Accurate modeling of temporal correlations in rapidly sampled fMRI time series

The impact of past childhood adversity and recent life events on neural responses during fear conditioning

BACKGROUND AND PURPOSE

Many studies have shown that exposure to life events can have a negative impact on mental health. Life events like the death of a spouse or the birth of a child pose a challenge and require temporal or permanent adjustments. Meta-analyses on brain stress responses found bilateral anterior insula activation in response to acute stress. Fear conditioning is assumed a crucial mechanism for the development of anxiety disorders associated with increased activation in the bilateral amygdala. Empirical evidence is lacking regarding the relationship of exposure to recent life events and past childhood adversity with neural processing during fear conditioning.

METHODS

In the present study, we analyzed data from 103 young, healthy participants. Multiple linear regressions were performed on functional magnetic resonance imaging activation during fear conditioning with the Life Events Scale for Students and the Childhood Trauma questionnaire included as covariates in two separate models.

RESULTS

We found a positive relationship between the number of life events in the last year and left amygdala activation to the conditioned stimulus. A second finding was a positive relationship between childhood adversity and right anterior insula response to the unconditioned stimulus.

CONCLUSIONS

Many studies have shown increased amygdala activity after stressful life events. In addition, the anterior insula is activated during acute stress. The present study points to stressor-induced increased salience processing during fear conditioning. We suggest that this could be a potential mechanism for resilience versus mental illness.

The significance of structural rich club hubs for the processing of hierarchical stimuli

The brain's structural network follows a hierarchy that is described as rich club (RC) organization, with RC hubs forming the well-interconnected top of this hierarchy. In this study, we tested whether RC hubs are involved in the processing of hierarchically higher structures in stimulus sequences. Moreover, we explored the role of previously suggested cortical gradients along anterior-posterior and medial-lateral axes throughout the frontal cortex. To this end, we conducted a functional magnetic resonance imaging (fMRI) experiment and presented participants with blocks of digit sequences that were structured on different hierarchically nested levels. We additionally collected diffusion weighted imaging data of the same subjects to identify RC hubs. This classification then served as the basis for a region of interest analysis of the fMRI data. Moreover, we determined structural network centrality measures in areas that were found as activation clusters in the whole-brain fMRI analysis. Our findings support the previously found anterior and medial shift for processing hierarchically higher structures of stimuli. Additionally, we found that the processing of hierarchically higher structures of the stimulus structure engages RC hubs more than for lower levels. Areas involved in the functional processing of hierarchically higher structures were also more likely to be part of the structural RC and were furthermore more central to the structural network. In summary, our results highlight the potential role of the structural RC organization in shaping the cortical processing hierarchy.

Superior Attentional Efficiency of Auditory Cue via the Ventral Auditory-thalamic Pathway

Auditory commands are often executed more efficiently than visual commands. However, empirical evidence on the underlying behavioral and neural mechanisms remains scarce. In two experiments, we manipulated the delivery modality of informative cues and the prediction violation effect and found consistently enhanced RT benefits for the matched auditory cues compared with the matched visual cues. At the neural level, when the bottom-up perceptual input matched the prior prediction induced by the auditory cue, the auditory-thalamic pathway was significantly activated. Moreover, the stronger the auditory-thalamic connectivity, the higher the behavioral benefits of the matched auditory cue. When the bottom-up input violated the prior prediction induced by the auditory cue, the ventral auditory pathway was specifically involved. Moreover, the stronger the ventral auditory-prefrontal connectivity, the larger the behavioral costs caused by the violation of the auditory cue. In addition, the dorsal frontoparietal network showed a supramodal function in reacting to the violation of informative cues irrespective of the delivery modality of the cue. Taken together, the results reveal novel behavioral and neural evidence that the superior efficiency of the auditory cue is twofold: The auditory-thalamic pathway is associated with improvements in task performance when the bottom-up input matches the auditory cue, whereas the ventral auditory-prefrontal pathway is involved when the auditory cue is violated.

A novel technique for delineating the effect of variation in the learning rate on the neural correlates of reward prediction errors in model-based fMRI

Introduction

Computational models play an increasingly important role in describing variation in neural activation in human neuroimaging experiments, including evaluating individual differences in the context of psychiatric neuroimaging. In particular, reinforcement learning (RL) techniques have been widely adopted to examine neural responses to reward prediction errors and stimulus or action values, and how these might vary as a function of clinical status. However, there is a lack of consensus around the importance of the precision of free parameter estimation for these methods, particularly with regard to the learning rate. In the present study, I introduce a novel technique which may be used within a general linear model (GLM) to model the effect of mis-estimation of the learning rate on reward prediction error (RPE)-related neural responses.

Methods

Simulations employed a simple RL algorithm, which was used to generate hypothetical neural activations that would be expected to be observed in functional magnetic resonance imaging (fMRI) studies of RL. Similar RL models were incorporated within a GLM-based analysis method including derivatives, with individual differences in the resulting GLM-derived beta parameters being evaluated with respect to the free parameters of the RL model or being submitted to other validation analyses.

Results

Initial simulations demonstrated that the conventional approach to fitting RL models to RPE responses is more likely to reflect individual differences in a reinforcement efficacy construct (lambda) rather than learning rate (alpha). The proposed method, adding a derivative regressor to the GLM, provides a second regressor which reflects the learning rate. Validation analyses were performed including examining another comparable method which yielded highly similar results, and a demonstration of sensitivity of the method in presence of fMRI-like noise.

Conclusion

Overall, the findings underscore the importance of the lambda parameter for interpreting individual differences in RPE-coupled neural activity, and validate a novel neural metric of the modulation of such activity by individual differences in the learning rate. The method is expected to find application in understanding aberrant reinforcement learning across different psychiatric patient groups including major depression and substance use disorder.

Stimulus awareness is associated with secondary somatosensory cortex activation in an inattentional numbness paradigm

While inattentional blindness and deafness studies have revealed neural correlates of consciousness (NCC) without the confound of task relevance in the visual and auditory modality, comparable studies for the somatosensory modality are lacking. Here, we investigated NCC using functional magnetic resonance imaging (fMRI) in an inattentional numbness paradigm. Participants (N = 44) received weak electrical stimulation on the left hand while solving a demanding visual task. Half of the participants were informed that task-irrelevant weak tactile stimuli above the detection threshold would be applied during the experiment, while the other half expected stimuli below the detection threshold. Unexpected awareness assessments after the experiment revealed that altogether 10 participants did not consciously perceive the somatosensory stimuli during the visual task. Awareness was not significantly modulated by prior information. The fMRI data show that awareness of stimuli led to increased activation in the contralateral secondary somatosensory cortex. We found no significant effects of stimulus awareness in the primary somatosensory cortex or frontoparietal areas. Thus, our results support the hypothesis that somatosensory stimulus awareness is mainly based on activation in higher areas of the somatosensory cortex and does not require strong activation in extended anterior or posterior networks, which is usually seen when perceived stimuli are task-relevant.

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

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

If you're happy and you know it: neural correlates of self-evaluated psychological health and well-being

Psychological health and well-being have important implications for individual and societal thriving. Research underscores the subjective nature of well-being, but how do individuals intuit this subjective sense of well-being in the moment? This pre-registered study addresses this question by examining the neural correlates of self-evaluated psychological health and their dynamic relationship with trial-level evaluations. Participants (N = 105) completed a self-evaluation task and made judgments about three facets of psychological health and positive functioning-self-oriented well-being, social well-being and ill-being. Consistent with pre-registered hypotheses, self-evaluation elicited activity in the default mode network, and there was strong spatial overlap among constructs. Trial-level analyses assessed whether and how activity in a priori regions of interest-perigenual anterior cingulate cortex (pgACC), ventromedial prefrontal cortex (vmPFC) and ventral striatum-were related to subjective evaluations. These regions explained additional variance in whether participants endorsed or rejected items but were differentially related to evaluations. Stronger activity in pgACC was associated with a higher probability of endorsement across constructs, whereas stronger activity in vmPFC was associated with a higher probability of endorsing ill-being items, but a lower probability of endorsing self-oriented and social well-being items. These results add nuance to neurocognitive accounts of self-evaluation and extend our understanding of the neurobiological basis of subjective psychological health and well-being.

Cognitive tasks affect the relationship between representational pattern similarity and subsequent item memory in the hippocampus

Episodic memories are records of personally experienced events, coded neurally via the hippocampus and surrounding medial temporal lobe cortex. Information about the neural signal corresponding to a memory representation can be measured in fMRI data when the pattern across voxels is examined. Prior studies have found that similarity in the voxel patterns across repetition of a to-be-remembered stimulus predicts later memory retrieval, but the results are inconsistent across studies. The current study investigates the possibility that cognitive goals (defined here via the task instructions given to participants) during encoding affect the voxel pattern that will later support memory retrieval, and therefore that neural representations cannot be interpreted based on the stimulus alone. The behavioral results showed that exposure to variable cognitive tasks across repetition of events benefited subsequent memory retrieval. Voxel patterns in the hippocampus indicated a significant interaction between cognitive tasks (variable vs. consistent) and memory (remembered vs. forgotten) such that reduced voxel pattern similarity for repeated events with variable cognitive tasks, but not consistent cognitive tasks, supported later memory success. There was no significant interaction in neural pattern similarity between cognitive tasks and memory success in medial temporal cortices or lateral occipital cortex. Instead, higher similarity in voxel patterns in right medial temporal cortices was associated with later memory retrieval, regardless of cognitive task. In conclusion, we found that the relationship between pattern similarity across repeated encoding and memory success in the hippocampus (but not medial temporal lobe cortex) changes when the cognitive task during encoding does or does not vary across repetitions of the event.

Anticipating social feedback involves basal forebrain and mesolimbic functional connectivity

The mesolimbic system and basal forebrain (BF) are implicated in processing rewards and punishment, but their interplay and functional properties of subregions with respect to future social outcomes remain unclear. Therefore, this study investigated regional responses and interregional functional connectivity of the lateral (l), medial (m), and ventral (v) Substantia Nigra (SN), Nucleus Accumbens (NAcc), Nucleus basalis of Meynert (NBM), and Medial Septum/Diagonal Band (MS/DB) during reward and punishment anticipation in a social incentive delay task with neutral, positive, and negative feedback using high-resolution fMRI (1.5mm³). Neuroimaging data (n=36 healthy humans) of the anticipation phase was analyzed using mass-univariate, functional connectivity, and multivariate-pattern analysis. As expected, participants responded faster when anticipating positive and negative compared to neutral social feedback. At the neural level, anticipating social information engaged valence-related and valence-unrelated functional connectivity patterns involving the BF and mesolimbic areas. Precisely, valence-related connectivity between the lSN and NBM was associated with anticipating neutral social feedback, while connectivity between the vSN and NBM was associated with anticipating positive social feedback. A more complex pattern was observed for anticipating negative social feedback, including connectivity between the lSN and MS/DB, lSN and NAcc, as well as mSN and NAcc. To conclude, behavioral responses are modulated by the possibility to obtain positive and avoid negative social feedback. The neural processing of feedback anticipation relies on functional connectivity patterns between the BF and mesolimbic areas associated with the emotional valence of the social information. As such, our findings give novel insights into the underlying neural processes of social information processing.

MP-PCA denoising of fMRI time-series data can lead to artificial activation "spreading"

MP-PCA denoising has become the method of choice for denoising MRI data since it provides an objective threshold to separate the signal components from unwanted thermal noise components. In rodents, thermal noise in the coils is an important source of noise that can reduce the accuracy of activation mapping in fMRI. Further confounding this problem, vendor data often contains zero-filling and other post-processing steps that may violate MP-PCA assumptions. Here, we develop an approach to denoise vendor data and assess activation "spreading" caused by MP-PCA denoising in rodent task-based fMRI data. Data was obtained from N = 3 mice using conventional multislice and ultrafast acquisitions (1 s and 50 ms temporal resolution, respectively), during visual stimulation. MP-PCA denoising produced SNR gains of 64% and 39% and Fourier Spectral Amplitude (FSA) increases in BOLD maps of 9% and 7% for multislice and ultrafast data, respectively, when using a small [2 2] denoising window. Larger windows provided higher SNR and FSA gains with increased spatial extent of activation that may or may not represent real activation. Simulations showed that MP-PCA denoising can incur activation "spreading" with increased false positive rate and smoother functional maps due to local "bleeding" of principal components, and that the optimal denoising window for improved specificity of functional mapping, based on Dice score calculations, depends on the data's tSNR and functional CNR. This "spreading" effect applies also to another recently proposed low-rank denoising method (NORDIC), although to a lesser degree. Our results bode well for enhancing spatial and/or temporal resolution in future fMRI work, while taking into account the sensitivity/specificity trade-offs of low-rank denoising methods.

Neural Basis of Social Influence of Observing Other's Perception in Dot-Number Estimation

Our perceptions and decisions are often implicitly influenced by observing another's actions. However, it is unclear how observing other people's perceptual decisions without interacting with them can engage the processing of self-other discrepancies and change the observer's decisions. In this study, we employed functional magnetic resonance imaging and a computational model to investigate the neural basis of how unilaterally observing the other's perceptual decisions modulated one's own decisions. The experimental task was to discriminate whether the number of presented dots was higher or lower than a reference number. The participants performed the task solely while unilaterally observing the performance of another "participant," who produced overestimations and underestimations in the same task in separate sessions. Results of the behavioral analysis showed that the participants' decisions were modulated to resemble those of the other. Image analysis based on computational model revealed that the activation in the medial prefrontal cortex was associated with the discrepancy between the inferred participant's and the presented other's decisions. In addition, the number-sensitive region in the superior parietal region showed altered activation patterns after observing the other's overestimations and underestimations. The activity of the superior parietal region was not involved in assessing the observation of other's perceptual decisions, but it was engaged in plain numerosity perception. These results suggest that computational modeling can capture the neuro-behavioral processing of self-other discrepancies in perception followed by the activity modulation in the number-sensitive region in the task of dot-number estimation.

Microstructural and neurochemical plasticity mechanisms interact to enhance human perceptual decision-making

Experience and training are known to boost our skills and mold the brain's organization and function. Yet, structural plasticity and functional neurotransmission are typically studied at different scales (large-scale networks, local circuits), limiting our understanding of the adaptive interactions that support learning of complex cognitive skills in the adult brain. Here, we employ multimodal brain imaging to investigate the link between microstructural (myelination) and neurochemical (GABAergic) plasticity for decision-making. We test (in males, due to potential confounding menstrual cycle effects on GABA measurements in females) for changes in MRI-measured myelin, GABA, and functional connectivity before versus after training on a perceptual decision task that involves identifying targets in clutter. We demonstrate that training alters subcortical (pulvinar, hippocampus) myelination and its functional connectivity to visual cortex and relates to decreased visual cortex GABAergic inhibition. Modeling interactions between MRI measures of myelin, GABA, and functional connectivity indicates that pulvinar myelin plasticity interacts-through thalamocortical connectivity-with GABAergic inhibition in visual cortex to support learning. Our findings propose a dynamic interplay of adaptive microstructural and neurochemical plasticity in subcortico-cortical circuits that supports learning for optimized decision-making in the adult human brain.

Social Touch Reduces Pain Perception—An fMRI Study of Cortical Mechanisms

Unmyelinated low-threshold mechanoreceptors (C-tactile, CT) in the human skin are important for signaling information about hedonic aspects of touch. We have previously reported that CT-targeted brush stroking by means of a robot reduces experimental mechanical pain. To improve the ecological validity of the stimulation, we developed standardized human–human touch gestures for signaling attention and calming. The attention gesture is characterized by tapping of the skin and is perceived as neither pleasant nor unpleasant, i.e., neutral. The calming gesture is characterized by slow stroking of the skin and is perceived as moderately to very pleasant. Furthermore, the attention (tapping) gesture is ineffective, whereas the calming (stroking) gesture is effective in activating CT-afferents. We conducted an fMRI study (n = 32) and capitalized on the previous development of touch gestures. We also developed an MR compatible stimulator for high-precision mechanical pain stimulation of the thenar region of the hand. Skin-to-skin touching (stroking or tapping) was applied and was followed by low and high pain. When the stroking gesture preceded pain, the pain was rated as less intense. When the tapping gesture preceded the pain, the pain was rated as more intense. Individual pain perception related to insula activation, but the activation was not higher for stroking than for tapping in any brain area during the stimulation period. However, during the evaluation period, stronger activation in the periaqueductal gray matter was observed after calming touch compared to after tapping touch. This finding invites speculation that human–human gentle skin stroking, effective in activating CT-afferents, reduced pain through neural processes involving CT-afferents and the descending pain pathway.

Neural correlates of affective task switching and asymmetric affective task switching costs

The control of emotions is of potentially great clinical relevance. Accordingly, there has been increasing interest in understanding the cognitive mechanisms underlying the ability to switch efficiently between the processing of affective and non-affective information. Reports of asymmetrically increased switch costs when switching toward the more salient emotion task indicate specific demands in the flexible control of emotion. The neural mechanisms underlying affective task switching, however, are so far not fully understood. Using functional Magnetic Resonance Imaging (MRI) (N = 57), we observed that affective task switching was accompanied by increased activity in domain-general fronto-parietal control systems. Blood-oxygen-level-dependent (BOLD) activity in the posterior medial frontal and anterolateral prefrontal cortex was directly related to affective switch costs, indicating that these regions play a particular role in individual differences in (affective) task-switching ability. Asymmetric switch costs were associated with increased activity in the right inferior frontal and dorsal anterior medial prefrontal cortex, two brain regions critical for response inhibition. This suggests that asymmetric switch costs might-to a great extent-reflect higher demands on inhibitory control of the dominant emotion task. These results contribute to a refined understanding of brain systems for the flexible control of emotions and thereby identify valuable target systems for future clinical research.

Transcranial direct current stimulation with functional magnetic resonance imaging: a detailed validation and operational guide

Introduction: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique used to modulate human brain and behavioural function in both research and clinical interventions. The combination of functional magnetic resonance imaging (fMRI) with tDCS enables researchers to directly test causal contributions of stimulated brain regions, answering questions about the physiology and neural mechanisms underlying behaviour. Despite the promise of the technique, advances have been hampered by technical challenges and methodological variability between studies, confounding comparability/replicability. Methods: Here tDCS-fMRI at 3T was developed for a series of experiments investigating language recovery after stroke. To validate the method, one healthy volunteer completed an fMRI paradigm with three conditions: No-tDCS, Sham-tDCS, Anodal-tDCS. MR data were analysed with region-of-interest (ROI) analyses of the electrodes and reference site. Results: Quality assessment indicated no visible signal dropouts or distortions in the brain introduced by the tDCS equipment. After modelling scanner drift, motion-related variance, and temporal autocorrelation, we found that functional MR sensitivity was not degraded or adversely affected by the tDCS set-up and stimulation protocol across conditions in grey matter and in the three ROIs. Discussion: Key safety factors and risk mitigation strategies that must be taken into consideration when integrating tDCS into an fMRI environment are outlined. To obtain reliable results, we provide practical solutions to technical challenges and complications of the method. It is hoped that sharing these data and Standard Operation Procedure (SOP) will promote methodological replication in future studies, enhancing the quality of tDCS-fMRI application, and improve the reliability of scientific results in this field. Conclusions: Our method and data provide a technically safe, reliable tDCS-fMRI procedure to obtain high quality MR data. The detailed framework of the SOP systematically reports the technical and procedural elements of our tDCS-fMRI approach, which can be adopted and prove useful in future studies.

Sources of residual autocorrelation in multiband task fMRI and strategies for effective mitigation

Introduction

Analysis of task fMRI studies is typically based on using ordinary least squares within a voxel- or vertex-wise linear regression framework known as the general linear model. This use produces estimates and standard errors of the regression coefficients representing amplitudes of task-induced activations. To produce valid statistical inferences, several key statistical assumptions must be met, including that of independent residuals. Since task fMRI residuals often exhibit temporal autocorrelation, it is common practice to perform "prewhitening" to mitigate that dependence. Prewhitening involves estimating the residual correlation structure and then applying a filter to induce residual temporal independence. While theoretically straightforward, a major challenge in prewhitening for fMRI data is accurately estimating the residual autocorrelation at each voxel or vertex of the brain. Assuming a global model for autocorrelation, which is the default in several standard fMRI software tools, may under- or over-whiten in certain areas and produce differential false positive control across the brain. The increasing popularity of multiband acquisitions with faster temporal resolution increases the challenge of effective prewhitening because more complex models are required to accurately capture the strength and structure of autocorrelation. These issues are becoming more critical now because of a trend toward subject-level analysis and inference. In group-average or group-difference analyses, the within-subject residual correlation structure is accounted for implicitly, so inadequate prewhitening is of little real consequence. For individual subject inference, however, accurate prewhitening is crucial to avoid inflated or spatially variable false positive rates.

Methods

In this paper, we first thoroughly examine the patterns, sources and strength of residual autocorrelation in multiband task fMRI data. Second, we evaluate the ability of different autoregressive (AR) model-based prewhitening strategies to effectively mitigate autocorrelation and control false positives. We consider two main factors: the choice of AR model order and the level of spatial regularization of AR model coefficients, ranging from local smoothing to global averaging. We also consider determining the AR model order optimally at every vertex, but we do not observe an additional benefit of this over the use of higher-order AR models (e.g. (AR(6)). To overcome the computational challenge associated with spatially variable prewhitening, we developed a computationally efficient R implementation using parallelization and fast C++ backend code. This implementation is included in the open source R package BayesfMRI.

Results

We find that residual autocorrelation exhibits marked spatial variance across the cortex and is influenced by many factors including the task being performed, the specific acquisition protocol, mis-modeling of the hemodynamic response function, unmodeled noise due to subject head motion, and systematic individual differences. We also find that local regularization is much more effective than global averaging at mitigating autocorrelation. While increasing the AR model order is also helpful, it has a lesser effect than allowing AR coefficients to vary spatially. We find that prewhitening with an AR(6) model with local regularization is effective at reducing or even eliminating autocorrelation and controlling false positives.

Conclusion

Our analysis revealed dramatic spatial differences in autocorrelation across the cortex. This spatial topology is unique to each session, being influenced by the task being performed, the acquisition technique, various modeling choices, and individual differences. If not accounted for, these differences will result in differential false positive control and power across the cortex and across subjects.

Functional relevance of the extrastriate body area for visual and haptic object recognition: a preregistered fMRI-guided TMS study

The extrastriate body area (EBA) is a region in the lateral occipito-temporal cortex (LOTC), which is sensitive to perceived body parts. Neuroimaging studies suggested that EBA is related to body and tool processing, regardless of the sensory modalities. However, how essential this region is for visual tool processing and nonvisual object processing remains a matter of controversy. In this preregistered fMRI-guided repetitive transcranial magnetic stimulation (rTMS) study, we examined the causal involvement of EBA in multisensory body and tool recognition. Participants used either vision or haptics to identify 3 object categories: hands, teapots (tools), and cars (control objects). Continuous theta-burst stimulation (cTBS) was applied over left EBA, right EBA, or vertex (control site). Performance for visually perceived hands and teapots (relative to cars) was more strongly disrupted by cTBS over left EBA than over the vertex, whereas no such object-specific effect was observed in haptics. The simulation of the induced electric fields confirmed that the cTBS affected regions including EBA. These results indicate that the LOTC is functionally relevant for visual hand and tool processing, whereas the rTMS over EBA may differently affect object recognition between the 2 sensory modalities.

Neural processing of self-touch and other-touch in anorexia nervosa and autism spectrum condition

INTRODUCTION

The tactile sense plays a crucial role in the development and maintenance of a functional bodily self. The ability to differentiate between self- and nonself-generated touch contributes to the perception of the bodies' boundaries and more generally to self-other-distinction, both of which are thought be altered in anorexia nervosa (AN) and autism spectrum condition (AS). While it has been suggested that AN and AS are characterized by overlapping symptomatology, they might differ regarding body perception and self-other-distinction.

METHODS

Participants with a diagnosis of AN (n = 25), AS (n = 29), and a comparison group without diagnoses (n = 57) performed a self-other-touch task during functional brain imaging. In the experimental conditions, they stroked their own arm or were stroked on the arm by an experimenter.

RESULTS

As shown previously, the CG group showed lower activation or deactivation in response to self-touch compared to social touch from someone else. A main group effect was found in areas including somatosensory cortex, frontal and temporal gyri, insula, and subcortical regions. This was driven by increased activations in participants with AN, while participants in the AS group showed mostly comparable activations to the comparison group.

CONCLUSIONS

AN diagnosis was associated with an increased neural activity in response to both self-touch and social touch. Failure to attenuate self-touch might relate to altered predictions regarding the own body and reduced perception of bodily boundaries. Participants with an AS diagnosis were mostly comparable to the comparison group, potentially indicating unaltered tactile self-other-distinction.

A comparison of multiband and multiband multiecho gradient-echo EPI for task fMRI at 3 T

A multiband (MB) echo-planar imaging (EPI) sequence is compared to a multiband multiecho (MBME) EPI protocol to investigate differences in sensitivity for task functional magnetic resonance imaging (fMRI) at 3 T. Multiecho sampling improves sensitivity in areas where single-echo-EPI suffers from dropouts. However, It requires in-plane acceleration to reduce the echo train length, limiting the slice acceleration factor and the temporal and spatial resolution Data were acquired for both protocols in two sessions 24 h apart using an adapted color-word interference Stroop task. Besides protocol comparison statistically, we performed test-retest reliability across sessions for different protocols and denoising methods. We evaluated the sensitivity of two different echo-combination strategies for MBME-EPI. We examined the performance of three different data denoising approaches: "Standard," "AROMA," and "FIX" for MB and MBME, and assessed whether a specific method is preferable. We consider using an appropriate autoregressive model order within the general linear model framework to correct TR differences between the protocols. The comparison between protocols and denoising methods showed at group level significantly higher mean z-scores and the number of active voxels for MBME in the motor, subcortical and medial frontal cortices. When comparing different echo combinations, our results suggest that a contrast-to-noise ratio weighted echo combination improves sensitivity in MBME compared to simple echo-summation. This study indicates that MBME can be a preferred protocol in task fMRI at spatial resolution (≥2 mm), primarily in medial prefrontal and subcortical areas.

A functional neuroimaging study of self-other processing alterations in atypical developmental trajectories of psychotic-like experiences

Self-disturbances constitute a hallmark of psychosis, but it remains unclear whether these alterations are present in at-risk populations, and therefore their role in the development of psychosis has yet to be confirmed. The present study addressed this question by measuring neural correlates of self-other processing in youth belonging to three developmental trajectories of psychotic experiences. Eighty-six youths were recruited from a longitudinal cohort of over 3800 adolescents based on their trajectories of Psychotic-Like Experiences from 12 to 16 years of age. Participants underwent neuroimaging at 17 years of age (mean). A functional neuroimaging task evaluating self- and other-related trait judgments was used to measure whole-brain activation and connectivity. Youth who showed an increasing trajectory displayed hypoactivation of the dorsomedial prefrontal cortex and hypoconnectivity with the cerebellum. By contrast, youth who showed a decreasing trajectory displayed decreased activation of the superior temporal gyrus, the inferior frontal gyrus, and the middle occipital gyrus. These findings suggest that the increasing trajectory is associated with alterations that might erode distinctions between self and other, influencing the emergence of symptoms such as hallucinations. The decreasing trajectory, in comparison, was associated with hypoactivations in areas influencing attention and basic information processing more generally. These alterations might affect the trajectories’ susceptibilities to positive vs. negative symptoms, respectively.

Enhanced Mirror Neuron Network Activity and Effective Connectivity during Live Interaction Among Female Subjects

Facial expressions are indispensable in daily human communication. Previous neuroimaging studies investigating facial expression processing have presented pre-recorded stimuli and lacked live face-to-face interaction. Our paradigm alternated between presentations of real-time model performance and pre-recorded videos of dynamic facial expressions to participants. Simultaneous functional magnetic resonance imaging (fMRI) and facial electromyography activity recordings, as well as post-scan valence and arousal ratings were acquired from 44 female participants. Live facial expressions enhanced the subjective valence and arousal ratings as well as facial muscular responses. Live performances showed greater engagement of the right posterior superior temporal sulcus (pSTS), right inferior frontal gyrus (IFG), right amygdala and right fusiform gyrus, and modulated the effective connectivity within the right mirror neuron system (IFG, pSTS, and right inferior parietal lobule). A support vector machine algorithm could classify multivoxel activation patterns in brain regions involved in dynamic facial expression processing in the mentalizing networks (anterior and posterior cingulate cortex). These results indicate that live social interaction modulates the activity and connectivity of the right mirror neuron system and enhances spontaneous mimicry, further facilitating emotional contagion.

Functional connectivity during orthographic, phonological, and semantic processing of Chinese characters identifies distinct visuospatial and phonosemantic networks

While neuroimaging studies have identified brain regions associated with single word reading, its three constituents, namely, orthography, phonology, and meaning, and the functional connectivity of their networks remain underexplored. This study examined the neurocognitive underpinnings of these neural activations and functional connectivity of the identified brain regions using a within-subject design. Thirty-one native Mandarin speakers performed orthographic, phonological, and semantic judgment tasks during functional magnetic resonance imaging. The results indicated that the three processes shared a core network consisting of a large region in the left prefrontal cortex, fusiform gyrus, and medial superior frontal gyrus but not the superior temporal gyrus. Orthographic processing more strongly recruited the left dorsolateral prefrontal cortex, left superior parietal lobule and bilateral fusiform gyri; semantic processing more strongly recruited the left inferior frontal gyrus and left middle temporal gyrus, whereas phonological processing more strongly activated the dorsal part of the precentral gyrus. Functional connectivity analysis identified a posterior visuospatial network and a frontal phonosemantic network interfaced by the left middle frontal gyrus. We conclude that reading Chinese recruits cognitive resources that correspond to basic task demands with unique features best explained in connection with the individual reading subprocesses.

Asymmetric representation of aversive prediction errors in Pavlovian threat conditioning

Survival in biological environments requires learning associations between predictive sensory cues and threatening outcomes. Such aversive learning may be implemented through reinforcement learning algorithms that are driven by the signed difference between expected and encountered outcomes, termed prediction errors (PEs). While PE-based learning is well established for reward learning, the role of putative PE signals in aversive learning is less clear. Here, we used functional magnetic resonance imaging in humans (21 healthy men and women) to investigate the neural representation of PEs during maintenance of learned aversive associations. Four visual cues, each with a different probability (0, 33, 66, 100%) of being followed by an aversive outcome (electric shock), were repeatedly presented to participants. We found that neural activity at omission (US-) but not occurrence of the aversive outcome (US+) encoded PEs in the medial prefrontal cortex. More expected omission of aversive outcome was associated with lower neural activity. No neural signals fulfilled axiomatic criteria, which specify necessary and sufficient components of PE signals, for signed PE representation in a whole-brain search or in a-priori regions of interest. Our results might suggest that, different from reward learning, aversive learning does not involve signed PE signals that are represented within the same brain region for all conditions.

Neural alterations of emotion processing in atypical trajectories of psychotic-like experiences

The aim of this study was to investigate the neural bases of facial emotion processing before the onset of clinical psychotic symptoms in youth belonging to well-defined developmental trajectories of psychotic-like experiences (PLEs). A unique sample of 86 youths was recruited from a population-based sample of over 3800 adolescents who had been followed from 13 to 17 years of age. Three groups were identified based on validated developmental trajectories: a control trajectory with low and decreasing PLEs, and two atypical trajectories with moderate to elevated baseline PLEs that subsequently decreased or increased. All had functional magnetic resonance imaging data collected during a facial emotion processing task. Functional activation and connectivity data were analyzed for different contrasts. The increasing PLE trajectory displayed more positive psychotic symptoms while the decreasing trajectory exhibited more negative symptoms relative to the control group. During face processing, both atypical trajectories displayed decreased activations of the right inferior frontal gyrus (IFG), while the increasing trajectory displayed a negative signal in the precentral gyrus. The increasing PLE trajectory also displayed impaired connectivity between the amygdala, ventromedial prefrontal cortex, and cerebellum, and between the IFG, precuneus, and temporal regions, while the decreasing trajectory exhibited reduced connectivity between the amygdala and visual regions during emotion processing. Both atypical PLE trajectories displayed alterations in brain regions involved in attention salience. While the increasing trajectory with more positive symptoms exhibited dysconnectivity in areas that influence emotion salience and face perception, the decreasing trajectory with more negative symptoms had impairments in visual information integration areas. These group-specific features might account for the differential symptom expression.

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

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

Task-specific network interactions across key cognitive domains

Human cognition is organized in distributed networks in the brain. Although distinct specialized networks have been identified for different cognitive functions, previous work also emphasizes the overlap of key cognitive domains in higher level association areas. The majority of previous studies focused on network overlap and dissociation during resting states whereas task-related network interactions across cognitive domains remain largely unexplored. A better understanding of network overlap and dissociation during different cognitive tasks may elucidate flexible (re-)distribution of resources during human cognition. The present study addresses this issue by providing a broad characterization of large-scale network dynamics in three key cognitive domains. Combining prototypical tasks of the larger domains of attention, language, and social cognition with whole-brain multivariate activity and connectivity approaches, we provide a spatiotemporal characterization of multiple large-scale, overlapping networks that differentially interact across cognitive domains. We show that network activity and interactions increase with increased cognitive complexity across domains. Interaction patterns reveal a common core structure across domains as well as dissociable domain-specific network activity. The observed patterns of activation and deactivation of overlapping and strongly coupled networks provide insight beyond region-specific activity within a particular cognitive domain toward a network perspective approach across diverse key cognitive functions.

Neurochemical and functional interactions for improved perceptual decisions through training

Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.

Mapping cortico-subcortical sensitivity to 4 Hz amplitude modulation depth in human auditory system with functional MRI

Temporal modulations in the envelope of acoustic waveforms at rates around 4 Hz constitute a strong acoustic cue in speech and other natural sounds. It is often assumed that the ascending auditory pathway is increasingly sensitive to slow amplitude modulation (AM), but sensitivity to AM is typically considered separately for individual stages of the auditory system. Here, we used blood oxygen level dependent (BOLD) fMRI in twenty human subjects (10 male) to measure sensitivity of regional neural activity in the auditory system to 4 Hz temporal modulations. Participants were exposed to AM noise stimuli varying parametrically in modulation depth to characterize modulation-depth effects on BOLD responses. A Bayesian hierarchical modeling approach was used to model potentially nonlinear relations between AM depth and group-level BOLD responses in auditory regions of interest (ROIs). Sound stimulation activated the auditory brainstem and cortex structures in single subjects. BOLD responses to noise exposure in core and belt auditory cortices scaled positively with modulation depth. This finding was corroborated by whole-brain cluster-level inference. Sensitivity to AM depth variations was particularly pronounced in the Heschl's gyrus but also found in higher-order auditory cortical regions. None of the sound-responsive subcortical auditory structures showed a BOLD response profile that reflected the parametric variation in AM depth. The results are compatible with the notion that early auditory cortical regions play a key role in processing low-rate modulation content of sounds in the human auditory system.

Temporal SNR optimization through RF coil combination in fMRI: The more, the better?

For functional MRI with a multi-channel receiver RF coil, images are often reconstructed channel by channel, resulting into multiple images per time frame. The final image to analyze usually is the result of the covariance Sum-of-Squares (covSoS) combination across these channels. Although this reconstruction is quasi-optimal in SNR, it is not necessarily the case in terms of temporal SNR (tSNR) of the time series, which is yet a more relevant metric for fMRI data quality. In this work, we investigated tSNR optimality through voxel-wise RF coil combination and its effects on BOLD sensitivity. An analytical solution for an optimal RF coil combination is described, which is somewhat tied to the extended Krueger-Glover model involving both thermal and physiological noise covariance matrices. Compared experimentally to covSOS on four volunteers at 7T, the method yielded great improvement of tSNR but, surprisingly, did not result into higher BOLD sensitivity. Solutions to improve the method such as for example the t-score for the mean recently proposed are also explored, but result into similar observations once the statistics are corrected properly. Overall, the work shows that data-driven RF coil combinations based on tSNR considerations alone should be avoided unless additional and unbiased assumptions can be made.

Functional Interactions between Sensory and Memory Networks for Adaptive Behavior

The brain's capacity to adapt to sensory inputs is key for processing sensory information efficiently and interacting in new environments. Following repeated exposure to the same sensory input, brain activity in sensory areas is known to decrease as inputs become familiar, a process known as adaptation. Yet, the brain-wide mechanisms that mediate adaptive processing remain largely unknown. Here, we combine multimodal brain imaging (functional magnetic resonance imaging [fMRI], magnetic resonance spectroscopy) with behavioral measures of orientation-specific adaptation (i.e., tilt aftereffect) to investigate the functional and neurochemical mechanisms that support adaptive processing. Our results reveal two functional brain networks: 1) a sensory-adaptation network including occipital and dorsolateral prefrontal cortex regions that show decreased fMRI responses for repeated stimuli and 2) a perceptual-memory network including regions in the parietal memory network (PMN) and dorsomedial prefrontal cortex that relate to perceptual bias (i.e., tilt aftereffect). We demonstrate that adaptation relates to increased occipito-parietal connectivity, while decreased connectivity between sensory-adaptation and perceptual-memory networks relates to GABAergic inhibition in the PMN. Thus, our findings provide evidence that suppressive interactions between sensory-adaptation (i.e., occipito-parietal) and perceptual-memory (i.e., PMN) networks support adaptive processing and behavior, proposing a key role of memory systems in efficient sensory processing.

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.

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.

Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI

Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.

Dynamic functional brain networks underlying the temporal inertia of negative emotions

Affective inertia represents the lasting impact of transient emotions at one time point on affective state at a subsequent time point. Here we describe the neural underpinnings of inertia following negative emotions elicited by sad events in movies. Using a co-activation pattern analysis of dynamic functional connectivity, we examined the temporal expression and reciprocal interactions among brain-wide networks during movies and subsequent resting periods in twenty healthy subjects. Our findings revealed distinctive spatiotemporal expression of visual (VIS), default mode (DMN), central executive (CEN), and frontoparietal control (FPCN) networks both in negative movies and in rest periods following these movies. We also identified different reciprocal relationships among these networks, in transitions from movie to rest. While FPCN and DMN expression increased during and after negative movies, respectively, FPCN occurrences during the movie predicted lower DMN and higher CEN expression during subsequent rest after neutral movies, but this relationship was reversed after the elicitation of negative emotions. Changes in FPCN and DMN activity correlated with more negative subjective affect. These findings provide new insights into the transient interactions of intrinsic brain networks underpinning the inertia of negative emotions. More specifically, they describe a major role of FPCN in emotion elicitation processes, with prolonged impact on DMN activity in subsequent rest, presumably involved in emotion regulation and restoration of homeostatic balance after negative events.

The integrative role of the M1 in motor sequence learning

The primary motor cortex (M1) is crucial in motor learning. Whether the M1 encodes the motor engram for sequential finger tapping formed by an emphasis on speed is still inconclusive. The active states of engrams are hard to discriminate from the motor execution per se. As preparatory activity reflects the upcoming movement parameters, we hypothesized that the retrieval of motor engrams generated by different learning modes is reflected as a learning-related increase in the preparatory activity of the M1. To test this hypothesis, we evaluated the preparatory activity during the learning of sequential finger-tapping with the non-dominant left hand using a 7T functional MRI. Participants alternated between performing a tapping sequence as quickly as possible (maximum mode) or at a constant speed of 2 Hz paced by a sequence-specifying visual cue (constant mode). We found a training-related increase in preparatory activity in the network covering the bilateral anterior intraparietal sulcus and inferior parietal lobule extending to the right M1 during the maximum mode and the right M1 during the constant mode. These findings indicate that the M1, as the last effector of the motor output, integrates the motor engram distributed through the networks despite training mode differences.

Transcranial direct current stimulation with functional magnetic resonance imaging: a detailed validation and operational guide

Introduction: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique used to modulate human brain and behavioural function in both research and clinical interventions. The combination of functional magnetic resonance imaging (fMRI) with tDCS enables researchers to directly test causal contributions of stimulated brain regions, answering questions about the physiology and neural mechanisms underlying behaviour. Despite the promise of the technique, advances have been hampered by technical challenges and methodological variability between studies, confounding comparability/replicability. Methods: Here tDCS-fMRI at 3T was developed for a series of experiments investigating language recovery after stroke. To validate the method, one healthy volunteer completed an fMRI paradigm with three conditions: (i) No-tDCS, (ii) Sham-tDCS, (iii) 2mA Anodal-tDCS. MR data were analysed in SPM12 with region-of-interest (ROI) analyses of the two electrodes and reference sites. Results: Quality assessment indicated no visible signal dropouts or distortions introduced by the tDCS equipment. After modelling scanner drift, motion-related variance, and temporal autocorrelation, we found no field inhomogeneity in functional sensitivity metrics across conditions in grey matter and in the three ROIs. Discussion: Key safety factors and risk mitigation strategies that must be taken into consideration when integrating tDCS into an fMRI environment are outlined. To obtain reliable results, we provide practical solutions to technical challenges and complications of the method. It is hoped that sharing these data and SOP will promote methodological replication in future studies, enhancing the quality of tDCS-fMRI application, and improve the reliability of scientific results in this field. Conclusions: The method and data provided here provide a technically safe, reliable tDCS-fMRI procedure to obtain high quality MR data. The detailed framework of the Standard Operation Procedure SOP (https://doi.org/10.5281/zenodo.4606564) systematically reports the technical and procedural elements of our tDCS-fMRI approach, which we hope can be adopted and prove useful in future studies.

The processing of angry faces in schizophrenia patients with a history of suicide: An fMRI study examining brain activity and connectivity

BACKGROUND

The high rate of suicidal behaviours (SBs) in psychiatric populations remain an important preoccupation to address. The literature reveals emotional instability as an important risk factor for SBs. However, the neural mechanisms underpinning this risk factor have never been investigated in schizophrenia patients with SBs. The following study implemented a task-based emotional processing functional magnetic resonance imaging (fMRI) paradigm to evaluate the activation and connectivity differences exhibited by schizophrenia patients with a history of suicide attempt (SA).

METHOD

A sample of 62 schizophrenia patients with and without SA and 22 controls completed an fMRI emotional processing task, which included the visualization of dynamic angry facial expressions. Task-based connectivity was assessed using generalized psychophysical interaction analyses.

RESULTS

During the processing of angry faces, suicidal schizophrenia patients displayed increased activation of the left median cingulate gyrus, left middle frontal gyrus, and left precuneus when compared to nonsuicidal schizophrenia patients and healthy controls. Whole-brain connectivity analyses yielded an increased coupling of the right amygdala and right superior frontal gyrus, as well as between the left precuneus and median cingulate gyrus, in suicidal schizophrenia patients. Schizophrenia patients' hostility scores on the Positive and Negative Symptom Scale (PANSS) were significantly and positively correlated with the activity of the left median cingulate gyrus.

CONCLUSION

When exposed to angry faces, suicidal schizophrenia patients demonstrate elevated activation of brain regions associated to executive functioning and self-processing, as well as aberrant fronto-limbic connectivity involved in emotion regulation. Our results highlight the neglected role of anger when investigating the neural alterations underpinning SBs in schizophrenia.

Brain networks underlying the processing of sound symbolism related to softness perception

Unlike the assumption of modern linguistics, there is non-arbitrary association between sound and meaning in sound symbolic words. Neuroimaging studies have suggested the unique contribution of the superior temporal sulcus to the processing of sound symbolism. However, because these findings are limited to the mapping between sound symbolism and visually presented objects, the processing of sound symbolic information may also involve the sensory-modality dependent mechanisms. Here, we conducted a functional magnetic resonance imaging experiment to test whether the brain regions engaged in the tactile processing of object properties are also involved in mapping sound symbolic information with tactually perceived object properties. Thirty-two healthy subjects conducted a matching task in which they judged the congruency between softness perceived by touch and softness associated with sound symbolic words. Congruency effect was observed in the orbitofrontal cortex, inferior frontal gyrus, insula, medial superior frontal gyrus, cingulate gyrus, and cerebellum. This effect in the insula and medial superior frontal gyri was overlapped with softness-related activity that was separately measured in the same subjects in the tactile experiment. These results indicate that the insula and medial superior frontal gyrus play a role in processing sound symbolic information and relating it to the tactile softness information.

An empirical investigation of the benefit of increasing the temporal resolution of task-evoked fMRI data with multi-band imaging

Objective

There is a tendency for reducing TR in MRI experiments with multi-band imaging. We empirically investigate its benefit for the group-level statistical outcome in task-evoked fMRI.

Methods

Three visual fMRI data sets were collected from 17 healthy adult participants. Multi-band acquisition helped vary the TR (2000/1000/410 ms, respectively). Because these data sets capture different temporal aspects of the haemodynamic response (HRF), we tested several HRF models. We computed a composite descriptive statistic, H, from β’s of each first-level model fit and carried it to the group-level analysis. The number of activated voxels and the t value of the group-level analysis as well as a goodness-of-fit measure were used as surrogate markers of data quality for comparison.

Results

Increasing the temporal sampling rate did not provide a universal improvement in the group-level statistical outcome. Rather, both the voxel-wise and ROI-averaged group-level results varied widely with anatomical location, choice of HRF and the setting of the TR. Correspondingly, the goodness-of-fit of HRFs became worse with increasing the sampling frequency.

Conclusion

Rather than universally increasing the temporal sampling rate in cognitive fMRI experiments, these results advocate the performance of a pilot study for the specific ROIs of interest to identify the appropriate temporal sampling rate for the acquisition and the correspondingly suitable HRF for the analysis of the data.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10334-021-00918-z.

Functional specialization within the inferior parietal lobes across cognitive domains

The inferior parietal lobe (IPL) is a key neural substrate underlying diverse mental processes, from basic attention to language and social cognition, that define human interactions. Its putative domain-global role appears to tie into poorly understood differences between cognitive domains in both hemispheres. Across attentional, semantic, and social cognitive tasks, our study explored functional specialization within the IPL. The task specificity of IPL subregion activity was substantiated by distinct predictive signatures identified by multivariate pattern-learning algorithms. Moreover, the left and right IPL exerted domain-specific modulation of effective connectivity among their subregions. Task-evoked functional interactions of the anterior and posterior IPL subregions involved recruitment of distributed cortical partners. While anterior IPL subregions were engaged in strongly lateralized coupling links, both posterior subregions showed more symmetric coupling patterns across hemispheres. Our collective results shed light on how under-appreciated hemispheric specialization in the IPL supports some of the most distinctive human mental capacities.

Improving the sensitivity of spin-echo fMRI at 3T by highly accelerated acquisitions

PURPOSE

Spin-echo (SE) functional MRI (fMRI) can be highly advantageous compared to gradient-echo (GE) fMRI with respect to magnetic field-inhomogeneity artifacts. However, at 3T, the majority of blood oxygenation level-dependent (BOLD) fMRI experiments are performed using T 2 ∗ -weighted GE sequences because of their superior sensitivity compared to SE-fMRI. The presented SE implementation of a highly accelerated GE pulse sequence therefore aims to improve the sensitivity of SE-fMRI while profiting from a reduction of susceptibility-induced signal dropout.

METHODS

Spin-echo MR encephalography (SE-MREG) is compared with the more conventionally used spin-echo echo-planar imaging (SE-EPI) and spin-echo simultaneous multislice (SE-SMS) at 3T in terms of capability to detect neuronal activations and resting-state functional connectivity. For activation analysis, healthy subjects underwent consecutive SE-MREG (pulse repetition time [TR] = 0.25 seconds), SE-SMS (TR = 1.3 seconds), and SE-EPI (TR = 4.4 seconds) scans in pseudorandomized order applied to a visual block design paradigm for generation of t-statistics maps. For the investigation of functional connectivity, additional resting-state data were acquired for 5 minutes and a seed-based correlation analysis using Stanford's FIND (Functional Imaging in Neuropsychiatric Disorders) atlas was performed.

RESULTS

The increased sampling rate of SE-MREG relative to SE-SMS and SE-EPI improves the sensitivity to detect BOLD activation by 33% and 54%, respectively, and increases the capability to extract resting-state networks. Compared with a brain region that is not affected by magnetic field inhomogeneities, SE-MREG shows 2.5 times higher relative signal strength than GE-MREG in mesial temporal structures.

CONCLUSION

SE-MREG offers a viable possibility for whole-brain fMRI with consideration of brain regions that are affected by strong susceptibility-induced magnetic field gradients.

Dynamic time warping outperforms Pearson correlation in detecting atypical functional connectivity in autism spectrum disorders

Resting state fMRI (rsfMRI) is frequently used to study brain function, including in clinical populations. Similarity of blood-oxygen-level-dependent (BOLD) fluctuations during rsfMRI between brain regions is thought to reflect intrinsic functional connectivity (FC), potentially due to history of coactivation. To quantify similarity, studies have almost exclusively relied on Pearson correlation, which assumes linearity and can therefore underestimate FC if the hemodynamic response function differs regionally or there is BOLD signal lag between timeseries. Here we show in three cohorts of children, adolescents and adults, with and without autism spectrum disorders (ASDs), that measuring the similarity of BOLD signal fluctuations using non-linear dynamic time warping (DTW) is more robust to global signal regression (GSR), has higher test-retest reliability and is more sensitive to task-related changes in FC. Additionally, when comparing FC between individuals with ASDs and typical controls, more group differences are detected using DTW. DTW estimates are also more related to ASD symptom severity and executive function, while Pearson correlation estimates of FC are more strongly associated with respiration during rsfMRI. Together these findings suggest that non-linear methods such as DTW improve estimation of resting state FC, particularly when studying clinical populations whose hemodynamics or neurovascular coupling may be altered compared to typical controls.

Brain Activity Associated With Regulating Food Cravings Predicts Changes in Self-Reported Food Craving and Consumption Over Time

Neural patterns associated with viewing energy-dense foods can predict changes in eating-related outcomes. However, most research on this topic is limited to one follow-up time point, and single outcome measures. The present study seeks to add to that literature by employing a more refined assessment of food craving and consumption outcomes along with a more detailed neurobiological model of behavior change over several time points. Here, a community sample of 88 individuals (age: M = 39.17, SD = 3.47; baseline BMI: M = 31.5, SD = 3.9, range 24–42) with higher body mass index (BMI) performed a food craving reactivity and regulation task while undergoing functional magnetic resonance imaging. At that time—and 1, 3, and 6 months later—participants reported craving for and consumption of healthy and unhealthy foods via the Food Craving Inventory (FCI) and ASA24 (N at 6 months = 52–55 depending on the measure). A priori hypotheses that brain activity associated with both viewing and regulating personally desired unhealthy, energy-dense foods would be associated with self-reported craving for and consumption of unhealthy foods at baseline were not supported by the data. Instead, regression models controlling for age, sex, and BMI demonstrated that brain activity across several regions measured while individuals were regulating their desires for unhealthy food was associated with the self-reported craving for and consumption of healthy food. The hypothesis that vmPFC activity would predict patterns of healthier eating was also not supported. Instead, linear mixed models controlling for baseline age and sex, as well as changes in BMI, revealed that more regulation-related activity in the dlPFC, dACC, IFG, and vmPFC at baseline predicted decreases in the craving for and consumption of healthy foods over the course of 6 months.

Fine-scale computations for adaptive processing in the human brain

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

Multivariate neural signatures for health neuroscience: assessing spontaneous regulation during food choice

Establishing links between neural systems and health can be challenging since there is not a one-to-one mapping between brain regions and psychological states. Building sensitive and specific predictive models of health-relevant constructs using multivariate activation patterns of brain activation is a promising new direction. We illustrate the potential of this approach by building two 'neural signatures' of food craving regulation (CR) using multivariate machine learning and, for comparison, a univariate contrast. We applied the signatures to two large validation samples of overweight adults who completed tasks measuring CR ability and valuation during food choice. Across these samples, the machine learning signature was more reliable. This signature decoded CR from food viewing and higher signature expression was associated with less craving. During food choice, expression of the regulation signature was stronger for unhealthy foods and inversely related to subjective value, indicating that participants engaged in CR despite never being instructed to control their cravings. Neural signatures thus have the potential to measure spontaneous engagement of mental processes in the absence of explicit instruction, affording greater ecological validity. We close by discussing the opportunities and challenges of this approach, emphasizing what machine learning tools bring to the field of health neuroscience.

The neural network underpinning social feedback contingent upon one's action: An fMRI study

Praise enhances motor performance; however, the underlying feedback pathway is unknown. Here, we hypothesized that the social evaluation feedback to the motor system is modified by the top-down effect of the social contingency valuation system, such as the anterior rostral medial prefrontal cortex (arMPFC). We developed a pseudo-interactive task that simplified a conversational student-teacher interaction and conducted a functional magnetic resonance imaging study with 33 participants (13 men, 20 women; mean age = 21.7 years; standard deviation = 2.0 years). The participant inside the scanner uttered the pseudo-English word to the English teacher outside the scanner. The teacher provided feedback of acceptance or rejection by either gestures or words, through video. As a control condition, the pseudo-word was read aloud by a computer. Approval from the teacher enhanced the participants' pleasure rate. Feedback to the participants' utterance, either rejection or acceptance, activated the arMPFC. Irrespective of the preceding utterance by self or computer, acceptance compared with rejection activated the right primary visual cortex (V1), and the reverse activated the left V1. This valence-dependent laterality of V1 activation indicates that the effect is not the domain-general modulation of visual processing. Instead, the early visual cortices are part of the valence-specific representation of the social signal. Physio-physiological interaction analysis with the seed regions in the right and left V1 and the modulator region in the arMPFC showed enhanced connectivity with the bilateral primary motor cortex. These findings indicate that the socially contingent, self-relevant signals from others act as feedback to the motor control system, and this process is mediated by the early visual cortex.

15 Years MR-encephalography

Objective

This review article gives an account of the development of the MR-encephalography (MREG) method, which started as a mere ‘Gedankenexperiment’ in 2005 and gradually developed into a method for ultrafast measurement of physiological activities in the brain. After going through different approaches covering k-space with radial, rosette, and concentric shell trajectories we have settled on a stack-of-spiral trajectory, which allows full brain coverage with (nominal) 3 mm isotropic resolution in 100 ms. The very high acceleration factor is facilitated by the near-isotropic k-space coverage, which allows high acceleration in all three spatial dimensions.

Methods

The methodological section covers the basic sequence design as well as recent advances in image reconstruction including the targeted reconstruction, which allows real-time feedback applications, and—most recently—the time-domain principal component reconstruction (tPCR), which applies a principal component analysis of the acquired time domain data as a sparsifying transformation to improve reconstruction speed as well as quality.

Applications

Although the BOLD-response is rather slow, the high speed acquisition of MREG allows separation of BOLD-effects from cardiac and breathing related pulsatility. The increased sensitivity enables direct detection of the dynamic variability of resting state networks as well as localization of single interictal events in epilepsy patients. A separate and highly intriguing application is aimed at the investigation of the glymphatic system by assessment of the spatiotemporal patterns of cardiac and breathing related pulsatility.

Discussion

MREG has been developed to push the speed limits of fMRI. Compared to multiband-EPI this allows considerably faster acquisition at the cost of reduced image quality and spatial resolution.

Sharpened self-other distinction in attention deficit hyperactivity disorder

INTRODUCTION

Differentiation between self-produced tactile stimuli and touch by others is necessary for social interactions and for a coherent concept of "self". In attention-deficit-hyperactivity-disorder (ADHD), tactile hypersensitivity and social cognition problems are part of the symptomatology, but pathophysiological mechanisms are largely unknown. Differentiation of self- and non-self- generated sensations might be key to understand and develop novel strategies for managing hypersensitivity. Here, we compared the neural signatures of affective self- and other-touch between adults with ADHD and neurotypical controls (NC).

METHODS

Twenty-eight adult ADHD participants and 30 age- and gender-matched NC performed a self-other-touch-task during functional magnetic resonance imaging: they stroked their own arm, an object, or were stroked by the experimenter. In addition, tactile detection thresholds and rubber hand illusion (RHI) were measured.

RESULTS

ADHD participants had more autistic traits than NC and reported to engage less in interpersonal touch. They also reported to be more sensitive to tactile stimuli. Compared to NC, ADHD participants showed enhanced responses to both the self- and other-touch conditions: stronger deactivation during self-touch in the anterior and posterior insula, and increased activation during other-touch in primary somatosensory cortex. ADHD participants had intact tactile detection thresholds, but were less susceptible to the RHI.

CONCLUSIONS

Unaltered detection thresholds suggest that peripheral processing is intact, and that hypersensitivity might be driven by central mechanisms. This has clinical implications for managing somatosensory hypersensitivity in ADHD. The more pronounced differentiation between self- and other-touch might indicate a clearer self-other-distinction. This is of interest regarding body ownership perception in both NC and ADHD, and possibly other psychiatric conditions with altered self-experiences, like schizophrenia. A sharper boundary of the own body might relate to deficits in social cognition and tactile hypersensitivity.

Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T

Multiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3 ​T scanner using five sequences, up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movie blocks showing complex actions with hand object interactions and (ii) control movie blocks without hand object interaction. Data were processed using a widely used analysis pipeline implemented in SPM12 including the unified segmentation and canonical HRF modelling. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7 ​mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit.