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Prior literature has debated whether syntax is separable from semantics in the brain. Using functional magnetic resonance imaging and multi-voxel pattern analysis, our previous studies investigated brain activity during morpho-syntactic versus semantic processing. These studies only detected semantic specialization in activation patterns and no syntactic specialization in 5- to 6-year-old and 7- to 8-year-old children. To examine if older children who have mastered morpho-syntactic skills would show specialization for syntax, the current study examined 64 9- to 10-year-old children using the same design and analyses. We observed that only the left IFG pars opercularis was sensitive to syntactic but not semantic information, supporting the hypothesis that this region serves as a core region for syntax. In addition, the left STG which has been implicated in the integration of semantics and syntax, as well as the left MTG and IFG pars triangularis which have been implicated in semantics, were sensitive to both semantic and syntactic information with no evidence of specialization. These findings suggest a lexicalized view of syntax, which argues that semantically sensitive regions are also critical regions for syntactic processing during language comprehension.

The human face plays a central role in emotions and social communication. The emotional and somatic motor networks generate facial behaviors, but whether facial behaviors have representations in the structural anatomy of the human brain is unknown. We coded 16 facial behaviors in 55 healthy older adults who viewed five videos that elicited emotions and examined whether individual differences in facial behavior were related to regional variation in gray matter volume. Voxel-based morphometry analyses revealed that greater emotional facial behavior during the disgust trial (i.e. greater brow furrowing and eye tightening as well as nose wrinkling and upper lip raising) and the amusement trial (i.e. greater smiling and eye tightening) was associated with larger gray matter volume in midcingulate cortex, supplementary motor area, and precentral gyrus, areas spanning both the emotional and somatic motor networks. When measured across trials, however, these facial behaviors (and others) only related to gray matter volume in the precentral gyrus, a somatic motor network hub. These findings suggest that the emotional and somatic motor networks store structural representations of facial behavior and that the midcingulate cortex is critical for generating the predictable movements in the face that arise during emotions.

Memory for temporal structure enables both planning of future events and retrospection of past events. We investigated how the brain flexibly represents extended temporal sequences into the past and future during anticipation. Participants learned sequences of environments in immersive virtual reality. Pairs of sequences had the same environments in a different order, enabling context-specific learning. During fMRI, participants anticipated upcoming environments multiple steps into the future in a given sequence. Temporal structure was represented in the hippocampus and across higher-order visual regions (1) bidirectionally, with graded representations into the past and future and (2) hierarchically, with further events into the past and future represented in successively more anterior brain regions. In hippocampus, these bidirectional representations were context-specific, and suppression of far-away environments predicted response time costs in anticipation. Together, this work sheds light on how we flexibly represent sequential structure to enable planning over multiple timescales.

Anorexia nervosa (AN) is associated with food restriction and significantly low body weight, but the neurobiology of food avoidance in AN is unknown. Animal research suggests that food avoidance can be triggered by conditioned fear that engages the anterior cingulate and nucleus accumbens. We hypothesized that the neural activation during food avoidance in AN could be modeled based on aversive goal value processing. Nineteen females with AN and thirty healthy controls matched for age underwent functional magnetic resonance brain imaging while conducting a food avoidance task. During active control free-bid and computer-generated forced-bid trials, participants bid money to avoid eating food items. Brain activation was parametrically modulated with the trial-by-trial placed bids. During free-bid trials, the AN group engaged the caudate nucleus, nucleus accumbens, ventral anterior cingulate, and inferior and medial orbitofrontal cortex more than the control group. High- versus low-bid trials in the AN group were associated with higher caudate nucleus response. Emotion dysregulation and intolerance of uncertainty scores were inversely associated with nucleus accumbens free-bid trial brain response in AN. This study supports the idea that food avoidance behavior in AN involves aversive goal value computation in the nucleus accumbens, caudate nucleus, anterior cingulate, and orbitofrontal cortex.

Humans are immensely curious and motivated to reduce uncertainty, but little is known about the neural mechanisms that generate curiosity. Curiosity is inversely associated with confidence, suggesting that it is triggered by states of low confidence (subjective uncertainty), but the neural mechanisms of this link, have been little investigated. Inspired by studies of sensory uncertainty, we hypothesized that visual areas provide multivariate representations of uncertainty, which are read out by higher-order structures to generate signals of confidence and, ultimately, curiosity. We scanned participants (17 female, 15 male) using fMRI while they performed a new task in which they rated their confidence in identifying distorted images of animals and objects and their curiosity to see the clear image. We measured the activity evoked by each image in the occipitotemporal cortex (OTC) and devised a new metric of "OTC Certainty" indicating the strength of evidence this activity conveys about the animal versus object categories. We show that, perceptual curiosity peaked at low confidence and OTC Certainty negatively correlated with curiosity, establishing a link between curiosity and a multivariate representation of sensory uncertainty. Moreover, univariate (average) activity in two frontal areas-vmPFC and ACC-correlated positively with confidence and negatively with curiosity, and the vmPFC mediated the relationship between OTC Certainty and curiosity. The results reveal novel mechanisms through which uncertainty about an event generates curiosity about that event.

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

AbstractPain anticipation during conditions of uncertainty can unveil intrinsic biases, and understanding these biases can guide pain treatment interventions. This study used machine learning and functional magnetic resonance imaging to predict anticipatory responses in a pain anticipation experiment. One hundred forty-seven participants that included healthy controls (n = 57) and individuals with current and/or past mental health diagnosis (n = 90) received cues indicating upcoming pain stimuli: 2 cues predicted high and low temperatures, while a third cue introduced uncertainty. Accurate differentiation of neural patterns associated with specific anticipatory conditions was observed, involving activation in the anterior short gyrus of the insula and the nucleus accumbens. Three distinct response profiles emerged: subjects with a negative bias towards high pain anticipation, those with a positive bias towards low pain anticipation, and individuals whose predictions during uncertainty were unbiased. These profiles remained stable over one year, were consistent across diagnosed psychopathologies, and correlated with cognitive coping styles and underlying insula anatomy. The findings suggest that individualized and stable pain anticipation occurs in uncertain conditions.

Patients with degenerative cervical myelopathy (DCM) experience structural and functional brain reorganization. However, few studies have investigated the influence of sex on cerebral alterations. The present study investigates the role of sex on brain functional connectivity (FC) and global network topology in DCM and healthy controls (HCs). The resting-state functional MRI data was acquired for 100 patients (58 males vs. 42 females). ROI-to-ROI FC and network topological features were characterized for each patient and HC. Group differences in FC and network topological features were examined. Compared to healthy counterparts, DCM males exhibited higher FC between vision-related brain regions, and cerebellum, brainstem, and thalamus, but lower FC between the intracalcarine cortex and frontal and somatosensory cortices, while DCM females demonstrated higher FC between the thalamus and cerebellar and sensorimotor regions, but lower FC between sensorimotor and visual regions. DCM males displayed higher FC within the cerebellum and between the posterior cingulate cortex (PCC) and vision-related regions, while DCM females displayed higher FC between frontal regions and the PCC, cerebellum, and visual regions. Additionally, DCM males displayed significantly greater intra-network connectivity and efficiency compared to healthy counterparts. Results from the present study imply sex-specific supraspinal functional alterations occur in patients with DCM.

In everyday life, people need to respond appropriately to many types of emotional stimuli. Here, we investigate whether human occipital-temporal cortex (OTC) shows co-representation of the semantic category and affective content of visual stimuli. We also explore whether OTC transformation of semantic and affective features extracts information of value for guiding behavior. Participants viewed 1620 emotional natural images while functional magnetic resonance imaging data were acquired. Using voxel-wise modeling we show widespread tuning to semantic and affective image features across OTC. The top three principal components underlying OTC voxel-wise responses to image features encoded stimulus animacy, stimulus arousal and interactions of animacy with stimulus valence and arousal. At low to moderate dimensionality, OTC tuning patterns predicted behavioral responses linked to each image better than regressors directly based on image features. This is consistent with OTC representing stimulus semantic category and affective content in a manner suited to guiding behavior.

Quantitative susceptibility mapping (QSM) is an MRI modality used to non-invasively measure iron content in the brain. Iron exhibits a specific anatomically varying pattern of accumulation in the brain across individuals. The highest regions of accumulation are the deep grey nuclei, where iron is stored in paramagnetic molecule ferritin. This form of iron is considered to be what largely contributes to the signal measured by QSM in the deep grey nuclei. It is also known that QSM is affected by diamagnetic myelin contents. Here, we investigate spatial gene expression of iron and myelin related genes, as measured by the Allen Human Brain Atlas, in relation to QSM images of age-matched subjects. We performed multiple linear regressions between gene expression and the average QSM signal within 34 distinct deep grey nuclei regions. Our results show a positive correlation (p

The ability to respond to emotional events in a context-sensitive and goal-oriented manner is essential for adaptive functioning. In models of behavioral and emotion regulation, the lateral prefrontal cortex (LPFC) is postulated to maintain goal-relevant representations that promote cognitive control, an idea rarely tested with causal inference. Here, we altered mid-LPFC function in healthy individuals using a putatively inhibitory brain stimulation protocol (continuous theta burst; cTBS), followed by fMRI scanning. Participants performed the Affective Go/No-Go task, which requires goal-oriented action during affective processing. We targeted mid-LPFC (vs. a Control site) based on the individualized location of action-goal representations observed during the task. cTBS to mid-LPFC reduced action-goal representations in mid-LPFC and impaired goal-oriented action, particularly during processing of negative emotional cues. During negative-cue processing, cTBS to mid-LPFC reduced functional coupling between mid-LPFC and nodes of the default mode network, including frontopolar cortex-a region thought to modulate LPFC control signals according to internal states. Collectively, these results indicate that mid-LPFC goal-relevant representations play a causal role in governing context-sensitive cognitive control during emotional processing.

The complex challenges of our mental life require us to coordinate multiple forms of neural information processing. Recent behavioural studies have found that people can coordinate multiple forms of attention, but the underlying neural control process remains obscure. We hypothesized that the brain implements multivariate control by independently monitoring feature-specific difficulty and independently prioritizing feature-specific processing. During functional MRI, participants performed a parametric conflict task that separately tags target and distractor processing. Consistent with feature-specific monitoring, univariate analyses revealed spatially segregated encoding of target and distractor difficulty in the dorsal anterior cingulate cortex. Consistent with feature-specific attentional priority, our encoding geometry analysis revealed overlapping but orthogonal representations of target and distractor coherence in the intraparietal sulcus. Coherence representations were mediated by control demands and aligned with both performance and frontoparietal activity, consistent with top-down attention. Together, these findings provide evidence for the neural geometry necessary to coordinate multivariate cognitive control.

Functional mapping during brain surgery is applied to define brain areas that control critical functions and cannot be removed. Currently, these procedures rely on verbal interactions between the neurosurgeon and electrophysiologist, which can be time-consuming. In addition, the electrode grids that are used to measure brain activity and to identify the boundaries of pathological versus functional brain regions have low resolution and limited conformity to the brain surface. Here, we present the development of an intracranial electroencephalogram (iEEG)-microdisplay that consists of freestanding arrays of 2048 GaN light-emitting diodes laminated on the back of micro-electrocorticography electrode grids. With a series of proof-of-concept experiments in rats and pigs, we demonstrate that these iEEG-microdisplays allowed us to perform real-time iEEG recordings and display cortical activities by spatially corresponding light patterns on the surface of the brain in the surgical field. Furthermore, iEEG-microdisplays allowed us to identify and display cortical landmarks and pathological activities from rat and pig models. Using a dual-color iEEG-microdisplay, we demonstrated coregistration of the functional cortical boundaries with one color and displayed the evolution of electrical potentials associated with epileptiform activity with another color. The iEEG-microdisplay holds promise to facilitate monitoring of pathological brain activity in clinical settings.

Asymmetry between the left and right hemisphere is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variants, which typically exert small effects on brain-related phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We designed a pattern-learning approach to dissect the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior data fusion highlights the consequences of genetically controlled brain lateralization on uniquely human cognitive capacities.

Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourettes syndrome, the supplementary motor area in Parkinsons disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.

Recent findings have shown that psychedelics reliably enhance brain entropy (understood as neural signal diversity), and this effect has been associated with both acute and long-term psychological outcomes, such as personality changes. These findings are particularly intriguing, given that a decrease of brain entropy is a robust indicator of loss of consciousness (e.g., from wakefulness to sleep). However, little is known about how context impacts the entropy-enhancing effect of psychedelics, which carries important implications for how it can be exploited in, for example, psychedelic psychotherapy. This article investigates how brain entropy is modulated by stimulus manipulation during a psychedelic experience by studying participants under the effects of lysergic acid diethylamide (LSD) or placebo, either with gross state changes (eyes closed vs open) or different stimuli (no stimulus vs music vs video). Results show that while brain entropy increases with LSD under all of the experimental conditions, it exhibits the largest changes when subjects have their eyes closed. Furthermore, brain entropy changes are consistently associated with subjective ratings of the psychedelic experience, but this relationship is disrupted when participants are viewing a video─potentially due to a competition between external stimuli and endogenous LSD-induced imagery. Taken together, our findings provide strong quantitative evidence of the role of context in modulating neural dynamics during a psychedelic experience, underlining the importance of performing psychedelic psychotherapy in a suitable environment.

Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the timescale over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.

Experimental work across species has demonstrated that spontaneously generated behaviors are robustly coupled to variations in neural activity within the cerebral cortex. Functional magnetic resonance imaging data suggest that temporal correlations in cortical networks vary across distinct behavioral states, providing for the dynamic reorganization of patterned activity. However, these data generally lack the temporal resolution to establish links between cortical signals and the continuously varying fluctuations in spontaneous behavior observed in awake animals. Here, we used wide-field mesoscopic calcium imaging to monitor cortical dynamics in awake mice and developed an approach to quantify rapidly time-varying functional connectivity. We show that spontaneous behaviors are represented by fast changes in both the magnitude and correlational structure of cortical network activity. Combining mesoscopic imaging with simultaneous cellular-resolution two-photon microscopy demonstrated that correlations among neighboring neurons and between local and large-scale networks also encode behavior. Finally, the dynamic functional connectivity of mesoscale signals revealed subnetworks not predicted by traditional anatomical atlas-based parcellation of the cortex. These results provide new insights into how behavioral information is represented across the neocortex and demonstrate an analytical framework for investigating time-varying functional connectivity in neural networks.

Language comprehension involves integrating low-level sensory inputs into a hierarchy of increasingly high-level features. Prior work studied brain representations of different levels of the language hierarchy, but has not determined whether these brain representations are shared between written and spoken language. To address this issue, we analyze fMRI BOLD data that were recorded while participants read and listened to the same narratives in each modality. Levels of the language hierarchy are operationalized as timescales, where each timescale refers to a set of spectral components of a language stimulus. Voxelwise encoding models are used to determine where different timescales are represented across the cerebral cortex, for each modality separately. These models reveal that between the two modalities timescale representations are organized similarly across the cortical surface. Our results suggest that, after low-level sensory processing, language integration proceeds similarly regardless of stimulus modality.

Dynamic functional connectivity investigates how the interactions among brain regions vary over the course of an fMRI experiment. Such transitions between different individual connectivity states can be modulated by changes in underlying physiological mechanisms that drive functional network dynamics, e.g., changes in attention or cognitive effort. In this paper, we develop a multi-subject Bayesian framework where the estimation of dynamic functional networks is informed by time-varying exogenous physiological covariates that are simultaneously recorded in each subject during the fMRI experiment. More specifically, we consider a dynamic Gaussian graphical model approach where a non-homogeneous hidden Markov model is employed to classify the fMRI time series into latent neurological states. We assume the state-transition probabilities to vary over time and across subjects as a function of the underlying covariates, allowing for the estimation of recurrent connectivity patterns and the sharing of networks among the subjects. We further assume sparsity in the network structures via shrinkage priors, and achieve edge selection in the estimated graph structures by introducing a multi-comparison procedure for shrinkage-based inferences with Bayesian false discovery rate control. We evaluate the performances of our method vs alternative approaches on synthetic data. We apply our modeling framework on a resting-state experiment where fMRI data have been collected concurrently with pupillometry measurements, as a proxy of cognitive processing, and assess the heterogeneity of the effects of changes in pupil dilation on the subjects propensity to change connectivity states. The heterogeneity of state occupancy across subjects provides an understanding of the relationship between increased pupil dilation and transitions toward different cognitive states.

• We assessed posture-dependent changes in cortical motor maps in awake marmosets. • The results demonstrated rapid modulation in forelimb motor maps. • Hindlimb posture was particularly effective in inducing these modulations. • Posture is a crucial variable to be controlled in future studies of motor control. Recent neuroimaging and electrophysiological studies have suggested substantial short-term plasticity in the topographic maps of the primary motor cortex (M1). However, previous methods lack the temporal resolution to detect rapid modulation of these maps, particularly in naturalistic conditions. To address this limitation, we previously developed a rapid stimulation mapping procedure with implanted cortical surface electrodes. In this study, employing our previously established procedure, we examined rapid topographical changes in forelimb M1 motor maps in three awake male marmoset monkeys. The results revealed that although the hotspot (the location in M1 that elicited a forelimb muscle twitch with the lowest stimulus intensity) remained constant across postures, the stimulus intensity required to elicit the forelimb muscle twitch in the perihotspot region and the size of motor representations were posture-dependent. Hindlimb posture was particularly effective in inducing these modulations. The angle of the body axis relative to the gravitational vertical line did not alter the motor maps. These results provide a proof of concept that a rapid stimulation mapping system with chronically implanted cortical electrodes can capture the dynamic regulation of forelimb motor maps in natural conditions. Moreover, they suggest that posture is a crucial variable to be controlled in future studies of motor control and cortical plasticity. Further exploration is warranted into the neural mechanisms regulating forelimb muscle representations in M1 by the hindlimb sensorimotor state. [ABSTRACT FROM AUTHOR]

The brain's white matter connections are thought to provide the structural basis for its functional connections between distant brain regions but how our brain selects the best structural routes for functional communications remains poorly understood. In this study, we propose a Unified Structural and Functional Connectivity (USFC) model and use an "economical assumption" to create the brain's first "traffic map" reflecting how frequently each segment of the brain structural connection is used to achieve the global functional communication system. The resulting USFC map highlights regions in the subcortical, default-mode, and salience networks as the most heavily traversed nodes and a midline frontal-caudate-thalamus-posterior cingulate-visual cortex corridor as the backbone of the whole brain connectivity system. Our results further revealed a striking negative association between structural and functional connectivity strengths in routes supporting negative functional connections, as well as significantly higher efficiency metrics and better predictive performance for cognition in the USFC connectome when compared to structural and functional ones alone. Overall, the proposed USFC model opens up a new window for integrated brain connectome modeling and provides a major leap forward in brain mapping efforts for a better understanding of the brain's fundamental communication mechanisms. Unified Structural and Functional Connectivity (USFC) model provides a novel framework for modeling the brain's integrated structural and functional pathway system and potentially opens up a new window uncovering the brain's working principles. [ABSTRACT FROM AUTHOR]

Functional magnetic resonance imaging (fMRI) enables indirect detection of brain activity changes via the blood-oxygen-level-dependent (BOLD) signal. Conventional analysis methods mainly rely on the real-valued magnitude of these signals. In contrast, research suggests that analyzing both real and imaginary components of the complex-valued fMRI (cv-fMRI) signal provides a more holistic approach that can increase power to detect neuronal activation. We propose a fully Bayesian model for brain activity mapping with cv-fMRI data. Our model accommodates temporal and spatial dynamics. Additionally, we propose a computationally efficient sampling algorithm, which enhances processing speed through image partitioning. Our approach is shown to be computationally efficient via image partitioning and parallel computation while being competitive with state-of-the-art methods. We support these claims with both simulated numerical studies and an application to real cv-fMRI data obtained from a finger-tapping experiment. [ABSTRACT FROM AUTHOR]

Introduction: As emerging technologies enable measurement of precise details of the activity within microcircuits at ever-increasing scales, there is a growing need to identify the salient features and patterns within the neural populations that represent physiologically and behaviorally relevant aspects of the network. Accumulating evidence from recordings of large neural populations suggests that neural population activity frequently exhibits relatively low-dimensional structure, with a small number of variables explaining a substantial fraction of the structure of the activity. While such structure has been observed across the brain, it is not known how reduced-dimension representations of neural population activity relate to classical metrics of "brain state," typically described in terms of fluctuations in the local field potential (LFP), single-cell activity, and behavioral metrics. Methods: Hidden state models were fit to spontaneous spiking activity of populations of neurons, recorded in the whisker area of primary somatosensory cortex of awake mice. Classic measures of cortical state in S1, including the LFP and whisking activity, were compared to the dynamics of states inferred from spiking activity. Results: A hidden Markov model fit the population spiking data well with a relatively small number of states, and putative inhibitory neurons played an outsize role in determining the latent state dynamics. Spiking states inferred from the model were more informative of the cortical state than a direct readout of the spiking activity of single neurons or of the population. Further, the spiking states predicted both the trial-by-trial variability in sensory responses and one aspect of behavior, whisking activity. Discussion: Our results show how classical measurements of brain state relate to neural population spiking dynamics at the scale of the microcircuit and provide an approach for quantitative mapping of brain state dynamics across brain areas. [ABSTRACT FROM AUTHOR]

Background: Alcohol withdrawal is widely recognized as a trigger for acute symptomatic seizures among individuals with chronic alcohol consumption. While most alcohol withdrawal seizures occur shortly after cessation, chronic alcohol consumption can be associated with the development of epilepsy, necessitating anti‐epileptic drug (AED) therapy. This study aimed to investigate the clinical characteristics, seizure recurrence, and epilepsy development in patients with alcohol‐related seizures and to identify prognostic factors for epilepsy. Methods: In a retrospective analysis at Ewha Womans University Mokdong Hospital, 206 patients with alcohol‐related seizures were examined and 15 were excluded due to preexisting epilepsy. Demographic and clinical data, including alcohol withdrawal duration, seizure recurrence, types, and comorbidities, were investigated. Logistic regression models were used to analyze the risk factors for seizure recurrence and epilepsy development. The performance of the final models was evaluated based on the area under the receiver operating characteristic curve (AUC) and validated using calibration plots and leave‐one‐out cross‐validation. Results: Of the 191 patients (146 males; mean age 48.3 ± 12.1 years) with alcohol‐related seizures, 99 patients (51.8%) experienced seizure recurrence and 79 patients (41.4%) developed epilepsy. Factors associated with seizure recurrence included alcohol consumption levels, occurrence of focal impaired awareness seizure, anxiety, and headache. The number of recurrent seizures, semiology, status epilepticus, electroencephalogram findings, and brain imaging findings was associated with epilepsy development. The predictive models showed strong diagnostic performance, with AUCs of 0.833 for seizure recurrence and 0.939 for epilepsy development. Conclusion: High alcohol consumption and specific clinical and diagnostic features are significant predictors of seizure recurrence and the development of epilepsy among patients with alcohol‐related seizures. These findings underscore the importance of early identification and intervention to prevent seizure recurrence and the onset of epilepsy, emphasizing the importance of AED treatment in managing these conditions. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to decode intended and overt speech from neuromagnetic signals while the participants performed spontaneous overt speech tasks without cues or prompts (stimuli). Method: Magnetoencephalography (MEG), a noninvasive neuroimaging technique, was used to collect neural signals from seven healthy adult English speakers performing spontaneous, overt speech tasks. The participants randomly spoke the words yes or no at a self-paced rate without cues. Two machine learning models, namely, linear discriminant analysis (LDA) and one-dimensional convolutional neural network (1D CNN), were employed to classify the two words from the recorded MEG signals. Results: LDA and 1D CNN achieved average decoding accuracies of 79.02% and 90.40%, respectively, in decoding overt speech, significantly surpassing the chance level (50%). The accuracy for decoding intended speech was 67.19% using 1D CNN. Conclusions: This study showcases the possibility of decoding spontaneous overt and intended speech directly from neural signals in the absence of perceptual interference. We believe that these findings make a steady step toward the future spontaneous speech-based brain-computer interface. [ABSTRACT FROM AUTHOR]

True and false memories recruit a number of shared brain regions; however, they are not completely overlapping. Extensive sex differences have been identified in the brain during true memories and, recently, we identified sex differences in the brain during false memories. In the current fMRI study, we sought to determine whether sex differences existed in the location and extent of overlap between true and false memories. True and false memories activated a number of shared brain regions. Compared to females, males produced a greater number of overlapping brain regions (8 versus 2 activations for males and females, respectively) including the prefrontal cortex, parietal cortex, and early/late visual processing cortices (including V1) in males and prefrontal and parietal cortices in females. Males had significantly higher similarity between true and false memory activation maps, revealed by our novel multi-voxel pattern correlation analysis. Moreover, higher similarity between true and false memory activation maps was associated with higher false memory rates. The current results suggest that true and false memories are more similar in males than females. The significant brain–behavior relationship also suggests that males may be more susceptible to false memory errors due to their highly similar true memory–false memory cortical representations. [ABSTRACT FROM AUTHOR]

Schemas allow us to make assumptions about the world based upon previous experiences and aid in memory organisation and retrieval. However, a reliance on schemas may also result in increased false memories to schematically related lures. Prior neuroimaging work has linked schematic processing in memory tasks to activity in prefrontal, visual, and temporal regions. Yet, it is unclear what type of processing in these regions underlies memory errors. The current study examined where schematic lures exhibit greater neural similarity to schematic targets, leading to this memory error, as compared to neural overlap with non-schematic lures, which, like schematic lures, are novel items at retrieval. Results showed that patterns of neural activity in ventromedial prefrontal cortex, medial frontal gyrus, middle temporal gyrus, hippocampus, and occipital cortices exhibited greater neural pattern similarity for schematic targets and schematic lures than between schematic lures and non-schematic lures. As such, results suggest that schematic membership, and not object history, may be more critical to the neural processes underlying memory retrieval in the context of a strong schema. [ABSTRACT FROM AUTHOR]

Prior work has shown Americans have higher levels of memory specificity than East Asians. Neuroimaging studies have not investigated mechanisms that account for cultural differences at retrieval. In this study, we use fMRI to assess whether mnemonic discrimination, distinguishing novel from previously encountered stimuli, accounts for cultural differences in memory. Fifty-five American and 55 Taiwanese young adults completed an object recognition paradigm testing discrimination of old targets, similar lures and novel foils. Mnemonic discrimination was tested by comparing discrimination of similar lures from studied targets, and results showed the relationship between activity in right fusiform gyrus and behavioural discrimination between target and lure objects differed across cultural groups. Parametric modulation analyses of activity during lure correct rejections also indicated that groups differed in left superior parietal cortex response to variations in lure similarity. Additional analyses of old vs. new activity indicated that Americans and Taiwanese differ in the neural activity supporting general object recognition in the hippocampus, left inferior frontal gyrus and middle frontal gyrus. Results are juxtaposed against comparisons of the regions activated in common across the two cultures. Overall, Americans and Taiwanese differ in the extent to which they recruit visual processing and attention modulating brain regions. [ABSTRACT FROM AUTHOR]

Behavioral inhibition (BI), an early-life temperament characterized by vigilant responses to novelty, is a risk factor for anxiety disorders. In this study, we investigated whether differences in neonatal brain responses to infrequent auditory stimuli relate to children's BI at 1 year of age. Using functional magnetic resonance imaging (fMRI), we collected blood-oxygen-level-dependent (BOLD) data from N = 45 full-term, sleeping neonates during an adapted auditory oddball paradigm and measured BI from n = 27 of these children 1 year later using an observational assessment. Whole-brain analyses corrected for multiple comparisons identified 46 neonatal brain regions producing novelty-evoked BOLD responses associated with children's BI scores at 1 year of age. More than half of these regions (n = 24, 52%) were in prefrontal cortex, falling primarily within regions of the default mode or frontoparietal networks or in ventromedial/orbitofrontal regions without network assignments. Hierarchical clustering of the regions based on their patterns of association with BI resulted in two groups with distinct anatomical, network, and response-timing profiles. The first group, located primarily in subcortical and temporal regions, tended to produce larger early oddball responses among infants with lower subsequent BI. The second group, located primarily in prefrontal cortex, produced larger early oddball responses among infants with higher subsequent BI. These results provide preliminary insights into brain regions engaged by novelty in infants that may relate to later BI. The findings may inform understanding of anxiety disorders and guide future research. Public Significance Statement: This study suggests that specific neural responses to novel sounds in the neonatal brain may be related to children's behavioral inhibition (BI), an early-life temperament characterized by increased vigilance to novelty, 1 year later. Neonatal brain areas producing these responses include regions of prefrontal cortex, temporal cortex, and subcortical structures including pons and amygdala. Given associations between BI and later anxiety symptoms, these findings may inform the understanding of neural antecedents of anxiety disorders. [ABSTRACT FROM AUTHOR]

Neurotransmitters and their receptors are key molecules in information transfer between neurons, thus enabling inter-areal communication. Therefore, multimodal atlases integrating the brain's cyto- and receptor architecture constitute crucial tools to understand the relationship between its structural and functional segregation. Cholinergic muscarinic M2 receptors have been shown to be an evolutionarily conserved molecular marker of primary sensory areas in the mammalian brain. To complement existing rodent atlases, we applied a silver cell body staining and quantitative in vitro receptor autoradiographic visualization of M2 receptors to alternating sections throughout the entire brain of five adult male Wistar rats (three sectioned coronally, one horizontally, one sagittally). Histological sections and autoradiographs were scanned at a spatial resolution of 1 µm and 20 µm per pixel, respectively, and files were stored as 8 bit images. We used these high-resolution datasets to create an atlas of the entire rat brain, including the olfactory bulb, cerebellum and brainstem. We describe the cyto- and M2 receptor architectonic features of 48 distinct iso- and proisocortical areas across the rat forebrain and provide their mean M2 receptor density. The ensuing parcellation scheme, which is discussed in the framework of existing comprehensive atlasses, includes the novel subdivision of mediomedial secondary visual area Oc2MM into anterior (Oc2MMa) and posterior (Oc2MMp) parts, and of lateral visual area Oc2L into rostrolateral (Oc2Lr), intermediate dorsolateral (Oc2Lid), intermediate ventrolateral (Oc2Liv) and caudolateral (Oc2Lc) secondary visual areas. The M2 receptor densities and the comprehensive map of iso-and proisocortical areas constitute useful tools for future computational and neuroscientific studies. [ABSTRACT FROM AUTHOR]

The cognitive neuroscience of language aims at revealing how linguistic information is represented and manipulated in the brain to enable communication and meaningful behaviour. An important aspect of the underlying brain processes is the integration and transformation of information across multiple brain systems. In order to understand these processes, a detailed characterisation of brain connectivity is key. For the most accurate characterisation of brain connectivity, connectivity methods should make use of the full multivariate and multidimensional information available from neuroimaging data. This should include a characterisation of transformations between patterns of activation across brain regions, and in particular their dependence on stimulus features, task and context. Methods for this type of analysis in event-related experimental designs have only recently begun to emerge. This paper describes these novel developments and their potential to transform the neuroscience of language, with a focus on fMRI and EEG/MEG research. [ABSTRACT FROM AUTHOR]

Several studies have been published which show that it is possible to decode semantic representations directly from brain responses. This has been repeatedly successful when the stimuli used were pictures of objects. However, there is a distinct scarcity of studies decoding responses to orthographic stimuli, particularly those employing time-sensitive imaging methods. We use examples from our own research to highlight the challenges we have faced when attempting to decode semantic representations from MEG responses to written words. We discuss differences in brain responses to pictures and orthographic stimuli to determine the characteristics of the brain responses that allow for successful decoding of semantics. We suspect the limited number of published studies on this topic indicates that these challenges are not unique to our experience. By bringing attention to these issues, we hope to stimulate a new wave of discussion leading to eventual progress. [ABSTRACT FROM AUTHOR]

Understanding the architecture of the human deep brain is especially challenging because of the complex organization of the nuclei and fascicles that support most sensorimotor and behaviour controls. There are scant dedicated tools to explore and analyse this region. Here we took a transdisciplinary approach to build a new deep-brain MRI architecture atlas drawing on advanced clinical experience of MRI-based deep brain mapping. This new tool comprises a young-male-adult MRI template spatially normalized to the ICBM152, containing T1, inversion-recovery, and diffusion MRI datasets (in vivo acquisition), and an MRI atlas of 118 labelled deep brain structures. It is open-source and gives users high resolution image datasets to describe nuclear-based and axonal architecture, combining pioneering and recent knowledge. It is a useful addition to current 3D atlases and clinical tools. [ABSTRACT FROM AUTHOR]

Purpose: T1 mapping and T1‐weighted contrasts have a complimentary but currently under utilized role in fetal MRI. Emerging clinical low field scanners are ideally suited for fetal T1 mapping. The advantages are lower T1 values which results in higher efficiency and reduced field inhomogeneities resulting in a decreased requirement for specialist tools. In addition the increased bore size associated with low field scanners provides improved patient comfort and accessibility. This study aims to demonstrate the feasibility of fetal brain T1 mapping at 0.55T. Methods: An efficient slice‐shuffling inversion‐recovery echo‐planar imaging (EPI)‐based T1‐mapping and postprocessing was demonstrated for the fetal brain at 0.55T in a cohort of 38 fetal MRI scans. Robustness analysis was performed and placental measurements were taken for validation. Results: High‐quality T1 maps allowing the investigation of subregions in the brain were obtained and significant correlation with gestational age was demonstrated for fetal brain T1 maps (p<0.05$$ p<0.05 $$) as well as regions‐of‐interest in the deep gray matter and white matter. Conclusions: Efficient, quantitative T1 mapping in the fetal brain was demonstrated on a clinical 0.55T MRI scanner, providing foundations for both future research and clinical applications including low‐field specific T1‐weighted acquisitions. [ABSTRACT FROM AUTHOR]

Purpose: To acquire accurate volumetric multi‐channel B1+$$ {\mathrm{B}}_1^{+} $$ maps in under 14 s whole‐brain or 23 heartbeats whole‐heart for parallel transmit (pTx) applications at 7 T. Theory and Methods: We evaluate the combination of three recently proposed techniques. The acquisition of multi‐channel transmit array B1+$$ {\mathrm{B}}_1^{+} $$ maps is accelerated using transmit low rank (TxLR) with absolute B1+$$ {\mathrm{B}}_1^{+} $$ mapping (Sandwich) acquired in a B1+$$ {\mathrm{B}}_1^{+} $$ time‐interleaved acquisition of modes (B1TIAMO) fashion. Simulations using synthetic body images derived from Sim4Life were used to test the achievable acceleration for small scan matrices of 24 × 24. Next, we evaluated the method by retrospectively undersampling a fully sampled B1+$$ {\mathrm{B}}_1^{+} $$ library of nine subjects in the brain. Finally, Cartesian undersampled phantom and in vivo images were acquired in both the brain of three subjects (8Tx/32 receive [Rx]) and the heart of another three subjects (8Tx/8Rx) at 7 T. Results: Simulation and in vivo results show that volumetric multi‐channel B1+$$ {\mathrm{B}}_1^{+} $$ maps can be acquired using acceleration factors of 4 in the body, reducing the acquisition time to within 23 heartbeats, which was previously not possible. In silico heart simulations demonstrated a RMS error to the fully sampled native resolution ground truth of 4.2° when combined in first‐order circularly polarized mode (mean flip angle 66°) at an acceleration factor of 4. The 14 s 3D B1+$$ {\mathrm{B}}_1^{+} $$ maps acquired in the brain have a RMS error of 1.9° to the fully sampled (mean flip angle 86°). Conclusion: The proposed method is demonstrated as a fast pTx calibration technique in the brain and a promising method for pTx calibration in the body. [ABSTRACT FROM AUTHOR]

Objectives: Resective surgery is a potential therapeutic option for select patients with intractable focal epilepsy. However, the presence of ictal onset zones within or surrounding highly functional brain areas presents a surgical challenge, leading to poor seizure and functional outcomes. This report describes our experiences with awake mapping-tailored resection of epileptogenic areas involving eloquent cortices and evaluates their feasibility, tolerance, limitations, and significance. Methods: The study included patients who underwent surgery for drug-resistant focal epilepsy at our center under awake conditions. The surgical approach aimed to achieve maximum resection of preoperatively defined epileptogenic zones, considering the boundaries defined by surrounding functional areas. We collected data on preoperative evaluations, intraoperative tests and seizures, postoperative status epilepticus, and neurological functional outcomes. Results: We included 22 patients, 10 of whom had non-lesional epilepsy. Language, motor function, and sensory function were at risk in 19, 9, and 4 patients, respectively. Resection was performed as planned in 14 (63.6%) patients, while modifications were necessary in 8 (36.4%) patients due to functional constraints. The mean follow-up duration was 29.8 months. Sixteen (72.7%) patients achieved Engel class Ia outcomes, indicating seizure freedom, while none of the patients experienced clinically significant permanent postoperative neurological deficits. Significance: Resective surgery with intraoperative brain mapping under awake conditions was a valid treatment option for achieving a cure in cases of drug-resistant focal epilepsy, even in situations in which the condition is considered inoperable due to the risk of significant postoperative neurological deficits. [ABSTRACT FROM AUTHOR]

Background: Second and third surgeries were demonstrated as safe and efficient in recurrent diffuse low-grade glioma (LGG). Here, the feasibility of more than 3 resections is investigated. Methods: Patients who underwent 4 or 5 operations for recurrent initially WHO grade 2 IDH-mutated gliomas were consecutively selected. Results: Twenty-three operations were performed in five patients (all males, mean age 27.2 ± 4 years). Three patients underwent 5 surgeries and two patients underwent 4 surgeries. Twelve procedures (52%) were achieved with awake mapping, including all 4th and 5th operations but one. Repeat electrical mapping detected changes of the cortical maps between at least two awake surgeries in 4 patients. No patients experienced permanent neurological impairment (KPS score ≥ 80 in all cases). The patients returned to work after 22 surgeries among 23 (95.6%). There were 3 oligodendrogliomas and 2 astrocytomas (4 gliomas became malignant at fourth or fifth operation). Although the preoperative tumor volume significantly increased before the fourth (p = 0.026) and fifth operation (p = 0.003) compared with the first operation, there was no significant difference between the residual tumor volume after the fourth or fifth resection versus the first one. The mean delay was 10.6 ± 3.9 years before chemotherapy and 15.4 ± 3.4 years before radiotherapy (one patient never received adjuvant treatment after 21.5 years). The mean follow-up duration was 18.3 ± 3.1 years since the first surgery (2.3 ± 1.8 years since the last surgery). Three patients were still alive at last follow-up. Conclusions: This is the first series showing that to reoperate beyond three times is feasible with a low functional risk and a long survival in multiple LGG recurrences, with the use of awake mapping in 87.5% of 4th and 5th surgeries. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by progressively worsening cognitive decline and memory loss. Excessive iron accumulation produces severe cognitive impairment. However, there are no uniform conclusions about changes in brain iron content in AD. This study aimed to investigate the iron content of the deep brain nuclei in AD, and its correlation with cognitive function. Methods: Thirty-one patients with mild to moderate AD, 17 patients with mild cognitive impairment (MCI), and 20 age-, sex-, and education-matched healthy controls (HC) were collected. The QSM was used to quantify the magnetic susceptibility values of the caudate nucleus, putamen, globus pallidus, substantia nigra, red nucleus, and dentate nucleus, and to analyze the differences that existed between the three groups. As well as the correlation between the magnetic susceptibility values and cognitive function was calculated. Results: The magnetic susceptibility values of bilateral globus pallidus, left putamen, and bilateral substantia nigra were significantly higher in AD patients than in HC, and the magnetic susceptibility values of the right globus pallidus were significantly higher in AD patients than in MCI (all p < 0.05). The magnetic susceptibility values of the left dentate nucleus in the AD group were negatively correlated with the writing function of the MMSE subitem (r = -0.42, p = 0.020), and the magnetic susceptibility values of the left caudate nucleus and right dentate nucleus were significantly and negatively correlated with the naming function and language function of the MoCA subitem, respectively (r = -0.43, p = 0.019; r = -0.36, p = 0.048). Conclusion: Magnetic susceptibility values based on QSM correlate with cognitive function are valuable in discriminating AD from MCI and AD from HC. [ABSTRACT FROM AUTHOR]

Objective: To determine the optimal montage and vocalization conditions for high-gamma language mapping using stereoelectroencephalography. Methods: We studied 12 epilepsy patients who underwent invasive monitoring with depth electrodes and measurement of auditory-naming related highgamma modulations. We determined the effects of electrode montage and vocalization conditions of the response on the high-gamma (60–140  Hz) amplitudes. Results: Compared to common average reference montage, bipolar and Laplacian montages effectively reduced the degree of auditory naming-related signal deflections in the white matter during the stimulus and response phases (mixed model estimate: −21.2 to −85.4%; p  <  0.001), while maintaining those at the cortical level (−4.4 to +7.8%; p  =  0.614 to 0.085). They also reduced signal deflections outside the brain parenchyma during the response phase (−90.6 to −91.2%; p  <  0.001). Covert responses reduced signal deflections outside the brain parenchyma during the response phase (−17.0%; p  =  0.010). Conclusion: On depth electrode recording, bipolar and Laplacian montages are suitable for measuring auditory naming-related high-gamma modulations in gray matter. The covert response may highlight the gray matter activity. Significance: This study helps establish the practical guidelines for high-gamma language mapping using stereoelectroencephalography. [ABSTRACT FROM AUTHOR]

Objectives: This study aims to reveal the current knowledge map, research hotspots of functional magnetic resonance imaging (fMRI) studies on depression, as well as identify the brain regions associated with depression. Methods: CiteSpace was conducted to analyze the publication outputs, country, institution, cited journals, author and cited author, references, keyword cocurrence and burst keywords of fMRI studies in depression from 2010 to 2024. And a meta-analysis of fMRI was used to identify brain regions associated with depression using Neurosynth. Results: A total of 4,049 publications were included, and Gong Qiyong was the most prolific authors. Neuroimage, Biological Psychiatry, and Human Brain Mapping were prominent journals. Default mode network (DMN), prefrontal cortex, amygdala, and anterior cingulate cortex were the popular keywords. The fMRI studies on depression have mainly focused on major depression, especially the DMN. Functional connectivity and regional homogeneity of brain regions were research hotspots. The meta-analysis revealed significant differences in brain regions between patients with depression and healthy controls, including the Amygdala_L, Insula_R, Frontal_Inf_Oper_R, Cingulum_Post_L, Putamen_L, Thalamus_R, Angular_L, Precuneus_R, Frontal_Sup_R, Occipital_Inf_L. Conclusions: This study sheds light on key issues and future directions in fMRI research on depression, elucidating the brain regions related to depression. [ABSTRACT FROM AUTHOR]

3D brain atlases are key resources to understand the brain's spatial organization and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of developing mouse brain 3D reference atlases hinders advancements in understanding brain development. Here, we present a 3D developmental common coordinate framework (DevCCF) spanning embryonic day (E)11.5, E13.5, E15.5, E18.5, and postnatal day (P)4, P14, and P56, featuring undistorted morphologically averaged atlas templates created from magnetic resonance imaging and co-registered high-resolution light sheet fluorescence microscopy templates. The DevCCF with 3D anatomical segmentations can be downloaded or explored via an interactive 3D web-visualizer. As a use case, we utilize the DevCCF to unveil GABAergic neuron emergence in embryonic brains. Moreover, we map the Allen CCFv3 and spatial transcriptome cell-type data to our stereotaxic P56 atlas. In summary, the DevCCF is an openly accessible resource for multi-study data integration to advance our understanding of brain development. 3D brain atlases enable spatial data integration across studies. Here, the authors present the Developmental Mouse Brain Common Coordinate Framework, a 3D multimodal atlas from embryonic to adult ages for cell type mapping through brain development. [ABSTRACT FROM AUTHOR]

Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention tool for the noninvasive modulation of brain activity and behavior in neuroscience research and clinical settings. However, the resting‐state dynamic evolution of large‐scale functional brain networks following rTMS has rarely been investigated. Here, using resting‐state fMRI images collected from 23 healthy individuals before (baseline) and after 1 Hz rTMS of the left frontal (FRO) and occipital (OCC) lobes, we examined the different effects of rTMS on brain dynamics across the human cortex. By fitting a pairwise maximum entropy model (pMEM), we constructed an energy landscape for the baseline and poststimulus conditions by fitting a pMEM. We defined dominant brain states (local minima) in the energy landscape with synergistic activation and deactivation patterns of large‐scale functional networks. We calculated state dynamics including appearance probability, transitions and duration. The results showed that 1 Hz rTMS induced increased and decreased state probability, transitions and duration when delivered to the FRO and OCC targets, respectively. Most importantly, the shortest path and minimum cost between dominant brain states were altered after stimulation. The absolute sum of the costs from the source states to the destinations was lower after OCC stimulation than after FRO stimulation. In conclusion, our study characterized the dynamic trajectory of state transitions in the energy landscape and suggested that local rTMS can induce significant dynamic perturbation involving stimulated and distant functional networks, which aligns with the modern view of the dynamic and complex brain. Our results suggest low‐dimensional mapping of rTMS‐induced brain adaption, which will contribute to a broader and more effective application of rTMS in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Although neuroimaging investigations have consistently demonstrated that "hyperresponsive" and "hyperconnected" visual cortices may represent the functional substrate of cortical spreading depolarization in patients with migraine with aura, the mechanisms which underpin the brain "tendency" to ignite the cortical spreading depolarization and, consequently, aura phenomenon are still matter of debate. Considering that triggers able to induce aura phenomenon constrain brain to increase global (such as physical activity, stressors and sleep abnormalities) or local (such as bright light visual stimulations) energy demand, a vascular supply unable to satisfy the increased energy requirement could be hypothesized in these patients. Methods: Twenty-three patients with migraine with aura, 25 patients with migraine without aura and 20 healthy controls underwent a 3-Tesla MRI study. Cerebral blood flow and local functional connectivity (regional homogeneity) maps were obtained and registered to the MNI space where 100 cortical regions were derived using a functional local-global normative parcellation. A surrogate estimate of the regional neurovascular coupling for each subject was obtained at each parcel from the correlation coefficient between the z-scored ReHo map and the z-scored cerebral blood flow maps. Results: A significantly higher regional cerebral blood flow across the visual cortex of both hemispheres (i.e. fusiform and lingual gyri) was detected in migraine with aura patients when compared to patients with migraine without aura (p < 0.05, corrected for multiple comparisons). Concomitantly, a significantly reduced neurovascular coupling (p < 0.05, false discovery rate corrected) in the primary visual cortex parcel (VIS-4) of the large-scale visual network was observed in the left hemisphere of patients with migraine with aura (0.23±0.03), compared to both patients with migraine without aura (0.32±0.05) and healthy controls (0.29±0.05). Conclusions: Visual cortex neurovascular "decoupling" might represent the "link" between the exposure to trigger factors and aura phenomenon ignition. While physiological vascular oversupply may compensate neurovascular demand-supply at rest, it becomes inadequate in case of increased energy demand (e.g. when patients face with trigger factors) paving the way to the aura phenomenon ignition in patients with migraine with aura. Whether preventive treatments may exert their therapeutic activity on migraine with aura restoring the energy demands and cerebral blood flow trade-off within the visual network should be further investigated. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment (CI) is common in Parkinson's disease (PD). Multiple brain regions and their interactions are involved in PD associated CI. Magnetic resonance imaging (MRI) technology is a non-invasive method in investigating brain structure and interregional connections. In this study, by comparing cortical thickness, subcortical volume, and brain network topology properties in PD patients with and without CI, we aimed to understand the changes of brain structure and structural covariance network properties in PD associated CI. Methods: A total of 18 PD patients with CI and 33 PD patients without CI were recruited. Movement Disorder Society Unified Parkinson's Disease Rating Scale, Hoehn and Yahr stage, Mini Mental State Examination Scale, Non-motor Symptom Rating Scale, Hamilton Anxiety Scale, and Hamilton Depression Scale were assessed. All participants underwent structural 3T MRI. Cortical thickness, subcortical volume, global and nodal network topology properties were measured. Results: Compared with PD patients without CI, the volumes of white matter, thalamus and hippocampus were lower in PD patients with CI. And decreased whole-brain local efficiency is associated with CI in PD patients. While the cortical thickness and nodal network topology properties were comparable between PD patients with and without CI. Conclusion: Our findings support the alterations of brain structure and disruption of structural covariance network are involved in PD associated CI, providing a new insight into the association between graph properties and PD associated CI. [ABSTRACT FROM AUTHOR]

Background: Charles Bonnet syndrome (CBS) is a condition in which people with vision loss experience complex visual hallucinations. These complex visual hallucinations may be caused by increased excitability in the visual cortex that are present in some people with vision loss but not others. Objectives: We aimed to evaluate the association between γ-aminobutyric acid (GABA) in the visual cortex and CBS. We also tested the relationship among visually evoked responses, functional connectivity, and CBS. Design: This is a prospective, case-controlled, cross-sectional observational study. Methods: We applied 3-Tesla magnetic resonance spectroscopy, as well as task-based and resting state (RS) connectivity functional magnetic resonance imaging in six participants with CBS and six controls without CBS. GABA+ was measured in the early visual cortex (EVC) and in the lateral occipital cortex (LOC). Participants also completed visual acuity and cognitive tests, and the North-East Visual Hallucinations Interview. Results: The two groups were well-matched for age, gender, visual acuity and cognitive scores. There was no difference in GABA+ levels between groups in the visual cortex. Most participants showed the expected blood oxygenation level dependent (BOLD) activation to images of objects and the phase-scrambled control. Using a fixed effects analysis, we found that BOLD activation was greater in participants with CBS compared to controls. Analysis of RS connectivity with LOC and EVC showed little difference between groups. A fixed effects analysis showed a correlation between the extent of functional connectivity with LOC and hallucination strength. Conclusion: Overall, our results provide no strong evidence for an association between GABAergic inhibition in the visual cortex and CBS. We only found subtle differences in visual function and connectivity between groups. These findings suggest that the neurochemistry and visual connectivity for people with Charles Bonnet hallucinations are comparable to a sight loss population. Differences between groups may emerge when investigating subtle and transient changes that occur at the time of visual hallucinations. Plain language summary: Brain imaging in Charles Bonnet syndrome In Charles Bonnet Syndrome (CBS), people with sight loss start to see hallucinations that they know are not real but can be disturbing. In this study we used MRI scanning to measure how the chemistry in the visual brain differs in people with CBS and those who have sight loss but no hallucinations. Surprisingly we did not find any differences in chemistry between these groups, suggesting that their brains do not differ greatly. Any differences in how their visual brain works may be too small to measure, or only present when people hallucinate. [ABSTRACT FROM AUTHOR]

Background: Although gray matter (GM) volume alterations have been extensively documented in previous voxel-based morphometry studies on vestibular migraine (VM), little is known about the impact of this disease on the topological organization of GM morphological networks. This study investigated the altered network patterns of the GM connectome in patients with VM. Methods: In this study, 55 patients with VM and 57 healthy controls (HCs) underwent structural T1-weighted MRI. GM morphological networks were constructed by estimating interregional similarity in the distributions of regional GM volume based on the Kullback–Leibler divergence measure. Graph-theoretical metrics and interregional morphological connectivity were computed and compared between the two groups. Partial correlation analyses were performed between significant GM connectome features and clinical parameters. Logistic regression (LR), support vector machine (SVM), and random forest (RF) classifiers were used to examine the performance of significant GM connectome features in distinguishing patients with VM from HCs. Results: Compared with HCs, patients with VM exhibited increased clustering coefficient and local efficiency, as well as reduced nodal degree and nodal efficiency in the left superior temporal gyrus (STG). Furthermore, we identified one connected component with decreased morphological connectivity strength, and the involved regions were mainly located in the STG, temporal pole, prefrontal cortex, supplementary motor area, cingulum, fusiform gyrus, and cerebellum. In the VM group, several connections in the identified connected component were correlated with clinical measures (i.e., symptoms and emotional scales); however, these correlations did not survive multiple comparison corrections. A combination of significant graph- and connectivity-based features allowed single-subject classification of VM versus HC with significant accuracy of 77.68%, 77.68%, and 72.32% for the LR, SVM, and RF models, respectively. Conclusion: Patients with VM had aberrant GM connectomes in terms of topological properties and network connections, reflecting potential dizziness, pain, and emotional dysfunctions. The identified features could serve as individualized neuroimaging markers of VM. [ABSTRACT FROM AUTHOR]

Introduction: Delineating subthalamic nucleus (STN) boundaries using microelectrode recordings (MER) and trajectory history is a valuable resource for neurosurgeons, aiding in the accurate and efficient positioning of deep brain stimulation (DBS) electrodes within the STN. Here, we aimed to assess the application of artificial intelligence, specifically Hidden Markov Models (HMM), in the context of STN localization. Methods: A comprehensive search strategy was employed, encompassing electronic databases, including PubMed, EuroPMC, and MEDLINE. This search strategy entailed a combination of controlled vocabulary (e.g., MeSH terms) and free-text keywords pertaining to “artificial intelligence,” “machine learning,” “deep learning,” and “deep brain stimulation.” Inclusion criteria were applied to studies reporting the utilization of HMM for predicting outcomes in DBS, based on structured patient-level health data, and published in the English language. Results: This systematic review incorporated a total of 14 studies. Various machine learning compared wavelet feature to proposed features in diagnosing the STN, with the HMM yielding a diagnostic odds ratio (DOR) of 838.677 (95% CI: 203.309–3459.645). Similarly, the K-Nearest Neighbors (KNN) model produced parameter estimates, including a diagnostic odds ratio of 25.151 (95% CI: 12.270–51.555). Meanwhile, the support vector machine (SVM) model exhibited parameter estimates, with a DOR of 13.959 (95% CI: 10.436–18.671). Conclusions: MER data demonstrates significant variability in neural activity, with studies employing a wide range of methodologies. Machine learning plays a crucial role in aiding STN diagnosis, though its accuracy varies across different approaches. [ABSTRACT FROM AUTHOR]

Background: Voxel-mirrored homotopic connectivity (VMHC) is utilized to assess the functional connectivity of neural networks by quantifying the similarity between corresponding regions in the bilateral hemispheres of the brain. The exploration of VMHC abnormalities in basal ganglia ischemic stroke (BGIS) patients across different cerebral hemispheres has been limited. This study seeks to establish a foundation for understanding the functional connectivity status of both brain hemispheres in BGIS patients through the utilization of VMHC analysis utilizing resting-state functional magnetic resonance imaging (rs-fMRI). Methods: This study examined a total of 38 patients with left basal ganglia ischemic stroke (LBGIS), 44 patients with right basal ganglia ischemic stroke (RBGIS), and 41 individuals in a healthy control (HC) group. Rs-fMRI studies were performed on these patients, and the pre-processed rs-fMRI data were analyzed using VMHC method. Subsequently, the VMHC values were compared between three groups using a one-way ANOVA and post hoc analysis. Correlation analysis with clinical scales was also conducted. Results: The results indicated that compared to the HC group, significant differences were detected in postcentral gyrus, extending to precentral gyrus in both BGIS groups. Post hoc analysis showed that in the pairwise ROI-based comparison, individuals with LBGIS and RBGIS exhibited reduced VMHC values compared to HC groups. There was no significant difference between the LBGIS and RBGIS groups. In the LBGIS group, the VMHC value showed a negative correlation with NIHSS and a positive correlation with BI. Conclusion: The analysis of VMHC in rs-fMRI revealed a pattern of brain functional remodeling in patients with unilateral BGIS, marked by reduced synchronization and coordination between hemispheres. This may contribute to the understanding of the neurological mechanisms underlying motor dysfunction in these patients. [ABSTRACT FROM AUTHOR]