.

RESULTS

Compared with HCs, patients with aICAO showed decreased PerAF in the ipsilateral (occlusion side, right) superior temporal gyrus (temporal pole), ipsilateral inferior frontal gyrus (triangular part). In addition, decreased DC was detected in the ipsilateral cuneus of patients with aICAO, while increased DC was observed in the contralateral (opposite to occlusion side, left) precuneus and contralateral inferior frontal gyrus (triangular part) among patients with aICAO. Furthermore, the DC value of contralateral precuneus in aICAO group was negatively correlated with Montreal Cognitive Assessment (MoCA) (r = -0.612, p = 0.002), Forward Digit Span Test (FDST) (r = -0.677, p = 0.001), and Backward Digit Span Test (BDST) (r = -0.531, p = 0.011) scores.

CONCLUSIONS

Our findings revealed abnormal local spontaneous brain activity within brain regions associated with cognitive functions in patients with unilateral aICAO. Notably, some of these abnormalities correlated with their cognitive impairments. This study contributes to the understanding of potential neural mechanisms underlying cognitive dysfunction in unilateral aICAO patients.

Association of Bidirectional Network Cores in the Brain with Perceptual Awareness and Cognition

The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence suggests that both feedforward and feedback signals are necessary for conscious perception, emphasizing the importance of subnetworks with bidirectional interactions. However, the link between such subnetworks and conscious perception remains unclear due to the complexity of brain networks. In this study, we propose a framework for extracting subnetworks with strong bidirectional interactions-termed the "cores" of a network-from brain activity. We applied this framework to resting-state and task-based human fMRI data from participants of both sexes to identify regions forming strongly bidirectional cores. We then explored the association of these cores with conscious perception and cognitive functions. We found that the extracted central cores predominantly included cerebral cortical regions rather than subcortical regions. Additionally, regarding their relation to conscious perception, we demonstrated that the cores tend to include regions previously reported to be affected by electrical stimulation that altered conscious perception, although the results are not statistically robust due to the small sample size. Furthermore, in relation to cognitive functions, based on a meta-analysis and comparison of the core structure with a cortical functional connectivity gradient, we found that the central cores were related to unimodal sensorimotor functions. The proposed framework provides novel insights into the roles of network cores with strong bidirectional interactions in conscious perception and unimodal sensorimotor functions.

Alterations in degree centrality and functional connectivity associated with cognitive Impairment in myotonic dystrophy type 1:A Preliminary functional MRI study

OBJECTIVES

The study aimed to examine alterations in voxel-based degree centrality (DC) and functional connectivity (FC), and their relationship with cognitive impairments in patients with myotonic dystrophy type 1 (DM1).

METHODS

Eighteen DM1 patients and eighteen healthy controls participated in the study and were assessed using a comprehensive neuropsychological battery. Voxel-wise DC and FC analyses were used to assess abnormalities in functional connections among aberrant hubs. Correlational analyses were used to identify and explore the relationship between DC and FC values and cognitive performance in DM1 patients.

RESULTS

DM1 patients exhibited reduced DC in the bilateral Rolandic operculum, left inferior frontal gyrus (triangular part), right angular gyrus, right median cingulate and paracingulate gyri, and right middle temporal gyrus. Conversely, increased DC was observed in the right fusiform gyrus, right hippocampus and left inferior temporal gyrus. FC analysis revealed that altered connectivity predominantly occurred among the right middle temporal gyrus, right angular gyrus and left inferior frontal gyrus (triangular part). DC value in left inferior temporal gyrus showed significant correlations with scores from the Digital Span Test-Forward (r = -0.556, p = 0.025), the Digital Span Test -Backward (r = -0.588, p = 0.017), the Auditory Verbal Learning Test (r = -0.586, p = 0.017) and the Rey-Osterrieth Complex Figure test (copying version) (r = 0.536, p = 0.032) in DM1 patients. No significant correlations were discovered between FC values and neurocognitive performances.

CONCLUSION

The study demonstrated that abnormalities in DC and FC may become potential neuroimaging biomarkers for cognitive decline in DM1 patients.

Degree centrality values in the left calcarine as a potential imaging biomarker for anxious major depressive disorder

BACKGROUND

Major depressive disorder (MDD) with comorbid anxiety is an intricate psychiatric condition, but limited research is available on the degree centrality (DC) between anxious MDD and nonanxious MDD patients.

AIM

To examine changes in DC values and their use as neuroimaging biomarkers in anxious and non-anxious MDD patients.

METHODS

We examined 23 anxious MDD patients, 30 nonanxious MDD patients, and 28 healthy controls (HCs) using the DC for data analysis.

RESULTS

Compared with HCs, the anxious MDD group reported markedly reduced DC values in the right fusiform gyrus (FFG) and inferior occipital gyrus, whereas elevated DC values in the left middle frontal gyrus and left inferior parietal angular gyrus. The nonanxious MDD group exhibited surged DC values in the bilateral cerebellum IX, right precuneus, and opercular part of the inferior frontal gyrus. Unlike the nonanxious MDD group, the anxious MDD group exhibited declined DC values in the right FFG and bilateral calcarine (CAL). Besides, declined DC values in the right FFG and bilateral CAL negatively correlated with anxiety scores in the MDD group.

CONCLUSION

This study shows that abnormal DC patterns in MDD, especially in the left CAL, can distinguish MDD from its anxiety subtype, indicating a potential neuroimaging biomarker.

Altered connection properties of the left dorsolateral superior frontal gyrus in de novo drug-naïve insomnia disorder

Background

Insomnia disorder (ID) is increasingly prevalent, posing significant risks to patients' physical and mental health. However, its neuropathological mechanisms remain unclear. Despite extensive research on ID using resting-state functional magnetic resonance imaging, a unified framework for describing its brain function alterations remains absent. Moreover, most prior studies have not fully accounted for the potential impact of medication on outcomes regarding enrollment criteria.

Methods

We recruited 22 ID and 22 healthy controls (HC), matched for age and gender. Patients with ID were never prescribed medications for sleep disorders before enrollment. We detected differences in voxel-wise degree centrality (DC) between the two groups and analyzed the correlation between altered DC values and insomnia severity. Additionally, we conducted receiver operating characteristic analysis to evaluate the diagnostic effectiveness of the altered DC values for ID.

Results

In ID patients, the weighted DC values of the left dorsolateral superior frontal gyrus (SFG) and the left supramarginal gyrus (SMG) were significantly lower than those of HC, with a notable negative correlation between the weighted DC values of the left dorsolateral SFG and PSQI scores. Receiver operating characteristic analysis showed that the weighted DC of the left dorsolateral SFG effectively differentiates between ID and HC, exhibiting high sensitivity and specificity.

Conclusion

This study offers new insights into brain dysfunction and the pathophysiology of ID through voxel-based DC measurements. The results indicate that altered DC properties of the left dorsolateral SFG might serve as a diagnostic marker for ID and a potential therapeutic target for brain function modulation.

Thalamic oscillatory dysrhythmia and disrupted functional connectivity in thalamocortical loops in perinatal stroke

Periventricular venous infarction (PVI) is a subtype of perinatal stroke localized to subcortical white matter occurring before 34 weeks of gestation. An emerging body of literature has reported life-long motor impairments and compromised quality of life in patients with PVI. However, there remains a paucity of foundational knowledge regarding the underlying neurobiological mechanisms that underpin these outcomes. Recent studies (Ferradal et al. in Cereb Cortex 29:1218-1229, 2019) in brain imaging suggest that healthy development of thalamocortical connections is instrumental in coordinating brain connectivity in both prenatal and postnatal periods given the central role the thalamus and basal ganglia play in motor circuitry. Therefore, we provide a regional and cross-network approach to the analysis of interactive pathways of the thalamus, basal ganglia, and cortex to explore possible neurobiological disruptions responsible for clinical motor function in children with PVI. A resting-state fMRI protocol was administered to children with left periventricular venous infarction (PVI) (n = 23) and typically developing children (TDC) (n = 22) to characterize regional oscillatory and thalamocortical disturbances and compare them to clinical motor function. We hypothesized that PVI would affect resting-state measures of both regional and global brain function, marked by abnormally high amplitudes of regional oscillatory activity, as well as lower local and cross-network communication. Using a combination of robust functional metrics to assess spontaneous, oscillatory activity (Amplitude of Low-Frequency Fluctuations [ALFF] and fractional ALFF), as well as local (Regional Homogeneity [ReHo]) and cross-network connectivity (Degree Centrality [DC] and Functional Connectivity [FC]). We found that compared with TDC, children with PVI exhibited higher levels of ALFF, and these functional differences were associated with the severity of motor impairment. Moreover, the thalamus in children with PVI also showed lower connectivity in relaying thalamocortical pathways. These disruptions in thalamocortical pathways from the thalamus were localized to the medial prefrontal cortex (mPFC), a key hub of the default mode network). Collectively, our findings suggest that heightened levels of regional, oscillatory activity in the thalamus may disrupt more widespread thalamocortical cross-network circuity, possibly contributing to motor impairments in children with PVI.

Frequency-band specific directed connectivity networks reveal functional disruptions and pathogenic patterns in temporal lobe epilepsy: a MEG study

This study investigates the network mechanisms of temporal lobe epilepsy (TLE) using MEG data, focusing on directed connectivity networks across different frequency bands. Unlike previous studies that primarily localize epileptogenic zones, this research aims to explore whole-brain network differences between left TLE (lTLE), right TLE (rTLE), and healthy controls (HCs). MEG data from 13 lTLE patients, 21 rTLE patients, and 14 HCs were source-reconstructed to 116 brain regions (AAL116). Directed Transfer Function (DTF) was used to construct directed connectivity networks, followed by networks and graph-theoretical analyses. The results indicate that, compared to HCs, TLE subjects exhibited a significant increase in average connectivity strength in the Low Gamma band. The connectivity patterns across frequency bands in TLE patients were found to be unstable. Both HC and TLE subjects demonstrated left hemisphere lateralization. In the mid-to-low frequency bands, TLE subjects showed increases in global clustering coefficient (GCC), global characteristic path length (GCPL), and local efficiency (LE) compared to HCs, which is attributed to enhanced synchronization between local brain regions in TLE subjects.

A reduction in energy costs induces integrated states of brain dynamics

In the human brain, interactions between multiple regions organize stable dynamics that enable enhanced cognitive processes. However, it is unclear how collective activities in the brain network can generate stable states while preserving unity across the whole brain scale under successive environmental changes. Herein, a network model was introduced in which network connections were adjusted to reduce the energy consumption level by avoiding excess changes in the activated states of each region during successive interactions. For time series data obtained from fMRI images, a connection matrix was generated by a simulation, and the predictions made by this matrix yielded accurate results relative to the real data. In this simulation, the adjustment process was activity-dependent, in which the interregional connections between intense active regions were reinforced to prohibit free behaviours. This resulted in a reduced excess energy loss and the integration of multiple regional activities into integrated dynamic states under constraints imposed by other regions. It was suggested that the simple rule of saving excess energy costs plays an important role in the mechanism that regulates large-scale brain networks and dynamics.

Identifying multilayer network hub by graph representation learning

The recent advances in neuroimaging technology allow us to understand how the human brain is wired in vivo and how functional activity is synchronized across multiple regions. Growing evidence shows that the complexity of the functional connectivity is far beyond the widely used mono-layer network. Indeed, the hierarchical processing information among distinct brain regions and across multiple channels requires using a more advanced multilayer model to understand the synchronization across the brain that underlies functional brain networks. However, the principled approach for characterizing network organization in the context of multilayer topologies is largely unexplored. In this work, we present a novel multi-variate hub identification method that takes both the intra- and inter-layer network topologies into account. Specifically, we put the spotlight on the multilayer graph embeddings that allow us to separate connector hubs (connecting across network modules) with their peripheral nodes. The removal of these hub nodes breaks down the entire multilayer brain network into a set of disconnected communities. We have evaluated our novel multilayer hub identification method in task-based and resting-state functional images. Complimenting ongoing findings using mono-layer brain networks, our multilayer network analysis provides a new understanding of brain network topology that links functional connectivities with brain states and disease progression.

Abnormal sensory processing cortex in insomnia disorder: a degree centrality study

Insomnia disorder is a significant global health concern. This research aimed to explore the pathogenesis of insomnia disorder using static and dynamic degree centrality methods at the voxel level. A total of 29 patients diagnosed with insomnia disorder and 28 healthy controls were ultimately included to examine differences in degree centrality between the two groups. Additionally, the relationship between altered degree centrality values and various clinical indicators was analyzed. The results revealed that patients with insomnia disorder exhibited higher static degree centrality in brain regions associated with sensory processing, such as the occipital gyrus, inferior temporal gyrus, and supramarginal gyrus. In contrast, lower static degree centrality was observed in the parahippocampal gyrus, amygdala, insula, and thalamus. Changes in dynamic degree centrality were identified in regions including the parahippocampal gyrus, anterior cingulum, medial superior frontal gyrus, inferior parietal gyrus, and precuneus. Notably, a negative correlation was found between dynamic degree centrality in the inferior parietal gyrus and the Pittsburgh Sleep Quality Index, while a positive correlation was observed between static degree centrality in the inferior temporal gyrus and the Hamilton Depression Scale. These findings suggest that dysfunction in centrality within the sensory processing cortex and subcortical nuclei may be associated with the sleep-wake imbalance in individuals with insomnia disorder, contributing to our understanding of hyperarousal mechanisms in insomnia. Moreover, the abnormalities observed in the default mode network and the salience network provide insights into understanding the neuropathogenesis of insomnia from both static and dynamic centrality perspectives. The clinical trial registration number: ChiCTR2200058768. Date: 2022-04-16.

Cortical functional connectivity and topology based on complex network graph theory analysis during acute pain stimuli

Purpose

We aimed to investigate alterations in the topological organization of functional brain networks in acute pain.

Methods

A total of 29 capsaicin group (CAP) and 19 sham controls (Sham) underwent a 10-min resting-state functional near-infrared spectroscopy scan. The CAP group applied capsaicin cream (0.1%) to the lower back, whereas the Sham group applied a hand cream without capsaicin ingredients to the same area. All subjects were healthy individuals prior to the experiment and did not report any pain or other medical history. The pain in the CAP was only caused by the topical application of capsaicin. Each subject was asked to complete a numerical rating scale. Graph theory-based analysis was used to construct functional connectivity (FC) matrices and extract the features of small-world networks of the brain in both groups. Then, FC differences in the prefrontal cortex were characterized by statistical analysis, and the altered brain features were explored.

Results

Compared with Sham, CAP had impaired functions in short- and long-distance connectivity ( p < 0.05 ). In particular, there was a greatly significant difference in connectivity associated with the left dorsolateral prefrontal cortex (ldlpfc) (CAP versus Sham: 0.80 ± 0.02 versus 0.70 ± 0.05 , p < 0.0001 ). Global efficiency, local efficiency, and small worldness were significantly lower in the topological parameters in CAP than in Sham (CAP versus Sham: 0.172 ± 0.018 versus 0.191 ± 0.015 , t = 3.758 , p = 0.0005 ; 0.253 ± 0.012 versus 0.283 ± 0.012 , t = 8.209 , p < 0.0001 ; 0.526 ± 0.031 versus 0.628 ± 0.082 , t = 3.856 , p = 0.0009 ). At the regional level, there were deficits in nodal efficiency within the medial prefrontal cortex and ldlpfc (CAP versus Sham: 0.156 ± 0.081 versus 0.175 ± 0.067 , t = 2.305 , p = 0.0257 ; 0.169 ± 0.089 versus 0.156 ± 0.081 , t = 2.194 , p = 0.0033 ).

Conclusions

Even brief episodes of acute pain can significantly reshape the brain's network architecture and FC, revealing a complex phenomenon beyond a transient sensory experience. Disruptions in brain network topology and connectivity due to pain suggest potential avenues for targeted therapeutic interventions and a reconfiguration of brain networks that could underlie chronic pain formation.

APOE ε4 influences the dynamic functional connectivity variability and cognitive performance in Alzheimer's disease

BackgroundApolipoprotein E (APOE) ε4 is the most significant genetic risk factor for sporadic Alzheimer's disease (AD). However, its impact on the dynamic changes in resting-state functional connectivity (FC), particularly concerning network formation, interaction, and dissolution over time, remains largely unexplored in AD.ObjectiveThis study aims to explore the effect of APOE ε4 on dynamic FC (dFC) variability and cognitive performance in AD.MethodsWe analyzed the dFC of AD patients, comparing APOE ε4 carriers (n = 33) with non-carriers (n = 41). The whole-brain dFC was assessed by calculating dynamic fractional amplitude of low-frequency fluctuations (dfALFF) and dynamic regional homogeneity (dReHo). To further explore the relationship between cognitive function and dFC in AD patients, we conducted a correlation analysis. Mediation analysis was also performed to determine whether dFC mediates the link between the APOE ε4 and cognitive decline in AD patients.ResultsAD patients carrying the APOE ε4 exhibited more severe cognitive impairment, along with reduced dReHo and dfALFF in both the left and right posterior cerebellar lobes. In these carriers, the dFC analysis showed lower dFC between the left posterior cerebellar lobe and the left middle temporal gyrus, which was positively correlated with executive function and information processing speed. Additionally, mediation analysis indicated that APOE ε4 influences dFC in this brain region, contributing to executive dysfunction in AD.ConclusionsThese findings offer preliminary evidence that APOE ε4 modulates fluctuating communication within the cerebellar lobe and the dFC between the cerebellar lobe and the temporal gyrus in AD.

Functional connectivity and white matter microstructural alterations in patients with left basal ganglia acute ischemic stroke

Lesions in the basal ganglia present different neuroimaging manifestations compared to other regions. The functional connectivity and white matter (WM) microstructural alterations in patients with left basal ganglia acute ischemic stroke (AIS) remain unknown. This study aimed to explore the alterations of functional connectivity and WM microstructure, as well as their relationship with cognitive performance in patients with left basal ganglia AIS. We acquired resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI) data from 41 individuals with left basal ganglia AIS and 41 healthy controls (HC). The degree centrality (DC) method was applied to calculate the functional connectivity and Tract-Based Spatial Statistics was employed to evaluate the voxel-based group differences of diffusion metrics for the values of fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD), radial diffusivity, mean kurtosis (MK), axial kurtosis, and radial kurtosis (RK). AIS showed attenuated DC in the bilateral precuneus and enhanced DC in the left caudate nucleus, compared with HC. In AIS, DC in the left caudate nucleus correlated positively with the Montreal Cognitive Assessment (MoCA) score (r = 0.681, p < 0.05). AIS had significantly decreased FA, AD, MK, and RK in WM tracts, including the internal capsule (IC), genu of corpus callosum (CC), body of CC, left superior longitudinal fasciculus (SLF), left cerebral peduncle, left corticospinal tract, anterior corona radiata (ACR), and left cingulum gyrus (CG). The MK in a cluster including the body of CC, right IC, left cingulate, SLF, ACR, and left CG was also significantly negatively correlated with MoCA scores (r = -0.508, p < 0.05). This study revealed that left basal ganglia AIS not only disrupted the functional connectivity of the whole brain but also had a pervasive impact on the WM microstructure of the whole brain. These findings provide novel insights into the underlying neural mechanisms of early cognitive decline in patients after AIS.

Concurrent brain structural and functional alterations related to cognition in patients with cerebral small vessel disease

PURPOSE

To investigate the concurrent brain structural and functional alterations related to cognition in patients with cerebral small vessel disease (CSVD).

METHODS

Thirty normal controls and 65 CSVD patients, including 33 patients with mild cognitive impairment and 32 patients with no cognitive impairment were included. Structural and resting-state functional MRI measures, including gray matter volume (GMV) and white matter volume (WMV) using voxel-based morphometry (VBM) analysis and amplitude of low-frequency fluctuation (ALFF), were obtained and compared among the three groups. Associations between cognitive scores and ALFF/VBM coupling in the co-altered regions were investigated in CSVD groups.

RESULTS

Multiple brain regions showed significant differences in GMV and WMV among the three groups (P < 0.01). Abnormal ALFF among the three groups was identified in the left putamen, Rolandic operculum, fusiform gyrus, caudate, parahippocampal gyrus, insula, middle cingulum, bilateral lingual gyrus, and right frontal lobe (P < 0.01). Importantly, a decrease in VBM and increase in ALFF in the left parahippocampal gyrus, caudate and Rolandic operculum, a reduction of the WMV and ALFF in the right superior frontal lobe, and a united rise of GMV and ALFF in the left caudate were detected in CSVD groups. In addition, abnormal ALFF/VBM coupling was significantly related to multiple cognitive assessments.

CONCLUSION

The study indicated a reversed pattern of the brain structural deficits and functional activation in the left parahippocampal gyrus, caudate, and Rolandic operculum, suggesting structure-function decoupling in CSVD groups. These might help further understand the pathophysiological mechanism of CSVD.

Brain network alterations in mobile phone use problem severity: A multimodal neuroimaging analysis

Background and aims

Problematic mobile phone use can disrupt social interaction and well-being, potentially influencing cognitive processes. This study investigated whether mobile phone use problem severity is associated with alterations in the topological organization of brain networks.

Methods

Rs-fMRI and DTI data were collected from 81 healthy participants. Graph theory analyses were applied. The Mobile Phone Problem Use Scale-10 (MPPUS-10) was used to assess mobile phone use problem severity. Correlation analyses were conducted between each graph metric and questionnaire scores.

Results

MPPUS-10 scores correlated with global fMRI metrics: higher scores linked to longer shortest path length (reduced integration) and lower global efficiency (reduced information transfer). Conversely, higher MPPUS-10 scores were correlated with a greater clustering coefficient and higher local efficiency, which reflect increased local connectivity. Furthermore, higher MPPUS-10 scores were associated with a higher sigma value from DTI, indicating altered structural network properties. Some specific brain regions also showed significant correlations with MPPUS-10 scores.

Discussion and conclusion

These findings indicate that higher mobile phone use problem severity is associated with decreased integration and increased segregation of functional networks, alongside enhanced small-worldness in structural networks. Reduced integration aligns with addiction theories suggesting digital overload worsens network dysfunction, disrupting brain connectivity. Additionally, higher severity was correlated with altered connectivity in multiple regions, such as the precentral gyrus, supplementary motor area, and postcentral gyrus. These regions are associated with motor control, sensorimotor processing, and memory function. Further research is needed to explore whether these findings reflect shifts in the integration and integrity of brain information-processing modules.

Brain functional and structural alteration following acute carbon monoxide poisoning contribute to delayed neurological sequelae

PURPOSE

To investigate whether altered functional activity, functional connectivity (FC), and structural connectivity (SC) following acute carbon monoxide (CO) poisoning contribute to delayed neurological sequelae (DNS) occurrence.

METHODS

Binary degree centrality (DC) and seed-based FC were investigated in 18 patients with DNS, 26 patients without DNS, and 30 healthy controls. Duration of CO exposure and coma severity indices-related fibers was detected by connectometry analysis and the identified fiber tracts were tracked and their SC alteration was quantify by fractional anisotropy (FA).

RESULTS

Acute CO exposure induced DC change in the prefrontal cortex (PFC), visual cortex, primary sensory cortex, and anterior cerebellum, and FC alteration between the right fusiform gyrus (seed) and bilateral PFC and left inferior occipital gyrus (Gaussian random field corrected, P < 0.05). Poisoning severity indices-related WM fibers consisted of corpus callosum and some association and projection fibers (false discovery rate corrected, P < 0.05). Only altered DC in the right fusiform gyrus and right postcentral gyrus and reduced FC of the PFC could identify DNS occurrence (P < 0.05).

CONCLUSIONS

The functional abnormalities in the visual- and sensory- cortex and PFC subsequent to acute CO poisoning represent one of the potential neural mechanisms underlying the occurrence of DNS.

The role of cerebellar-cortical connectivity in modulating attentional abilities: insight from football athletes

Neuroplasticity, a phenomenon present throughout the lifespan, is thought to be influenced by physical training. However, the relationship between neuroplastic differences and attentional abilities remains unclear. This study explored the differences in brain function and attentional abilities between professional football athletes and novices, and further investigated the relationship between the two. To address this question, we included 49 football athletes and 63 novices in our study, collecting data on resting-state functional connectivity and Attention Network Test (ANT). Behavioral results from the ANT indicated that football experts had superior orienting attention but weaker alerting functions compared to novices, with no difference in executive control attention. fMRI results revealed that football experts exhibited higher fractional Amplitude of Low-Frequency Fluctuations (fALFF) values in the bilateral anterior cerebellar lobes, bilateral insula, and left superior temporal gyrus. Functional connectivity analysis showed increased connectivity between the left anterior cerebellar lobe and various cortical regions, including the right supramarginal gyrus, left precuneus, left superior frontal gyrus, bilateral posterior cerebellar lobes, and bilateral precentral gyri in experts compared to novices. More importantly, in the expert group but not in novice group, functional connectivity differences significantly predicted attentional orienting scores. Graph theoretical analysis showed that experts exhibited higher betweenness centrality and node efficiency in the right cerebellar lobule III (Cerebelum_3_R) node. Our findings demonstrate that long-term professional football training may significantly affect neuroplasticity and attentional functions. Importantly, our analysis reveals a substantive connection between these two aspects, suggesting that the integration of neuroplastic and attentional changes is likely mediated by cerebellar-cortical connectivity.

Brain structural alterations in vestibular schwannoma beyond tinnitus and hearing loss

Brain tumours alter brain structures and functions. However, morphometric alterations induced by unilateral vestibular schwannoma, a benign tumour of the vestibulocochlear nerve, have not been extensively explored. Recent studies have suggested that the tumour does not grow bigger following diagnosis in several patients, suggesting an avenue for conservative therapy. This study aims to comprehensively investigate brain structural re-organizations in vestibular schwannoma patients taking into account the effects of hearing loss and tinnitus-the most common symptoms. To this end, preoperative data from 48 vestibular schwannoma pathology-confirmed patients and a healthy control group of 30 volunteers were retrospectively included in this study. The clinical and imaging data from these participants were processed. General linear models were designed to identify tumour-related brain alterations in grey matter volume and cortical thickness, alongside three other surface measures: sulcal depth, gyrification index and fractal dimension. The differences obtained were further analysed for correlation with tumour size and pure tone audiometry. Interestingly, grey matter volume, cortical thickness and for the first time, fractal dimension measures were increased in vestibular schwannoma patients across key frontal regions (PFWE < 0.05). The precuneus, superior and inferior frontal gyrus had increased grey matter volumes and cortical thickening in patients compared to controls, among other changes (P FWE < 0.05). Meanwhile, the sulcal depth and gyrification index measures demonstrated no significant alterations. Furthermore, grey matter volume changes at the paracentral lobule and precuneus were positively correlated to the tumour size, while the fractal dimension at the superior frontal sulcus was negatively correlated. Finally, grey matter volume increase at the inferior frontal gyrus and cortical thickening at the supramarginal gyrus were negatively correlated to pure tone audiometry. These findings suggest that factors beyond hearing loss and tinnitus contribute to brain structural alterations in this tumour, a better understanding of which might pave the way for non-surgical symptomatic therapies.

Hubs and interaction: the brain's meta-loop

We must reconcile the needs of the internal world and the demands of the external world to make decisions relevant to homeostasis, well-being, and flexible behavior. Engagement with the internal (eg interoceptive) world is linked to medial brain systems, whereas the extrapersonal space (eg exteroceptive) is associated with lateral brain systems. Using Human Connectome Project data, we found three association tracts connecting the action-related frontal lobe with perception-related posterior lobes. A lateral dorsal tract and a medial dorsal tract interact independently with a ventral tract at frontal and posterior hubs. The two frontal and the two posterior hubs are interconnected, forming a meta-loop that integrates lateral and medial brain systems. The four anatomical hubs correspond to the common nodes of the intrinsic cognitive brain networks such as the default mode network. These functional networks depend on the integration of both realms. Thus, the positioning of functional cognitive networks can be understood as the intersection of long anatomical association tracts. The strength of structural connectivity within lateral and medial brain systems correlates with performance on behavioral tests assessing theory of mind. The meta-loop provides an anatomical framework to associate neurological and psychiatric symptoms with functional and structural changes.

The causal association between resting state intrinsic functional networks and neurodegeneration

Alterations of resting state intrinsic functional networks have been associated with neurodegenerative diseases even before the onset of cognitive symptoms. Emerging hypotheses propose a role of resting state intrinsic functional networks alterations in the risk or vulnerability to neurodegeneration. It is unknown whether intrinsic functional network alterations can be causal for neurodegenerative diseases. We sought to answer this question using two-sample Mendelian randomization. Using the largest genome-wide association study of resting state intrinsic functional connectivity (n = 47 276), we generated genetic instruments (at the significance level 2.8 ×10-11) to proxy resting state intrinsic functional network features. Based on the known brain regions implicated in different neurodegenerative diseases, we generated genetically proxied resting state intrinsic functional features and tested their association with their paired neurodegenerative outcomes: features in parieto-temporal regions and Alzheimer dementia (111 326 cases, 677 663 controls); frontal region and frontotemporal dementia (2154 cases, 4308 controls); temporal pole region and semantic dementia (308 cases, 616 controls), and occipital region with Lewy body dementia (LBD) (2591 cases, 4027 controls). Major depressive disorder outcome (170 756 cases, 329 443 controls) was included as a positive control and tested for its association with genetically proxied default mode network (DMN) exposure. Inverse-variance weighted analysis was used to estimate the association between the exposures (standard deviation units) and outcomes. Power and sensitivity analyses were completed to assess the robustness of the results. None of the genetically proxied functional network features were significantly associated with neurodegenerative outcomes (adjusted P value >0.05), despite sufficient calculated power. Two resting state features in the visual cortex showed a nominal level of association with LBD (P = 0.01), a finding that was replicated using a different instrument (P = 0.03). The genetically proxied DMN connectivity was associated with the risk of depression (P = 0.024), supporting the validity of the genetic instruments. Sensitivity analyses were supportive of the main results. This is the first study to comprehensively assess the potential causal effect of resting state intrinsic functional network features on the risk of neurodegeneration. Overall, the results do not support a causal role for the tested associations. However, we report a nominal association between visual network connectivity and Lewy body dementia that requires further evaluation.

A Novel Spatio-Temporal Hub Identification in Brain Networks by Learning Dynamic Graph Embedding on Grassmannian Manifolds

Mounting evidence has revealed that functional brain networks are intrinsically dynamic, undergoing changes over time, even in the resting-state environment. Notably, recent studies have highlighted the existence of a small number of critical brain regions within each functional brain network that exhibit a flexible role in adapting the geometric pattern of brain connectivity over time, referred to as "temporal hub" regions. Therefore, the identification of these temporal hubs becomes pivotal for comprehending the mechanisms that underlie the dynamic evolution of brain connectivity. However, existing spatio-temporal hub identification methods rely on static network-based approaches, wherein each temporal hub region is independently inferred from individual time-segmented networks without considering their temporal consistency and consequently fails to align the evolution of hubs with the dynamic changes in brain states. To address this limitation, we propose a novel spatio-temporal hub identification method that fully leverages dynamic graph embedding to distinguish temporal hubs from peripheral nodes, in which dynamic graph embeddings are learned from both spatial and temporal dimensions. Specifically, to preserve the temporal consistency of evolving networks, we model the dynamic graph embedding as a physical model of time, where the network-to-network transition is mathematically expressed as a total variation of dynamic graph embedding with respect to time. Furthermore, a Grassmannian manifold optimization scheme is introduced to enhance graph embedding learning and capture the time-varying topology of brain networks. Experimental results on both synthetic and real fMRI data demonstrate superior temporal consistency in hub identification, surpassing conventional approaches.

Separating neurocognitive mechanisms of maintenance and compensation to support financial ability in middle-aged and older adults: The role of language and the inferior frontal gyrus

This study investigated the role of brain regions involved in arithmetic processing in explaining individual differences in financial ability in 67 50-74-year-old cognitively normal adults. Structural integrity and resting-state functional connectivity measures were collected in the MRI scanner. Outside the scanner, participants performed financial ability and other cognitive tasks, and answered questionnaires to determine dementia risk, and financial risk and protective factors. Regions of interest involved in arithmetic processing were defined, focusing on language- and quantity-processing areas in temporo-frontal and parieto-frontal cortices, respectively. Our results showed that structural integrity and functional connectivity in brain regions associated with arithmetic retrieval were positively associated with financial ability, with language skill mediating left IFG structural integrity and financial ability. Connectivity patterns suggested that reliance on quantity mechanisms (i.e. calculation) was associated with poorer financial ability. Analyses revealed that reliance on these brain mechanisms did not depend on participants' age or risk of dementia and that protective factors such as household income or financial literacy supported the maintenance of connectivity related to financial abilities.

Prospective memory performance and its resting-state functional connectivity correlates in individuals with memory complaints

This study aimed to investigate prospective memory (PM) in patients with memory complaints but without dementia (PWD) and correlate findings with resting-state functional connectivity (rsFC) alterations. We hypothesized that PM impairment would be evident at a certain relatively early point in the continuum and specific rsFC patterns would be the neuroimaging signature of this impairment. Sixty PWD participated in the study. The Memory Screening Test for Intentions and the Virtual Week were used to assess PM. Using the participants' PM scores as a regressor, the rsFC for PM was analyzed by Network-Based Statistics (NBS). Participants were divided into high and low PM groups (HPMG, LPMG) according to their PM scores and then their neuropsychological scores, rsFC patterns, and CSF biomarker levels were compared. The effect of education on the relationship between connectivity and CSF Aβ42 level was examined by moderation analysis. Compared with HPMG, LPMG was impaired in both event- and time-based PM tasks, but the difference was more distinct in the event-based ones. While HPMG was more successful in event-based tasks than time-based ones, LPMG was not. As a result of NBS analysis, the middle frontal gyrus (MFG), supramarginal gyrus (SMG), and anterior cingulate cortex (ACC) were determined as central seeds. The HPMG's performance and connectivity were higher for most comparisons but had lower CSF Aβ42 than LPMG and therefore was closer to the positivity threshold. When the education level was at the mean and above, there was a negative correlation between CSF Aβ42 level and overall connectivity. The connectivities of MFG, SMG, and ACC play an important role in PM performance in the PWD. In more advanced PM impairment, the impairment of spontaneous processes is more prominent. At the onset of amyloidosis, the cognitive reserve may compensate for cognitive impairment by increasing connectivity.

Heterogeneous clinical phenotypes of sporadic early-onset Alzheimer's disease: a neuropsychological data-driven approach

BACKGROUND

The clinical presentations of early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease are distinct, with EOAD having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) described EOAD as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the phenotypic range of EOAD presentation, we applied a neuropsychological data-driven method to subtype the LEADS cohort.

METHODS

Neuropsychological test performance from 169 amyloid-positive EOAD participants were analyzed. Education-corrected normative comparisons were made using a sample of 98 cognitively normal participants. Comparing the relative levels of impairment between each cognitive domain, we applied a cut-off of 1 SD below all other domain scores to indicate a phenotype of "predominant" impairment in a given cognitive domain. Individuals were otherwise considered to have multidomain impairment. Whole-cortex general linear modeling of cortical atrophy was applied as an MRI-based validation of these distinct clinical phenotypes.

RESULTS

We identified 6 phenotypic subtypes of EOAD: Dysexecutive Predominant (22% of sample), Amnestic Predominant (11%), Language Predominant (11%), Visuospatial Predominant (15%), Mixed Amnestic/Dysexecutive Predominant (11%), and Multidomain (30%). These phenotypes did not differ by age, sex, or years of education. The APOE ɛ4 genotype was enriched in the Amnestic Predominant group, who were also rated as least impaired. Cortical thickness analysis validated these clinical phenotypes with dissociations in atrophy patterns observed between the Dysexecutive and Amnestic Predominant groups. In contrast to the heterogeneity observed from our neuropsychological data-driven approach, diagnostic classifications for this same sample based solely on clinical judgment indicated that 82% of individuals were amnestic-predominant, 9% were non-amnestic, 4% met criteria for Posterior Cortical Atrophy, and 5% met criteria for Primary Progressive Aphasia.

CONCLUSION

A neuropsychological data-driven method to phenotype EOAD individuals uncovered a more detailed understanding of the presenting heterogeneity in this atypical AD sample compared to clinical judgment alone. Clinicians and patients may over-report memory dysfunction at the expense of non-memory symptoms. These findings have important implications for diagnostic accuracy and treatment considerations.

Intrinsic brain functional connectivity mediates the relationship between psychological resilience and cognitive decline in ageing

Ageing individuals often experience cognitive decline and intrinsic functional connectivity (FC) changes. Psychological resilience, a personality trait that reflects the capacity to adapt and cope with age-related challenges, plays a key role in mitigating cognitive decline. In this study involving 101 older adults, we investigated how psychological resilience influences cognitive decline measured by processing speed. Particularly, we obtained resting-state functional magnetic resonance imaging (fMRI) to assess how intrinsic FC, represented by degree centrality, modulates the relationship between resilience and processing speed. Our results indicated while psychological resilience positively predicted processing speed, this relationship was mainly driven by education. Additionally, the degree centrality of both thalamus and caudate negatively correlated with processing speed and resilience. Notably, the degree centrality of both thalamus and caudate significantly mediated the relationship between resilience and processing speed. These findings suggest that psychological resilience could protect against age-related cognitive decline via its influence on FC in the thalamus and caudate, highlighting these areas as potential intervention targets for reducing cognitive decline in ageing people.

Soluble Aβ pathology predicts neurodegeneration and cognitive decline independently on p-tau in the earliest Alzheimer's continuum: Evidence across two independent cohorts

INTRODUCTION

Identifying the link between early Alzheimer's disease (AD) pathological changes and neurodegeneration in asymptomatic individuals may lead to the discovery of preventive strategies. We assessed longitudinal brain atrophy and cognitive decline as a function of cerebrospinal fluid (CSF) AD biomarkers in two independent cohorts of cognitively unimpaired (CU) individuals.

METHODS

We used longitudinal voxel-based morphometry (VBM) in combination with hippocampal subfield segmentation. Changes in neuroimaging and cognitive variables were inspected using general linear models (GLMs) adjusting by age, sex, apolipoprotein E (APOE) status, follow-up time, and years of education.

RESULTS

In both cohorts, baseline CSF amyloid beta (Aβ) biomarkers significantly predicted medial temporal lobe (MTL) atrophy rates and episodic memory (EM) decline independently of CSF phosphorylated tau (p-tau).

DISCUSSION

Our data suggest that soluble Aβ dyshomeostasis triggers MTL longitudinal atrophy and EM decline independently of CSF p-tau. Our data underscore the need for secondary preventive strategies at the earliest stages of the AD pathological cascade.

HIGHLIGHTS

We assessed brain atrophy and cognitive decline in asymptomatic individuals. Aβ biomarkers predicted MTL atrophy independently of p-tau. Our results underscore the importance of undertaking Alzheimer's preclinical trials.

Structure-function relationships in the human aging brain: An account of cross-sectional and longitudinal multimodal neuroimaging studies

The patterns of brain activation and functional connectivity, task-related and task-free, as a function of age have been well documented over the past 30 years. However, the aging brain undergoes structural changes that are likely to affect the functional properties of the brain. The relationship between brain structure and function started to be investigated more recently. Brain structure and brain function can influence behavioral outcomes independently, and several studies highlight independent contribution of structure and function on cognition. Here, a central assumption is that brain structure also affects behavior indirectly through its influence on brain function. In such a model, structure supports function. Although findings generally suggest that structure may indeed influence function, the direction of the associations, the variability in terms of regional effects and age windows when associations are observed vary greatly. Also, a certain number of studies highlight the independent contribution of structure and function on cognition. A critical aspect of studying aging is the necessity of longitudinal designs, allowing to observe true aging effects - as compared with age differences in cross-sectional designs. This review aims to give an updated account on research dealing with multimodal neuroimaging in aging, and more specifically on the links between structure and function and associated cognitive outcomes, putting in parallel findings from cross-sectional and longitudinal studies. Additionally, we discuss potential mechanisms by which age-related changes in structure may affect function, but also factors (sample characteristics, methodology) that may contribute to the heterogeneity of the findings and the lack of consensus on the associations between structure, function, cognition and aging.

Local molecular and connectomic contributions of tau-related neurodegeneration

Neurodegeneration in Alzheimer's disease (AD) is known to be mostly driven by tau neurofibrillary tangles. However, both tau and neurodegeneration exhibit variability in their distribution across the brain and among individuals, and the relationship between tau and neurodegeneration might be influenced by several factors. I aimed to map local molecular and connectivity characteristics that affect the association between tau pathology and neurodegeneration. The current study was conducted on the cross-sectional tau-PET and longitudinal T1-weighted MRI scan data of 186 participants from the ADNI dataset including 71 cognitively unimpaired (CU) and 115 mild cognitive impairment (MCI) individuals. Furthermore, the normative molecular profile of a region was defined using neurotransmitter receptor densities, gene expression, T1w/T2w ratio (myelination), FDG-PET (glycolytic index, glucose metabolism, and oxygen metabolism), and synaptic density. I found that the excitatory-inhibitory (E:I) ratio, myelination, synaptic density, glycolytic index, and functional connectivity are linked with deviation in the relationship between tau and neurodegeneration. Furthermore, there was spatial similarity between tau pathology and glycolytic index, synaptic density, and functional connectivity across brain regions. The current study demonstrates that the regional susceptibility to tau-related neurodegeneration is associated with specific molecular and connectomic characteristics of the affected neural systems. I found that the molecular and connectivity architecture of the human brain is linked to the different effects of tau pathology on downstream neurodegeneration.

Decreases in frequency-dependent intrinsic activity of the default mode network are associated with depression and cognition in patients with postacute sequelae of SARS-CoV-2 infection

A significant proportion of patients who have recovered from COVID-19 suffer from persistent symptoms, referred to as "post-acute sequelae of SARS-CoV-2 infection (PASC)". Abnormal brain intrinsic activity has been observed in PASC patients, but the patterns of frequency-dependent intrinsic activity in the PASC and non-PASC (recovered COVID-19 patients without persistent symptoms) groups and their association with neuropsychiatric sequelae remain unclear in PASC. Twenty-nine PASC patients, 27 non-PASC subjects, and 31 healthy controls (HCs) were recruited. The voxel-level fractional amplitude of low-frequency fluctuation (fALFF) was calculated in different frequency bands (typical frequency band: 0.01-0.10 Hz; slow 5: 0.01-0.023 Hz; slow 4: 0.023-0.073 Hz) to assess regional intrinsic activity patterns within different groups. Correlation analyses were performed to explore the associations between frequency-dependent alterations and clinical variables. Significant frequency-dependent alterations in intrinsic activity patterns were observed in both the PASC and non-PASC groups, primarily involving regions of the default mode network (DMN). The decreased fALFF values of the DMN in different frequency bands were associated with different symptoms in PASC. For example, decreased fALFF in the left precuneus in the typical frequency band was related to general attention impairment in PASC, whereas decreased fALFF in the left superior frontal gyrus appeared in non-PASC. The fALFF alterations in the left precuneus/posterior cingulate gyrus in the slow 5 band were also related to cognitive performance in PASC. Additionally, in the slow 4 band, decreased fALFF in the right angular gyrus was associated with depressive symptoms in the PASC. Our results may provide insights into the potential neural mechanisms underlying symptoms in PASC patients.

Network Diffusion-Constrained Variational Generative Models for Investigating the Molecular Dynamics of Brain Connectomes Under Neurodegeneration

Alzheimer's disease (AD) is a complex and progressive neurodegenerative condition with significant societal impact. Understanding the temporal dynamics of its pathology is essential for advancing therapeutic interventions. Empirical and anatomical evidence indicates that network decoupling occurs as a result of gray matter atrophy. However, the scarcity of longitudinal clinical data presents challenges for computer-based simulations. To address this, a first-principles-based, physics-constrained Bayesian framework is proposed to model time-dependent connectome dynamics during neurodegeneration. This temporal diffusion network framework segments pathological progression into discrete time windows and optimizes connectome distributions for biomarker Bayesian regression, conceptualized as a learning problem. The framework employs a variational autoencoder-like architecture with computational enhancements to stabilize and improve training efficiency. Experimental evaluations demonstrate that the proposed temporal meta-models outperform traditional static diffusion models. The models were evaluated using both synthetic and real-world MRI and PET clinical datasets that measure amyloid beta, tau, and glucose metabolism. The framework successfully distinguishes normative aging from AD pathology. Findings provide novel support for the "decoupling" hypothesis and reveal eigenvalue-based evidence of pathological destabilization in AD. Future optimization of the model, integrated with real-world clinical data, is expected to improve applications in personalized medicine for AD and other neurodegenerative diseases.

Revealing excitation-inhibition imbalance in Alzheimer's disease using multiscale neural model inversion of resting-state functional MRI

BACKGROUND

Alzheimer's disease (AD) is a serious neurodegenerative disorder without a clear understanding of pathophysiology. Recent experimental data have suggested neuronal excitation-inhibition (E-I) imbalance as an essential element of AD pathology, but E-I imbalance has not been systematically mapped out for either local or large-scale neuronal circuits in AD, precluding precise targeting of E-I imbalance in AD treatment.

METHOD

In this work, we apply a Multiscale Neural Model Inversion (MNMI) framework to the resting-state functional MRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify brain regions with disrupted E-I balance in a large network during AD progression.

RESULTS

We observe that both intra-regional and inter-regional E-I balance is progressively disrupted from cognitively normal individuals, to mild cognitive impairment (MCI) and to AD. Also, we find that local inhibitory connections are more significantly impaired than excitatory ones and the strengths of most connections are reduced in MCI and AD, leading to gradual decoupling of neural populations. Moreover, we reveal a core AD network comprised mainly of limbic and cingulate regions. These brain regions exhibit consistent E-I alterations across MCI and AD, and thus may represent important AD biomarkers and therapeutic targets. Lastly, the E-I balance of multiple brain regions in the core AD network is found to be significantly correlated with the cognitive test score.

CONCLUSIONS

Our study constitutes an important attempt to delineate E-I imbalance in large-scale neuronal circuits during AD progression, which may facilitate the development of new treatment paradigms to restore physiological E-I balance in AD.

The global research of magnetic resonance imaging in Alzheimer's disease: a bibliometric analysis from 2004 to 2023

Background

Alzheimer's disease (AD) is a common neurodegenerative disorder worldwide and the using of magnetic resonance imaging (MRI) in the management of AD is increasing. The present study aims to summarize MRI in AD researches via bibliometric analysis and predict future research hotspots.

Methods

We searched for records related to MRI studies in AD patients from 2004 to 2023 in the Web of Science Core Collection (WoSCC) database. CiteSpace was applied to analyze institutions, references and keywords. VOSviewer was used for the analysis of countries, authors and journals.

Results

A total of 13,659 articles were obtained in this study. The number of published articles showed overall exponential growth from 2004 to 2023. The top country and institution were the United States and the University of California System, accounting for 40.30% and 9.88% of the total studies, respectively. Jack CR from the United States was the most productive author. The most productive journal was the Journal of Alzheimers Disease. Keyword burst analysis revealed that "machine learning" and "deep learning" were the keywords that frequently appeared in the past 6 years. Timeline views of the references revealed that "#0 tau pathology" and "#1 deep learning" are currently the latest research focuses.

Conclusion

This study provides an in-depth overview of publications on MRI studies in AD. The United States is the leading country in this field with a concentration of highly productive researchers and high-level institutions. The current research hotspot is deep learning, which is being applied to develop noninvasive diagnosis and safer treatment of AD.

Association of bidirectional network cores in the brain with perceptual awareness and cognition

The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence suggests that both feedforward and feedback signals are necessary for conscious perception, emphasizing the importance of subnetworks with bidirectional interactions. However, the link between such subnetworks and conscious perception remains unclear due to the complexity of brain networks. In this study, we propose a framework for extracting subnetworks with strong bidirectional interactions-termed the "cores" of a network-from brain activity. We applied this framework to resting-state and task-based human fMRI data from participants of both sexes to identify regions forming strongly bidirectional cores. We then explored the association of these cores with conscious perception and cognitive functions. We found that the extracted central cores predominantly included cerebral cortical regions rather than subcortical regions. Additionally, regarding their relation to conscious perception, we demonstrated that the cores tend to include regions previously reported to be affected by electrical stimulation that altered conscious perception, although the results are not statistically robust due to the small sample size. Furthermore, in relation to cognitive functions, based on a meta-analysis and comparison of the core structure with a cortical functional connectivity gradient, we found that the central cores were related to unimodal sensorimotor functions. The proposed framework provides novel insights into the roles of network cores with strong bidirectional interactions in conscious perception and unimodal sensorimotor functions.

The Brain's Aging Resting State Functional Connectivity

Resting state networks (RSNs) of the brain are characterized as correlated spontaneous time-varying fluctuations in the absence of goal-directed tasks. These networks can be local or large-scale spanning the brain. The study of the spatiotemporal properties of such networks has helped understand the brain's fundamental functional organization under healthy and diseased states. As we age, these spatiotemporal properties change. Moreover, RSNs exhibit neural plasticity to compensate for the loss of cognitive functions. This narrative review aims to summarize current knowledge from functional magnetic resonance imaging (fMRI) studies on age-related alterations in RSNs. Underlying mechanisms influencing such changes are discussed. Methodological challenges and future directions are also addressed. By providing an overview of the current state of knowledge in this field, this review aims to guide future research endeavors aimed at promoting healthy brain aging and developing effective interventions for age-related cognitive impairment and neurodegenerative diseases.

Altered effective connectivity in Parkinson's disease patients with rapid eye movement sleep behavior disorder: a resting-state functional magnetic resonance imaging study and support vector machine analysis

Background

Rapid eye movement sleep behavior disorder (RBD) is associated with pathological α-synuclein deposition and may have different damage directions due to α-synuclein spreading orientations. Recent functional imaging studies of Parkinson's disease (PD) with RBD have identified abnormalities in connectivity, but effective connectivity (EC) for this altered orientation is understudied. Here, we aimed to explore altered intrinsic functional connectivity (FC) and EC in PD patients with probable RBD (pRBD).

Methods

This was a cross-sectional study. A total of 31 PD patients with pRBD (PD-pRBD), 35 PD without pRBD (PD-npRBD), and 32 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (RS-fMRI) scans. The voxel-wise degree centrality (DC) calculation was first performed to investigate the inherent connectivity of the PD-pRBD patients. Subsequently, we applied Granger causality analysis (GCA) to probe the causal effects of anomalous brain regions. Finally, the support vector machine (SVM) method was executed to evaluate the DC values in identifying PD-pRBD.

Results

PD-pRBD patients exhibited reduced z-DC values in the right precentral gyrus relative to PD-npRBD (voxel-level P<0.001, cluster-level P<0.05), as well as decreased z-DC values in the right postcentral gyrus and the superior parietal lobule compared to HCs. Then, our GCA revealed that decreased EC was located predominantly from the right precentral gyrus to the right caudate nucleus in the PD-pRBD group. Additionally, the SVM results revealed that the z-DC values of the right precentral gyrus could discriminate PD-pRBD from the PD-npRBD group [area under the curve (AUC) =0.905].

Conclusions

The altered z-DC in the right precentral gyrus and the anomaly causal effects from the precentral motor cortex to the ipsilateral striatum represented by the caudate nucleus might play vital roles in the pathogenesis of PD-pRBD. It was speculated that the attenuation of FC from the precentral motor cortex to the subcortical striatum might be associated with nocturnal muscle dyskinesia and behavioral abnormalities in PD-pRBD patients. This disruption pattern may be a prospective imaging marker in the characterization of PD with pRBD.

Mapping glioma's impact on cognition: Insights from macrostructure, microstructure, and beyond

Background

Cognitive impairment (CI) significantly impacts the quality of life of glioma patients. The main contributing risk factors include tumor characteristics, treatment-related factors, and their complex interplay. This review explores the role of advanced structural neuroimaging techniques in understanding CI in glioma patients.

Methods

A literature search was conducted in PubMed, PsycINFO, and ISI Web of Knowledge using specific keywords. We included studies with advanced magnetic resonance imaging techniques and objective neuropsychological exams.

Results

At diagnosis, during the pre-surgery phase, associations between glioma characteristics and cognitive outcomes have been described. Specifically, patients with isocitrate dehydrogenase (IDH)-wild-type gliomas exhibit more adverse cognitive outcomes, accompanied by disruptions in gray (GM) and white matter (WM) networks when compared to IDH-mutant. In addition, pre- and post-surgery imaging analyses highlight the importance of preserving specific WM tracts, such as the inferior longitudinal and arcuate fasciculus, in mitigating verbal memory and language processing decline. Furthermore, examining gliomas in perisylvian regions emphasizes deleterious effects on various cognitive domains. Additionally, it has been suggested that neuroplastic reorganization could serve as a compensatory mechanism against CI. Lastly, a limited number of studies suggest long-term CI linked to GM atrophy and leukoencephalopathy induced by radiotherapy ± chemotherapy in glioma survivors, highlighting the need for improving treatment approaches, particularly for patients with extended survival expectations.

Conclusion

This review underscores the need for nuanced understanding and an individual approach in the management of glioma patients. Neuroplastic insights offer clinicians valuable guidance in surgical decision-making and personalized therapeutic approaches thus improving patient outcomes in neuro-oncology.

Neuroscience of coma

Coma and disorders of consciousness are frequently considered in terms of two linked anatomic-functional systems: the arousal system and the awareness system. The mesopontine tegmentum (namely the cuneiform/subcuneiform nuclei of the caudal midbrain and the pontis oralis nucleus of the rostral pons) and the monoamine nuclei generate signals of arousal. These signals are augmented in lateral hypothalamus and basal forebrain, which then project to the thalamus and diffusely across the cortex. The medial dorsal tegmental tract is the main conduit for the ascending arousal system to directly activate the thalamic intralaminar nuclei and modulate thalamocortical networks, while the lateral dorsal tegmental tract connects to the thalamic reticular nucleus for regulation of intrathalamic inhibitory networks. The central thalamus (particularly the intralaminar nuclei) and the mesocircuit regulate the arousal system. Lesions to any part of this system, particularly paramedian and bilateral lesions, result in a depressed level of arousal. Distinct from the arousal pathways, the awareness system runs continuously as a stream of consciousness. It consists of large-scale distributed cortical networks that are necessary for representations of the external (executive control network with the dorsal/ventral attention networks) and the internal world (executive control network in conjunction with the default network). A feature of the awareness system is that it does not capture external and internal worlds at once and instead, holds singular representations, serially moment-by-moment. The medial dorsal nucleus of the thalamus serves as the associative nuclei of the default network, and the thalamic reticular nucleus regulates the awareness system. Lesions that disrupt large-scale networks, particularly nodes of cortical hubs, result in lack of awareness. Integrative paradigms such as the integrated information theory and the global neuronal workspace models are attempts to bind awareness and arousal into a unified experience of consciousness.

Connectivity Regression

Assessing how brain functional connectivity networks vary across individuals promises to uncover important scientific questions such as patterns of healthy brain aging through the lifespan or dysconnectivity associated with disease. In this article, we introduce a general regression framework, Connectivity Regression (ConnReg), for regressing subject-specific functional connectivity networks on covariates while accounting for within-network inter-edge dependence. ConnReg utilizes a multivariate generalization of Fisher's transformation to project network objects into an alternative space where Gaussian assumptions are justified and positive semidefinite constraints are automatically satisfied. Penalized multivariate regression is fit in the transformed space to simultaneously induce sparsity in regression coefficients and in covariance elements, which capture within network inter-edge dependence. We use permutation tests to perform multiplicity-adjusted inference to identify covariates associated with connectivity, and stability selection scores to identify network edges that vary with selected covariates. Simulation studies validate the inferential properties of our proposed method and demonstrate how estimating and accounting for within-network inter-edge dependence leads to more efficient estimation, more powerful inference, and more accurate selection of covariate-dependent network edges. We apply ConnReg to the Human Connectome Project Young Adult study, revealing insights into how connectivity varies with language processing covariates and structural brain features.

Role of homeostatic plasticity in critical brain dynamics following focal stroke lesions

Can focal brain lesions, such as those caused by stroke, disrupt critical brain dynamics? What biological mechanisms drive its recovery? In a recent study, we showed that focal lesions generate a sub-critical state that recovers over time in parallel with behavior (Rocha et al., Nat. Commun. 13, 2022). The loss of criticality in a cohort of stroke patients was associated with structural brain disconnections, while its recovery was accompanied by the re-modeling of specific white-matter tracts. These results were challenged by Janarek et al. (Sci. Rep. 13, 2023), who proposed an alternative interpretation for the anomalous monotonic decaying of the second cluster size, which is the neural signature originally used to infer loss of criticality. The present study tackles this controversy and provides evidence that the theoretical framework proposed by Janarek et al. cannot explain the anomalous cluster dynamics observed in our patients. Notably, this invalidates the claim that the brain maintains its critical dynamics regardless of the lesion severity. In addition, we explore biological mechanisms beyond white-matter remodeling that may facilitate the recovery of criticality over time. We considered two distinct scenarios: one where we suppress homeostatic plasticity, and another where we increase the excitability of brain regions. We find that suppressing homeostatic plasticity - specifically, the inhibition-excitation balance - disfavors the emergence of criticality. Conversely, increasing brain excitability can help to restore criticality when the latter is disrupted. Our results suggest that normalizing the excitation-inhibition balance is crucial for supporting recovery of critical brain dynamics.

An experimental framework for conjoint measures of olfaction, navigation, and motion as pre-clinical biomarkers of Alzheimer's disease

Elucidating Alzheimer's disease (AD) prodromal symptoms can resolve the outstanding challenge of early diagnosis. Based on intrinsically related substrates of olfaction and spatial navigation, we propose a novel experimental framework for their conjoint study. Artificial intelligence-driven multimodal study combining self-collected olfactory and motion data with available big clinical datasets can potentially promote high-precision early clinical screenings to facilitate timely interventions targeting neurodegenerative progression.

Stepwise pathways from the olfactory cortex to central hub regions in the human brain

The human brain is organized as a hierarchical global network. Functional connectivity research reveals that sensory cortices are connected to corresponding association cortices via a series of intermediate nodes linked by synchronous neural activity. These sensory pathways and relay stations converge onto central cortical hubs such as the default-mode network (DMN). The DMN regions are believed to be critical for representing concepts and, hence, language acquisition and use. Although prior research has established that major senses are placed at a similar distance from the DMN-five to six connective steps-it is still unknown how the olfactory system functionally connects to the large-scale cortical hubs of the human brain. In this study, we investigated the connective distance from olfactory seed areas to the DMN. The connective distance involves a series of three to four intermediate steps. Furthermore, we parcellated the olfactory cortical subregions and found evidence of two distinct olfactory pathways. One emerges from the anterior olfactory nucleus and olfactory tubercle; it involves early access to the orbitofrontal cortex, known for processing reward and multisensory signals. The other emerges from the frontal and temporal regions of the piriform cortex, involving the anterior insula, intermediate frontal sulcus, and parietal operculum. The results were confirmed in a replication cohort. Our results provide evidence that olfaction has unique early access to the central cortical networks via dual pathways.