Anatomical and functional connectivity of cytoarchitectonic areas within the human parietal operculum

Functional reorganization of the locomotor network in Parkinson patients with freezing of gait

Freezing of gait (FoG) is a transient inability to initiate or maintain stepping that often accompanies advanced Parkinson’s disease (PD) and significantly impairs mobility. The current study uses a multimodal neuroimaging approach to assess differences in the functional and structural locomotor neural network in PD patients with and without FoG and relates these findings to measures of FoG severity. Twenty-six PD patients and fifteen age-matched controls underwent resting-state functional magnetic resonance imaging and diffusion tensor imaging along with self-reported and clinical assessments of FoG. After stringent movement correction, fifteen PD patients and fourteen control participants were available for analysis. We assessed functional connectivity strength between the supplementary motor area (SMA) and the following locomotor hubs: 1) subthalamic nucleus (STN), 2) mesencephalic and 3) cerebellar locomotor region (MLR and CLR, respectively) within each hemisphere. Additionally, we quantified structural connectivity strength between locomotor hubs and assessed relationships with metrics of FoG. FoG+ patients showed greater functional connectivity between the SMA and bilateral MLR and between the SMA and left CLR compared to both FoG− and controls. Importantly, greater functional connectivity between the SMA and MLR was positively correlated with i) clinical, ii) self-reported and iii) objective ratings of freezing severity in FoG+, potentially reflecting a maladaptive neural compensation. The current findings demonstrate a re-organization of functional communication within the locomotor network in FoG+ patients whereby the higher-order motor cortex (SMA) responsible for gait initiation communicates with the MLR and CLR to a greater extent than in FoG− patients and controls. The observed pattern of altered connectivity in FoG+ may indicate a failed attempt by the CNS to compensate for the loss of connectivity between the STN and SMA and may reflect a loss of lower-order, automatic control of gait by the basal ganglia.

Meta-analytic connectivity modeling revisited: controlling for activation base rates

Co-activation of distinct brain regions is a measure of functional interaction, or connectivity, between those regions. The co-activation pattern of a given region can be investigated using seed-based activation likelihood estimation meta-analysis of functional neuroimaging data stored in databases such as BrainMap. This method reveals inter-regional functional connectivity by determining brain regions that are consistently co-activated with a given region of interest (the "seed") across a broad range of experiments. In current implementations of this meta-analytic connectivity modeling (MACM), significant spatial convergence (i.e. consistent co-activation) is distinguished from noise by comparing it against an unbiased null-distribution of random spatial associations between experiments according to which all gray-matter voxels have the same chance of convergence. As the a priori probability of finding activation in different voxels markedly differs across the brain, computing such a quasi-rectangular null-distribution renders the detection of significant convergence more likely in those voxels that are frequently activated. Here, we propose and test a modified MACM approach that takes this activation frequency bias into account. In this new specific co-activation likelihood estimation (SCALE) algorithm, a null-distribution is generated that reflects the base rate of reporting activation in any given voxel and thus equalizes the a priori chance of finding across-study convergence in each voxel of the brain. Using four exemplary seed regions (right visual area V4, left anterior insula, right intraparietal sulcus, and subgenual cingulum), our tests corroborated the enhanced specificity of the modified algorithm, indicating that SCALE may be especially useful for delineating distinct core networks of co-activation.

Interoperable atlases of the human brain

The last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different aspects of the human brain including micro- and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topographically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and representation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored.

Connectivity-based parcellation of the human frontal polar cortex

The frontal pole corresponds to Brodmann area (BA) 10, the largest single architectonic area in the human frontal lobe. Generally, BA10 is thought to contain two or three subregions that subserve broad functions such as multitasking, social cognition, attention, and episodic memory. However, there is a substantial debate about the functional and structural heterogeneity of this large frontal region. Previous connectivity-based parcellation studies have identified two or three subregions in the human frontal pole. Here, we used diffusion tensor imaging to assess structural connectivity of BA10 in 35 healthy subjects and delineated subregions based on this connectivity. This allowed us to determine the correspondence of structurally based subregions with the scheme previously defined functionally. Three subregions could be defined in each subject. However, these three subregions were not spatially consistent between subjects. Therefore, we accepted a solution with two subregions that encompassed the lateral and medial frontal pole. We then examined resting-state functional connectivity of the two subregions and found significant differences between their connectivities. The medial cluster was connected to nodes of the default-mode network, which is implicated in internally focused, self-related thought, and social cognition. The lateral cluster was connected to nodes of the executive control network, associated with directed attention and working memory. These findings support the concept that there are two major anatomical subregions of the frontal pole related to differences in functional connectivity.

Processing of nociceptive input from posterior to anterior insula in humans

Previous brain imaging studies have shown robust activations in the insula during nociceptive stimulation. Most activations involve the posterior insular cortex but they can cover all insular gyri in some fMRI studies. However, little is known about the timing of activations across the different insular sub-regions. We report on the distribution of intracerebrally recorded nociceptive laser evoked potentials (LEPs) acquired from the full extent of the insula in 44 epileptic patients. Our study shows that both posterior and anterior subdivisions of the insular cortex respond to a nociceptive heat stimulus within a 200-400 ms latency range. This nociceptive cortical potential occurs firstly, and is larger, in the posterior granular insular cortex. The presence of phase reversals in LEP components in both posterior and anterior insular regions suggests activation of distinct, presumably functionally separate, sources in the posterior and anterior parts of the insula. Our results suggest that nociceptive input is first processed in the posterior insula, where it is known to be coded in terms of intensity and anatomical location, and then conveyed to the anterior insula, where the emotional reaction to pain is elaborated.

Neural networks related to dysfunctional face processing in autism spectrum disorder

One of the most consistent neuropsychological findings in autism spectrum disorders (ASD) is a reduced interest in and impaired processing of human faces. We conducted an activation likelihood estimation meta-analysis on 14 functional imaging studies on neural correlates of face processing enrolling a total of 164 ASD patients. Subsequently, normative whole-brain functional connectivity maps for the identified regions of significant convergence were computed for the task-independent (resting-state) and task-dependent (co-activations) state in healthy subjects. Quantitative functional decoding was performed by reference to the BrainMap database. Finally, we examined the overlap of the delineated network with the results of a previous meta-analysis on structural abnormalities in ASD as well as with brain regions involved in human action observation/imitation. We found a single cluster in the left fusiform gyrus showing significantly reduced activation during face processing in ASD across all studies. Both task-dependent and task-independent analyses indicated significant functional connectivity of this region with the temporo-occipital and lateral occipital cortex, the inferior frontal and parietal cortices, the thalamus and the amygdala. Quantitative reverse inference then indicated an association of these regions mainly with face processing, affective processing, and language-related tasks. Moreover, we found that the cortex in the region of right area V5 displaying structural changes in ASD patients showed consistent connectivity with the region showing aberrant responses in the context of face processing. Finally, this network was also implicated in the human action observation/imitation network. In summary, our findings thus suggest a functionally and structurally disturbed network of occipital regions related primarily to face (but potentially also language) processing, which interact with inferior frontal as well as limbic regions and may be the core of aberrant face processing and reduced interest in faces in ASD.

Imaging the where and when of tic generation and resting state networks in adult Tourette patients

Introduction: Tourette syndrome (TS) is a neuropsychiatric disorder with the core phenomenon of tics, whose origin and temporal pattern are unclear. We investigated the When and Where of tic generation and resting state networks (RSNs) via functional magnetic resonance imaging (fMRI).

Methods: Tic-related activity and the underlying RSNs in adult TS were studied within one fMRI session. Participants were instructed to lie in the scanner and to let tics occur freely. Tic onset times, as determined by video-observance were used as regressors and added to preceding time-bins of 1 s duration each to detect prior activation. RSN were identified by independent component analysis (ICA) and correlated to disease severity by the means of dual regression.

Results: Two seconds before a tic, the supplementary motor area (SMA), ventral primary motor cortex, primary sensorimotor cortex and parietal operculum exhibited activation; 1 s before a tic, the anterior cingulate, putamen, insula, amygdala, cerebellum and the extrastriatal-visual cortex exhibited activation; with tic-onset, the thalamus, central operculum, primary motor and somatosensory cortices exhibited activation. Analysis of resting state data resulted in 21 components including the so-called default-mode network. Network strength in those regions in SMA of two premotor ICA maps that were also active prior to tic occurrence, correlated significantly with disease severity according to the Yale Global Tic Severity Scale (YGTTS) scores.

Discussion: We demonstrate that the temporal pattern of tic generation follows the cortico-striato-thalamo-cortical circuit, and that cortical structures precede subcortical activation. The analysis of spontaneous fluctuations highlights the role of cortical premotor structures. Our study corroborates the notion of TS as a network disorder in which abnormal RSN activity might contribute to the generation of tics in SMA.

Fatigue in ankylosing spondylitis is associated with the brain networks of sensory salience and attention

OBJECTIVE

Fatigue is one of the cardinal features of ankylosing spondylitis (AS) and contributes substantially to the disability associated with this disease. The mechanisms underlying fatigue in AS remain poorly understood, and this has hampered the development of targeted, effective treatment of this disabling feature of AS. The current study was undertaken, therefore, to investigate the brain networks underlying fatigue in AS.

METHODS

Twenty patients with back pain secondary to AS (15 men and 5 women; mean ± SD age 34.8 ± 11.9 years) and 20 age- and sex-matched controls consented to participate in the study. Patients underwent clinical assessment of AS using the Fatigue Severity Scale, the Affect Intensity Measure, and the McGill Pain Questionnaire. Brain gray matter and white matter connectivity was assessed using 3T magnetic resonance imaging.

RESULTS

The patients with AS had significant fatigue that correlated with measures of their emotional strength and spinal mobility. Individual fatigue scores were negatively correlated with the amount of gray matter in areas of the dorsal and ventral attention networks, the somatosensory cortices, and the caudate nucleus, but were positively correlated with gray matter within the executive control network and putamen. Moreover, in patients with high fatigue scores, white matter tracts connecting these brain structures (e.g., inferior fronto-occipital fasciculi, superior/inferior longitudinal fasciculi, and corticothalamic tracts) exhibited low fractional anisotropy (indicative of decreased white matter tract integrity).

CONCLUSION

These data indicate that fatigue in AS involves sensory salience and attention brain networks.

You'd better think twice: post-decision perceptual confidence

Current findings suggest that confidence emerges only after decision making. However, the temporal and neural dynamics of the emergence of post-decision confidence--a metacognitive judgement--are not fully explored. To gain insight into the dynamics of post-decision confidence processing and to disentangle the processes underlying confidence judgements and decision making, we applied a tactile discrimination task during functional magnetic resonance imaging (fMRI). Our results revealed that reaction times to post-decision confidence depend on the level of confidence, suggesting that post-decision confidence in a perceptual choice is not processed in parallel to perceptual decision making. Moreover, we demonstrated by the parametric analysis of fMRI data that post-decisionally modelled confidence processing can be distinguished from processes related to decision making through anatomical location and through the pattern of neural activity. In contrast to perceptual decision making, post-decision confidence appears to be strictly allocated to a prefrontal network of brain regions, primarily the anterior and dorsolateral prefrontal cortex, areas that have been related to metacognition. Moreover, the processes underlying decision making and post-decision confidence may share recruitment of the dorsolateral prefrontal cortex, although the former probably has distinct functions with regard to processing of perceptual choices and post-decision confidence. Thus, this is the first fMRI study to disentangle the processes underlying post-decision confidence and decision making on behavioural, neuroanatomical, and neurofunctional levels. With regard to the temporal evolution of post-decision confidence, results of the present study provide strong support for the most recent theoretical models of human perceptual decision making, and thus provide implications for investigating confidence in perceptual paradigms.

Comparison of structural covariance with functional connectivity approaches exemplified by an investigation of the left anterior insula

The anterior insula is a multifunctional region involved in various cognitive, perceptual and socio-emotional processes. In particular, a portion of the left anterior insula is closely associated with working memory processes in healthy participants and shows gray matter reduction in schizophrenia. To unravel the functional networks related to this left anterior insula region, we here combined resting state connectivity, meta-analytic-connectivity modeling (MACM) and structural covariance (SC) in addition to functional characterization based on BrainMap meta-data. Apart from allowing new insight into the seed region, this approach moreover provided an opportunity to systematically compare these different connectivity approaches. The results showed that the left anterior insula has a broad response profile and is part of multiple functional networks including language, memory and socio-emotional networks. As all these domains are linked with several symptoms of schizophrenia, dysfunction of the left anterior insula might be a crucial component contributing to this disorder. Moreover, although converging connectivity across all three connectivity approaches for the left anterior insula were found, also striking differences were observed. RS and MACM as functional connectivity approaches specifically revealed functional networks linked with internal cognition and active perceptual/language processes, respectively. SC, in turn, showed a clear preference for highlighting regions involved in social cognition. These differential connectivity results thus indicate that the use of multiple forms of connectivity is advantageous when investigating functional networks as conceptual differences between these approaches might lead to systematic variation in the revealed functional networks.

How the brain decides when to work and when to rest: dissociation of implicit-reactive from explicit-predictive computational processes

A pervasive case of cost-benefit problem is how to allocate effort over time, i.e. deciding when to work and when to rest. An economic decision perspective would suggest that duration of effort is determined beforehand, depending on expected costs and benefits. However, the literature on exercise performance emphasizes that decisions are made on the fly, depending on physiological variables. Here, we propose and validate a general model of effort allocation that integrates these two views. In this model, a single variable, termed cost evidence, accumulates during effort and dissipates during rest, triggering effort cessation and resumption when reaching bounds. We assumed that such a basic mechanism could explain implicit adaptation, whereas the latent parameters (slopes and bounds) could be amenable to explicit anticipation. A series of behavioral experiments manipulating effort duration and difficulty was conducted in a total of 121 healthy humans to dissociate implicit-reactive from explicit-predictive computations. Results show 1) that effort and rest durations are adapted on the fly to variations in cost-evidence level, 2) that the cost-evidence fluctuations driving the behavior do not match explicit ratings of exhaustion, and 3) that actual difficulty impacts effort duration whereas expected difficulty impacts rest duration. Taken together, our findings suggest that cost evidence is implicitly monitored online, with an accumulation rate proportional to actual task difficulty. In contrast, cost-evidence bounds and dissipation rate might be adjusted in anticipation, depending on explicit task difficulty.

Imagine that ahead of you is a long time of work: when will you take a break? This sort of issue – how to allocate effort over time – has been addressed by distinct theoretical fields, with different emphasis on reactive and predictive processes. An intuitive view is that you start working, stop when you are tired, and start again when fatigue goes away. Biologically, this means that decisions are taken when some physiological variable reaches a given bound on the risk of homeostatic failure. In a more economic perspective, fatigue translates into effort cost, which must be anticipated and compared to expected benefit before engaging an action. We proposed a computational model that bridges these perspectives from sport physiology and decision theory. Decisions are made in reaction to bounds being reached by an implicit cost variable that accumulates during effort, at a rate proportional to task difficulty, and dissipates during rest. However, some latent parameters (bounds and dissipation rate) are adjusted in anticipation, depending on explicit costs and benefits. This model was supported by behavioral data obtained using a paradigm where participants squeeze a handgrip to win a monetary payoff proportional to effort duration.

Functional streams and cortical integration in the human brain

The processing of brain information relies on the organization of neuronal networks and circuits that in the end must provide the substrate for human cognition. However, the presence of highly complex and multirelay neuronal interactions has limited our ability to disentangle the assemblies of brain systems. The present review article focuses on the latest developments to understand the architecture of functional streams of the human brain at the large-scale level. Particularly, this article presents a comprehensive framework and recent findings about how the highly modular sensory cortex, such as the visual, somatosensory, auditory, as well as motor cortex areas, connects to more parallel-organized cortical hubs in the brain's functional connectome.

Vestibular-somatosensory interactions: effects of passive whole-body rotation on somatosensory detection

Vestibular signals are strongly integrated with information from several other sensory modalities. For example, vestibular stimulation was reported to improve tactile detection. However, this improvement could reflect either a multimodal interaction or an indirect interaction driven by vestibular effects on spatial attention and orienting. Here we investigate whether natural vestibular activation induced by passive whole-body rotation influences tactile detection. In particular, we assessed the ability to detect faint tactile stimuli to the fingertips of the left and right hand during spatially congruent or incongruent rotations. We found that passive whole-body rotations significantly enhanced sensitivity to faint shocks, without affecting response bias. Critically, this enhancement of somatosensory sensitivity did not depend on the spatial congruency between the direction of rotation and the hand stimulated. Thus, our results support a multimodal interaction, likely in brain areas receiving both vestibular and somatosensory signals.

Meta-analysis in human neuroimaging: computational modeling of large-scale databases

Spatial normalization--applying standardized coordinates as anatomical addresses within a reference space--was introduced to human neuroimaging research nearly 30 years ago. Over these three decades, an impressive series of methodological advances have adopted, extended, and popularized this standard. Collectively, this work has generated a methodologically coherent literature of unprecedented rigor, size, and scope. Large-scale online databases have compiled these observations and their associated meta-data, stimulating the development of meta-analytic methods to exploit this expanding corpus. Coordinate-based meta-analytic methods have emerged and evolved in rigor and utility. Early methods computed cross-study consensus, in a manner roughly comparable to traditional (nonimaging) meta-analysis. Recent advances now compute coactivation-based connectivity, connectivity-based functional parcellation, and complex network models powered from data sets representing tens of thousands of subjects. Meta-analyses of human neuroimaging data in large-scale databases now stand at the forefront of computational neurobiology.

A novel meta-analytic approach: mining frequent co-activation patterns in neuroimaging databases

In recent years, coordinate-based meta-analyses have become a powerful and widely used tool to study co-activity across neuroimaging experiments, a development that was supported by the emergence of large-scale neuroimaging databases like BrainMap. However, the evaluation of co-activation patterns is constrained by the fact that previous coordinate-based meta-analysis techniques like Activation Likelihood Estimation (ALE) and Multilevel Kernel Density Analysis (MKDA) reveal all brain regions that show convergent activity within a dataset without taking into account actual within-experiment co-occurrence patterns. To overcome this issue we here propose a novel meta-analytic approach named PaMiNI that utilizes a combination of two well-established data-mining techniques, Gaussian mixture modeling and the Apriori algorithm. By this, PaMiNI enables a data-driven detection of frequent co-activation patterns within neuroimaging datasets. The feasibility of the method is demonstrated by means of several analyses on simulated data as well as a real application. The analyses of the simulated data show that PaMiNI identifies the brain regions underlying the simulated activation foci and perfectly separates the co-activation patterns of the experiments in the simulations. Furthermore, PaMiNI still yields good results when activation foci of distinct brain regions become closer together or if they are non-Gaussian distributed. For the further evaluation, a real dataset on working memory experiments is used, which was previously examined in an ALE meta-analysis and hence allows a cross-validation of both methods. In this latter analysis, PaMiNI revealed a fronto-parietal "core" network of working memory and furthermore indicates a left-lateralization in this network. Finally, to encourage a widespread usage of this new method, the PaMiNI approach was implemented into a publicly available software system.

ICA model order selection of task co-activation networks

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

Long-range connectomics

Decoding neural algorithms is one of the major goals of neuroscience. It is generally accepted that brain computations rely on the orchestration of neural activity at local scales, as well as across the brain through long-range connections. Understanding the relationship between brain activity and connectivity is therefore a prerequisite to cracking the neural code. In the past few decades, tremendous technological advances have been achieved in connectivity measurement techniques. We now possess a battery of tools to measure brain activity and connections at all available scales. A great source of excitement are the new in vivo tools that allow us to measure structural and functional connections noninvasively. Here, we discuss how these new technologies may contribute to deciphering the neural code.

Adult age-dependent differences in resting-state connectivity within and between visual-attention and sensorimotor networks

Healthy aging is accompanied by structural and functional changes in the brain, among which a loss of neural specificity (i.e., dedifferentiation) is one of the most consistent findings. Little is known, however, about changes in interregional integration underlying a dedifferentiation across different functional systems. In a large sample (n = 399) of healthy adults aged from 18 to 85 years, we analyzed age-dependent differences in resting-state (RS) (task-independent) functional connectivity (FC) of a set of brain regions derived from a previous fMRI study. In that study, these regions had shown an age-related loss of activation specificity in visual-attention (superior parietal area 7A and dorsal premotor cortex) or sensorimotor (area OP4 of the parietal operculum) tasks. In addition to these dedifferentiated regions, the FC analysis of the present study included “task-general” regions associated with both attention and sensorimotor systems (rostral supplementary motor area and bilateral anterior insula) as defined via meta-analytical co-activation mapping. Within this network, we observed both selective increases and decreases in RS-FC with age. In line with regional activation changes reported previously, we found diminished anti-correlated FC for inter-system connections (i.e., between sensorimotor-related and visual attention-related regions). Our analysis also revealed reduced FC between system-specific and task-general regions, which might reflect age-related deficits in top-down control possibly leading to dedifferentiation of task-specific brain activity. Together, our results underpin the notion that RS-FC changes concur with regional activity changes in the healthy aging brain, presumably contributing jointly to age-related behavioral changes.

Bridging the gap between functional and anatomical features of cortico-cerebellar circuits using meta-analytic connectivity modeling

Theories positing that the cerebellum contributes to cognitive as well as motor control are driven by two sources of information: (1) studies highlighting connections between the cerebellum and both prefrontal and motor territories, (2) functional neuroimaging studies demonstrating cerebellar activations evoked during the performance of both cognitive and motor tasks. However, almost no studies to date have combined these two sources of information and investigated cortico-cerebellar connectivity during task performance. Through the use of a novel neuroimaging tool (Meta-Analytic Connectivity Modelling) we demonstrate for the first time that cortico-cerebellar connectivity patterns seen in anatomical studies and resting fMRI are also present during task performance. Consistent with human and nonhuman primate anatomical studies cerebellar lobules Crus I and II were significantly coactivated with prefrontal and parietal cortices during task performance, whilst lobules HV, HVI, HVIIb, and HVIII were significantly coactivated with the pre- and postcentral gyrus. An analysis of the behavioral domains showed that these circuits were driven by distinct tasks. Prefrontal-parietal-cerebellar circuits were more active during cognitive and emotion tasks whilst motor-cerebellar circuits were more active during action execution tasks. These results highlight the separation of prefrontal and motor cortico-cerebellar loops during task performance, and further demonstrate that activity within these circuits relates to distinct functions.

An OP4 functional stream in the language-related neuroarchitecture

Sensory comprehension and motor production of language symbols form the basis of human speech. Classical neuroanatomy has pointed to Wernicke's and Broca's areas as playing important roles in the integration of these 2 functions. However, recent studies have proposed that more direct pathways may exist between auditory input and motor output, bypassing Wernicke's and Broca's areas. We used functional network analyses to investigate potential auditory-motor (A-M) couplings between language-related cortices. We found that operculum parietale (OP) interconnectivity in region OP4 seems to play a critical role in the A-M integration of the brain. This finding supports a novel landscape in the functional neuroarchitecture that sustains language in humans.

The role of anterior midcingulate cortex in cognitive motor control: evidence from functional connectivity analyses

The rostral cingulate cortex has been associated with a multitude of cognitive control functions. Recent neuroimaging data suggest that the anterior midcingulate cortex (aMCC) has a key role for cognitive aspects of movement generation, i.e., intentional motor control. We here tested the functional connectivity of this area using two complementary approaches: (1) resting-state connectivity of the aMCC based on fMRI scans obtained in 100 subjects, and (2) functional connectivity in the context of explicit task conditions using meta-analytic connectivity modeling (MACM) over 656 imaging experiment. Both approaches revealed a convergent functional network architecture of the aMCC with prefrontal, premotor and parietal cortices as well as anterior insula, area 44/45, cerebellum and dorsal striatum. To specifically test the role of the aMCC's task-based functional connectivity in cognitive motor control, separate MACM analyses were conducted over "cognitive" and "action" related experimental paradigms. Both analyses confirmed the same task-based connectivity pattern of the aMCC. While the "cognition" domain showed higher convergence of activity in supramodal association areas in prefrontal cortex and anterior insula, "action" related experiments yielded higher convergence in somatosensory and premotor areas. Secondly, to probe the functional specificity of the aMCC's convergent functional connectivity, it was compared with a neural network of intentional movement initiation. This exemplary comparison confirmed the involvement of the state independent FC network of the aMCC in the intentional generation of movements. In summary, the different experiments of the present study suggest that the aMCC constitute a key region in the network realizing intentional motor control.

Functional characterization and differential coactivation patterns of two cytoarchitectonic visual areas on the human posterior fusiform gyrus

The ventral stream of the human extrastriate visual cortex shows a considerable functional heterogeneity from early visual processing (posterior) to higher, domain-specific processing (anterior). The fusiform gyrus hosts several of those "high-level" functional areas. We recently found a subdivision of the posterior fusiform gyrus on the microstructural level, that is, two distinct cytoarchitectonic areas, FG1 and FG2 (Caspers et al., Brain Structure & Function, 2013). To gain a first insight in the function of these two areas, here we studied their behavioral involvement and coactivation patterns by means of meta-analytic connectivity modeling based on the BrainMap database (www.brainmap.org), using probabilistic maps of these areas as seed regions. The coactivation patterns of the areas support the concept of a common involvement in a core network subserving different cognitive tasks, that is, object recognition, visual language perception, or visual attention. In addition, the analysis supports the previous cytoarchitectonic parcellation, indicating that FG1 appears as a transitional area between early and higher visual cortex and FG2 as a higher-order one. The latter area is furthermore lateralized, as it shows strong relations to the visual language processing system in the left hemisphere, while its right side is stronger associated with face selective regions. These findings indicate that functional lateralization of area FG2 relies on a different pattern of connectivity rather than side-specific cytoarchitectonic features.

Capturing brain metrics of neuropathic pain using nuclear magnetic resonance

SUMMARY Neuropathic pain is typically caused by a lesion or dysfunction in the nervous system that results in both negative (i.e., reduced sensitivity) and positive symptoms (i.e., paraesthesia, spontaneous ongoing pain with shooting, electric shock-like sensations and abnormal responses to evoked pain). Intriguingly, chronic pain disorders manifest profound alterations in brain structure and function, and thus, modern nuclear magnetic resonance (NMR) techniques have allowed us to begin to dissect the complexities of how neuropathic pain affects the brain. NMR approaches can be used as an independent measure to improve our understanding of key changes in brain structure, function and chemistry in chronic neuropathic pain. Accordingly, NMR techniques provide neurobiological metrics that allow us to understand the neurobiological basis of chronic neuropathic pain. Additionally, although at an early stage, NMR methods can also be useful to define clinical metrics to predict chronification of neuropathic pain and responses to drugs. This article provides a review of NMR techniques and their capacity to study spontaneous pain and evoked pain, as well as structural, functional and neurochemical alterations that have repeatedly been associated with chronic neuropathic pain. Finally, the importance for quantifying disease state and treatment efficacy in neuropathic pain using NMR techniques is discussed.

The organization of dorsal frontal cortex in humans and macaques

The human dorsal frontal cortex has been associated with the most sophisticated aspects of cognition, including those that are thought to be especially refined in humans. Here we used diffusion-weighted magnetic resonance imaging (DW-MRI) and functional MRI (fMRI) in humans and macaques to infer and compare the organization of dorsal frontal cortex in the two species. Using DW-MRI tractography-based parcellation, we identified 10 dorsal frontal regions lying between the human inferior frontal sulcus and cingulate cortex. Patterns of functional coupling between each area and the rest of the brain were then estimated with fMRI and compared with functional coupling patterns in macaques. Areas in human medial frontal cortex, including areas associated with high-level social cognitive processes such as theory of mind, showed a surprising degree of similarity in their functional coupling patterns with the frontal pole, medial prefrontal, and dorsal prefrontal convexity in the macaque. We failed to find evidence for "new" regions in human medial frontal cortex. On the lateral surface, comparison of functional coupling patterns suggested correspondences in anatomical organization distinct from those that are widely assumed. A human region sometimes referred to as lateral frontal pole more closely resembled area 46, rather than the frontal pole, of the macaque. Overall the pattern of results suggest important similarities in frontal cortex organization in humans and other primates, even in the case of regions thought to carry out uniquely human functions. The patterns of interspecies correspondences are not, however, always those that are widely assumed.

Asymmetric pedunculopontine network connectivity in parkinsonian patients with freezing of gait

Freezing of gait is one of the most debilitating symptoms in Parkinson's disease as it causes falls and reduces mobility and quality of life. The pedunculopontine nucleus is one of the major nuclei of the mesencephalic locomotor region and has neurons related to anticipatory postural adjustments preceding step initiation as well as to the step itself, thus it may be critical for coupling posture and gait to avoid freezing. Because freezing of gait and postural impairments have been related to frontal lesions and frontal dysfunction such as executive function, we hypothesized that freezing is associated with disrupted connectivity between midbrain locomotor regions and medial frontal cortex. We used diffusion tensor imaging to quantify structural connectivity of the pedunculopontine nucleus in patients with Parkinson's disease with freezing of gait, without freezing, and healthy age-matched controls. We also included behavioural tasks to gauge severity of freezing of gait, quantify gait metrics, and assess executive cognitive functions to determine whether between-group differences in executive dysfunction were related to pedunculopontine nucleus structural network connectivity. Using seed regions from the pedunculopontine nucleus, we were able to delineate white matter connections between the spinal cord, cerebellum, pedunculopontine nucleus, subcortical and frontal/prefrontal cortical regions. The current study is the first to demonstrate differences in structural connectivity of the identified locomotor pathway in patients with freezing of gait. We report reduced connectivity of the pedunculopontine nucleus with the cerebellum, thalamus and multiple regions of the frontal cortex. Moreover, these structural differences were observed solely in the right hemisphere of patients with freezing of gait. Finally, we show that the more left hemisphere-lateralized the pedunculopontine nucleus tract volume, the poorer the performance on cognitive tasks requiring the initiation of appropriate actions and/or the inhibition of inappropriate actions, specifically within patients with freezing. These results support the notion that freezing of gait is strongly related to structural deficits in the right hemisphere's locomotor network involving prefrontal cortical areas involved in executive inhibition function.

Connectivity-based parcellation of the human frontal pole with diffusion tensor imaging

The human frontal pole (FP) approximately corresponds to Brodmann's area 10 and is a highly differentiated cortical area with unique cytoarchitectonic characteristics. However, its functional diversity is highly suggestive of the existence of functional subregions. Based on anatomical connection patterns derived from diffusion tensor imaging data, we applied a spectral clustering algorithm to parcellate the human right FP into orbital (FPo), lateral (FPl), and medial (FPm) subregions. This parcellation scheme was validated by corresponding analyses of the left FP and right FP in another independent dataset. Both visual observation and quantitative comparison of the anatomical connection patterns of the three FP subregions revealed that the FPo showed greater connection probabilities to brain regions of the social emotion network (SEN), including the orbitofrontal cortex, temporal pole, and amygdala, the FPl showed stronger connections to the dorsolateral prefrontal cortex of the cognitive processing network (CPN), and the FPm showed stronger connections to brain areas of the default mode network (DMN), including the anterior cingulate cortex and medial prefrontal cortex. We further analyzed the resting-state functional connectivity patterns of the three FP subregions. Consistent with the findings of anatomical connection analyses, the FPo was functionally correlated with the SEN, the FPl was correlated with the CPN, and the FPm was correlated with the DMN. These findings suggest that the human FP includes three separable subregions with different anatomical and functional connectivity patterns and that these subregions are involved in different brain functional networks and serve different functions.

Dysregulated left inferior parietal activity in schizophrenia and depression: functional connectivity and characterization

The inferior parietal cortex (IPC) is a heterogeneous region that is known to be involved in a multitude of diverse different tasks and processes, though its contribution to these often-complex functions is yet poorly understood. In a previous study we demonstrated that patients with depression failed to deactivate the left IPC during processing of congruent audiovisual information. We now found the same dysregulation (same region and condition) in schizophrenia. By using task-independent (resting state) and task-dependent meta-analytic connectivity modeling (MACM) analyses we aimed at characterizing this particular region with regard to its connectivity and function. Across both approaches, results revealed functional connectivity of the left inferior parietal seed region with bilateral IPC, precuneus and posterior cingulate cortex (PrC/PCC), medial orbitofrontal cortex (mOFC), left middle frontal (MFG) as well as inferior frontal (IFG) gyrus. Network-level functional characterization further revealed that on the one hand, all interconnected regions are part of a network involved in memory processes. On the other hand, sub-networks are formed when emotion, language, social cognition and reasoning processes are required. Thus, the IPC-region that is dysregulated in both depression and schizophrenia is functionally connected to a network of regions which, depending on task demands may form sub-networks. These results therefore indicate that dysregulation of left IPC in depression and schizophrenia might not only be connected to deficits in audiovisual integration, but is possibly also associated to impaired memory and deficits in emotion processing in these patient groups.

Networks of task co-activations

Recent progress in neuroimaging informatics and meta-analytic techniques has enabled a novel domain of human brain connectomics research that focuses on task-dependent co-activation patterns across behavioral tasks and cognitive domains. Here, we review studies utilizing the BrainMap database to investigate data trends in the activation literature using methods such as meta-analytic connectivity modeling (MACM), connectivity-based parcellation (CPB), and independent component analysis (ICA). We give examples of how these methods are being applied to learn more about the functional connectivity of areas such as the amygdala, the default mode network, and visual area V5. Methods for analyzing the behavioral metadata corresponding to regions of interest and to their intrinsically connected networks are described as a tool for local functional decoding. We finally discuss the relation of observed co-activation connectivity results to resting state connectivity patterns, and provide implications for future work in this domain.

Subregions of the human superior frontal gyrus and their connections

The superior frontal gyrus (SFG) is located at the superior part of the prefrontal cortex and is involved in a variety of functions, suggesting the existence of functional subregions. However, parcellation schemes of the human SFG and the connection patterns of each subregion remain unclear. We firstly parcellated the human SFG into the anteromedial (SFGam), dorsolateral (SFGdl), and posterior (SFGp) subregions based on diffusion tensor tractography. The SFGam was anatomically connected with the anterior and mid-cingulate cortices, which are critical nodes of the cognitive control network and the default mode network (DMN). The SFGdl was connected with the middle and inferior frontal gyri, which are involved in the cognitive execution network. The SFGp was connected with the precentral gyrus, caudate, thalamus, and frontal operculum, which are nodes of the motor control network. Resting-state functional connectivity analysis further revealed that the SFGam was mainly correlated with the cognitive control network and the DMN; the SFGdl was correlated with the cognitive execution network and the DMN; and the SFGp was correlated with the sensorimotor-related brain regions. The SFGam and SFGdl were further parcellated into three and two subclusters that are well corresponding to Brodmann areas. These findings suggest that the human SFG consists of multiple dissociable subregions that have distinct connection patterns and that these subregions are involved in different functional networks and serve different functions. These results may improve our understanding on the functional complexity of the SFG and provide us an approach to investigate the SFG at the subregional level.

Microstructural grey matter parcellation and its relevance for connectome analyses

The human brain connectome is closely linked to the anatomical framework provided by the structural segregation of the cortex into distinct cortical areas. Therefore, a thorough anatomical reference for the analysis and interpretation of connectome data is indispensable to understand the structure and function of different regions of the cortex, the white matter fibre architecture connecting them, and the interplay between these different entities. This article focuses on parcellation schemes of the cerebral grey matter and their relevance for connectome analyses. In particular, benefits and limitations of using different available atlases and parcellation schemes are reviewed. It is furthermore discussed how atlas information is currently used in connectivity analyses with major focus on seed-based and seed-target analyses, connectivity-based parcellation results, and the robust anatomical interpretation of connectivity data. Particularly this last aspect opens the possibility of integrating connectivity information into given anatomical frameworks, paving the way to multi-modal atlases of the human brain for a thorough understanding of structure-function relationships.

Do EEG paradigms work in fMRI? Varying task demands in the visual oddball paradigm: Implications for task design and results interpretation

We investigate the effects of variations in response requirements on BOLD activation in a visual oddball task and consider implications for fMRI task designs. Sixteen healthy subjects completed 3 runs of a visual oddball task: passive, count and respond. Besides expected activation patterns during passive viewing, we identified joint activations, but more importantly crucial differences between the count and respond versions of the task. Middle frontal gyrus activation was seen in the respond but not the count condition suggesting that this region is associated with action execution rather than the decision-making aspect of the task. In addition, activation observed in the central opercular cortex and parietal operculum in the respond (but not count) condition is likely to reflect integration of the sensory, decision and response processes. We also observed activation in the supplementary motor area (SMA) during count as well as respond. Since the count condition requires no motor planning or response our data provide evidence for an SMA involvement in decision-making. Our study clearly shows that the count and respond versions of the visual oddball task result in different patterns of BOLD activation that could both be attributed to 'target detection' if information on the respective other condition was not available. We also show that considering the elements of a complex task is crucial when transferring it from one imaging modality to another and that a motor response is not always necessary in fMRI studies when the task has been set up appropriately.

Dissociations between the horizontal and dorsoventral axes in body-size perception

Body size can vary throughout a person's lifetime, inducing plasticity of the internal body representation. Changes in horizontal width accompany those in dorsal-to-ventral thickness. To examine differences in the perception of different body axes, neural correlates of own-body-size perception in the horizontal and dorsoventral directions were compared using functional magnetic resonance imaging. Original and distorted (-30, -10, +10 and +30%) images of the neck-down region of their own body were presented to healthy female participants, who were then asked whether the images were of their own body or not based explicitly on body size. Participants perceived body images distorted by -10% as their own, whereas those distorted by +30% as belonging to others. Horizontal width images yielded slightly more subjective own-body perceptions than dorsoventral thickness images did. Subjective perception of own-body size was associated with bilateral inferior parietal activity. In contrast, other-body judgments showed pre-supplementary motor and superior parietal activity. Expansion in the dorsoventral direction was associated with the left fusiform gyrus and the right inferior parietal lobule, whereas horizontal expansions were associated with activity in the bilateral somatosensory area. These results suggest neural dissociations between the two body axes: dorsoventral images of thickness may require visual processing, whereas bodily sensations are involved in horizontal body-size perception. Somatosensory rather than visual processes can be critical for the assessment of frontal own-body appearance. Visual body thickness and somatosensory body width may be integrated to construct a whole-body representation.

Activation shift in elderly subjects across functional systems: an fMRI study

The functional specificity of brain areas is diminished with age and accompanied by the recruitment of additional brain regions in healthy older adults. This process has repeatedly been demonstrated within distinct functional domains, in particular the visual system. However, it is yet unclear, whether this phenomenon in healthy aging, i.e., a reduced activation of task-associated areas and increased activation of additional regions, is also present across different functional systems. In the present functional imaging study, comprising 102 healthy subjects, we therefore assessed two distinct tasks engaging the sensory-motor system and the visual attention system, respectively. We found a significant interaction between age and task in the parietal operculum bilaterally. This area as a part of the sensory-motor system showed an age-related decrease in its BOLD-response to the motor task and an age-related increase of neural activity in response to the visual attention task. The opposite response pattern, i.e., reduced visual attention activation and increased response to the motor task, was observed for regions associated with the visual task: the superior parietal area 7A and the dorsal pre-motor cortex. Importantly, task performance was not correlated with age in either task. This age-by-task interaction indicates that a reduction of functional specificity in the aging brain may be counteracted by the increased recruitment of additional regions not only within, but also across functional domains. Our results thus emphasize the need for comparisons across different functional domains to gain a better understanding of age-related effects on the specificity of functional systems.

Task- and resting-state functional connectivity of brain regions related to affection and susceptible to concurrent cognitive demand

A recent fMRI-study revealed neural responses for affective processing of stimuli for which overt attention irrespective of stimulus valence was required in the orbitofrontal cortex (OFC) and bilateral amygdala (AMY): activation decreased with increasing cognitive demand. To further characterize the network putatively related to this attenuation, we here characterized these regions with respect to their functional properties and connectivity patterns in task-dependent and task-independent states. All experiments of the BrainMap database activating the seed regions OFC and bilateral AMY were identified. Their functional characteristics were quantitatively inferred using the behavioral meta-data of the retrieved experiments. Task-dependent functional connectivity was characterized by meta-analytic connectivity modeling (MACM) of significant co-activations with these seed regions. Task-independent resting-state functional connectivity analysis in a sample of 100 healthy subjects complemented these analyses. All three seed regions co-activated with subgenual cingulum (SGC), precuneus (PCu) and nucleus accumbens (NAcc) in the task-dependent MACM analysis. Task-independent resting-state connectivity revealed significant coupling of the seeds only with the SGC, but not the PCu and the NAcc. The former region (SGC) moreover was shown to feature significant resting-state connectivity with all other regions implicated in the network connected to regions where emotional processing may be modulated by a cognitive distractor. Based on its functional profile and connectivity pattern, we suggest that the SGC might serve as a key hub in the identified network, as such linking autobiographic information [PCu], reward [NAcc], (reinforce) values [OFC] and emotional significance [AMY]. Such a role, in turn, may allow the SGC to influence the OFC and AMY to modulate affective processing.

Neurocomputational account of how the human brain decides when to have a break

No pain, no gain: cost-benefit trade-off has been formalized in classical decision theory to account for how we choose whether to engage effort. However, how the brain decides when to have breaks in the course of effort production remains poorly understood. We propose that decisions to cease and resume work are triggered by a cost evidence accumulation signal reaching upper and lower bounds, respectively. We developed a task in which participants are free to exert a physical effort knowing that their payoff would be proportional to their effort duration. Functional MRI and magnetoencephalography recordings conjointly revealed that the theoretical cost evidence accumulation signal was expressed in proprioceptive regions (bilateral posterior insula). Furthermore, the slopes and bounds of the accumulation process were adapted to the difficulty of the task and the money at stake. Cost evidence accumulation might therefore provide a dynamical mechanistic account of how the human brain maximizes benefits while preventing exhaustion.

Brain structural correlates of reward sensitivity and impulsivity in adolescents with normal and excess weight

Introduction

Neuroscience evidence suggests that adolescent obesity is linked to brain dysfunctions associated with enhanced reward and somatosensory processing and reduced impulse control during food processing. Comparatively less is known about the role of more stable brain structural measures and their link to personality traits and neuropsychological factors on the presentation of adolescent obesity. Here we aimed to investigate regional brain anatomy in adolescents with excess weight vs. lean controls. We also aimed to contrast the associations between brain structure and personality and cognitive measures in both groups.

Methods

Fifty-two adolescents (16 with normal weight and 36 with excess weight) were scanned using magnetic resonance imaging and completed the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ), the UPPS-P scale, and the Stroop task. Voxel-based morphometry (VBM) was used to assess possible between-group differences in regional gray matter (GM) and to measure the putative differences in the way reward and punishment sensitivity, impulsivity and inhibitory control relate to regional GM volumes, which were analyzed using both region of interest (ROI) and whole brain analyses. The ROIs included areas involved in reward/somatosensory processing (striatum, somatosensory cortices) and motivation/impulse control (hippocampus, prefrontal cortex).

Results

Excess weight adolescents showed increased GM volume in the right hippocampus. Voxel-wise volumes of the second somatosensory cortex (SII) were correlated with reward sensitivity and positive urgency in lean controls, but this association was missed in excess weight adolescents. Moreover, Stroop performance correlated with dorsolateral prefrontal cortex volumes in controls but not in excess weight adolescents.

Conclusion

Adolescents with excess weight have structural abnormalities in brain regions associated with somatosensory processing and motivation.

Differentiated parietal connectivity of frontal regions for "what" and "where" memory

In a previous meta-analysis across almost 200 neuroimaging experiments, working memory for object location showed significantly stronger convergence on the posterior superior frontal gyrus, whereas working memory for identity showed stronger convergence on the posterior inferior frontal gyrus (dorsal to, but overlapping with Brodmann’s area BA 44). As similar locations have been discussed as part of a dorsal frontal—superior parietal reach system and an inferior frontal grasp system, the aim of the present study was to test whether the regions of working-memory related “what” and “where” processing show a similar distinction in parietal connectivity. The regions that were found in the previous meta-analysis were used as seeds for functional connectivity analyses using task-based meta-analytic connectivity modelling and task-independent resting state correlations. While the ventral seed showed significantly stronger connectivity with the bilateral intraparietal sulcus (IPS), the dorsal seed showed stronger connectivity with the bilateral posterior inferior parietal and the medial superior parietal lobule. The observed connections of regions involved in memory for object location and identity thus clearly demonstrate a distinction into separate pathways that resemble the parietal connectivity patterns of the dorsal and ventral premotor cortex in non-human primates and humans. It may hence be speculated that memory for a particular location and reaching towards it as well as object memory and finger positioning for manipulation may rely on shared neural systems. Moreover, the ensuing regions, in turn, featured differential connectivity with the bilateral ventral and dorsal extrastriate cortex, suggesting largely segregated bilateral connectivity pathways from the dorsal visual cortex via the superior and inferior parietal lobules to the dorsal posterior frontal cortex and from the ventral visual cortex via the IPS to the ventral posterior frontal cortex that may underlie action and cognition.

Parietal influence on temporal encoding indexed by simultaneous transcranial magnetic stimulation and electroencephalography

Previous studies have suggested that contingent negative variation (CNV), as recorded by electroencaphalography (EEG), may serve as an index of temporal encoding. The interpretation of these studies is complicated by the fact that, in a majority of studies, the CNV signal was obtained at a time when subjects were not only registering stimulus duration but also making decisions and preparing to act. Previously, we demonstrated that repetitive transcranial magnetic stimulation (rTMS) of the right supramarginal gyrus (rSMG) in humans lengthened the perceived duration of a visual stimulus (Wiener et al., 2010a), suggesting the rSMG is involved in basic encoding processes. Here, we report a replication of this effect with simultaneous EEG recordings during the encoding of stimulus duration. Stimulation of the rSMG led to an increase in perceived duration and the amplitude of N1 and CNV components recorded from frontocentral sites. Furthermore, the size of the CNV amplitude, but not N1, positively correlated with the size of the rTMS effect but negatively correlated with bias (the baseline tendency to report a comparison stimulus as shorter), suggesting that the CNV indexes stimulus duration. These results suggest that a feedforward mechanism from parietal to prefrontal regions mediates temporal encoding and demonstrate a dissociation between early and late phases of encoding processes.

Mapping repetition suppression of the P50 evoked response to the human cerebral cortex

OBJECTIVE

The cerebral network subserving repetition suppression (RS) of the P50 auditory evoked response as observed using paired-identical-stimulus (S1-S2) paradigms is not well-described.

METHODS

We analyzed S1-S2 data from electrodes placed on the cortices of 64 epilepsy patients. We identified regions with maximal amplitude responses to S1 (i.e., stimulus registration), regions with maximal suppression of responses to S2 relative to S1 (i.e., RS), and regions with no or minimal RS 30-80 ms post stimulation.

RESULTS

Several temporal, parietal and cingulate area regions were shown to have significant initial registration activity (i.e., strong P50 response to S1). Moreover, prefrontal, cingulate, and parietal lobe regions not previously proposed to be part of the P50 habituation neural circuitry were found to exhibit significant RS.

CONCLUSIONS

The data suggest that the neural network underlying the initial phases of the RS process may include regions not previously thought to be involved like the parietal and cingulate cortexes. In addition, a significant role for the frontal lobe in mediating this function is supported.

SIGNIFICANCE

A number of regions of interest are identified through invasive recording that will allow further probing of the RS function using less invasive technology.

Meta-analytic connectivity modeling reveals differential functional connectivity of the medial and lateral orbitofrontal cortex

The orbitofrontal cortex (OFC) is implicated in a broad range of behaviors and neuropsychiatric disorders. Anatomical tracing studies in nonhuman primates reveal differences in connectivity across subregions of the OFC, but data on the connectivity of the human OFC remain limited. We applied meta-analytic connectivity modeling in order to examine which brain regions are most frequently coactivated with the medial and lateral portions of the OFC in published functional neuroimaging studies. The analysis revealed a clear divergence in the pattern of connectivity for the medial OFC (mOFC) and lateral OFC (lOFC) regions. The lOFC showed coactivations with a network of prefrontal regions and areas involved in cognitive functions including language and memory. In contrast, the mOFC showed connectivity with default mode, autonomic, and limbic regions. Convergent patterns of coactivations were observed in the amygdala, hippocampus, striatum, and thalamus. A small number of regions showed connectivity specific to the anterior or posterior sectors of the OFC. Task domains involving memory, semantic processing, face processing, and reward were additionally analyzed in order to identify the different patterns of OFC functional connectivity associated with specific cognitive and affective processes. These data provide a framework for understanding the human OFC's position within widespread functional networks.

Functional connectivity profile of the human inferior frontal junction: involvement in a cognitive control network

Background

The human inferior frontal junction area (IFJ) is critically involved in three main component processes of cognitive control (working memory, task switching and inhibitory control). As it overlaps with several areas in established anatomical labeling schemes, it is considered to be underreported as a functionally distinct location in the neuroimaging literature. While recent studies explicitly focused on the IFJ's anatomical organization and functional role as a single brain area, it is usually not explicitly denominated in studies on cognitive networks. However based on few analyses in small datasets constrained by specific a priori assumptions on its functional specialization, the IFJ has been postulated to be part of a cognitive control network. Goal of this meta-analysis was to establish the IFJ’s connectivity profile on a high formal level of evidence by aggregating published implicit knowledge about its co-activations. We applied meta-analytical connectivity modeling (MACM) based on the activation likelihood estimation (ALE) method without specific assumptions regarding functional specialization on 180 (reporting left IFJ activity) and 131 (right IFJ) published functional neuroimaging experiments derived from the BrainMap database. This method is based on coordinates in stereotaxic space, not on anatomical descriptors.

Results

The IFJ is significantly co-activated with areas in the dorsolateral and ventrolateral prefrontal cortex, anterior insula, medial frontal gyrus / pre-SMA, posterior parietal cortex, occipitotemporal junction / cerebellum, thalamus and putamen as well as language and motor areas. Results are corroborated by an independent resting-state fMRI analysis.

Conclusions

These results support the assumption that the IFJ is part of a previously described cognitive control network. They also highlight the involvement of subcortical structures in this system. A direct line is drawn from works on the functional significance of brain activity located at the IFJ and its anatomical definition to published results related to distributed cognitive brain systems. The IFJ is therefore introduced as a convenient starting point to investigate the cognitive control network in further studies.

A coordinate-based meta-analytic model of trauma processing in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) has a well-defined set of symptoms that can be elicited during traumatic imagery tasks. For this reason, trauma imagery tasks are often employed in functional neuroimaging studies. Here, coordinate-based meta-analysis (CBM) was used to pool eight studies applying traumatic imagery tasks to identify sites of task-induced activation in 170 PTSD patients and 104 healthy controls. In this way, right anterior cingulate (ACC), right posterior cingulate (PCC), and left precuneus (Pcun) were identified as regions uniquely active in PTSD patients relative to healthy controls. To further characterize these regions, their normal interactions, and their typical functional roles, meta-analytic connectivity modeling (MACM) with behavioral filtering was applied. MACM indicated that the PCC and Pcun regions were frequently co-active and associated with processing of cognitive information, particularly in explicit memory tasks. Emotional processing was particularly associated with co-activity of the ACC and PCC, as mediated by the thalamus. By narrowing the regions of interest to those commonly active across multiple studies (using CBM) and developing a priori hypotheses about directed probabilistic dependencies amongst these regions, this proposed model-when applied in the context of graphical and causal modeling-should improve model fit and thereby increase statistical power for detecting differences between subject groups and between treatments in neuroimaging studies of PTSD.

Is there "one" DLPFC in cognitive action control? Evidence for heterogeneity from co-activation-based parcellation

The dorsolateral prefrontal cortex (DLPFC) has consistently been implicated in cognitive control of motor behavior. There is, however, considerable variability in the exact location and extension of these activations across functional magnetic resonance imaging (fMRI) experiments. This poses the question of whether this variability reflects sampling error and spatial uncertainty in fMRI experiments or structural and functional heterogeneity of this region. This study shows that the right DLPFC as observed in 4 different experiments tapping executive action control may be subdivided into 2 distinct subregions-an anterior-ventral and a posterior-dorsal one -based on their whole-brain co-activation patterns across neuroimaging studies. Investigation of task-dependent and task-independent connectivity revealed both clusters to be involved in distinct neural networks. The posterior subregion showed increased connectivity with bilateral intraparietal sulci, whereas the anterior subregion showed increased connectivity with the anterior cingulate cortex. Functional characterization with quantitative forward and reverse inferences revealed the anterior network to be more strongly associated with attention and action inhibition processes, whereas the posterior network was more strongly related to action execution and working memory. The present data provide evidence that cognitive action control in the right DLPFC may rely on differentiable neural networks and cognitive functions.

Consistent neurodegeneration and its association with clinical progression in Huntington's disease: a coordinate-based meta-analysis

BACKGROUND

The neuropathological hallmark of Huntington's disease (HD) is progressive striatal loss starting several years prior to clinical onset. In the past decade, whole-brain magnetic resonance imaging (MRI) studies have provided accumulating evidence for widely distributed cortical and subcortical atrophy in the early course of the disease.

OBJECTIVE

In order to synthesize current morphometric MRI findings and to investigate the impact of clinical and genetic features on structural changes, we performed a coordinate-based meta-analysis of voxel-based morphometry (VBM) studies in HD.

METHODS

Twenty HD samples derived from 17 studies were integrated in the analysis comparing a total of 685 HD mutation carriers [345 presymptomatic (pre-HD) and 340 symptomatic (symp-HD) subjects] and 507 controls. Convergent findings across studies were delineated using the anatomical likelihood estimation approach. Effects of genetic and clinical parameters on the likelihood of observing VBM findings were calculated by means of correlation analyses.

RESULTS

Pre-HD studies featured convergent evidence for neurodegeneration in the basal ganglia, amygdala, thalamus, insula and occipital regions. In symp-HD, cerebral atrophy was more pronounced and spread to cortical regions (i.e., inferior frontal, premotor, sensorimotor, midcingulate, frontoparietal and temporoparietal cortices). Higher cytosine-adenosine-guanosine repeats were associated with striatal degeneration, while parameters of disease progression and motor impairment additionally correlated with cortical atrophy, especially in sensorimotor areas.

CONCLUSION

This first quantitative meta-analysis in HD demonstrates the extent of striatal atrophy and further consistent extrastriatal degeneration before clinical conversion. Sensorimotor areas seem to be core regions affected in symp-HD and, along with widespread cortical atrophy, may account for the clinical heterogeneity in HD.