Test-retest reliability of fMRI activation during prosaccades and antisaccades

Brain responses to self- and other- unfairness under resource distribution context: Meta-analysis of fMRI studies

Under resource distribution context, individuals have a strong aversion to unfair treatment not only toward themselves but also toward others. However, there is no clear consensus regarding the commonality and distinction between these two types of unfairness. Moreover, many neuroimaging studies have investigated how people evaluate and respond to unfairness in the abovementioned two contexts, but the consistency of the results remains to be investigated. To resolve these two issues, we sought to summarize existing findings regarding unfairness to self and others and to further elucidate the neural underpinnings related to distinguishing evaluation and response processes through meta-analyses of previous neuroimaging studies. Our results indicated that both types of unfairness consistently activate the affective and conflict-related anterior insula (AI) and dorsal anterior cingulate cortex/supplementary motor area (dACC/SMA), but the activations related to unfairness to self appeared stronger than those related to others, suggesting that individuals had negative reactions to both unfairness and a greater aversive response toward unfairness to self. During the evaluation process, unfairness to self activated the bilateral AI, dACC, and right dorsolateral prefrontal cortex (DLPFC), regions associated with unfairness aversion, conflict, and cognitive control, indicating reactive, emotional and automatic responses. In contrast, unfairness to others activated areas associated with theory of mind, the inferior parietal lobule and temporoparietal junction (IPL-TPJ), suggesting that making rational judgments from the perspective of others was needed. During the response, unfairness to self activated the affective-related left AI and striatum, whereas unfairness to others activated cognitive control areas, the left DLPFC and the thalamus. This indicated that the former maintained the traits of automaticity and emotionality, whereas the latter necessitated cognitive control. These findings provide a fine-grained description of the common and distinct neurocognitive mechanisms underlying unfairness to self and unfairness to others. Overall, this study not only validates the inequity aversion model but also provides direct evidence of neural mechanisms for neurobiological models of fairness.

The characteristics and reproducibility of motor speech functional neuroimaging in healthy controls

Introduction

Functional magnetic resonance imaging (fMRI) can improve our understanding of neural processes subserving motor speech function. Yet its reproducibility remains unclear. This study aimed to evaluate the reproducibility of fMRI using a word repetition task across two time points.

Methods

Imaging data from 14 healthy controls were analysed using a multi-level general linear model.

Results

Significant activation was observed during the task in the right hemispheric cerebellar lobules IV-V, right putamen, and bilateral sensorimotor cortices. Activation between timepoints was found to be moderately reproducible across time in the cerebellum but not in other brain regions.

Discussion

Preliminary findings highlight the involvement of the cerebellum and connected cerebral regions during a motor speech task. More work is needed to determine the degree of reproducibility of speech fMRI before this could be used as a reliable marker of changes in brain activity.

The Functional Neuroimaging of Autobiographical Memory for Happy Events: A Coordinate-Based Meta-Analysis

Neuroimaging studies using autobiographical recall methods investigated the neural correlates of happy autobiographical memories (AMs). The scope of the present activation likelihood estimation (ALE) meta-analysis was to quantitatively analyze neuroimaging studies of happy AMs conducted with autobiographical recall paradigms. A total of 17 studies (12 fMRI; 5 PET) on healthy individuals were included in this meta-analysis. During recall of happy life events, consistent activation foci were found in the frontal gyrus, the cingulate cortex, the basal ganglia, the parahippocampus/hippocampus, the hypothalamus, and the thalamus. The result of this quantitative coordinate-based ALE meta-analysis provides an objective view of brain responses associated with AM recollection of happy events, thus identifying brain areas consistently activated across studies. This extended brain network included frontal and limbic regions involved in remembering emotionally relevant positive events. The frontal gyrus and the cingulate cortex may be responsible for cognitive appraisal processes during recollection of happy AMs, while the subthalamic nucleus and globus pallidus may be involved in pleasure reactions associated with recollection of happy life events. These findings shed light on the neural network involved in recalling positive AMs in healthy individuals, opening further avenues for future research in clinical populations with mood disorders.

Spinal fMRI demonstrates segmental organisation of functionally connected networks in the cervical spinal cord: A test-retest reliability study

Resting functional magnetic resonance imaging (fMRI) studies have identified intrinsic spinal cord activity, which forms organised motor (ventral) and sensory (dorsal) resting-state networks. However, to facilitate the use of spinal fMRI in, for example, clinical studies, it is crucial to first assess the reliability of the method, particularly given the unique anatomical, physiological, and methodological challenges associated with acquiring the data. Here, we characterise functional connectivity relationships in the cervical cord and assess their between-session test-retest reliability in 23 young healthy volunteers. Resting-state networks were estimated in two ways (1) by estimating seed-to-voxel connectivity maps and (2) by calculating seed-to-seed correlations. Seed regions corresponded to the four grey matter horns (ventral/dorsal and left/right) of C5-C8 segmental levels. Test-retest reliability was assessed using the intraclass correlation coefficient. Spatial overlap of clusters derived from seed-to-voxel analysis between sessions was examined using Dice coefficients. Following seed-to-voxel analysis, we observed distinct unilateral dorsal and ventral organisation of cervical spinal resting-state networks that was largely confined in the rostro-caudal extent to each spinal segmental level, with more sparse connections observed between segments. Additionally, strongest correlations were observed between within-segment ipsilateral dorsal-ventral connections, followed by within-segment dorso-dorsal and ventro-ventral connections. Test-retest reliability of these networks was mixed. Reliability was poor when assessed on a voxelwise level, with more promising indications of reliability when examining the average signal within clusters. Reliability of correlation strength between seeds was highly variable, with the highest reliability achieved in ipsilateral dorsal-ventral and dorso-dorsal/ventro-ventral connectivity. However, the spatial overlap of networks between sessions was excellent. We demonstrate that while test-retest reliability of cervical spinal resting-state networks is mixed, their spatial extent is similar across sessions, suggesting that these networks are characterised by a consistent spatial representation over time.

Increased task-relevant fMRI responsiveness in comatose cardiac arrest patients is associated with improved neurologic outcomes

Early prediction of the recovery of consciousness in comatose cardiac arrest patients remains challenging. We prospectively studied task-relevant fMRI responses in 19 comatose cardiac arrest patients and five healthy controls to assess the fMRI's utility for neuroprognostication. Tasks involved instrumental music listening, forward and backward language listening, and motor imagery. Task-specific reference images were created from group-level fMRI responses from the healthy controls. Dice scores measured the overlap of individual subject-level fMRI responses with the reference images. Task-relevant responsiveness index (Rindex) was calculated as the maximum Dice score across the four tasks. Correlation analyses showed that increased Dice scores were significantly associated with arousal recovery (P < 0.05) and emergence from the minimally conscious state (EMCS) by one year (P < 0.001) for all tasks except motor imagery. Greater Rindex was significantly correlated with improved arousal recovery (P = 0.002) and consciousness (P = 0.001). For patients who survived to discharge (n = 6), the Rindex's sensitivity was 75% for predicting EMCS (n = 4). Task-based fMRI holds promise for detecting covert consciousness in comatose cardiac arrest patients, but further studies are needed to confirm these findings. Caution is necessary when interpreting the absence of task-relevant fMRI responses as a surrogate for inevitable poor neurological prognosis.

Anterior hippocampal dysfunction in early psychosis: a 2-year follow-up study

BACKGROUND

Cross-sectional studies indicate that hippocampal function is abnormal across stages of psychosis. Neural theories of psychosis pathophysiology suggest that dysfunction worsens with illness stage. Here, we test the hypothesis that hippocampal function is impaired in the early stage of psychosis and declines further over the next 2 years.

METHODS

We measured hippocampal function over 2 years using a scene processing task in 147 participants (76 individuals in the early stage of a non-affective psychotic disorder and 71 demographically similar healthy control individuals). Two-year follow-up was completed in 97 individuals (50 early psychosis, 47 healthy control). Voxelwise longitudinal analysis of activation in response to scenes was carried out within a hippocampal region of interest to test for group differences at baseline and a group by time interaction.

RESULTS

At baseline, we observed lower anterior hippocampal activation in the early psychosis group relative to the healthy control group. Contrary to our hypothesis, hippocampal activation remained consistent and did not show the predicted decline over 2 years in the early psychosis group. Healthy controls showed a modest reduction in hippocampal activation after 2 years.

CONCLUSIONS

The results of this study suggest that hippocampal dysfunction in early psychosis does not worsen over 2 years and highlight the need for longer-term longitudinal studies.

Test-retest reliability of fMRI during an emotion processing task: Investigating the impact of analytical approaches on ICC values

Test-retest reliability of fMRI is often assessed using the intraclass correlation coefficient (ICC), a numerical representation of reliability. Reports of low reliability at the individual level may be attributed to analytical approaches and inherent bias/error in the measures used to calculate ICC. It is unclear whether low reliability at the individual level is related to methodological decisions or if fMRI is inherently unreliable. The purpose of this study was to investigate methodological considerations when calculating ICC to improve understanding of fMRI reliability. fMRI data were collected from adolescent females (N=23) at pre- and post-cognitive behavioral therapy. Participants completed an emotion processing task during fMRI. We calculated ICC values using contrasts and β coefficients separately from voxelwise and network (ICA) analyses of the task-based fMRI data. For both voxelwise analysis and ICA, ICC values were higher when calculated using β coefficients. This work provides support for the use of β coefficients over contrasts when assessing reliability of fMRI, and the use of contrasts may underlie low reliability estimates reported in the existing literature. Continued research in this area is warranted to establish fMRI as a reliable measure to draw conclusions and utilize fMRI in clinical settings.

A New Perspective on Individual Reliability beyond Group Effect for Event-related Potentials: A Multisensory Investigation and Computational Modeling

The dominant approach in investigating the individual reliability for event-related potentials (ERPs) is to extract peak-related features at electrodes showing the strongest group effects. Such a peak-based approach implicitly assumes ERP components showing a stronger group effect are also more reliable, but this assumption has not been substantially validated and few studies have investigated the reliability of ERPs beyond peaks. In this study, we performed a rigorous evaluation of the test-retest reliability of ERPs collected in a multisensory and cognitive experiment from 82 healthy adolescents, each having two sessions. By comparing group effects and individual reliability, we found that a stronger group-level response in ERPs did not guarantee higher reliability. A perspective of neural oscillation should be adopted for the analysis of reliability. Further, by simulating ERPs with an oscillation-based computational model, we found that the consistency between group-level ERP responses and individual reliability was modulated by inter-subject latency jitter and inter-trial variability. The current findings suggest that the conventional peak-based approach may underestimate the individual reliability in ERPs and a neural oscillation perspective on ERP reliability should be considered. Hence, a comprehensive evaluation of the reliability of ERP measurements should be considered in individual-level neurophysiological trait evaluation and psychiatric disorder diagnosis.

Reliability of subsequent memory effects in children and adults: The good, the bad, and the hopeful

Functional MRI (fMRI) is a key tool for investigating neural underpinnings of cognitive development. Yet, in recent years, the reliability of fMRI effects has come into question and with it, the feasibility of using task-based fMRI to identify developmental changes related to cognition. Here, we investigated the reliability of task-based fMRI activations with a widely used subsequent memory paradigm using two developmental samples: a cross-sectional sample (n = 85, age 8-25 years) and a test-retest sample (n = 24, one-month follow up, age 8-20 years). In the large cross-sectional sample, we found good to excellent group-level reliability when assessing activation patterns related to the encoding task and subsequent memory effects. In the test-retest sample, while group-level reliability was excellent, the consistency of activation patterns within individuals was low, particularly for subsequent memory effects. We observed consistent activation patterns in frontal, parietal, and occipital cortices, but comparatively lower test-retest reliability in subcortical regions and the hippocampus. Together, these findings highlight the limitations of interpreting task-based fMRI effects and the importance of incorporating reliability analyses in developmental studies. Leveraging larger and densely collected longitudinal data may help contribute to increased reproducibility and the accumulation of knowledge in developmental sciences.

Test-Retest Reliability of Neural Correlates of Response Inhibition and Error Monitoring: An fMRI Study of a Stop-Signal Task

Response inhibition (RI) and error monitoring (EM) are important processes of adaptive goal-directed behavior, and neural correlates of these processes are being increasingly used as transdiagnostic biomarkers of risk for a range of neuropsychiatric disorders. Potential utility of these purported biomarkers relies on the assumption that individual differences in brain activation are reproducible over time; however, available data on test-retest reliability (TRR) of task-fMRI are very mixed. This study examined TRR of RI and EM-related activations using a stop signal task in young adults (n = 56, including 27 pairs of monozygotic (MZ) twins) in order to identify brain regions with high TRR and familial influences (as indicated by MZ twin correlations) and to examine factors potentially affecting reliability. We identified brain regions with good TRR of activations related to RI (inferior/middle frontal, superior parietal, and precentral gyri) and EM (insula, medial superior frontal and dorsolateral prefrontal cortex). No subcortical regions showed significant TRR. Regions with higher group-level activation showed higher TRR; increasing task duration improved TRR; within-session reliability was weakly related to the long-term TRR; motion negatively affected TRR, but this effect was abolished after the application of ICA-FIX, a data-driven noise removal method.

Reliability of single-subject neural activation patterns in speech production tasks

Speech neuroimaging research targeting individual speakers could help elucidate differences that may be crucial to understanding speech disorders. However, this research necessitates reliable brain activation across multiple speech production sessions. In the present study, we evaluated the reliability of speech-related brain activity measured by functional magnetic resonance imaging data from twenty neuro-typical subjects who participated in two experiments involving reading aloud simple speech stimuli. Using traditional methods like the Dice and intraclass correlation coefficients, we found that most individuals displayed moderate to high reliability. We also found that a novel machine-learning subject classifier could identify these individuals by their speech activation patterns with 97% accuracy from among a dataset of seventy-five subjects. These results suggest that single-subject speech research would yield valid results and that investigations into the reliability of speech activation in people with speech disorders are warranted.

Functional connectivity during smooth pursuit eye movements

Smooth pursuit eye movements (SPEM) hold the image of a slowly moving stimulus on the fovea. The neural system underlying SPEM primarily includes visual, parietal, and frontal areas. In the present study, we investigated how these areas are functionally coupled and how these couplings are influenced by target motion frequency. To this end, healthy participants (n = 57) were instructed to follow a sinusoidal target stimulus moving horizontally at two different frequencies (0.2 Hz, 0.4 Hz). Eye movements and blood oxygen level-dependent (BOLD) activity were recorded simultaneously. Functional connectivity of the key areas of the SPEM network was investigated with a psychophysiological interaction (PPI) approach. How activity in five eye movement-related seed regions (lateral geniculate nucleus, V1, V5, posterior parietal cortex, frontal eye fields) relates to activity in other parts of the brain during SPEM was analyzed. The behavioral results showed clear deterioration of SPEM performance at higher target frequency. BOLD activity during SPEM versus fixation occurred in a geniculo-occipito-parieto-frontal network, replicating previous findings. PPI analysis yielded widespread, partially overlapping networks. In particular, frontal eye fields and posterior parietal cortex showed task-dependent connectivity to large parts of the entire cortex, whereas other seed regions demonstrated more regionally focused connectivity. Higher target frequency was associated with stronger activations in visual areas but had no effect on functional connectivity. In summary, the results confirm and extend previous knowledge regarding the neural mechanisms underlying SPEM and provide a valuable basis for further investigations such as in patients with SPEM impairments and known alterations in brain connectivity.NEW & NOTEWORTHY This study provides a comprehensive investigation of blood oxygen level-dependent (BOLD) functional connectivity during smooth pursuit eye movements. Results from a large sample of healthy participants suggest that key oculomotor regions interact closely with each other but also with regions not primarily associated with eye movements. Understanding functional connectivity during smooth pursuit is important, given its potential role as an endophenotype of psychoses.

Neural signatures of prosocial behaviors

Prosocial behaviors are hypothesized to require socio-cognitive and empathic abilities-engaging brain regions attributed to the mentalizing and empathy brain networks. Here, we tested this hypothesis with a coordinate-based meta-analysis of 600 neuroimaging studies on prosociality, mentalizing and empathy (∼12,000 individuals). We showed that brain areas recruited by prosocial behaviors only partially overlap with the mentalizing (dorsal posterior cingulate cortex) and empathy networks (middle cingulate cortex). Additionally, the dorsolateral and ventromedial prefrontal cortices were preferentially activated by prosocial behaviors. Analyses on the functional connectivity profile and functional roles of the neural patterns underlying prosociality revealed that in addition to socio-cognitive and empathic processes, prosocial behaviors further involve evaluation processes and action planning, likely to select the action sequence that best satisfies another person's needs. By characterizing the multidimensional construct of prosociality at the neural level, we provide insights that may support a better understanding of normal and abnormal social cognition (e.g., psychopathy).

Estimating the prevalence of missing experiments in a neuroimaging meta-analysis

Coordinate-based meta-analyses (CBMA) allow researchers to combine the results from multiple functional magnetic resonance imaging experiments with the goal of obtaining results that are more likely to generalize. However, the interpretation of CBMA findings can be impaired by the file drawer problem, a type of publication bias that refers to experiments that are carried out but are not published. Using foci per contrast count data from the BrainMap database, we propose a zero-truncated modeling approach that allows us to estimate the prevalence of nonsignificant experiments. We validate our method with simulations and real coordinate data generated from the Human Connectome Project. Application of our method to the data from BrainMap provides evidence for the existence of a file drawer effect, with the rate of missing experiments estimated as at least 6 per 100 reported. The R code that we used is available at https://osf.io/ayhfv/.

Reliability of a functional magnetic resonance imaging task of emotional conflict in healthy participants

Task-based functional neuroimaging methods are increasingly being used to identify biomarkers of treatment response in psychiatric disorders. To facilitate meaningful interpretation of neural correlates of tasks and their potential changes with treatment over time, understanding the reliability of the blood-oxygen-level dependent (BOLD) signal of such tasks is essential. We assessed test-retest reliability of an emotional conflict task in healthy participants collected as part of the Canadian Biomarker Integration Network in Depression. Data for 36 participants, scanned at three time points (weeks 0, 2, and 8) were analyzed, and intra-class correlation coefficients (ICC) were used to quantify reliability. We observed moderate reliability (median ICC values between 0.5 and 0.6), within occipital, parietal, and temporal regions, specifically for conditions of lower cognitive complexity, that is, face, congruent or incongruent trials. For these conditions, activation was also observed within frontal and sub-cortical regions, however, their reliability was poor (median ICC < 0.2). Clinically relevant prognostic markers based on task-based fMRI require high predictive accuracy at an individual level. For this to be achieved, reliability of BOLD responses needs to be high. We have shown that reliability of the BOLD response to an emotional conflict task in healthy individuals is moderate. Implications of these findings to further inform studies of treatment effects and biomarker discovery are discussed.

Test-retest reliability of brain responses to risk-taking during the balloon analogue risk task

The Balloon Analogue Risk Task (BART) provides a reliable and ecologically valid model for the assessment of individual risk-taking propensity and is frequently used in neuroimaging and developmental research. Although the test-retest reliability of risk-taking behavior during the BART is well established, the reliability of brain activation patterns in response to risk-taking during the BART remains elusive. In this study, we used functional magnetic resonance imaging (fMRI) and evaluated the test-retest reliability of brain responses in 34 healthy adults during a modified BART by calculating the intraclass correlation coefficients (ICC) and Dice's similarity coefficients (DSC). Analyses revealed that risk-induced brain activation patterns showed good test-retest reliability (median ICC ​= ​0.62) and moderate to high spatial consistency, while brain activation patterns associated with win or loss outcomes only had poor to fair reliability (median ICC ​= ​0.33 for win and 0.42 for loss). These findings have important implications for future utility of the BART in fMRI to examine brain responses to risk-taking and decision-making.

Test-retest reliability of fMRI-measured brain activity during decision making under risk

Neural correlates of decision making under risk are being increasingly utilized as biomarkers of risk for substance abuse and other psychiatric disorders, treatment outcomes, and brain development. This research relies on the basic assumption that fMRI measures of decision making represent stable, trait-like individual differences. However, reliability needs to be established for each individual construct. Here we assessed long-term test-retest reliability (TRR) of regional brain activations related to decision making under risk using the Balloon Analogue Risk Taking task (BART) and identified regions with good TRRs and familial influences, an important prerequisite for the use of fMRI measures in genetic studies. A secondary goal was to examine the factors potentially affecting fMRI TRRs in one particular risk task, including the magnitude of neural activation, data analytical approaches, different methods of defining boundaries of a region, and participant motion. For the average BOLD response, reliabilities ranged across brain regions from poor to good (ICCs of 0 to 0.8, with a mean ICC of 0.17) and highest reliabilities were observed for parietal, occipital, and temporal regions. Among the regions that were of a priori theoretical importance due to their reported associations with decision making, the activation of left anterior insula and right caudate during the decision period showed the highest reliabilities (ICCs of 0.54 and 0.63, respectively). Among the regions with highest reliabilities, the right fusiform, right rostral anterior cingulate and left superior parietal regions also showed high familiality as indicated by intrapair monozygotic twin correlations (ranging from 0.66 to 0.69). Overall, regions identified by modeling the average BOLD response to a specific event type (rather than its modulation by a parametric regressor), regions including significantly activated vertices (compared to a whole parcel), and regions with greater magnitude of task-related activations showed greater reliabilities. Participant motion had a moderate negative effect on TRR. Regions activated during decision period rather than outcome period of risky decisions showed the greatest TRR and familiality. Regions with reliable activations can be utilized as neural markers of individual differences or endophenotypes in future clinical neuroscience and genetic studies of risk-taking.

Test-Retest Reliability of Functional Magnetic Resonance Imaging Activation for a Vergence Eye Movement Task

Vergence eye movements are the inward and outward rotation of the eyes responsible for binocular coordination. While studies have mapped and investigated the neural substrates of vergence, it is not well understood whether vergence eye movements evoke the blood oxygen level-dependent signal reliably in separate experimental visits. The test-retest reliability of stimulus-induced vergence eye movement tasks during a functional magnetic resonance imaging (fMRI) experiment is important for future randomized clinical trials (RCTs). In this study, we established region of interest (ROI) masks for the vergence neural circuit. Twenty-seven binocularly normal young adults participated in two functional imaging sessions measured on different days on the same 3T Siemens scanner. The fMRI experiments used a block design of sustained visual fixation and rest blocks interleaved between task blocks that stimulated eight or four vergence eye movements. The test-retest reliability of task-activation was assessed using the intraclass correlation coefficient (ICC), and that of spatial extent was assessed using the Dice coefficient. Functional activation during the vergence eye movement task of eight movements compared to rest was repeatable within the primary visual cortex (ICC = 0.8), parietal eye fields (ICC = 0.6), supplementary eye field (ICC = 0.5), frontal eye fields (ICC = 0.5), and oculomotor vermis (ICC = 0.6). The results demonstrate significant test-retest reliability in the ROIs of the vergence neural substrates for functional activation magnitude and spatial extent using the stimulus protocol of a task block stimulating eight vergence eye movements compared to sustained fixation. These ROIs can be used in future longitudinal RCTs to study patient populations with vergence dysfunctions.

Addressing the reliability fallacy in fMRI: Similar group effects may arise from unreliable individual effects

To cast valid predictions of future behavior or diagnose disorders, the reliable measurement of a "biomarker" such as the brain activation to prospective reward is a prerequisite. Surprisingly, only a small fraction of functional magnetic resonance imaging (fMRI) studies report or cite the reliability of brain activation maps involved in group analyses. Here, using simulations and exemplary longitudinal data of 126 healthy adolescents performing an intertemporal choice task, we demonstrate that reproducing a group activation map over time is not a sufficient indication of reliable measurements at the individual level. Instead, selecting regions based on significant main effects at the group level may yield estimates that fail to reliably capture individual variance in the subjective evaluation of an offer. Collectively, our results call for more attention on the reliability of supposed biomarkers at the level of the individual. Thus, caution is warranted in employing brain activation patterns prematurely for clinical applications such as diagnosis or tailored interventions before their reliability has been conclusively established by large-scale studies. To facilitate assessing and reporting of the reliability of fMRI contrasts in future studies, we provide a toolbox that incorporates common measures of global and local reliability.

Machine learning in major depression: From classification to treatment outcome prediction

AIMS

Major depression disorder (MDD) is the single greatest cause of disability and morbidity, and affects about 10% of the population worldwide. Currently, there are no clinically useful diagnostic biomarkers that are able to confirm a diagnosis of MDD from bipolar disorder (BD) in the early depressive episode. Therefore, exploring translational biomarkers of mood disorders based on machine learning is in pressing need, though it is challenging, but with great potential to improve our understanding of these disorders.

DISCUSSIONS

In this study, we review popular machine-learning methods used for brain imaging classification and predictions, and provide an overview of studies, specifically for MDD, that have used magnetic resonance imaging data to either (a) classify MDDs from controls or other mood disorders or (b) investigate treatment outcome predictors for individual patients. Finally, challenges, future directions, and potential limitations related to MDD biomarker identification are also discussed, with a goal of offering a comprehensive overview that may help readers to better understand the applications of neuroimaging data mining in depression.

CONCLUSIONS

We hope such efforts may highlight the need for an urgently needed paradigm shift in treatment, to guide personalized optimal clinical care.

Generative models for clinical applications in computational psychiatry

Despite the success of modern neuroimaging techniques in furthering our understanding of cognitive and pathophysiological processes, translation of these advances into clinically relevant tools has been virtually absent until now. Neuromodeling represents a powerful framework for overcoming this translational deadlock, and the development of computational models to solve clinical problems has become a major scientific goal over the last decade, as reflected by the emergence of clinically oriented neuromodeling fields like Computational Psychiatry, Computational Neurology, and Computational Psychosomatics. Generative models of brain physiology and connectivity in the human brain play a key role in this endeavor, striving for computational assays that can be applied to neuroimaging data from individual patients for differential diagnosis and treatment prediction. In this review, we focus on dynamic causal modeling (DCM) and its use for Computational Psychiatry. DCM is a widely used generative modeling framework for functional magnetic resonance imaging (fMRI) and magneto-/electroencephalography (M/EEG) data. This article reviews the basic concepts of DCM, revisits examples where it has proven valuable for addressing clinically relevant questions, and critically discusses methodological challenges and recent methodological advances. We conclude this review with a more general discussion of the promises and pitfalls of generative models in Computational Psychiatry and highlight the path that lies ahead of us. This article is categorized under: Neuroscience > Computation Neuroscience > Clinical Neuroscience.

The coordinate-based meta-analysis of neuroimaging data

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research.

Task and resting-state fMRI studies in first-episode schizophrenia: A systematic review

In the last two decades there has been an increase on task and resting-state functional Magnetic Resonance Imaging (fMRI) studies that explore the brain's functional changes in schizophrenia. However, it remains unclear as to whether the brain's functional changes during the resting state are sensitive to the same brain regions during task fMRI. Therefore, we conducted a systematic literature search of task and resting-state fMRI studies that investigated brain pathological changes in first-episode schizophrenia (Fleischhacker et al.). Nineteen studies met the inclusion criteria; seven were resting state fMRI studies with 371 FES patients and 363 healthy controls and twelve were task fMRI studies with 235 FES patients and 291 healthy controls. We found overlapping task and resting-state fMRI abnormalities in the prefrontal regions, including the dorsal lateral prefrontal cortex, the orbital frontal cortex and the temporal lobe, especially in the left superior temporal gyrus (STG). The findings of this systematic review support the frontotemporal hypothesis of schizophrenia, and the disruption in prefrontal and STG might represent the pathophysiology of schizophrenia disorder at a relatively early stage.

Speech perception in autism spectrum disorder: An activation likelihood estimation meta-analysis

Autism spectrum disorder (ASD) is often characterized by atypical language profiles and auditory and speech processing. These can contribute to aberrant language and social communication skills in ASD. The study of the neural basis of speech perception in ASD can serve as a potential neurobiological marker of ASD early on, but mixed results across studies renders it difficult to find a reliable neural characterization of speech processing in ASD. To this aim, the present study examined the functional neural basis of speech perception in ASD versus typical development (TD) using an activation likelihood estimation (ALE) meta-analysis of 18 qualifying studies. The present study included separate analyses for TD and ASD, which allowed us to examine patterns of within-group brain activation as well as both common and distinct patterns of brain activation across the ASD and TD groups. Overall, ASD and TD showed mostly common brain activation of speech processing in bilateral superior temporal gyrus (STG) and left inferior frontal gyrus (IFG). However, the results revealed trends for some distinct activation in the TD group showing additional activation in higher-order brain areas including left superior frontal gyrus (SFG), left medial frontal gyrus (MFG), and right IFG. These results provide a more reliable neural characterization of speech processing in ASD relative to previous single neuroimaging studies and motivate future work to investigate how these brain signatures relate to behavioral measures of speech processing in ASD.

Psychophysiological Interactions in a Visual Checkerboard Task: Reproducibility, Reliability, and the Effects of Deconvolution

Psychophysiological interaction (PPI) is a regression based method to study task modulated brain connectivity. Despite its popularity in functional MRI (fMRI) studies, its reliability and reproducibility have not been evaluated. We investigated reproducibility and reliability of PPI effects during a simple visual task, and examined the effect of deconvolution on the PPI results. A large open-access dataset was analyzed (n = 138), where a visual task was scanned twice with repetition times (TRs) of 645 and 1,400 ms, respectively. We first replicated our previous results by using the left and right middle occipital gyrus as seeds. Then regions of interest (ROI)-wise analysis was performed among 20 visual-related thalamic and cortical regions, and negative PPI effects were found between many ROIs with the posterior fusiform gyrus as a hub region. Both the seed-based and ROI-wise results were similar between the two runs and between the two PPI methods with and without deconvolution. The non-deconvolution method and the short TR run in general had larger effect sizes and greater extents. However, the deconvolution method performed worse in the 645 ms TR run than the 1,400 ms TR run in the voxel-wise analysis. Given the general similar results between the two methods and the uncertainty of deconvolution, we suggest that deconvolution may be not necessary for PPI analysis on block-designed data. Lastly, intraclass correlations (ICC) between the two runs were much lower for the PPI effects than the activation main effects, which raise cautions on performing inter-subject correlations and group comparisons on PPI effects.

A Resilient, Non-neuronal Source of the Spatiotemporal Lag Structure Detected by BOLD Signal-Based Blood Flow Tracking

Recent evidence has suggested that blood oxygenation level-dependent (BOLD) signals convey information about brain circulation via low frequency oscillation of systemic origin (sLFO) that travels through the vascular structure ("lag mapping"). Prompted by its promising application in both physiology and pathology, we examined this signal component using multiple approaches. A total of 30 healthy volunteers were recruited to perform two reproducibility experiments at 3 Tesla using multiband echo planar imaging. The first experiment investigated the effect of denoising and the second was designed to study the effect of subject behavior on lag mapping. The lag map's intersession test-retest reproducibility and image contrast were both diminished by removal of either the neuronal or the non-neuronal (e.g., cardiac, respiratory) components by independent component analysis-based denoising, suggesting that the neurovascular coupling also comprises a part of the BOLD lag structure. The lag maps were, at the same time, robust against local perfusion increases due to visuomotor task and global changes in perfusion induced by breath-holding at the same level as the intrasession reliability. The lag structure was preserved after time-locked averaging to the visuomotor task and breath-holding events, while any preceding signal changes were canceled out for the visuomotor task, consistent with the passive effect of neurovascular coupling in the venous side of the vasculature. These findings support the current assumption that lag mapping primarily reflects vascular structure despite the presence of sLFO perturbation of neuronal or non-neuronal origin and, thus, emphasize the vascular origin of the lag map, encouraging application of BOLD-based blood flow tracking.

Basic taste processing recruits bilateral anteroventral and middle dorsal insulae: An activation likelihood estimation meta-analysis of fMRI studies

BACKGROUND AND PURPOSE

Numerous task-based functional magnetic resonance imaging (fMRI) studies have reported the locations of basic taste representations in the human brain, but they usually employed a limited number of subjects (<20) with different methodologies and stimuli. Moreover, the reported brain regions were sometimes inconsistent. Thus, we aimed at performing a meta-analysis of the published data to identify locations consistently activated across studies, and performed a connectivity analysis to reveal how these taste processing regions connect with other brain regions.

MATERIALS AND METHODS

A meta-analysis was performed based on 34 experiments, with 238 total participants in 16 studies, to establish the activation likelihood estimation (ALE) of taste-mediated regional activation. Meta-analytic connectivity modeling (MACM) and data stored in BrainMap database were employed to reveal the functional connectivity of the regions identified by ALE with other brain regions, across all types of experiments that caused activation among healthy subjects.

RESULTS

ALE identified nine activated clusters in bilateral anteroventral and middle dorsal insulae, bilateral thalamus and caudate, bilateral pre-/postcentral gyrus, and right hippocampus. The concurrence between studies was moderate, with at best 38% of experiments contributed to the significant clusters activated by taste stimulation. Sweet taste was the predominant contributing taste. MACM revealed that at least 50% of the nine clusters coactivated with the middle cingulate cortex, medial frontal gyrus, inferior parietal lobule, and putamen.

CONCLUSION

Results suggested that fMRI studies have reported reproducible patterns of activations across studies. The basic taste stimulations resulted in activations in a mostly bilateral network. Moreover, they were connected with cognitive and emotional relevant brain regions.

Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms

Functional connectivity analysis has become a powerful tool for probing the human brain function and its breakdown in neuropsychiatry disorders. So far, most studies adopted resting-state paradigm to examine functional connectivity networks in the brain, thanks to its low demand and high tolerance that are essential for clinical studies. However, the test-retest reliability of resting-state connectivity measures is moderate, potentially due to its low behavioral constraint. On the other hand, naturalistic neuroimaging paradigms, an emerging approach for cognitive neuroscience with high ecological validity, could potentially improve the reliability of functional connectivity measures. To test this hypothesis, we characterized the test-retest reliability of functional connectivity measures during a natural viewing condition, and benchmarked it against resting-state connectivity measures acquired within the same functional magnetic resonance imaging (fMRI) session. We found that the reliability of connectivity and graph theoretical measures of brain networks is significantly improved during natural viewing conditions over resting-state conditions, with an average increase of almost 50% across various connectivity measures. Not only sensory networks for audio-visual processing become more reliable, higher order brain networks, such as default mode and attention networks, but also appear to show higher reliability during natural viewing. Our results support the use of natural viewing paradigms in estimating functional connectivity of brain networks, and have important implications for clinical application of fMRI. Hum Brain Mapp 38:2226-2241, 2017. © 2017 Wiley Periodicals, Inc.

Neural signatures of trust in reciprocity: A coordinate-based meta-analysis

Trust in reciprocity (TR) is defined as the risky decision to invest valued resources in another party with the hope of mutual benefit. Several fMRI studies have investigated the neural correlates of TR in one-shot and multiround versions of the investment game (IG). However, an overall characterization of the underlying neural networks remains elusive. Here, a coordinate-based meta-analysis was employed (activation likelihood estimation method, 30 articles) to investigate consistent brain activations in each of the IG stages (i.e., the trust, reciprocity and feedback stage). Results showed consistent activations in the anterior insula (AI) during trust decisions in the one-shot IG and decisions to reciprocate in the multiround IG, likely related to representations of aversive feelings. Moreover, decisions to reciprocate also consistently engaged the intraparietal sulcus, probably involved in evaluations of the reciprocity options. On the contrary, trust decisions in the multiround IG consistently activated the ventral striatum, likely associated with reward prediction error signals. Finally, the dorsal striatum was found consistently recruited during the feedback stage of the multiround IG, likely related to reinforcement learning. In conclusion, our results indicate different neural networks underlying trust, reciprocity, and feedback learning. These findings suggest that although decisions to trust and reciprocate may elicit aversive feelings likely evoked by the uncertainty about the decision outcomes and the pressing requirements of social standards, multiple interactions allow people to build interpersonal trust for cooperation via a learning mechanism by which they arguably learn to distinguish trustworthy from untrustworthy partners. Hum Brain Mapp 38:1233-1248, 2017. © 2016 Wiley Periodicals, Inc.

Neural Systems Underlying Emotional and Non-emotional Interference Processing: An ALE Meta-Analysis of Functional Neuroimaging Studies

Understanding how the nature of interference might influence the recruitments of the neural systems is considered as the key to understanding cognitive control. Although, interference processing in the emotional domain has recently attracted great interest, the question of whether there are separable neural patterns for emotional and non-emotional interference processing remains open. Here, we performed an activation likelihood estimation meta-analysis of 78 neuroimaging experiments, and examined common and distinct neural systems for emotional and non-emotional interference processing. We examined brain activation in three domains of interference processing: emotional verbal interference in the face-word conflict task, non-emotional verbal interference in the color-word Stroop task, and non-emotional spatial interference in the Simon, SRC and Flanker tasks. Our results show that the dorsal anterior cingulate cortex (ACC) was recruited for both emotional and non-emotional interference. In addition, the right anterior insula, presupplementary motor area (pre-SMA), and right inferior frontal gyrus (IFG) were activated by interference processing across both emotional and non-emotional domains. In light of these results, we propose that the anterior insular cortex may serve to integrate information from different dimensions and work together with the dorsal ACC to detect and monitor conflicts, whereas pre-SMA and right IFG may be recruited to inhibit inappropriate responses. In contrast, the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC) showed different degrees of activation and distinct lateralization patterns for different processing domains, which suggests that these regions may implement cognitive control based on the specific task requirements.

Subject-level reliability analysis of fast fMRI with application to epilepsy

PURPOSE

Recent studies have applied the new magnetic resonance encephalography (MREG) sequence to the study of interictal epileptic discharges (IEDs) in the electroencephalogram (EEG) of epileptic patients. However, there are no criteria to quantitatively evaluate different processing methods, to properly use the new sequence.

METHODS

We evaluated different processing steps of this new sequence under the common generalized linear model (GLM) framework by assessing the reliability of results. A bootstrap sampling technique was first used to generate multiple replicated data sets; a GLM with different processing steps was then applied to obtain activation maps, and the reliability of these maps was assessed.

RESULTS

We applied our analysis in an event-related GLM related to IEDs. A higher reliability was achieved by using a GLM with head motion confound regressor with 24 components rather than the usual 6, with an autoregressive model of order 5 and with a canonical hemodynamic response function (HRF) rather than variable latency or patient-specific HRFs. Comparison of activation with IED field also favored the canonical HRF, consistent with the reliability analysis.

CONCLUSION

The reliability analysis helps to optimize the processing methods for this fast fMRI sequence, in a context in which we do not know the ground truth of activation areas. Magn Reson Med 78:370-382, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Specificity, reliability and sensitivity of social brain responses during spontaneous mentalizing

The debilitating effects of social dysfunction in many psychiatric disorders prompt the need for systems-level biomarkers of social abilities that can be applied in clinical populations and longitudinal studies. A promising neuroimaging approach is the animated shapes paradigm based on so-called Frith-Happé animations (FHAs) which trigger spontaneous mentalizing with minimal cognitive demands. Here, we presented FHAs during functional magnetic resonance imaging to 46 subjects and examined the specificity and sensitivity of the elicited social brain responses. Test-retest reliability was additionally assessed in 28 subjects within a two-week interval. Specific responses to spontaneous mentalizing were observed in key areas of the social brain with high sensitivity and independently from the variant low-level kinematics of the FHAs. Mentalizing-specific responses were well replicable on the group level, suggesting good-to-excellent cross-sectional reliability [intraclass correlation coefficients (ICCs): 0.40-0.99; dice overlap at P_uncorr<0.001: 0.26-1.0]. Longitudinal reliability on the single-subject level was more heterogeneous (ICCs of 0.40-0.79; dice overlap at P_uncorr<0.001: 0.05-0.43). Posterior temporal sulcus activation was most reliable, including a robust differentiation between subjects across sessions (72% of voxels with ICC>0.40). These findings encourage the use of FHAs in neuroimaging research across developmental stages and psychiatric conditions, including the identification of biomarkers and pharmacological interventions.

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis.

Building a Science of Individual Differences from fMRI

To date, fMRI research has been concerned primarily with evincing generic principles of brain function through averaging data from multiple subjects. Given rapid developments in both hardware and analysis tools, the field is now poised to study fMRI-derived measures in individual subjects, and to relate these to psychological traits or genetic variations. We discuss issues of validity, reliability and statistical assessment that arise when the focus shifts to individual subjects and that are applicable also to other imaging modalities. We emphasize that individual assessment of neural function with fMRI presents specific challenges and necessitates careful consideration of anatomical and vascular between-subject variability as well as sources of within-subject variability.

Reproducibility of Resting State Connectivity in Patients with Stable Multiple Sclerosis

Given increasing efforts to use resting-state fMRI (rfMRI) as a biomarker of disease progression in multiple sclerosis (MS) we here explored the reproducibility of longitudinal rfMRI over three months in patients with clinically and radiologically stable MS. To pursue this aim, two approaches were applied in nine rfMRI networks: First, the intraclass correlation coefficient (ICC 3,1) was assessed for the mean functional connectivity maps across the entire network and a region of interest (ROI). Second, the ratio of overlap between Z-thresholded connectivity maps for each network was assessed. We quantified between-session functional reproducibility of rfMRI for 20 patients with stable MS and 14 healthy controls (HC). Nine rfMRI networks (RSNs) were examined at baseline and after 3 months of follow-up: three visual RSNs, the default-mode network, sensorimotor-, auditory-, executive control, and the left and right fronto-parietal RSN. ROI analyses were constrained to thresholded overlap masks for each individual (Z>0) at baseline and follow-up.In both stable MS and HC mean functional connectivity across the entire network did not reach acceptable ICCs for several networks (ICC<0.40) but we found a high reproducibility of ROI ICCs and of the ratio of overlap. ROI ICCs of all nine networks were between 0.98 and 0.99 for HC and ranged from 0.88 to 0.99 in patients with MS, respectively. The ratio of overlap for all networks was similar for both groups, ranging from 0.60 to 0.75.Our findings attest to a high reproducibility of rfMRI networks not only in HC but also in patients with stable MS when applying ROI analysis. This supports the utility of rfMRI to monitor functional changes related to disease progression or therapeutic interventions in MS.

Improving fMRI reliability in presurgical mapping for brain tumours

PURPOSE

Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps.

METHODS

Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel.

RESULTS

The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively).

CONCLUSIONS

We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping.

Test-retest reliability of fMRI experiments during robot-assisted active and passive stepping

BACKGROUND

Brain activity has been shown to undergo cortical and sub-cortical functional reorganisation over the course of gait rehabilitation in patients suffering from a spinal cord injury or a stroke. These changes however, have not been completely elucidated by neuroimaging to date, mainly due to the scarcity of long-term, follow-up investigations. The magnetic resonance imaging (MRI) compatible stepper MARCOS was specifically developed to enable the investigation of the supraspinal adaptations in paretic patients undergoing gait-rehabilitation in a controlled and repeatable manner. In view of future clinical research, the present study aims at examining the test-retest reliability of functional MRI (fMRI) experiments using MARCOS.

METHODS

The effect of repeated active and passive stepping movements on brain activity was investigated in 16 healthy participants from fMRI data collected in two separate imaging sessions six weeks apart. Root mean square errors (RMSE) were calculated for the metrics of motor performance. Regional overlap of brain activation between sessions, as well as an intra-class correlation coefficient (ICC) was computed from the single-subject and group activation maps for five regions of interest (ROI).

RESULTS

Data from eight participants had to be excluded due to excessive head motion. Reliability of motor performance was higher during passive than active movements, as seen in 4.5- to 13-fold lower RMSE for passive movements. In contrast, ICC ranged from 0.48 to 0.72 during passive movements and from 0.77 to 0.85 during active movements. Regional overlap of activations was also higher during active than during passive movements.

CONCLUSION

These findings imply that an increased variability of motor performance during active movements of healthy participants may be associated with a stable neuronal activation pattern across repeated measurements. In contrast, a stable motor performance during passive movements may be accompanied by a confined reliability of brain activation across repeated measurements.

Test-retest reliability of fMRI experiments during robot-assisted active and passive stepping

Background

Brain activity has been shown to undergo cortical and sub-cortical functional reorganisation over the course of gait rehabilitation in patients suffering from a spinal cord injury or a stroke. These changes however, have not been completely elucidated by neuroimaging to date, mainly due to the scarcity of long-term, follow-up investigations. The magnetic resonance imaging (MRI) compatible stepper MARCOS was specifically developed to enable the investigation of the supraspinal adaptations in paretic patients undergoing gait-rehabilitation in a controlled and repeatable manner. In view of future clinical research, the present study aims at examining the test-retest reliability of functional MRI (fMRI) experiments using MARCOS.

Methods

The effect of repeated active and passive stepping movements on brain activity was investigated in 16 healthy participants from fMRI data collected in two separate imaging sessions six weeks apart. Root mean square errors (RMSE) were calculated for the metrics of motor performance. Regional overlap of brain activation between sessions, as well as an intra-class correlation coefficient (ICC) was computed from the single-subject and group activation maps for five regions of interest (ROI).

Results

Data from eight participants had to be excluded due to excessive head motion. Reliability of motor performance was higher during passive than active movements, as seen in 4.5- to 13-fold lower RMSE for passive movements. In contrast, ICC ranged from 0.48 to 0.72 during passive movements and from 0.77 to 0.85 during active movements. Regional overlap of activations was also higher during active than during passive movements.

Conclusion

These findings imply that an increased variability of motor performance during active movements of healthy participants may be associated with a stable neuronal activation pattern across repeated measurements. In contrast, a stable motor performance during passive movements may be accompanied by a confined reliability of brain activation across repeated measurements.

Quantitative assessment of visual cortex function with fMRI at 7 Tesla-test-retest variability

fMRI-based retinotopic mapping was used to assess systematic variations in activated cortical surface area, amplitude, and coherence across sessions. Seven healthy subjects were scanned at 7 T in three separate sessions with intervals of 51.4 ± 5.4 days (Sessions 1 and 2) and 167.9 ± 24.4 days (Sessions 2 and 3). We found a reduction between Sessions 1 and 2 for activated cortical surface area, between Sessions 1 and 3 for amplitude, and between Sessions 1 and 2/3 for coherence. The results do not support head motion as a major cause of the observed effect seen in Session 1, suggesting that cognitive effects were the underlying cause of change. The phase correlations for both eccentricity and polar angle mapping were highly correlated between sessions, demonstrating the stability of the maps. Furthermore, the sensitivity in determining inter-session changes of cortical surface area, response amplitude, and coherence were, at a 5% significance level, estimated to be 1.5, 6, and 5%, respectively. Any future longitudinal fMRI study should carefully evaluate activation across sessions to determine the eligibility of inclusion of all time points. This experimental design provides guidance in methodological issues of clinical longitudinal fMRI-studies, specifically regarding effects of subject experience.

The Neurobiology and Psychology of Pedophilia: Recent Advances and Challenges

A pedophilic disorder is recognized for its impairment to the individual and for the harm it may cause to others. Pedophilia is often considered a side issue and research into the nature of pedophilia is delayed in comparison to research into other psychiatric disorders. However, with the increasing use of neuroimaging techniques, such as functional and structural magnetic resonance imaging (sMRI, fMRI), together with neuropsychological studies, we are increasing our knowledge of predisposing and accompanying factors contributing to pedophilia development. At the same time, we are faced with methodological challenges, such as group differences between studies, including age, intelligence, and comorbidities, together with a lack of careful assessment and control of child sexual abuse. Having this in mind, this review highlights the most important studies investigating pedophilia, with a strong emphasis on (neuro-) biological studies, combined with a brief explanation of research into normal human sexuality. We focus on some of the recent theories on the etiology of pedophilia such as the concept of a general neurodevelopmental disorder and/or alterations of structure and function in frontal, temporal, and limbic brain areas. With this approach, we aim to not only provide an update and overview but also a framework for future research and to address one of the most significant questions of how pedophilia may be explained by neurobiological and developmental alterations.

Bringing memory fMRI to the clinic: comparison of seven memory fMRI protocols in temporal lobe epilepsy

fMRI is increasingly implemented in the clinic to assess memory function. There are multiple approaches to memory fMRI, but limited data on advantages and reliability of different methods. Here, we compared effect size, activation lateralisation, and between‐sessions reliability of seven memory fMRI protocols: Hometown Walking (block design), Scene encoding (block design and event‐related design), Picture encoding (block and event‐related), and Word encoding (block and event‐related). All protocols were performed on three occasions in 16 patients with temporal lobe epilepsy (TLE). Group T‐maps showed activity bilaterally in medial temporal lobe for all protocols. Using ANOVA, there was an interaction between hemisphere and seizure‐onset lateralisation (P = 0.009) and between hemisphere, protocol and seizure‐onset lateralisation (P = 0.002), showing that the distribution of memory‐related activity between left and right temporal lobes differed between protocols and between patients with left‐onset and right‐onset seizures. Using voxelwise intraclass Correlation Coefficient, between‐sessions reliability was best for Hometown and Scenes (block and event). The between‐sessions spatial overlap of activated voxels was also greatest for Hometown and Scenes. Lateralisation of activity between hemispheres was most reliable for Scenes (block and event) and Words (event). Using receiver operating characteristic analysis to explore the ability of each fMRI protocol to classify patients as left‐onset or right‐onset TLE, only the Words (event) protocol achieved a significantly above‐chance classification of patients at all three sessions. We conclude that Words (event) protocol shows the best combination of between‐sessions reliability of the distribution of activity between hemispheres and reliable ability to distinguish between left‐onset and right‐onset patients. Hum Brain Mapp 36:1595–1608, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Cognitive deterioration and functional compensation in ALS measured with fMRI using an inhibitory task

Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of upper and lower motor neurons, resulting in progressive weakness and muscle atrophy. Recent studies suggest that nondemented ALS patients can show selective cognitive impairments, predominantly executive dysfunction, but little is known about the neural basis of these impairments. Oculomotor studies in ALS have described deficits in antisaccade execution, which requires the implementation of a task set that includes inhibition of automatic responses followed by generation of a voluntary action. It has been suggested that the dorsolateral prefrontal cortex (DLPFC) contributes in this process. Thus, we investigated whether deterioration of executive functions in ALS patients, such as the ability to implement flexible behavior during the antisaccade task, is related to DLPFC dysfunction. While undergoing an fMRI scan, 12 ALS patients and 12 age-matched controls performed an antisaccade task with concurrent eye tracking. We hypothesized that DLPFC deficits would appear during the antisaccade preparation stage, when the task set is being established. ALS patients made more antisaccade direction errors and showed significant reductions in DLPFC activation. In contrast, regions, such as supplementary eye fields and frontal eye fields, showed increased activation that was anticorrelated with the number of errors. The ALS group also showed reduced saccadic latencies that correlated with increased activation across the oculomotor saccade system. These findings suggest that ALS results in deficits in the inhibition of automatic responses that are related to impaired DLPFC activation. However, they also suggest that ALS patients undergo functional changes that partially compensate the neurological impairment.

A Study of Long-Term fMRI Reproducibility Using Data-Driven Analysis Methods

The reproducibility of functional magnetic resonance imaging (fMRI) is important for fMRI-based neuroscience research and clinical applications. Previous studies show considerable variation in amplitude and spatial extent of fMRI activation across repeated sessions on individual subjects even using identical experimental paradigms and imaging conditions. Most existing fMRI reproducibility studies were typically limited by time duration and data analysis techniques. Particularly, the assessment of reproducibility is complicated by a fact that fMRI results may depend on data analysis techniques used in reproducibility studies. In this work, the long-term fMRI reproducibility was investigated with a focus on the data analysis methods. Two spatial smoothing techniques, including a wavelet-domain Bayesian method and the Gaussian smoothing, were evaluated in terms of their effects on the long-term reproducibility. A multivariate support vector machine (SVM)-based method was used to identify active voxels, and compared to a widely used general linear model (GLM)-based method at the group level. The reproducibility study was performed using multisession fMRI data acquired from eight healthy adults over 1.5 years' period of time. Three regions-of-interest (ROI) related to a motor task were defined based upon which the long-term reproducibility were examined. Experimental results indicate that different spatial smoothing techniques may lead to different reproducibility measures, and the wavelet-based spatial smoothing and SVM-based activation detection is a good combination for reproducibility studies. On the basis of the ROIs and multiple numerical criteria, we observed a moderate to substantial within-subject long-term reproducibility. A reasonable long-term reproducibility was also observed from the inter-subject study. It was found that the short-term reproducibility is usually higher than the long-term reproducibility. Furthermore, the results indicate that brain regions with high contrast-to-noise ratio do not necessarily exhibit high reproducibility. These findings may provide supportive information for optimal design/implementation of fMRI studies and data interpretation.

Inter-hemispheric language functional reorganization in low-grade glioma patients after tumour surgery

Despite many claims of functional reorganization following tumour surgery, empirical studies that investigate changes in functional activation patterns are rare. This study investigates whether functional recovery following surgical treatment in patients with a low-grade glioma in the left hemisphere is linked to inter-hemispheric reorganization. Based on literature, we hypothesized that reorganization would induce changes in the spatial pattern of activation specifically in tumour homologue brain areas in the healthy right hemisphere. An experimental group (EG) of 14 patients with a glioma in the left hemisphere near language related brain areas, and a control group of 6 patients with a glioma in the right, non-language dominant hemisphere were scanned before and after resection. In addition, an age and gender matched second control group of 18 healthy volunteers was scanned twice. A verb generation task was used to map language related areas and a novel technique was used for data analysis. Contrary to our hypothesis, we found that functional recovery following surgery of low-grade gliomas cannot be linked to functional reorganization in language homologue brain areas in the healthy, right hemisphere. Although elevated changes in the activation pattern were found in patients after surgery, these were largest in brain areas in proximity to the surgical resection, and were very similar to the spatial pattern of the brain shift following surgery. This suggests that the apparent perilesional functional reorganization is mostly caused by the brain shift as a consequence of surgery. Perilesional functional reorganization can however not be excluded. The study suggests that language recovery after transient post-surgical language deficits involves recovery of functioning of the presurgical language system.

Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease

BACKGROUND

Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients.

METHOD

Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity.

RESULTS

Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition.

CONCLUSIONS

This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

fMRI reliability: influences of task and experimental design

As scientists, it is imperative that we understand not only the power of our research tools to yield results, but also their ability to obtain similar results over time. This study is an investigation into how common decisions made during the design and analysis of a functional magnetic resonance imaging (fMRI) study can influence the reliability of the statistical results. To that end, we gathered back-to-back test-retest fMRI data during an experiment involving multiple cognitive tasks (episodic recognition and two-back working memory) and multiple fMRI experimental designs (block, event-related genetic sequence, and event-related m-sequence). Using these data, we were able to investigate the relative influences of task, design, statistical contrast (task vs. rest, target vs. nontarget), and statistical thresholding (unthresholded, thresholded) on fMRI reliability, as measured by the intraclass correlation (ICC) coefficient. We also utilized data from a second study to investigate test-retest reliability after an extended, six-month interval. We found that all of the factors above were statistically significant, but that they had varying levels of influence on the observed ICC values. We also found that these factors could interact, increasing or decreasing the relative reliability of certain Task × Design combinations. The results suggest that fMRI reliability is a complex construct whose value may be increased or decreased by specific combinations of factors.