Detecting activations in PET and fMRI: levels of inference and power

The neural basis of sharing information through goal-directed conversation: A hyperscanning functional magnetic resonance imaging study

The human brain maintains internal models of physical and social environments, representing an individual's "subjectivity". Through conversation, two or more individuals share their models and modify them based on the exchange, a process that represents and is referred to as "intersubjectivity." To investigate the neural substrates of this dynamic process, hyperscanning functional magnetic resonance imaging was conducted to test the hypothesis that Inter-Brain Synchronization (IBS) in the default mode network (DMN) is involved in representing intersubjectivity. Twenty-four Japanese-speaking participant pairs played maze games over a two-day period. Each participant pair received a different maze, i.e., a maze with a different pathway to its goal. Although pairs shared a maze, each participant in a pair had only partial knowledge of the maze layout and what they knew about the layout differed. Taking turns, participants moved their pieces to their goals. Since each had only partial information about the pathway, effective communication between partners was important. Behavioral data showed participants' conversation about potential maze piece moves significantly increased as the game proceeded, implying that the exchange for such information was critical. Correspondingly, the DMN increased task-related activation, including the dorsomedial prefrontal cortex (dmPFC) and the bilateral temporoparietal junction (TPJ), extending through the superior temporal sulcus to the temporal pole and the right middle frontal gyrus. Within these areas, the dmPFC and the right TPJ showed task- and partner-specific IBS throughout all games. Thus, the DMN is likely required for representing intersubjectivity, based on internal models shared through real-time conversations.

The leftmost digit change induces a decrease in brain activity related to visuospatial processing: An fMRI study of the price ending effect

Consumers perceive prices that have been slightly reduced from round price as irrationally cheap. This price ending effect is thought to be driven primarily by two factors: the left-digit effect which occurs when a small price drop changes the leftmost digit, and the image effect which stems from the symbolic association of a particular price ending with low prices or sales. Our study aimed to investigate the neural basis of these irrational effects on perceived cheapness using functional magnetic resonance imaging (fMRI). We used five price values in Yen (197, 198, 201, 202, 206; Japanese consumers tend to perceive prices ending in the number 8 as cheap) for fMRI experiment. Participants were asked to rate the price value of a product. The "left-digit effect" was observed based on the deactivation in brain regions associated with visuospatial processing including the left lingual gyrus and posterior middle temporal gyrus, and the right dorsal posterior precuneus and anterior precuneus. From these regions, the degree of deactivation in the right dorsal posterior precuneus was negatively correlated with the irrational perception of cheapness. Furthermore, this region showed negative functional connectivity with the dorsal striatal regions. No regions were found with "the image effect". Our results suggested that a decrease in activity in the regions associated with visuospatial processing suggests that changes in the leftmost digits alter the level of visuospatial attention towards the price, leading to an underestimation of the payment amount. This reduced attention might activate the dorsal striatum driving unconscious purchasing.

Multifractal dynamic changes of spontaneous brain activity in psychiatric disorders: Adult attention deficit-hyperactivity disorder, bipolar disorder, and schizophrenia

It is one of the strategies to study the complexity of spontaneous fluctuation of brain neurons based on resting-state functional magnetic resonance imaging (rs-fMRI), but the multifractal characteristics of spontaneous fluctuation of brain neurons in psychiatric diseases need to be studied. Therefore, this paper will study the multifractal spontaneous brain activity changes in psychiatric disorders using the multifractal detrended fluctuation analysis algorithm based on the UCLA datasets. Specifically: (1) multifractal characteristics in adult attention deficit-hyperactivity disorder (ADHD), bipolar disorder (BP), and schizophrenia (SCHZ); (2) the source of those multifractal characteristics. Results showed that for adult ADHD, BP, and SCHZ, all 6 functional brain regions exhibit multifractal characteristics, and the multifractal spectrum shows a reduction in bell-shaped asymmetry, unlike the intensity of healthy control (HC) asymmetry. Besides, compared with HC, the multifractal sources of all functional brain regions were fat-tail probability distribution and the long-range dependence correlation, but the intensity of fat-tail probability distribution was decreased and the long-range dependence correlation was increased. The results provide a reference for further understanding the complexity of spontaneous fluctuation of neurons in psychiatric disorders.

Neural substrates of choking under pressure: A 7T-fMRI study

Performance decrement under excessive psychological pressure is known as "choking," yet its mechanisms and neural foundations remain underexplored. Hypothesizing that changes in the internal model could induce choking, we conducted a 7 T functional MRI introducing excessive pressure through a rare Jackpot condition that offers high rewards for successful performance. Twenty-nine volunteers underwent a visual reaching task. We monitored practice and main sessions to map the task's internal model through learning. Participants were pre-informed of four potential reward conditions upon success at the beginning of the main session task. The success rates in the Jackpot condition were significantly lower than in other conditions, indicative of choking. During the preparation phase, activations in the cerebellum and the middle temporal visual area (hMT+) were associated with Jackpot-specific failures. The cluster in the cerebellar hemisphere overlapped with the internal model regions identified by a learning-related decrease in activation during the practice session. We observed task-specific functional connectivity between the cerebellum and hMT+. These findings suggest a lack of sensory attenuation when an internal model predicting the outcome of one's actions is preloaded during motor preparation. Within the active inference framework of motor control, choking stems from the cerebellum's internal model modulation by psychological pressure, manifested through improper sensory attenuation.

Cerebellum abnormalities in vascular mild cognitive impairment with depression symptom patients: A multimodal magnetic resonance imaging study

BACKGROUND

Subcortical vascular mild cognitive impairment (svMCI) frequently occurs alongside depression symptoms, significantly affecting patients' quality of life. While cognitive decline and depression symptoms are linked to cerebellar changes, the specific relationship between these changes and cognitive status in svMCI patients with depression symptoms remains unclear.

OBJECTIVE

This study aimed to investigates the gray matter volume and functional alterations in the cerebellum of svMCI patients, with and without depression symptoms, and their correlation with cognitive and depressive symptoms.

METHODS

We enrolled 16 svMCI patients with depression symptoms (svMCI+D), 15 without (svMCI-D), and 12 normal controls (NC). Multimodal MRI scans were conducted, assessing gray matter volume and resting-state functional connectivity (RSFC) in the cerebellum. Correlations between RSFC and clinical scores from the Montreal Cognitive Assessment (MoCA) and Hamilton Depression Scale (HAMD) were analyzed.

RESULTS

Structural analysis indicated gray matter atrophy in left cerebellar lobules I_IV and VI (Cere6.L) in svMCI patients. svMCI+D patients showed reduced RSFC between Cere6.L and left cerebellar region IX and the left superior frontal gyrus (SFGdor.L). Both svMCI+D and svMCI-D groups showed increased RSFC between Cere6.L and the right caudate nucleus. RSFC between Cere6.L and SFGdor.L correlated negatively with HAMD scores in svMCI+D and positively with MoCA scores in svMCI-D. RSFC between Cere6.L and the right caudate nucleus also correlated positively with MoCA in the svMCI-D.

CONCLUSION

Cerebellar abnormalities, including the gray matter atrophy and RSFC changes, are associated with svMCI, particularly when depression symptoms are present. These results suggest potential diagnostic and therapeutic implications for svMCI and emphasize the need for further research on the cerebellum's role in cognitive and emotional disorders.

Age-related differences of the time-varying features in the brain functional connectivity and cognitive aging

Brain functional modular organization changes with age. Considering the brain as a dynamic system, recent studies have suggested that time-varying connectivity provides more information on brain functions. However, the spontaneous reconfiguration of modular brain structures over time during aging remains poorly understood. In this study, we investigated the age-related dynamic modular reconfiguration using resting-state functional MRI data (615 participants, aged 18-88 years) from Cam-CAN. We employed a graph-based modularity analysis to investigate modular variability and the transition of nodes from one module to another in modular brain networks across the adult lifespan. Results showed that modular structure exhibits both linear and nonlinear age-related trends. The modular variability is higher in early and late adulthood, with higher modular variability in the association networks and lower modular variability in the primary networks. In addition, the whole-brain transition matrix showed that the times of transition from other networks to the dorsal attention network were the largest. Furthermore, the modular structure was closely related to the number of cognitive components and memory-related cognitive performance, suggesting a potential contribution to flexibility cognitive function. Our findings highlighted the notable dynamic characteristics in large-scale brain networks across the adult lifespan, which enhanced our understanding of the neural substrate in various cognitions during aging. These findings also provided further evidence that dedifferentiation and compensation are the outcomes of functional brain interactions.

Enlargement of the human prefrontal cortex and brain mentalizing network: anatomically homogenous cross-species brain transformation

To achieve a better understanding of the evolution of the large brain in humans, a comparative analysis of species differences in the brains of extant primate species is crucial, as it allows direct comparisons of the brains. We developed a method to achieve anatomically precise region-to-region homologous brain transformations across species using computational neuroanatomy. Utilizing three-dimensional neuroimaging data from humans (Homo sapiens), chimpanzees (Pan troglodytes), and Japanese macaques (Macaca fuscata), along with the anatomical labels of their respective brains, we aimed to create a cross-species average template brain that preserves neuroanatomical correspondence across species. Homologous transformation of the brain from one species to another can be computed using the cross-species average brain. Applying this transformation to human and chimpanzee brains revealed that, compared to chimpanzees, humans had significantly larger and more expanded prefrontal cortex, middle and posterior temporal gyrus, angular gyrus, precuneus, and cortical areas associated with mentalization. This neuroanatomically homologous brain transformation enables the systematic investigation of the similarities and differences in brain anatomy and structure across different species.

Impaired insight in schizophrenia is associated with higher frontoparietal cerebral blood flow: an arterial spin labeling study

Impaired insight into illness occurs in up to 98% of patients with schizophrenia, depending on the stage of illness, and leads to negative clinical outcomes. Previous neuroimaging studies suggest that impaired insight in patients with schizophrenia may be related to structural and functional anomalies in frontoparietal brain regions. To date, limited studies have investigated the association between regional cerebral blood flow (CBF) and impaired insight in schizophrenia. Therefore, we sought to investigate the relationship between regional CBF, as measured by arterial spin labeling (ASL), and impaired insight in participants with schizophrenia. A total of 32 participants were included in the analysis. Impaired insight in patients with schizophrenia was measured using the VAGUS, Self-report (VAGUS-SR). Resting-state regional CBF was measured using pseudo-continuous ASL (pCASL) and extracted using SPM12 and REX toolbox. Whole brain analysis found that impaired insight was associated with higher regional CBF in the right angular gyrus, left supramarginal gyrus, and right superior frontal region when controlling for age, gender, smoking status, and illness severity. The results indicate that impaired insight in schizophrenia is related to regional CBF in frontoparietal areas. These neuroimaging findings can serve as therapeutic targets for intervention, such as with non-invasive brain stimulation.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

DISCUSSION

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

HIGHLIGHTS

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

The left primary motor cortex and cerebellar vermis are critical hubs in bimanual sequential learning

We conducted an fMRI study to investigate the neural basis of bimanual coordination, which is fundamental to upper extremity control. Considering bimanual movement as a combination of bimanual chord formation and sequence control, we hypothesized that the areas with the learning effect of both chord formation and sequence learning are critical in bimanual coordination. We adopted the serial reaction time task (SRTT) to test this hypothesis. Thirty-five healthy right-handed volunteers practiced visually cued bimanual SRTT, including the "mirror" and more complex "parallel" modes of random movements or repeating fixed sequences to separately depict the neural substrates of bimanual posture control for chord formation and those of sequence. Random movements' reaction time (RT) continuously declined, indicating learning of bimanual chord formation. The RT in the sequential condition declined more rapidly than in the random condition, confirming sequence learning. The parallel random conditions evoked a more prominent learning-related decrease of task-related activation in the left M1 and cerebellar vermis than the less difficult mirror random conditions. The left M1 showed learning-related enhancement of functional connectivity with the anterior cingulate cortex during the parallel random conditions compared with the mirror random conditions. Thus, the left M1, anterior cingulate cortex, and cerebellar vermis are related to learning bimanual chord formation. The left M1 and cerebellar vermis also showed sequence-specific learning-related activity increments more prominent in the parallel mode than in the mirror mode. Thus, the left M1 and cerebellar vermis are critical in the bimanual motor learning network.

Cortical gyrification in women and men and the (missing) link to prenatal androgens

Previous studies have reported sex differences in cortical gyrification. Since most cortical folding is principally defined in utero, sex chromosomes as well as gonadal hormones are likely to influence sex-specific aspects of local gyrification. Classic congenital adrenal hyperplasia (CAH) causes high levels of androgens during gestation in females, whereas levels in males are largely within the typical male range. Therefore, CAH provides an opportunity to study the possible effects of prenatal androgens on cortical gyrification. Here, we examined the vertex-wise absolute mean curvature-a common estimate for cortical gyrification-in individuals with CAH (33 women and 20 men) and pair-wise matched controls (33 women and 20 men). There was no significant main effect of CAH and no significant CAH-by-sex interaction. However, there was a significant main effect of sex in five cortical regions, where gyrification was increased in women compared to men. These regions were located on the lateral surface of the brain, specifically left middle frontal (rostral and caudal), right inferior frontal, left inferior parietal, and right occipital. There was no cortical region where gyrification was increased in men compared to women. Our findings do not only confirm prior reports of increased cortical gyrification in female brains but also suggest that cortical gyrification is not significantly affected by prenatal androgen exposure. Instead, cortical gyrification might be determined by sex chromosomes either directly or indirectly-the latter potentially by affecting the underlying architecture of the cortex or the size of the intracranial cavity, which is smaller in women.

Multi-modal morphometric association study of subclinical depressive symptoms using voxel-based morphometry, cortical thickness, and diffusion tensor imaging (DTI)

BACKGROUND

Case-control studies in major depression have established numerous regional grey and white matter effects in fronto-limbic brain regions. Yet, brain structural studies of dimensional depressive psychopathology within the subclinical spectrum are still limited, in particular for multi-modal imaging approaches.

METHODS

Using voxel-based and surface-based morphometry (cortical thickness) in combination with diffusion tensor imaging (DTI) in a large non-clinical sample (N = 300), we correlated grey and white matter structural variation with subclinical depressive symptoms assessed with Beck's Depression inventory (BDI).

RESULTS

We found a significant decrease of axial diffusivity associated with higher BDI scores in the left hippocampal part of the cingulum bundle (p < 0.05, threshold free cluster enhanced [TFCE] p-value) and some grey matter trend results e.g., a non-linear negative correlation of cortical thickness with depressive symptom load in the right pre/postcentral cortex (pFWE = 0.054, family wise error [FWE] peak level corrected) and a trend in grey matter volume decrease in women in the inferior frontal gyrus (pFWE = 0.054).

LIMITATIONS

Since all grey matter effects disappear after FWE correction, we assume more stable effects in a larger, less homogenous sample enriched by help-seeking subjects covering a wider range of subclinical psychopathology.

CONCLUSION

Our study adds correlations between single depressive symptoms and brain structure to a growing literature. Since subclinical depression is increasingly recognised to be relevant in our understanding of manifest depression, early detection and identification of potential brain correlates of minor depressive symptoms has the potential to expand and reveal possible biomarkers and early psychological treatment.

Striato-cortical functional connectivity changes in mild cognitive impairment with Lewy bodies

BACKGROUND

Functional connectivity changes in clinically overt neurodegenerative diseases such as dementia with Lewy bodies have been described, but studies on connectivity changes in the pre-dementia phase are scarce.

OBJECTIVES

We concentrated on evaluating striato-cortical functional connectivity differences between patients with Mild Cognitive Impairment with Lewy bodies and healthy controls and on assessing the relation to cognition.

METHODS

Altogether, we enrolled 77 participants (47 patients, of which 35 met all the inclusion criteria for the final analysis, and 30 age- and gender-matched healthy controls, of which 28 met all the inclusion criteria for the final analysis) to study the seed-based connectivity of the dorsal, middle, and ventral striatum. We assessed correlations between functional connectivity in the regions of between-group differences and neuropsychological scores of interest (visuospatial and executive domains z-scores).

RESULTS

Subjects with Mild Cognitive Impairment with Lewy Bodies, as compared to healthy controls, showed increased connectivity from the dorsal part of the striatum particularly to the bilateral anterior part of the temporal cortex with an association with executive functions.

CONCLUSIONS

We were able to capture early abnormal connectivity within cholinergic and noradrenergic pathways that correlated with cognitive functions known to be linked to cholinergic/noradrenergic deficits. The knowledge of specific alterations may improve our understanding of early neural changes in pre-dementia stages and enhance research of disease modifying therapy.

Brain age prediction across the human lifespan using multimodal MRI data

Measuring differences between an individual's age and biological age with biological information from the brain have the potential to provide biomarkers of clinically relevant neurological syndromes that arise later in human life. To explore the effect of multimodal brain magnetic resonance imaging (MRI) features on the prediction of brain age, we investigated how multimodal brain imaging data improved age prediction from more imaging features of structural or functional MRI data by using partial least squares regression (PLSR) and longevity data sets (age 6-85 years). First, we found that the age-predicted values for each of these ten features ranged from high to low: cortical thickness (R = 0.866, MAE = 7.904), all seven MRI features (R = 0.8594, MAE = 8.24), four features in structural MRI (R = 0.8591, MAE = 8.24), fALFF (R = 0.853, MAE = 8.1918), gray matter volume (R = 0.8324, MAE = 8.931), three rs-fMRI feature (R = 0.7959, MAE = 9.744), mean curvature (R = 0.7784, MAE = 10.232), ReHo (R = 0.7833, MAE = 10.122), ALFF (R = 0.7517, MAE = 10.844), and surface area (R = 0.719, MAE = 11.33). In addition, the significance of the volume and size of brain MRI data in predicting age was also studied. Second, our results suggest that all multimodal imaging features, except cortical thickness, improve brain-based age prediction. Third, we found that the left hemisphere contributed more to the age prediction, that is, the left hemisphere showed a greater weight in the age prediction than the right hemisphere. Finally, we found a nonlinear relationship between the predicted age and the amount of MRI data. Combined with multimodal and lifespan brain data, our approach provides a new perspective for chronological age prediction and contributes to a better understanding of the relationship between brain disorders and aging.

Functional correlates of cognitive abilities vary with age in pediatric multiple sclerosis

BACKGROUND

Pediatric multiple sclerosis (PedMS) can hamper brain maturation. Aim of this study was to assess the neuropsychological profile of PedMS patients and their resting-state functional connectivity (RS FC).

METHODS

We assessed intelligence quotient (IQ), executive speed, and language in 76 PedMS patients. On a 3.0T scanner RS FC of brain networks was estimated with a seed-based analysis (subset of 58 right-handed PedMS patients and 22 matched healthy controls). Comparisons were run between controls and PedMS (whole cohort and by age).

RESULTS

Ninety-five% of patients had normal IQ. The highest rate of failure was observed in executive speed. PedMS showed reduced RS FC in all networks than controls, especially in the basal ganglia. In younger patients (<16-year-old, n = 32) reduced RS FC in the basal ganglia, language, and sensorimotor networks associated with poorer cognitive performance (p < 0.05; r range: 0.39; 0.56). Older patients (≥16-year-old, n = 26) showed increased RS FC in the basal ganglia, default-mode, sensorimotor, executive, and language networks, associated with poorer performance in executive speed and language abilities (p < 0.05; r range: -0.40; -0.59). In both groups, lower RS FC of the caudate nucleus associated with poorer executive speed.

CONCLUSIONS

The effect of PedMS on RS FC is clinically relevant and differs according to patients' age.

Mapping Gilles de la Tourette syndrome through the distress and relief associated with tic-related behaviors: an fMRI study

Personal distress associated with tic urges or inhibition and relief associated with tic production are defining features of the personal experience in Gilles de la Tourette syndrome (GTS). These affective phenomena have not been studied using fMRI, hindering our understanding of GTS pathophysiology and possible treatments. Here, we present a novel cross-sectional fMRI study designed to map tic-related phenomenology using distress and relief as predicting variables. We adopted a mental imagery approach and dissected the brain activity associated with different phases of tic behaviors, premonitory urges, and the ensuing tic execution or inhibition: these were compared with the mental simulation of "relaxed situations" and pre-determined stereotyped motor behaviors. We then explored whether the ensuing brain patterns correlated with the distress or relief perceived for the different phases of the tasks. Patients experienced a higher level of distress during the imagery of tic-triggering scenarios and no relief during tic inhibition. On the other hand, patients experienced significant relief during tic imagery. Distress during tic-triggering scenarios and relief during tic imagery were significantly correlated. The distress perceived during urges correlated with increased activation in cortical sensorimotor areas, suggesting a motor alarm. Conversely, relief during tic execution was positively associated with the activity of a subcortical network. The activity of the putamen was associated with both distress during urges and relief during tic execution. These findings highlight the importance of assessing the affective component of tic-related phenomenology. Subcortical structures may be causally involved in the affective component of tic pathophysiology, with the putamen playing a central role in both tic urge and generation. We believe that our results can be readily translated into clinical practice for the development of personalized treatment plans tailored to each patient's unique needs.

Multifractal long-range dependence pattern of functional magnetic resonance imaging in the human brain at rest

Long-range dependence is a prevalent phenomenon in various biological systems that characterizes the long-memory effect of temporal fluctuations. While recent research suggests that functional magnetic resonance imaging signal has fractal property, it remains unknown about the multifractal long-range dependence pattern of resting-state functional magnetic resonance imaging signals. The current study adopted the multifractal detrended fluctuation analysis on highly sampled resting-state functional magnetic resonance imaging scans to investigate long-range dependence profile associated with the whole-brain voxels as specific functional networks. Our findings revealed the long-range dependence's multifractal properties. Moreover, long-term persistent fluctuations are found for all stations with stronger persistency in whole-brain regions. Subsets with large fluctuations contribute more to the multifractal spectrum in the whole brain. Additionally, we found that the preprocessing with band-pass filtering provided significantly higher reliability for estimating long-range dependence. Our validation analysis confirmed that the optimal pipeline of long-range dependence analysis should include band-pass filtering and removal of daily temporal dependence. Furthermore, multifractal long-range dependence characteristics in healthy control and schizophrenia are different significantly. This work has provided an analytical pipeline for the multifractal long-range dependence in the resting-state functional magnetic resonance imaging signal. The findings suggest differential long-memory effects in the intrinsic functional networks, which may offer a neural marker finding for understanding brain function and pathology.

Premovement activity in the mesocortical system links peak force but not initiation of force generation under incentive motivation

Motivation facilitates motor performance; however, the neural substrates of the psychological effects on motor performance remain unclear. We conducted a functional magnetic resonance imaging experiment while human subjects performed a ready-set-go task with monetary incentives. Although subjects were only motivated to respond quickly, increasing the incentives improved not only reaction time but also peak grip force. However, the trial-by-trial correlation between reaction time and peak grip force was weak. Extensive areas in the mesocortical system, including the ventral midbrain (VM) and cortical motor-related areas, exhibited motivation-dependent activity in the premovement "Ready" period when the anticipated monetary reward was displayed. This premovement activity in the mesocortical system correlated only with subsequent peak grip force, whereas the activity in motor-related areas alone was associated with subsequent reaction time and peak grip force. These findings suggest that the mesocortical system linking the VM and motor-related regions plays a role in controlling the peak of force generation indirectly associated with incentives but not the initiation of force generation.

Charting Aging Trajectories of Knee Cartilage Thickness for Early Osteoarthritis Risk Prediction: An MRI Study from the Osteoarthritis Initiative Cohort

Knee osteoarthritis (OA), a prevalent joint disease in the U.S., poses challenges in terms of predicting of its early progression. Although high-resolution knee magnetic resonance imaging (MRI) facilitates more precise OA diagnosis, the heterogeneous and multifactorial aspects of OA pathology remain significant obstacles for prognosis. MRI-based scoring systems, while standardizing OA assessment, are both time-consuming and labor-intensive. Current AI technologies facilitate knee OA risk scoring and progression prediction, but these often focus on the symptomatic phase of OA, bypassing initial-stage OA prediction. Moreover, their reliance on complex algorithms can hinder clinical interpretation. To this end, we make this effort to construct a computationally efficient, easily-interpretable, and state-of-the-art approach aiding in the radiographic OA (rOA) auto-classification and prediction of the incidence and progression, by contrasting an individual's cartilage thickness with a similar demographic in the rOA-free cohort. To better visualize, we have developed the toolset for both prediction and local visualization. A movie demonstrating different subtypes of dynamic changes in local centile scores during rOA progression is available at https://tli3.github.io/KneeOA/. Specifically, we constructed age-BMI-dependent reference charts for knee OA cartilage thickness, based on MRI scans from 957 radiographic OA (rOA)-free individuals from the Osteoarthritis Initiative cohort. Then we extracted local and global centiles by contrasting an individual's cartilage thickness to the rOA-free cohort with a similar age and BMI. Using traditional boosting approaches with our centile-based features, we obtain rOA classification of KLG ≤ 1 versus KLG = 2 (AUC = 0.95, F1 = 0.89), KLG ≤ 1 versus KLG ≥ 2 (AUC = 0.90, F1 = 0.82) and prediction of KLG2 progression (AUC = 0.98, F1 = 0.94), rOA incidence (KLG increasing from < 2 to ≥ 2; AUC = 0.81, F1 = 0.69) and rOA initial transition (KLG from 0 to 1; AUC = 0.64, F1 = 0.65) within a future 48-month period. Such performance in classifying KLG ≥ 2 matches that of deep learning methods in recent literature. Furthermore, its clinical interpretation suggests that cartilage changes, such as thickening in lateral femoral and anterior femoral regions and thinning in lateral tibial regions, may serve as indicators for prediction of rOA incidence and early progression. Meanwhile, cartilage thickening in the posterior medial and posterior lateral femoral regions, coupled with a reduction in the central medial femoral region, may signify initial phases of rOA transition.

How images of food become cravingly salient in obesity

OBJECTIVE

This case-control study was aimed at testing two main hypotheses: (i) obesity is characterized by neurofunctional alterations within the mesocorticolimbic reward system, a brain network originating from the midbrain ventral tegmental area (VTA); and (ii) these alterations are associated with a bias for food-related stimuli and craving.

METHODS

Normal-weight individuals and individuals with obesity underwent a resting-state functional magnetic resonance imaging scan and the assessment of impulsivity, food craving, appetite, and implicit bias for food and non-food stimuli. The VTA was used as a seed to map, for each participant, the strength of its functional connections with the rest of the brain. The between-group difference in functional connectivity was then computed, and brain-behavior correlations were performed.

RESULTS

Individuals with obesity showed hyper-connectivity of the VTA with part of the ventral occipitotemporal cortex, recently found to be specialized for food images, and hypo-connectivity with the left inferior frontal gyrus, devoted to cognitive control. VTA-ventral occipitotemporal cortex connectivity was positively associated with food craving and food-related bias; the reverse correlation was observed for VTA-inferior frontal gyrus connectivity.

CONCLUSIONS

These findings reveal that, in obesity, food-related visual stimuli become cravingly salient through an imbalanced connectivity of the reward system with sensory-specific regions and the frontal cortex involved in cognitive control.

Pupil size reflects activation of subcortical ascending arousal system nuclei during rest

Neuromodulatory nuclei that are part of the ascending arousal system (AAS) play a crucial role in regulating cortical state and optimizing task performance. Pupil diameter, under constant luminance conditions, is increasingly used as an index of activity of these AAS nuclei. Indeed, task-based functional imaging studies in humans have begun to provide evidence of stimulus-driven pupil-AAS coupling. However, whether there is such a tight pupil-AAS coupling during rest is not clear. To address this question, we examined simultaneously acquired resting-state fMRI and pupil-size data from 74 participants, focusing on six AAS nuclei: the locus coeruleus, ventral tegmental area, substantia nigra, dorsal and median raphe nuclei, and cholinergic basal forebrain. Activation in all six AAS nuclei was optimally correlated with pupil size at 0-2 s lags, suggesting that spontaneous pupil changes were almost immediately followed by corresponding BOLD-signal changes in the AAS. These results suggest that spontaneous changes in pupil size that occur during states of rest can be used as a noninvasive general index of activity in AAS nuclei. Importantly, the nature of pupil-AAS coupling during rest appears to be vastly different from the relatively slow canonical hemodynamic response function that has been used to characterize task-related pupil-AAS coupling.

Neural substrates on the judgment of sequential benefits and losses

People need to adapt to situations where they experience sequential benefits (or losses) to ensure survival. This study investigated the neural substrates involved in judgments of sequential benefits and losses. A total of 29 healthy volunteers participated in this study, in which they were asked to participate in a game of purchasing stocks while a magnetic resonance imaging scan was performed. This game had two main types of trials: (1) participants received four sequential financial benefits (or losses), and (2) participants received an equal amount of benefits (or losses) immediately. The results showed greater activation of the orbitofrontal cortex (OFC) when four benefits were received sequentially than when an equal amount of benefits was received immediately. This indicates that the OFC plays a crucial role in the process of mental integration of sequential benefits and interpretation of their valuations. It also showed greater activation of the dorsal striatum when four sequental losses were received than when an equal amount of losses was received immediately. However, it cannot be concluded that activation of the dorsal striatum reflects the differences between sequential and immediate losses, because previous studies have not confirmed this perspective. Therefore, it is necessary to clarify the function of the striatum in processing these losses.

Neural correlates of visual and tactile path integration and their task related modulation

Self-motion induces sensory signals that allow to determine travel distance (path integration). For veridical path integration, one must distinguish self-generated from externally induced sensory signals. Predictive coding has been suggested to attenuate self-induced sensory responses, while task relevance can reverse the attenuating effect of prediction. But how is self-motion processing affected by prediction and task demands, and do effects generalize across senses? In this fMRI study, we investigated visual and tactile self-motion processing and its modulation by task demands. Visual stimuli simulated forward self-motion across a ground plane. Tactile self-motion stimuli were delivered by airflow across the subjects' forehead. In one task, subjects replicated a previously observed distance (Reproduction/Active; high behavioral demand) of passive self-displacement (Reproduction/Passive). In a second task, subjects travelled a self-chosen distance (Self/Active; low behavioral demand) which was recorded and played back to them (Self/Passive). For both tasks and sensory modalities, Active as compared to Passive trials showed enhancement in early visual areas and suppression in higher order areas of the inferior parietal lobule (IPL). Contrasting high and low demanding active trials yielded supramodal enhancement in the anterior insula. Suppression in the IPL suggests this area to be a comparator of sensory self-motion signals and predictions thereof.

Semantic novelty modulates neural responses to visual change across the human brain

Our continuous visual experience in daily life is dominated by change. Previous research has focused on visual change due to stimulus motion, eye movements or unfolding events, but not their combined impact across the brain, or their interactions with semantic novelty. We investigate the neural responses to these sources of novelty during film viewing. We analyzed intracranial recordings in humans across 6328 electrodes from 23 individuals. Responses associated with saccades and film cuts were dominant across the entire brain. Film cuts at semantic event boundaries were particularly effective in the temporal and medial temporal lobe. Saccades to visual targets with high visual novelty were also associated with strong neural responses. Specific locations in higher-order association areas showed selectivity to either high or low-novelty saccades. We conclude that neural activity associated with film cuts and eye movements is widespread across the brain and is modulated by semantic novelty.

Associations of lesion location, structural disconnection, and functional diaschisis with depressive symptoms post stroke

Introduction

Post-stroke depressive symptoms (PSDS) are common and relevant for patient outcome, but their complex pathophysiology is ill understood. It likely involves social, psychological and biological factors. Lesion location is a readily available information in stroke patients, but it is unclear if the neurobiological substrates of PSDS are spatially localized. Building on previous analyses, we sought to determine if PSDS are associated with specific lesion locations, structural disconnection and/or localized functional diaschisis.

Methods

In a prospective observational study, we examined 270 patients with first-ever stroke with the Hospital Anxiety and Depression Scale (HADS) around 6 months post-stroke. Based on individual lesion locations and the depression subscale of the HADS we performed support vector regression lesion-symptom mapping, structural-disconnection-symptom mapping and functional lesion network-symptom-mapping, in a reanalysis of this previously published cohort to infer structure-function relationships.

Results

We found that depressive symptoms were associated with (i) lesions in the right insula, right putamen, inferior frontal gyrus and right amygdala and (ii) structural disconnection in the right temporal lobe. In contrast, we found no association with localized functional diaschisis. In addition, we were unable to confirm a previously described association between depressive symptom load and a network damage score derived from functional disconnection maps.

Discussion

Based on our results, and other recent lesion studies, we see growing evidence for a prominent role of right frontostriatal brain circuits in PSDS.

Geometry-derived statistical significance: A probabilistic framework for detecting true positive findings in MRI data

INTRODUCTION

The false discovery rate (FDR) procedure does not incorporate the geometry of the random field and requires high statistical power at each voxel, a requirement not satisfied by the limited number of participants in imaging studies. Topological FDR, threshold free cluster enhancement (TFCE), and probabilistic TFCE improve statistical power by incorporating local geometry. However, topological FDR requires specifying a cluster defining threshold and TFCE requires specifying transformation weights.

METHODS

Geometry-derived statistical significance (GDSS) procedure overcomes these limitations by combining voxelwise p-values for the test statistic with the probabilities computed from the local geometry for the random field, thereby providing substantially greater statistical power than the procedures currently used to control for multiple comparisons. We use synthetic data and real-world data to compare its performance against the performance of these other, previously developed procedures.

RESULTS

GDSS provided substantially greater statistical power relative to the comparator procedures, which was less variable to the number of participants. GDSS was more conservative than TFCE: that is, it rejected null hypotheses at voxels with much higher effect sizes than TFCE. Our experiments also showed that the Cohen's D effect size decreases as the number of participants increases. Therefore, sample size calculations from small studies may underestimate the participants required in larger studies. Our findings also suggest effect size maps should be presented along with p-value maps for correct interpretation of findings.

CONCLUSIONS

GDSS compared with the other procedures provides considerably greater statistical power for detecting true positives while limiting false positives, especially in small sized (<40 participants) imaging cohorts.

Functional ultrasound imaging reveals 3D structure of orientation domains in ferret primary visual cortex

BACKGROUND AND PURPOSE

The sensory cortex is organized into "maps" that represent sensory space across cortical space. In primary visual cortex (V1) of highly visual mammals, multiple visual feature maps are organized into a functional architecture anchored by orientation domains: regions containing neurons preferring the same stimulus orientation. Although the pinwheel-like structure of orientation domains is well-characterized in the superficial cortical layers in dorsal regions of V1, the 3D shape of orientation domains spanning all 6 cortical layers and across dorsal and ventral regions of V1 has never been revealed.

METHODS

We utilized an emerging research method in neuroscience, functional ultrasound imaging (fUS), to resolve the 3D structure of orientation domains throughout V1 in anesthetized female ferrets. fUS measures blood flow from which neuronal population activity is inferred with improved spatial resolution over fMRI.

RESULTS

fUS activations in response to drifting gratings placed at multiple locations in visual space generated unique activation patterns in V1 and visual thalamus, confirming prior observations that fUS can resolve retinotopy. Iso-orientation domains, determined from clusters of activations driven by large oriented gratings, were cone-shaped and present in both dorsal and ventral regions of V1. The spacing between iso-orientation domains was consistent with spacing measured previously using optical imaging methods.

CONCLUSIONS

Orientation domains are cones rather than columns. Their width and intra-domain distances may vary across dorsal and ventral regions of V1. These findings demonstrate the power of fUS at revealing 3D functional architecture in cortical regions not accessible to traditional surface imaging methods.

The Role of the Left Inferior Frontal Gyrus in Introspection during Verbal Communication

Conversation enables the sharing of our subjective experiences through verbalizing introspected thoughts and feelings. The mentalizing network represents introspection, and successful conversation is characterized by alignment through imitation mediated by the mirror neuron system (MNS). Therefore, we hypothesized that the interaction between the mentalizing network and MNS mediates the conversational exchange of introspection. To test this, we performed hyperscanning functional magnetic resonance imaging during structured real-time conversations between 19 pairs of healthy participants. The participants first evaluated their preference for and familiarity with a presented object and then disclosed it. The control was the object feature identification task. When contrasted with the control, the preference/familiarity evaluation phase activated the dorso-medial prefrontal cortex, anterior cingulate cortex, precuneus, left hippocampus, right cerebellum, and orbital portion of the left inferior frontal gyrus (IFG), which represents introspection. The left IFG was activated when the two participants' statements of introspection were mismatched during the disclosure. Disclosing introspection enhanced the functional connectivity of the left IFG with the bilateral superior temporal gyrus and primary motor cortex, representing the auditory MNS. Thus, the mentalizing system and MNS are hierarchically linked in the left IFG during a conversation, allowing for the sharing of introspection of the self and others.

The underlying neural bases of the reversal error while solving algebraic word problems

Problem solving is a core element in mathematical learning. The reversal error in problem solving occurs when students are able to recognize the information in the statement of comparison word problems, but they reverse the relationship between two variables when building the equations. Functional magnetic resonance images were acquired to identify for the first time the neural bases associated with the reversal error. The neuronal bases linked to this error have been used as inputs in 13 classifiers to discriminate between reversal error and non-reversal error groups. We found brain activation in bilateral fronto-parietal areas in the participants who committed reversal errors, and only left fronto-parietal activation in those who did not, suggesting that the reversal error group needed a greater cognitive demand. Instead, the non-reversal error group seems to show that they have developed solid algebraic knowledge. Additionally, the results showed brain activation in the right middle temporal gyrus when comparing the reversal error vs non-reversal error groups. This activation would be associated with the semantic processing which is required to understand the statement and build the equation. Finally, the classifier results show that the brain areas activated could be considered good biomarkers to help us identify competent solvers.

Leveraging edge-centric networks complements existing network-level inference for functional connectomes

The human connectome is modular with distinct brain regions clustering together to form large-scale communities, or networks. This concept has recently been leveraged in novel inferencing procedures by averaging the edge-level statistics within networks to induce more powerful inferencing at the network level. However, these networks are constructed based on the similarity between pairs of nodes. Emerging work has described novel edge-centric networks, which instead use the similarity between pairs of edges to construct networks. In this work, we use these edge-centric networks in a network-level inferencing procedure and compare this novel method to traditional inferential procedures and the network-level procedure using node-centric networks. We use data from the Human Connectome Project, the Healthy Brain Network, and the Philadelphia Neurodevelopmental Cohort and use a resampling technique with various sample sizes (n=40, 80, 120) to probe the power and specificity of each method. Across datasets and sample sizes, using the edge-centric networks outperforms using node-centric networks for inference as well as edge-level FDR correction and NBS. Additionally, the edge-centric networks were found to be more consistent in clustering effect sizes of similar values as compared to node-centric networks, although node-centric networks often had a lower average within-network effect size variability. Together, these findings suggest that using edge-centric networks for network-level inference can procure relatively powerful results while remaining similarly accurate to the underlying edge-level effects across networks, complementing previous inferential methods.

The complexity of spontaneous brain activity changes in schizophrenia, bipolar disorder, and ADHD was examined using different variations of entropy

Adult attention deficit/hyperactivity disorder (ADHD), schizophrenia (SCHZ), and bipolar disorder (BP) have common symptoms and differences, and the underlying neural mechanisms are still unclear. This article will thoroughly discuss the differences between ADHD, BP, and SCHZ (31 healthy control and 31 ADHD; 34 healthy control and 34 BP; 42 healthy control and 42 SCHZ) relative to healthy subjects in combination with three atlases (et al., the Brainnetome atlas, the Dosenbach atlas, the Power atlas) and seven entropies (et al., approximate entropy (ApEn), sample entropy (SaEn), permutation entropy (PeEn), fuzzy entropy (FuEn), differential entropy (DiffEn), range entropy (RaEn), and dispersion entropy (DispEn)), as well as the prominent significant brain regions, in the hope of giving information that is more suitable for analyzing different diseases' entropy. First, the reliability (et al., intraclass correlation coefficient [ICC]) of seven kinds of entropy is calculated and analyzed by using the MSC dataset (10 subjects and 100 sessions in total) and simulation data; then, seven types of entropy and multiscale entropy expanded based on seven kinds of entropy are used to explore the differences and brain regions of ADHD, BP, and SCHZ relative to healthy subjects; and finally, by verifying the classification performance of the seven information entropies on ADHD, BP, and SCHZ, the effectiveness of the seven entropy methods is evaluated through these three methods. The core brain regions that affect the classification are given, and DiffEn performed best on ADHD, SaEn for BP, and RaEn for SCHZ.

Neural underpinning of Japanese particle processing in non-native speakers

Grammar acquisition by non-native learners (L2) is typically less successful and may produce fundamentally different grammatical systems than that by native speakers (L1). The neural representation of grammatical processing between L1 and L2 speakers remains controversial. We hypothesized that working memory is the primary source of L1/L2 differences, by considering working memory within the predictive coding account, which models grammatical processes as higher-level neuronal representations of cortical hierarchies, generating predictions (forward model) of lower-level representations. A functional MRI study was conducted with L1 Japanese speakers and highly proficient Japanese learners requiring oral production of grammatically correct Japanese particles. We assumed selecting proper particles requires forward model-dependent processes of working memory as their functions are highly context-dependent. As a control, participants read out a visually designated mora indicated by underlining. Particle selection by L1/L2 groups commonly activated the bilateral inferior frontal gyrus/insula, pre-supplementary motor area, left caudate, middle temporal gyrus, and right cerebellum, which constituted the core linguistic production system. In contrast, the left inferior frontal sulcus, known as the neural substrate of verbal working memory, showed more prominent activation in L2 than in L1. Thus, the working memory process causes L1/L2 differences even in highly proficient L2 learners.

Strategic complexity and cognitive skills affect brain response in interactive decision-making

Deciding the best action in social settings requires decision-makers to consider their and others’ preferences, since the outcome depends on the actions of both. Numerous empirical investigations have demonstrated variability of behavior across individuals in strategic situations. While prosocial, moral, and emotional factors have been intensively investigated to explain this diversity, neuro-cognitive determinants of strategic decision-making and their relation with intelligence remain mostly unknown. This study presents a new model of the process of strategic decision-making in repeated interactions, first providing a precise measure of the environment’s complexity, and then analyzing how this complexity affects subjects’ performance and neural response. The results confirm the theoretical predictions of the model. The frequency of deviations from optimal behavior is explained by a combination of higher complexity of the strategic environment and cognitive skills of the individuals. Brain response correlates with strategic complexity, but only in the subgroups with higher cognitive skills. Furthermore, neural effects were only observed in a fronto-parietal network typically involved in single-agent tasks (the Multiple Demand Network), thus suggesting that neural processes dealing with cognitively demanding individual tasks also have a central role in interactive decision-making. Our findings contribute to understanding how cognitive factors shape strategic decision-making and may provide the neural pathway of the reported association between strategic sophistication and fluid intelligence.

Improving power in functional magnetic resonance imaging by moving beyond cluster-level inference

Inference in neuroimaging typically occurs at the level of focal brain areas or circuits. Yet, increasingly, well-powered studies paint a much richer picture of broad-scale effects distributed throughout the brain, suggesting that many focal reports may only reflect the tip of the iceberg of underlying effects. How focal versus broad-scale perspectives influence the inferences we make has not yet been comprehensively evaluated using real data. Here, we compare sensitivity and specificity across procedures representing multiple levels of inference using an empirical benchmarking procedure that resamples task-based connectomes from the Human Connectome Project dataset (∼1,000 subjects, 7 tasks, 3 resampling group sizes, 7 inferential procedures). Only broad-scale (network and whole brain) procedures obtained the traditional 80% statistical power level to detect an average effect, reflecting >20% more statistical power than focal (edge and cluster) procedures. Power also increased substantially for false discovery rate- compared with familywise error rate-controlling procedures. The downsides are fairly limited; the loss in specificity for broad-scale and FDR procedures was relatively modest compared to the gains in power. Furthermore, the broad-scale methods we introduce are simple, fast, and easy to use, providing a straightforward starting point for researchers. This also points to the promise of more sophisticated broad-scale methods for not only functional connectivity but also related fields, including task-based activation. Altogether, this work demonstrates that shifting the scale of inference and choosing FDR control are both immediately attainable and can help remedy the issues with statistical power plaguing typical studies in the field.

The influence of insulin on anticipation and consummatory reward to food intake: A functional imaging study on healthy normal weight and overweight subjects employing intranasal insulin delivery

Aberrant responses within homeostatic, hedonic and cognitive systems contribute to poor appetite control in those with an overweight phenotype. The hedonic system incorporates limbic and meso-limbic regions involved in learning and reward processing, as well as cortical regions involved in motivation, decision making and gustatory processing. Equally important within this complex, multifaceted framework are the cognitive systems involved in inhibitory control and valuation of food choices. Regions within these systems display insulin receptors and pharmacologically increasing central insulin concentrations using intranasal administration (IN-INS) has been shown to significantly reduce appealing food cue responsiveness and also food intake. In this work we describe a placebo-controlled crossover pharmacological functional magnetic resonance imaging (fMRI) study that looks at how IN-INS (160 IU) affects anticipatory and consummatory responses to sweet stimuli and importantly how these responses differ between healthy normal weight and overweight male individuals. This work shows that age matched normal weight and overweight (not obese) individuals respond similarly to both the anticipation and receipt of sweet stimuli under placebo conditions. However, increased central insulin concentrations produce marked differences between groups when anticipating sweet stimuli within the prefrontal cortex and midbrain as well as observed differences in the amygdala during consummatory responses.

Time-varying connectivity of the precuneus and its association with cognition and depressive symptoms in neuromyelitis optica: A pilot MRI study

Background:

The precuneus is involved in cognition and depression; static functional connectivity (SFC) abnormalities of this region have been observed in neuromyelitis optica spectrum disorders (NMOSD). Time-varying functional connectivity (TVC) underpins dynamic variations of brain connectivity.

Objective:

The aim of this study was to explore precuneus SFC and TVC in NMOSD patients and their associations with neuropsychological features.

Methods:

This retrospective study includes 27 NMOSD patients and 30 matched healthy controls undergoing resting state functional magnetic resonance imaging (MRI) and a neuropsychological evaluation of cognitive performance and depressive symptoms. A sliding-window correlation analysis using bilateral precuneus as seed region assessed TVC, which was quantified by the standard deviation of connectivity across windows. Mean connectivity indicated SFC.

Results:

Compared to controls, patients had reduced SFC between precuneus, temporal lobe, putamen and cerebellum, and reduced TVC between precuneus and prefronto-parietal-temporo-occipital cortices and caudate. Patients also had increased intra-precuneal TVC and increased TVC between the precuneus and the temporal cortex. More severe depressive symptoms correlated with increased TVC between the precuneus and the temporal lobe; worse cognitive performance mainly correlated with higher TVC between the precuneus and the parietal lobe.

Conclusion:

TVC rather than SFC of the precuneus correlates with NMOSD neuropsychological features; different TVC abnormalities underlie depressive symptoms and cognitive impairment.

Pupillometry as an integrated readout of distinct attentional networks

The course of pupillary constriction and dilation provides an easy-to-access, inexpensive, and noninvasive readout of brain activity. We propose a new taxonomy of factors affecting the pupil and link these to associated neural underpinnings in an ascending hierarchy. In addition to two well-established low-level factors (light level and focal distance), we suggest two further intermediate-level factors, alerting and orienting, and a higher-level factor, executive functioning. Alerting, orienting, and executive functioning - including their respective underlying neural circuitries - overlap with the three principal attentional networks, making pupil size an integrated readout of distinct states of attention. As a now widespread technique, pupillometry is ready to provide meaningful applications and constitutes a viable part of the psychophysiological toolbox.

Latency structure of BOLD signals within white matter in resting-state fMRI

PURPOSE

Previous studies have demonstrated that BOLD signals in gray matter in resting-state functional MRI (RSfMRI) have variable time lags, representing apparent propagations of fMRI BOLD signals in gray matter. We complemented existing findings and explored the corresponding variations of signal latencies in white matter.

METHODS

We used data from the Brain Genomics Superstruct Project, consisting of 1412 subjects (both sexes included) and divided the dataset into ten equal groups to study both the patterns and reproducibility of latency estimates within white matter. We constructed latency matrices by computing cross-covariances between voxel pairs. We also applied a clustering analysis to identify functional networks within white matter, based on which latency analysis was also performed to investigate lead/lag relationship at network level. A dataset consisting of various sensory states (eyes closed, eyes open and eyes open with fixation) was also included to examine the relationship between latency structure and different states.

RESULTS

Projections of voxel latencies from the latency matrices were highly correlated (average Pearson correlation coefficient = 0.89) across the subgroups, confirming the reproducibility and structure of signal lags in white matter. Analysis of latencies within and between networks revealed a similar pattern of inter- and intra-network communication to that reported for gray matter. Moreover, a dominant direction, from inferior to superior regions, of BOLD signal propagation was revealed by higher resolution clustering. The variations of lag structure within white matter are associated with different sensory states.

CONCLUSIONS

These findings provide additional insight into the character and roles of white matter BOLD signals in brain functions.

The dorsal premotor cortex encodes the step-by-step planning processes for goal-directed motor behavior in humans

The dorsal premotor cortex (PMd) plays an essential role in visually guided goal-directed motor behavior. Although there are several planning processes for achieving goal-directed behavior, the separate neural processes are largely unknown. Here, we created a new visuo-goal task to investigate the step-by-step planning processes for visuomotor and visuo-goal behavior in humans. Using functional magnetic resonance imaging, we found activation in different portions of the bilateral PMd during each processing step. In particular, the activated area for rule-based visuomotor and visuo-goal mapping was located at the ventrorostral portion of the bilateral PMd, that for action plan specification was at the dorsocaudal portion of the left PMd, that for transformation was at the rostral portion of the left PMd, and that for action preparation was at the caudal portion of the bilateral PMd. Thus, the left PMd was involved throughout all of the processes, but the right PMd was involved only in rule-based visuomotor and visuo-goal mapping and action preparation. The locations related to each process were generally spatially separated from each other, but they overlapped partially. These findings revealed that there are functional subregions in the bilateral PMd in humans and these subregions form a functional gradient to achieve goal-directed behavior.

The expected behaviour of random fields in high dimensions: contradictions in the results of Bansal and Peterson [ ]

Bansal and Peterson (2018) found that in simple stationary Gaussian simulations Random Field Theory incorrectly estimates the number of clusters of a Gaussian field that lie above a threshold. Their results contradict the existing literature and appear to have arisen due to errors in their code. Using reproducible code we demonstrate that in their simulations Random Field Theory correctly predicts the expected number of clusters and therefore that many of their results are invalid.

Connectome spatial smoothing (CSS): Concepts, methods, and evaluation

Structural connectomes are increasingly mapped at high spatial resolutions comprising many hundreds-if not thousands-of network nodes. However, high-resolution connectomes are particularly susceptible to image registration misalignment, tractography artifacts, and noise, all of which can lead to reductions in connectome accuracy and test-retest reliability. We investigate a network analogue of image smoothing to address these key challenges. Connectome Spatial Smoothing (CSS) involves jointly applying a carefully chosen smoothing kernel to the two endpoints of each tractography streamline, yielding a spatially smoothed connectivity matrix. We develop computationally efficient methods to perform CSS using a matrix congruence transformation and evaluate a range of different smoothing kernel choices on CSS performance. We find that smoothing substantially improves the identifiability, sensitivity, and test-retest reliability of high-resolution connectivity maps, though at a cost of increasing storage burden. For atlas-based connectomes (i.e. low-resolution connectivity maps), we show that CSS marginally improves the statistical power to detect associations between connectivity and cognitive performance, particularly for connectomes mapped using probabilistic tractography. CSS was also found to enable more reliable statistical inference compared to connectomes without any smoothing. We provide recommendations for optimal smoothing kernel parameters for connectomes mapped using both deterministic and probabilistic tractography. We conclude that spatial smoothing is particularly important for the reliability of high-resolution connectomes, but can also provide benefits at lower parcellation resolutions. We hope that our work enables computationally efficient integration of spatial smoothing into established structural connectome mapping pipelines.

The Neural Correlates of Semantic and Grammatical Encoding During Sentence Production in a Second Language: Evidence From an fMRI Study Using Structural Priming

Japanese English learners have difficulty speaking Double Object (DO; give B A) than Prepositional Object (PO; give A to B) structures which neural underpinning is unknown. In speaking, syntactic and phonological processing follow semantic encoding, conversion of non-verbal mental representation into a structure suitable for expression. To test whether DO difficulty lies in linguistic or prelinguistic process, we conducted functional magnetic resonance imaging. Thirty participants described cartoons using DO or PO, or simply named them. Greater reaction times and error rates indicated DO difficulty. DO compared with PO showed parieto-frontal activation including left inferior frontal gyrus, reflecting linguistic process. Psychological priming in PO produced immediately after DO and vice versa compared to after control, indicated shared process between PO and DO. Cross-structural neural repetition suppression was observed in occipito-parietal regions, overlapping the linguistic system in pre-SMA. Thus DO and PO share prelinguistic process, whereas linguistic process imposes overload in DO.

Neural substrates of accurate perception of time duration: A functional magnetic resonance imaging study

Time duration, an essential feature of the physical world, is perceived and cognitively interpreted subjectively. While this perception is deeply connected with arousal and interoceptive signals, the underlying neural mechanisms remain elusive. As the insula is critical for integrating information from the external world with the organism's inner state, we hypothesized that it might have a central role in the perception of time duration and contribute to its estimation accuracy. We conducted a functional magnetic resonance imaging study with 27 healthy participants performing temporal duration and pitch bisection tasks that used the same stimuli. By comparison with two referents with short and long duration in the time range of 1 s (close to the heart rate period), or low and high pitch, participants had to decide whether target stimuli were closer in duration or pitch to the referent stimuli. The temporal bisection point between short and long duration perception was obtained through a psychometric response curve analysis for each participant. The deviation between the bisection point and the average of reference stimuli durations was used as a marker of duration accuracy. Duration discrimination-specific activation, contrasted to pitch discrimination, was found in the dorsomedial prefrontal cortex, bilateral cerebellum, and right anterior insular cortex (AIC), extending to the inferior frontal gyrus (IFG), inferior parietal lobule, and frontal pole. The activity in the right AIC and IFG was positively correlated with the accuracy of duration discrimination. The right AIC is known to be related to the reproduction of duration, whereas the right IFG is involved in categorical decisions. Thus, the comparison between the referent durations reproduced in the AIC and the target duration may occur in the right IFG. We conclude that the right AIC and IFG contribute to the accurate perception of temporal duration.

Neural substrates of shared visual experiences: a hyperscanning fMRI study

Sharing experience is a fundamental human social cognition. Since visual experience is a mental state directed toward the world, we hypothesized that sharing visual experience is mediated by joint attention (JA) for sharing directedness and mentalizing for mental state inferences. We conducted a hyperscanning functional magnetic resonance imaging with 44 healthy adult volunteers to test this hypothesis. We employed spoken-language-cued spatial and feature-based JA tasks. The initiator attracts the partner's attention by a verbal command to a spatial location or an object feature to which the responder directs their attention. Pair-specific inter-individual neural synchronization of task-specific activities was found in the right anterior insular cortex (AIC)-inferior frontal gyrus (IFG) complex, the core node of JA and salience network, and the right posterior superior temporal sulcus, which represents the shared categories of the target. The right AIC-IFG also showed inter-individual synchronization of the residual time-series data, along with the right temporoparietal junction and dorsomedial prefrontal cortex-the core components for mentalization and the default mode network (DMN). This background synchronization represents sharing the belief of sharing the situation. Thus, shared visual experiences are represented by coherent coordination between the DMN and salience network linked through the right AIC-IFG.

Distinct Patterns of Brain Metabolism in Patients at Risk of Sudden Unexpected Death in Epilepsy

Objective: To characterize regional brain metabolic differences in patients at high risk of sudden unexpected death in epilepsy (SUDEP), using fluorine-18-fluorodeoxyglucose positron emission tomography (¹⁸FDG-PET).

Methods: We studied patients with refractory focal epilepsy at high (n = 56) and low (n = 69) risk of SUDEP who underwent interictal ¹⁸FDG-PET as part of their pre-surgical evaluation. Binary SUDEP risk was ascertained by thresholding frequency of focal to bilateral tonic-clonic seizures (FBTCS). A whole brain analysis was employed to explore regional differences in interictal metabolic patterns. We contrasted these findings with regional brain metabolism more directly related to frequency of FBTCS.

Results: Regions associated with cardiorespiratory and somatomotor regulation differed in interictal metabolism. In patients at relatively high risk of SUDEP, fluorodeoxyglucose (FDG) uptake was increased in the basal ganglia, ventral diencephalon, midbrain, pons, and deep cerebellar nuclei; uptake was decreased in the left planum temporale. These patterns were distinct from the effect of FBTCS frequency, where increasing frequency was associated with decreased uptake in bilateral medial superior frontal gyri, extending into the left dorsal anterior cingulate cortex.

Significance: Regions critical to cardiorespiratory and somatomotor regulation and to recovery from vital challenges show altered interictal metabolic activity in patients with frequent FBTCS considered to be at relatively high-risk of SUDEP, and shed light on the processes that may predispose patients to SUDEP.

Cognitive control affects motor learning through local variations in GABA within the primary motor cortex

The primary motor cortex (M1) is crucial for motor learning; however, its interaction with other brain areas during motor learning remains unclear. We hypothesized that the fronto-parietal execution network (FPN) provides learning-related information critical for the flexible cognitive control that is required for practice. We assessed network-level changes during sequential finger tapping learning under speed pressure by combining magnetic resonance spectroscopy and task and resting-state functional magnetic resonance imaging. There was a motor learning-related increase in preparatory activity in the fronto-parietal regions, including the right M1, overlapping the FPN and sensorimotor network (SMN). Learning-related increases in M1-seeded functional connectivity with the FPN, but not the SMN, were associated with decreased GABA/glutamate ratio in the M1, which were more prominent in the parietal than the frontal region. A decrease in the GABA/glutamate ratio in the right M1 was positively correlated with improvements in task performance (p = 0.042). Our findings indicate that motor learning driven by cognitive control is associated with local variations in the GABA/glutamate ratio in the M1 that reflects remote connectivity with the FPN, representing network-level motor sequence learning formations.

Moderated t-tests for group-level fMRI analysis

In recent years, there has been significant criticism of functional magnetic resonance imaging (fMRI) studies with small sample sizes. The argument is that such studies have low statistical power, as well as reduced likelihood for statistically significant results to be true effects. The prevalence of these studies has led to a situation where a large number of published results are not replicable and likely false. Despite this growing body of evidence, small sample fMRI studies continue to be regularly performed; likely due to the high cost of scanning. In this report we investigate the use of a moderated t-statistic for performing group-level fMRI analysis to help alleviate problems related to small sample sizes. The proposed approach, implemented in the popular R-package LIMMA (linear models for microarray data), has found wide usage in the genomics literature for dealing with similar issues. Utilizing task-based fMRI data from the Human Connectome Project (HCP), we compare the performance of the moderated t-statistic with the standard t-statistic, as well as the pseudo t-statistic commonly used in non-parametric fMRI analysis. We find that the moderated t-test significantly outperforms both alternative approaches for studies with sample sizes less than 40 subjects. Further, we find that the results were consistent both when using voxel-based and cluster-based thresholding. We also introduce an R-package, LIMMI (linear models for medical images), that provides a quick and convenient way to apply the method to fMRI data.

Evaluation of the early-phase [18F]AV45 PET as an optimal surrogate of [18F]FDG PET in ageing and Alzheimer's clinical syndrome

Dual-phase [18F]AV45 positron emission tomography (PET) is highly promising in the assessment of neurodegenerative diseases, allowing to obtain information on both neurodegeneration (early-phase; eAV45) and amyloid deposition (late-phase; lAV45) which are highly complementary; yet eAV45 needs further evaluation. This study aims at validating eAV45 as an optimal proxy of [18F]FDG PET in a large mixed-population of healthy ageing and Alzheimer's clinical syndrome participants (n = 191) who had [18F]FDG PET, eAV45 and lAV45 scans. We found early time frame 0-4 min to give maximal correlation with [18F]FDG PET and minimal correlation with lAV45. Moreover, maximal overlap of [18F]FDG PET versus eAV45 associations with clinical diagnosis and cognition was obtained with pons scaling. Across reference regions, classification performance between clinical subgroups was similar for both eAV45 and [18F]FDG PET. These findings highlight the optimal use of eAV45 to assess neurodegeneration as a validated proxy of [18F]FDG PET. On top of this purpose, this study showed that combined [18F]AV45 PET dual-biomarker even outperformed [18F]FDG PET or lAV45 alone.