Detecting the subtle shape differences in hemodynamic responses at the group level

BOLD Response is more than just magnitude: Improving detection sensitivity through capturing hemodynamic profiles

Typical fMRI analyses often assume a canonical hemodynamic response function (HRF) that primarily focuses on the peak height of the overshoot, neglecting other morphological aspects. Consequently, reported analyses often reduce the overall response curve to a single scalar value. In this study, we take a data-driven approach to HRF estimation at the whole-brain voxel level, without assuming a response profile at the individual level. We then employ a roughness penalty at the population level to estimate the response curve, aiming to enhance predictive accuracy, inferential efficiency, and cross-study reproducibility. By examining a fast event-related FMRI dataset, we demonstrate the shortcomings and information loss associated with adopting the canonical approach. Furthermore, we address the following key questions: 1) To what extent does the HRF shape vary across different regions, conditions, and participant groups? 2) Does the data-driven approach improve detection sensitivity compared to the canonical approach? 3) Can analyzing the HRF shape help validate the presence of an effect in conjunction with statistical evidence? 4) Does analyzing the HRF shape offer evidence for whole-brain response during a simple task?

Thalamocortical Coherence Predicts Persistent Postconcussive Symptoms

The pathogenetic mechanism of persistent post-concussive symptoms (PCS) following concussion remains unclear. Thalamic damage is known to play a role in PCS prolongation while the evidence and biomarkers that trigger persistent PCS have never been elucidated. We collected longitudinal neuroimaging and behavior data from patients and rodents after concussion, complemented with rodents' histological staining data, to unravel the early biomarkers of persistent PCS. Diffusion tensor imaging (DTI) were acquired to investigated the thalamic damage, while quantitative thalamocortical coherence was derived through resting-state functional MRI for evaluating thalamocortical functioning and predicting long-term behavioral outcome. Patients with prolonged symptoms showed abnormal DTI-derived indices at the boundaries of bilateral thalami (peri-thalamic regions). Both patients and rats with persistent symptoms demonstrated enhanced thalamocortical coherence between different thalamocortical circuits, which disrupted thalamocortical multifunctionality. In rodents, the persistent DTI abnormalities were validated in thalamic reticular nucleus (TRN) through immunohistochemistry, and correlated with enhanced thalamocortical coherence. Strong predictive power of these coherence biomarkers for long-term PCS was also validated using another patient cohort. Postconcussive events may begin with persistent TRN injury, followed by disrupted thalamocortical coherence and prolonged PCS. Functional MRI-based coherence measures can be surrogate biomarkers for early prediction of long-term PCS.

The entorhinal-DG/CA3 pathway in the medial temporal lobe retains visual working memory of a simple surface feature

Classic models consider working memory (WM) and long-term memory as distinct mental faculties that are supported by different neural mechanisms. Yet, there are significant parallels in the computation that both types of memory require. For instance, the representation of precise item-specific memory requires the separation of overlapping neural representations of similar information. This computation has been referred to as pattern separation, which can be mediated by the entorhinal-DG/CA3 pathway of the medial temporal lobe (MTL) in service of long-term episodic memory. However, although recent evidence has suggested that the MTL is involved in WM, the extent to which the entorhinal-DG/CA3 pathway supports precise item-specific WM has remained elusive. Here, we combine an established orientation WM task with high-resolution fMRI to test the hypothesis that the entorhinal-DG/CA3 pathway retains visual WM of a simple surface feature. Participants were retrospectively cued to retain one of the two studied orientation gratings during a brief delay period and then tried to reproduce the cued orientation as precisely as possible. By modeling the delay-period activity to reconstruct the retained WM content, we found that the anterior-lateral entorhinal cortex (aLEC) and the hippocampal DG/CA3 subfield both contain item-specific WM information that is associated with subsequent recall fidelity. Together, these results highlight the contribution of MTL circuitry to item-specific WM representation.

Pubertal development underlies optimization of inhibitory control through specialization of ventrolateral prefrontal cortex

Inhibitory control improves into young adulthood after specialization of relevant brain systems during adolescence. However, the biological mechanisms supporting this unique transition are not well understood. Given that adolescence is defined by puberty, we examined relative contributions of chronological age and pubertal maturation to inhibitory control development. 105 8-19-year-olds completed 1-5 longitudinal visits (227 visits total) in which pubertal development was assessed via self-reported Tanner stage and inhibitory control was assessed with an in-scanner antisaccade task. As expected, percentage and latency of correct antisaccade responses improved with age and pubertal stage. When controlling for pubertal stage, chronological age was distinctly associated with correct response rate. In contrast, pubertal stage was uniquely associated with antisaccade latency even when controlling for age. Chronological age was associated with fMRI task activation in several regions including the right dorsolateral prefrontal cortex, while puberty was associated with right ventrolateral prefrontal cortex (VLPFC) activation. Furthermore, task-related connectivity between VLPFC and cingulate was associated with both pubertal stage and response latency. These results suggest that while age-related developmental processes may support maturation of brain systems underlying the ability to inhibit a response, puberty may play a larger role in the effectiveness of generating cognitive control responses.

Improved localization of language areas using single voxel signal analysis of unprocessed fMRI data

Activated brain regions can be visualized and localized with the use of fMRI (functional magnetic imaging). This is based on changes in the blood flow in activated regions, or more precisely on the hemodynamic response function (HRF) and the Blood-Oxygen-Level-Dependent (BOLD) effect. This study used a task-based fMRI examination with language paradigms in order to stimulate the language areas. The measured fMRI data are frequently altered by different preprocessing steps for the analysis and the display of activations. These changes can lead to discrepancies between the displayed and the truly measured location of the activations. Simple t-maps were created with unprocessed fMRI data, to provide a more realistic representation of the language areas. HRF-dependent single-voxel fMRI signal analysis was performed to improve the analyzability of these activation maps.

Auditory Target Detection Enhances Visual Processing and Hippocampal Functional Connectivity

Though dividing one's attention between two input streams typically impairs performance, detecting a behaviorally relevant stimulus can sometimes enhance the encoding of unrelated information presented at the same time. Previous research has shown that selection of this kind boosts visual cortical activity and memory for concurrent items. An important unanswered question is whether such effects are reflected in processing quality and functional connectivity in visual regions and in the hippocampus. In this fMRI study, participants were asked to memorize a stream of naturalistic images and press a button only when they heard a predefined target tone (400 or 1,200 Hz, counterbalanced). Images could be presented with a target tone, with a distractor tone, or without a tone. Auditory target detection increased activity throughout the ventral visual cortex but lowered it in the hippocampus. Enhancements in functional connectivity between the ventral visual cortex and the hippocampus were also observed following auditory targets. Multi-voxel pattern classification of image category was more accurate on target tone trials than on distractor and no tone trials in the fusiform gyrus and parahippocampal gyrus. This effect was stronger in visual cortical clusters whose activity was more correlated with the hippocampus on target tone than on distractor tone trials. In agreement with accounts suggesting that subcortical noradrenergic influences play a role in the attentional boost effect, auditory target detection also caused an increase in locus coeruleus activity and phasic pupil responses. These findings outline a network of cortical and subcortical regions that are involved in the selection and processing of information presented at behaviorally relevant moments.

Time for a paradigm shift: The adolescent brain in addiction treatment

OBJECTIVE

One route to improve adolescent addiction treatment outcomes is to use translational approaches to help identify developmental neuroscience mechanisms that undergird active treatment ingredients and advance adolescent behavior change.

METHODS

This sample included 163 adolescents (ages 15-19) randomized to motivational interviewing (MI) vs. brief adolescent mindfulness (BAM). Youth completed an fMRI paradigm assessing adolescent brain response to therapist language (complex reflection vs. mindful; complex reflection vs. confront; mindful vs. confront) at pre- (prior to the completion of the full intervention) and post-treatment (at 3-month follow-up) and behavioral measures at 3, 6 and 12 months.

RESULTS

Youth in both treatment groups showed significant problem drinking reductions at 3 and 6 months, but MI youth demonstrated significantly better treatment outcomes than BAM youth at 12 months. We observed several significant treatment group differences (MI > BAM) in neural response to therapist language, including at pre-treatment when examining complex reflection vs. mindful, and complex reflection vs. confront (e.g., superior temporal gyrus, lingual gyrus); and at post-treatment when examining mindful vs. confront (e.g., supplementary motor area; middle frontal gyrus). When collapsed across treatment groups (MI + BAM), we observed significant differences by time, with youth showing a pattern of brain change in response to complex reflection vs. mindful, and complex reflection vs. confront (e.g., precuneus; postcentral gyrus). There was no evidence of a significant group × time interaction. However, brain change in response to therapist language (complex reflection vs. confront) in regions such as middle frontal gyrus, was associated with reductions in problem drinking at 12 months. Yet, few treatment group differences were observed.

CONCLUSIONS

These data underscore the need to better understand therapist language and it's impact on the developing brain, in order to inform and aggregate the most impactful elements of addiction treatment for future treatment development for adolescents.

Neural basis of positive and negative emotion regulation in remitted depression

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RRMDD patients show deviant uninstructed neural emotion regulation.

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This is reflected in residual problems in daily strategy use.

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RRMDD patients are capable to engage frontolimbic areas upon instructed reappraisal.

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Neural regulation capacity is related to inadequate rumination.

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Positive, next to negative, affect is highly relevant for understanding vulnerability.

The recurrent nature of Major Depressive Disorder (MDD) necessitates a better understanding of mechanisms facilitating relapse. MDD has often been associated with abnormal emotion regulation, underpinned by aberrant interactions between the prefrontal cortex and subcortical areas. We assessed whether neural regulation abnormalities remain after remission and relate to emotion regulation problems in daily life.

At the baseline measurement of a randomized controlled trial, an emotion regulation task was performed during fMRI scanning by 46 remitted recurrent (rrMDD) patients and 24 healthy controls. We assessed both fMRI peak activity and the temporal dynamics of the neural response during passive attendance and explicit regulation of positive and negative emotions. Furthermore, we assessed regulation strategy use in daily life using questionnaires, and attentional biases using a modified attentional dot-probe task.

RrMDD patients showed lower activation and different temporal dynamics in occipital, parietal, and prefrontal brain regions during passive attendance of emotional material compared to healthy controls. During explicit downregulation of negative emotions, no group differences were found. However, during explicit upregulation of positive emotions, rrMDD patients showed a different neural response over time in the insula. Behaviourally, rrMDD patients were characterized by dysfunctional regulation strategies in daily life. Within rrMDD patients, rumination was associated with activation within a limbic- prefrontal network.

After remission, immediate emotional processing seems unaffected, but regulatory abnormalities remain, especially uninstructed and in daily life. Abnormal insula activation during positive upregulation suggests decreased monitoring of positive emotions. The relation between inadequate rumination and brain activity during emotion regulation suggests that regulation of both positive and negative affect is important in understanding neurocognitive underpinnings of resilience.

Distributed and Multifaceted Effects of Threat and Safety

In the present fMRI study, we examined how anxious apprehension is processed in the human brain. A central goal of the study was to test the prediction that a subset of brain regions would exhibit sustained response profiles during threat periods, including the anterior insula, a region implicated in anxiety disorders. A second important goal was to evaluate the responses in the amygdala and the bed nucleus of the stria terminals, regions that have been suggested to be involved in more transient and sustained threat, respectively. A total of 109 participants performed an experiment in which they encountered "threat" or "safe" trials lasting approximately 16 sec. During the former, they experienced zero to three highly unpleasant electrical stimulations, whereas in the latter, they experienced zero to three benign electrical stimulations (not perceived as unpleasant). The timing of the stimulation during trials was randomized, and as some trials contained no stimulation, stimulation delivery was uncertain. We contrasted responses during threat and safe trials that did not contain electrical stimulation, but only the potential that unpleasant (threat) or benign (safe) stimulation could occur. We employed Bayesian multilevel analysis to contrast responses to threat and safe trials in 85 brain regions implicated in threat processing. Our results revealed that the effect of anxious apprehension is distributed across the brain and that the temporal evolution of the responses is quite varied, including more transient and more sustained profiles, as well as signal increases and decreases with threat.

rsHRF: A toolbox for resting-state HRF estimation and deconvolution

The hemodynamic response function (HRF) greatly influences the intra- and inter-subject variability of brain activation and connectivity, and might confound the estimation of temporal precedence in connectivity analyses, making its estimation necessary for a correct interpretation of neuroimaging studies. Additionally, the HRF shape itself is a useful local measure. However, most algorithms for HRF estimation are specific for task-related fMRI data, and only a few can be directly applied to resting-state protocols. Here we introduce rsHRF, a Matlab and Python toolbox that implements HRF estimation and deconvolution from the resting-state BOLD signal. We first provide an overview of the main algorithm, practical implementations, and then demonstrate the feasibility and usefulness of rsHRF by validation experiments with a publicly available resting-state fMRI dataset. We also provide tools for statistical analyses and visualization. We believe that this toolbox may significantly contribute to a better analysis and understanding of the components and variability of BOLD signals.

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.

Dopamine-related striatal neurophysiology is associated with specialization of frontostriatal reward circuitry through adolescence

Characterizing developmental changes in frontostriatal circuitry is critical to understanding adolescent development and can clarify neurobiological mechanisms underlying increased reward sensitivity and risk-taking and the emergence of psychopathology during this period. However, the role of striatal neurobiology in the development of frontostriatal circuitry through human adolescence remains largely unknown. We examined background connectivity during a reward-guided decision-making task ("reward-state"), in addition to resting-state, and assessed the association between age-related changes in frontostriatal connectivity and age-related changes in reward learning and risk-taking through adolescence. Further, we examined the contribution of dopaminergic processes to changes in frontostriatal circuitry and decision-making using MR-based assessments of striatal tissue-iron as a correlate of dopamine-related neurobiology. Connectivity between the nucleus accumbens (NAcc) and ventral anterior cingulate, subgenual cingulate, and orbitofrontal cortices decreased through adolescence into adulthood, and decreases in reward-state connectivity were associated with improvements reward-guided decision-making as well as with decreases in risk-taking. Finally, NAcc tissue-iron mediated age-related changes and was associated with variability in connectivity, and developmental increases in NAcc R2' corresponded with developmental decreases in connectivity. Our results provide evidence that dopamine-related striatal properties contribute to the specialization of frontostriatal circuitry, potentially underlying changes in risk-taking and reward sensitivity into adulthood.

Beyond linearity in neuroimaging: Capturing nonlinear relationships with application to longitudinal studies

The ubiquitous adoption of linearity for quantitative predictors in statistical modeling is likely attributable to its advantages of straightforward interpretation and computational feasibility. The linearity assumption may be a reasonable approximation especially when the variable is confined within a narrow range, but it can be problematic when the variable's effect is non-monotonic or complex. Furthermore, visualization and model assessment of a linear fit are usually omitted because of challenges at the whole brain level in neuroimaging. By adopting a principle of learning from the data in the presence of uncertainty to resolve the problematic aspects of conventional polynomial fitting, we introduce a flexible and adaptive approach of multilevel smoothing splines (MSS) to capture any nonlinearity of a quantitative predictor for population-level neuroimaging data analysis. With no prior knowledge regarding the underlying relationship other than a parsimonious assumption about the extent of smoothness (e.g., no sharp corners), we express the unknown relationship with a sufficient number of smoothing splines and use the data to adaptively determine the specifics of the nonlinearity. In addition to introducing the theoretical framework of MSS as an efficient approach with a counterbalance between flexibility and stability, we strive to (a) lay out the specific schemes for population-level nonlinear analyses that may involve task (e.g., contrasting conditions) and subject-grouping (e.g., patients vs controls) factors; (b) provide modeling accommodations to adaptively reveal, estimate and compare any nonlinear effects of a predictor across the brain, or to more accurately account for the effects (including nonlinear effects) of a quantitative confound; (c) offer the associated program 3dMSS to the neuroimaging community for whole-brain voxel-wise analysis as part of the AFNI suite; and (d) demonstrate the modeling approach and visualization processes with a longitudinal dataset of structural MRI scans.

Executive function network's white matter alterations relate to Parkinson's disease motor phenotype

Parkinson's disease (PD) patients with postural instability and gait disorder phenotype (PIGD) are at high risk of cognitive deficits compared to those with tremor dominant phenotype (TD). Alterations of white matter (WM) integrity can occur in patients with normal cognitive functions (PD-N). However, the alterations of WM integrity related to cognitive functions in PD-N, especially in these two motor phenotypes, remain unclear. Diffusion tensor imaging (DTI) is a non-invasive neuroimaging method to evaluate WM properties and by applying DTI tractography, one can identify WM tracts connecting functional regions. Here, we 1) compared the executive function (EF) in PIGD phenotype with normal cognitive functions (PIGD-N) and TD phenotype with normal cognitive functions (TD-N) phenotypes; 2) used DTI tractography to evaluated differences in WM alterations between these two phenotypes within a task-based functional network; and 3) examined the WM integrity alterations related to EF in a whole brain network for PD-N patients regardless of phenotypes. Thirty-four idiopathic PD-N patients were classified into two groups based on phenotypes: TD-N and PIGD-N, using an algorithm based on UPDRS part III. Neuropsychological tests were used to evaluate patients' EF, including the Trail making test part A and B, the Stroop color naming, the Stroop word naming, the Stroop color-word interference task, as well as the FAS verbal fluency task and the animal category fluency tasks. DTI measures were calculated among WM regions associated with the verbal fluency network defined from previous task fMRI studies and compared between PIGD-N and TD-N groups. In addition, the relationship of DTI measures and verbal fluency scores were evaluated for our full cohort of PD-N patients within the whole brain network. These values were also correlated with the scores of the FAS verbal fluency task. Only the FAS verbal fluency test showed significant group differences, having lower scores in PIGD-N when compared to TD-N phenotype (p < 0.05). Compared to the TD-N, PIGD-N group exhibited significantly higher MD and RD in the tracts connecting the left superior temporal gyrus and left insula, and those connecting the right pars opercularis and right insula. Moreover, compared to TD-N, PIGD-N group had significantly higher RD in the tracts connecting right pars opercularis and right pars triangularis, and the tracts connecting right inferior temporal gyrus and right middle temporal gyrus. For the entire PD-N cohort, FAS verbal fluency scores positively correlated with MD in the superior longitudinal fasciculus (SLF). This study confirmed that PIGD-N phenotype has more deficits in verbal fluency task than TD-N phenotype. Additionally, our findings suggest: (1) PIGD-N shows more microstructural changes related to FAS verbal fluency task when compared to TD-N phenotype; (2) SLF plays an important role in FAS verbal fluency task in PD-N patients regardless of motor phenotypes.

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.

Influences of affective context on amygdala functional connectivity during cognitive control from adolescence through adulthood

Emotion processing is believed to dominate over other brain functions during adolescence, including inhibitory control. However, few studies have examined the neural underpinnings of affective states during cognitive control. Here, we characterized the brain in an affective state by cross-sectionally assessing age-related changes in amygdala background connectivity during an affective inhibitory control task. Participants completed an antisaccade (AS) fMRI task while affective auditory stimuli were presented, and a 5-minute resting state scan. Results showed that while adolescents reported similar arousal levels across emotional conditions, adults perceived negative sounds to be more “arousing” and performed better than adolescents in negative trials. Amygdala background connectivity showed age-related increases with brain regions related to attention and executive control, which were not evident during resting state. Together, results suggest that amygdala connectivity within an affective context is fairly low in mid-adolescence but much stronger in adulthood, supporting age-related improvements in inhibitory control within an affective state. These findings suggest limitations during adolescence in differentiating between the arousing effects of various emotions, potentially undermining the ability to optimally engage inhibitory control. Furthermore, the age-related fMRI findings suggest that low amygdala connectivity to brain areas involved in executive control may underlie these limited abilities during adolescence.

Hemodynamic responses are abnormal in isolated cervical dystonia

Neuroimaging studies using functional magnetic resonance imaging (fMRI), which measures brain activity by detecting the changes in blood oxygenation levels, are advancing our understanding of the pathophysiology of dystonia. Neurobiological disturbances in dystonia, however, may affect neurovascular coupling and impact the interpretability of fMRI studies. We evaluated here whether the hemodynamic response patterns during a behaviorally matched motor task are altered in isolated cervical dystonia (CD). Twenty-five CD patients and 25 healthy controls (HCs) underwent fMRI scanning during a paced finger tapping task (nondystonic task in patients). Imaging data were analyzed using a constrained principal component analysis-a statistical method that combines regression analysis and principal component analysis and enables the extraction of task-related functional networks and determination of the spatial and temporal hemodynamic response patterns associated with the task performance. Data from three patients and two controls were removed due to excessive movement. No significant differences in demographics or motor performance were observed. Three task-associated functional brain networks were identified. During task performance, reduced hemodynamic responses were seen in a sensorimotor network and in a network that included key nodes of the default mode, executive control and visual networks. During rest, reductions in hemodynamic responses were seen in the cognitive/visual network. Lower hemodynamic responses within the primary sensorimotor network in patients were correlated with the increased dystonia severity. Pathophysiological disturbances in isolated CD, such as alterations in inhibitory signaling and dopaminergic neurotransmission, may impact neurovascular coupling. Not accounting for hemodynamic response differences in fMRI studies of dystonia could lead to inaccurate results and interpretations.

Distinct temporal brain dynamics in bipolar disorder and schizophrenia during emotion regulation

BACKGROUND

Disturbances in emotion regulation (ER) are characteristic of both patients with bipolar disorder (BD) and schizophrenia (SZ). We investigated the temporal dynamics of brain activation during cognitive ER in BD and SZ to understand the contribution of temporal characteristics of disturbed ER to their unique and shared symptomatology.

METHOD

Forty-six participants performed an ER-task (BD, n = 15; SZ, n = 16; controls, n = 15) during functional magnetic resonance imaging, in which they were instructed to use cognitive reappraisal techniques to regulate their emotional responses. Finite impulse response modeling was applied to estimate the temporal dynamics of brain responses during cognitive reappraisal (v. passive attending) of negative pictures. Group, time, and group × time effects were tested using multivariate modeling.

RESULTS

We observed a group × time interaction during ER in the ventrolateral prefrontal cortex (VLPFC), supplementary motor area (SMA) and inferior occipital gyrus. Patients with SZ demonstrated initial hyper-activation of the VLPFC and SMA activation that was not sustained in later regulatory phases. Response profiles in the inferior occipital gyrus in SZ showed abnormal activation in the later phases of regulation. BD-patients showed general blunted responsivity in these regions.

CONCLUSIONS

These results suggest that ER-disturbances in SZ are characterized by an inefficient initialization and failure to sustain regulatory control, whereas in BD, a failure to recruit regulatory resources may represent initial deficits in formulating adequate representations of the regulatory needs. This may help to further understand how ER-disturbances give rise to symptomatology of BD and SZ.

I am Me: Brain systems integrate and segregate to establish a multidimensional sense of self

Humans experience a sense of self, which is proposed to emerge from the integration of intrinsic and extrinsic self-processing through the propagation of information across brain systems. Using a novel functional magnetic resonance imaging (fMRI) paradigm, we tested this hypothesis in a non-clinical sample by modulating the intrinsic and extrinsic self-relatedness of auditory action consequences in terms of identity and agency, respectively. In addition, the relevance of individual traits associated with altered self-experiences (e.g., psychosis-like experiences) was examined. The task-evoked fMRI results showed distinctive associations between the neural coding of identity and negative affect traits, and between agency and psychosis-like experiences. Most importantly, regarding the functional connectivity analysis, graph theoretical measures demonstrated that the simultaneous processing of identity and agency relies on the functional integration and segregation of default mode, sensorimotor, language, and executive brain networks. Finally, cross-network interactions mediated by executive and sensorimotor regions were negatively associated with psychosis-like experiences when the intrinsic and extrinsic self-relatedness of action consequences conflicted. These findings provide evidence that the self is a multidimensional phenomenon rooted in the functional interactions between large-scale neuronal networks. Such interactions may have particular relevance for self-experience alterations.

Handling Multiplicity in Neuroimaging Through Bayesian Lenses with Multilevel Modeling

Here we address the current issues of inefficiency and over-penalization in the massively univariate approach followed by the correction for multiple testing, and propose a more efficient model that pools and shares information among brain regions. Using Bayesian multilevel (BML) modeling, we control two types of error that are more relevant than the conventional false positive rate (FPR): incorrect sign (type S) and incorrect magnitude (type M). BML also aims to achieve two goals: 1) improving modeling efficiency by having one integrative model and thereby dissolving the multiple testing issue, and 2) turning the focus of conventional null hypothesis significant testing (NHST) on FPR into quality control by calibrating type S errors while maintaining a reasonable level of inference efficiency. The performance and validity of this approach are demonstrated through an application at the region of interest (ROI) level, with all the regions on an equal footing: unlike the current approaches under NHST, small regions are not disadvantaged simply because of their physical size. In addition, compared to the massively univariate approach, BML may simultaneously achieve increased spatial specificity and inference efficiency, and promote results reporting in totality and transparency. The benefits of BML are illustrated in performance and quality checking using an experimental dataset. The methodology also avoids the current practice of sharp and arbitrary thresholding in the p-value funnel to which the multidimensional data are reduced. The BML approach with its auxiliary tools is available as part of the AFNI suite for general use.

Proactive and reactive cognitive control rely on flexible use of the ventrolateral prefrontal cortex

The role of ventral versus dorsolateral prefrontal regions in instantiating proactive and reactive cognitive control remains actively debated, with few studies parsing cue versus probe-related activity. Rapid sampling (460 ms), long cue-probe delays, and advanced analytic techniques (deconvolution) were therefore used to quantify the magnitude and variability of neural responses during the AX Continuous Performance Test (AX-CPT; N = 46) in humans. Behavioral results indicated slower reaction times during reactive cognitive control (AY trials) in conjunction with decreased accuracy and increased variability for proactive cognitive control (BX trials). The anterior insula/ventrolateral prefrontal cortex (aI/VLPFC) was commonly activated across comparisons of both proactive and reactive cognitive control. In contrast, activity within the dorsomedial and dorsolateral prefrontal cortex was limited to reactive cognitive control. The instantiation of proactive cognitive control during the probe period was also associated with sparse neural activation relative to baseline, potentially as a result of the high degree of neural and behavioral variability observed across individuals. Specifically, the variability of the hemodynamic response function (HRF) within motor circuitry increased after the presentation of B relative to A cues (i.e., late in HRF) and persisted throughout the B probe period. Finally, increased activation of right aI/VLPFC during the cue period was associated with decreased motor circuit activity during BX probes, suggesting a possible role for the aI/VLPFC in proactive suppression of neural responses. Considered collectively, current results highlight the flexible role of the VLPFC in implementing cognitive control during the AX-CPT task but suggest large individual differences in proactive cognitive control strategies.

The experience of vivid autobiographical reminiscence is supported by subjective content representations in the precuneus

The human posteromedial cortex, which includes core regions of the default mode network (DMN), is thought to play an important role in episodic memory. However, the nature and functional role of representations in these brain regions remain unspecified. Nine participants (all female) wore smartphone devices to record episodes from their daily lives for multiple weeks, each night indicating the personally-salient attributes of each episode. Participants then relived their experiences in an fMRI scanner cued by images from their own lives. Representational Similarity Analysis revealed a broad network, including parts of the DMN, that represented personal semantics during autobiographical reminiscence. Within this network, activity in the right precuneus reflected more detailed representations of subjective contents during vivid relative to non-vivid, recollection. Our results suggest a more specific mechanism underlying the phenomenology of vivid autobiographical reminiscence, supported by rich subjective content representations in the precuneus, a hub of the DMN previously implicated in metacognitive evaluations during memory retrieval.

Functional connections between activated and deactivated brain regions mediate emotional interference during externally directed cognition

Recent evidence shows that task-deactivations are functionally relevant for cognitive performance. Indeed, higher cognitive engagement has been associated with higher suppression of activity in task-deactivated brain regions - usually ascribed to the Default Mode Network (DMN). Moreover, a negative correlation between these regions and areas actively engaged by the task is associated with better performance. DMN regions show positive modulation during autobiographical, social, and emotional tasks. However, it is not clear how processing of emotional stimuli affects the interplay between the DMN and executive brain regions. We studied this interplay in an fMRI experiment using emotional negative stimuli as distractors. Activity modulations induced by the emotional interference of negative stimuli were found in frontal, parietal, and visual areas, and were associated with modulations of functional connectivity between these task-activated areas and DMN regions. A worse performance was predicted both by lower activity in the superior parietal cortex and higher connectivity between visual areas and frontal DMN regions. Connectivity between right inferior frontal gyrus and several DMN regions in the left hemisphere was related to the behavioral performance. This relation was weaker in the negative than in the neutral condition, likely suggesting less functional inhibitions of DMN regions during emotional processing. These results show that both executive and DMN regions are crucial for the emotional interference process and suggest that DMN connections are related to the interplay between externally-directed and internally-focused processes. Among DMN regions, superior frontal gyrus may be a key node in regulating the interference triggered by emotional stimuli.

Adolescent cannabis use and brain systems supporting adult working memory encoding, maintenance, and retrieval

Given prior reports of adverse effects of cannabis use on working memory, an executive function with a protracted developmental course during adolescence, we examined associations between developmental patterns of cannabis use and adult working memory (WM) processes. Seventy-five adults with longitudinal assessments of cannabis use (60 with reported use, 15 with no reported use) and prenatal drug exposure assessment completed a spatial WM task during fMRI at age 28. All subjects passed a multi-drug urine screen on the day of testing and denied recreational drug use in the past week. A fast event-related design with partial trials was used to separate the BOLD response associated with encoding, maintenance, and retrieval periods of the WM task. Behavioral results showed that subjects who began using cannabis earlier in adolescence had longer reaction times (RT) than those with later initiation. Cannabis age of onset was further associated with reduced posterior parietal cortex (PPC) encoding BOLD activation, which significantly mediated age of onset WM RT associations. However, cannabis age of onset brain-behavior associations did not differ between groups with a single reported use and those with repeated use, suggesting age of onset effects may reflect substance use risk characteristics rather than a developmentally-timed cannabis exposure effect. Within repeated cannabis users, greater levels of total cannabis use were associated with performance-related increases in dorsolateral prefrontal cortex (DLPFC) activation during maintenance. This pattern of significant results remained unchanged with inclusion of demographic and prenatal measures as covariates. Surprisingly, however, at the group level, cannabis users generally performed better than participants who reported never using cannabis (faster RT, higher accuracy). We extend previous investigations by identifying that WM associations with cannabis age of onset may be primary to PPC stimulus encoding activity, while the amount of cannabis use is associated with DLPFC maintenance processes. Poorer performance of participants who reported never using cannabis and the consistency of cannabis age of onset associations across single and repeated users limit interpretation of direct developmental effects of cannabis on WM in adulthood.

Revisiting the Functional and Structural Connectivity of Large-Scale Cortical Networks

Multimodal neuroimaging research has become increasingly popular, and structure-function correspondence is tacitly assumed. Researchers have not yet adequately assessed whether the functional connectivity (FC) and structural connectivity (SC) of large-scale cortical networks are in agreement. Structural magnetic resonance imaging (sMRI), resting-state functional MRI (rfMRI), and diffusion-weighted imaging (DWI) data sets from 36 healthy subjects (age 27.4) were selected from a Rockland sample (Enhanced Nathan Kline Institute). The cerebral cortex was parcellated into 62 regions according to the Desikan-Killiany atlas for FC and SC analyses. Thresholded correlations in rfMRI and tractography derived from DWI were used to construct FC and SC maps, respectively. A community detection algorithm was applied to reveal the underlying organization, and modular consistency was quantified to bridge cross-modal comparisons. The distributions of correlation coefficients in FC and SC maps were significantly different. Approximately one-fourth of the connections in the SC map were located at a correlation level below 0.2 (df 253). The index of modular consistency in the within-modality interindividual condition (either FC or SC) was considerably greater than that in the between-modality intraindividual analog. In addition, the SC-FC differential map (SC connections with lower correlations) revealed reliable modular structures. Based on these results, the hypothesized FC-SC agreement is partially valid. Contingent on extant neuroimaging tools and analytical conventions, the neural informatics of FC and SC should be regarded as complementary rather than concordant. Furthermore, the results verify the physiological significance of moderately (or mildly) correlated brain signals in rfMRI, which are often discarded by stringent thresholding.

Behavioral and Neural Sustained Attention Deficits in Bipolar Disorder and Familial Risk of Bipolar Disorder

BACKGROUND

Few neuroimaging studies compare individuals affected with bipolar disorder (BP), at high familial risk of BP, and at low risk to identify endophenotypes for BP. None have examined variability in attention, despite promising behavioral work in this area. We used functional magnetic resonance imaging (fMRI) methods uniquely powered to compare the neural correlates of attention variability in these three groups.

METHODS

The present study examined 8- to 25-year-old individuals (n = 106) who completed an fMRI attention task: 24 with BP, 29 at risk based on a first-degree relative with BP, and 53 healthy, low-risk individuals. Group differences in intrasubject variability in reaction time were examined, and a sophisticated fMRI analytic approach was used to quantify precisely trialwise associations between reaction time and brain activity. The latter has not been examined previously in BP or risk of BP.

RESULTS

Relative to healthy individuals, those with BP or at risk for BP exhibited increased reaction time variability (F_2,102 = 4.26, p = .02, η_p² = .08). Importantly, we identified blunted relationships between trialwise variation in reaction time and brain activity in the inferior and middle frontal gyri, precuneus, cingulate cortex, caudate, and postcentral gyrus (all regions: p < .001, η_p² > .06) in both at-risk and BP individuals compared with healthy, low-risk individuals. This blunting partially mediated group differences in reaction time variability (β = .010, 95% confidence interval 0.002 to 0.020, Sobel Z = 2.08, p = .038).

CONCLUSIONS

Blunting in key frontal, cingulate, and striatal areas was evident in unaffected, at-risk individuals and in euthymic BP patients. Elucidating such novel neural endophenotypes can facilitate new approaches to BP prediction, diagnosis, and prevention.

Behavioral and Neural Sustained Attention Deficits in Disruptive Mood Dysregulation Disorder and Attention-Deficit/Hyperactivity Disorder

OBJECTIVE

Disruptive mood dysregulation disorder (DMDD), characterized by severe irritability, and attention-deficit/hyperactivity disorder (ADHD) are highly comorbid. This is the first study to characterize neural and behavioral similarities and differences in attentional functioning across these disorders.

METHOD

Twenty-seven healthy volunteers, 31 patients with DMDD, and 25 patients with ADHD (8 to 18 years old) completed a functional magnetic resonance imaging attention task. Group differences in intra-subject variability in reaction time (RT) were examined. The present functional magnetic resonance imaging analytic approach precisely quantified trial-wise associations between RT and brain activity.

RESULTS

Group differences manifested in the relation between RT and brain activity (all regions: p < .01, F > 2.54, partial eta-squared [ηp2] > 0.06). Patients with DMDD showed specific alterations in the right paracentral lobule, superior parietal lobule, fusiform gyrus, and cerebellar culmen. In contrast, patients with DMDD and those with ADHD exhibited blunted compensatory increases in activity on long RT trials. In addition, youth with DMDD exhibited increased activity in the postcentral gyrus, medial frontal gyrus, and cerebellar tonsil and declive (all regions: p < .05, F > 2.46, ηp2 > 0.06). Groups in the imaging sample did not differ significantly in intra-subject variability in RT (F2,79 = 2.664, p = .076, ηp2 = 0.063), although intra-subject variability in RT was significantly increased in youth with DMDD and ADHD when including those not meeting strict motion and accuracy criteria for imaging analysis (F2,96 = 4.283, p = .017, ηp2 = 0.083).

CONCLUSION

Patients with DMDD exhibited specific alterations in the relation between pre-stimulus brain activity and RT. Patients with DMDD and those with ADHD exhibited similar blunting of compensatory neural activity in frontal, parietal, and other regions. In addition, patients with DMDD showed increased RT variability compared with healthy youth. This work is the first to identify common and unique behavioral and neural signatures of DMDD and ADHD.

Is the statistic value all we should care about in neuroimaging?

Here we address an important issue that has been embedded within the neuroimaging community for a long time: the absence of effect estimates in results reporting in the literature. The statistic value itself, as a dimensionless measure, does not provide information on the biophysical interpretation of a study, and it certainly does not represent the whole picture of a study. Unfortunately, in contrast to standard practice in most scientific fields, effect (or amplitude) estimates are usually not provided in most results reporting in the current neuroimaging publications and presentations. Possible reasons underlying this general trend include (1) lack of general awareness, (2) software limitations, (3) inaccurate estimation of the BOLD response, and (4) poor modeling due to our relatively limited understanding of FMRI signal components. However, as we discuss here, such reporting damages the reliability and interpretability of the scientific findings themselves, and there is in fact no overwhelming reason for such a practice to persist. In order to promote meaningful interpretation, cross validation, reproducibility, meta and power analyses in neuroimaging, we strongly suggest that, as part of good scientific practice, effect estimates should be reported together with their corresponding statistic values. We provide several easily adaptable recommendations for facilitating this process.

Untangling the relatedness among correlations, part I: Nonparametric approaches to inter-subject correlation analysis at the group level

FMRI data acquisition under naturalistic and continuous stimuli (e.g., watching a video or listening to music) has become popular recently due to the fact that it entails less manipulation and more realistic/complex contexts involved in the task, compared to the conventional task-based experimental designs. The synchronization or response similarities among subjects are typically measured through inter-subject correlation (ISC) between any pair of subjects. At the group level, summarizing the collection of ISC values is complicated by their intercorrelations, which necessarily lead to the violation of independence assumed in typical parametric approaches such as Student's t-test. Nonparametric methods, such as bootstrapping and permutation testing, have previously been adopted for testing purposes by resampling the time series of each subject, but the quantitative validity of these specific approaches in terms of controllability of false positive rate (FPR) has never been explored before. Here we survey the methods of ISC group analysis that have been employed in the literature, and discuss the issues involved in those methods. We then propose less computationally intensive nonparametric methods that can be performed at the group level (for both one- and two-sample analyses), as compared to the popular method of circularly shifting the EPI time series at the individual level. As part of the new approaches, subject-wise (SW) resampling is adopted instead of element-wise (EW) resampling, so that exchangeability and independence assumptions are satisfied, and the patterned correlation structure among the ISC values can be more accurately captured. We examine the FPR controllability and power achievement of all the methods through simulations, as well as their performance when applied to a real experimental dataset.

Open Environment for Multimodal Interactive Connectivity Visualization and Analysis

Brain connectivity investigations are becoming increasingly multimodal and they present challenges for quantitatively characterizing and interactively visualizing data. In this study, we present a new set of network-based software tools for combining functional and anatomical connectivity from magnetic resonance imaging (MRI) data. The computational tools are available as part of Functional and Tractographic Connectivity Analysis Toolbox (FATCAT), a toolbox that interfaces with Analysis of Functional NeuroImages (AFNI) and SUrface MApping (SUMA) for interactive queries and visualization. This includes a novel, tractographic mini-probabilistic approach to improve streamline tracking in networks. We show how one obtains more robust tracking results for determining white matter connections by utilizing the uncertainty of the estimated diffusion tensor imaging (DTI) parameters and a few Monte Carlo iterations. This allows for thresholding based on the number of connections between target pairs to reduce the presence of tracts likely due to noise. To assist users in combining data, we describe an interface for navigating and performing queries in two-dimensional and three-dimensional data defined over voxel, surface, tract, and graph domains. These varied types of information can be visualized simultaneously and the queries performed interactively using SUMA and AFNI. The methods have been designed to increase the user's ability to visualize and combine functional MRI and DTI modalities, particularly in the context of single-subject inferences (e.g., in deep brain stimulation studies). Finally, we present a multivariate framework for statistically modeling network-based features in group analysis, which can be implemented for both functional and structural studies.