Classical and Bayesian inference in neuroimaging: theory

To lie or to tell the truth? The influence of processing the opponent's feedback on the forthcoming choice

Introduction

The brain mechanisms of deceptive behavior are relatively well studied, and the key brain regions involved in its processing were established. At the same time, the brain mechanisms underlying the processes of preparation for deception are less known.

Methods

We studied BOLD-signal changes during the presentation of the opponent's feedback to a previous deceptive or honest action during the computer game. The goal of the game was to mislead the opponent either by means of deception or by means of telling the truth.

Results

As a result, it was shown that several brain regions that were previously demonstrated as involved in deception execution, such as the left anterior cingulate cortex and anterior insula, also underlie processes related to deception preparation.

Discussion

The results obtained also allowed us to suggest that brain regions responsible for performance monitoring, intention assessment, suppression of non-selected solutions, and reward processing could be involved in shaping future action selection and preparation for deception. By shedding light on the brain mechanisms underlying deception, our study contributes to a deeper understanding of this complex cognitive process. Furthermore, it emphasizes the significance of exploring brain mechanisms governing the choice between deception and truth at various stages of decision-making.

Negative emotions enhance memory-guided attention in a visual search task by increasing frontoparietal, insular, and parahippocampal cortical activity

Previous literature demonstrated that long-term memory representations guide spatial attention during visual search in real-world pictures. However, it is currently unknown whether memory-guided visual search is affected by the emotional content of the picture. During functional magnetic resonance imaging (fMRI), participants were asked to encode the position of high-contrast targets embedded in emotional (negative or positive) or neutral pictures. At retrieval, they performed a visual search for targets presented at the same location as during encoding, but at a much lower contrast. Behaviorally, participants detected more accurately targets presented in negative pictures compared to those in positive or neutral pictures. They were also faster in detecting targets presented at encoding in emotional (negative or positive) pictures than in neutral pictures, or targets not presented during encoding (i.e., memory-guided attention effect). At the neural level, we found increased activation in a large circuit of regions involving the dorsal and ventral frontoparietal cortex, insular and parahippocampal cortex, selectively during the detection of targets presented in negative pictures during encoding. We propose that these regions might form an integrated neural circuit recruited to select and process previously encoded target locations (i.e., memory-guided attention sustained by the frontoparietal cortex) embedded in emotional contexts (i.e., emotional contexts recollection supported by the parahippocampal cortex and emotional monitoring supported by the insular cortex). Ultimately, these findings reveal that negative emotions can enhance memory-guided visual search performance by increasing neural activity in a large-scale brain circuit, contributing to disentangle the complex relationship between emotion, attention, and memory.

Resting-state brain activity distinguishes patients with generalised epilepsy from others

PURPOSE

Epilepsy is a prevalent neurological disorder characterised by repetitive seizures. It is categorised into three types: generalised epilepsy (GE), focal epilepsy (FE), and combined generalised and focal epilepsy. Correctly subtyping the epilepsy is important to select appropriate treatments. The types are mainly determined (i.e., diagnosed) by their semiologies supported by clinical examinations, such as electroencephalography and magnetoencephalography (MEG). Although these examinations are traditionally based on visual inspections of interictal epileptic discharges (IEDs), which are not always visible, alternative analyses have been anticipated. We examined if resting-state brain activities can distinguish patients with GE, which would help us to diagnose the type of epilepsy.

METHODS

The 5 min resting-state brain activities acquired using MEG were obtained retrospectively from 15 patients with GE. The cortical source of the activities was estimated at each frequency band from delta to high-frequency oscillation (HFO). These estimated activities were compared with reference datasets from 133 healthy individuals and control data from 29 patients with FE.

RESULTS

Patients with GE showed larger theta in the occipital, alpha in the left temporal, HFO in the rostral deep regions, and smaller HFO in the caudal ventral regions. Their area under the curves of the receiver operating characteristic curves was around 0.8-0.9. The distinctive pattern was not found for data from FE.

CONCLUSION

Patients with GE show distinctive resting-state brain activity, which could be a potential biomarker and used complementarily to classical analysis based on the visual inspection of IEDs.

A practical model-based segmentation approach for improved activation detection in single-subject functional magnetic resonance imaging studies

Functional magnetic resonance imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and single-subject studies. Accurate activation detection can be guided by the fact that very few voxels are, in reality, truly activated and that these voxels are spatially localized, but it is challenging to incorporate both these facts. We address these twin challenges to single-subject and low-signal fMRI by developing a computationally feasible and methodologically sound model-based approach, implemented in the R package MixfMRI, that bounds the a priori expected proportion of activated voxels while also incorporating spatial context. An added benefit of our methodology is the ability to distinguish voxels and regions having different intensities of activation. Our suggested approach is evaluated in realistic two- and three-dimensional simulation experiments as well as on multiple real-world datasets. Finally, the value of our suggested approach in low-signal and single-subject fMRI studies is illustrated on a sports imagination experiment that is often used to detect awareness and improve treatment in patients in persistent vegetative state (PVS). Our ability to reliably distinguish activation in this experiment potentially opens the door to the adoption of fMRI as a clinical tool for the improved treatment and therapy of PVS survivors and other patients.

Statistical analyses of motion-corrupted MRI relaxometry data computed from multiple scans

BACKGROUND

Consistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses.

NEW METHOD

The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2 * , which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2 * , and MTsat, computed from multiple sets of images.

RESULTS

QUIQI restores homoscedasticity in analyses of quantitative MRI data computed from multiple scans. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy.

COMPARISON WITH EXISTING METHODS

QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis.

CONCLUSION

QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.

Permutation-based group sequential analyses for cognitive neuroscience

Cognitive neuroscientists have been grappling with two related experimental design problems. First, the complexity of neuroimaging data (e.g. often hundreds of thousands of correlated measurements) and analysis pipelines demands bespoke, non-parametric statistical tests for valid inference, and these tests often lack an agreed-upon method for performing a priori power analyses. Thus, sample size determination for neuroimaging studies is often arbitrary or inferred from other putatively but questionably similar studies, which can result in underpowered designs - undermining the efficacy of neuroimaging research. Second, when meta-analyses estimate the sample sizes required to obtain reasonable statistical power, estimated sample sizes can be prohibitively large given the resource constraints of many labs. We propose the use of sequential analyses to partially address both of these problems. Sequential study designs - in which the data is analyzed at interim points during data collection and data collection can be stopped if the planned test statistic satisfies a stopping rule specified a priori - are common in the clinical trial literature, due to the efficiency gains they afford over fixed-sample designs. However, the corrections used to control false positive rates in existing approaches to sequential testing rely on parametric assumptions that are often violated in neuroimaging settings. We introduce a general permutation scheme that allows sequential designs to be used with arbitrary test statistics. By simulation, we show that this scheme controls the false positive rate across multiple interim analyses. Then, performing power analyses for seven evoked response effects seen in the EEG literature, we show that this sequential analysis approach can substantially outperform fixed-sample approaches (i.e. require fewer subjects, on average, to detect a true effect) when study designs are sufficiently well-powered. To facilitate the adoption of this methodology, we provide a Python package "niseq" with sequential implementations of common tests used for neuroimaging: cluster-based permutation tests, threshold-free cluster enhancement, t-max, F-max, and the network-based statistic with tutorial examples using EEG and fMRI data.

Reward Processing During Monetary Incentive Delay Task After Leptin Substitution in Lipodystrophy-an fMRI Case Series

Context

Behaviorally, the most pronounced effects of leptin substitution in leptin deficiency are the hunger-decreasing and postprandial satiety-prolonging effects of the adipokine. Previously, with functional magnetic resonance imaging (MRI), we and others showed that eating behavior-controlling effects are at least in part conveyed by the reward system. However, to date, it is unclear if leptin only modulates eating behavior specific brain reward action or if it also alters the reward function of the brain unrelated to eating behavior.

Objective

We investigated with functional MRI the effects of metreleptin on the reward system in a reward task unrelated to eating behavior, the monetary incentive delay task.

Design

Measurements in 4 patients with the very rare disease of lipodystrophy (LD), resulting in leptin deficiency, and 3 untreated healthy control persons were performed at 4 different time points: before start and over 12 weeks of metreleptin treatment. Inside the MRI scanner, participants performed the monetary incentive delay task and brain activity during the reward receipt phase of the trial was analyzed.

Results

We found a reward-related brain activity decrease in our 4 patients with LD over the 12 weeks of metreleptin treatment in the subgenual region, a brain area associated with the reward network, which was not observed in our 3 untreated healthy control persons.

Conclusions

These results suggest that leptin replacement in LD induces changes of brain activity during reward reception processing completely unrelated to eating behavior or food stimuli. This could suggest eating behavior-unrelated functions of leptin in the human reward system.

Trial registration

The trial is registered as trial No. 147/10-ek at the ethics committee of the University of Leipzig and at the State Directorate of Saxony (Landesdirektion Sachsen).

A framework for focal and connectomic mapping of transiently disrupted brain function

The distributed nature of the neural substrate, and the difficulty of establishing necessity from correlative data, combine to render the mapping of brain function a far harder task than it seems. Methods capable of combining connective anatomical information with focal disruption of function are needed to disambiguate local from global neural dependence, and critical from merely coincidental activity. Here we present a comprehensive framework for focal and connective spatial inference based on sparse disruptive data, and demonstrate its application in the context of transient direct electrical stimulation of the human medial frontal wall during the pre-surgical evaluation of patients with focal epilepsy. Our framework formalizes voxel-wise mass-univariate inference on sparsely sampled data within the statistical parametric mapping framework, encompassing the analysis of distributed maps defined by any criterion of connectivity. Applied to the medial frontal wall, this transient dysconnectome approach reveals marked discrepancies between local and distributed associations of major categories of motor and sensory behaviour, revealing differentiation by remote connectivity to which purely local analysis is blind. Our framework enables disruptive mapping of the human brain based on sparsely sampled data with minimal spatial assumptions, good statistical efficiency, flexible model formulation, and explicit comparison of local and distributed effects.

Neural unscrambling of temporal information during a nonlinear narrative

Although we must experience our lives chronologically, storytellers often manipulate the order in which they relay events. How the brain processes temporal information while encoding a nonlinear narrative remains unclear. Here, we use functional magnetic resonance imaging during movie watching to investigate which brain regions are sensitive to information about time in a narrative and test whether the representation of temporal context across a narrative is more influenced by the order in which events are presented or their underlying chronological sequence. Results indicate that medial parietal regions are sensitive to cued jumps through time over and above other changes in context (i.e., location). Moreover, when processing non-chronological narrative information, the precuneus and posterior cingulate engage in on-the-fly temporal unscrambling to represent information chronologically. Specifically, days that are closer together in chronological time are represented more similarly regardless of when they are presented in the movie, and this representation is consistent across participants. Additional analyses reveal a strong spatial signature associated with higher magnitude jumps through time. These findings are consistent with prior theorizing on medial parietal regions as central to maintaining and updating narrative situation models, and suggest the priority of chronological information when encoding narrative events.

Impaired Non-Selective Response Inhibition in Obsessive-Compulsive Disorder

Two prominent features of obsessive-compulsive disorder (OCD) are the inability to inhibit intrusive thoughts and behaviors and pathological doubt or intolerance of uncertainty. Previous study showed that uncertain context modeled by equiprobable presentation of excitatory (Go) and inhibitory (NoGo) stimuli requires non-selective response inhibition in healthy subjects. In other words, it requires transient global inhibition triggered not only by excitatory stimuli but also by inhibitory stimuli. Meanwhile, it is unknown whether OCD patients show abnormal brain activity of the non-selective response inhibition system. In order to test this assumption, we performed an fMRI study with an equiprobable Go/NoGo task involving fourteen patients with OCD and compared them with 34 healthy controls. Patients with OCD showed pathological slowness in the Go/NoGo task. The non-selective response inhibition system in OCD included all brain areas seen in healthy controls and, in addition, involved the right anterior cingulate cortex (ACC) and the anterior insula/frontal operculum (AIFO). Moreover, a between-group comparison revealed hypoactivation of brain regions within cingulo-opercular and cortico-striato-thalamo-cortical (CSTC) circuits in OCD. Among hypoactivated areas, the right ACC and the right dorsolateral prefrontal cortex (DLPFC) were associated with non-selective inhibition. Furthermore, regression analysis showed that OCD slowness was associated with decreased activation in cingulate regions and two brain areas related to non-selective inhibition: the right DLPFC and the right inferior parietal lobule (IPL). These results suggest that non-selective response inhibition is impaired in OCD, which could be a potential explanation for a relationship between inhibitory deficits and the other remarkable characteristic of OCD known as intolerance of uncertainty.

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.

Spatiotemporal and sensory modality attention processing with domain-specific representations in frontoparietal areas

The frontoparietal network (FPN), including bilateral frontal eye field, inferior parietal sulcus, and supplementary motor area, has been linked to attention processing, including spatiotemporal and sensory modality domains. However, it is unclear whether FPN encodes representations of these domains that are generalizable across subdomains. We decomposed multivariate patterns of functional magnetic resonance imaging activity from 20 participants into domain-specific components and identified latent multivariate representations that generalized across subdomains. The 30 experimental conditions were organized into unimodal-bimodal and spatial-temporal models. We found that brain areas in the FPN, form the primary network that modulated during attention across domains. However, the activation patterns of areas within the FPN were reorganized according to the specific attentional demand, especially when pay attention to different sensory, suggesting distinct regional neural representations associated with specific attentional processes within FPN. In addition, there were also other domain-specific areas outside the FPN, such as the dorsolateral prefrontal cortex. Our conclusion is that, according to the results of the analysis of representation similarity, 2 types of activated brain regions, related to attention domain detailed information processing and general information processing, can be revealed.

Detection of emerging neurodegeneration using Bayesian linear mixed-effect modeling

Early detection of neurodegeneration, and prediction of when neurodegenerative diseases will lead to symptoms, are critical for developing and initiating disease modifying treatments for these disorders. While each neurodegenerative disease has a typical pattern of early changes in the brain, these disorders are heterogeneous, and early manifestations can vary greatly across people. Methods for detecting emerging neurodegeneration in any part of the brain are therefore needed. Prior publications have described the use of Bayesian linear mixed-effects (BLME) modeling for characterizing the trajectory of change across the brain in healthy controls and patients with neurodegenerative disease. Here, we use an extension of such a model to detect emerging neurodegeneration in cognitively healthy individuals at risk for dementia. We use BLME to quantify individualized rates of volume loss across the cerebral cortex from the first two MRIs in each person and then extend the BLME model to predict future values for each voxel. We then compare observed values at subsequent time points with the values that were expected from the initial rates of change and identify voxels that are lower than the expected values, indicating accelerated volume loss and neurodegeneration. We apply the model to longitudinal imaging data from cognitively normal participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI), some of whom subsequently developed dementia, and two cognitively normal cases who developed pathology-proven frontotemporal lobar degeneration (FTLD). These analyses identified regions of accelerated volume loss prior to or accompanying the earliest symptoms, and expanding across the brain over time, in all cases. The changes were detected in regions that are typical for the likely diseases affecting each patient, including medial temporal regions in patients at risk for Alzheimer's disease, and insular, frontal, and/or anterior/inferior temporal regions in patients with likely or proven FTLD. In the cases where detailed histories were available, the first regions identified were consistent with early symptoms. Furthermore, survival analysis in the ADNI cases demonstrated that the rate of spread of accelerated volume loss across the brain was a statistically significant predictor of time to conversion to dementia. This method for detection of neurodegeneration is a potentially promising approach for identifying early changes due to a variety of diseases, without prior assumptions about what regions are most likely to be affected first in an individual.

Event-Related Potential Evidence for Involuntary Consciousness During Implicit Memory Retrieval

Classical notion claims that a memory is implicit if has nothing to do with consciousness during the information retrieval from storage, or is otherwise explicit. Here, we demonstrate event-related potential evidence for involuntary consciousness during implicit memory retrieval. We designed a passive oddball paradigm for retrieval of implicit memory in which an auditory stream of Shepard tones with musical pitch interval contrasts were delivered to the subjects. These contrasts evoked a mismatch negativity response, which is an event-related potential and a neural marker of implicit memory, in the subjects with long-term musical training, but not in the subjects without. Notably, this response was followed by a salient P3 component which implies involvement of involuntary consciousness in the implicit memory retrieval. Finally, source analysis of the P3 revealed moving dipoles from the frontal lobe to the insula, a brain region closely related to conscious attention. Our study presents a case of involvement of involuntary consciousness in the implicit memory retrieval and suggests a potential challenge to the classical definition of implicit memory.

Evidence for non-selective response inhibition in uncertain contexts revealed by combined meta-analysis and Bayesian analysis of fMRI data

Response inhibition is typically considered a brain mechanism selectively triggered by particular “inhibitory” stimuli or events. Based on recent research, an alternative non-selective mechanism was proposed by several authors. Presumably, the inhibitory brain activity may be triggered not only by the presentation of “inhibitory” stimuli but also by any imperative stimuli, including Go stimuli, when the context is uncertain. Earlier support for this notion was mainly based on the absence of a significant difference between neural activity evoked by equiprobable Go and NoGo stimuli. Equiprobable Go/NoGo design with a simple response time task limits potential confounds between response inhibition and accompanying cognitive processes while not preventing prepotent automaticity. However, previous neuroimaging studies used classical null hypothesis significance testing, making it impossible to accept the null hypothesis. Therefore, the current research aimed to provide evidence for the practical equivalence of neuronal activity in the Go and NoGo trials using Bayesian analysis of functional magnetic resonance imaging (fMRI) data. Thirty-four healthy participants performed a cued Go/NoGo task with an equiprobable presentation of Go and NoGo stimuli. To independently localize brain areas associated with response inhibition in similar experimental conditions, we performed a meta-analysis of fMRI studies using equal-probability Go/NoGo tasks. As a result, we observed overlap between response inhibition areas and areas that demonstrate the practical equivalence of neuronal activity located in the right dorsolateral prefrontal cortex, parietal cortex, premotor cortex, and left inferior frontal gyrus. Thus, obtained results favour the existence of non-selective response inhibition, which can act in settings of contextual uncertainty induced by the equal probability of Go and NoGo stimuli.

Quantifying Differences Between Affine and Nonlinear Spatial Normalization of FP-CIT Spect Images

Spatial normalization helps us to compare quantitatively two or more input brain scans. Although using an affine normalization approach preserves the anatomical structures, the neuroimaging field is more common to find works that make use of nonlinear transformations. The main reason is that they facilitate a voxel-wise comparison, not only when studying functional images but also when comparing MRI scans given that they fit better to a reference template. However, the amount of bias introduced by the nonlinear transformations can potentially alter the final outcome of a diagnosis especially when studying functional scans for neurological disorders like Parkinson's Disease. In this context, we have tried to quantify the bias introduced by the affine and the nonlinear spatial registration of FP-CIT SPECT volumes of healthy control subjects and patients with PD. For that purpose, we calculated the deformation fields of each participant and applied these deformation fields to a 3D-grid. As the space between the edges of small cubes comprising the grid change, we can quantify which parts from the brain have been enlarged, compressed or just remain the same. When the nonlinear approach is applied, scans from PD patients show a region near their striatum very similar in shape to that of healthy subjects. This artificially increases the interclass separation between patients with PD and healthy subjects as the local intensity is decreased in the latter region, and leads machine learning systems to biased results due to the artificial information introduced by these deformations.

Sex and strategy effects on brain activation during a 3D-navigation task

Sex differences in navigation have often been attributed to the use of different navigation strategies in men and women. However, no study so far has investigated sex differences in the brain networks supporting different navigation strategies. To address this issue, we employed a 3D-navigation task during functional MRI in 36 men and 36 women, all scanned thrice, and modeled navigation strategies by instructions requiring an allocentric vs. egocentric reference frame on the one hand, as well as landmark-based vs. Euclidian strategies on the other hand. We found distinct brain networks supporting different perspectives/strategies. Men showed stronger activation of frontal areas, whereas women showed stronger activation of posterior brain regions. The left inferior frontal gyrus was more strongly recruited during landmark-based navigation in men. The hippocampus showed stronger connectivity with left-lateralized frontal areas in women and stronger connectivity with superior parietal areas in men. We discuss these findings in the light of a stronger recruitment of verbal networks supporting a more verbal strategy in women compared to a stronger recruitment of spatial networks supporting a more spatial strategy use in men. In summary, this study provides evidence that different navigation strategies activate different brain areas in men and women.

Effects of oral alkali drug therapy on clinical outcomes in pre-dialysis chronic kidney disease patients: a systematic review and meta-analysis

BACKGROUND

Metabolic acidosis accelerates the progression of chronic kidney disease (CKD) and increases the mortality rate. Whether oral alkali drug therapy benefits pre-dialysis CKD patients is controversial. We performed a meta-analysis of the effects of oral alkali drug therapy on major clinical outcomes in pre-dialysis CKD patients.

METHODS

We systematically searched MEDLINE using the Ovid, EMBASE, and Cochrane Library databases without language restriction. We included all eligible clinical studies that involved pre-dialysis CKD adults and compared those who received oral alkali drug therapy with controls.

RESULTS

A total of 18 eligible studies, including 14 randomized controlled trials and 4 cohort studies reported in 19 publications with 3695 participants, were included. Oral alkali drug therapy led to a 55% reduction in renal failure events (relative risk [RR]: 0.45; 95% confidence interval [CI]: 0.25-0.82), a rate of decline in the estimated glomerular filtration rate (eGFR) of 2.59 mL/min/1.73 m² per year (95% CI, 0.88-4.31). There was no significant effect on decline in eGFR events (RR: 0.34; 95% CI: 0.09-1.23), proteinuria (standardized mean difference: -0.32; 95% CI: -1.08 to 0.43), all-cause mortality events (RR: 0.90; 95% CI: 0.40-2.02) and cardiovascular (CV) events (RR: 1.03; 95% CI: 0.32-3.37) compared with the control groups.

CONCLUSION

Based on the available and low-to-moderate certainty evidence, oral alkali drug therapy might potentially reduce the risk of kidney failure events, but no benefit in reducing all-cause mortality events, CV events, decline in eGFR and porteninuria.

Restoring statistical validity in group analyses of motion-corrupted MRI data

Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data‐driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of quantitative MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality.

Effect of a low-salt diet on chronic kidney disease outcomes: a systematic review and meta-analysis

OBJECTIVE

The benefits of a low-salt diet for patients with chronic kidney disease (CKD) are controversial. We conducted a systematic review and meta-analysis of the effect of a low-salt diet on major clinical outcomes.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE by Ovid, EMBASE and the Cochrane Library databases.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

We included randomised controlled trials (RCTs) and cohort studies that assessed the effect of a low-salt diet on the renal composite outcomes (more than 50% decline in estimated glomerular filtration rate (eGFR) during follow-up, doubling of serum creatinine or end-stage renal disease), rate of eGFR decline, change in proteinuria, all-cause mortality events, cardiovascular (CV) events, and changes in systolic blood pressure and diastolic blood pressure.

DATA EXTRACTION AND SYNTHESIS

Two independent researchers extracted data and evaluated their quality. Relative risks (RRs) with 95% CIs were used for dichotomous data. Differences in means (MDs) or standardised mean differences (SMDs) with 95% CIs were used to pool continuous data. We used the Cochrane Collaboration risk-of-bias tool to evaluate the quality of RCTs, and Newcastle-Ottawa Scale to evaluate the quality of cohort studies.

RESULTS

We found 9948 potential research records. After removing duplicates, we reviewed the titles and abstracts, and screened the full text of 230 publications. Thirty-three studies with 101 077 participants were included. A low-salt diet produced a 28% reduction in renal composite outcome events (RR: 0.72; 95% CI: 0.58 to 0.89). No significant effects were found in terms of changes in proteinuria (SMD: -0.71; 95% CI: -1.66 to 0.24), rate of eGFR (decline MD: 1.16; 95% CI: -2.02 to 4.33), risk of all-cause mortality (RR: 0.92; 95% CI: 0.58 to 1.46) and CV events (RR: 1.01; 95% CI: 0.46 to 2.22).

CONCLUSION

A low-salt diet seems to reduce the risk for renal composite outcome events in patients with CKD. However, no compelling evidence indicated that such a diet would reduce the eGFR decline rate, proteinuria, incidence of all-cause mortality and CV events. Further, more definitive studies are needed.

PROSPERO REGISTRATION NUMBER

CRD42017072395.

Duration of oral contraceptive use relates to cognitive performance and brain activation in current and past users

Previous studies indicate effects of oral contraceptive (OC) use on spatial and verbal cognition. However, a better understanding of the OC effects is still needed, including the differential effects of androgenic or anti-androgenic OC use and whether the possible impact persists beyond the OC use. We aim to investigate the associations of OC use duration with spatial and verbal cognition, differentiating between androgenic and anti-androgenic OC. Using functional magnetic resonance imaging (MRI), we scanned a group of 94 past and current OC-users in a single session. We grouped current OC users (N=53) and past OC users with a natural cycle (N=41) into androgenic and anti-androgenic user. Effects of OC use duration were observed for current use and after discontinuation. Duration of OC use was reflected only in verbal fluency performance but not navigation: The longer the current OC use, the less words were produced in the verbal fluency task. During navigation, deactivation in the caudate and postcentral gyrus was duration-dependent in current androgenic OC users. Only during the verbal fluency task, duration of previous OC use affects several brain parameters, including activation of the left putamen and connectivity between right-hemispheric language areas (i.e., right inferior frontal gyrus and right angular gyrus). The results regarding performance and brain activation point towards stronger organizational effects of OCs on verbal rather than spatial processing. Irrespective of the task, a duration-dependent connectivity between the hippocampus and various occipital areas was observed. This could suggest a shift in strategy or processing style with long-term contraceptive use during navigation/verbal fluency. The current findings suggest a key role of the progestogenic component of OCs in both tasks. The influence of OC use on verbal fluency remains even after discontinuation which further points out the importance of future studies on OC effects and their reversibility.

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.

Providing Evidence for the Null Hypothesis in Functional Magnetic Resonance Imaging Using Group-Level Bayesian Inference

Classical null hypothesis significance testing is limited to the rejection of the point-null hypothesis; it does not allow the interpretation of non-significant results. This leads to a bias against the null hypothesis. Herein, we discuss statistical approaches to ‘null effect’ assessment focusing on the Bayesian parameter inference (BPI). Although Bayesian methods have been theoretically elaborated and implemented in common neuroimaging software packages, they are not widely used for ‘null effect’ assessment. BPI considers the posterior probability of finding the effect within or outside the region of practical equivalence to the null value. It can be used to find both ‘activated/deactivated’ and ‘not activated’ voxels or to indicate that the obtained data are not sufficient using a single decision rule. It also allows to evaluate the data as the sample size increases and decide to stop the experiment if the obtained data are sufficient to make a confident inference. To demonstrate the advantages of using BPI for fMRI data group analysis, we compare it with classical null hypothesis significance testing on empirical data. We also use simulated data to show how BPI performs under different effect sizes, noise levels, noise distributions and sample sizes. Finally, we consider the problem of defining the region of practical equivalence for BPI and discuss possible applications of BPI in fMRI studies. To facilitate ‘null effect’ assessment for fMRI practitioners, we provide Statistical Parametric Mapping 12 based toolbox for Bayesian inference.

Sparse algorithms for EEG source localization

Source localization using EEG is important in diagnosing various physiological and psychiatric diseases related to the brain. The high temporal resolution of EEG helps medical professionals assess the internal physiology of the brain in a more informative way. The internal sources are obtained from EEG by an inversion process. The number of sources in the brain outnumbers the number of measurements. In this article, a comprehensive review of the state-of-the-art sparse source localization methods in this field is presented. A recently developed method, certainty-based-reduced-sparse-solution (CARSS), is implemented and is examined. A vast comparative study is performed using a sixty-four-channel setup involving two source spaces. The first source space has 5004 sources and the other has 2004 sources. Four test cases with one, three, five, and seven simulated active sources are considered. Two noise levels are also being added to the noiseless data. The CARSS is also evaluated. The results are examined. A real EEG study is also attempted. Graphical Abstract.

Dissociating the Neural Correlates of Consciousness and Task Relevance in Face Perception Using Simultaneous EEG-fMRI

Current theories of visual consciousness disagree about whether it emerges during early stages of processing in sensory brain regions or later when a widespread frontoparietal network becomes involved. Moreover, disentangling conscious perception from task-related postperceptual processes (e.g., report) and integrating results across different neuroscientific methods remain ongoing challenges. The present study addressed these problems using simultaneous EEG-fMRI and a specific inattentional blindness paradigm with three physically identical phases in female and male human participants. In phase 1, participants performed a distractor task during which line drawings of faces and control stimuli were presented centrally. While some participants spontaneously noticed the faces in phase 1, others remained inattentionally blind. In phase 2, all participants were made aware of the task-irrelevant faces but continued the distractor task. In phase 3, the faces became task-relevant. Bayesian analysis of brain responses demonstrated that conscious face perception was most strongly associated with activation in fusiform gyrus (fMRI) as well as the N170 and visual awareness negativity (EEG). Smaller awareness effects were revealed in the occipital and prefrontal cortex (fMRI). Task-relevant face processing, on the other hand, led to strong, extensive activation of occipitotemporal, frontoparietal, and attentional networks (fMRI). In EEG, it enhanced early negativities and elicited a pronounced P3b component. Overall, we provide evidence that conscious visual perception is linked with early processing in stimulus-specific sensory brain areas but may additionally involve prefrontal cortex. In contrast, the strong activation of widespread brain networks and the P3b are more likely associated with task-related processes.SIGNIFICANCE STATEMENT How does our brain generate visual consciousness-the subjective experience of what it is like to see, for example, a face? To date, it is hotly debated whether it emerges early in sensory brain regions or later when a widespread frontoparietal network is activated. Here, we use simultaneous fMRI and EEG for high spatial and temporal resolution and demonstrate that conscious face perception is predominantly linked to early and occipitotemporal processes, but also prefrontal activity. Task-related processes (e.g., decision-making), on the other hand, elicit brain-wide activations including late and strong frontoparietal activity. These findings challenge numerous previous studies and highlight the importance of investigating the neural correlates of consciousness in the absence of task relevance.

Networks underpinning emotion: A systematic review and synthesis of functional and effective connectivity

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We reviewed 33 studies of functional connectivity of emotion in healthy participants.

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Our results challenge a hierarchical model of emotion processing.

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Causal connectivity analyze identify dynamic modulatory relationships between regions.

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We derive a quality tool to make recommendations addressing variability in study design.

Existing models of emotion processing are based almost exclusively on brain activation data, yet make assumptions about network connectivity. There is a need to integrate connectivity findings into these models.

We systematically reviewed all studies of functional and effective connectivity employing tasks to investigate negative emotion processing and regulation in healthy participants. Thirty-three studies met inclusion criteria. A quality assessment tool was derived from prominent neuroimaging papers. The evidence supports existing models, with primarily limbic regions for salience and identification, and frontal areas important for emotion regulation. There was mixed support for the assumption that regulatory influences on limbic and sensory areas come predominantly from prefrontal areas. Rather, studies quantifying effective connectivity reveal context-dependent dynamic modulatory relationships between occipital, subcortical, and frontal regions, arguing against purely top-down regulatory theoretical models. Our quality assessment tool found considerable variability in study design and tasks employed.

The findings support and extend those of previous syntheses focused on activation studies, and provide evidence for a more nuanced view of connectivity in networks of human emotion processing and regulation.

Mixed-effects multilevel analysis followed by canonical correlation analysis is an effective fMRI tool for the investigation of idiosyncrasies

We report that regions-of-interest (ROIs) associated with idiosyncratic individual behavior can be identified from functional magnetic resonance imaging (fMRI) data using statistical approaches that explicitly model individual variability in neuronal activations, such as mixed-effects multilevel analysis (MEMA). We also show that the relationship between neuronal activation in fMRI and behavioral data can be modeled using canonical correlation analysis (CCA). A real-world dataset for the neuronal response to nicotine use was acquired using a custom-made MRI-compatible apparatus for the smoking of electronic cigarettes (e-cigarettes). Nineteen participants smoked e-cigarettes in an MRI scanner using the apparatus with two experimental conditions: e-cigarettes with nicotine (ECIG) and sham e-cigarettes without nicotine (SCIG) and subjective ratings were collected. The right insula was identified in the ECIG condition from the χ² -test of the MEMA but not from the t-test, and the corresponding activations were significantly associated with the similarity scores (r = -.52, p = .041, confidence interval [CI] = [-0.78, -0.17]) and the urge-to-smoke scores (r = .73, p <.001, CI = [0.52, 0.88]). From the contrast between the two conditions (i.e., ECIG > SCIG), the right orbitofrontal cortex was identified from the χ² -tests, and the corresponding neuronal activations showed a statistically meaningful association with similarity (r = -.58, p = .01, CI = [-0.84, -0.17]) and the urge to smoke (r = .34, p = .15, CI = [0.09, 0.56]). The validity of our analysis pipeline (i.e., MEMA followed by CCA) was further evaluated using the fMRI and behavioral data acquired from the working memory and gambling tasks available from the Human Connectome Project.

Reinstatement of Event Details during Episodic Simulation in the Hippocampus

According to the constructive episodic simulation hypothesis, episodic simulation (i.e., imagining specific novel future episodes) draws on some of the same neurocognitive processes that support episodic memory (i.e., recalling specific past episodes). Episodic retrieval supports the ability to simulate future experiences by providing access to episodic details (e.g., the people and locations that comprise memories) that can be recombined in new ways. In the current functional neuroimaging study, we test this hypothesis by examining whether the hippocampus, a region implicated in the reinstatement of episodic information during memory, supports reinstatement of episodic information during simulation. Employing a multivoxel pattern similarity analysis, we interrogated the similarity between hippocampal neural patterns during memory and simulation at the level of individual event details. Our findings indicate that the hippocampus supports the reinstatement of detail-specific information from episodic memory during simulation, with the level of reinstatement contributing to the subjective experience of simulated details.

The missing N1 or jittered P2: Electrophysiological correlates of pattern glare in the time and frequency domain

Excessive sensitivity to certain visual stimuli (cortical hyperexcitability) is associated with a number of neurological disorders including migraine, epilepsy, multiple sclerosis, autism and possibly dyslexia. Others show disruptive sensitivity to visual stimuli with no other obvious pathology or symptom profile (visual stress) which can extend to discomfort and nausea. We used event‐related potentials (ERPs) to explore the neural correlates of visual stress and headache proneness. We analysed ERPs in response to thick (0.37 cycles per degree [c/deg]), medium (3 c/deg) and thin (12 c/deg) gratings, using mass univariate analysis, considering three factors in the general population: headache proneness, visual stress and discomfort. We found relationships between ERP features and the headache and discomfort factors. Stimulus main effects were driven by the medium stimulus regardless of participant characteristics. Participants with high discomfort ratings had larger P1 components for the initial presentation of medium stimuli, suggesting initial cortical hyperexcitability that is later suppressed. The participants with high headache ratings showed atypical N1‐P2 components for medium stripes relative to the other stimuli. This effect was present only after repeated stimulus presentation. These effects were also explored in the frequency domain, suggesting variations in intertrial theta band phase coherence. Our results suggest that discomfort and headache in response to striped stimuli are related to different neural processes; however, more exploration is needed to determine whether the results translate to a clinical migraine population.

Increased prefrontal top-down control in older adults predicts motor performance and age-group association

Bimanual motor control declines during ageing, affecting the ability of older adults to maintain independence. An important underlying factor is cortical atrophy, particularly affecting frontal and parietal areas in older adults. As these regions and their interplay are highly involved in bimanual motor preparation, we investigated age-related connectivity changes between prefrontal and premotor areas of young and older adults during the preparatory phase of complex bimanual movements using high-density electroencephalography. Generative modelling showed that excitatory inter-hemispheric prefrontal to premotor coupling in older adults predicted age-group affiliation and was associated with poor motor-performance. In contrast, excitatory intra-hemispheric prefrontal to premotor coupling enabled older adults to maintain motor-performance at the cost of lower movement speed. Our results disentangle the complex interplay in the prefrontal-premotor network during movement preparation underlying reduced bimanual control and the well-known speed-accuracy trade-off seen in older adults.

Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework

Methods for electro- or magnetoencephalography (EEG/MEG) based brain source imaging (BSI) using sparse Bayesian learning (SBL) have been demonstrated to achieve excellent performance in situations with low numbers of distinct active sources, such as event-related designs. This paper extends the theory and practice of SBL in three important ways. First, we reformulate three existing SBL algorithms under the majorization-minimization (MM) framework. This unification perspective not only provides a useful theoretical framework for comparing different algorithms in terms of their convergence behavior, but also provides a principled recipe for constructing novel algorithms with specific properties by designing appropriate bounds of the Bayesian marginal likelihood function. Second, building on the MM principle, we propose a novel method called LowSNR-BSI that achieves favorable source reconstruction performance in low signal-to-noise-ratio (SNR) settings. Third, precise knowledge of the noise level is a crucial requirement for accurate source reconstruction. Here we present a novel principled technique to accurately learn the noise variance from the data either jointly within the source reconstruction procedure or using one of two proposed cross-validation strategies. Empirically, we could show that the monotonous convergence behavior predicted from MM theory is confirmed in numerical experiments. Using simulations, we further demonstrate the advantage of LowSNR-BSI over conventional SBL in low-SNR regimes, and the advantage of learned noise levels over estimates derived from baseline data. To demonstrate the usefulness of our novel approach, we show neurophysiologically plausible source reconstructions on averaged auditory evoked potential data.

Computational approach to understand temporal and spatial tactile transmission processes from mechanical stimuli of the index fingertip to the primary somatosensory cortex

Mechanisms of information transmission using tactile sense are one of major concerns in producing simulated experience in virtual or augmented reality as well as in compensating elderly or impaired people with diminished tactile sensory function. However, important mechanism of the difference of peak latency in the primary somatosensory cortex (SI) between electrical and mechanical stimulations of finger skin is not fully understood. We propose a computational approach to fuse a computational model to simulate temporal and spatial transmission processes from mechanical stimuli to the SI and experimental method using a magnetoencephalograph (MEG). In our model, a tactile model that combined a three-dimensional mechanical model of fingertip skin and a neurophysiological model of a slowly adapting type 1 (SA1) mechanoreceptor was integrated with a somatosensory evoked field (SEF) response model. Electrical and mechanical stimulations were applied to the same locations of the right or left index fingertips of three subjects using a MEG. By identifying parameters of the SEF response model using the electrical stimulation test data, predicted first peak latency due to a mechanical stimulus was identical to its average value obtained from the mechanical stimulation test data, while the spatial map predicted at the multiple SA1 receptors qualitatively corresponded to the MEG image map in the timings of peak latency. This suggests that mechanical change in the skin and neurophysiological responses generate the difference of peak latency in SI between electrical and mechanical stimulations. The computational approach has the potential for detailed investigation of mechanisms of tactile information transmission.

The lateral intraparietal sulcus takes viewpoint changes into account during memory-guided attention in natural scenes

Previous studies demonstrated that long-term memory related to object-position in natural scenes guides visuo-spatial attention during subsequent search. Memory-guided attention has been associated with the activation of memory regions (the medial-temporal cortex) and with the fronto-parietal attention network. Notably, these circuits represent external locations with different frames of reference: egocentric (i.e., eyes/head-centered) in the dorsal attention network vs. allocentric (i.e., world/scene-centered) in the medial temporal cortex. Here we used behavioral measures and fMRI to assess the contribution of egocentric and allocentric spatial information during memory-guided attention. At encoding, participants were presented with real-world scenes and asked to search for and memorize the location of a high-contrast target superimposed in half of the scenes. At retrieval, participants viewed again the same scenes, now all including a low-contrast target. In scenes that included the target at encoding, the target was presented at the same scene-location. Critically, scenes were now shown either from the same or different viewpoint compared with encoding. This resulted in a memory-by-view design (target seen/unseen x same/different view), which allowed us teasing apart the role of allocentric vs. egocentric signals during memory-guided attention. Retrieval-related results showed greater search-accuracy for seen than unseen targets, both in the same and different views, indicating that memory contributes to visual search notwithstanding perspective changes. This view-change independent effect was associated with the activation of the left lateral intra-parietal sulcus. Our results demonstrate that this parietal region mediates memory-guided attention by taking into account allocentric/scene-centered information about the objects' position in the external world.

Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy

In functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions.

Neuro-Clinical Signatures of Language Impairments: A Theoretical Framework for Function-to-structure Mapping in Clinics

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.

Breast Cancer Image Classification: A Review

BACKGROUND

Breast cancer represents uncontrolled breast cell growth. Breast cancer is the most diagnosed cancer in women worldwide. Early detection of breast cancer improves the chances of survival and increases treatment options. There are various methods for screening breast cancer, such as mammogram, ultrasound, computed tomography and Magnetic Resonance Imaging (MRI). MRI is gaining prominence as an alternative screening tool for early detection and breast cancer diagnosis. Nevertheless, MRI can hardly be examined without the use of a Computer-Aided Diagnosis (CAD) framework, due to the vast amount of data.

OBJECTIVE

This paper aims to cover the approaches used in the CAD system for the detection of breast cancer.

METHODS

In this paper, the methods used in CAD systems are categories into two classes: the conventional approach and artificial intelligence (AI) approach.

RESULTS

The conventional approach covers the basic steps of image processing, such as preprocessing, segmentation, feature extraction and classification. The AI approach covers the various convolutional and deep learning networks used for diagnosis.

CONCLUSION

This review discusses some of the core concepts used in breast cancer and presents a comprehensive review of efforts in the past to address this problem.

Neural Mechanisms of Parental Communicative Adjustments in Spoken Language

During cultural transmission, caregivers typically adjust their form of speech according to the presumed characteristics of an infant/child, a phenomenon known as infant/child directed speech (IDS/CDS) or "parentese." Although ventromedial prefrontal cortex (vmPFC) damage was previously found to be associated with failure in adjusting non-verbal communicative behaviors, little is known about the neural mechanisms of verbal communicative adjustments, such as IDS/CDS. In the current study, 30 healthy mothers with preschool-age children underwent functional magnetic resonance imaging (fMRI) while performing a picture naming task which required them to name an object for either a child or an adult. In the picture naming task, mothers exhibited a longer naming duration in the toward-child condition than the toward-adult control condition. Naming an object for a child, compared with naming it for an adult, resulted in greater involvement in the vmPFC and other regions (e.g., cerebellum) in the global caregiving network. In particular, the vmPFC exhibited task-related deactivation and decreased functional connectivity with the supplementary motor, precentral, postcentral, and supramarginal regions. These findings suggest that the vmPFC, which is included in the default mode network, is involved in optimizing communicative behaviors for the inter-generational transmission of knowledge. This function of the vmPFC may be considered as a prosocial drive to lead to prosocial communicative behaviors depending on the context. This study provides a better understanding of the neural mechanisms involved in communicative adjustments for children and insight into related applied research fields such as parenting, pedagogy, and education.

Gender identity better than sex explains individual differences in episodic and semantic components of autobiographical memory: An fMRI study

Advances in the literature of sex-related differences in autobiographical memory increasingly tend to highlight the importance of psychosocial factors such as gender identity, which may explain these differences better than sex as a biological factor. To date, however, none of these behavioral studies have investigated this hypothesis using neuroimaging. The purpose of this fMRI study is to examine for the first time sex and gender identity-related differences in episodic and semantic autobiographical memory in healthy participants (M=19, W=18). No sex-related differences were found; however, sex-related effects of masculine and feminine gender identity were identified in men and women independently. These results confirm the hypothesis that differences in episodic and semantic autobiographical memory are best explained by gender but are an interaction between biological sex and gender identity and extend these findings to the field of neuroimaging. We discuss the importance of hormonal factors to be taken into consideration in the future.

Subthalamic Nucleus Deep Brain Stimulation Modulates 2 Distinct Neurocircuits

OBJECTIVE

Current understanding of the neuromodulatory effects of deep brain stimulation (DBS) on large-scale brain networks remains elusive, largely due to the lack of techniques that can reveal DBS-induced activity at the whole-brain level. Using a novel 3T magnetic resonance imaging (MRI)-compatible stimulator, we investigated whole-brain effects of subthalamic nucleus (STN) stimulation in patients with Parkinson disease.

METHODS

Fourteen patients received STN-DBS treatment and participated in a block-design functional MRI (fMRI) experiment, wherein stimulations were delivered during "ON" blocks interleaved with "OFF" blocks. fMRI responses to low-frequency (60Hz) and high-frequency(130Hz) STN-DBS were measured 1, 3, 6, and 12 months postsurgery. To ensure reliability, multiple runs (48 minutes) of fMRI data were acquired at each postsurgical visit. Presurgical resting-state fMRI (30 minutes) data were also acquired.

RESULTS

Two neurocircuits showed highly replicable, but distinct responses to STN-DBS. A circuit involving the globus pallidus internus (GPi), thalamus, and deep cerebellar nuclei was significantly activated, whereas another circuit involving the primary motor cortex (M1), putamen, and cerebellum showed DBS-induced deactivation. These 2 circuits were dissociable in terms of their DBS-induced responses and resting-state functional connectivity. The GPi circuit was frequency-dependent, selectively responding to high-frequency stimulation, whereas the M1 circuit was responsive in a time-dependent manner, showing enhanced deactivation over time. Finally, activation of the GPi circuit was associated with overall motor improvement, whereas M1 circuit deactivation was related to reduced bradykinesia.

INTERPRETATION

Concurrent DBS-fMRI using 3T revealed 2 distinct circuits that responded differentially to STN-DBS and were related to divergent symptoms, a finding that may provide novel insights into the neural mechanisms underlying DBS. ANN NEUROL 2020;88:1178-1193.

Rates of Brain Atrophy Across Disease Stages in Familial Frontotemporal Dementia Associated With MAPT, GRN, and C9orf72 Pathogenic Variants

Importance

Several clinical trials are planned for familial forms of frontotemporal lobar degeneration (f-FTLD). Precise modeling of brain atrophy in f-FTLD could improve the power to detect a treatment effect.

Objective

To characterize regions and rates of atrophy in the 3 primary f-FTLD genetic groups (MAPT, GRN, and C9orf72) across all disease stages from asymptomatic to dementia.

Design, Setting, and Participants

This investigation was a case-control study of participants enrolled in the Advancing Research and Treatment for Frontotemporal Lobar Degeneration or Longitudinal Evaluation of Familial Frontotemporal Dementia studies. The study took place at 18 North American academic medical centers between January 2009 and September 2018. Participants with f-FTLD (n = 100) with a known pathogenic variant (MAPT [n = 28], GRN [n = 33], or C9orf72 [n = 39]) were grouped according to disease stage (ie, Clinical Dementia Rating [CDR] plus National Alzheimer's Coordinating Center [NACC] FTLD module). Included were participants with at least 2 structural magnetic resonance images at presymptomatic (CDR + NACC FTLD = 0 [n = 57]), mild or questionable (CDR + NACC FTLD = 0.5 [n = 15]), or symptomatic (CDR + NACC FTLD = ≥1 [n = 28]) disease stages. The control group included family members of known pathogenic variant carriers who did not carry the pathogenic variant (n = 60).

Main Outcomes and Measures

This study fitted bayesian linear mixed-effects models in each voxel of the brain to quantify the rate of atrophy in each of the 3 genes, at each of the 3 disease stages, compared with controls. The study also analyzed rates of clinical decline in each of these groups, as measured by the CDR + NACC FTLD box score.

Results

The sample included 100 participants with f-FTLD with a known pathogenic variant (mean [SD] age, 50.48 [13.78] years; 53 [53%] female) and 60 family members of known pathogenic variant carriers who did not carry the pathogenic variant (mean [SD] age, 47.51 [12.43] years; 36 [60%] female). MAPT and GRN pathogenic variants were associated with increased rates of volume loss compared with controls at all stages of disease. In MAPT pathogenic variant carriers, statistically significant regions of accelerated volume loss compared with controls were identified in temporal regions bilaterally in the presymptomatic stage, with global spread in the symptomatic stage. For example, mean [SD] rates of atrophy in the left temporal were -231 [47] mm3 per year during the presymptomatic stage, -381 [208] mm3 per year during the mild stage, and -1485 [1025] mm3 per year during the symptomatic stage (P < .05). GRN pathogenic variant carriers generally had minimal increases in atrophy rates between the presymptomatic and mild stages, with rapid increases in atrophy rates in the symptomatic stages. For example, in the right frontal lobes, annualized volume loss was -267 [81] mm3 per year in the presymptomatic stage and -182 [90] mm3 per year in the mild stage, but -1169 [555] mm3 per year in the symptomatic stage. Compared with the other groups, C9orf72 expansion carriers showed minimal increases in rate of volume loss with disease progression. For example, the mean (SD) annualized rates of atrophy in the right frontal lobe in C9orf72 expansion carriers was -272 (118) mm3 per year in presymptomatic stages, -310 (189) mm3 per year in mildly symptomatic stages, and -251 (145) mm3 per year in symptomatic stages.

Conclusions and Relevance

These findings are relevant to clinical trial planning and suggest that the mechanism by which C9orf72 pathogenic variants lead to symptoms may be fundamentally different from the mechanisms associated with other pathogenic variants.

Differential effects of deep brain stimulation and levodopa on brain activity in Parkinson's disease

Levodopa is the first-line treatment for Parkinson’s disease, although the precise mechanisms mediating its efficacy remain elusive. We aimed to elucidate treatment effects of levodopa on brain activity during the execution of fine movements and to compare them with deep brain stimulation of the subthalamic nuclei. We studied 32 patients with Parkinson’s disease using functional MRI during the execution of finger-tapping task, alternating epochs of movement and rest. The task was performed after withdrawal and administration of a single levodopa dose. A subgroup of patients (n = 18) repeated the experiment after electrode implantation with stimulator on and off. Investigating levodopa treatment, we found a significant interaction between both factors of treatment state (off, on) and experimental task (finger tapping, rest) in bilateral putamen, but not in other motor regions. Specifically, during the off state of levodopa medication, activity in the putamen at rest was higher than during tapping. This represents an aberrant activity pattern probably indicating the derangement of basal ganglia network activity due to the lack of dopaminergic input. Levodopa medication reverted this pattern, so that putaminal activity during finger tapping was higher than during rest, as previously described in healthy controls. Within-group comparison with deep brain stimulation underlines the specificity of our findings with levodopa treatment. Indeed, a significant interaction was observed between treatment approach (levodopa, deep brain stimulation) and treatment state (off, on) in bilateral putamen. Our functional MRI study compared for the first time the differential effects of levodopa treatment and deep brain stimulation on brain motor activity. We showed modulatory effects of levodopa on brain activity of the putamen during finger movement execution, which were not observed with deep brain stimulation.

Self-other overlap and interpersonal neural synchronization serially mediate the effect of behavioral synchronization on prosociality

Behavioral synchronization has been found to facilitate social bonding and prosociality but the neural mechanisms underlying such effects are not well understood. In the current study, 60 dyads were hyperscanned using functional near-infrared spectroscopy while they performed either a synchronous key-pressing task or a control task. After the task, they were asked to perform the dictator game to assess their prosocial behavior. We also measured three potential mediating variables: self–other overlap, perceived similarity and interpersonal neural synchronization. Results showed that dyads in the synchronization group were higher in behavioral synchronization, interpersonal neural synchronization (INS) at the right dorsolateral prefrontal cortex, self–other overlap, perceived similarity and prosociality than those in the control group. INS was significantly associated with prosocial behaviors and self–other overlap. After testing four meditation models, we found that self–other overlap and INS played a serial mediation role in the effect of behavioral synchronization on prosociality. These results contribute to our understanding of the neural and cognitive mechanisms underlying the effect of behavioral synchronization on prosocial behavior.

Analysing brain networks in population neuroscience: a case for the Bayesian philosophy

Network connectivity fingerprints are among today's best choices to obtain a faithful sampling of an individual's brain and cognition. Widely available MRI scanners can provide rich information tapping into network recruitment and reconfiguration that now scales to hundreds and thousands of humans. Here, we contemplate the advantages of analysing such connectome profiles using Bayesian strategies. These analysis techniques afford full probability estimates of the studied network coupling phenomena, provide analytical machinery to separate epistemological uncertainty and biological variability in a coherent manner, usher us towards avenues to go beyond binary statements on existence versus non-existence of an effect, and afford credibility estimates around all model parameters at play which thus enable single-subject predictions with rigorous uncertainty intervals. We illustrate the brittle boundary between healthy and diseased brain circuits by autism spectrum disorder as a recurring theme where, we argue, network-based approaches in neuroscience will require careful probabilistic answers. This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Context-Dependent Coding of Temporal Distance Between Cinematic Events in the Human Precuneus

How temporal and contextual information interactively impact on behavior and brain activity during the retrieval of temporal order about naturalistic episodes remains incompletely understood. Here, we used fMRI to examine the effects of contextual signals derived from the content of the movie on the neural correlates underlying memory retrieval of temporal-order in human subjects of both sexes. By contrasting SAME versus DIFF storyline conditions during the retrieval of the temporal order of cinematic events, we found that the activation in the precuneus, as well as behavior, are significantly modulated according to storyline condition, supporting our prediction of contextual information contributing to temporal retrieval. We suggest that the precuneus engages in memory retrieval via reconstructive mechanisms, entailing search within a movie-specific, situational knowledge-structure. Furthermore, information-based analyses of multivoxel activity revealed that the precuneus also contains a context-independent linear representation of temporal distances, consistent with a chronological organization of memory traces. We thus put forward that the retrieval of the temporal-order of naturalistic events encoded in rich and dynamic contexts relies on the joint contribution of chronological and reconstructive mechanisms, both of which rely on the medioposterior parietal cortex in humans.SIGNIFICANCE STATEMENT Successful retrieval of episodic memory is dependent on both temporal and contextual signals. However, when contextual signals derived from multiple storylines or narratives are complex and intertwined, the behavioral and neural correlates underpinning the interplay between time and context is not completely understood. Here we characterized the activation level and multivoxel pattern of BOLD signals underlying the modulation of such contextual information during temporal order judgment in the precuneus. Our findings provide us with an elucidation of subprocesses implicating the medial parietal cortex in realizing temporal organization of episodic details.

An fMRI Study on Self-Perception of Patients after Aesthetic Implant-Prosthetic Rehabilitation

Objectives: In this functional magnetic resonance (fMRI) study, we investigated the activation of cerebral pathways involved in the elaboration of self-retracting photos (SELF) and the same pictures of others (OTHER). Each of the photographs showed one of the participants during different stages of the rehabilitation: pre-treatment (PRE), virtual planning using “Smile-Lynx” smile design software (VIR), and post-rehabilitation (POST). Methods: We selected eighteen volunteers, both male and female, between 22 and 67 years of age, who previously underwent prosthetic rehabilitation. Each of them was subjected to an fMRI acquisition. Various stimuli were then shown to the subjects in the form of self-retracting photographs and photographs of other participants, all in pseudo-randomized order. We then carried out a two- stage mixed-effects group data analysis with statistical contrast targeting two main effects: one regarding the main effect of Identity (SELF vs. OTHER) and the other regarding the effect of the prosthetic rehabilitation phase (PRE vs. VIR vs. POS). All the effects mentioned above survived a peak-level of p < 0.05. Results: For the effect of identity, results reported the involvement of dorsolateral frontoparietal areas bilaterally. For the phase by identity effect, results reported activation in the supplementary motor area (SMA) in the right hemisphere. A stronger activation in observing self-retracting photos (SELF) post-treatment (POST) was reported compared to the other phases considered in the experiment. Conclusions: All the collected data showed differences regarding the main effect of Identity (SELF vs. OTHER). Most importantly, the present study provides some trend-wise evidence that the pictures portraying the subject in their actual physiognomy (POST) have a somewhat special status in eliciting selectively greater brain activation in the SMA. This effect was interpreted as a plausible correlate of an empathic response for beautiful and neutral faces. The present research suggests a possible way to measure self-perception of the subject after an appearance-altering procedure such an implant-prosthetic rehabilitation. However, future clinical studies are needed to investigate this matter further.

Are you laughing at me? Neural correlates of social intent attribution to auditory and visual laughter

Laughter is a multifaceted signal, which can convey social acceptance facilitating social bonding as well as social rejection inflicting social pain. In the current study, we addressed the neural correlates of social intent attribution to auditory or visual laughter within an fMRI study to identify brain areas showing linear increases of activation with social intent ratings. Negative social intent attributions were associated with activation increases within the medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC). Interestingly, negative social intent attributions of auditory laughter were represented more rostral than visual laughter within this area. Our findings corroborate the role of the mPFC/ACC as key node for processing “social pain” with distinct modality‐specific subregions. Other brain areas that showed an increase of activation included bilateral inferior frontal gyrus and right superior/middle temporal gyrus (STG/MTG) for visually presented laughter and bilateral STG for auditory presented laughter with no overlap across modalities. Similarly, positive social intent attributions were linked to hemodynamic responses within the right inferior parietal lobe and right middle frontal gyrus, but there was no overlap of activity for visual and auditory laughter. Our findings demonstrate that social intent attribution to auditory and visual laughter is located in neighboring, but spatially distinct neural structures.

Brain-Heart Pathways to Blood Pressure-Related Hypoalgesia

OBJECTIVE

High blood pressure (BP) is associated with reduced pain sensitivity, known as BP-related hypoalgesia. The underlying neural mechanisms remain uncertain, yet arterial baroreceptor signaling, occurring at cardiac systole, is implicated. We examined normotensives using functional neuroimaging and pain stimulation during distinct phases of the cardiac cycle to test the hypothesized neural mediation of baroreceptor-induced attenuation of pain.

METHODS

Eighteen participants (10 women; 32.7 (6.5) years) underwent BP monitoring for 1 week at home, and individual pain thresholds were determined in the laboratory. Subsequently, participants were administered unpredictable painful and nonpainful electrocutaneous shocks (stimulus type), timed to occur either at systole or at diastole (cardiac phase) in an event-related design. After each trial, participants evaluated their subjective experience.

RESULTS

Subjective pain was lower for painful stimuli administered at systole compared with diastole, F(1, 2283) = 4.82, p = 0.03. Individuals with higher baseline BP demonstrated overall lower pain perception, F(1, 2164) = 10.47, p < .0001. Within the brain, painful stimulation activated somatosensory areas, prefrontal cortex, cingulate cortex, posterior insula, amygdala, and the thalamus. Stimuli delivered during systole (concurrent with baroreceptor discharge) activated areas associated with heightened parasympathetic drive. No stimulus type by cardiac phase interaction emerged except for a small cluster located in the right parietal cortex.

CONCLUSIONS

We confirm the negative associations between BP and pain, highlighting the antinociceptive impact of baroreceptor discharge. Neural substrates associated with baroreceptor/BP-related hypoalgesia include superior parietal lobule, precentral, and lingual gyrus, regions typically involved in the cognitive aspects of pain experience.