Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation

The Right Dorsal Premotor Mosaic: Organization, Functions, and Connectivity

The right dorsal premotor cortex (PMd) of humans has been reported to be involved in a broad range of motor and cognitive functions. We explored the basis of this behavioral heterogeneity by performing a connectivity-based parcellation using meta-analytic approach applied to PMd coactivations. We compared our connectivity-based parcellation results with parcellations obtained through resting-state functional connectivity and probabilistic diffusion tractography. Functional connectivity profiles and behavioral decoding of the resulting PMd subregions allowed characterizing their respective behavior profile. These procedures divided the right PMd into 5 distinct subregions that formed a cognitive-motor gradient along a rostro-caudal axis. In particular, we found 1) a rostral subregion functionally connected with prefrontal cortex, which likely supports high-level cognitive processes, such as working memory, 2) a central subregion showing a mixed behavioral profile and functional connectivity to parietal regions of the dorsal attention network, and 3) a caudal subregion closely integrated with the motor system. Additionally, we found 4) a dorsal subregion, preferentially related to hand movements and connected to both cognitive and motor regions, and 5) a ventral subregion, whose functional profile fits the concept of an eye movement-related field. In conclusion, right PMd may be considered as a functional mosaic formed by 5 subregions.

Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex

The macro-connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity-driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity-driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting-state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject-level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously.

Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis

Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Studies using resting-state functional magnetic resonance imaging (fMRI) to investigate underlying pathophysiology of motor and non-motor symptoms in PD yielded largely inconsistent results. This quantitative neuroimaging meta-analysis aims to identify consistent abnormal intrinsic functional patterns in PD across studies. We used PubMed to retrieve suitable resting-state studies and stereotactic data were extracted from 28 individual between-group comparisons. Convergence across their findings was tested using the activation likelihood estimation (ALE) approach. We found convergent evidence for intrinsic functional disturbances in bilateral inferior parietal lobule (IPL) and the supramarginal gyrus in PD patients compared to healthy subjects. In follow-up task-based and task-independent functional connectivity (FC) analyses using two independent healthy subject data sets, we found that the regions showing convergent aberrations in PD formed an interconnected network mainly with the default mode network (DMN). Behavioral characterization of these regions using the BrainMap database suggested associated dysfunction of perception and executive processes. Taken together, our findings highlight the role of parietal cortex in the pathophysiology of PD.

Informing the Structure of Executive Function in Children: A Meta-Analysis of Functional Neuroimaging Data

The structure of executive function (EF) has been the focus of much debate for decades. What is more, the complexity and diversity provided by the developmental period only adds to this contention. The development of executive function plays an integral part in the expression of children's behavioral, cognitive, social, and emotional capabilities. Understanding how these processes are constructed during development allows for effective measurement of EF in this population. This meta-analysis aims to contribute to a better understanding of the structure of executive function in children. A coordinate-based meta-analysis was conducted (using BrainMap GingerALE 2.3), which incorporated studies administering functional magnetic resonance imaging (fMRI) during inhibition, switching, and working memory updating tasks in typical children (aged 6-18 years). The neural activation common across all executive tasks was compared to that shared by tasks pertaining only to inhibition, switching or updating, which are commonly considered to be fundamental executive processes. Results support the existence of partially separable but partially overlapping inhibition, switching, and updating executive processes at a neural level, in children over 6 years. Further, the shared neural activation across all tasks (associated with a proposed "unitary" component of executive function) overlapped to different degrees with the activation associated with each individual executive process. These findings provide evidence to support the suggestion that one of the most influential structural models of executive functioning in adults can also be applied to children of this age. However, the findings also call for careful consideration and measurement of both specific executive processes, and unitary executive function in this population. Furthermore, a need is highlighted for a new systematic developmental model, which captures the integrative nature of executive function in children.

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.

Heterogeneous fractionation profiles of meta-analytic coactivation networks

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication.

The heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization

Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the PMd. A previous study revealed that the right PMd is characterized by a rostro-caudal and a ventro-dorsal distinction dividing it into five subregions: rostral, central, caudal, ventral and dorsal. The present study assessed whether a similar organization is present in the left hemisphere, by capitalizing on a multimodal data-driven approach combining connectivity-based parcellation (CBP) based on meta-analytic modeling, resting-state functional connectivity, and probabilistic diffusion tractography. The resulting PMd modules were then characterized based on multimodal functional connectivity and a quantitative analysis of associated behavioral functions. Analyzing the clusters consistent across all modalities revealed an organization of the left PMd that mirrored its right counterpart to a large degree. Again, caudal, central and rostral modules reflected a cognitive-motor gradient and a premotor eye-field was found in the ventral part of the left PMd. In addition, a distinct module linked to abstract cognitive functions was observed in the rostro-ventral left PMd across all CBP modalities, implying greater differentiation of higher cognitive functions for the left than the right PMd.

Toward understanding the impact of trauma on the early developing human brain

Traumatic experiences early in life predispose animals and humans to later cognitive-behavioral, emotional, and somatic problems. In humans, traumatic experiences are strong predictors of psychiatric illness. A growing body of research has emphasized alterations in neurological structure and function that underscore phenotypic changes following trauma. However, results are mixed and imprecise. We argue that future translation of neurological findings to clinical practice will require: (1) discovery of neurobehavioral associations within a longitudinal context, (2) dissociation of trauma types and of trauma versus chronic stress, and (3) better localization of neural sequelae considerate of the fine resolution of neural circuitry. We provide a brief overview of early brain development and highlight the role of longitudinal research in unearthing brain-behavior relations in youth. We relay an emergent framework in which dissociable trauma types are hypothesized to impact distinct, rationally informed neural systems. In line with this, we discuss the long-standing challenge of separating effects of chronic stress and trauma, as these are often intertwined. We bring to light inconsistencies in localization of neural correlates of trauma, emphasizing results in medial prefrontal regions. We assert that more precise spatial brain localization will help to advance prevailing models of trauma pathways and inform future research.

Dopamine Modulates the Functional Organization of the Orbitofrontal Cortex

Neuromodulators such as dopamine can alter the intrinsic firing properties of neurons and may thereby change the configuration of larger functional circuits. The primate orbitofrontal cortex (OFC) receives dopaminergic input from midbrain nuclei, but the role of dopamine in the OFC is still unclear. Here we tested the idea that dopaminergic activity changes the pattern of connectivity between the OFC and the rest of the brain and thereby reconfigures functional networks in the OFC. To this end, we combined double-blind, placebo-controlled pharmacology [D₂ receptor (D2R) antagonist amisulpride] in humans with resting-state functional magnetic resonance imaging and clustering methods. In the placebo group, we replicated previously observed parcellations of the OFC into two and six subregions based on connectivity patterns with the rest of the brain. Most importantly, while the twofold clustering did not differ significantly between groups, blocking D2Rs significantly changed the composition of the sixfold parcellation, suggesting a dopamine-dependent reconfiguration of functional OFC subregions. Moreover, multivariate decoding analyses revealed that amisulpride changed the whole-brain connectivity patterns of individual OFC subregions. In particular, D2R blockade shifted the balance of OFC connectivity from associative areas in the temporal and parietal lobe toward functional connectivity with the frontal cortex. In summary, our results suggest that dopamine alters the composition of functional OFC circuits, possibly indicating a broader role for neuromodulators in the dynamic reconfiguration of functional brain networks.SIGNIFICANCE STATEMENT A key role of any neuromodulator may be the reconfiguration of functional brain circuits. Here we test this idea with regard to dopamine and the organization of functional networks in the orbitofrontal cortex (OFC). We show that blockade of dopamine D₂ receptors has profound effects on the functional connectivity patterns of the OFC, yielding altered connectivity-based subdivisions of this region. Our results suggest that dopamine changes the connectional configuration of the OFC, possibly leading to transitions between different operating modes that favor either sensory input or recurrent processing in the prefrontal cortex. More generally, our findings support a broader role for neuromodulators in the dynamic reconfiguration of functional brain networks and may have clinical implications for understanding the actions of antipsychotic agents.

Correspondent Functional Topography of the Human Left Inferior Parietal Lobule at Rest and Under Task Revealed Using Resting-State fMRI and Coactivation Based Parcellation

The human left inferior parietal lobule (LIPL) plays a pivotal role in many cognitive functions and is an important node in the default mode network (DMN). Although many previous studies have proposed different parcellation schemes for the LIPL, the detailed functional organization of the LIPL and the exact correspondence between the DMN and LIPL subregions remain unclear. Mounting evidence indicates that spontaneous fluctuations in the brain are strongly associated with cognitive performance at the behavioral level. However, whether a consistent functional topographic organization of the LIPL during rest and under task can be revealed remains unknown. Here, they used resting-state functional connectivity (RSFC) and task-related coactivation patterns separately to parcellate the LIPL and identified seven subregions. Four subregions were located in the supramarginal gyrus (SMG) and three subregions were located in the angular gyrus (AG). The subregion-specific networks and functional characterization revealed that the four anterior subregions were found to be primarily involved in sensorimotor processing, movement imagination and inhibitory control, audition perception and speech processing, and social cognition, whereas the three posterior subregions were mainly involved in episodic memory, semantic processing, and spatial cognition. The results revealed a detailed functional organization of the LIPL and suggested that the LIPL is a functionally heterogeneous area. In addition, the present study demonstrated that the functional architecture of the LIPL during rest corresponds with that found in task processing. Hum Brain Mapp 38:1659-1675, 2017. © 2017 Wiley Periodicals, Inc.

The hearing ear is always found close to the speaking tongue: Review of the role of the motor system in speech perception

Does "the motor system" play "a role" in speech perception? If so, where, how, and when? We conducted a systematic review that addresses these questions using both qualitative and quantitative methods. The qualitative review of behavioural, computational modelling, non-human animal, brain damage/disorder, electrical stimulation/recording, and neuroimaging research suggests that distributed brain regions involved in producing speech play specific, dynamic, and contextually determined roles in speech perception. The quantitative review employed region and network based neuroimaging meta-analyses and a novel text mining method to describe relative contributions of nodes in distributed brain networks. Supporting the qualitative review, results show a specific functional correspondence between regions involved in non-linguistic movement of the articulators, covertly and overtly producing speech, and the perception of both nonword and word sounds. This distributed set of cortical and subcortical speech production regions are ubiquitously active and form multiple networks whose topologies dynamically change with listening context. Results are inconsistent with motor and acoustic only models of speech perception and classical and contemporary dual-stream models of the organization of language and the brain. Instead, results are more consistent with complex network models in which multiple speech production related networks and subnetworks dynamically self-organize to constrain interpretation of indeterminant acoustic patterns as listening context requires.

Brain regions that show repetition suppression and enhancement: A meta-analysis of 137 neuroimaging experiments

Repetition suppression and enhancement refer to the reduction and increase in the neural responses for repeated rather than novel stimuli, respectively. This study provides a meta-analysis of the effects of repetition suppression and enhancement, restricting the data used to that involving fMRI/PET, visual stimulus presentation, and healthy participants. The major findings were as follows. First, the global topography of the repetition suppression effects was strikingly similar to that of the "subsequent memory" effects, indicating that the mechanism for repetition suppression is the reduced engagement of an encoding system. The lateral frontal cortex effects involved the frontoparietal control network regions anteriorly and the dorsal attention network regions posteriorly. The left fusiform cortex effects predominantly involved the dorsal attention network regions, whereas the right fusiform cortex effects mainly involved the visual network regions. Second, the category-specific meta-analyses and their comparisons indicated that most parts of the alleged category-specific regions showed repetition suppression for more than one stimulus category. In this regard, these regions may not be "dedicated cortical modules," but are more likely parts of multiple overlapping large-scale maps of simple features. Finally, the global topography of the repetition enhancement effects was similar to that of the "retrieval success" effects, suggesting that the mechanism for repetition enhancement is voluntary or involuntary explicit retrieval during an implicit memory task. Taken together, these results clarify the network affiliations of the regions showing reliable repetition suppression and enhancement effects and contribute to the theoretical interpretations of the local and global topography of these two effects. Hum Brain Mapp 38:1894-1913, 2017. © 2017 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.

You say 'prefrontal cortex' and I say 'anterior cingulate': meta-analysis of spatial overlap in amygdala-to-prefrontal connectivity and internalizing symptomology

Connections between the amygdala and medial prefrontal cortex (mPFC) are considered critical for the expression and regulation of emotional behavior. Abnormalities in frontoamygdala circuitry are reported across several internalizing conditions and associated risk factors (for example, childhood trauma), which may underlie the strong phenotypic overlap and co-occurrence of internalizing conditions. However, it is unclear if these findings converge on the same localized areas of mPFC or adjacent anterior cingulate cortex (ACC). Examining 46 resting-state functional connectivity magnetic resonance imaging studies of internalizing conditions or risk factors (for example, early adversity and family history), we conducted an activation likelihood estimation meta-analysis of frontoamygdala circuitry. We included all reported amygdala to frontal coordinate locations that fell within a liberal anatomically defined frontal mask. Peak effects across studies were centered in two focal subareas of the ACC: pregenual (pgACC) and subgenual (sgACC). Using publicly available maps and databases of healthy individuals, we found that observed subareas have unique connectivity profiles, patterns of neural co-activation across a range of neuropsychological tasks, and distribution of tasks spanning various behavioral domains within peak regions, also known as 'functional fingerprints'. These results suggest disruptions in unique amygdala-ACC subcircuits across internalizing, genetic and environmental risk studies. Based on functional characterizations and the studies contributing to each peak, observed amygdala-ACC subcircuits may reflect separate transdiagnostic neural signatures. In particular, they may reflect common neurobiological substrates involved in developmental risk (sgACC), or the broad expression of emotional psychopathology (pgACC) across disease boundaries.

Common and distinct brain regions in both parietal and frontal cortex support symbolic and nonsymbolic number processing in humans: A functional neuroimaging meta-analysis

In recent years, there has been substantial growth in neuroimaging studies investigating neural correlates of symbolic (e.g. Arabic numerals) and non-symbolic (e.g. dot arrays) number processing. At present it remains contested whether number is represented abstractly, or if number representations in the brain are format-dependent. In order to quantitatively evaluate the available neuroimaging evidence, we used activation likelihood estimation (ALE) to conduct quantitative meta-analyses of the results reported in 57 neuroimaging papers. Consistent with the existence of an abstract representation of number in the brain, conjunction analyses revealed overlapping activation for symbolic and nonsymbolic numbers in frontal and parietal lobes. Consistent with the notion of format-dependent activation, contrast analyses demonstrated anatomically distinct fronto-parietal activation for symbolic and non-symbolic processing. Therefore, symbolic and non-symbolic numbers are subserved by format-dependent and abstract neural systems. Moreover, the present results suggest that regions across the parietal cortex, not just the intraparietal sulcus, are engaged in both symbolic and non-symbolic number processing, challenging the notion that the intraparietal sulcus is the key region for number processing. Additionally, our analyses indicate that regions in the frontal cortex subserve magnitude representations rather than non-numerical cognitive processes associated with number tasks, thereby highlighting the importance of considering both frontal and parietal regions as important for number processing.

An Activation Likelihood Estimation Meta-Analysis Study of Simple Motor Movements in Older and Young Adults

The functional neuroanatomy of finger movements has been characterized with neuroimaging in young adults. However, less is known about the aging motor system. Several studies have contrasted movement-related activity in older versus young adults, but there is inconsistency among their findings. To address this, we conducted an activation likelihood estimation (ALE) meta-analysis on within-group data from older adults and young adults performing regularly paced right-hand finger movement tasks in response to external stimuli. We hypothesized that older adults would show a greater likelihood of activation in right cortical motor areas (i.e., ipsilateral to the side of movement) compared to young adults. ALE maps were examined for conjunction and between-group differences. Older adults showed overlapping likelihoods of activation with young adults in left primary sensorimotor cortex (SM1), bilateral supplementary motor area, bilateral insula, left thalamus, and right anterior cerebellum. Their ALE map differed from that of the young adults in right SM1 (extending into dorsal premotor cortex), right supramarginal gyrus, medial premotor cortex, and right posterior cerebellum. The finding that older adults uniquely use ipsilateral regions for right-hand finger movements and show age-dependent modulations in regions recruited by both age groups provides a foundation by which to understand age-related motor decline and motor disorders.

The neural basis of sex differences in sexual behavior: A quantitative meta-analysis

Sexuality as to its etymology presupposes the duality of sexes. Using quantitative neuroimaging meta-analyses, we demonstrate robust sex differences in the neural processing of sexual stimuli in thalamus, hypothalamus, and basal ganglia. In a narrative review, we show how these relate to the well-established sex differences on the behavioral level. More specifically, we describe the neural bases of known poor agreement between self-reported and genital measures of female sexual arousal, of previously proposed male proneness to affective sexual conditioning, as well as hints of unconscious activation of bonding mechanisms during sexual stimulation in women. In summary, our meta-analytic review demonstrates that neurofunctional sex differences during sexual stimulation can account for well-established sex differences in sexual behavior.

Left inferior parietal lobe engagement in social cognition and language

Social cognition and language are two core features of the human species. Despite distributed recruitment of brain regions in each mental capacity, the left parietal lobe (LPL) represents a zone of topographical convergence. The present study quantitatively summarizes hundreds of neuroimaging studies on social cognition and language. Using connectivity-based parcellation on a meta-analytically defined volume of interest (VOI), regional coactivation patterns within this VOI allowed identifying distinct subregions. Across parcellation solutions, two clusters emerged consistently in rostro-ventral and caudo-ventral aspects of the parietal VOI. Both clusters were functionally significantly associated with social-cognitive and language processing. In particular, the rostro-ventral cluster was associated with lower-level processing facets, while the caudo-ventral cluster was associated with higher-level processing facets in both mental capacities. Contrarily, in the (less stable) dorsal parietal VOI, all clusters reflected computation of general-purpose processes, such as working memory and matching tasks, that are frequently co-recruited by social or language processes. Our results hence favour a rostro-caudal distinction of lower- versus higher-level processes underlying social cognition and language in the left inferior parietal lobe.

Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps

Resting-state functional connectivity analysis has become a widely used method for the investigation of human brain connectivity and pathology. The measurement of neuronal activity by functional MRI, however, is impeded by various nuisance signals that reduce the stability of functional connectivity. Several methods exist to address this predicament, but little consensus has yet been reached on the most appropriate approach. Given the crucial importance of reliability for the development of clinical applications, we here investigated the effect of various confound removal approaches on the test-retest reliability of functional-connectivity estimates in two previously defined functional brain networks. Our results showed that gray matter masking improved the reliability of connectivity estimates, whereas denoising based on principal components analysis reduced it. We additionally observed that refraining from using any correction for global signals provided the best test-retest reliability, but failed to reproduce anti-correlations between what have been previously described as antagonistic networks. This suggests that improved reliability can come at the expense of potentially poorer biological validity. Consistent with this, we observed that reliability was proportional to the retained variance, which presumably included structured noise, such as reliable nuisance signals (for instance, noise induced by cardiac processes). We conclude that compromises are necessary between maximizing test-retest reliability and removing variance that may be attributable to non-neuronal sources.

Implementation errors in the GingerALE Software: Description and recommendations

Neuroscience imaging is a burgeoning, highly sophisticated field the growth of which has been fostered by grant-funded, freely distributed software libraries that perform voxel-wise analyses in anatomically standardized three-dimensional space on multi-subject, whole-brain, primary datasets. Despite the ongoing advances made using these non-commercial computational tools, the replicability of individual studies is an acknowledged limitation. Coordinate-based meta-analysis offers a practical solution to this limitation and, consequently, plays an important role in filtering and consolidating the enormous corpus of functional and structural neuroimaging results reported in the peer-reviewed literature. In both primary data and meta-analytic neuroimaging analyses, correction for multiple comparisons is a complex but critical step for ensuring statistical rigor. Reports of errors in multiple-comparison corrections in primary-data analyses have recently appeared. Here, we report two such errors in GingerALE, a widely used, US National Institutes of Health (NIH)-funded, freely distributed software package for coordinate-based meta-analysis. These errors have given rise to published reports with more liberal statistical inferences than were specified by the authors. The intent of this technical report is threefold. First, we inform authors who used GingerALE of these errors so that they can take appropriate actions including re-analyses and corrective publications. Second, we seek to exemplify and promote an open approach to error management. Third, we discuss the implications of these and similar errors in a scientific environment dependent on third-party software. Hum Brain Mapp 38:7-11, 2017. © 2016 Wiley Periodicals, Inc.

L1 and L2 processing in the bilingual brain: A meta-analysis of neuroimaging studies

Neuroimaging studies investigating bilingual processes have produced controversial results in determining similarities versus differences between L1 and L2 neural networks. The current meta-analytic study was conducted to examine what factors play a role in the similarities and differences between L1 and L2 networks with a focus on age of acquisition (AOA) and whether the orthographic transparency of L2 is more or less transparent than that of L1. Using activation likelihood estimation (ALE), we found L2 processing involved more additional regions than L1 for late bilinguals in comparison to early bilinguals, suggesting L2 processing is more demanding in late bilinguals. We also provide direct evidence that AOA of L2 influences L1 processing through the findings that early bilinguals had greater activation in the left fusiform gyrus than late bilinguals during L1 processing even when L1 languages were the same in the two groups, presumably due to greater co-activation of orthography in L1 and L2 in early bilinguals. In addition, we found that the same L2 languages evoked different brain activation patterns depending on whether it was more or less transparent than L1 in orthographic transparency. The bilateral auditory cortex and right precentral gyrus were more involved in shallower-than-L1 L2s, suggesting a "sound-out" strategy for a more regular language by involving the phonological regions and sensorimotor regions to a greater degree. In contrast, the left frontal cortex was more involved in the processing of deeper-than-L1 L2s, presumably due to the increased arbitrariness of mapping between orthography and phonology in L2.

The neural mechanisms of hallucinations: A quantitative meta-analysis of neuroimaging studies

Activation likelihood estimation meta-analysis of functional neuroimaging data was used to investigate the neural mechanisms underlying auditory-verbal and visual hallucinations (AVHs and VHs). Consistent activation across studies during AVHs, but not VHs, in Wernicke's and Broca's areas is consistent with involvement of speech and language processes in the experience of hearing voices when none are present. Similarly, greater activity in auditory cortex during AVHs and in visual cortex during VHs supports models proposing over-stimulation of sensory cortices in the generation of these perceptual anomalies. Activation across studies in the medial temporal lobe highlights a role for memory intrusions in the provision of content for AVHs, whereas insula activation may relate to the involvement of awareness and self-representation. Finally, activation in the paracingulate region of medial prefrontal cortex during AVHs is consistent with models implicating reality monitoring impairment in the misattribution of self-generated information as externally perceived. In the light of the results, the need for unified theoretical frameworks that account for the full range of hallucinatory experiences is discussed.

Functional topography of the right inferior parietal lobule structured by anatomical connectivity profiles

The nature of the relationship between structure and function is a fundamental question in neuroscience, especially at the macroscopic neuroimaging level. Although mounting studies have revealed that functional connectivity reflects structural connectivity, whether similar structural and functional connectivity patterns can reveal corresponding similarities in the structural and functional topography remains an open problem. In our current study, we used the right inferior parietal lobule (RIPL), which has been demonstrated to have similar anatomical and functional connectivity patterns at the subregional level, to directly test the hypothesis that similar structural and functional connectivity patterns can inform the corresponding topography of this area. In addition, since the association between the RIPL regions and particular functions and networks is still largely unknown, post-hoc functional characterizations and connectivity analyses were performed to identify the main functions and cortical networks in which each subregion participated. Anatomical and functional connectivity-based parcellations of the RIPL have consistently identified five subregions. Our functional characterization using meta-analysis-based behavioral and connectivity analyses revealed that the two anterior subregions (Cl1 and Cl2) primarily participate in interoception and execution, respectively; whereas the posterior subregion (Cl3) in the SMG primarily participates in attention and action inhibition. The two posterior subregions (Cl4, Cl5) in the AG were primarily involved in social cognition and spatial cognition, respectively. These results indicated that similar anatomical and functional connectivity patterns of the RIPL are reflected in corresponding structural and functional topographies. The identified cortical connectivity and functional characterization of each subregion may facilitate RIPL-related clinical research. Hum Brain Mapp 37:4316-4332, 2016. © 2016 Wiley Periodicals, Inc.

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.

Effects of cue focality on the neural mechanisms of prospective memory: A meta-analysis of neuroimaging studies

Remembering to execute pre-defined intentions at the appropriate time in the future is typically referred to as Prospective Memory (PM). Studies of PM showed that distinct cognitive processes underlie the execution of delayed intentions depending on whether the cue associated with such intentions is focal to ongoing activity processing or not (i.e., cue focality). The present activation likelihood estimation (ALE) meta-analysis revealed several differences in brain activity as a function of focality of the PM cue. The retrieval of intention is supported mainly by left anterior prefrontal cortex (Brodmann Area, BA 10) in nonfocal tasks, and by cerebellum and ventral parietal regions in focal tasks. Furthermore, the precuneus showed increased activation during the maintenance phase of intentions compared to the retrieval phase in nonfocal tasks, whereas the inferior parietal lobule showed increased activation during the retrieval of intention compared to maintenance phase in the focal tasks. Finally, the retrieval of intention relies more on the activity in anterior cingulate cortex for nonfocal tasks, and on posterior cingulate cortex for focal tasks. Such focality-related pattern of activations suggests that prospective remembering is mediated mainly by top-down and stimulus-independent processes in nonfocal tasks, whereas by more automatic, bottom-up, processes in focal tasks.

Toward a cumulative science of functional integration: A meta-analysis of psychophysiological interactions

Much of the work in cognitive neuroscience is shifting from a focus on single brain regions to a focus on the connectivity between multiple brain regions. These inter-regional connectivity patterns contribute to a wide range of behaviors and are studied with models of functional integration. The rapid expansion of the literature on functional integration offers an opportunity to scrutinize the consistency and specificity of one of the most popular approaches for quantifying connectivity: psychophysiological interaction (PPI) analysis. We performed coordinate-based meta-analyses on 284 PPI studies, which allowed us to test (a) whether those studies consistently converge on similar target regions and (b) whether the identified target regions are specific to the chosen seed region and psychological context. Our analyses revealed two key results. First, we found that different types of PPI studies-e.g., those using seeds such as amygdala and dorsolateral prefrontal cortex (DLPFC) and contexts such as emotion and cognitive control, respectively-each consistently converge on similar target regions, thus supporting the reliability of PPI as a tool for studying functional integration. Second, we also found target regions that were specific to the chosen seed region and psychological context, indicating distinct patterns of brain connectivity. For example, the DLPFC seed reliably contributed to a posterior cingulate cortex target during cognitive control but contributed to an amygdala target in other contexts. Our results point to the robustness of PPI while highlighting common and distinct patterns of functional integration, potentially advancing models of brain connectivity. Hum Brain Mapp 37:2904-2917, 2016. © 2016 Wiley Periodicals, Inc.

Understanding the minds of others: A neuroimaging meta-analysis

Theory of mind (ToM) is an important skill that refers broadly to the capacity to understand the mental states of others. A large number of neuroimaging studies have focused on identifying the functional brain regions involved in ToM, but many important questions remain with respect to the neural networks implicated in specific types of ToM tasks. In the present study, we conducted a series of activation likelihood estimation (ALE) meta-analyses on 144 datasets (involving 3150 participants) to address these questions. The ALE results revealed common regions shared across all ToM tasks and broader task parameters, but also some important dissociations. In terms of commonalities, consistent activation was identified in the medial prefrontal cortex and bilateral temporoparietal junction. On the other hand, ALE contrast analyses on our dataset, as well as meta-analytic connectivity modelling (MACM) analyses on the BrainMap database, indicated that different types of ToM tasks reliably elicit activity in unique brain areas. Our findings provide the most accurate picture to date of the neural networks that underpin ToM function.

Meta-connectomics: human brain network and connectivity meta-analyses

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Structural and functional neural adaptations in obstructive sleep apnea: An activation likelihood estimation meta-analysis

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The right basolateral amygdala, the hippocampus and the right insular cortex are important nodes in obstructive sleep apnea (OSA).

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Functional characterization of these regions suggested associated dysfunction of emotional, sensory, and limbic processes in OSA.

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Connectivity analysis demonstrated that these regions are part of a joint network comprising the anterior insula, posterior-medial frontal cortex and thalamus.

Obstructive sleep apnea (OSA) is a common multisystem chronic disorder. Functional and structural neuroimaging has been widely applied in patients with OSA, but these studies have often yielded diverse results. The present quantitative meta-analysis aims to identify consistent patterns of abnormal activation and grey matter loss in OSA across studies. We used PubMed to retrieve task/resting-state functional magnetic resonance imaging and voxel-based morphometry studies. Stereotactic data were extracted from fifteen studies, and subsequently tested for convergence using activation likelihood estimation. We found convergent evidence for structural atrophy and functional disturbances in the right basolateral amygdala/hippocampus and the right central insula. Functional characterization of these regions using the BrainMap database suggested associated dysfunction of emotional, sensory, and limbic processes. Assessment of task-based co-activation patterns furthermore indicated that the two regions obtained from the meta-analysis are part of a joint network comprising the anterior insula, posterior-medial frontal cortex and thalamus. Taken together, our findings highlight the role of right amygdala, hippocampus and insula in the abnormal emotional and sensory processing in OSA.

Connectivity-based parcellation increases network detection sensitivity in resting state fMRI: An investigation into the cingulate cortex in autism

Although resting state fMRI (RS-fMRI) is increasingly used to generate biomarkers of psychiatric illnesses, analytical choices such as seed size and placement can lead to variable findings. Seed placement especially impacts on RS-fMRI studies of Autism Spectrum Disorder (ASD), because individuals with ASD are known to possess more variable network topographies. Here, we present a novel pipeline for analysing RS-fMRI in ASD using the cingulate cortex as an exemplar anatomical region of interest. Rather than using seeds based on previous literature, or gross morphology, we used a combination of structural information, task-independent (RS-fMRI) and task-dependent functional connectivity (Meta-Analytic Connectivity Modeling) to partition the cingulate cortex into six subregions with unique connectivity fingerprints and diverse behavioural profiles. This parcellation was consistent between groups and highly replicable across individuals (up to 93% detection) suggesting that the organisation of cortico-cingulo connections is highly similar between groups. However, our results showed an age-related increase in connectivity between the anterior middle cingulate cortex and right lateral prefrontal cortex in ASD, whilst this connectivity decreased in controls. There was also a Group × Grey Matter (GM) interaction, showing increased connectivity between the anterior cingulate cortex and the rectal gyrus in concert with increasing rectal gyrus GM in controls. By comparing our approach to previously established methods we revealed that our approach improves network detection in both groups, and that the ability to detect group differences using 4 mm radius spheres varies greatly with seed placement. Using our multi-modal approach we find disrupted cortico-cingulo circuits that, based on task-dependent information, may contribute to ASD deficits in attention and social interaction. Moreover, we highlight how more sensitive approaches to RS-fMRI are crucial for establishing robust and reproducible connectivity-based biomarkers in psychiatric disorders.

Meta-analytic connectivity modeling of the human superior temporal sulcus

The superior temporal sulcus (STS) is a critical region for multiple neural processes in the human brain Hein and Knight (J Cogn Neurosci 20(12): 2125-2136, 2008). To better understand the multiple functions of the STS it would be useful to know more about its consistent functional coactivations with other brain regions. We used the meta-analytic connectivity modeling technique to determine consistent functional coactivation patterns across experiments and behaviors associated with bilateral anterior, middle, and posterior anatomical STS subregions. Based on prevailing models for the cortical organization of audition and language, we broadly hypothesized that across various behaviors the posterior STS (pSTS) would coactivate with dorsal-stream regions, whereas the anterior STS (aSTS) would coactivate with ventral-stream regions. The results revealed distinct coactivation patterns for each STS subregion, with some overlap in the frontal and temporal areas, and generally similar coactivation patterns for the left and right STS. Quantitative comparison of STS subregion coactivation maps demonstrated that the pSTS coactivated more strongly than other STS subregions in the same hemisphere with dorsal-stream regions, such as the inferior parietal lobule (only left pSTS), homotopic pSTS, precentral gyrus and supplementary motor area. In contrast, the aSTS showed more coactivation with some ventral-stream regions, such as the homotopic anterior temporal cortex and left inferior frontal gyrus, pars orbitalis (only right aSTS). These findings demonstrate consistent coactivation maps across experiments and behaviors for different anatomical STS subregions, which may help future studies consider various STS functions in the broader context of generalized coactivations for individuals with and without neurological disorders.

Reinforcement learning models and their neural correlates: An activation likelihood estimation meta-analysis

Reinforcement learning describes motivated behavior in terms of two abstract signals. The representation of discrepancies between expected and actual rewards/punishments-prediction error-is thought to update the expected value of actions and predictive stimuli. Electrophysiological and lesion studies have suggested that mesostriatal prediction error signals control behavior through synaptic modification of cortico-striato-thalamic networks. Signals in the ventromedial prefrontal and orbitofrontal cortex are implicated in representing expected value. To obtain unbiased maps of these representations in the human brain, we performed a meta-analysis of functional magnetic resonance imaging studies that had employed algorithmic reinforcement learning models across a variety of experimental paradigms. We found that the ventral striatum (medial and lateral) and midbrain/thalamus represented reward prediction errors, consistent with animal studies. Prediction error signals were also seen in the frontal operculum/insula, particularly for social rewards. In Pavlovian studies, striatal prediction error signals extended into the amygdala, whereas instrumental tasks engaged the caudate. Prediction error maps were sensitive to the model-fitting procedure (fixed or individually estimated) and to the extent of spatial smoothing. A correlate of expected value was found in a posterior region of the ventromedial prefrontal cortex, caudal and medial to the orbitofrontal regions identified in animal studies. These findings highlight a reproducible motif of reinforcement learning in the cortico-striatal loops and identify methodological dimensions that may influence the reproducibility of activation patterns across studies.

ALE meta-analysis reveals dissociable networks for affective and discriminative aspects of touch

Emotionally-laden tactile stimulation-such as a caress on the skin or the feel of velvet-may represent a functionally distinct domain of touch, underpinned by specific cortical pathways. In order to determine whether, and to what extent, cortical functional neuroanatomy supports a distinction between affective and discriminative touch, an activation likelihood estimate (ALE) meta-analysis was performed. This meta-analysis statistically mapped reported functional magnetic resonance imaging (fMRI) activations from 17 published affective touch studies in which tactile stimulation was associated with positive subjective evaluation (n = 291, 34 experimental contrasts). A separate ALE meta-analysis mapped regions most likely to be activated by tactile stimulation during detection and discrimination tasks (n = 1,075, 91 experimental contrasts). These meta-analyses revealed dissociable regions for affective and discriminative touch, with posterior insula (PI) more likely to be activated for affective touch, and primary somatosensory cortices (SI) more likely to be activated for discriminative touch. Secondary somatosensory cortex had a high likelihood of engagement by both affective and discriminative touch. Further, meta-analytic connectivity (MCAM) analyses investigated network-level co-activation likelihoods independent of task or stimulus, across a range of domains and paradigms. Affective-related PI and discriminative-related SI regions co-activated with different networks, implicated in dissociable functions, but sharing somatosensory co-activations. Taken together, these meta-analytic findings suggest that affective and discriminative touch are dissociable both on the regional and network levels. However, their degree of shared activation likelihood in somatosensory cortices indicates that this dissociation reflects functional biases within tactile processing networks, rather than functionally and anatomically distinct pathways.

Functional Segregation of the Human Dorsomedial Prefrontal Cortex

The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition.

Emotion Regulatory Brain Function and SSRI Treatment in PTSD: Neural Correlates and Predictors of Change

Posttraumatic stress disorder (PTSD)-a chronic, debilitating condition, broadly characterized by emotion dysregulation-is prevalent among US military personnel who have returned from Operations Enduring Freedom (OEF) and Iraqi Freedom (OIF). Selective serotonin reuptake inhibitors (SSRIs) are a first-line treatment for PTSD, but treatment mechanisms are unknown and patient response varies. SSRIs may exert their effects by remediating emotion regulatory brain activity and individual differences in patient response might be explained, in part, by pre-treatment differences in neural systems supporting the downregulation of negative affect. Thirty-four OEF/OIF veterans, 17 with PTSD and 17 without PTSD underwent 2 functional magnetic resonance imaging scans 12 weeks apart. At each scan, they performed an emotion regulation task; in the interim, veterans with PTSD were treated with the SSRI, paroxetine. SSRI treatment increased activation in both the left dorsolateral prefrontal cortex (PFC) and supplementary motor area (SMA) during emotion regulation, although only change in the SMA over time occurred in veterans with PTSD and not those without PTSD. Less activation of the right ventrolateral PFC/inferior frontal gyrus during pre-treatment emotion regulation was associated with greater reduction in PTSD symptoms with SSRI treatment, irrespective of pre-treatment severity. Patients with the least recruitment of prefrontal emotion regulatory brain regions may benefit most from treatment with SSRIs, which appear to augment activity in these regions.

Long-term neural and physiological phenotyping of a single human

Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders.

Co-activation based parcellation of the human frontal pole

Historically, the human frontal pole (FP) has been considered as a single architectonic area. Brodmann's area 10 is located in the frontal lobe with known contributions in the execution of various higher order cognitive processes. However, recent cytoarchitectural studies of the FP in humans have shown that this portion of cortex contains two distinct cytoarchitectonic regions. Since architectonic differences are accompanied by differential connectivity and functions, the frontal pole qualifies as a candidate region for exploratory parcellation into functionally discrete sub-regions. We investigated whether this functional heterogeneity is reflected in distinct segregations within cytoarchitectonically defined FP-areas using meta-analytic co-activation based parcellation (CBP). The CBP method examined the co-activation patterns of all voxels within the FP as reported in functional neuroimaging studies archived in the BrainMap database. Voxels within the FP were subsequently clustered into sub-regions based on the similarity of their respective meta-analytically derived co-activation maps. Performing this CBP analysis on the FP via k-means clustering produced a distinct 3-cluster parcellation for each hemisphere corresponding to previously identified cytoarchitectural differences. Post-hoc functional characterization of clusters via BrainMap metadata revealed that lateral regions of the FP mapped to memory and emotion domains, while the dorso- and ventromedial clusters were associated broadly with emotion and social cognition processes. Furthermore, the dorsomedial regions contain an emphasis on theory of mind and affective related paradigms whereas ventromedial regions couple with reward tasks. Results from this study support previous segregations of the FP and provide meta-analytic contributions to the ongoing discussion of elucidating functional architecture within human FP.

Neuroimaging distinction between neurological and psychiatric disorders

BACKGROUND

It is unclear to what extent the traditional distinction between neurological and psychiatric disorders reflects biological differences.

AIMS

To examine neuroimaging evidence for the distinction between neurological and psychiatric disorders.

METHOD

We performed an activation likelihood estimation meta-analysis on voxel-based morphometry studies reporting decreased grey matter in 14 neurological and 10 psychiatric disorders, and compared the regional and network-level alterations for these two classes of disease. In addition, we estimated neuroanatomical heterogeneity within and between the two classes.

RESULTS

Basal ganglia, insula, sensorimotor and temporal cortex showed greater impairment in neurological disorders; whereas cingulate, medial frontal, superior frontal and occipital cortex showed greater impairment in psychiatric disorders. The two classes of disorders affected distinct functional networks. Similarity within classes was higher than between classes; furthermore, similarity within class was higher for neurological than psychiatric disorders.

CONCLUSIONS

From a neuroimaging perspective, neurological and psychiatric disorders represent two distinct classes of disorders.

Multi-Modal Imaging of Neural Correlates of Motor Speed Performance in the Trail Making Test

The assessment of motor and executive functions following stroke or traumatic brain injury is a key aspect of impairment evaluation and used to guide further therapy. In clinical routine, such assessments are largely dominated by pen-and-paper tests. While these provide standardized, reliable, and ecologically valid measures of the individual level of functioning, rather little is yet known about their neurobiological underpinnings. Therefore, the aim of this study was to investigate brain regions and their associated networks that are related to upper extremity motor function, as quantified by the motor speed subtest of the trail making test (TMT-MS). Whole-brain voxel-based morphometry and whole-brain tract-based spatial statistics were used to investigate the association between TMT-MS performance with gray-matter volume (GMV) and white-matter integrity, respectively. While results demonstrated no relationship to local white-matter properties, we found a significant correlation between TMT-MS performance and GMV of the lower bank of the inferior frontal sulcus, a region associated with cognitive processing, as indicated by assessing its functional profile by the BrainMap database. Using this finding as a seed region, we further examined and compared networks as reflected by resting state connectivity, meta-analytic connectivity modeling, structural covariance, and probabilistic tractography. While differences between the different approaches were observed, all approaches converged on a network comprising regions that overlap with the multiple-demand network. Our data therefore indicate that performance may primarily depend on executive function, thus suggesting that motor speed in a more naturalistic setting should be more associated with executive rather than primary motor function. Moreover, results showed that while there were differences between the approaches, a convergence indicated that common networks can be revealed across highly divergent methods.