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Postherpetic neuralgia (PHN) manifests as persistent chronic pain that emerges after a herpes zoster outbreak and greatly diminishes quality of life. Unfortunately, its treatment efficacy has remained elusive, with many therapeutic efforts yielding less than satisfactory results. The research to discern risk factors predicting the onset, trajectory, and prognosis of PHN has been extensive. However, these risk factors often present as nonspecific and diverse, indicating the need for more reliable, measurable, and objective detection methods. The exploration of potential biological markers, including hematological indices, pathological insights, and supportive tests, is increasing. This review highlights potential biomarkers that are instrumental for the diagnosis, management, and prognosis of PHN while also delving deeper into its genesis. Drawing from prior research, aspects such as immune responsiveness, neuronal injury, genetic makeup, cellular metabolism, and pain signal modulation have emerged as prospective biomarkers. The immune spectrum spans various cell subtypes, with an emphasis on T cells, interferons, interleukins, and other related cytokines. Studies on nerve injury are directed toward pain-related proteins and the density and health of epidermal nerve fibers. On the genetic and metabolic fronts, the focus lies in the detection of predisposition genes, atypical protein manifestations, and energy-processing dynamics, with a keen interest in vitamin metabolism. Tools such as functional magnetic resonance imaging, electromyography, and infrared imaging have come to the forefront in the pain signaling domain. This review compiles the evidence, potential clinical implications, and challenges associated with these promising biomarkers, paving the way for innovative strategies for predicting, diagnosing, and addressing PHN. [ABSTRACT FROM AUTHOR]

Dynamic resting state functional connectivity (RSFC) characterizes time-varying fluctuations of functional brain network activity. While many studies have investigated static functional connectivity, it has been unclear whether features of dynamic functional connectivity are associated with neurodegenerative diseases. Popular sliding-window and clustering methods for extracting dynamic RSFC have various limitations that prevent extracting reliable features to address this question. Here, we use a novel and robust time-varying dynamic network (TVDN) approach to extract the dynamic RSFC features from high resolution magnetoencephalography (MEG) data of participants with Alzheimer's disease (AD) and matched controls. The TVDN algorithm automatically and adaptively learns the low-dimensional spatiotemporal manifold of dynamic RSFC and detects dynamic state transitions in data. We show that amongst all the functional features we investigated, the dynamic manifold features are the most predictive of AD. These include: the temporal complexity of the brain network, given by the number of state transitions and their dwell times, and the spatial complexity of the brain network, given by the number of eigenmodes. These dynamic features have higher sensitivity and specificity in distinguishing AD from healthy subjects than the existing benchmarks do. Intriguingly, we found that AD patients generally have higher spatial complexity but lower temporal complexity compared with healthy controls. We also show that graph theoretic metrics of dynamic component of TVDN are significantly different in AD versus controls, while static graph metrics are not statistically different. These results indicate that dynamic RSFC features are impacted in neurodegenerative disease like Alzheimer's disease, and may be crucial to understanding the pathophysiological trajectory of these diseases.

Abstract Postherpetic neuralgia (PHN) manifests as persistent chronic pain that emerges after a herpes zoster outbreak and greatly diminishes quality of life. Unfortunately, its treatment efficacy has remained elusive, with many therapeutic efforts yielding less than satisfactory results. The research to discern risk factors predicting the onset, trajectory, and prognosis of PHN has been extensive. However, these risk factors often present as nonspecific and diverse, indicating the need for more reliable, measurable, and objective detection methods. The exploration of potential biological markers, including hematological indices, pathological insights, and supportive tests, is increasing. This review highlights potential biomarkers that are instrumental for the diagnosis, management, and prognosis of PHN while also delving deeper into its genesis. Drawing from prior research, aspects such as immune responsiveness, neuronal injury, genetic makeup, cellular metabolism, and pain signal modulation have emerged as prospective biomarkers. The immune spectrum spans various cell subtypes, with an emphasis on T cells, interferons, interleukins, and other related cytokines. Studies on nerve injury are directed toward pain-related proteins and the density and health of epidermal nerve fibers. On the genetic and metabolic fronts, the focus lies in the detection of predisposition genes, atypical protein manifestations, and energy-processing dynamics, with a keen interest in vitamin metabolism. Tools such as functional magnetic resonance imaging, electromyography, and infrared imaging have come to the forefront in the pain signaling domain. This review compiles the evidence, potential clinical implications, and challenges associated with these promising biomarkers, paving the way for innovative strategies for predicting, diagnosing, and addressing PHN.

Abstract Recent research shows that emotional facial expressions impact behavioral responses only when their valence is relevant to the task. Under such conditions, threatening faces delay attentional disengagement, resulting in slower reaction times and increased omission errors compared to happy faces. To investigate the neural underpinnings of this phenomenon, we used functional magnetic resonance imaging to record the brain activity of 23 healthy participants while they completed two versions of the go/no-go task. In the emotion task (ET), participants responded to emotional expressions (fearful or happy faces) and refrained from responding to neutral faces. In the gender task (GT), the same images were displayed, but participants had to respond based on the posers’ gender. Our results confirmed previous behavioral findings and revealed a network of brain regions (including the angular gyrus, the ventral precuneus, the left posterior cingulate cortex, the right anterior superior frontal gyrus, and two face-responsive regions) displaying distinct activation patterns for the same facial emotional expressions in the ET compared to the GT. We propose that this network integrates internal representations of task rules with sensory characteristics of facial expressions to evaluate emotional stimuli and exert top-down control, guiding goal-directed actions according to the context.

Dynamic resting state functional connectivity (RSFC) characterizes fluctuations that occur over time in functional brain networks. Existing methods to extract dynamic RSFCs, such as sliding-window and clustering methods that are inherently non-adaptive, have various limitations such as high-dimensionality, an inability to reconstruct brain signals, insufficiency of data for reliable estimation, insensitivity to rapid changes in dynamics, and a lack of generalizability across multiply functional imaging modalities. To overcome these deficiencies, we develop a novel and unifying time-varying dynamic network (TVDN) framework for examining dynamic resting state functional connectivity. TVDN includes a generative model that describes the relation between a low-dimensional dynamic RSFC and the brain signals, and an inference algorithm that automatically and adaptively learns the low-dimensional manifold of dynamic RSFC and detects dynamic state transitions in data. TVDN is applicable to multiple modalities of functional neuroimaging such as fMRI and MEG/EEG. The estimated low-dimensional dynamic RSFCs manifold directly links to the frequency content of brain signals. Hence we can evaluate TVDN performance by examining whether learnt features can reconstruct observed brain signals. We conduct comprehensive simulations to evaluate TVDN under hypothetical settings. We then demonstrate the application of TVDN with real fMRI and MEG data, and compare the results with existing benchmarks. Results demonstrate that TVDN is able to correctly capture the dynamics of brain activity and more robustly detect brain state switching both in resting state fMRI and MEG data.

Background: Currently, there is no gold standard for diagnosing minimal hepatic encephalopathy (MHE). Diffusion-weighted imaging (DWI) can non-invasively evaluate changes in brain volume and damage to brain function. Objectives: The current study aims to evaluate changes in cerebral blood flow and brain function as predictors of MHE using DWI. Patients and Methods: Participants from October 2016 to October 2021 were scanned using a 3.0T superconductive MR machine (Discovery MR750, GE Medical Systems). Intravoxel incoherent motion DWI (MM-DWI) images of 30 patients with MHE and 30 controls were analyzed in a retrospective case-control study. The parameters of mono-, bi-, and stretched exponential models of the regions of interest, delineated from cerebral perfusion pseudo-color maps, were measured. The significance of the differences in parameter values between the groups was assessed using an independent t-test. Furthermore, the receiver operating characteristic curve was used to analyze the predictive efficiency of each parameter for MHE. Results: Compared to the control group, the distributed diffusion coefficient (DDC) of the bilateral frontal lobe, temporal lobe, occipital lobe, parietal lobe, cingulate gyrus, and thalamus in the MHE group was statistically different (P < 0.05). The pseudo-diffusion coefficient (D*) and DDC demonstrated good diagnostic efficacy for MHE. D* had the highest area under the curve (AUC) in the bilateral parietal lobe, bilateral cingulate gyrus, and left occipital lobe. In contrast, DDC had the highest AUC in the right occipital and bilateral temporal lobes. Conclusion: Intravoxel incoherent motion DWI is an imaging method that can detect MHE. In addition, D* and DDC are better diagnostic parameters for screening MHE. Intravoxel incoherent motion DWI will be helpful in uncovering deeper intrinsic pathophysiological mechanisms and improving predictive efficiency. [ABSTRACT FROM AUTHOR]

Noisy thoughts or perceptions are characteristics of psychosis (PSY) and, they are deeply related to source monitoring (SM) — the ability to discriminate the origin of internal/external experiences. This MOOSE, PRISMA-compliant meta-analysis compared SM performances in PSY compared to healthy controls (HC) focusing on signal-to-noise discrimination in order to: i) test whether neuroimaging procedures (fMRI/EEG) might be a group-specific source of noise for SM; ii) compare error- and accuracy-based indexes; iii) to meta-analyze signal-detection measures (i.e., discrimination index and response bias); iv) to determine the best index capturing SM deficits in psychosis. We conducted a 3-level meta-analysis for each aim to estimate pooled effect-sizes (Cohen's d). SM type, source discrimination and stimulus modality were used as meta-regressors. Heterogeneity (I2), publication bias (Egger's test) and multiple comparisons (Bonferroni correction) were considered. Sixteen neuroimaging, 44 error/accuracy-based behavioral and 7 signal-detection trials were included (2297 PSY, age range = 18.78–52.6; 1745 HC, age range = 21.1–53.3). The noise generated by neuroimaging procedures slightly influenced error, but not accuracy. Accuracy-based (d = -0.83), but not error-based, indexes showed significant and large SM impairments in PSY compared to HC. Overall SM performance differences between PSY and HC were larger in discrimination index (d = -0.65) and accuracy (d = -0.61), followed by response bias (d = −0.59, ns) and error-based (d = 0.35) indexes. Although both accuracy and discrimination indexes differentiate patients with PSY from HC, discrimination index is more reliable and may better capture the bi-directional nature of the internal/external source confusion. [ABSTRACT FROM AUTHOR]

Purposes For the purpose of predicting the functional brain network and providing reference for studying the evolution patterns of functional brain network, a model of sequential brain function network based on Generative Adversarial Networks has been built. Methods The topological and temporal characteristics of brain function network are captured through Graph Convolutional Network and long-term and short-term memory network separately, and through feature fusion in the whole connection layer to realize the prediction of functional brain network. Findings The accuracy of network prediction with AUC and MAP indicators has been tested. The experimental results show that the AUC and MAP of the proposed method are 0.95 and 0.92, respectively on two different resting state fMRI data. Compared with other link prediction models, this method can achieve better prediction effect on functional brain network. The accurate prediction of brain function network owns a wide application prospect in the field of brain network decoding and brain computer interface.

Dynamic resting state functional connectivity (RSFC) characterizes time-varying fluctuations of functional brain network activity. While many studies have investigated static functional connectivity, it has been unclear whether features of dynamic functional connectivity are associated with neurodegenerative diseases. Popular sliding-window and clustering methods for extracting dynamic RSFC have various limitations that prevent extracting reliable features to address this question. Here, we use a novel and robust time-varying dynamic network (TVDN) approach to extract the dynamic RSFC features from high resolution magnetoencephalography (MEG) data of participants with Alzheimer’s disease (AD) and matched controls. The TVDN algorithm automatically and adaptively learns the low-dimensional spatiotemporal manifold of dynamic RSFC and detects dynamic state transitions in data. We show that amongst all the functional features we investigated, the dynamic manifold features are the most predictive of AD. These include: the temporal complexity of the brain network, given by the number of state transitions and their dwell times, and the spatial complexity of the brain network, given by the number of eigenmodes. These dynamic features have higher sensitivity and specificity in distinguishing AD from healthy subjects than the existing benchmarks do. Intriguingly, we found that AD patients generally have higher spatial complexity but lower temporal complexity compared with healthy controls. We also show that graph theoretic metrics of dynamic component of TVDN are significantly different in AD versus controls, while static graph metrics are not statistically different. These results indicate that dynamic RSFC features are impacted in neurodegenerative disease like Alzheimer’s disease, and may be crucial to understanding the pathophysiological trajectory of these diseases.

Glaucoma is the leading cause of blindness worldwide. It is classically associated with structural and functional changes in the optic nerve head and retinal nerve fiber layer, but the damage is not limited to the eye. The involvement of the central visual pathways and disruption of brain network organization have been reported using advanced neuroimaging techniques. The brain structural changes at the level of the areas implied in processing visual information could justify the discrepancy between signs and symptoms and underlie the analogy of this disease with neurodegenerative dementias, such as Alzheimer's disease, and with the complex group of pathologies commonly referred to as "disconnection syndromes." This review aims to summarize the current state of the art on the use of advanced neuroimaging techniques in glaucoma and Alzheimer's disease, highlighting the emerging biomarkers shared by both diseases. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to examine the neural mechanisms underlying the decision-making process of off-ball movements among high-level football players and ordinary college students, as well as the effect of long-term skill training on these neural mechanisms using functional magnetic resonance imaging (fMRI). Methods: The study recruited 20 professional college football players as the expert group (EG) and 20 novice football players with no background in sportsrelated disciplines as the novice group (NG). The participants performed the motor video observation and button-decision-making tasks, and fMRI data were acquired, pre-processed, and analyzed. Results: During the decision-making process regarding running without the ball, whole-brain fMRI scans were conducted on both the EG and NG. The analysis of these scans revealed noteworthy disparities in brain activity between the two groups. These disparities were observed during tasks involving motor video observation and button-based decision-making. According to the behavioral data, the EG made more correct decisions than the NG (p < 0.05); however, there was no significant difference in their reaction speed (p > 0.05). During video observation, both the EG and NG exhibited simultaneous activation in the frontoparietal cognitive area, primary somatosensory cortex, visual cortex, and insula. However, there were no significant differences between the two groups in terms of activated brain regions [false discovery rate (FDR) corrected to p < 0.05]. Regarding button-press decisions, the areas of the brain that were commonly activated in both the NG and EG were primarily located in the frontoparietal cognitive area, temporal cortex, and cuneus cortex. Notably, the left superior temporal gyrus, left inferior temporal gyrus, and left middle occipital gyrus exhibited greater activation in the NG compared to those in the EG (FDR corrected to p < 0.05). Conclusion: This study demonstrated that during motor video observation, the EG's sports experience and professional knowledge can help them achieve better visual information processing strategies in specific areas of sports. During button decision-making, the EG was more economical, whereas the NG required more brain function activity to process visual information, confirming the "neural efficiency" hypothesis. [ABSTRACT FROM AUTHOR]

This paper developed a comprehensive magnetic resonance imaging (MRI)-compatible electrophysiological (EP) acquisition system, which can acquire various physiological electrical signals, including electrocardiography (ECG), electromyography (EMG), electroencephalography (EEG) and electrocorticogram (ECoG), and EP recording combined with multimodal stimulation. The system is designed to be compatible with the 7-Tesla (7T) ultra-high field MRI environment, providing convenience for neuroscience and physiological research. To achieve MRI compatibility, the device uses magnetically compatible materials and shielding measures on the hardware and algorithm processing on the software side. Different filtering algorithms are adopted for different signals to suppress all kinds of interference in the MRI environment. The system can allow input signals up to ±0.225 V and channels up to 256. The equipment has been tested and proven to be able to collect a variety of physiological electrical signals effectively. When scanned under the condition of a 7T high-intensity magnetic field, the system does not generate obvious heating and can meet the safety requirements of MRI and EEG acquisition requirements. Moreover, an algorithm is designed and improved to efficiently and automatically remove the gradient artifact (GA) noise generated by MRI, which is a thousand-fold gradient artifact. Overall, this work proposes a complete, portable, MRI-compatible system that can collect a variety of physiological electrical signals and integrate more efficient GA removal algorithms. [ABSTRACT FROM AUTHOR]

Myofascial pain syndrome is the most common cause of TMD, characterised by trigger points of skeletal muscles in the masticatory region. Patients with myofascial pain suffer from orofacial pain and headaches. Parafunctional activity such as unconscious teeth clenching predisposes a higher possibility of developing myofascial pain. We report the results of a prospective study of 10 patients with a myofascial pain diagnosis related to TMD who underwent treatment with passive aligners and biofeedback exercise. All patients underwent pain assessment (visual analogic scale and muscular palpation test), measurement of masseters thickness with Dolphin Imaging Software, nuclear magnetic resonance of the temporomandibular joint, and functional nuclear magnetic resonance of the brain before and after gnathological treatment. The same patients underwent pain assessment (VAS and palpation test) for the entire duration of their treatment. This study aimed to assess if the results obtained with the therapy were repeatable using functional magnetic resonance imaging. This enabled us to correlate a subjective datum (pain) to an objective one (variation in the functional connectivity of the networks correlated to pain perception). According to the pain assessment, the treatment considerably reduced the pain in 9 out of 10 patients. Furthermore, the functional nuclear magnetic resonance of the brain showed similar modifications in the cerebral pain and default mode networks in these nine patients. The change in the masseter muscle dimensions was not correlated with the modification of pain. Statistical analysis was performed to evaluate the effects of treatment on VAS and trigger point stimulation and on the length and width of the masseter muscle. Linear regression analysis was used to assess a correlation between the modification of the masseter muscle dimension and the amendment of VAS. A paired t-test was used to evaluate statistically significant differences in the connectivity of brain areas of the DMN and the pain network. Our results suggest that the proper treatment of myofascial pain can reduce pain and consistently modify the functional activation of the cerebral pain and default mode networks. Overall, the treatment was repeatable because brain network changes were homogeneous in all patients and did not relate to the intracapsular TMJ condition but only to pain symptoms. [ABSTRACT FROM AUTHOR]

Objective To study the efficacy of modified Wuqinxi on gait and balance dysfunction in elderly stroke patients and the brain mechanism based on fMRI. Methods The 60 stroke patients treated in our hospital from September 2021 to January 2023 were selected as the study subjects, and were randomly divided into 28 control groups and 32 experimental groups. The control group used conventional rehabilitation treatment, and the experimental group improved Wuqinxi by video practice based on the control group. The fMRI scan of two brain activation area was used to evaluate the cerebral hemodynamic index, immune function index and gait parameters, and the Berg Scale Assessment（berg balance scale, BBS）. Results After treatment, the average cerebral artery blood flow rate（Vm）, the average blood flow rate（Qm）, immunoglobulin G（lmmunoglobin G, IgG）, and Immunoglobulin A（lmmunoglobin）in the experimental group compared with the control group. A, IgA）, immunoglobulin M（lmmunoglobin M, IgM）levels increase, vascular resistance index（RI）level decline, statistical difference （P < 0.05）, the BBS score increase, statistical difference（P < 0.05）, the step frequency, stride speed increase, gait cycle decline, statistical difference（P < 0.05）;the stride frequency, stride amplitude and stride speed of the experimental group decreased, with the statistical difference（P < 0.05）;the range of brain activation areas and brain function in the experimental group were greater than those in the control group. Conclusion The modified Wuqinxi treatment of elderly stroke patients can improve their immune ability, balance ability and gait. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea syndrome (OSAS) is considered a major public health issue due to its high prevalence and severe consequences. Several published studies have revealed that electro-acupuncture may relieve OSAS symptoms. However, the mechanism of electro-acupuncture in the treatment of patients with OSAS remains unclear. We evaluated the efficacy and mechanism of electro-acupuncture in the treatment of patients with OSAS. This was a two-group parallel randomized controlled trial. Sixty patients with OSAS will be randomly divided into an electro-acupuncture or shallow acupuncture group in a proportion of 1:1, and the patients will be administered 36 sessions of electro/shallow acupuncture treatment (three times a week for 12 weeks, 20 min for each session). The Epworth Sleepiness Scale (ESS) will be used as the primary outcome. Secondary outcomes will include polysomnography (PSG), sleep quality, emotional state, and cognitive function. In addition, patients will receive neuroimaging scanning before and after the entire acupuncture treatment to evaluate neuroplasticity changes, including gray matter density, white matter integrity, and functional connections. We believe that the use of electro-acupuncture will be more effective in patients with mild to moderate OSAS and that the cognitive and emotional status of patients will improve after acupuncture treatment. In addition, we aim to clarify which brain areas can be altered by acupuncture in patients with OSAS. This randomized clinical trial aims to explore the curative effect and central mechanism of acupuncture treatment for OSAS. We will explore gray matter density, white matter integrity, and functional connections of the brain using fMRI technology. The results of this study will be significant to the guidelines for clinical OSAS treatment. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is an incurable neurodegenerative disease and the most frequently diagnosed type of dementia, characterized by (1) perturbed cerebral perfusion, vasculature, and cortical metabolism; (2) induced proinflammatory processes; and (3) the aggregation of amyloid beta and hyperphosphorylated Tau proteins. Subclinical AD changes are commonly detectable by using radiological and nuclear neuroimaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). Furthermore, other valuable modalities exist (in particular, structural volumetric, diffusion, perfusion, functional, and metabolic magnetic resonance methods) that can advance the diagnostic algorithm of AD and our understanding of its pathogenesis. Recently, new insights into AD pathoetiology revealed that deranged insulin homeostasis in the brain may play a role in the onset and progression of the disease. AD-related brain insulin resistance is closely linked to systemic insulin homeostasis disorders caused by pancreas and/or liver dysfunction. Indeed, in recent studies, linkages between the development and onset of AD and the liver and/or pancreas have been established. Aside from standard radiological and nuclear neuroimaging methods and clinically fewer common methods of magnetic resonance, this article also discusses the use of new suggestive non-neuronal imaging modalities to assess AD-associated structural changes in the liver and pancreas. Studying these changes might be of great clinical importance because of their possible involvement in AD pathogenesis during the prodromal phase of the disease. [ABSTRACT FROM AUTHOR]

The human middle-temporal region MT+ is highly specialized in processing visual motion. However, recent studies have shown that this region is modulated by extraretinal signals, suggesting a possible involvement in processing motion information also from non-visual modalities. Here, we used functional MRI data to investigate the influence of retinal and extraretinal signals on MT+ in a large sample of subjects. Moreover, we used resting-state functional MRI to assess how the subdivisions of MT+ (i.e., MST, FST, MT, and V4t) are functionally connected. We first compared responses in MST, FST, MT, and V4t to coherent vs. random visual motion. We found that only MST and FST were positively activated by coherent motion. Furthermore, regional analyses revealed that MST and FST were positively activated by leg, but not arm, movements, while MT and V4t were deactivated by arm, but not leg, movements. Taken together, regional analyses revealed a visuomotor role for the anterior areas MST and FST and a pure visual role for the anterior areas MT and V4t. These findings were mirrored by the pattern of functional connections between these areas and the rest of the brain. Visual and visuomotor regions showed distinct patterns of functional connectivity, with the latter preferentially connected with the somatosensory and motor areas representing leg and foot. Overall, these findings reveal a functional sensitivity for coherent visual motion and lower-limb movements in MST and FST, suggesting their possible involvement in integrating sensory and motor information to perform locomotion. [ABSTRACT FROM AUTHOR]

Purpose. Cognitive impairment (CI) is very common in patients with chronic obstructive pulmonary disease (COPD). Cerebral structural and functional abnormalities have been reported in cognitively impaired patients with COPD, and the neurovascular coupling changes are rarely investigated. To address this issue, arterial spin labeling (ASL) and resting-state blood oxygenation level dependent (BOLD) fMRI techniques were used to determine whether any neurovascular changes in COPD patients. Methods. Forty-five stable COPD patients and forty gender- and age-matched healthy controls were recruited. Furthermore, resting-state BOLD fMRI and ASL were acquired to calculate degree centrality (DC) and cerebral blood flow (CBF) respectively. The CBF-DC coupling and CBF/DC ratio were compared between the two groups. Results. COPD patients showed abnormal CBF, DC and CBF/DC ratio in several regions. Moreover, lower CBF/DC ratio in the left lingual gyrus negatively correlated with naming scores, lower CBF/DC ratio in medial frontal cortex/temporal gyrus positively correlated with the Montreal Cognitive Assessment (MoCA), visuospatial/executive and delayed recall scores. Conclusion. These findings may provide new potential insights into neuropathogenesis of cognition decline in stable COPD patients. [ABSTRACT FROM AUTHOR]

Glaucoma is the leading cause of blindness worldwide. It is classically associated with structural and functional changes in the optic nerve head and retinal nerve fiber layer, but the damage is not limited to the eye. The involvement of the central visual pathways and disruption of brain network organization have been reported using advanced neuroimaging techniques. The brain structural changes at the level of the areas implied in processing visual information could justify the discrepancy between signs and symptoms and underlie the analogy of this disease with neurodegenerative dementias, such as Alzheimer’s disease, and with the complex group of pathologies commonly referred to as “disconnection syndromes.” This review aims to summarize the current state of the art on the use of advanced neuroimaging techniques in glaucoma and Alzheimer’s disease, highlighting the emerging biomarkers shared by both diseases.

Regional homogeneity (ReHo) was used to evaluate the changes of brain function and the relationship with cognitive function in perimenopausal women. The cross-sectional study recruited 25 perimenopausal women and 25 postmenopausal women who underwent sex hormone level measurements, clinical and neuropsychological assessments, and magnetic resonance imaging (MRI) scans. ReHo was measured based on the resting-state functional MRI (rs-fMRI) data and the differences in ReHo between the perimenopausal and postmenopausal groups were compared. Gray matter volume (GMV) values of brain regions with differences (region of interest [ROI]) in ReHo were extracted and the differences of GMV between the two groups were compared. We analyzed the correlations of the ReHo and GMV values of these ROIs with the results of sex hormone levels, clinical and neuropsychological assessments in the two groups. ReHo values in the left lingual gyrus and the right precentral gyrus increased in perimenopause, whereas ReHo values in the left inferior temporal gyrus and bilateral putamen decreased. Correlation analysis showed that the ReHo values of the left inferior temporal gyrus positively correlated with the reaction time of the Stroop color word test in perimenopausal women. Changes in abnormal patterns of the ReHo in perimenopausal women affect cognitive function. These changes in brain function may provide more insights and information on the neural mechanisms of cognitive dysfunction in perimenopausal women. [ABSTRACT FROM AUTHOR]

Background: Previous studies of hippocampal function and volume related to episodic memory deficits in patients with amnestic mild cognitive impairment (aMCI) have produced mixed results including increased or decreased activity and volume. However, most of them have not included biomarkers, such as amyloid-β (Aβ) deposition which is the hallmark for early identification of the Alzheimer's disease continuum.Objective: We investigated the role of Aβ deposition, functional hippocampal activity and structural volume in aMCI patients and healthy elderly controls (HC) using a new functional MRI (fMRI) ecological episodic memory task.Methods: Forty-six older adults were included, among them Aβ PET PIB positive (PIB+) aMCI (N = 17), Aβ PET PIB negative (PIB-) aMCI (N = 15), and HC (N = 14). Hippocampal volume and function were analyzed using Freesurfer v6.0 and FSL for news headlines episodic memory fMRI task, and logistic regression for group classification in conjunction with episodic memory task and traditional neuropsychological tests.Results: The aMCI PIB+ and PIB-patients showed significantly worse performance in relation to HC in most traditional neuropsychological tests and within group difference only on story recall and the ecological episodic memory fMRI task delayed recall. The classification model reached a significant accuracy (78%) and the classification pattern characterizing the PIB+ included decreased left hippocampal function and volume, increased right hippocampal function and volume, and worse episodic memory performance differing from PIB-which showed increased left hippocampus volume.Conclusion: The main findings showed differential neural correlates, hippocampal volume and function during episodic memory in aMCI patients with the presence of Aβ deposition. [ABSTRACT FROM AUTHOR]

Integration of proprioceptive signals from the various effectors with visual feedback of self-motion from the retina is necessary for whole-body movement and locomotion. Here, we tested whether the human visual motion areas involved in processing optic flow signals simulating self-motion are also activated by goal-directed movements (as saccades or pointing) performed with different effectors (eye, hand, and foot), suggesting a role in visually guiding movements through the external environment. To achieve this aim, we used a combined approach of task-evoked activity and effective connectivity (PsychoPhysiological Interaction, PPI) by fMRI. We localized a set of six egomotion-responsive visual areas through the flow field stimulus and distinguished them into visual (pIPS/V3A, V6+ , IPSmot/VIP) and visuomotor (pCi, CSv, PIC) areas according to recent literature. We tested their response to a visuomotor task implying spatially directed delayed eye, hand, and foot movements. We observed a posterior-to-anterior gradient of preference for eye-to-foot movements, with posterior (visual) regions showing a preference for saccades, and anterior (visuomotor) regions showing a preference for foot pointing. No region showed a clear preference for hand pointing. Effective connectivity analysis showed that visual areas were more connected to each other with respect to the visuomotor areas, particularly during saccades. We suggest that visual and visuomotor egomotion regions can play different roles within a network that integrates sensory–motor signals with the aim of guiding movements in the external environment. [ABSTRACT FROM AUTHOR]

Background/Aim: Misophonia is a disorder characterized by reduced tolerance to specific sounds or stimuli known as "triggers," which tend to evoke negative emotional, physiological, and behavioral responses. In this study, we aimed to better characterize participants with misophonia through the evaluation of the response of the autonomic nervous system to "trigger sounds," a psychometric assessment, and the analysis of the neurological pathways. Materials and methods: Participants included 11 adults presenting with misophonic disturbance and 44 sex-matched healthy controls (HCs). Following recently proposed diagnostic criteria, the participants listened to six "trigger sounds" and a "general annoyance" sound (baby crying) during a series of physiological tests. The effects were examined through functional magnetic resonance imaging (fMRI), the analysis of heart rate variability (HRV), and of galvanic skin conductance (GSC). The fMRI was performed on a 3T Scanner. The HRV was obtained through the analysis of electrocardiogram, whereas the GSC was examined through the positioning of silver-chloride electrodes on fingers. Furthermore, the psychometric assessment included questionnaires focused on misophonia, psychopathology, resilience, anger, and motivation. Results: Participants with misophonia showed patterns of increased sympathetic activation in response to trigger sounds and a general annoyance sound, the low frequency (LF) component of HRV, the sympathetic index, and the number of significant GSC over the threshold, where the amplitude/phasic response of GSC was higher. The fMRI analysis provided evidence for the activation of the temporal cortex, the limbic area, the ventromedial prefrontal/premotor/cingulate cortex, and the cerebellum in participants with misophonia. In addition, the psychometric assessment seemed to differentiate misophonia as a construct independent from general psychopathology. Conclusion: These results suggest the activation of a specific auditoryinsulalimbic pathway at the basis of the sympathetic activation observed in participants with misophonia in response to "trigger and general annoyance sounds." Further studies should disentangle the complex issue of whether misophonia represents a new clinical disorder or a non-pathological condition. These results could help to build diagnostic tests to recognize and better classify this disorder. The relevance of this question goes beyond purely theoretical issues, as in the first case, participants with misophonia should receive a diagnosis and a targeted treatment, while in the second case, they should not. [ABSTRACT FROM AUTHOR]

Recent research shows that emotional facial expressions impact behavioral responses only when their valence is relevant to the task. Under such conditions, threatening faces delay attentional disengagement, resulting in slower reaction times and increased omission errors compared to happy faces. To investigate the neural underpinnings of this phenomenon, we used functional magnetic resonance imaging to record the brain activity of 23 healthy participants while they completed two versions of the go/no-go task. In the emotion task (ET), participants responded to emotional expressions (fearful or happy faces) and refrained from responding to neutral faces. In the gender task (GT), the same images were displayed, but participants had to respond based on the posers' gender. Our results confirmed previous behavioral findings and revealed a network of brain regions (including the angular gyrus, the ventral precuneus, the left posterior cingulate cortex, the right anterior superior frontal gyrus, and two face-responsive regions) displaying distinct activation patterns for the same facial emotional expressions in the ET compared to the GT. We propose that this network integrates internal representations of task rules with sensory characteristics of facial expressions to evaluate emotional stimuli and exert top-down control, guiding goal-directed actions according to the context., (© 2024. The Author(s).)

Background/AimMisophonia is a disorder characterized by reduced tolerance to specific sounds or stimuli known as “triggers,” which tend to evoke negative emotional, physiological, and behavioral responses. In this study, we aimed to better characterize participants with misophonia through the evaluation of the response of the autonomic nervous system to “trigger sounds,” a psychometric assessment, and the analysis of the neurological pathways.Materials and methodsParticipants included 11 adults presenting with misophonic disturbance and 44 sex-matched healthy controls (HCs). Following recently proposed diagnostic criteria, the participants listened to six “trigger sounds” and a “general annoyance” sound (baby crying) during a series of physiological tests. The effects were examined through functional magnetic resonance imaging (fMRI), the analysis of heart rate variability (HRV), and of galvanic skin conductance (GSC). The fMRI was performed on a 3T Scanner. The HRV was obtained through the analysis of electrocardiogram, whereas the GSC was examined through the positioning of silver-chloride electrodes on fingers. Furthermore, the psychometric assessment included questionnaires focused on misophonia, psychopathology, resilience, anger, and motivation.ResultsParticipants with misophonia showed patterns of increased sympathetic activation in response to trigger sounds and a general annoyance sound, the low frequency (LF) component of HRV, the sympathetic index, and the number of significant GSC over the threshold, where the amplitude/phasic response of GSC was higher. The fMRI analysis provided evidence for the activation of the temporal cortex, the limbic area, the ventromedial prefrontal/premotor/cingulate cortex, and the cerebellum in participants with misophonia. In addition, the psychometric assessment seemed to differentiate misophonia as a construct independent from general psychopathology.ConclusionThese results suggest the activation of a specific auditory-insula-limbic pathway at the basis of the sympathetic activation observed in participants with misophonia in response to “trigger and general annoyance sounds.” Further studies should disentangle the complex issue of whether misophonia represents a new clinical disorder or a non-pathological condition. These results could help to build diagnostic tests to recognize and better classify this disorder. The relevance of this question goes beyond purely theoretical issues, as in the first case, participants with misophonia should receive a diagnosis and a targeted treatment, while in the second case, they should not.

Myofascial pain syndrome is the most common cause of TMD, characterised by trigger points of skeletal muscles in the masticatory region. Patients with myofascial pain suffer from orofacial pain and headaches. Parafunctional activity such as unconscious teeth clenching predisposes a higher possibility of developing myofascial pain. We report the results of a prospective study of 10 patients with a myofascial pain diagnosis related to TMD who underwent treatment with passive aligners and biofeedback exercise. All patients underwent pain assessment (visual analogic scale and muscular palpation test), measurement of masseters thickness with Dolphin Imaging Software, nuclear magnetic resonance of the temporomandibular joint, and functional nuclear magnetic resonance of the brain before and after gnathological treatment. The same patients underwent pain assessment (VAS and palpation test) for the entire duration of their treatment. This study aimed to assess if the results obtained with the therapy were repeatable using functional magnetic resonance imaging. This enabled us to correlate a subjective datum (pain) to an objective one (variation in the functional connectivity of the networks correlated to pain perception). According to the pain assessment, the treatment considerably reduced the pain in 9 out of 10 patients. Furthermore, the functional nuclear magnetic resonance of the brain showed similar modifications in the cerebral pain and default mode networks in these nine patients. The change in the masseter muscle dimensions was not correlated with the modification of pain. Statistical analysis was performed to evaluate the effects of treatment on VAS and trigger point stimulation and on the length and width of the masseter muscle. Linear regression analysis was used to assess a correlation between the modification of the masseter muscle dimension and the amendment of VAS. A paired t-test was used to evaluate statistically significant differences in the connectivity of brain areas of the DMN and the pain network. Our results suggest that the proper treatment of myofascial pain can reduce pain and consistently modify the functional activation of the cerebral pain and default mode networks. Overall, the treatment was repeatable because brain network changes were homogeneous in all patients and did not relate to the intracapsular TMJ condition but only to pain symptoms.

Objective: To explore the therapeutic effect and mechanism of low-frequency repetitive transcranial magnetic stimulation on the speech function of patients with non-fluent aphasia after stroke. Methods: According to the inclusion and exclusion criteria, 60 patients with post-stroke non-fluent aphasia were included and randomly divided into treatment group (rTMS group) and sham stimulation group (S-rTMS group). Patients in rTMS group were given low-frequency rTMS + ST training. Patients in the S-rTMS group were given sham low-frequency rTMS + ST training. Once a day, 5 days a week, for a total of 4 weeks. The Western Aphasia Battery and the short-form Token test were used to evaluate the language function of the patients in the two groups before and after treatment. Part of the enrolled patients were subjected to functional magnetic resonance imaging examination, and the morning fasting venous blood of the enrolled patients was drawn before and after treatment to determine the content of BDNF and TNF-α. Results: In the comparison before and after treatment within the group, all dimensions of the WAB scale of the patients in the rTMS group increased significantly. Only two dimensions of the WAB scale of the patients in the S-rTMS group improved significantly after treatment. The results of the short-form Token test showed that patients in the rTMS group improved significantly before and after treatment. The resting state functional magnetic resonance imaging of the two groups of patients before and after treatment showed: the activation of multiple brain regions in the left hemisphere of the rTMS group increased compared with the control group. The serum BDNF content of the patients in the rTMS group was significantly higher than that of the patients in the S-rTMS group after treatment. Conclusion: Low-frequency rTMS combined with conventional speech training can significantly improve the speech function of patients with non-fluent aphasia after stroke. [ABSTRACT FROM AUTHOR]

Dynamic resting state functional connectivity (RSFC) characterizes fluctuations that occur over time in functional brain networks. Existing methods to extract dynamic RSFCs, such as sliding-window and clustering methods that are inherently non-adaptive, have various limitations such as high-dimensionality, an inability to reconstruct brain signals, insufficiency of data for reliable estimation, insensitivity to rapid changes in dynamics, and a lack of generalizability across multiply functional imaging modalities. To overcome these deficiencies, we develop a novel and unifying time-varying dynamic network (TVDN) framework for examining dynamic resting state functional connectivity. TVDN includes a generative model that describes the relation between a low-dimensional dynamic RSFC and the brain signals, and an inference algorithm that automatically and adaptively learns the low-dimensional manifold of dynamic RSFC and detects dynamic state transitions in data. TVDN is applicable to multiple modalities of functional neuroimaging such as fMRI and MEG/EEG. The estimated low-dimensional dynamic RSFCs manifold directly links to the frequency content of brain signals. Hence we can evaluate TVDN performance by examining whether learnt features can reconstruct observed brain signals. We conduct comprehensive simulations to evaluate TVDN under hypothetical settings. We then demonstrate the application of TVDN with real fMRI and MEG data, and compare the results with existing benchmarks. Results demonstrate that TVDN is able to correctly capture the dynamics of brain activity and more robustly detect brain state switching both in resting state fMRI and MEG data.

ObjectiveTo explore the therapeutic effect and mechanism of low-frequency repetitive transcranial magnetic stimulation on the speech function of patients with non-fluent aphasia after stroke.MethodsAccording to the inclusion and exclusion criteria, 60 patients with post-stroke non-fluent aphasia were included and randomly divided into treatment group (rTMS group) and sham stimulation group (S-rTMS group). Patients in rTMS group were given low-frequency rTMS + ST training. Patients in the S-rTMS group were given sham low-frequency rTMS + ST training. Once a day, 5 days a week, for a total of 4 weeks. The Western Aphasia Battery and the short-form Token test were used to evaluate the language function of the patients in the two groups before and after treatment. Part of the enrolled patients were subjected to functional magnetic resonance imaging examination, and the morning fasting venous blood of the enrolled patients was drawn before and after treatment to determine the content of BDNF and TNF-α.ResultsIn the comparison before and after treatment within the group, all dimensions of the WAB scale of the patients in the rTMS group increased significantly. Only two dimensions of the WAB scale of the patients in the S-rTMS group improved significantly after treatment. The results of the short-form Token test showed that patients in the rTMS group improved significantly before and after treatment. The resting state functional magnetic resonance imaging of the two groups of patients before and after treatment showed: the activation of multiple brain regions in the left hemisphere of the rTMS group increased compared with the control group. The serum BDNF content of the patients in the rTMS group was significantly higher than that of the patients in the S-rTMS group after treatment.ConclusionLow-frequency rTMS combined with conventional speech training can significantly improve the speech function of patients with non-fluent aphasia after stroke.

Alzheimer’s disease (AD) is an incurable neurodegenerative disease and the most frequently diagnosed type of dementia, characterized by (1) perturbed cerebral perfusion, vasculature, and cortical metabolism; (2) induced proinflammatory processes; and (3) the aggregation of amyloid beta and hyperphosphorylated Tau proteins. Subclinical AD changes are commonly detectable by using radiological and nuclear neuroimaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). Furthermore, other valuable modalities exist (in particular, structural volumetric, diffusion, perfusion, functional, and metabolic magnetic resonance methods) that can advance the diagnostic algorithm of AD and our understanding of its pathogenesis. Recently, new insights into AD pathoetiology revealed that deranged insulin homeostasis in the brain may play a role in the onset and progression of the disease. AD-related brain insulin resistance is closely linked to systemic insulin homeostasis disorders caused by pancreas and/or liver dysfunction. Indeed, in recent studies, linkages between the development and onset of AD and the liver and/or pancreas have been established. Aside from standard radiological and nuclear neuroimaging methods and clinically fewer common methods of magnetic resonance, this article also discusses the use of new suggestive non-neuronal imaging modalities to assess AD-associated structural changes in the liver and pancreas. Studying these changes might be of great clinical importance because of their possible involvement in AD pathogenesis during the prodromal phase of the disease.

Background: Borderline Personality Disorder (BPD) is a severe and disabling psychiatric syndrome, frequently associated with self-injurious behaviours (SIB). In recent years, functional magnetic resonance imaging (fMRI) investigations have tried to identify alterations associated with SIB amongst BPD patients, in order to better delineate possible neurobiological underpinnings of these manifestations. In this mini-review, we aimed at summarizing fMRI studies exploring patterns of neural activation associated with SIB in BPD patients.Methods: Literature searches on PubMed, Psych-Info and Embase databases were performed for all fMRI studies including adult patients with BPD and SIB undergoing different tasks, including painful or thermic stimulation, affective stimulation through the presentation of picturesor the recollection of personal memories as well as tasks that evaluate sustained attention and impulsivity, and reward processing. Thirteen relevant papers were considered eligible for the present review.Results: Patients with BPD and SIB, compared to HC, showed prefrontal, nucleus accumbens overactivation and amygdala deactivation during pain stimulation. During negative affective stimulation, BPD patients showed a hyperactivation of the amygdala and a hypoactivation of the orbitofrontal cortex (OFC), which was also found to be enhanced during a gambling task and during a recalling of aversive memories. In contrast, during cognitive tasks with negative affective interference, BPD patients showed hypoactivation of OFC, anterior cingulated cortex, and basal ganglia.Limitations: The limited number of studies and the heterogeneity regarding the fMRI tasks employed allowed only suggestive conclusions.Conclusions: The reviewed fMRI studies highlighted that BPD patients with a history of SIB showed altered brain activity, compared to HC, in regions involved in inhibitory cognitive processes and affect regulation, which may in turn, explain the overwhelming emotional experiences eliciting SIB in these patients. [ABSTRACT FROM AUTHOR]

Visual cues coming from the lower visual field (VF) play an important role in the visual guidance of upper and lower limb movements. A recently described region situated in the dorsomedial parietal cortex, area hPEc (Pitzalis et al. in NeuroImage 202:116092, 2019), might have a role in integrating visually derived information with somatomotor signals to guide limb interaction with the environment. In macaque, it has been demonstrated that PEc receives visual information mostly from the lower visual field but, to date, there has been no systematic investigation of VF preference in the newly defined human homologue of macaque area PEc (hPEc). Here we examined the VF preferences of hPEc while participants performed a visuomotor task implying spatially directed delayed eye-, hand- and foot-movements towards different spatial locations within the VF. By analyzing data as a function of the different target locations towards which upcoming movements were planned (and then executed), we observed the presence of asymmetry in the vertical dimension of VF in area hPEc, being this area more strongly activated by limb movements directed towards visual targets located in the lower compared to the upper VF. This result confirms the view, first advanced in macaque monkey, that PEc is involved in processing visual information to guide body interaction with the external environment, including locomotion. We also observed a contralateral dominance for the lower VF preference in the foot selective somatomotor cortex anterior to hPEc. This result might reflect the role of this cortex (which includes areas PE and S-I) in providing highly topographically organized signals, likely useful to achieve an appropriate foot posture during locomotion. [ABSTRACT FROM AUTHOR]

Arterial spin labeling (ASL), a non-invasive MRI technique, has emerged as a valuable tool for researchers that can measure blood flow and related parameters. This review aims to provide a qualitative overview of the technical principles and recent developments in ASL and to highlight its potential clinical applications. A growing literature demonstrates impressive ASL sensitivity to a range of neuropathologies and treatment responses. Despite its potential, challenges persist in the translation of ASL to widespread clinical use, including the lack of standardization and the limited availability of comprehensive training. As experience with ASL continues to grow, the final stage of translation will require moving beyond single site observational studies to multi-site experience and measurement of the added contribution of ASL to patient care and outcomes.

Dynamic resting state functional connectivity (RSFC) characterizes time-varying fluctuations of functional brain network activity. While many studies have investigated static functional connectivity, it has been unclear whether features of dynamic functional connectivity are associated with neurodegenerative diseases. Popular sliding-window and clustering methods for extracting dynamic RSFC have various limitations that prevent extracting reliable features to address this question. Here, we use a novel and robust time-varying dynamic network (TVDN) approach to extract the dynamic RSFC features from high resolution magnetoencephalography (MEG) data of participants with Alzheimer's disease (AD) and matched controls. The TVDN algorithm automatically and adaptively learns the low-dimensional spatiotemporal manifold of dynamic RSFC and detects dynamic state transitions in data. We show that amongst all the functional features we investigated, the dynamic manifold features are the most predictive of AD. These include: the temporal complexity of the brain network, given by the number of state transitions and their dwell times, and the spatial complexity of the brain network, given by the number of eigenmodes. These dynamic features have higher sensitivity and specificity in distinguishing AD from healthy subjects than the existing benchmarks do. Intriguingly, we found that AD patients generally have higher spatial complexity but lower temporal complexity compared with healthy controls. We also show that graph theoretic metrics of dynamic component of TVDN are significantly different in AD versus controls, while static graph metrics are not statistically different. These results indicate that dynamic RSFC features are impacted in neurodegenerative disease like Alzheimer's disease, and may be crucial to understanding the pathophysiological trajectory of these diseases., Competing Interests: Declaration of competing interest None., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: This study aimed to examine the neural mechanisms underlying the decision-making process of off-ball movements among high-level football players and ordinary college students, as well as the effect of long-term skill training on these neural mechanisms using functional magnetic resonance imaging (fMRI)., Methods: The study recruited 20 professional college football players as the expert group (EG) and 20 novice football players with no background in sports-related disciplines as the novice group (NG). The participants performed the motor video observation and button-decision-making tasks, and fMRI data were acquired, pre-processed, and analyzed., Results: During the decision-making process regarding running without the ball, whole-brain fMRI scans were conducted on both the EG and NG. The analysis of these scans revealed noteworthy disparities in brain activity between the two groups. These disparities were observed during tasks involving motor video observation and button-based decision-making. According to the behavioral data, the EG made more correct decisions than the NG ( p < 0.05); however, there was no significant difference in their reaction speed ( p > 0.05). During video observation, both the EG and NG exhibited simultaneous activation in the frontoparietal cognitive area, primary somatosensory cortex, visual cortex, and insula. However, there were no significant differences between the two groups in terms of activated brain regions [false discovery rate (FDR) corrected to p < 0.05]. Regarding button-press decisions, the areas of the brain that were commonly activated in both the NG and EG were primarily located in the frontoparietal cognitive area, temporal cortex, and cuneus cortex. Notably, the left superior temporal gyrus, left inferior temporal gyrus, and left middle occipital gyrus exhibited greater activation in the NG compared to those in the EG (FDR corrected to p < 0.05)., Conclusion: This study demonstrated that during motor video observation, the EG's sports experience and professional knowledge can help them achieve better visual information processing strategies in specific areas of sports. During button decision-making, the EG was more economical, whereas the NG required more brain function activity to process visual information, confirming the "neural efficiency" hypothesis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Huang, Lang, Li, Qin and Cao.)

• Pathological pain and negative emotions occurred at the different stages of NeuP. • Specific RSN connectivity alterations at the different stages of NeuP. • The SMN, DMN, and IN were the main affected RSNs during NeuP. Neuropathic pain (NeuP) is shown to be associated with abnormal changes in several specific brain regions. However, the large-scale interactivity of neuronal networks underlying the sensory and emotional abnormalities during NeuP remains unexplored. The present study aimed to explore the alterations in the relevant functional resting-state networks (RSNs) and their intra-networks at the different stages of NeuP based on resting-state functional magnetic resonance imaging (rs-fMRI). A NeuP rat model was established by chronic constriction injury (CCI). Three RSNs were identified to be associated with the NeuP, including the default mode network (DMN), sensorimotor network (SMN), and interoceptive network (IN). The functional connectivity (FC) of the left caudate putamen (CPu) within the DMN and the right piriform cortex within the IN were significantly reduced at the early stage of NeuP, when the maximum allodynia was apparent early, which reflected the suppressed function of the DMN and IN. At 4 weeks post-CCI, when negative emotions were present, the FC of the right insular cortex in the SMN and left visual cortex in the IN were significantly elevated, representing the increased excitability of both SMN and IN. Our study revealed the characteristic functional organization at the network level induced by NeuP and emphasized the role of SMN, DMN, and IN in the pathological mechanisms of NeuP. [ABSTRACT FROM AUTHOR]

Pediatric bipolar disorder (PBD) is associated with significant psychosocial impairment, high use of mental health services and a high number of relapses and hospitalization. Neuroimaging techniques provide the opportunity to study the neurodevelopmental processes underlying PBD, helping to identify the endophenotypic markers of illness and early biological markers of PBD. The aim of the study is to review available studies assessing structural and functional brain correlates associated with PBD. PubMed, ISI Web of Knowledge and PsychINFO databases have been searched. Studies were included if they enrolled patients aged 0-18 years with a main diagnosis of PBD according to ICD or DSM made by a mental health professional, adopted structural and/or functional magnetic resonance as the main neuroimaging method, were written in English and included a comparison with healthy subjects. Of the 400 identified articles, 46 papers were included. Patients with PBD present functional and anatomic alterations in structures normally affecting regulations and cognition. Structural neuroimaging revealed a significant reduction in gray matter, with cortical thinning in bilateral frontal, parietal and occipital cortices. Functional neuroimaging studies reported a reduced engagement of the frontolimbic and hyperactivation of the frontostriatal circuitry. Available studies on brain connectivity in PBD patients potentially indicate less efficient connections between regions involved in cognitive and emotional functions. A greater functional definition of alteration in brain functioning of PBD patients will be useful to set up a developmentally sensitive targeted pharmacological and nonpharmacological intervention., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Previous Resting-state functional magnetic resonance imaging (fMRI) studies have mainly focused on cerebral functional alteration in processing different emotional stimuli in patients with narcolepsy type 1 (NT1), but were short of exploration of characteristic brain activity and its remote interaction patterns. This study aimed to investigate the spontaneous blood oxygen fluctuations at rest and to elucidate the neural mechanisms underlying neuropsychiatric behavior., Method: A total of 18 unmedicated patients with NT1 and matched healthy individuals were recruited in a resting-state fMRI study. Magnetic resonance imaging (MRI) data were first analyzed using fractional low-frequency amplitude of low-frequency fluctuation (fALFF) to detect changes in local neural activity, and regions with group differences were taken as regions of interest (ROIs). Secondly, functional connectivity (FC) analysis was used to explore altered connectivity between ROIs and other areas. Lastly, the relationship between functional brain activity and neuropsychiatric behaviors was analyzed with correlation analysis., Results: fALFF analysis revealed enhanced neural activity in bilateral fusiform gyrus (FFG), right precentral gyrus, and left postcentral gyrus (PoCG) in the NT1 group. The patients indicated reduced activity in the bilateral temporal pole middle temporal gyrus (TPOmid), left caudate nucleus (CAU), left parahippocampus, left precuneus (PCUN), right amygdala, and right anterior cingulate and paracingulate gyri. ESS score was negatively correlated with fALFF in the right FFG. The NT1 group revealed decreased connectivity between left TPOmid and right PoCG, the bilateral middle frontal gyrus, left superior frontal gyrus, medial, and right supramarginal gyrus. Epworth Sleepiness Scale (ESS) was negatively correlated with FC of the left TPOmid with left putamen (PUT) in NT1. Compared with healthy controls (HCs), enhanced FC of the left CAU with right FFG was positively associated with MSLT-SOREMPs in patients. Furthermore, increased FC of the left PCUN with right PoCG was positively correlated with SDS score., Conclusions: We found that multiple functional activities related to the processing of emotional regulation and sensory information processing were abnormal, and some were related to clinical characteristics. fALFF in the left postcentral or right precentral gyrus may be used as a biomarker of narcolepsy, whereas fALFF in the right fusiform and the FC strength of the left temporal pole middle temporal gyrus with the putamen may be clinical indicators to assess the drowsiness severity of narcolepsy.

Purpose: Cognitive impairment (CI) is very common in patients with chronic obstructive pulmonary disease (COPD). Cerebral structural and functional abnormalities have been reported in cognitively impaired patients with COPD, and the neurovascular coupling changes are rarely investigated. To address this issue, arterial spin labeling (ASL) and resting-state blood oxygenation level dependent (BOLD) fMRI techniques were used to determine whether any neurovascular changes in COPD patients., Methods: Forty-five stable COPD patients and forty gender- and age-matched healthy controls were recruited. Furthermore, resting-state BOLD fMRI and ASL were acquired to calculate degree centrality (DC) and cerebral blood flow (CBF) respectively. The CBF-DC coupling and CBF/DC ratio were compared between the two groups., Results: COPD patients showed abnormal CBF, DC and CBF/DC ratio in several regions. Moreover, lower CBF/DC ratio in the left lingual gyrus negatively correlated with naming scores, lower CBF/DC ratio in medial frontal cortex/temporal gyrus positively correlated with the Montreal Cognitive Assessment (MoCA), visuospatial/executive and delayed recall scores., Conclusion: These findings may provide new potential insights into neuropathogenesis of cognition decline in stable COPD patients., Competing Interests: Juntao Zhang is employed by GE Healthcare, Precision Health Institution., (©2022 Peng et al.)

Perinatal stroke affects child's language development and can change language lateralization. Language generation and comprehension tasks in functional magnetic resonance imaging were used to determine language lateralization in term born children with perinatal left-side arterial ischemic stroke (AIS) (n = 9, mean age (SD) 13.4 (3.1) y.) and periventricular venous infarction (PVI) (n = 12, 11.8 (2.8) y.), and in healthy right-handed controls (n = 30, 11.6 (2.6) y.). Lateralization index was calculated for the Broca and Wernicke areas and correlated with language and cognitive outcomes measured by the Kaufman Assessment Battery for Children II ed. Language outcome in children with perinatal stroke is poorer compared to healthy controls. Children with small AIS lesions and most children with PVI showed left-side language activation. Most children with large AIS lesions and one child with large PVI had language activation reorganized to the right hemisphere. Language reorganization to the unlesioned right hemisphere did not ensure normal language outcome. [ABSTRACT FROM AUTHOR]

Background/aim: Misophonia is a disorder characterized by reduced tolerance to specific sounds or stimuli known as "triggers," which tend to evoke negative emotional, physiological, and behavioral responses. In this study, we aimed to better characterize participants with misophonia through the evaluation of the response of the autonomic nervous system to "trigger sounds," a psychometric assessment, and the analysis of the neurological pathways., Materials and Methods: Participants included 11 adults presenting with misophonic disturbance and 44 sex-matched healthy controls (HCs). Following recently proposed diagnostic criteria, the participants listened to six "trigger sounds" and a "general annoyance" sound (baby crying) during a series of physiological tests. The effects were examined through functional magnetic resonance imaging (fMRI), the analysis of heart rate variability (HRV), and of galvanic skin conductance (GSC). The fMRI was performed on a 3T Scanner. The HRV was obtained through the analysis of electrocardiogram, whereas the GSC was examined through the positioning of silver-chloride electrodes on fingers. Furthermore, the psychometric assessment included questionnaires focused on misophonia, psychopathology, resilience, anger, and motivation., Results: Participants with misophonia showed patterns of increased sympathetic activation in response to trigger sounds and a general annoyance sound, the low frequency (LF) component of HRV, the sympathetic index, and the number of significant GSC over the threshold, where the amplitude/phasic response of GSC was higher. The fMRI analysis provided evidence for the activation of the temporal cortex, the limbic area, the ventromedial prefrontal/premotor/cingulate cortex, and the cerebellum in participants with misophonia. In addition, the psychometric assessment seemed to differentiate misophonia as a construct independent from general psychopathology., Conclusion: These results suggest the activation of a specific auditory-insula-limbic pathway at the basis of the sympathetic activation observed in participants with misophonia in response to "trigger and general annoyance sounds." Further studies should disentangle the complex issue of whether misophonia represents a new clinical disorder or a non-pathological condition. These results could help to build diagnostic tests to recognize and better classify this disorder. The relevance of this question goes beyond purely theoretical issues, as in the first case, participants with misophonia should receive a diagnosis and a targeted treatment, while in the second case, they should not., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Grossini, Stecco, Gramaglia, De Zanet, Cantello, Gori, Negroni, Azzolina, Ferrante, Feggi, Carriero and Zeppegno.)

Dynamic resting state functional connectivity (RSFC) characterizes fluctuations that occur over time in functional brain networks. Existing methods to extract dynamic RSFCs, such as sliding-window and clustering methods that are inherently non-adaptive, have various limitations such as high-dimensionality, an inability to reconstruct brain signals, insufficiency of data for reliable estimation, insensitivity to rapid changes in dynamics, and a lack of generalizability across multiply functional imaging modalities. To overcome these deficiencies, we develop a novel and unifying time-varying dynamic network (TVDN) framework for examining dynamic resting state functional connectivity. TVDN includes a generative model that describes the relation between a low-dimensional dynamic RSFC and the brain signals, and an inference algorithm that automatically and adaptively learns the low-dimensional manifold of dynamic RSFC and detects dynamic state transitions in data. TVDN is applicable to multiple modalities of functional neuroimaging such as fMRI and MEG/EEG. The estimated low-dimensional dynamic RSFCs manifold directly links to the frequency content of brain signals. Hence we can evaluate TVDN performance by examining whether learnt features can reconstruct observed brain signals. We conduct comprehensive simulations to evaluate TVDN under hypothetical settings. We then demonstrate the application of TVDN with real fMRI and MEG data, and compare the results with existing benchmarks. Results demonstrate that TVDN is able to correctly capture the dynamics of brain activity and more robustly detect brain state switching both in resting state fMRI and MEG data., (Copyright © 2022. Published by Elsevier Inc.)