Task-based fMRI Research Articles

Why graph theory deserves more focus. Comment on “Connectivity analyses for task-based fMRI” by Huang et al.

Huang et al. have conducted a thorough examination of methodologies used for identifying and analyzing functional connectivity using task-based fMRI. Their review adeptly describes current approaches without bias or preference. In this commentary, we explain why we believe that graph theory is the optimal approach for studying neural mechanisms associated with complex behaviors and cognitive processes that are engaged during task-based fMRI.

Covert Consciousness in the ICU.

For critically ill patients with acute severe brain injuries, consciousness may reemerge before behavioral responsiveness. The phenomenon of covert consciousness (i.e., cognitive motor dissociation) may be detected by advanced neurotechnologies such as task-based functional MRI (fMRI) and electroencephalography (EEG) in patients who appear unresponsive on the bedside behavioral examination. In this narrative review, we summarize the state-of-the-science in ICU detection of covert consciousness. Further, we consider the prognostic and therapeutic implications of diagnosing covert consciousness in the ICU, as well as its potential to inform discussions about continuation of life-sustaining therapy for patients with severe brain injuries. We reviewed salient medical literature regarding covert consciousness. We included clinical studies investigating the diagnostic performance characteristics and prognostic utility of advanced neurotechnologies such as task-based fMRI and EEG. We focus on clinical guidelines, professional society scientific statements, and neuroethical analyses pertaining to the implementation of advanced neurotechnologies in the ICU to detect covert consciousness. We extracted study results, guideline recommendations, and society scientific statement recommendations regarding the diagnostic, prognostic, and therapeutic relevance of covert consciousness to the clinical care of ICU patients with severe brain injuries. Emerging evidence indicates that covert consciousness is present in approximately 15-20% of ICU patients who appear unresponsive on behavioral examination. Covert consciousness may be detected in patients with traumatic and nontraumatic brain injuries, including patients whose behavioral examination suggests a comatose state. The presence of covert consciousness in the ICU may predict the pace and extent of long-term functional recovery. Professional society guidelines now recommend assessment of covert consciousness using task-based fMRI and EEG. However, the clinical criteria for patient selection for such investigations are uncertain and global access to advanced neurotechnologies is limited.

Surveying the neuroimager's connectivity toolbox: Comment on “Connectivity analyses for task-based fMRI” by Huang, De Brigard, Cabeza, & Davis

Surveying the neuroimager's connectivity toolbox: Comment on “Connectivity analyses for task-based fMRI” by Huang, De Brigard, Cabeza, & Davis

Opportunities and challenges in connectivity analysis for task-based fMRI comment on “connectivity analyses for task-based fMRI” by Huang S, De Brigard, F., Cabeza, R, and Davis, S.W.

Opportunities and challenges in connectivity analysis for task-based fMRI comment on “connectivity analyses for task-based fMRI” by Huang S, De Brigard, F., Cabeza, R, and Davis, S.W.

A comparison of fMRI presurgical mapping techniques with intraoperative brain mapping-based validation

Abstract Resting-state functional MRI (rsfMRI) could enable preoperative risk assessment and intraoperative guidance for patients who cannot undergo task-based fMRI (tbfMRI). To ascertain rsfMRI’s applicability, we investigated differences in accuracy between tbfMRI with a voxel size of 1.8 x 1.8 x 3.2 mm³ and rsfMRI acquired with single-echo (sTE) with a voxel size of 2 x 2 x 2.2 mm³ and multiecho (mTE) with a voxel size of 3 x 3 x 3 mm³ using intraoperative mapping with direct electrical stimulations (DES) as the ground truth. Functional sensory-motor mapping results of hands and feet were spatially compared relative to positive (pDES, functional effect) and negative (nDES, no functional effect) coordinates in 16 preoperative patients. A general linear model analysis was used for tbfMRI, and seed-based analysis (SBA) for rsfMRI. Minimum Euclidean distances between fMRI and DES were calculated and compared between fMRI methods. Receiver-operating characteristic (ROC) curves were used to compare accuracy and determine distance cutoffs for fMRI agreement with DES, and binary agreement rates were compared at different cutoffs. Two-part mixed-effects linear models were used to compare fMRI methods while accounting for unequal intersubject DES repetition. Only minor differences were found between fMRI methods in unthresholded distances (mean differences ~2 mm). ROCs and binary agreement measures showed comparable accuracy for tbfMRI and sTE-rsfMRI at 2 mm, but mildly worse for sTE-rsfMRI at 3 mm and mTE-rsfMRI. However, differences in relative accuracy between sTE-rsfMRI and mTE-rsfMRI were minor when the same distance cutoff was applied to all methods. This was also reflected in comparing binary agreement rates and confirmed by the two-part linear models, which showed no significant differences between fMRI methods and a significant effect of DES response. A similar accuracy for SBA rsfMRI functional sensory-motor mapping compared with tbfMRI for the hands and feet indicates that rsfMRI may be suitable for presurgical mapping. The differences in relative accuracy between sTE-rsfMRI and mTE-rsfMRI warrant further investigation in a larger sample.

Functional near-infrared spectroscopy-based neurofeedback training targeting the dorsolateral prefrontal cortex induces changes in cortico-striatal functional connectivity

Due to its central role in cognitive control, the dorso–lateral prefrontal cortex (dlPFC) has been the target of multiple brain modulation studies. In the context of the present pilot study, the dlPFC was the target of eight repeated neurofeedback (NF) sessions with functional near infrared spectroscopy (fNIRS) to assess the brain responses during NF and with functional and resting state magnetic resonance imaging (task-based fMRI and rsMRI) scanning. Fifteen healthy participants were recruited. Cognitive task fMRI and rsMRI were performed during the 1st and the 8th NF sessions. During NF, our data revealed an increased activity in the dlPFC as well as in brain regions involved in cognitive control and self-regulation learning (pFWE < 0.05). Changes in functional connectivity between the 1st and the 8th session revealed increased connectivity between the posterior cingulate cortex and the dlPFC, and between the posterior cingulate cortex and the dorsal striatum (pFWE < 0.05). Decreased left dlPFC-left insula connectivity was also observed. Behavioural results revealed a significant effect of hunger and motivation on the participant control feeling and a lower control feeling when participants did not identify an effective mental strategy, providing new insights on the effects of behavioural factors that may affect the NF learning.

Trait reward sensitivity modulates connectivity with the temporoparietal junction and Anterior Insula during strategic decision making

Many decisions happen in social contexts such as negotiations, yet little is understood about how people balance fairness versus selfishness. Past investigations found that activation in brain areas involved in executive function and reward processing was associated with people offering less with no threat of rejection from their partner, compared to offering more when there was a threat of rejection. However, it remains unclear how trait reward sensitivity may modulate activation and connectivity patterns in these situations. To address this gap, we used task-based fMRI to examine the relation between reward sensitivity and the neural correlates of bargaining choices. Participants (N = 54) completed the Sensitivity to Punishment (SP)/Sensitivity to Reward (SR) Questionnaire and the Behavioral Inhibition System/Behavioral Activation System scales. Participants performed the Ultimatum and Dictator Games as proposers and exhibited strategic decisions by being fair when there was a threat of rejection, but being selfish when there was not a threat of rejection. We found that strategic decisions evoked activation in the Inferior Frontal Gyrus (IFG) and the Anterior Insula (AI). Next, we found elevated IFG connectivity with the Temporoparietal junction (TPJ) during strategic decisions. Finally, we explored whether trait reward sensitivity modulated brain responses while making strategic decisions. We found that people who scored lower in reward sensitivity made less strategic choices when they exhibited higher AI-Angular Gyrus connectivity. Taken together, our results demonstrate how trait reward sensitivity modulates neural responses to strategic decisions, potentially underscoring the importance of this factor within social and decision neuroscience.

Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis.

Recent studies have provided promising evidence that neuroimaging data can predict treatment outcomes for patients with major depressive disorder (MDD). As most of these studies had small sample sizes, a meta-analysis is warranted to identify the most robust findings and imaging modalities, and to compare predictive outcomes obtained in magnetic resonance imaging (MRI) and studies using clinical and demographic features. We conducted a literature search from database inception to July 22, 2023, to identify studies using pretreatment clinical or brain MRI features to predict treatment outcomes in patients with MDD. Two meta-analyses were conducted on clinical and MRI studies, respectively. The meta-regression was employed to explore the effects of covariates and compare the predictive performance between clinical and MRI groups, as well as across MRI modalities and intervention subgroups. Meta-analysis of 13 clinical studies yielded an area under the curve (AUC) of 0.73, while in 44 MRI studies, the AUC was 0.89. MRI studies showed a higher sensitivity than clinical studies (0.78 vs. 0.62, Z = 3.42, P = 0.001). In MRI studies, resting-state functional MRI (rsfMRI) exhibited a higher specificity than task-based fMRI (tbfMRI) (0.79 vs. 0.69, Z = -2.86, P = 0.004). No significant differences in predictive performance were found between structural and functional MRI, nor between different interventions. Of note, predictive MRI features for treatment outcomes in studies using antidepressants were predominantly located in the limbic and default mode networks, while studies of electroconvulsive therapy (ECT) were restricted mainly to the limbic network. Our findings suggest a promise for pretreatment brain MRI features to predict MDD treatment outcomes, outperforming clinical features. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. Overlapping but distinct network-level measures predicted antidepressants and ECT outcomes. Future studies are needed to predict outcomes using multiple MRI features, and to clarify whether imaging features predict outcomes generally or differ depending on treatments.

Reliability of task-based fMRI in the dorsal horn of the human spinal cord

Abstract The application of functional magnetic resonance imaging (fMRI) to the human spinal cord is still a relatively small field of research and faces many challenges. Here we aimed to probe the limitations of task-based spinal fMRI at 3T by investigating the reliability of spinal cord blood oxygen level dependent (BOLD) responses to repeated nociceptive stimulation across 2 consecutive days in 40 healthy volunteers. We assessed the test–retest reliability of subjective ratings, autonomic responses, and spinal cord BOLD responses to short heat-pain stimuli (1 s duration) using the intraclass correlation coefficient (ICC). At the group level, we observed robust autonomic responses as well as spatially specific spinal cord BOLD responses at the expected location, but no spatial overlap in BOLD response patterns across days. While autonomic indicators of pain processing showed good-to-excellent reliability, both β-estimates and z-scores of task-related BOLD responses showed poor reliability across days in the target region (gray matter of the ipsilateral dorsal horn). When taking into account the sensitivity of gradient-echo echo planar imaging (GE-EPI) to draining vein signals by including the venous plexus in the analysis, we observed BOLD responses with fair reliability across days. Taken together, these results demonstrate that heat-pain stimuli as short as 1 s are able to evoke a robust and spatially specific BOLD response, which is, however, strongly variable within participants across time, resulting in low reliability in the dorsal horn gray matter. Further improvements in data acquisition and analysis techniques are thus necessary before event-related spinal cord fMRI as used here can be reliably employed in longitudinal designs or clinical settings.

Decoding acceptance and reappraisal strategies from resting state macro networks

Acceptance and reappraisal are considered adaptive emotion regulation strategies. While previous studies have explored the neural underpinnings of these strategies using task-based fMRI and sMRI, a gap exists in the literature concerning resting-state functional brain networks’ contributions to these abilities, especially regarding acceptance. Another intriguing question is whether these strategies rely on similar or different neural mechanisms. Building on the well-known improved emotion regulation and increased cognitive flexibility of individuals who rely on acceptance, we expected to find decreased activity inside the affective network and increased activity inside the executive and sensorimotor networks to be predictive of acceptance. We also expect that these networks may be associated at least in part with reappraisal, indicating a common mechanism behind different strategies. To test these hypotheses, we conducted a functional connectivity analysis of resting-state data from 134 individuals (95 females; mean age: 30.09 ± 12.87 years, mean education: 12.62 ± 1.41 years). To assess acceptance and reappraisal abilities, we used the Cognitive Emotion Regulation Questionnaire (CERQ) and a group-ICA unsupervised machine learning approach to identify resting-state networks. Subsequently, we conducted backward regression to predict acceptance and reappraisal abilities. As expected, results indicated that acceptance was predicted by decreased affective, and executive, and increased sensorimotor networks, while reappraisal was predicted by an increase in the sensorimotor network only. Notably, these findings suggest both distinct and overlapping brain contributions to acceptance and reappraisal strategies, with the sensorimotor network potentially serving as a core common mechanism. These results not only align with previous findings but also expand upon them, illustrating the complex interplay of cognitive, affective, and sensory abilities in emotion regulation.

Trait Reward Sensitivity Modulates Connectivity with the Temporoparietal Junction and Anterior Insula during Strategic Decision Making.

Many decisions happen in social contexts such as negotiations, yet little is understood about how people balance fairness versus selfishness. Past investigations found that activation in brain areas involved in executive function and reward processing was associated with people offering less with no threat of rejection from their partner, compared to offering more when there was a threat of rejection. However, it remains unclear how trait reward sensitivity may modulate activation and connectivity patterns in these situations. To address this gap, we used task-based fMRI to examine the relation between reward sensitivity and the neural correlates of bargaining choices. Participants (N = 54) completed the Sensitivity to Punishment (SP)/Sensitivity to Reward (SR) Questionnaire and the Behavioral Inhibition System/Behavioral Activation System scales. Participants performed the Ultimatum and Dictator Games as proposers and exhibited strategic decisions by being fair when there was a threat of rejection, but being selfish when there was not a threat of rejection. We found that strategic decisions evoked activation in the Inferior Frontal Gyrus (IFG) and the Anterior Insula (AI). Next, we found elevated IFG connectivity with the Temporoparietal junction (TPJ) during strategic decisions. Finally, we explored whether trait reward sensitivity modulated brain responses while making strategic decisions. We found that people who scored lower in reward sensitivity made less strategic choices when they exhibited higher AI-Angular Gyrus connectivity. Taken together, our results demonstrate how trait reward sensitivity modulates neural responses to strategic decisions, potentially underscoring the importance of this factor within social and decision neuroscience.

Cognitive Motor Dissociation in Disorders of Consciousness

BackgroundPatients with brain injury who are unresponsive to commands may perform cognitive tasks that are detected on functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). This phenomenon, known as cognitive motor dissociation, has not been systematically studied in a large cohort of persons with disorders of consciousness.MethodsIn this prospective cohort study conducted at six international centers, we collected clinical, behavioral, and task-based fMRI and EEG data from a convenience sample of 353 adults with disorders of consciousness. We assessed the response to commands on task-based fMRI or EEG in participants without an observable response to verbal commands (i.e., those with a behavioral diagnosis of coma, vegetative state, or minimally conscious state–minus) and in participants with an observable response to verbal commands. The presence or absence of an observable response to commands was assessed with the use of the Coma Recovery Scale–Revised (CRS-R).ResultsData from fMRI only or EEG only were available for 65% of the participants, and data from both fMRI and EEG were available for 35%. The median age of the participants was 37.9 years, the median time between brain injury and assessment with the CRS-R was 7.9 months (25% of the participants were assessed with the CRS-R within 28 days after injury), and brain trauma was an etiologic factor in 50%. We detected cognitive motor dissociation in 60 of the 241 participants (25%) without an observable response to commands, of whom 11 had been assessed with the use of fMRI only, 13 with the use of EEG only, and 36 with the use of both techniques. Cognitive motor dissociation was associated with younger age, longer time since injury, and brain trauma as an etiologic factor. In contrast, responses on task-based fMRI or EEG occurred in 43 of 112 participants (38%) with an observable response to verbal commands.ConclusionsApproximately one in four participants without an observable response to commands performed a cognitive task on fMRI or EEG as compared with one in three participants with an observable response to commands. (Funded by the James S. McDonnell Foundation and others.)

Altered functional connectivity of primary olfactory cortex-hippocampus-frontal cortex in subjective cognitive decline during odor stimulation.

Subjective cognitive decline (SCD) is a high-risk population in the preclinical stage of Alzheimer's disease (AD), and olfactory dysfunction is a risk factor for dementia progression. The present study aimed to explore the patterns of functional connectivity (FC) changes in the olfactory neural circuits during olfactory stimulation in SCD subjects. A total of 56 SCD subjects and 56 normal controls (NCs) were included. All subjects were assessed with a cognitive scale, an olfactory behavior test, and olfactory task-based functional magnetic resonance imaging scanning. The FC differences in olfactory neural circuits between the two groups were analyzed by the generalized psychophysiological interaction. Additionally, we calculated and compared the activation of brain regions within the olfactory neural circuits during odor stimulation, the volumetric differences in brain regions showing FC differences between groups, and the correlations between neuroimaging indicators and olfactory behavioral and cognitive scale scores. During odor stimulation, the FC between the bilateral primary olfactory cortex (bPOC) and the right hippocampus in the SCD group was significantly reduced; while the FC between the right hippocampus and the right frontal cortex was significantly increased in the SCD group. The bPOC of all subjects showed significant activation, but no significant difference in activation between groups was found. No significant differences were observed in the volume of the brain regions within the olfactory neural circuits or in olfactory behavior between groups. The volume of the bPOC and right frontal cortex was significantly positively correlated with olfactory identification, and the volume of the right frontal cortex and right hippocampus was significantly correlated with cognitive functions. Furthermore, a significant correlation between the activation of bPOC and the olfactory threshold was found in the whole cohort. These results suggested that while the structure of the olfactory neural circuits and olfactory behavior in SCD subjects remained stable, there were significant changes observed in the FC of the olfactory neural circuits (specifically, the POC-hippocampus-frontal cortex neural circuits) during odor stimulation. These findings highlight the potential of FC alterations as sensitive imaging markers for identifying high-risk individuals in the early stage of AD.

Leveraging Multi-Echo EPI to Enhance BOLD Sensitivity in Task-based Olfactory fMRI.

Functional magnetic resonance imaging (fMRI) using blood-oxygenation-level-dependent (BOLD) contrast relies on gradient echo echo-planar imaging (GE-EPI) to quantify dynamic susceptibility changes associated with the hemodynamic response to neural activity. However, acquiring BOLD fMRI in human olfactory regions is particularly challenging due to their proximity to the sinuses where large susceptibility gradients induce magnetic field distortions. BOLD fMRI of the human olfactory system is further complicated by respiratory artifacts that are highly correlated with event onsets in olfactory tasks. Multi-echo EPI (ME-EPI) acquires gradient echo data at multiple echo times (TEs) during a single acquisition and can leverage signal evolution over the multiple echo times to enhance BOLD sensitivity and reduce artifactual signal contributions. In the current study, we developed a ME-EPI acquisition protocol for olfactory task-based fMRI and demonstrated significant improvement in BOLD signal sensitivity over conventional single-echo EPI (1E-EPI). The observed improvement arose from both an increase in BOLD signal changes through a T 2 * -weighted echo combination and a reduction in non-BOLD artifacts through the application of the Multi-Echo Independent Components Analysis (ME-ICA) denoising method. This study represents one of the first direct comparisons between 1E-EPI and ME-EPI in high-susceptibility regions and provides compelling evidence in favor of using ME-EPI for future task-based fMRI studies.

From Maps to Models: A Survey on the Reliability of Small Studies of Task-Based fMRI.

Task-based functional magnetic resonance imaging is a powerful tool for studying brain function, but neuroimaging research produces ongoing concerns regarding small-sample studies and how to interpret them. Although it is well understood that larger samples are preferable, many situations require researchers to make judgments from small studies, including reviewing the existing literature, analyzing pilot data, or assessing subsamples. Quantitative guidance on how to make these judgments remains scarce. To address this, we leverage the Human Connectome Project's Young Adult dataset to survey various analyses-from regional activation maps to predictive models. We find that, for some classic analyses such as detecting regional activation or cluster peak location, studies with as few as 40 subjects are adequate, although this depends crucially on effect sizes. For predictive modeling, similar sizes can be adequate for detecting whether features are predictable, but at least an order of magnitude more (at least hundreds) may be required for developing consistent predictions. These results offer valuable insights for designing and interpreting fMRI studies, emphasizing the importance of considering effect size, sample size, and analysis approach when assessing the reliability of findings. We hope that this survey serves as a reference for identifying which kinds of research questions can be reliably answered with small-scale studies.

The role of functional emotion circuits in distinct dimensions of psychopathology in youth

Several mental disorders emerge during childhood or adolescence and are often characterized by socioemotional difficulties, including alterations in emotion perception. Emotional facial expressions are processed in discrete functional brain modules whose connectivity patterns encode emotion categories, but the involvement of these neural circuits in psychopathology in youth is poorly understood. This study examined the associations between activation and functional connectivity patterns in emotion circuits and psychopathology during development. We used task-based fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC, N = 1221, 8–23 years) and conducted generalized psycho-physiological interaction (gPPI) analyses. Measures of psychopathology were derived from an independent component analysis of questionnaire data. The results showed positive associations between identifying fearful, sad, and angry faces and depressive symptoms, and a negative relationship between sadness recognition and positive psychosis symptoms. We found a positive main effect of depressive symptoms on BOLD activation in regions overlapping with the default mode network, while individuals reporting higher levels of norm-violating behavior exhibited emotion-specific lower functional connectivity within regions of the salience network and between modules that overlapped with the salience and default mode network. Our findings illustrate the relevance of functional connectivity patterns underlying emotion processing for behavioral problems in children and adolescents.

Relationships between tryptophan-related gut metabolites, brain activity, and autism symptomatology.

Gut microbial metabolites have been theorized to play a causative role in the pathophysiology of autism spectrum disorder (ASD). This hypothesis is based on results from mechanistic preclinical studies and several correlational studies showing differences in gut microbial composition between ASD subjects and neurotypical (NT) controls. However, alterations in how the human brain interacts with the gut microbiome in ASD have not been examined. In this cross-sectional, case-control observational study, fecal metabolomics, task-based functional magnetic resonance imaging (fMRI), and behavioral assessments were obtained from 43 ASD and 41 NT children aged 8-17. The fMRI tasks were based on socio-emotional and sensory paradigms that commonly show strong evoked brain differences in ASD participants. General linear models and mediational modeling were applied to examine the links between tryptophan metabolism and evoked brain activity and behavior. Results indicated that fecal levels of specific tryptophan-related metabolites were associated with: 1) brain activity atypicalities in regions previously implicated in ASD (i.e., insula and cingulate); and 2) ASD severity and symptomatology (i.e., ADOS scores, disgust propensity, and sensory sensitivities). Importantly, activity in the mid-insula and mid-cingulate significantly mediated relationships between the microbial tryptophan metabolites, indolelactate and tryptophan betaine, and ASD severity and disgust sensitivity. To our knowledge, this is the first study to elucidate how interactions between gut metabolites and brain activity may impact autism symptomatology, particularly in functional brain pathways associated with vagal and interoceptive/emotion processing.

Probing the functional magnetic resonance imaging response to psilocybin in functional neurological disorder (PsiFUND): study protocol.

Functional neurological disorder (FND) is a common cause of neurological symptoms including paralysis, seizures, and movement disorders. It is often debilitating, is associated with high health and social care costs, and can have a poor prognosis. Functional magnetic resonance imaging (fMRI) has suggested FND is a multi-network disorder; the default mode network (DMN) may be specifically implicated. Converging evidence suggests that other variable mechanisms including dissociation, interoception, and motor agency may be differentially abnormal in people with FND. Psychedelics are currently under investigation for numerous neuropsychiatric disorders and have been shown to disrupt functional networks such as the DMN. Administering psychedelics to people with FND will help us to probe mechanistic theories of the disorder. In this open-label neuroimaging study, we will administer 25mg oral psilocybin with psychological support to people with chronic FND (target n = 24). Participants will undergo resting-state and task-based (Libet's clock, a measure of motor agency) fMRI sequences which will be compared in a pre-post manner. Additional mechanistic outcomes including measures of interoception (heartbeat tracking task), somatisation, illness perceptions, imaginative suggestibility, and dissociation will be collected. Data on expectancy, preparedness, and subjective experience of the psychedelic experience will also be gathered. Participants will be followed up for three months following psilocybin administration. fMRI changes in networks such as the DMN will be analysed using seed-based approaches, and additional exploratory analysis of resting-state imaging will take place. The study will help us to probe the mechanisms thought to potentially underpin FND. As the first modern study of psychedelics in FND, it will also help us to understand whether psychedelic administration alongside psychological support might be safe and feasible in this patient population.

Dissecting task-based fMRI activity using normative modelling: an application to the Emotional Face Matching Task

Functional neuroimaging has contributed substantially to understanding brain function but is dominated by group analyses that index only a fraction of the variation in these data. It is increasingly clear that parsing the underlying heterogeneity is crucial to understand individual differences and the impact of different task manipulations. We estimate large-scale (N = 7728) normative models of task-evoked activation during the Emotional Face Matching Task, which enables us to bind heterogeneous datasets to a common reference and dissect heterogeneity underlying group-level analyses. We apply this model to a heterogenous patient cohort, to map individual differences between patients with one or more mental health diagnoses relative to the reference cohort and determine multivariate associations with transdiagnostic symptom domains. For the face>shapes contrast, patients have a higher frequency of extreme deviations which are spatially heterogeneous. In contrast, normative models for faces>baseline have greater predictive value for individuals’ transdiagnostic functioning. Taken together, we demonstrate that normative modelling of fMRI task-activation can be used to illustrate the influence of different task choices and map replicable individual differences, and we encourage its application to other neuroimaging tasks in future studies.

Cognitive tasks, anatomical MRI, and functional MRI data evaluating the construct of self-regulation

We describe the following shared data from N = 103 healthy adults who completed a broad set of cognitive tasks, surveys, and neuroimaging measurements to examine the construct of self-regulation. The neuroimaging acquisition involved task-based fMRI, resting state fMRI, and structural MRI. Each subject completed the following ten tasks in the scanner across two 90-minute scanning sessions: attention network test (ANT), cued task switching, Columbia card task, dot pattern expectancy (DPX), delay discounting, simple and motor selective stop signal, Stroop, a towers task, and a set of survey questions. The dataset is shared openly through the OpenNeuro project, and the dataset is formatted according to the Brain Imaging Data Structure (BIDS) standard.