Most recent paper

Estimating the energy of dissipative neural systems

Mon, 12/23/2024 - 19:00

Cogn Neurodyn. 2024 Dec;18(6):3839-3846. doi: 10.1007/s11571-024-10166-1. Epub 2024 Aug 29.

ABSTRACT

There is, at present, a lack of consensus regarding precisely what is meant by the term 'energy' across the sub-disciplines of neuroscience. Definitions range from deficits in the rate of glucose metabolism in consciousness research to regional changes in neuronal activity in cognitive neuroscience. In computational neuroscience virtually all models define the energy of neuronal regions as a quantity that is in a continual process of dissipation to its surroundings. This, however, is at odds with the definition of energy used across all sub-disciplines of physics: a quantity that does not change as a dynamical system evolves in time. Here, we bridge this gap between the dissipative models used in computational neuroscience and the energy-conserving models of physics using a mathematical technique first proposed in the context of fluid dynamics. We go on to derive an expression for the energy of the linear time-invariant (LTI) state space equation. We then use resting-state fMRI data obtained from the human connectome project to show that LTI energy is associated with glucose uptake metabolism. Our hope is that this work paves the way for an increased understanding of energy in the brain, from both a theoretical as well as an experimental perspective.

PMID:39712109 | PMC:PMC11655998 | DOI:10.1007/s11571-024-10166-1

Advancements in automated diagnosis of autism spectrum disorder through deep learning and resting-state functional mri biomarkers: a systematic review

Mon, 12/23/2024 - 19:00

Cogn Neurodyn. 2024 Dec;18(6):3585-3601. doi: 10.1007/s11571-024-10176-z. Epub 2024 Sep 13.

ABSTRACT

Autism Spectrum Disorder(ASD) is a type of neurological disorder that is common among children. The diagnosis of this disorder at an early stage is the key to reducing its effects. The major symptoms include anxiety, lack of communication, and less social interaction. This paper presents a systematic review conducted based on PRISMA guidelines for automated diagnosis of ASD. With rapid development in the field of Data Science, numerous methods have been proposed that can diagnose the disease at an early stage which can minimize the effects of the disorder. Machine learning and deep learning have proven suitable techniques for the automated diagnosis of ASD. These models have been developed on various datasets such as ABIDE I and ABIDE II, a frequently used dataset based on rs-fMRI images. Approximately 26 articles have been reviewed after the screening process. The paper highlights a comparison between different algorithms used and their accuracy as well. It was observed that most researchers used DL algorithms to develop the ASD detection model. Different accuracies were recorded with a maximum accuracy close to 0.99. Recommendations for future work have also been discussed in a later section. This analysis derived a conclusion that AI-emerged DL and ML technologies can diagnose ASD through rs-fMRI images with maximum accuracy. The comparative analysis has been included to show the accuracy range.

PMID:39712105 | PMC:PMC11656001 | DOI:10.1007/s11571-024-10176-z

A whole-brain functional connectivity model of Alzheimer's disease pathology

Mon, 12/23/2024 - 19:00

Alzheimers Dement. 2024 Dec 23. doi: 10.1002/alz.14349. Online ahead of print.

ABSTRACT

INTRODUCTION: Alzheimer's disease (AD) is characterized by the presence of two proteinopathies, amyloid and tau, which have a cascading effect on the functional and structural organization of the brain.

METHODS: In this study, we used a supervised machine learning technique to build a model of functional connections that predicts cerebrospinal fluid (CSF) p-tau/Aβ42 (the PATH-fc model). Resting-state functional magnetic resonance imaging (fMRI) data from 289 older adults in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were utilized for this model.

RESULTS: We successfully derived the PATH-fc model to predict the ratio of p-tau/Aβ42 as well as cognitive functioning in older adults across the spectrum of healthy and pathological aging. However, the in-sample fit magnitude was low, indicating a need for further model development.

DISCUSSION: Our pathology-based model of functional connectivity included representation from multiple canonical networks of the brain with intra-network connectivity associated with low pathology and inter-network connectivity associated with higher levels of pathology.

HIGHLIGHTS: Whole-brain functional connectivity model (PATH-fc) is linked to AD pathophysiology. The PATH-fc model predicts performance in multiple domains of cognitive functioning. The PATH-fc model is a distributed model including representation from all canonical networks.

PMID:39711458 | DOI:10.1002/alz.14349

Transcranial Direct Current Stimulation Over Bilateral Temporal Lobes Modulates Hippocampal-Occipital Functional Connectivity and Visual Short-Term Memory Precision

Mon, 12/23/2024 - 19:00

Hippocampus. 2025 Jan;35(1):e23678. doi: 10.1002/hipo.23678.

ABSTRACT

Although the medial temporal lobe (MTL) is traditionally considered a region dedicated to long-term memory, recent neuroimaging and intracranial recording evidence suggests that the MTL also contributes to certain aspects of visual short-term memory (VSTM), such as the quality or precision of retained VSTM content. This study aims to further investigate the MTL's role in VSTM precision through the application of transcranial direct current stimulation (tDCS) and functional magnetic resonance imaging (fMRI). Participants underwent 1.5 mA offline tDCS over bilateral temporal lobes using left cathodal and right anodal electrodes, administered for either 20 min (active) or 0.5 min within a 20-min window (sham), in a counterbalanced design. As the electrical current passes through midbrain structures with this bilateral stimulation montage, prior behavioral and modeling evidence suggests that this tDCS protocol can modulate MTL functions. To confirm this and examine its impacts on VSTM, participants completed a VSTM color recall task immediately following tDCS, while undergoing a 20-min fMRI scan and a subsequent 7.5-min resting-state scan, during which they focused on a fixation cross. Behavioral results indicated that this tDCS protocol decreased VSTM precision without significantly affecting overall recall success. Furthermore, psychophysiological interaction analysis revealed that tDCS over the temporal lobe modulated hippocampal-occipital functional connectivity during the VSTM task, despite no main effect on fMRI BOLD activity. Notably, this modulation was also observed during resting-state fMRI 15-20 min post-tDCS, with the magnitude of the effect correlating with participants' behavioral changes in VSTM precision across active and control conditions. Combined, these findings suggest that tDCS over the temporal lobe can modulate the intrinsic functional connectivity between the MTL and visual sensory areas, thereby affecting VSTM precision.

PMID:39711102 | DOI:10.1002/hipo.23678

Effect of carotid artery stenting on cognitive function in patients with asymptomatic carotid artery stenosis, a multimodal magnetic resonance study

Sun, 12/22/2024 - 19:00

Magn Reson Imaging. 2024 Dec 20:110296. doi: 10.1016/j.mri.2024.110296. Online ahead of print.

ABSTRACT

INTRODUCTION: More and more evidence suggesting that internal carotid artery stenosis is not only a risk factor for ischemic stroke but also for cognitive impairments. Hypoperfusion and silent micro emboli have been reported as the pathophysiological mechanisms causing cognitive impairment. The effect of carotid artery stenting (CAS) on cognitive function varied from study to study. This study aims to explore the effect of CAS on cognition and exam the changes in cerebral perfusion and brain connectivity with pulsed arterial spin labeling (pASL) and resting-state functional MRI (R-fMRI).

METHODS: We conducted a controlled trial to assess alterations in cognitive performance among patients with "asymptomatic" carotid artery stenosis prior to and 3 months post-CAS intervention. Cognitive function including the Montreal Cognitive Assessment (MoCA) Beijing Version, the Minimum Mental State Examination (MMSE), the Digit Symbol Test, the Rey Auditory Verbal Learning Test (RAVLT), and the Verbal Memory Test. pASL perfusion MRI and R-fMRI were also performed prior to and 3 months post-CAS intervention.

RESULTS: 13 patients completed all the follow-up. We observed increased perfusion in the right parietal lobe and right occipital lobe, increased amplitude of low-frequency fluctuation (ALFF) in the right precentral gyrus, increased connectivity to the posterior cingulate cortex (PCC) in the right frontal gyrus and right precuneus, and increased voxel-wise mirrored homotopic connectivity (VMHC) in the right precuneus 3 months after CAS when compared with prior to CAS. Cognitive test results showed significant improvement in the scores on the MMSE, the Verbal Memory test, and the delayed recall.

CONCLUSION: CAS can partly improve the cognitive function in patients with "asymptomatic" carotid artery stenosis, and the improvement may be attributable to the increased perfusion in the right parietal lobe and right occipital lobe, increased ALFF in the right precentral gyrus, increased connectivity to the PCC in the right frontal gyrus and right precuneus, and increased VMHC in the right precuneus.

PMID:39710010 | DOI:10.1016/j.mri.2024.110296

Altered coupling relationships across resting-state functional connectivity measures in schizophrenia, bipolar disorder, and attention deficit/hyperactivity disorder

Sun, 12/22/2024 - 19:00

Psychiatry Res Neuroimaging. 2024 Dec 18;347:111943. doi: 10.1016/j.pscychresns.2024.111943. Online ahead of print.

ABSTRACT

Resting-state functional connectivity (rsFC) measures have enjoyed significant success in discovering the neuropathological characteristics of schizophrenia (SZ), bipolar disorder (BD), and attention deficit/hyperactivity disorder (ADHD). However, it is unknown whether and how the spatial and temporal coupling relationships across rsFC measures would be altered in these psychiatric disorders. Here, resting-state fMRI data were obtained from a transdiagnostic sample of healthy controls (HC) and individuals with SZ, BD, and ADHD. We used Kendall's W to compute volume-wise and voxel-wise concordance across rsFC measures, followed by group comparisons. In terms of the spatial coupling, both SZ and BD individuals exhibited decreased volume-wise concordance compared with HC. Regarding the temporal coupling, SZ individuals showed decreased voxel-wise concordance in the right lateral occipital cortex relative to HC. BD individuals exhibited decreased voxel-wise concordance in the bilateral basal forebrain and bilateral superior/middle temporal gyrus compared to HC. Additionally, correlation analyses demonstrated positive associations of voxel-wise concordance in the left basal forebrain with negative symptoms including alogia and affective flattening in pooled SZ and BD individuals. Our findings of distinct patterns of spatial and temporal decoupling across rsFC measures among SZ, BD, and ADHD may provide unique insights into the neuropathological mechanisms of these psychiatric disorders.

PMID:39709676 | DOI:10.1016/j.pscychresns.2024.111943

Brain networks and intelligence: A graph neural network based approach to resting state fMRI data

Sat, 12/21/2024 - 19:00

Med Image Anal. 2024 Dec 16;101:103433. doi: 10.1016/j.media.2024.103433. Online ahead of print.

ABSTRACT

Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying on a specific task or stimuli. In this paper, we present a novel modeling architecture called BrainRGIN for predicting intelligence (fluid, crystallized and total intelligence) using graph neural networks on rsfMRI derived static functional network connectivity matrices. Extending from the existing graph convolution networks, our approach incorporates a clustering-based embedding and graph isomorphism network in the graph convolutional layer to reflect the nature of the brain sub-network organization and efficient network expression, in combination with TopK pooling and attention-based readout functions. We evaluated our proposed architecture on a large dataset, specifically the Adolescent Brain Cognitive Development Dataset, and demonstrated its effectiveness in predicting individual differences in intelligence. Our model achieved lower mean squared errors and higher correlation scores than existing relevant graph architectures and other traditional machine learning models for all of the intelligence prediction tasks. The middle frontal gyrus exhibited a significant contribution to both fluid and crystallized intelligence, suggesting their pivotal role in these cognitive processes. Total composite scores identified a diverse set of brain regions to be relevant which underscores the complex nature of total intelligence. Our GitHub implementation is publicly available on https://github.com/bishalth01/BrainRGIN/.

PMID:39708510 | DOI:10.1016/j.media.2024.103433

Impact of Spinal Manipulative Therapy on Brain Function and Pain Alleviation in Lumbar Disc Herniation: A Resting-State fMRI Study

Fri, 12/20/2024 - 19:00

Chin J Integr Med. 2024 Dec 21. doi: 10.1007/s11655-024-4205-7. Online ahead of print.

ABSTRACT

OBJECTIVE: To elucidate how spinal manipulative therapy (SMT) exerts its analgesic effects through regulating brain function in lumbar disc herniation (LDH) patients by utilizing resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: From September 2021 to September 2023, we enrolled LDH patients (LDH group, n=31) and age- and sex-matched healthy controls (HCs, n=28). LDH group underwent rs-fMRI at 2 distinct time points (TPs): prior to the initiation of SMT (TP1) and subsequent to the completion of the SMT sessions (TP2). SMT was administered once every other day for 30 min per session, totally 14 treatment sessions over a span of 4 weeks. HCs did not receive SMT treatment and underwent only one fMRI scan. Additionally, participants in LDH group completed clinical questionnaires on pain using the Visual Analog Scale (VAS) and the Japanese Orthopedic Association (JOA) score, whereas HCs did not undergo clinical scale assessments. The effects on the brain were jointly characterized using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Correlation analyses were conducted between specific brain regions and clinical scales.

RESULTS: Following SMT treatment, pain symptoms in LDH patients were notably alleviated and accompanied by evident activation of effects in the brain. In comparison to TP1, TP2 exhibited the most significant increase in ALFF values for Temporal_Sup_R and the most notable decrease in ALFF values for Paracentral_Lobule_L (voxelwise P<0.005; clusters >30; FDR correction). Additionally, the most substantial enhancement in ReHo values was observed for the Cuneus_R, while the most prominent reduction was noted for the Olfactory_R (voxelwise P<0.005; clusters >30; FDR correction). Moreover, a comparative analysis revealed that, in contrast to HCs, LDH patients at TP1 exhibited the most significant increase in ALFF values for Temporal_Pole_Sup_L and the most notable decrease in ALFF values for Frontal_Mid_L (voxelwise P<0.005; clusters >30; FDR correction). Furthermore, the most significant enhancement in ReHo values was observed for Postcentral_L, while the most prominent reduction was identified for ParaHippocampal_L (voxelwise P<0.005; clusters >30; FDR correction). Notably, correlation analysis with clinical scales revealed a robust positive correlation between the Cuneus_R score and the rate of change in the VAS score (r=0.9333, P<0.0001).

CONCLUSIONS: Long-term chronic lower back pain in patients with LDH manifests significant activation of the "AUN-DMN-S1-SAN" neural circuitry. The visual network, represented by the Cuneus_R, is highly likely to be a key brain network in which the analgesic efficacy of SMT becomes effective in treating LDH patients. (Trial registration No. NCT06277739).

PMID:39707137 | DOI:10.1007/s11655-024-4205-7

Aging of visual word perception is related to decreased segregation within and beyond the word network in the brain

Fri, 12/20/2024 - 19:00

Front Aging Neurosci. 2024 Dec 5;16:1483449. doi: 10.3389/fnagi.2024.1483449. eCollection 2024.

ABSTRACT

INTRODUCTION: We investigated the neural correlates of cognitive decline in visual word perception from the perspective of intrinsic brain networks.

METHODS: A total of 19 healthy older adults and 22 young adults were recruited to participate in two functional magnetic resonance imaging (fMRI) sessions (one resting-state session and one for localizer tasks), along with a visual word perceptual processing task. We examined age-related alterations in resting-state functional connectivity (FC) within the word network, as well as between the word network and other networks. We tested their associations with behavioral performance in word and symbol-form processing.

RESULTS: We found that, compared to young adults, older adults exhibited increased FC between the two word-selective regions in the left and right ventral occipitotemporal cortex (vOT). Additionally, older adults exhibited increased FC between these two word-selective regions and non-word-selective regions. Notably, these FC alterations correlated with individual differences in behavioral performance in visual word perception.

DISCUSSION: These results suggest that cognitive decline in visual word perception is associated with decreased segregation within and beyond the word network in the aging brain. Our findings support the neural dedifferentiation hypothesis for cognitive decline in visual word processing and improve our understanding of interactive neural specialization theory.

PMID:39703923 | PMC:PMC11655501 | DOI:10.3389/fnagi.2024.1483449

Alterations in spontaneous brain activity of maintenance hemodialysis patients with restless legs syndrome: a cross-sectional case-control study

Fri, 12/20/2024 - 19:00

BMC Neurol. 2024 Dec 19;24(1):486. doi: 10.1186/s12883-024-03985-6.

ABSTRACT

OBJECTIVE: Through resting state functional magnetic resonance imaging (rs-fMRI) we evaluate the spontaneous brain activity changes of maintenance hemodialysis (MHD) patients with restless legs syndrome (RSL) and analyzed the imaging features and related mechanisms of RLS in patients with MHD.

METHOD: We select 27 MHD patients with RLS and 27 patients without RSL matched by age, gender, cognitive function. Both groups underwent neuropsychological tests and MRI scans. MRI data analysis was performed to obtain and compare the amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo) values, which were mALFF, mfALFF, and mReHo. Clinical data were collected and compared. Differentiated indicators and RLS scores conduct Pearson correlation analysis.

RESULT: Compared with the MHD-nRLS group, the MHD-RLS group showed significantly lower mALFF values in the left precentral, right precentral gyrus, and right postcentral gyrus, lower mfALFF values in the left precentral gyrus, right precentral gyrus, left calcarine fissure, left lingual gyrus, left postcentral gyrus, and right postcentral gyrus, and lower mReHo values in the left precentral gyrus, right precentral gyrus, left calcarine fissure, left lingual gyrus, left postcentral gyrus, and right postcentral gyrus, and right postcentral gyrus (P < 0.05). The MHD-RLS group exhibited lower hemoglobin levels (P = 0.001), higher total iron-binding capacity levels (P = 0.011), and higher folic acid levels (P = 0.022). The above indicators were correlated with RLS scores using Pearson correlation analysis, and it was found that the mfALFF value of the right precentral gyrus and the right postcentral gyrus, and the mReHo values of the right precentral gyrus and right postcentral gyrus were negatively correlated with the RLS score (r = -0.567, P = 0.002;r = -0.705, P < 0.001;r = -0.414, P = 0.032; r = -0.410, P = 0.034), and the hemoglobin concentration was negatively correlated with the RLS scores (r = -0.394, P = 0.042).

CONCLUSION: Patients with MHD-RLS exhibit abnormal spontaneous brain activity in the right precentral gyrus and right postcentral gyrus within the sensorimotor network, along with lower hemoglobin levels, which may be associated with the pathogenesis and severity of MHD-RLS.

PMID:39702164 | DOI:10.1186/s12883-024-03985-6

Rumination induction task in fMRI: Effects of rumination focused cognitive behavioral therapy and stability in youth

Thu, 12/19/2024 - 19:00

J Affect Disord. 2024 Dec 17:S0165-0327(24)02044-5. doi: 10.1016/j.jad.2024.12.056. Online ahead of print.

ABSTRACT

BACKGROUND: Rumination is implicated in the onset and maintenance of major depressive disorder (MDD). Rumination-Focused Cognitive Behavioral Therapy (RF-CBT) effectively targets rumination and may change resting-state brain connectivity and change in activation during a rumination induction task (RIT) post-intervention predicts depressive symptoms two years later. We examined brain activation changes during an RIT in adolescents with remitted MDD following RF-CBT and evaluated RIT reliability (or stability) during treatment as usual (TAU).

METHOD: Fifty-five adolescents ages 14-17 completed an RIT at baseline, were randomized to 10-14 sessions of RF-CBT (n = 30) or treatment as usual (n = 25) and completed an RIT at post-treatment or equivalent time delay. The RIT includes recalling negative memories (Rumination Instruction), dwelling on their meaning/consequences (Rumination Prompt), and imagining unrelated scenes and objects (Distraction). We assessed activation change in the RF-CBT group using paired-samples t-tests. We assessed reliability (or stability) via intraclass correlation coefficients (ICCs) of five rumination-related ROIs for TAU and RF-CBT separately across task blocks.

RESULTS: Following treatment, participants receiving RF-CBT demonstrated increased activation of left precuneus during Rumination Instruction and of left angular and superior temporal gyri during Rumination Prompt blocks (p < .01). From baseline to post-treatment, across most ROIs and task blocks, the RF-CBT group demonstrated poor stability (M = 0.21, range = -0.19-0.69), while the TAU group demonstrated fair-to-excellent stability (M = 0.52, range = 0.27-0.86).

CONCLUSION: RF-CBT changes activation of rumination-related circuitry during state-induced rumination, offering exciting avenues for future interventions. The RIT has fair-to-excellent stability among individuals not explicitly treated for rumination, and as expected, RIT stability is disrupted by RF-CBT.

PMID:39701467 | DOI:10.1016/j.jad.2024.12.056

State-dependent inter-network functional connectivity development in neonatal brain from the developing human connectome project

Thu, 12/19/2024 - 19:00

Dev Cogn Neurosci. 2024 Dec 12;71:101496. doi: 10.1016/j.dcn.2024.101496. Online ahead of print.

ABSTRACT

Although recent studies have consistently reported the emergence of resting-state networks in early infancy, the changes in inter-network functional connectivity with age are controversial and the alterations in its dynamics remain unclear at this stage. This study aimed to investigate dynamic functional network connectivity (dFNC) using resting-state functional MRI in 244 full-term (age: 37-44 weeks) and 36 preterm infants (age: 37-43 weeks) from the dHCP dataset. We evaluated whether early dFNC exhibits age-dependent changes and is influenced by preterm birth. Gestational age (GA) and postnatal age (PNA) showed different effects on variance of FNC change over time during fMRI scan in resting-state networks, especially among high-order association networks. These variances were significantly reduced by preterm birth. Moreover, two states of weakly-connected (State Ⅰ) and strongly-connected (State Ⅱ) FNC were identified. The fraction window and dwell time in State Ⅰ, and the transition from State Ⅱ to State Ⅰ, all showed significantly negative correlations with both GA and PNA. Preterm-born infants spent a longer time in the weakly-connected state compared to term-born infants. These findings suggest a state-dependent development of dynamic FNC across brain networks in the early stages, gradually reconfiguring towards a more flexible and dynamic system with stronger connections.

PMID:39700911 | DOI:10.1016/j.dcn.2024.101496

Consistent frontal-limbic-occipital connections in distinguishing treatment-resistant and non-treatment-resistant schizophrenia

Thu, 12/19/2024 - 19:00

Neuroimage Clin. 2024 Dec 12;45:103726. doi: 10.1016/j.nicl.2024.103726. Online ahead of print.

ABSTRACT

BACKGROUND AND HYPOTHESIS: Treatment-resistant schizophrenia (TR-SZ) and non-treatment-resistant schizophrenia (NTR-SZ) lack specific biomarkers to distinguish from each other. This investigation aims to identify consistent dysfunctional brain connections with different atlases, multiple feature selection strategies, and several classifiers in distinguishing TR-SZ and NTR-SZ.

STUDY DESIGN: 55 TR-SZs, 239 NTR-SZs, and 87 healthy controls (HCs) were recruited from the Affiliated Brain Hospital of Nanjing Medical University. Resting-state functional connection (FC) matrices were constructed from automated anatomical labeling (AAL), Yeo-Networks (YEO) and Brainnetome (BNA) atlases. Two feature selection methods (Select From Model and Recursive Feature Elimination) and four classifiers (Adaptive Boost, Bernoulli Naïve Bayes, Gradient Boosting and Random Forest) were combined to identify the consistent FCs in distinguishing TR-SZ and HC, NTR-SZ and HC, TR-SZ and NTR-SZ.

STUDY RESULTS: The whole brain FCs, except the temporal-occipital FC, were consistent in distinguishing SZ and HC. Abnormal frontal-limbic, frontal-parietal and occipital-temporal FCs were consistent in distinguishing TR-SZ and NTR-SZ, that were further correlated with disease progression, symptoms and medication dosage. Moreover, the frontal-limbic and frontal-parietal FCs were highly consistent for the diagnosis of SZ (TR-SZ vs. HC, NTR-SZ vs. HC and TR-SZ vs. NTR-SZ). The BNA atlas achieved the highest classification accuracy (>90 %) comparing with AAL and YEO in the most diagnostic tasks.

CONCLUSIONS: These results indicate that the frontal-limbic and the frontal-parietal FCs are the robust neural pathways in the diagnosis of SZ, whereas the frontal-limbic, frontal-parietal and occipital-temporal FCs may be informative in recognizing those TR-SZ in the clinical practice.

PMID:39700898 | DOI:10.1016/j.nicl.2024.103726

Association of Early fMRI Connectivity Alterations With Different Cognitive Phenotypes in Patients With Newly Diagnosed Parkinson Disease

Thu, 12/19/2024 - 19:00

Neurology. 2025 Jan 14;104(1):e210192. doi: 10.1212/WNL.0000000000210192. Epub 2024 Dec 19.

ABSTRACT

BACKGROUND AND OBJECTIVES: According to the dual syndrome hypothesis, patients with Parkinson disease (PD) with visuospatial deficits are more likely to progress to dementia, compared with patients with a prevalent dysexecutive syndrome. In this study, we aimed to investigate whether early connectivity changes in the dorsolateral prefrontal cortex (DLPFC) and the precuneus (PCun)-which are critical to fronto-executive and visuospatial functions, respectively-can identify distinct cognitive phenotypes in cognitively intact newly diagnosed patients with PD.

METHODS: Newly diagnosed, drug-naïve patients with PD (≤2 years from clinical onset) with normal Montreal Cognitive Assessment (MoCA), were consecutively enrolled from our Movement Disorders Clinics in Italy. Sex-matched and age-matched healthy controls (HCs) were enrolled among nonconsanguineous patients' relatives. Participants underwent 3T-fMRI to investigate resting-state functional connectivity (rs-FC) of DLPFC and PCun with a seed-based approach at baseline (T0). K-means cluster analysis was performed on z scores of rs-FC values of patients with PD to identify clusters of patients sharing common patterns of connectivity. Differences in neurophysiologic, motor, and nonmotor scales among PD clusters were assessed at T0 and after a 3.5-year follow-up (T1).

RESULTS: The study included 68 patients with PD (27% women; mean age: 60 ± 9 years; Hoehn & Yahr score: 1.4 ± 0.5; MoCA score: 27.9 ± 1.6) and 31 HCs (39% women; mean age 64.2 ± 9.3 years) at T0. Forty-two patients completed T1 evaluation. Patients displayed reduced rs-FC of both DLPFC and PCun with several cortical and subcortical areas compared with HCs. Cluster 1 was defined by lower values of rs-FC in all investigated regions of interest while clusters 2 and 3, respectively, by higher and intermediate values. Despite none meeting criteria for mild cognitive impairment (MCI) at T0, cluster 1 was older and lower performing in global cognition, fronto-executive, and memory domains, compared with clusters 2 and 3 (all p < 0.031). At T1, a more evident worsening in global cognition, fronto-executive, and visuospatial domains and nonmotor and motor symptoms was observed in clusters 1 and 3 vs cluster 2 (all p < 0.04), with MCI being more frequent in clusters 1 and 3.

DISCUSSION: Early connectivity changes of the DLPFC and the PCun occur in newly diagnosed patients with PD without MCI and can distinguish cognitive phenotypes, as confirmed after a longitudinal clinical observation.

PMID:39700449 | DOI:10.1212/WNL.0000000000210192

Assessing regional homogeneity and cognitive function alterations in pediatric brain tumor patients: a resting-state functional magnetic resonance imaging study

Thu, 12/19/2024 - 19:00

Quant Imaging Med Surg. 2024 Dec 5;14(12):8686-8695. doi: 10.21037/qims-24-529. Epub 2024 Oct 25.

ABSTRACT

BACKGROUND: Cognitive impairment mechanisms in children with preoperative brain tumors are not well understood. This study aimed to determine the correlation between the changes of resting-state functional magnetic resonance imaging (rs-fMRI) and the fourth edition of the Wechsler Intelligence Scale for Children (WISC-IV) in patients with brain tumors before surgery and in healthy controls (HCs).

METHODS: rs-fMRI data were acquired using 3-T magnetic resonance imaging (MRI) scanners for 21 patients with pediatric brain tumor and 19 age- and gender-matched HCs. The data of WISC-IV were collected by psychiatrists. We used chi-square tests and two-sample t-tests to identify clinical features with significant associations before surgery. A two-sample t-tests was used to identify brain regions with significant changes in regional homogeneity (ReHo) before surgery in patients. Pearson correlation coefficients were used to assess the relationship between changes in ReHo and the five measures in the WISC-IV.

RESULTS: The ReHo values were significantly decreased in the left anterior cingulate (T=-4.391) and right middle frontal gyrus (MFG) (T=-5.130) in patients compared to controls. Notably, ReHo values in the right MFG showed a positive correlation with the Perceptual Reasoning Index (R=0.471; P=0.031) and Working Memory Index (R=0.531; P=0.013) of the WISC-IV.

CONCLUSIONS: The study identified significant ReHo alterations in patients with pediatric brain tumor, primarily in brain regions associated with cognitive processing, and revealed a positive correlation between these alterations and specific cognitive functions. These findings contribute to understanding cognitive impairments in this patient group and suggest potential areas for targeted intervention.

PMID:39698679 | PMC:PMC11651996 | DOI:10.21037/qims-24-529

Sustained effects of repeated levodopa (L-DOPA) administration on reward circuitry, effort-based motivation, and anhedonia in depressed patients with higher inflammation

Wed, 12/18/2024 - 19:00

Brain Behav Immun. 2024 Dec 16:S0889-1591(24)00755-4. doi: 10.1016/j.bbi.2024.12.026. Online ahead of print.

ABSTRACT

Inflammatory biomarkers like C-reactive protein (CRP) are elevated in a subset of patients with depression and associated with lower functional connectivity (FC) in a ventral striatum (VS) to ventromedial prefrontal cortex (vmPFC) reward circuit and symptoms of anhedonia. Evidence linking these relationships to the effects of inflammation on dopamine is consistent with our recent findings that acute levodopa (L-DOPA) increased VS-vmPFC FC in association with deceased anhedonia in depressed patients with higher but not lower CRP (>2 versus ≤ 2 mg/L). To determine whether repeated L-DOPA administration caused sustained effects on FC and behavior in these patients, medically stable depressed outpatients with CRP > 2 mg/L and anhedonia (n = 18) received one week of three doses of L-DOPA (150-450 mg/day/week with carbidopa) or placebo in a randomized order. Resting-state (rs) and task-based (tb; monetary incentive delay) fMRI, effort-based motivation, and exploratory measures of anhedonia and depression severity were assessed at baseline and after one week of placebo and each dose of L-DOPA. Responses to individual doses of L-DOPA varied across outcomes. For example, VS-vmPFC rs-FC was significantly increased by L-DOPA at 150 and 450 mg/day/week (p < 0.01), whereby approximately half of patients responded optimally to 150 mg/day L-DOPA and approximately half required higher doses for maximum effect. While effort-based motivation was only significantly increased by L-DOPA at 150 mg/day (p < 0.05), it correlated with VS-vmPFC rs-FC at this dose (r = 0.64, p = 0.024), and all L-DOPA doses met a clinically significant threshold of ≥ 10 % increase versus placebo. When comparing the maximum response at any L-DOPA dose to placebo, high effect sizes were observed for these primary outcomes and tb-FC during reward anticipation (dz = 0.82-0.98, p < 0.01), as well as secondary and exploratory measures of anhedonia and depression severity (dz = 0.48-0.97, p < 0.05). Sustained effects on reward circuitry, effort-based motivation, and anhedonia by repeated L-DOPA administration support the therapeutic potential of agents that increase dopamine in depressed patients with higher inflammation.

PMID:39694342 | DOI:10.1016/j.bbi.2024.12.026

Altered Hippocampal Subfields Functional Connectivity in Benign Paroxysmal Positional Vertigo Patients With Residual Dizziness: A Resting-State fMRI Study

Wed, 12/18/2024 - 19:00

CNS Neurosci Ther. 2024 Dec;30(12):e70175. doi: 10.1111/cns.70175.

ABSTRACT

OBJECTIVE: To explore alterations in functional connectivity (FC) focusing on hippocampal subfields in benign paroxysmal positional vertigo (BPPV) patients with residual dizziness (RD) after successful canalith repositioning procedure (CRP).

METHODS: We conducted resting-state functional magnetic resonance imaging (fMRI) on 95 BPPV patients, comprising 50 patients with RD and 45 without. Seed-to-voxel and seed-to-seed analyses were employed to examine changes in FC between the two groups. The hippocampal subfields, including the bilateral dentate gyrus (DG), cornu ammonis (CA), entorhinal cortex (EC), subiculum, and hippocampal amygdalar transition area (HATA) were selected as seeds. Additionally, we assessed the relationship between abnormal FC and clinical symptoms.

RESULTS: Seed-to-voxel analysis indicated that, compared to non-RD patients, those with RD exhibited decreased FC between the right DG and right parietal operculum cortex, right HATA and right precuneus, left HATA and left precuneus, left EC and cerebellar vermis 8/-crus 1, and between the left subiculum and left angular gyrus. Conversely, we observed increased FC between the left CA and left lingual gyrus, as well as between the right CA and right fusiform gyrus in RD patients. Furthermore, these variations in FC were significantly correlated with clinical features including the duration of RD and scores on the Hamilton Anxiety Scale and Dizziness Handicap Inventory.

CONCLUSION: BPPV patients with RD exhibited altered FC between hippocampal subfields and brain regions associated with spatial orientation and navigation, vestibular and visual processing, and emotional regulation. These findings offer novel insights into the pathophysiological mechanisms in BPPV patients with RD following successful CRP.

PMID:39690894 | DOI:10.1111/cns.70175

Functional Segregation-Integration Preference Configures the Cognitive Decline Against Cerebral Small Vessel Disease: An MRI Study

Wed, 12/18/2024 - 19:00

CNS Neurosci Ther. 2024 Dec;30(12):e70162. doi: 10.1111/cns.70162.

ABSTRACT

INTRODUCTION: Cerebral small vessel disease (CSVD) is highly prevalent in elder individuals, and its variable cognitive outcomes indicate some cognitive reserve mechanisms. Contribution from functional network features is still unclear. Here we explore how functional segregation-integration preference influences the cognitive changes against CSVD.

MATERIALS AND METHODS: A total of, 271 CSVD patients were included, all underwent MRI scans including routine and resting-state functional MRI (rs-fMRI). Hierarchical balance index (HB) was obtained from the rs-fMRI connectivity using eigenmode-based approach. Individuals were classified into segregated and integrated groups according to negative and positive HB. A composite CSVD lesion score was calculated from imaging findings. Global and five specific cognitive functions were assessed.

RESULTS: Hierarchical regression analysis revealed negative contribution from lesion load to global and all cognitive domains (β = -0.22~-0.35, ∆R2 = 0.046~0.112, all p < 0.001). Inclusion of HB did not show significant contribution (all p > 0.05), but interaction between HB and lesion score was significantly associated with global (β = -0.27, ∆R2 = 0.013, p = 0.034) and execution score (β = -0.34, ∆R2 = 0.023, p = 0.002). Integrated patients show significant better global cognitive (23.9 ± 3.9 vs. 25.5 ± 3.1, p = 0.044) and executive ability (0.235 ± 0.678 vs. 0.535 ± 0.688, p = 0.049) at mild damage stage, visuospatial (-0.001 ± 0.804 vs. 0.379 ± 0.249, p = 0.034) and language ability (-0.133 ± 0.849 vs. 0.218 ± 0.704, p = 0.037) at moderate damage stage. Cross-overs of cognitive scores were observed. Significant better execution (-0.277 ± 0.717 vs. -0.675 ± 0.883, p = 0.027) was found in severe damage stage for segregated patients.

CONCLUSION: Thus, we concluded that integrated network contributes to cognitive resilience in mild and moderate but not in severe damage stages.

PMID:39690801 | DOI:10.1111/cns.70162

Effective connectivity of default mode network subsystems and automatic smoking behaviour among males

Tue, 12/17/2024 - 19:00

J Psychiatry Neurosci. 2024 Dec 17;49(6):E429-E439. doi: 10.1503/jpn.240058. Print 2024 Nov-Dec.

ABSTRACT

BACKGROUND: The default mode network (DMN) is not a single system, but rather is composed of smaller and distinct functional subsystems that interact with each other. The functional relevance of these subsystems in tobacco use disorder (TUD) and the neurobiological features associated with smoking motivation are still unclear; thus, we sought to assess causal or direct connectivity alterations within 3 subsystems of the DMN among people with TUD.

METHODS: We recruited male smokers and nonsmokers. We conducted resting-state functional magnetic resonance imaging (rs-fMRI) and collected ratings on smoking-related clinical scales. We applied dynamic causal modelling (DCM) to rs-fMRI to characterize changes of effective connectivity in TUD from 3 DMN subsystems, including the midline core network (i.e., the posterior cingulate cortex and the anterior medial prefrontal cortex [PCC-aMPFC] core DMN), the medial temporal subsystem (MTL-DMN), and the dorsal medial prefrontal cortex subsystem (dMPFC-DMN). We used leave-one-out cross-validation to investigate whether the neural response could predict smoking reasons, evaluated using the Russell Reason for Smoking Questionnaire).

RESULTS: We recruited 88 smokers and 54 nonsmokers. Among people with TUD, the parahippocampal cortex (PHC) region showed enhanced self-connection, which was associated with the severity of TUD after nighttime withdrawal. Compared with nonsmokers, people with TUD displayed significant increased effective connectivity within the dMPFC-DMN, and decreased effective connectivity from the dMPFC-DMN to the PCC-aMPFC core DMN. Moreover, decreased effective connectivity from the lateral temporal cortex to the dMPFC could predict the smoking reason related to automatic behaviour.

LIMITATIONS: Although we found aberrance in causal connections in DMN subsystems among people with TUD, our cross-sectional study could not be used to investigate changes in effective connectivity over time and their relationship with clinical features.

CONCLUSION: This study emphasized the aberrant causal connections of different functional subsystems of the DMN in TUD and revealed the neural correlates of automatic smoking behaviours. These findings suggested DMN subsystem-derived indicators could be a potential biomarker for TUD and could be used to identify the heterogeneity in motivation for smoking behaviour.

PMID:39689937 | DOI:10.1503/jpn.240058

Contrastive machine learning reveals species -shared and -specific brain functional architecture

Tue, 12/17/2024 - 19:00

Med Image Anal. 2024 Dec 12;101:103431. doi: 10.1016/j.media.2024.103431. Online ahead of print.

ABSTRACT

A deep comparative analysis of brain functional connectome across species in primates has the potential to yield valuable insights for both scientific and clinical applications. However, the interspecies commonality and differences are inherently entangled with each other and with other irrelevant factors. Here we develop a novel contrastive machine learning method, called shared-unique variation autoencoder (SU-VAE), to allow disentanglement of the species-shared and species-specific functional connectome variation between macaque and human brains on large-scale resting-state fMRI datasets. The method was validated by confirming that human-specific features are differentially related to cognitive scores, while features shared with macaque better capture sensorimotor ones. The projection of disentangled connectomes to the cortex revealed a gradient that reflected species divergence. In contrast to macaque, the introduction of human-specific connectomes to the shared ones enhanced network efficiency. We identified genes enriched on 'axon guidance' that could be related to the human-specific connectomes. The code contains the model and analysis can be found in https://github.com/BBBBrain/SU-VAE.

PMID:39689450 | DOI:10.1016/j.media.2024.103431