Constrained linear basis sets for HRF modelling using Variational Bayes

Evidence for control of cerebral neurovascular function by circulating platelets in healthy older adults

Platelets play a vital role in preventing haemorrhage through haemostasis, but complications arise when platelets become overly reactive, leading to pathophysiology such as atherothrombosis. Elevated haemostatic markers are linked to dementia and predict its onset in long-term studies. Despite epidemiological evidence, the mechanism linking haemostasis with early brain pathophysiology remains unclear. Here, we aimed to determine whether a mechanistic association exists between platelet function and cerebral neurovascular function in 52 healthy mid- to older-age adults. To do this, we combined, for the first time, magnetic resonance imaging of cerebral neurovascular function, peripheral vascular physiology and in vitro platelet assaying. We show an association between platelet reactivity and cerebral neurovascular function that is both independent of vascular reactivity and mechanistically specific: Distinct platelet signalling mechanisms (ADP, collagen-related peptide, thrombin receptor activator peptide 6) were associated with different physiological components of the haemodynamic response to neuronal (visual) stimulation (full-width half-maximum, time to peak, area under the curve), an association that was not mediated by peripheral vascular effects. This finding challenges the previous belief that systemic vascular health determines the vascular component of cerebral neurovascular function, highlighting a specific link between circulating platelets and the neurovascular unit. Because altered cerebral neurovascular function marks the initial stages of neurodegenerative pathophysiology, understanding this novel association is now imperative, with the potential to lead to a significant advancement in our comprehension of early dementia pathophysiology. KEY POINTS: Haemostasis (platelet function) has been linked to the early stages of dementia, but the precise mechanisms are not well understood. This study considers whether a causal mechanism exists through atherothrombotic effects on the vasculature which can in turn affect brain health, or through platelet-specific interactions with brain physiology. Here, we show that elevated platelet reactivity is associated with blunted (delayed, shorter and smaller) cerebral blood flow responses to neuronal activation in healthy middle-aged and older adults. However, the association between platelet reactivity and cerebral neurovascular function was not mediated by systemic vascular reactivity. This finding challenges the previous belief that systemic vascular health determines the vascular component of cerebral neurovascular function, highlighting a specific link between circulating platelets and the neurovascular unit in early dementia pathophysiology.

Simultaneous measurement of cerebral blood flow and cerebrospinal fluid flow using pseudo-continuous arterial spin labeling

In the brain clearance system, the movement of cerebrospinal fluid (CSF) plays a key role in processing waste products. Previous studies have shown that CSF flow interacts significantly with cerebral blood flow (CBF) during brain waste clearance, but there are no simultaneous measurements and comparisons of these two metrics in humans. This study introduces a novel method for simultaneously measuring CSF pulsatile movement and CBF using pseudo-continuous arterial spin labeling (pCASL) MRI. We conducted a comparative analysis of the correlation between CBF and CSF pulsatile movement in human subjects during breath-holding and motor task conditions. Our findings demonstrate the effectiveness of our proposed technique in measuring CSF pulsatile movement, as validated by comparing results with phase-contrast MRI at corresponding locations. Importantly, we observed a robust positive correlation between CBF and CSF pulsation concurrently measured through pCASL during breath-holding. Furthermore, through inter-subject comparisons of regional CBF and CSF pulsation, we established that higher blood perfusion in putamen, caudate, and pallidum regions, which are included in basal ganglia structure, corresponds to greater CSF pulsatile movement. Our motor tasks significantly increased CBF in the motor cortex, and CSF pulsation measured in the dorsal part around cisterna magna showed a decreasing tendency in the motor condition compared to the resting state, aligning with the Monroe-Kelly doctrine. Accordingly, these results demonstrate the feasibility of simultaneous measurement of CBF and CSF pulsation using the proposed pCASL technique in humans, which warrants further investigation.

An interaction-centric approach for quantifying eye-to-eye reciprocal interaction

This study presents an interaction-centric framework for analytically investigating brain-to-brain dynamics during eye contact, advancing beyond the traditional spectator model. The foundation of the interactor approach is to delineate the interaction. To achieve this, simultaneous brain activity engaged in eye contact was captured using hyperscanning fMRI. The BOLD responses were first divided into eye-to-eye reciprocal interaction and eye-to-face non-reciprocal communication based on the experimental design; then the reciprocal interaction response was further differentiated into sensory-based (exogenous) and mind-based (endogenous) components to characterize agentic interaction. The proposed interactor approach not only determines interaction from dyadic brain states but also computes emergent interactive brain states arising from the interaction. To achieve these, reciprocal interactive fMRI responses were quantified into an interaction matrix, from which interaction-induced communication channels were identified using Correspondence Analysis, and information flow within those channels was measured with Mutual Information. The advantage of the interactor approach is its ability to reveal emergent dyadic brain states that a spectator approach cannot fully unravel. When applied to parent-child eye contact, this method confirmed existing developmental findings, clarified previous inconsistencies, and uncovered new insights into how reciprocal social engagement shapes brain function.

Towards whole brain mapping of the haemodynamic response function

Functional magnetic resonance imaging time-series are conventionally processed by linear modelling the evoked response as the convolution of the experimental conditions with a stereotyped haemodynamic response function (HRF). However, the neural signal in response to a stimulus can vary according to task, brain region, and subject-specific conditions. Moreover, HRF shape has been suggested to carry physiological information. The BOLD signal across a range of sensorial and cognitive tasks was fitted using a sine series expansion, and modelled signals were deconvolved, thus giving rise to a task-specific deconvolved HRF (dHRF), which was characterized in terms of amplitude, latency, time-to-peak and full-width at half maximum for each task. We found that the BOLD response shape changes not only across activated regions and tasks, but also across subjects despite the age homogeneity of the cohort. Largest variabilities were observed in mean amplitude and latency across tasks and regions, while time-to-peak and full width at half maximum were relatively more consistent. Additionally, the dHRF was found to deviate from canonicity in several brain regions. Our results suggest that the choice of a standard, uniform HRF may be not optimal for all fMRI analyses and may lead to model misspecifications and statistical bias.

Associations of Device-Measured Physical Activity and Sedentary Time With Neural Responses to Visual Food Cues in Adults: A Functional Magnetic Resonance Imaging Study

Self-reported physical activity is associated with lower brain food cue responsiveness in reward-related regions, but relationships utilizing objective physical activity measurement tools have not been explored. This cross-sectional study examined whether device-measured moderate-to-vigorous intensity physical activity and sedentary time are related to neural responses to visual food cues using functional magnetic resonance imaging. Fifty-one healthy adults (30 men, 21 women; mean ± SD: age 26 ± 6 years; body mass index 24.1 ± 3.0 kg/m2) underwent a functional magnetic resonance imaging scan after an overnight fast while viewing images of high/very high-energy density foods (HED), very low/low-energy density foods (LED) and non-food objects. Free-living moderate-to-vigorous intensity physical activity and sedentary time were measured for seven consecutive days using an ActiGraph wGT3X-BT and activPAL4 accelerometer, respectively. Associations of behavioural variables with brain food cue reactivity were examined in regression models controlling for physiological and behavioural covariates. After adjusting for age, sex, body mass index and device weartime, moderate-to-vigorous intensity physical activity was negatively associated with reactivity to LED versus non-food cues in the precentral gyrus, hippocampus, posterior insula, and amygdala, which may diminish inhibitory-related responses towards healthier lower energy value foods. Time spent in moderate-to-vigorous intensity physical activity was positively associated with reactivity to LED versus non-food cues in the dorsal striatum, a region implicated in food motivation. A positive association was identified between sedentary time and reactivity to HED versus non-food cues in the dorsal division of the posterior cingulate gyrus that has been implicated in attention allocation. These findings suggest that moderate-to-vigorous intensity physical activity may enhance the appeal of and motivation to consume LED foods, whereas sedentary time may promote attention towards HED foods, highlighting the potential for engaging in greater physical activity and less sedentary time to positively influence the central (brain) appetite control system.

Your brain on art, nature, and meditation: a pilot neuroimaging study

Objectives

Exposure to art, nature, or meditation, all transcending human experiences, has beneficial effects on health and wellbeing. Focusing inward or watching art and nature videos elicits positive emotions that can help heal stress-related conditions. In a pilot functional magnetic resonance (fMRI) study, we explored the effect of watching digital art or nature videos compared to contemplating the universal connectedness (also known as transcendental meditation). The instructions were to meditate on the connection to a Universal Soul linked to a sense of expansion and universal connectedness ("one with everything"), which was prompted by a video of the galactic nebula that also controlled for the visual stimuli of the two other conditions.

Methods

Nine healthy adults (mean age = 29; range = 19-42; 5 women) underwent a block design fMRI scan using a Siemens 3T Prisma scanner. The blocks included (1) nature videos, (2) AI-generated digital art ("machine hallucinations" by Refik Anadol), and (3) videos of NASA Webb-produced images of galactic nebulas. Brain oxygen-level dependent (BOLD) images were processed using FSL Version 6.0 and a general linear model (GLM) tested the contrasts between art, nature, and meditation blocks, using a cluster-corrected p-value of 0.05.

Results

Compared to rest, meditation led to BOLD increases in bilateral lateral occipital and fusiform gyri, as well as right postcentral gyrus and hippocampus. Compared to viewing AI-generated digital art, increased BOLD responses during meditation were observed in left parietal and central operculum, and right pre- and postcentral gyri, and compared to nature, in the left parietal operculum, bilateral postcentral and supramarginal gyri, and bilateral lateral occipital cortices.

Conclusion

Meditation compared to rest showed brain activation in regions associated with object, sensory, and memory processing. Meditation compared to nature videos led to activity in bilateral sensory and object processing areas, as well as a left sensory integration region (error monitoring), while meditation compared to art showed activity in left sensory integration and right sensorimotor regions. Further studies are needed to delineate the distinct neural signature and therapeutic effects of inner contemplation using human connection to art, nature, or meditative transcendent practices, in the brain and its potential in clinical applications.

Enabling brain-wide mapping of layer-specific functional connectivity at 3T via layer-dependent fMRI with draining-vein suppression

Layer-dependent functional magnetic resonance imaging (fMRI) is a promising yet challenging approach for investigating layer-specific functional connectivity (FC). Achieving a brain-wide mapping of layer-specific FC requires several technical advancements, including sub-millimeter spatial resolution, sufficient temporal resolution, functional sensitivity, global brain coverage, and high spatial specificity. Although gradient echo (GE)-based echo planar imaging (EPI) is commonly used for rapid fMRI acquisition, it faces significant challenges due to the draining-vein contamination. In this study, we addressed these limitations by integrating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence to suppress vascular signals from the vessels with fast-flowing velocity. The extravascular contamination from pial veins was mitigated using a GE-EPI sequence at 3T rather than 7T, combined with phase regression methods. Additionally, we incorporated advanced techniques, including simultaneous multislice (SMS) acceleration and NOise Reduction with DIstribution Corrected principal component analysis (NORDIC PCA) denoising, to improve temporal resolution, spatial coverage, and signal sensitivity. This resulted in a VN fMRI sequence with 0.9-mm isotropic spatial resolution, a repetition time (TR) of 4 seconds, and brain-wide coverage. The VN gradient strength was determined based on results from a button-pressing task. Using resting-state data, we validated layer-specific FC through seed-based analyses, identifying distinct connectivity patterns in the superficial and deep layers of the primary motor cortex (M1), with significant inter-layer differences. Further analyses with a seed in the primary sensory cortex (S1) demonstrated the reliability of the method. Brain-wide layer-dependent FC analyses yielded results consistent with prior literature, reinforcing the efficacy of VN fMRI in resolving layer-specific functional connectivity. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.

Enhanced generalization and specialization of brain representations of semantic knowledge in healthy aging

Aging is often associated with a decrease in cognitive capacities. However, semantic memory appears relatively well preserved in healthy aging. Both behavioral and neuroimaging studies support the view that changes in brain networks contribute to this preservation of semantic cognition. However, little is known about the role of healthy aging in the brain representation of semantic categories. Here we used pattern classification analyses and computational models to examine the neural representations of living and non-living word concepts. The results demonstrate that brain representations of animacy in healthy aging exhibit increased similarity across categories, even across different task contexts. This pattern of results aligns with the neural dedifferentiation hypothesis that proposes that aging is associated with decreased specificity in brain activity patterns and less efficient neural resource allocation. However, the loss in neural specificity for different categories was accompanied by increased dissimilarity of item-based conceptual representations within each category. Taken together, the age-related patterns of increased generalization and specialization in the brain representations of semantic knowledge may reflect a compensatory mechanism that enables a more efficient coding scheme characterized by both compression and sparsity, thereby helping to optimize the limited neural resources and maintain semantic processing in the healthy aging brain.

Evaluating Models of the Ageing BOLD Response

Neural activity cannot be directly observed using fMRI; rather it must be inferred from the hemodynamic responses that neural activity causes. Solving this inverse problem is made possible through the use of forward models, which generate predicted hemodynamic responses given hypothesised underlying neural activity. Commonly-used hemodynamic models were developed to explain data from healthy young participants; however, studies of ageing and dementia are increasingly shifting the focus toward elderly populations. We evaluated the validity of a range of hemodynamic models across the healthy adult lifespan: from basis sets for the linear convolution models commonly used to analyse fMRI studies, to more advanced models including nonlinear fitting of a parameterised hemodynamic response function (HRF) and nonlinear fitting of a biophysical generative model (hemodynamic modelling, HDM). Using an exceptionally large sample of participants, and a sensorimotor task optimized for detecting the shape of the BOLD response to brief stimulation, we first characterised the effects of age on descriptive features of the response (e.g., peak amplitude and latency). We then compared these to features from more complex nonlinear models, fit to four regions of interest engaged by the task, namely left auditory cortex, bilateral visual cortex, left (contralateral) motor cortex and right (ipsilateral) motor cortex. Finally, we validated the extent to which parameter estimates from these models have predictive validity, in terms of how well they predict age in cross-validated multiple regression. We conclude that age-related differences in the BOLD response can be captured effectively by models with three free parameters. Furthermore, we show that biophysical models like the HDM have predictive validity comparable to more common models, while additionally providing insights into underlying mechanisms, which go beyond descriptive features like peak amplitude or latency, and include estimation of nonlinear effects. Here, the HDM revealed that most of the effects of age on the BOLD response could be explained by an increased rate of vasoactive signal decay and decreased transit rate of blood, rather than changes in neural activity per se. However, in the absence of other types of neural/hemodynamic data, unique interpretation of HDM parameters is difficult from fMRI data alone, and some brain regions in some tasks (e.g., ipsilateral motor cortex) can show responses that are more difficult to capture using current models.

Functional activity and connectivity signatures of ketamine and lamotrigine during negative emotional processing: a double-blind randomized controlled fMRI study

Ketamine is a highly effective antidepressant (AD) that targets the glutamatergic system and exerts profound effects on brain circuits during negative emotional processing. Interestingly, the effects of ketamine on brain measures are sensitive to modulation by pretreatment with lamotrigine, which inhibits glutamate release. Examining the antagonistic effects of ketamine and lamotrigine on glutamate transmission holds promise to identify effects of ketamine that are mediated through changes in the glutamatergic system. Investigating this modulation in relation to both the acute and sustained effects of ketamine on functional activity and connectivity during negative emotional processing should therefore provide novel insights. 75 healthy subjects were investigated in a double-blind, single-dose, randomized, placebo-controlled, parallel-group study with three treatment conditions (ketamine, lamotrigine pre-treatment, placebo). Participants completed an emotional face viewing task during ketamine infusion and 24 h later. Acute ketamine administration decreased hippocampal and Default Mode Network (DMN) activity and increased fronto-limbic coupling during negative emotional processing. Furthermore, while lamotrigine abolished the ketamine-induced increase in functional connectivity, it had no acute effect on activity. Sustained (24 h later) effects of ketamine were only found for functional activity, with a significant reduction in the posterior DMN. This effect was blocked by pretreatment with lamotrigine. Our results suggest that both the acute increases in fronto-limbic coupling and the delayed decrease in posterior DMN activity, but not the attenuated limbic and DMN recruitment after ketamine, are mediated by altered glutamatergic transmission.

Understanding the Changes in Brain Activation When Viewing Products with Differences in Attractiveness

Product design and attractiveness are pivotal factors that determine people's positive reactions when viewing a product and may eventually affect their purchasing choices. Comprehending how people assess product design is crucial. Various studies have explored the link between product attractiveness and consumer behavior, but these were predominantly behavioral studies that offered limited insight into the neural processes underlying perceptions of product attractiveness. Gaining a deeper understanding of these neural mechanisms is valuable, as it enables the formulation of more objective design guidelines based on brain activity, enhancing product appeal and, ultimately, spurring consumer purchases. In our study, we sought to (1) elucidate the neural network engaged when individuals evaluate highly attractive product images, (2) delineate the neural network activated during the evaluation of less attractive product images, and (3) contrast the differences in neural networks between evaluations of highly and less attractive images. We utilized fMRI to investigate the neural activation patterns elicited by viewing product images of varying attractiveness levels. The results indicated distinct neural activations in response to the two types of attractive images. Highly attractive product images elicited activity in the anterior cingulate cortex (ACC) and the occipital pole, whereas less attractive product images stimulated the insula and the inferior frontal gyrus (IFG). The findings of this project provide some of the first insights of its kind and valuable insights for future product design, suggesting that incorporating more positive and rewarding elements could enhance product appeal. This research elucidates the neural correlates of people's responses to product attractiveness, revealing that highly attractive designs activate reward-related brain regions, while less attractive designs engage areas associated with emotional processing. These findings offer a neuroscientific basis for further studies on developing design strategies that align with consumers' innate preferences, potentially transforming product design and marketing practices. By leveraging this knowledge, designers can craft products that not only meet functional needs but also resonate more deeply on an esthetic level, thereby enhancing consumer engagement and purchase likelihood.

A Multimodal Magnetic Resonance Imaging Study on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Feasibility and Clinical Correlation

Background/Objectives: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a neurological disorder characterized by post-exertional malaise. Despite its clinical relevance, the disease mechanisms of ME/CFS are not fully understood. The previous studies targeting brain function or metabolites have been inconclusive in understanding ME/CFS complexity. We combined single-voxel magnetic resonance spectroscopy (SV-MRS) and functional magnetic resonance imaging (fMRI). Our objectives were to examine the feasibility of the multimodal MRI protocol, identify possible differences between ME/CFS and healthy controls (HCs), and relate MRI findings with clinical symptoms. Methods: We enrolled 18 female ME/CFS participants (mean age: 39.7 ± 12.0 years) and five HCs (mean age: 45.6 ± 14.5 years). SV-MRS spectra were acquired from three voxels of interest: the anterior cingulate gyrus (ACC), brainstem (BS), and left dorsolateral prefrontal cortex (L-DLPFC). Whole-brain fMRI used n-back task testing working memory and executive function. The feasibility was assessed as protocol completion rate and time. Group differences in brain metabolites and fMRI activation between ME/CFS and HCs were compared and correlated with behavioral and symptom severity measurements. Results: The completion rate was 100% regardless of participant group without causing immediate fatigue. ME/CFS appeared to show a higher N-Acetylaspartate in L-DLPFC compared to HCs (OR = 8.49, p = 0.040), correlating with poorer fatigue, pain, and sleep quality scores (p's = 0.001-0.015). An increase in brain activation involving the frontal lobe and the brainstem was observed in ME/CFS compared to HCs (Z > 3.4, p's < 0.010). Conclusions: The study demonstrates the feasibility of combining MRS and fMRI to capture neurochemical and neurophysiological features of ME/CFS in female participants. Further research with larger cohorts of more representative sampling and follow-ups is needed to validate these apparent differences between ME/CFS and HCs.

Impact of data processing varieties on DCM estimates of effective connectivity from task-fMRI

Effective connectivity (EC) refers to directional or causal influences between interacting neuronal populations or brain regions and can be estimated from functional magnetic resonance imaging (fMRI) data via dynamic causal modeling (DCM). In contrast to functional connectivity, the impact of data processing varieties on DCM estimates of task-evoked EC has hardly ever been addressed. We therefore investigated how task-evoked EC is affected by choices made for data processing. In particular, we considered the impact of global signal regression (GSR), block/event-related design of the general linear model (GLM) used for the first-level task-evoked fMRI analysis, type of activation contrast, and significance thresholding approach. Using DCM, we estimated individual and group-averaged task-evoked EC within a brain network related to spatial conflict processing for all the parameters considered and compared the differences in task-evoked EC between any two data processing conditions via between-group parametric empirical Bayes (PEB) analysis and Bayesian data comparison (BDC). We observed strongly varying patterns of the group-averaged EC depending on the data processing choices. In particular, task-evoked EC and parameter certainty were strongly impacted by GLM design and type of activation contrast as revealed by PEB and BDC, respectively, whereas they were little affected by GSR and the type of significance thresholding. The event-related GLM design appears to be more sensitive to task-evoked modulations of EC, but provides model parameters with lower certainty than the block-based design, while the latter is more sensitive to the type of activation contrast than is the event-related design. Our results demonstrate that applying different reasonable data processing choices can substantially alter task-evoked EC as estimated by DCM. Such choices should be made with care and, whenever possible, varied across parallel analyses to evaluate their impact and identify potential convergence for robust outcomes.

Temporal Sensitivity for Achromatic and Chromatic Flicker across the Visual Cortex

The retinal ganglion cells (RGCs) receive different combinations of L, M, and S cone inputs and give rise to one achromatic and two chromatic postreceptoral channels. The goal of the current study was to determine temporal sensitivity across the three postreceptoral channels in subcortical and cortical regions involved in human vision. We measured functional magnetic resonance imaging (fMRI) responses at 7 T from three participants (two males, one female) viewing a high-contrast, flickering, spatially uniform wide field (∼140°). Stimulus flicker frequency varied logarithmically between 2 and 64 Hz and targeted the L + M + S, L - M, and S - (L + M) cone combinations. These measurements were used to create temporal sensitivity functions of the primary visual cortex (V1) across eccentricity and spatially averaged responses from the lateral geniculate nucleus (LGN), and the V2/V3, hV4, and V3A/B regions. fMRI responses reflected the known properties of the visual system, including higher peak temporal sensitivity to achromatic versus chromatic stimuli and low-pass filtering between the LGN and V1. Peak temporal sensitivity increased across levels of the cortical visual hierarchy. Unexpectedly, peak temporal sensitivity varied little across eccentricity within area V1. Measures of adaptation and distributed pattern activity revealed a subtle influence of 64 Hz achromatic flicker in area V1, despite this stimulus evoking only a minimal overall response. The comparison of measured cortical responses to a model of the integrated retinal output to our stimuli demonstrates that extensive filtering and amplification are applied to postretinal signals.

Temporal sensitivity for achromatic and chromatic flicker across the visual cortex

The retinal ganglion cells (RGCs) receive different combinations of L, M, and S cone inputs and give rise to one achromatic and two chromatic post-receptoral channels. Beyond the retina, RGC outputs are subject to filtering and normalization along the geniculo-striate pathway, ultimately producing the properties of human vision. The goal of the current study was to determine temporal sensitivity across the three post-receptoral channels in subcortical and cortical regions involved in vision. We measured functional magnetic resonance imaging (MRI) responses at 7 Tesla from three participants (two males, one female) viewing a high-contrast, flickering, spatially-uniform wide field (~140°). Stimulus flicker frequency varied logarithmically between 2 and 64 Hz and targeted the L+M+S, L-M, and S-[L+M] cone combinations. These measurements were used to create temporal sensitivity functions of primary visual cortex (V1) across eccentricity, and spatially averaged responses from lateral geniculate nucleus (LGN), V2/V3, hV4, and V3A/B. Functional MRI responses reflected known properties of the visual system, including higher peak temporal sensitivity to achromatic vs. chromatic stimuli, and low-pass filtering between the LGN and V1. Peak temporal sensitivity increased across levels of the cortical visual hierarchy. Unexpectedly, peak temporal sensitivity varied little across eccentricity within area V1. Measures of adaptation and distributed pattern activity revealed a subtle influence of 64 Hz achromatic flicker in area V1, despite this stimulus evoking only a minimal overall response. Comparison of measured cortical responses to a model of integrated retinal output to our stimuli demonstrates that extensive filtering and amplification is applied to post-retinal signals.

Unconscious Manipulation of Conceptual Representations with Decoded Neurofeedback Impacts Search Behavior

The necessity of conscious awareness in human learning has been a long-standing topic in psychology and neuroscience. Previous research on non-conscious associative learning is limited by the low signal-to-noise ratio of the subliminal stimulus, and the evidence remains controversial, including failures to replicate. Using functional MRI decoded neurofeedback, we guided participants from both sexes to generate neural patterns akin to those observed when visually perceiving real-world entities (e.g., dogs). Importantly, participants remained unaware of the actual content represented by these patterns. We utilized an associative DecNef approach to imbue perceptual meaning (e.g., dogs) into Japanese hiragana characters that held no inherent meaning for our participants, bypassing a conscious link between the characters and the dogs concept. Despite their lack of awareness regarding the neurofeedback objective, participants successfully learned to activate the target perceptual representations in the bilateral fusiform. The behavioral significance of our training was evaluated in a visual search task. DecNef and control participants searched for dogs or scissors targets that were pre-cued by the hiragana used during DecNef training or by a control hiragana. The DecNef hiragana did not prime search for its associated target but, strikingly, participants were impaired at searching for the targeted perceptual category. Hence, conscious awareness may function to support higher-order associative learning. Meanwhile, lower-level forms of re-learning, modification, or plasticity in existing neural representations can occur unconsciously, with behavioral consequences outside the original training context. The work also provides an account of DecNef effects in terms of neural representational drift.

Self-regulating arousal via pupil-based biofeedback

The brain's arousal state is controlled by several neuromodulatory nuclei known to substantially influence cognition and mental well-being. Here we investigate whether human participants can gain volitional control of their arousal state using a pupil-based biofeedback approach. Our approach inverts a mechanism suggested by previous literature that links activity of the locus coeruleus, one of the key regulators of central arousal and pupil dynamics. We show that pupil-based biofeedback enables participants to acquire volitional control of pupil size. Applying pupil self-regulation systematically modulates activity of the locus coeruleus and other brainstem structures involved in arousal control. Furthermore, it modulates cardiovascular measures such as heart rate, and behavioural and psychophysiological responses during an oddball task. We provide evidence that pupil-based biofeedback makes the brain's arousal system accessible to volitional control, a finding that has tremendous potential for translation to behavioural and clinical applications across various domains, including stress-related and anxiety disorders.

Cacao Polyphenol-Rich Dark Chocolate Intake Contributes to Efficient Brain Activity during Cognitive Tasks: A Randomized, Single-Blinded, Crossover, and Dose-Comparison fMRI Study

Cacao polyphenol-enriched dark chocolate may have beneficial effects on human health, such as facilitating maintaining good performance in long-lasting cognitive tasks. This study examined the effects of dark chocolate intake on improving brain function during cognitive tasks using functional magnetic resonance imaging (fMRI). In this randomized, single-blinded, crossover, and dose-comparison study, 26 healthy middle-aged participants ingested dark chocolate (25 g) either with a low concentration (LC) (211.7 mg) or a high concentration (HC) (635 mg) of cacao polyphenols. Thereafter, their brain activities were analyzed during continuous and effortful cognitive tasks relevant to executive functioning using fMRI in two consecutive 15 min sessions (25 and 50 min after ingestion). We observed significant interaction effects between chocolate consumption and brain activity measurement sessions in the left dorsolateral prefrontal cortex and left inferior parietal lobule. After HC chocolate ingestion, these areas showed lower brain activity in the second session than in the first session; however, these areas showed higher activity in the second session after LC chocolate ingestion. These results suggest that cacao polyphenol-enriched dark chocolate enhances the efficient use of cognitive resources by reducing the effort of brain activity.

Organization of sensorimotor activity in anterior cruciate ligament reconstructed individuals: an fMRI conjunction analysis

Introduction

Anterior cruciate ligament reconstruction (ACLR) is characterized by persistent involved limb functional deficits that persist for years despite rehabilitation. Previous research provides evidence of both peripheral and central nervous system adaptations following ACLR. However, no study has compared functional organization of the brain for involved limb motor control relative to the uninvolved limb and healthy controls. The purpose of this study was to examine sensorimotor cortex and cerebellar functional activity overlap and non-overlap during a knee motor control task between groups (ACLR and control), and to determine cortical organization of involved and uninvolved limb movement between groups.

Methods

Eighteen participants with left knee ACLR and 18 control participants performed a knee flexion/extension motor control task during functional magnetic resonance imaging (fMRI). A conjunction analysis was conducted to determine the degree of overlap in brain activity for involved and uninvolved limb knee motor control between groups.

Results

The ACLR group had a statistically higher mean percent signal change in the sensorimotor cortex for the involved > uninvolved contrast compared to the control group. Brain activity between groups statistically overlapped in sensorimotor regions of the cortex and cerebellum for both group contrasts: involved > uninvolved and uninvolved > involved. Relative to the control group, the ACLR group uniquely activated superior parietal regions (precuneus, lateral occipital cortex) for involved limb motor control. Additionally, for involved limb motor control, the ACLR group displayed a medial and superior shift in peak voxel location in frontal regions; for parietal regions, the ACLR group had a more posterior and superior peak voxel location relative to the control group.

Conclusion

ACLR may result in unique activation of the sensorimotor cortex via a cortically driven sensory integration strategy to maintain involved limb motor control. The ACLR group's unique brain activity was independent of strength, self-reported knee function, and time from surgery.

Spatial frequency channels depend on stimulus bandwidth in normal and amblyopic vision: an exploratory factor analysis

The Contrast Sensitivity Function (CSF) is the measure of an observer's contrast sensitivity as a function of spatial frequency. It is a sensitive measure to assess visual function in fundamental and clinical settings. Human contrast sensitivity is subserved by different spatial frequency channels. Also, it is known that amblyopes have deficits in contrast sensitivity, particularly at high spatial frequencies. Therefore, the aim of this study was to assess whether the contrast sensitivity function is subtended by the same spatial frequency channels in control and amblyopic populations. To determine these spatial frequency channels, we performed an exploratory factor analysis on five datasets of contrasts sensitivity functions of amblyopic and control participants measured using either gratings or noise patches, taken from our previous studies. In the range of 0.25-10 c/d, we identified two spatial frequency channels. When the CSF was measured with noise patches, the spatial frequency channels presented very similar tuning in the amblyopic eye and the fellow eye and were also similar to what was observed in controls. The only major difference was that the weight attributed to the high frequency channel was reduced by approximately 50% in the amblyopic eye. However, when the CSF was measured using gratings, the spatial frequency channels of the amblyopic eye were tuned toward lower spatial frequencies. These findings suggest that there is no mechanistic deficit for contrast sensitivity in amblyopia and that amblyopic vision may just be subjected to excessive internal noise and attenuation at higher spatial frequencies, thereby supporting the use of therapeutic strategies that involve rebalancing contrast.

Transdiagnostic phenomena of psychopathology in the context of the RDoC: protocol of a multimodal cross-sectional study

In the past, affective and cognitive processes related to psychopathology have been examined within the boundaries of phenotype-based diagnostic labels, which has led to inconsistent findings regarding their underlying operating principles. Investigating these processes dimensionally in healthy individuals and by means of multiple modalities may provide additional insights into the psychological and neuronal mechanisms at their core. The transdiagnostic phenomena Neuroticism and Rumination are known to be closely linked. However, the exact nature of their relationship remains to be elucidated. The same applies to the associations between Hedonic Capacity, Negativity Bias and different Emotion Regulation strategies.This multimodal cross-sectional study examines the relationship of the transdiagnostic phenomena Neuroticism and Rumination as well as Hedonic Capacity, the Negativity Bias and Emotion Regulation from a RDoC (Research Domain Criteria) perspective. A total of 120 currently healthy subjects (past 12 months) will complete several questionnaires regarding personality, emotion regulation, hedonic capacity, and psychopathologies as well as functional magnetic resonance imaging (fMRI) during cognitive and emotional processing, to obtain data on the circuit, behavioral and self-report level.This study aims to contribute to the understanding of the relationship between cognitive and affective processes associated with psychopathologies as well as their neuronal correlates. Ultimately, a grounded understanding of these processes could guide improvement of diagnostic labels and treatments. Limitations include the cross-sectional design and the limited variability in psychopathology scores due to the restriction of the sample to currently healthy subjects.

Impact of region of interest definition on visual stimulation-based cerebral vascular reactivity functional MRI with a special focus on applications in cerebral amyloid angiopathy

Cerebral vascular reactivity quantified using blood oxygen level-dependent functional MRI in conjuncture with a visual stimulus has been proven to be a potent and early marker for cerebral amyloid angiopathy. This work investigates the influence of different postprocessing methods on the outcome of such vascular reactivity measurements. Three methods for defining the region of interest (ROI) over which the reactivity is measured are investigated: structural (transformed V1), functional (template based on the activation of a subset of subjects), and percentile (11.5 cm³ most responding voxels). Evaluation is performed both in a test-retest experiment in healthy volunteers (N = 12), as well as in 27 Dutch-type cerebral amyloid angiopathy patients and 33 age- and sex-matched control subjects. The results show that the three methods select a different subset of voxels, although all three lead to similar outcome measures in healthy subjects. However, in (severe) pathology, the percentile method leads to higher reactivity measures than the other two, due to circular analysis or "double dipping" by defining a subject-specific ROI based on the strongest responses within each subject. Furthermore, while different voxels are included in the presence of lesions, this does not necessarily result in different outcome measures. In conclusion, to avoid bias created by the method, either a structural or a functional method is recommended. Both of these methods provide similar reactivity measures, although the functional ROI appears to be less reproducible between studies, because slightly different subsets of voxels were found to be included. On the other hand, the functional method did include fewer lesion voxels than the structural method.

Cognitive and affective interaction with somatosensory afference in acupuncture-a specific brain response to compound stimulus

Introduction

Acupuncture is a clinical intervention consisting of multiple stimulus components, including somatosensory stimulation and manipulation of therapeutic context. Existing findings in neuroscience consolidated cognitive modulation to somatosensory afferent process, which could differ from placebo mechanism in brain. Here, we aimed to identify intrinsic process of brain interactions induced by compound stimulus of acupuncture treatment.

Methods

To separately and comprehensively investigate somatosensory afferent and cognitive/affective processes in brain, we implemented a novel experimental protocol of contextual manipulation with somatosensory stimulation (real acupuncture: REAL) and only contextual manipulation (phantom acupuncture: PHNT) for fMRI scan, and conducted independent component (IC)-wise assessment with the concatenated fMRI data.

Results

By our double (experimentally and analytically) dissociation, two ICs (CA1: executive control, CA2: goal-directed sensory process) for cognitive/affective modulation (associated with both REAL and PHNT) and other two ICs (SA1: interoceptive attention and motor-reaction, SA2: somatosensory representation) for somatosensory afference (associated with only REAL) were identified. Moreover, coupling between SA1 and SA2 was associated with a decreased heart rate during stimulation, whereas CA1 was associated with a delayed heart rate decrease post-stimulation. Furthermore, partial correlation network for these components demonstrated a bi-directional interaction between CA1 and SA1/SA2, suggesting the cognitive modulation to somatosensory process. The expectation for the treatment negatively affected CA1 but positively affected SA1 in REAL, whereas the expectation positively affected CA1 in PHNT.

Discussion

These specific cognitive-somatosensory interaction in REAL were differed from vicarious sensation mechanism in PHNT; and might be associated with a characteristic of acupuncture, which induces voluntary attention for interoception. Our findings on brain interactions in acupuncture treatment elucidated the underlying brain mechanisms for compound stimulus of somatosensory afferent and therapeutic contextual manipulation, which might be a specific response to acupuncture.

Neural Correlates of Self-Reported Knee Function in Individuals After Anterior Cruciate Ligament Reconstruction

BACKGROUND

Anterior cruciate ligament (ACL) rupture is a common knee injury among athletes and physically active adults. Despite surgical reconstruction and extensive rehabilitation, reinjuries are common and disability levels are high, even years after therapy and return to activity. Prolonged knee dysfunction may result in part from unresolved neuromuscular deficits of the surrounding joint musculature in response to injury. Indeed, "upstream" neurological adaptations occurring after injury may explain these persistent functional deficits. Despite evidence for injury consequences extending beyond the joint to the nervous system, the link between neurophysiological impairments and patient-reported measures of knee function remains unclear.

HYPOTHESIS

Patterns of brain activation for knee control are related to measures of patient-reported knee function in individuals after ACL reconstruction (ACL-R).

STUDY DESIGN

Cross-sectional study.

LEVEL OF EVIDENCE

Level 3.

METHODS

In this multicenter, cross-sectional study, participants with unilateral ACL-R (n = 25; 10 men, 15 women) underwent task-based functional magnetic resonance imaging testing. Participants performed repeated cycles of open-chain knee flexion/extension. Neural activation patterns during the movement task were quantified using blood oxygen level-dependent (BOLD) signals. Regions of interest were generated using the Juelich Histological Brain Atlas. Pearson product-moment correlations were used to determine the relationship between mean BOLD signal within each brain region and self-reported knee function level, as measured by the International Knee Documentation Committee index. Partial correlations were also calculated after controlling for time from surgery and sex.

RESULTS

Patient-reported knee function was positively and moderately correlated with the ipsilateral secondary somatosensory cortex (r = 0.57, P = 0.005) and the ipsilateral supplementary motor area (r = 0.51, P = 0.01).

CONCLUSION

Increased ipsilateral secondary sensorimotor cortical activity is related to higher perceived knee function.

CLINICAL RELEVANCE

Central nervous system mechanisms for knee control are related to subjective levels of knee function after ACL-R. Increased neural activity may reflect central neuroplastic strategies to preserve knee functionality after traumatic injury.

Modeling the dynamics of cerebrovascular reactivity to carbon dioxide in fMRI under task and resting-state conditions

Conventionally, cerebrovascular reactivity (CVR) is estimated as the amplitude of the hemodynamic response to vascular stimuli, most commonly carbon dioxide (CO₂). While the CVR amplitude has established clinical utility, the temporal characteristics of CVR (dCVR) have been increasingly explored and may yield even more pathology-sensitive parameters. This work is motivated by the current need to evaluate the feasibility of dCVR modeling in various experimental conditions. In this work, we present a comparison of several recently published/utilized model-based deconvolution (response estimation) approaches for estimating the CO₂ response function h(t), including maximum a posteriori likelihood (MAP), inverse logit (IL), canonical correlation analysis (CCA), and basis expansion (using Gamma and Laguerre basis sets). To aid the comparison, we devised a novel simulation framework that incorporates a wide range of SNRs, ranging from 10 to -7 dB, representative of both task and resting-state CO₂ changes. In addition, we built ground-truth h(t) into our simulation framework, overcoming the conventional limitation that the true h(t) is unknown. Moreover, to best represent realistic noise found in fMRI scans, we extracted noise from in-vivo resting-state scans. Furthermore, we introduce a simple optimization of the CCA method (CCA_opt) and compare its performance to these existing methods. Our findings suggest that model-based methods can accurately estimate dCVR even amidst high noise (i.e. resting-state), and in a manner that is largely independent of the underlying model assumptions for each method. We also provide a quantitative basis for making methodological choices, based on the desired dCVR parameters, the estimation accuracy and computation time. The BEL method provided the highest accuracy and robustness, followed by the CCA_opt and IL methods. Of the three, the CCA_opt method has the lowest computational requirements. These findings lay the foundation for wider adoption of dCVR estimation in CVR mapping.

Disruption of the brain-esophagus axis in obese patients with heartburn

Obesity is a risk factor for gastroesophageal reflux disease. Studies addressing the brain-esophagus axis in obese are lacking. In obese with and without heartburn, we assessed: (i) the brain responses to esophageal acid perfusion during functional brain imaging; (ii) esophageal impedance baseline before and after acid perfusion; and (iii) abdominal fat distribution. In this exploratory study, 26 obese underwent functional magnetic resonance imaging (fMRI) of the brain combined with esophageal acid perfusion. Esophageal impedance baseline was determined before and after fMRI, followed by tomographic quantification of the abdominal fat. Among 26 obese (54% men, 39.7 years old, 33.5 kg/m2), there were 17 with heartburn and 9 without heartburn. Before fMRI, the esophageal impedance baseline was lower in obese with heartburn than without heartburn (median 1187 vs. 1890 Ω; P = 0.025). After acid perfusion, impedance baseline decreased in obese with heartburn (from 1187 to 899 Ω; P = 0.011) and was lower in this group than in obese without heartburn (899 vs. 1614 Ω; P = 0.001). fMRI task-residual analysis showed that obese with heartburn presented higher functional connectivity in several brain regions than obese without heartburn. Abdominal fat area did not differ between obese with and without heartburn either for total (72.8 ± 4.4% vs. 70.3 ± 6.0%; P = 0.280), subcutaneous (42.2 ± 9.0% vs. 37.4 ± 9.0%; P = 0.226), or visceral (30.6 ± 7.9% vs. 33.0 ± 7.8%; P = 0.484). In subjects with obesity, the brain-esophagus axis is disrupted centrally with higher functional brain connectivity and peripherally with decreased esophageal mucosa integrity in the presence of heartburn.

Reconstruction of time-shifted hemodynamic response

Regression of voxel time course onto expected response is a standard procedure in functional magnetic resonance imaging that relies on exact onset time and shape of superimposed hemodynamic response functions. Elegant capture of time deviation by time derivative regressors appears complicated by shape distortion and limited to ±1 s, and is usually not exploited for reconstructing the true time-shifted response function together with its magnitude. This analysis of the time-derivative approach provides closed-form functional relations between time shift and regression coefficients that allow for hemodynamic shifts of ±5 s and can explain shape distortion and reconstruction behavior. Reliable absolute latencies were no smaller than 0.6 s in a best-case experiment. Confusions of latency are a previously undiscussed shortcoming where current limitation strategy may eliminate correct latencies and protect incorrect ones.

Evidence suggesting common mechanisms underlie contralateral and ipsilateral negative BOLD responses in human visual cortex

The task-evoked positive BOLD response (PBR) to a unilateral visual hemi-field stimulation is often accompanied by robust and sustained contralateral as well as ipsilateral negative BOLD responses (NBRs) in the visual cortex. The signal characteristics and the neural and/or vascular mechanisms that underlie these two types of NBRs are not completely understood. In this paper, we investigated the properties of these two types of NBRs. We first demonstrated the linearity of both NBRs with respect to stimulus duration. Next, we showed that the hemodynamic response functions (HRFs) of the two NBRs were similar to each other, but significantly different from that of the PBR. Moreover, the subject-wise expressions of the two NBRs were tightly coupled to the degree that the correlation between the two NBRs was significantly higher than the correlation between each NBR and the PBR. However, the activation patterns of the two NBRs did not show a high level of interhemispheric spatial similarity, and the functional connectivity between them was not different than the interhemispheric functional connectivity between the NBRs and PBR. Finally, while attention did modulate both NBRs, the attention-related changes in their HRFs were similar. Our findings suggest that the two NBRs might be generated through common neural and/or vascular mechanisms involving distal/deep brain regions that project to the two hemispheres.

The normative modeling framework for computational psychiatry

Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior, which can then be used to make statistical inferences at the level of the individual. The fields of computational psychiatry and clinical neuroscience have been slow to transition away from patient versus 'healthy' control analytic approaches, probably owing to a lack of tools designed to properly model biological heterogeneity of mental disorders. Normative modeling provides a solution to address this issue and moves analysis away from case-control comparisons that rely on potentially noisy clinical labels. Here we define a standardized protocol to guide users through, from start to finish, normative modeling analysis using the Predictive Clinical Neuroscience toolkit (PCNtoolkit). We describe the input data selection process, provide intuition behind the various modeling choices and conclude by demonstrating several examples of downstream analyses that the normative model may facilitate, such as stratification of high-risk individuals, subtyping and behavioral predictive modeling. The protocol takes ~1-3 h to complete.

Measurement of CSF pulsation from EPI-based human fMRI

It is recently discovered that the glymphatic system and meningeal lymphatic system are the primary routes for the clearance of brain waste products. The CSF flow is part of these systems, facilitating the clearance procedure. Nonetheless, the relationship between CSF flow and brain functional activity has been underexplored. To investigate CSF dynamics and functional brain activity simultaneously, recent studies have proposed a CSF inflow index measured on edge slices (CSFedge) of echo-planar imaging (EPI) based functional magnetic resonance imaging (fMRI), however, it lacks the quantitative aspect of the CSF pulsation. We proposed a new method for quantifying CSF pulsation (CSFpulse) based on an interslice CSF pulsation model in the 4^th ventricle of EPI-based fMRI. The proposed CSFpulse successfully detected the higher CSF flow during the resting state than the typical task states (visual and motor) (p<.05), which is consistent with previous studies based on phase contrast (PC) MRI and CSF volume MRI, while it was not detected in CSFedge based indices or baseline CSF signals in various regions of interest (ROIs). Moreover, CSFpulse demonstrated dynamic functional changes in CSF pulsation: it decreased during the activation-on blocks while it increased during the activation-off blocks. CSFpulse significantly correlated with stroke volume measured using PC MRI, a standard method for CSF pulsation quantification, under the same functional state, while CSFedge based indices or CSF ROIs showed no correlation with the PC MRI stroke volume. Lastly, the correlation of CSFpulse with global BOLD was weaker than that of CSFedge, suggesting that CSFpulse may reflect distinct CSF physiological information that is less affected by global BOLD effects. Based on these results, the proposed CSFpulse provides CSF pulsatility information more accurately in a quantitative manner than CSFedge based indices from the recent CSF studies or the conventional ROI-based analysis. In addition to the high correlation with PC MRI, CSFpulse is much faster than PC MRI and provides information of functional brain activations simultaneously, advantageous over PC MRI or CSF volume MRI. Accordingly, the suggested CSFpulse can be used for investigating intra-subject functional changes in BOLD and CSF pulsation simultaneously and inter-subject CSF pulsation variations based on conventional EPI-based fMRI, which warrants further investigation.

Reproducibility of cerebrovascular reactivity measurements: A systematic review of neuroimaging techniques. J Cereb Blood Flow Metab 2022;42:700-717. [PMID: 34806918 PMCID: PMC9254040 DOI: 10.1177/0271678x211056702]

Cerebrovascular reactivity (CVR), the capacity of the brain to increase cerebral blood flow (CBF) to meet changes in physiological demand, is an important biomarker to evaluate brain health. Typically, this brain "stress test" is performed by using a medical imaging modality to measure the CBF change between two states: at baseline and after vasodilation. However, since there are many imaging modalities and many ways to augment CBF, a wide range of CVR values have been reported. An understanding of CVR reproducibility is critical to determine the most reliable methods to measure CVR as a clinical biomarker. This review focuses on CVR reproducibility studies using neuroimaging techniques in 32 articles comprising 427 total subjects. The literature search was performed in PubMed, Embase, and Scopus. The review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We identified 5 factors of the experimental subjects (such as sex, blood characteristics, and smoking) and 9 factors of the measuring technique (such as the imaging modality, the type of the vasodilator, and the quantification method) that have strong effects on CVR reproducibility. Based on this review, we recommend several best practices to improve the reproducibility of CVR quantification in neuroimaging studies.

Ultrasound localization microscopy and functional ultrasound imaging reveal atypical features of the trigeminal ganglion vasculature

The functional imaging within the trigeminal ganglion (TG) is highly challenging due to its small size and deep localization. This study combined a methodological framework able to dive into the rat trigeminal nociceptive system by jointly providing 1) imaging of the TG blood vasculature at microscopic resolution, and 2) the measurement of hemodynamic responses evoked by orofacial stimulations in anesthetized rats. Despite the small number of sensory neurons within the TG, functional ultrasound imaging was able to image and quantify a strong and highly localized hemodynamic response in the ipsilateral TG, evoked not only by mechanical or chemical stimulations of corneal nociceptive fibers, but also by cutaneous mechanical stimulations of the ophthalmic and maxillary orofacial regions using a von Frey hair. The in vivo quantitative imaging of the TG’s vasculature using ultrasound localization microscopy combined with in toto labelling reveals particular features of the vascularization of the area containing the sensory neurons, that are likely the origin of this strong vaso-trigeminal response. This innovative imaging approach opens the path for future studies on the mechanisms underlying changes in trigeminal local blood flow and evoked hemodynamic responses, key mechanisms for the understanding and treatment of debilitating trigeminal pain conditions.

Visualisation of rat trigeminal ganglia activation during ophthalmic or maxillary nociceptive stimulations shows atypical tortuous vascularisation and a somatotopic hemodynamic response.

Distinct networks coupled with parietal cortex for spatial representations inside and outside the visual field

Our mental representation of egocentric space is influenced by the disproportionate sensory perception of the body. Previous studies have focused on the neural architecture for egocentric representations within the visual field. However, the space representation underlying the body is still unclear. To address this problem, we applied both functional Magnitude Resonance Imaging (fMRI) and Magnetoencephalography (MEG) to a spatial-memory paradigm by using a virtual environment in which human participants remembered a target location left, right, or back relative to their own body. Both experiments showed larger involvement of the frontoparietal network in representing a retrieved target on the left/right side than on the back. Conversely, the medial temporal lobe (MTL)-parietal network was more involved in retrieving a target behind the participants. The MEG data showed an earlier activation of the MTL-parietal network than that of the frontoparietal network during retrieval of a target location. These findings suggest that the parietal cortex may represent the entire space around the self-body by coordinating two distinct brain networks.

Activity-dependent spinal cord neuromodulation rapidly restores trunk and leg motor functions after complete paralysis

Epidural electrical stimulation (EES) targeting the dorsal roots of lumbosacral segments restores walking in people with spinal cord injury (SCI). However, EES is delivered with multielectrode paddle leads that were originally designed to target the dorsal column of the spinal cord. Here, we hypothesized that an arrangement of electrodes targeting the ensemble of dorsal roots involved in leg and trunk movements would result in superior efficacy, restoring more diverse motor activities after the most severe SCI. To test this hypothesis, we established a computational framework that informed the optimal arrangement of electrodes on a new paddle lead and guided its neurosurgical positioning. We also developed software supporting the rapid configuration of activity-specific stimulation programs that reproduced the natural activation of motor neurons underlying each activity. We tested these neurotechnologies in three individuals with complete sensorimotor paralysis as part of an ongoing clinical trial ( www.clinicaltrials.gov identifier NCT02936453). Within a single day, activity-specific stimulation programs enabled these three individuals to stand, walk, cycle, swim and control trunk movements. Neurorehabilitation mediated sufficient improvement to restore these activities in community settings, opening a realistic path to support everyday mobility with EES in people with SCI.

Investigating the specificity of the neurologic pain signature against breathlessness and finger opposition

ABSTRACT

Brain biomarkers of pain, including pain-predictive "signatures" based on brain activity, can provide measures of neurophysiological processes and potential targets for interventions. A central issue relates to the specificity of such measures, and understanding their current limits will both advance their development and explore potentially generalizable properties of pain to other states. Here, we used 2 data sets to test the neurologic pain signature (NPS), an established pain neuromarker. In study 1, brain activity was measured using high-field functional magnetic resonance imaging (7T fMRI, N = 40) during 5 to 25 seconds of experimental breathlessness (induced by inspiratory resistive loading), conditioned breathlessness anticipation, and finger opposition. In study 2, we assessed anticipation and breathlessness perception (3T, N = 19) under blinded saline (placebo) and remifentanil administration. The NPS responded to breathlessness, anticipation, and finger opposition, although no direct comparisons with painful events were possible. Local NPS patterns in anterior or midinsula, S2, and dorsal anterior cingulate responded to breathlessness and finger opposition and were reduced by remifentanil. Local NPS responses in the dorsal posterior insula did not respond to any manipulations. Therefore, significant global NPS activity alone is not specific for pain, and we offer insight into the overlap between NPS responses, breathlessness, and somatomotor demand.

Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.

Population receptive fields in non-human primates from whole-brain fMRI and large-scale neurophysiology in visual cortex

Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake nonhuman primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF models based on the fMRI blood-oxygen-level-dependent (BOLD) signal, multi-unit spiking activity (MUA), and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. fMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF size with increasing eccentricity, as well as a retinotopically specific deactivation of default mode network nodes similar to previous observations in humans.

Parametric fMRI analysis of videos of variable arousal levels reveals different dorsal vs ventral activation preferences between autism and controls

Atypical sensory processing is now considered a ubiquitous feature of autism spectrum disorder (ASD) and is responsible for the atypical sensory-based behaviours seen in these individuals. Specifically, emotional arousal is a critical ASD target since it comprises emotion regulation and sensory processing, two core aspects of autism. So, in this project, we used task-based fMRI and a well-catalogued dataset of videos with variable arousal levels to characterize the sensory processing of emotional arousal content in ASD and typically developed controls. Our analysis revealed a difference in the secondary attention network where ASD individuals showed a clear yet lateralized preference to the dorsal attention network, whereas the neurotypical individuals preferred the ventral attention network.

Hierarchical modelling of functional brain networks in population and individuals from big fMRI data

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We introduce stochastic PROFUMO (sPROFUMO) for inferring functional brain networks from big data.

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sPROFUMO hierarchically estimates fMRI networks for the population and every individual.

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We characterised high dimensional resting state fMRI networks from UK Biobank.

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Model outperforms ICA and dual regression for estimation of individual-specific network topography.

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We demonstrate the model's utility for predicting cognitive traits, and capturing subject variability in network topographies versus connectivity.

A major goal of large-scale brain imaging datasets is to provide resources for investigating heterogeneous populations. Characterisation of functional brain networks for individual subjects from these datasets will have an enormous potential for prediction of cognitive or clinical traits. We propose for the first time a technique, Stochastic Probabilistic Functional Modes (sPROFUMO), that is scalable to UK Biobank (UKB) with expected 100,000 participants, and hierarchically estimates functional brain networks in individuals and the population, while allowing for bidirectional flow of information between the two. Using simulations, we show the model's utility, especially in scenarios that involve significant cross-subject variability, or require delineation of fine-grained differences between the networks. Subsequently, by applying the model to resting-state fMRI from 4999 UKB subjects, we mapped resting state networks (RSNs) in single subjects with greater detail than has been possible previously in UKB (>100 RSNs), and demonstrate that these RSNs can predict a range of sensorimotor and higher-level cognitive functions. Furthermore, we demonstrate several advantages of the model over independent component analysis combined with dual-regression (ICA-DR), particularly with respect to the estimation of the spatial configuration of the RSNs and the predictive power for cognitive traits. The proposed model and results can open a new door for future investigations into individualised profiles of brain function from big data.

The Normative Modeling Framework for Computational Psychiatry.. [PMID: 35650452 PMCID: PMC7613648 DOI: 10.1101/2021.08.08.455583]

Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior which can then be used to make statistical inferences at the level of the individual. The fields of computational psychiatry and clinical neuroscience have been slow to transition away from patient versus “healthy” control analytic approaches, likely due to a lack of tools designed to properly model biological heterogeneity of mental disorders. Normative modeling provides a solution to address this issue and moves analysis away from case-control comparisons that rely on potentially noisy clinical labels. In this article, we define a standardized protocol to guide users through, from start to finish, normative modeling analysis using the Predictive Clinical Neuroscience toolkit (PCNtoolkit). We describe the input data selection process, provide intuition behind the various modeling choices, and conclude by demonstrating several examples of down-stream analyses the normative model results may facilitate, such as stratification of high-risk individuals, subtyping, and behavioral predictive modeling. The protocol takes approximately 1-3 hours to complete.

A quadratic model captures the human V1 response to variations in chromatic direction and contrast

An important goal for vision science is to develop quantitative models of the representation of visual signals at post-receptoral sites. To this end, we develop the quadratic color model (QCM) and examine its ability to account for the BOLD fMRI response in human V1 to spatially-uniform, temporal chromatic modulations that systematically vary in chromatic direction and contrast. We find that the QCM explains the same, cross-validated variance as a conventional general linear model, with far fewer free parameters. The QCM generalizes to allow prediction of V1 responses to a large range of modulations. We replicate the results for each subject and find good agreement across both replications and subjects. We find that within the LM cone contrast plane, V1 is most sensitive to L-M contrast modulations and least sensitive to L+M contrast modulations. Within V1, we observe little to no change in chromatic sensitivity as a function of eccentricity.

Multivariate semi-blind deconvolution of fMRI time series

Whole brain estimation of the haemodynamic response function (HRF) in functional magnetic resonance imaging (fMRI) is critical to get insight on the global status of the neurovascular coupling of an individual in healthy or pathological condition. Most of existing approaches in the literature works on task-fMRI data and relies on the experimental paradigm as a surrogate of neural activity, hence remaining inoperative on resting-stage fMRI (rs-fMRI) data. To cope with this issue, recent works have performed either a two-step analysis to detect large neural events and then characterize the HRF shape or a joint estimation of both the neural and haemodynamic components in an univariate fashion. In this work, we express the neural activity signals as a combination of piece-wise constant temporal atoms associated with sparse spatial maps and introduce an haemodynamic parcellation of the brain featuring a temporally dilated version of a given HRF model in each parcel with unknown dilation parameters. We formulate the joint estimation of the HRF shapes and spatio-temporal neural representations as a multivariate semi-blind deconvolution problem in a paradigm-free setting and introduce constraints inspired from the dictionary learning literature to ease its identifiability. A fast alternating minimization algorithm, along with its efficient implementation, is proposed and validated on both synthetic and real rs-fMRI data at the subject level. To demonstrate its significance at the population level, we apply this new framework to the UK Biobank data set, first for the discrimination of haemodynamic territories between balanced groups (n=24 individuals in each) patients with an history of stroke and healthy controls and second, for the analysis of normal aging on the neurovascular coupling. Overall, we statistically demonstrate that a pathology like stroke or a condition like normal brain aging induce longer haemodynamic delays in certain brain areas (e.g. Willis polygon, occipital, temporal and frontal cortices) and that this haemodynamic feature may be predictive with an accuracy of 74 % of the individual's age in a supervised classification task performed on n=459 subjects.

BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks

In this paper we propose BVAR-connect, a variational inference approach to a Bayesian multi-subject vector autoregressive (VAR) model for inference on effective brain connectivity based on resting-state functional MRI data. The modeling framework uses a Bayesian variable selection approach that flexibly integrates multi-modal data, in particular structural diffusion tensor imaging (DTI) data, into the prior construction. The variational inference approach we develop allows scalability of the methods and results in the ability to estimate subject- and group-level brain connectivity networks over whole-brain parcellations of the data. We provide a brief description of a user-friendly MATLAB GUI released for public use. We assess performance on simulated data, where we show that the proposed inference method can achieve comparable accuracy to the sampling-based Markov Chain Monte Carlo approach but at a much lower computational cost. We also address the case of subject groups with imbalanced sample sizes. Finally, we illustrate the methods on resting-state functional MRI and structural DTI data on children with a history of traumatic injury.

Effects of repeated menstrual pain on empathic neural responses in women with primary dysmenorrhea across the menstrual cycle

Primary dysmenorrhea (PDM) is cyclic menstrual pain in the absence of pelvic anomalies, and it is thought to be a sex-hormone related disorder. Existing study has focused on the effects of menstrual cramps on brain function and structure, ignoring the psychological changes associated with menstrual pain. Here we examined whether pain empathy in PDM differs from healthy controls (HC) using task-based functional magnetic resonance imaging (fMRI). Fifty-seven PDM women and 53 matched HC were recruited, and data were collected at the luteal and menstruation phases, respectively. During fMRI scans, participants viewed pictures displaying exposure to painful situations and pictures without any pain cues and assessed the level of pain experienced by the person in the picture. Regarding the main effect of the pain pictures, our results showed that compared to viewing neutral pictures, viewing pain pictures caused significantly higher activation in the anterior insula (AI), anterior cingulate cortex, and the left inferior parietal lobule; and only the right AI exhibited a significant interaction effect (group × picture). Post-hoc analyses confirmed that, relative to neutral pictures, the right AI failed to be activated in PDM women viewing painsss pictures. Additionally, there was no significant interaction effect between the luteal and menstruation phases. It suggests that intermittent pain can lead to abnormal empathy in PDM women, which does not vary with the pain or pain-free phase. Our study may deepen the understanding of the relationship between recurrent spontaneous pain and empathy in a clinical disorder characterized by cyclic episodes of pain.

Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data

EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor multivariate relations in the fMRI data, and it is nontrivial to accurately handle varying neurovascular coupling over patients and brain regions. We aim to overcome these drawbacks in a data-driven manner by means of a novel structured matrix-tensor factorization: the single-subject EEG data (represented as a third-order spectrogram tensor) and fMRI data (represented as a spatiotemporal BOLD signal matrix) are jointly decomposed into a superposition of several sources, characterized by space-time-frequency profiles. In the shared temporal mode, Toeplitz-structured factors account for a spatially specific, neurovascular 'bridge' between the EEG and fMRI temporal fluctuations, capturing the hemodynamic response's variability over brain regions. By analyzing interictal data from twelve patients, we show that the extracted source signatures provide a sensitive localization of the ictal onset zone (10/12). Moreover, complementary parts of the IOZ can be uncovered by inspecting those regions with the most deviant neurovascular coupling, as quantified by two entropy-like metrics of the hemodynamic response function waveforms (9/12). Hence, this multivariate, multimodal factorization provides two useful sets of EEG-fMRI biomarkers, which can assist the presurgical evaluation of epilepsy. We make all code required to perform the computations available at https://github.com/svaneynd/structured-cmtf.

A collaborative resource platform for non-human primate neuroimaging

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field.

Emotional face processing across neurodevelopmental disorders: a dynamic faces study in children with autism spectrum disorder, attention deficit hyperactivity disorder and obsessive-compulsive disorder

Autism spectrum disorder (ASD) is classically associated with poor face processing skills, yet evidence suggests that those with obsessive-compulsive disorder (OCD) and attention deficit hyperactivity disorder (ADHD) also have difficulties understanding emotions. We determined the neural underpinnings of dynamic emotional face processing across these three clinical paediatric groups, including developmental trajectories, compared with typically developing (TD) controls. We studied 279 children, 5-19 years of age but 57 were excluded due to excessive motion in fMRI, leaving 222: 87 ASD, 44 ADHD, 42 OCD and 49 TD. Groups were sex- and age-matched. Dynamic faces (happy, angry) and dynamic flowers were presented in 18 pseudo-randomized blocks while fMRI data were collected with a 3T MRI. Group-by-age interactions and group difference contrasts were analysed for the faces vs. flowers and between happy and angry faces. TD children demonstrated different activity patterns across the four contrasts; these patterns were more limited and distinct for the NDDs. Processing happy and angry faces compared to flowers yielded similar activation in occipital regions in the NDDs compared to TDs. Processing happy compared to angry faces showed an age by group interaction in the superior frontal gyrus, increasing with age for ASD and OCD, decreasing for TDs. Children with ASD, ADHD and OCD differentiated less between dynamic faces and dynamic flowers, with most of the effects seen in the occipital and temporal regions, suggesting that emotional difficulties shared in NDDs may be partly attributed to shared atypical visual information processing.

White Matter Neuroplasticity: Motor Learning Activates the Internal Capsule and Reduces Hemodynamic Response Variability

Numerous studies have noted the importance of white matter changes in motor learning, but existing literature only focuses on structural and microstructural MRI changes, as there are limited tools available for in vivo investigations of white matter function. One method that has gained recent prominence is the application of blood oxygen level dependent (BOLD) fMRI to white matter, with high-field scanners now being able to better detect the smaller hemodynamic changes present in this tissue type compared to those in the gray matter. However, fMRI techniques have yet to be applied to investigations of neuroplastic change with motor learning in white matter. White matter function represents an unexplored component of neuroplasticity and is essential for gaining a complete understanding of learning-based changes occurring throughout the whole brain. Twelve healthy, right-handed participants completed fine motor and gross motor tasks with both hands, using an MRI compatible computer mouse. Using a crossover design along with a prior analysis approach to establish WM activation, participants received a baseline scan followed by 2 weeks of training, returning for a midpoint and endpoint scan. The motor tasks were designed to be selectively difficult for the left hand, leading to a training effect only in that condition. Analysis targeted the comparison and detection of training-associated right vs left hand changes. A statistically significant improvement in motor task score was only noted for the left-hand motor condition. A corresponding change in the temporal characteristics of the white matter hemodynamic response was shown within only the right corticospinal tract. The hemodynamic response exhibited a reduction in the dispersion characteristics after the training period. To our knowledge, this is the first report of MRI detectable functional neuroplasticity in white matter, suggesting that modifications in temporal characteristics of white matter hemodynamics may underlie functional neuroplasticity in this tissue.

A temporal decomposition method for identifying venous effects in task-based fMRI

The spatial resolution of functional magnetic resonance imaging (fMRI) is fundamentally limited by effects from large draining veins. Here we describe an analysis method that provides data-driven estimates of these effects in task-based fMRI. The method involves fitting a one-dimensional manifold that characterizes variation in response timecourses observed in a given dataset, and then using identified early and late timecourses as basis functions for decomposing responses into components related to the microvasculature (capillaries and small venules) and the macrovasculature (large veins), respectively. We show the removal of late components substantially reduces the superficial cortical depth bias of fMRI responses and helps eliminate artifacts in cortical activity maps. This method provides insight into the origins of the fMRI signal and can be used to improve the spatial accuracy of fMRI.