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.
The association cortex supports cognitive functions enabling flexible behavior. Here, we explored the organization of human association cortex by mathematically formalizing the notion that a behavioral task engages multiple cognitive components, which are in turn supported by multiple overlapping brain regions. Application of the model to a large data set of neuroimaging experiments (N = 10 449) identified complex zones of frontal and parietal regions that ranged from being highly specialized to highly flexible. The network organization of the specialized and flexible regions was explored with an independent resting-state fMRI data set (N = 1000). Cortical regions specialized for the same components were strongly coupled, suggesting that components function as partially isolated networks. Functionally flexible regions participated in multiple components to different degrees. This heterogeneous selectivity was predicted by the connectivity between flexible and specialized regions. Functionally flexible regions might support binding or integrating specialized brain networks that, in turn, contribute to the ability to execute multiple and varied tasks.
Resting-state fMRI (rs-fMRI) has been widely used to segregate the brain into individual modules based on the presence of distinct connectivity patterns. Many parcellation methods have been proposed for brain parcellation using rs-fMRI, but their results have been somewhat inconsistent, potentially due to various types of noise. In this study, we provide a robust parcellation method for rs-fMRI-based brain parcellation, which constructs a sparse similarity graph based on the sparse representation coefficients of each seed voxel and then uses spectral clustering to identify distinct modules. Both the local time-varying BOLD signals and whole-brain connectivity patterns may be used as features and yield similar parcellation results. The robustness of our method was tested on both simulated and real rs-fMRI datasets. In particular, on simulated rs-fMRI data, sparse representation achieved good performance across different noise levels, including high accuracy of parcellation and high robustness to noise. On real rs-fMRI data, stable parcellation of the medial frontal cortex (MFC) and parietal operculum (OP) were achieved on three different datasets, with high reproducibility within each dataset and high consistency across these results. Besides, the parcellation of MFC was little influenced by the degrees of spatial smoothing. Furthermore, the consistent parcellation of OP was also well corresponding to cytoarchitectonic subdivisions and known somatotopic organizations. Our results demonstrate a new promising approach to robust brain parcellation using resting-state fMRI by sparse representation.
Cortico-basal ganglia connections are involved in a range of behaviors within motor, cognitive, and emotional domains; however, the whole-brain functional connections of individual nuclei are poorly understood in humans. The first aim of this study was to characterize and compare the connectivity of the subthalamic nucleus (STN) and globus pallidus pars interna (GPi) using meta-analytic connectivity modeling. Structure-based activation likelihood estimation meta-analyses were performed for STN and GPi seeds using archived functional imaging coordinates from the BrainMap database. Both regions coactivated with caudate, putamen, thalamus, STN, GPi, and GPe, SMA, IFG, and insula. Contrast analyses also revealed coactivation differences within SMA, IFG, insula, and premotor cortex. The second aim of this study was to examine the degree of overlap between the connectivity maps derived for STN and GPi and a functional activation map representing the speech network. To do this, we examined the intersection of coactivation maps and their respective contrasts (STN?>?GPi and GPi?>?STN) with a coordinate-based meta-analysis of speech function. In conjunction with the speech map, both STN and GPi coactivation maps revealed overlap in the anterior insula with GPi map additionally showing overlap in the supplementary motor area (SMA). Among cortical regions activated by speech tasks, STN was found to have stronger connectivity than GPi with regions involved in cognitive linguistic processes (pre-SMA, dorsal anterior insula, and inferior frontal gyrus), while GPi demonstrated stronger connectivity to regions involved in motor speech processes (middle insula, SMA, and premotor cortex).
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.
Theta burst stimulation (TBS), a specific protocol of repetitive transcranial magnetic stimulation (rTMS), induces changes in cortical excitability that last beyond stimulation. TBS-induced aftereffects, however, vary between subjects, and the mechanisms underlying these aftereffects to date remain poorly understood. Therefore, the purpose of this study was to investigate whether increasing the number of pulses of intermittent TBS (iTBS) (1) increases cortical excitability as measured by motor-evoked potentials (MEPs) and (2) alters functional connectivity measured using resting-state fMRI, in a dose-dependent manner. Sixteen healthy, human subjects received three serially applied iTBS blocks of 600 pulses over the primary motor cortex (M1 stimulation) and the parieto-occipital vertex (sham stimulation) to test for dose-dependent iTBS effects on cortical excitability and functional connectivity (four sessions in total). iTBS over M1 increased MEP amplitudes compared with sham stimulation after each stimulation block. Although the increase in MEP amplitudes did not differ between the first and second block of M1 stimulation, we observed a significant increase after three blocks (1800 pulses). Furthermore, iTBS enhanced resting-state functional connectivity between the stimulated M1 and premotor regions in both hemispheres. Functional connectivity between M1 and ipsilateral dorsal premotor cortex further increased dose-dependently after 1800 pulses of iTBS over M1. However, no correlation between changes in MEP amplitudes and functional connectivity was detected. In summary, our data show that increasing the number of iTBS stimulation blocks results in dose-dependent effects at the local level (cortical excitability) as well as at a systems level (functional connectivity) with a dose-dependent enhancement of dorsal premotor cortex-M1 connectivity.
Cognitive flexibility, a core aspect of executive functioning, is required for the speeded shifting between different tasks and sets. Using an interindividual differences approach, we examined whether cognitive flexibility, as assessed by the Delis-Kaplan card-sorting test, is associated with gray matter volume (GMV) and functional connectivity (FC) of regions of a core network of multiple cognitive demands as well as with different facets of trait impulsivity. The core multiple-demand network was derived from three large-scale neuroimaging meta-analyses and only included regions that showed consistent associations with sustained attention, working memory as well as inhibitory control. We tested to what extent self-reported impulsivity as well as GMV and resting-state FC in this core network predicted cognitive flexibility independently and incrementally. Our analyses revealed that card-sorting performance correlated positively with GMV of the right anterior insula, FC between bilateral anterior insula and midcingulate cortex/supplementary motor area as well as the impulsivity dimension "Premeditation." Importantly, GMV, FC and impulsivity together accounted for more variance of card-sorting performance than every parameter alone. Our results therefore indicate that various factors contribute individually to cognitive flexibility, underlining the need to search across multiple modalities when aiming to unveil the mechanisms behind executive functioning.
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.
Handedness denotes the individual predisposition to consistently use the left or right hand for most types of skilled movements. A putative neurobiological mechanism for handedness consists in hemisphere-specific differences in network dynamics that govern unimanual movements. We, therefore, used functional magnetic resonance imaging and dynamic causal modeling to investigate effective connectivity between key motor areas during fist closures of the dominant or non-dominant hand performed by 18 right- and 18 left-handers. Handedness was assessed employing the Edinburgh-Handedness-Inventory (EHI). The network of interest consisted of key motor regions in both hemispheres including the primary motor cortex (M1), supplementary motor area (SMA), ventral premotor cortex (PMv), motor putamen (Put) and motor cerebellum (Cb). The connectivity analysis revealed that in right-handed subjects movements of the dominant hand were associated with significantly stronger coupling of contralateral (left, i.e., dominant) SMA with ipsilateral SMA, ipsilateral PMv, contralateral motor putamen and contralateral M1 compared to equivalent connections in left-handers. The degree of handedness as indexed by the individual EHI scores also correlated with coupling parameters of these connections. In contrast, we found no differences between right- and left-handers when testing for the effect of movement speed on effective connectivity. In conclusion, the data show that handedness is associated with differences in effective connectivity within the human motor network with a prominent role of SMA in right-handers. Left-handers featured less asymmetry in effective connectivity implying different hemispheric mechanisms underlying hand motor control compared to right-handers.
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.
Healthy aging has been found associated with less efficient response conflict solution, but the cognitive and neural mechanisms have remained elusive. In a two-experiment study, we first examined the behavioural consequences of this putative age-related decline for conflicts induced by spatial stimulus-response incompatibility. We then used resting-state functional magnetic resonance imaging data from a large, independent sample of adults (n = 399; 18-85 years) to investigate age differences in functional connectivity between the nodes of a network previously found associated with incompatibility-induced response conflicts in the very same paradigm. As expected, overcoming interference from conflicting response tendencies took longer in older adults, even after accounting for potential mediator variables (general response speed and accuracy, motor speed, visuomotor coordination ability, and cognitive flexibility). Experiment 2 revealed selective age-related decreases in functional connectivity between bilateral anterior insula, pre-supplementary motor area, and right dorsolateral prefrontal cortex. Importantly, these age effects persisted after controlling for regional grey-matter atrophy assessed by voxel-based morphometry. Meta-analytic functional profiling using the BrainMap database showed these age-sensitive nodes to be more strongly linked to highly abstract cognition, as compared with the remaining network nodes, which were more strongly linked to action-related processing. These findings indicate changes in interregional coupling with age among task-relevant network nodes that are not specifically associated with conflict resolution per se. Rather, our behavioural and neural data jointly suggest that healthy aging is associated with difficulties in properly activating non-dominant but relevant task schemata necessary to exert efficient cognitive control over action.
Episodic memory is typically affected during the course of Alzheimer's disease (AD). Due to the pronounced heterogeneity of functional neuroimaging studies on episodic memory impairments in mild cognitive impairment (MCI) and AD regarding their methodology and findings, we aimed to delineate consistent episodic memory-related brain activation patterns. We performed a systematic, quantitative, coordinate-based whole-brain activation likelihood estimation meta-analysis of 28 functional magnetic resonance imaging (fMRI) studies comprising 292 MCI and 102 AD patients contrasted to 409 age-matched control subjects. We included episodic encoding and/or retrieval phases, investigated the effects of group, verbal or image stimuli and correlated mean Mini-Mental-Status-Examination (MMSE) scores with the modelled activation estimates. MCI patients presented increased right hippocampal activation during memory encoding, decreased activation in the left hippocampus and fusiform gyrus during retrieval tasks, as well as attenuated activation in the right anterior insula/inferior frontal gyrus during verbal retrieval. In AD patients, however, stronger activation within the precuneus during encoding tasks was accompanied by attenuated right hippocampal activation during retrieval tasks. Low cognitive performance (MMSE scores) was associated with stronger activation of the precuneus and reduced activation of the right (para)hippocampus and anterior insula/inferior frontal gyrus. This meta-analysis provides evidence for a specific and probably disease stage-dependent brain activation pattern related to the pathognomonic AD characteristic of episodic memory loss.
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.
G72 (syn. DAOA, D-amino acid oxidase activator) is a susceptibility gene for both schizophrenia and bipolar disorder. Diffusion tensor imaging studies hint at changes in fiber tract integrity in both disorders. We aimed to investigate whether a G72 susceptibility haplotype causes changes in fiber tract integrity in young healthy subjects. We compared fractional anisotropy in 47 subjects that were either homozygous for the M23/M24 risk haplotype (n = 20) or homozygous for M23(rs3918342)/M24(rs1421292) wild type (n = 27) using diffusion tensor imaging with 3 T. Tract-based spatial statistics, a method especially developed for diffusion data analysis, was used to delineate the major fiber tracts. We found clusters of increased FA values in homozygous risk haplotype carriers in the right periinsular region and in the right inferior parietal lobe (IPL). We did not find clusters indicating decreased FA values. The insula and the IPL have been implicated in both schizophrenia and bipolar pathophysiology. Increased FA values might reflect changes in dendritic morphology as previously described by in vitro studies. These findings further corroborate the hypothesis that a shared gene pool between schizophrenia and bipolar disorder might lead to neuroanatomic changes that confer an unspecific vulnerability for both disorders.
Uniform coordinate systems in neuroimaging research have enabled comprehensive systematic and quantitative meta-analyses. Such approaches are particularly relevant for neuropsychiatric diseases, the understanding of their symptoms, prediction and treatment. Behavioral variant frontotemporal dementia (bvFTD), a common neurodegenerative syndrome, is characterized by deep alterations in behavior and personality. Investigating this 'nexopathy' elucidates the healthy social and emotional brain.
Changes in fiber tract architecture have gained attention as a potentially important aspect of schizophrenia neuropathology. Although the exact pathogenesis of these abnormalities yet remains to be elucidated, a genetic component is highly likely. Neuregulin-1 (NRG1) is one of the best-validated schizophrenia susceptibility genes. We here report the impact of the Neuregulin-1 rs35753505 variant on white matter structure in healthy young individuals with no family history of psychosis.
Cerebral ischemia triggers a cascade of cellular processes, which induce neuroprotection, inflammation, apoptosis and regeneration. At the neural network level, lesions concomitantly induce cerebral plasticity. Yet, many stroke survivors are left with a permanent motor deficit, and only little is known about the neurobiological factors that determine functional outcome after stroke. Transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI) are non-invasive approaches that allow insights into the functional (re-) organization of the cortical motor system. We here combined neuronavigated TMS, MRI and analyses of connectivity to investigate to which degree recovery of hand function depends on corticospinal tract (CST) damage and biomarkers of cerebral plasticity like cortical excitability and motor network effective connectivity. As expected, individual motor performance of 12 stroke patients with persistent motor deficits was found to depend upon the degree of CST damage but also motor cortex excitability and interhemispheric connectivity. In addition, the data revealed a strong correlation between reduced ipsilesional motor cortex excitability and reduced interhemispheric inhibition in severely impaired patients. Interindividual differences in ipsilesional motor cortex excitability were stronger related to the motor deficit than abnormal interhemispheric connectivity or CST damage. Multivariate linear regression analysis combining the three factors accounted for more than 80 % of the variance in functional impairment. The inter-relation of cortical excitability and reduced interhemispheric inhibition provides direct multi-modal evidence for the disinhibition theory of the contralesional hemisphere following stroke. Finally, our data reveal a key mechanism (i.e., the excitability-related reduction in interhemispheric inhibition) accounting for the rehabilitative potential of novel therapeutic approaches which aim at modulating cortical excitability in stroke patients.
Recent evidence suggests considerable overlap between the default mode network (DMN) and regions involved in social, affective and introspective processes. We considered these overlapping regions as the social-affective part of the DMN. In this study, we established a robust mapping of the underlying brain network formed by these regions and those strongly connected to them (the extended social-affective default network). We first seeded meta-analytic connectivity modeling and resting-state analyses in the meta-analytically defined DMN regions that showed statistical overlap with regions associated with social and affective processing. Consensus connectivity of each seed was subsequently delineated by a conjunction across both connectivity analyses. We then functionally characterized the ensuing regions and performed several cluster analyses. Among the identified regions, the amygdala/hippocampus formed a cluster associated with emotional processes and memory functions. The ventral striatum, anterior cingulum, subgenual cingulum and ventromedial prefrontal cortex formed a heterogeneous subgroup associated with motivation, reward and cognitive modulation of affect. Posterior cingulum/precuneus and dorsomedial prefrontal cortex were associated with mentalizing, self-reference and autobiographic information. The cluster formed by the temporo-parietal junction and anterior middle temporal sulcus/gyrus was associated with language and social cognition. Taken together, the current work highlights a robustly interconnected network that may be central to introspective, socio-affective, that is, self- and other-related mental processes.
Healthy aging is associated with decline in basic motor functioning and higher motor control. Here, we investigated age-related differences in the brain-wide functional connectivity (FC) pattern of the subthalamic nucleus (STN), which plays an important role in motor response control. As earlier studies revealed functional coupling between STN and basal ganglia, which both are known to influence the conservativeness of motor responses on a superordinate level, we tested the hypothesis that STN FC with the striatum becomes dysbalanced with age. To this end, we performed a seed-based resting-state analysis of fMRI data from 361 healthy adults (mean age: 41.8, age range: 18-85) using bilateral STN as the seed region of interest. Age was included as a covariate to identify regions showing age-related changes of FC with the STN seed. The analysis revealed positive FC of the STN with several previously described subcortical and cortical regions like the anterior cingulate and sensorimotor cortex, as well as not-yet reported regions including central and posterior insula. With increasing age, we observed reduced positive FC with caudate nucleus, thalamus, and insula as well as increased positive FC with sensorimotor cortex and putamen. Furthermore, an age-related reduction of negative FC was found with precuneus and posterior cingulate cortex. We suggest that this reduced de-coupling of brain areas involved in self-relevant but motor-unrelated cognitive processing (i.e. precuneus and posterior cingulate cortex) from the STN motor network may represent a potential mechanism behind the age-dependent decline in motor performance. At the same time, older adults appear to compensate for this decline by releasing superordinate motor control areas, in particular caudate nucleus and insula, from STN interference while increasing STN-mediated response control over lower level motor areas like sensorimotor cortex and putamen.
Neural characteristics of verbal creativity as assessed by word generation tasks have been recently identified, but differences in resting-state functional connectivity (rFC) between experts and non-experts in creative writing have not been reported yet. Previous electroencephalography (EEG) coherence measures during rest demonstrated a decreased cooperation between brain areas in association with creative thinking ability. Here, we used resting-state functional magnetic resonance imaging to compare 20 experts in creative writing and 23 age-matched non-experts with respect to rFC strengths within a brain network previously found to be associated with creative writing. Decreased rFC for experts was found between areas 44 of both hemispheres. Increased rFC for experts was observed between right hemispheric caudate and intraparietal sulcus. Correlation analysis of verbal creativity indices (VCIs) with rFC values in the expert group revealed predominantly negative associations, particularly of rFC between left area 44 and left temporal pole. Overall, our data support previous findings of reduced connectivity between interhemispheric areas and increased right-hemispheric connectivity during rest in highly verbally creative individuals.
The ongoing 1000 brains study (1000BRAINS) is an epidemiological and neuroscientific investigation of structural and functional variability in the human brain during aging. The two recruitment sources are the 10-year follow-up cohort of the German Heinz Nixdorf Recall (HNR) Study, and the HNR MultiGeneration Study cohort, which comprises spouses and offspring of HNR subjects. The HNR is a longitudinal epidemiological investigation of cardiovascular risk factors, with a comprehensive collection of clinical, laboratory, socioeconomic, and environmental data from population-based subjects aged 45-75 years on inclusion. HNR subjects underwent detailed assessments in 2000, 2006, and 2011, and completed annual postal questionnaires on health status. 1000BRAINS accesses these HNR data and applies a separate protocol comprising: neuropsychological tests of attention, memory, executive functions and language; examination of motor skills; ratings of personality, life quality, mood and daily activities; analysis of laboratory and genetic data; and state-of-the-art magnetic resonance imaging (MRI, 3 Tesla) of the brain. The latter includes (i) 3D-T1- and 3D-T2-weighted scans for structural analyses and myelin mapping; (ii) three diffusion imaging sequences optimized for diffusion tensor imaging, high-angular resolution diffusion imaging for detailed fiber tracking and for diffusion kurtosis imaging; (iii) resting-state and task-based functional MRI; and (iv) fluid-attenuated inversion recovery and MR angiography for the detection of vascular lesions and the mapping of white matter lesions. The unique design of 1000BRAINS allows: (i) comprehensive investigation of various influences including genetics, environment and health status on variability in brain structure and function during aging; and (ii) identification of the impact of selected influencing factors on specific cognitive subsystems and their anatomical correlates.
In the recent perceptual decision-making literature, a fronto-parietal network is typically reported to primarily represent the neural substrate of human perceptual decision-making. However, the view that only cortical areas are involved in perceptual decision-making has been challenged by several neurocomputational models which all argue that the basal ganglia play an essential role in perceptual decisions. To consolidate these different views, we conducted an Activation Likelihood Estimation (ALE) meta-analysis on the existing neuroimaging literature. The results argue in favor of the involvement of a frontal-parietal network in general perceptual decision-making that is possibly complemented by the basal ganglia, and modulated in substantial parts by task difficulty. In contrast, expectation of reward, an important aspect of many decision-making processes, shows almost no overlap with the general perceptual decision-making network.
Abnormalities in the brain's attention network may represent early identifiable neurobiological impairments in individuals at increased risk for schizophrenia or bipolar disorder. Here, we provide evidence of dysfunctional regional and network function in adolescents at higher genetic risk for schizophrenia or bipolar disorder [henceforth higher risk (HGR)]. During fMRI, participants engaged in a sustained attention task with variable demands. The task alternated between attention (120?s), visual control (passive viewing; 120?s), and rest (20?s) epochs. Low and high demand attention conditions were created using the rapid presentation of two- or three-digit numbers. Subjects were required to detect repeated presentation of numbers. We demonstrate that the recruitment of cortical and striatal regions are disordered in HGR: relative to typical controls (TC), HGR showed lower recruitment of the dorsal prefrontal cortex, but higher recruitment of the superior parietal cortex. This imbalance was more dramatic in the basal ganglia. There, a group by task demand interaction was observed, such that increased attention demand led to increased engagement in TC, but disengagement in HGR. These activation studies were complemented by network analyses using dynamic causal modeling. Competing model architectures were assessed across a network of cortical-striatal regions, distinguished at a second level using random-effects Bayesian model selection. In the winning architecture, HGR were characterized by significant reductions in coupling across both frontal-striatal and frontal-parietal pathways. The effective connectivity analyses indicate emergent network dysconnection, consistent with findings in patients with schizophrenia. Emergent patterns of regional dysfunction and dysconnection in cortical-striatal pathways may provide functional biological signatures in the adolescent risk-state for psychiatric illness.
Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.
Functional neuroimaging research on the neural basis of social evaluation has traditionally focused on face perception paradigms. Thus, little is known about the neurobiology of social evaluation processes based on auditory cues, such as voices. To investigate the top-down effects of social trait judgments on voices, hemodynamic responses of 44 healthy participants were measured during social trait (trustworthiness [TR] and attractiveness [AT]), emotional (happiness, HA), and cognitive (age, AG) voice judgments. Relative to HA and AG judgments, TR and AT judgments both engaged the bilateral inferior parietal cortex (IPC; area PGa) and the dorsomedial prefrontal cortex (dmPFC) extending into the perigenual anterior cingulate cortex. This dmPFC activation overlapped with previously reported areas specifically involved in social judgments on faces. Moreover, social trait judgments were expected to share neural correlates with emotional HA and cognitive AG judgments. Comparison of effects pertaining to social, social-emotional, and social-cognitive appraisal processes revealed a dissociation of the left IPC into 3 functional subregions assigned to distinct cytoarchitectonic subdivisions. In total, the dmPFC is proposed to assume a central role in social attribution processes across sensory qualities. In social judgments on voices, IPC activity shifts from rostral processing of more emotional judgment facets to caudal processing of more cognitive judgment facets.
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.
Schizophrenia is characterized by marked deficits in executive and psychomotor functions, as demonstrated for goal-directed actions in the antisaccade task. Recent studies, however, suggest that this deficit represents only one manifestation of a general deficit in stimulus-response integration and volitional initiation of motor responses. We here used functional magnetic resonance imaging to investigate brain activation patterns during a manual stimulus-response compatibility task in 18 schizophrenic patients and 18 controls. We found that across groups incongruent vs. congruent responses recruited a bilateral network consisting of dorsal fronto-parietal circuits as well as bilateral anterior insula, dorsolateral prefrontal cortex (DLPFC) and the presupplementary motor area (preSMA). When testing for the main-effect across all conditions, patients showed significantly lower activation of the right DLPFC and, in turn, increased activation in a left hemispheric network including parietal and premotor areas as well as the preSMA. For incongruent responses patients showed significantly increased activation in a similar left hemispheric network, as well as additional activation in parietal and premotor regions in the right hemisphere. The present study reveals that hypoactivity in the right DLPFC in schizophrenic patients is accompanied by hyperactivity in several fronto-parietal regions associated with task execution. Impaired top-down control due to a dysfunctional DLPFC might thus be partly compensated by an up-regulation of task-relevant regions in schizophrenic patients.
Emotional reactivity and the ability to modulate an emotional state, which are important factors for psychological well-being, are often dysregulated in psychiatric disorders. Neural correlates of emotional states have mostly been studied at the group level, thereby neglecting individual differences in the intensity of emotional experience. This study investigates the relationship between brain activity and interindividual variation in subjective affect ratings. A standardized mood induction (MI) procedure, using positive facial expression and autobiographical memories, was applied to 54 healthy participants (28 female), who rated their subjective affective state before and after the MI. We performed a regression analysis with brain activation during MI and changes in subjective affect ratings. An increase in positive affective ratings correlated with activity in the amygdala, hippocampus and the fusiform gyrus (FFG), whereas reduced positive affect correlated with activity of the subgenual anterior cingulate cortex. Activations in the amygdala, hippocampus and FFG are possibly linked to strategies adopted by the participants to achieve mood changes. Subgenual cingulate cortex activation has been previously shown to relate to rumination. This finding is in line with previous observations of the subgenual cingulates role in emotion regulation and its clinical relevance to therapy and prognosis of mood disorders.
Major depression goes along with affective and social-cognitive deficits. Most research on affective deficits in depression has, however, only focused on unimodal emotion processing, whereas in daily life, emotional perception is often highly dependent on the evaluation of multimodal inputs. We thus investigated emotional audiovisual integration in patients with depression and healthy subjects. Subjects rated the expression of happy, neutral and fearful faces while concurrently being exposed to emotional or neutral sounds. Results demonstrated group differences in left inferior frontal gyrus and inferior parietal cortex when comparing incongruent to congruent happy facial conditions, mainly due to a failure of patients to deactivate these regions in response to congruent stimulus pairs. Moreover, healthy subjects decreased activation in right posterior superior temporal gyrus/sulcus and midcingulate cortex when an emotional stimulus was paired with a neutral rather than another emotional one. In contrast, patients did not show such deactivation when neutral stimuli were integrated. These results demonstrate aberrant neural response in audiovisual processing in depression, indicated by failure to deactivate regions involved in inhibition and salience processing when congruent and neutral audiovisual stimuli pairs are integrated, providing a possible mechanism of constant arousal and readiness to act in this patient group.
Motor skills are mediated by a dynamic and finely regulated interplay of the primary motor cortex (M1) with various cortical and subcortical regions engaged in movement preparation and execution. To date, data elucidating the dynamics in the motor network that enable movements at different levels of behavioral performance remain scarce. We here used functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to investigate effective connectivity of key motor areas at different movement frequencies performed by right-handed subjects (n=36) with the left or right hand. The network of interest consisted of motor regions in both hemispheres including M1, supplementary motor area (SMA), ventral premotor cortex (PMv), motor putamen, and motor cerebellum. The connectivity analysis showed that performing hand movements at higher frequencies was associated with a linear increase in neural coupling strength from premotor areas (SMA, PMv) contralateral to the moving hand and ipsilateral cerebellum towards contralateral, active M1. In addition, we found hemispheric differences in the amount by which the coupling of premotor areas and M1 was modulated, depending on which hand was moved. Other connections were not modulated by changes in motor performance. The results suggest that a stronger coupling, especially between contralateral premotor areas and M1, enables increased motor performance of simple unilateral hand movements.
The diversity of chronic pain syndromes and the methods employed to study them make integrating experimental findings challenging. This study performed coordinate-based meta-analyses using voxel-based morphometry imaging results to examine gray matter volume (GMV) differences between chronic pain patients and healthy controls. There were 12 clusters where GMV was decreased in patients compared with controls, including many regions thought to be part of the "pain matrix" of regions involved in pain perception, but also including many other regions that are not commonly regarded as pain-processing areas. The right hippocampus and parahippocampal gyrus were the only regions noted to have increased GMV in patients. Functional characterizations were implemented using the BrainMap database to determine which behavioral domains were significantly represented in these regions. The most common behavioral domains associated with these regions were cognitive, affective, and perceptual domains. Because many of these regions are not classically connected with pain and because there was such significance in functionality outside of perception, it is proposed that many of these regions are related to the constellation of comorbidities of chronic pain, such as fatigue and cognitive and emotional impairments. Further research into the mechanisms of GMV changes could provide a perspective on these findings.
Patients with the unresponsive wakefulness syndrome (UWS; formerly vegetative state) or in a minimally conscious state (MCS) open their eyes spontaneously but show no (UWS) or only marginal (MCS) signs of awareness. Because these states can become permanent, residual information processing capacities need to be determined, and reliable outcome predictors need to be found. We assessed higher-order cortical information processing in UWS or MCS in a large group of patients using electroencephalographic event-related potentials (ERPs) and determined their long-term prognostic value for recovery.
Several independent studies have demonstrated that small amounts of in-scanner motion systematically bias estimates of resting-state functional connectivity. This confound is of particular importance for studies of neurodevelopment in youth because motion is strongly related to subject age during this period. Critically, the effects of motion on connectivity mimic major findings in neurodevelopmental research, specifically an age-related strengthening of distant connections and weakening of short-range connections. Here, in a sample of 780 subjects ages 8-22, we re-evaluate patterns of change in functional connectivity during adolescent development after rigorously controlling for the confounding influences of motion at both the subject and group levels. We find that motion artifact inflates both overall estimates of age-related change as well as specific distance-related changes in connectivity. When motion is more fully accounted for, the prevalence of age-related change as well as the strength of distance-related effects is substantially reduced. However, age-related changes remain highly significant. In contrast, motion artifact tends to obscure age-related changes in connectivity associated with segregation of functional brain modules; improved preprocessing techniques allow greater sensitivity to detect increased within-module connectivity occurring with development. Finally, we show that subjects age can still be accurately estimated from the multivariate pattern of functional connectivity even while controlling for motion. Taken together, these results indicate that while motion artifact has a marked and heterogeneous impact on estimates of connectivity change during adolescence, functional connectivity remains a valuable phenotype for the study of neurodevelopment.
Cytoarchitectonic area 44 of Brocas region in the left inferior frontal gyrus is known to be involved in several functional domains including language, action and music processing. We investigated whether this functional heterogeneity is reflected in distinct modules within cytoarchitectonically defined left area 44 using meta-analytic connectivity-based parcellation (CBP). This method relies on identifying the whole-brain co-activation pattern for each area 44 voxel across a wide range of functional neuroimaging experiments and subsequently grouping the voxels into distinct clusters based on the similarity of their co-activation patterns. This CBP analysis revealed that five separate clusters exist within left area 44. A post-hoc functional characterization and functional connectivity analysis of these five clusters was then performed. The two posterior clusters were primarily associated with action processes, in particular with phonology and overt speech (posterior-dorsal cluster) and with rhythmic sequencing (posterior-ventral cluster). The three anterior clusters were primarily associated with language and cognition, in particular with working memory (anterior-dorsal cluster), with detection of meaning (anterior-ventral cluster) and with task switching/cognitive control (inferior frontal junction cluster). These five clusters furthermore showed specific and distinct connectivity patterns. The results demonstrate that left area 44 is heterogeneous, thus supporting anatomical data on the molecular architecture of this region, and provide a basis for more specific interpretations of activations localized in area 44.
The right temporo-parietal junction (RTPJ) is consistently implicated in two cognitive domains, attention and social cognitions. We conducted multi-modal connectivity-based parcellation to investigate potentially separate functional modules within RTPJ implementing this cognitive dualism. Both task-constrained meta-analytic coactivation mapping and task-free resting-state connectivity analysis independently identified two distinct clusters within RTPJ, subsequently characterized by network mapping and functional forward/reverse inference. Coactivation mapping and resting-state correlations revealed that the anterior cluster increased neural activity concomitantly with a midcingulate-motor-insular network, functionally associated with attention, and decreased neural activity concomitantly with a parietal network, functionally associated with social cognition and memory retrieval. The posterior cluster showed the exact opposite association pattern. Our data thus suggest that RTPJ links two antagonistic brain networks processing external versus internal information.
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.
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.
The mechanisms driving cortical plasticity in response to brain stimulation are still incompletely understood. We here explored whether neural activity and connectivity in the motor system relate to the magnitude of cortical plasticity induced by repetitive transcranial magnetic stimulation (rTMS). Twelve right-handed volunteers underwent functional magnetic resonance imaging during rest and while performing a simple hand motor task. Resting-state functional connectivity, task-induced activation, and task-related effective connectivity were assessed for a network of key motor areas. We then investigated the effects of intermittent theta-burst stimulation (iTBS) on motor-evoked potentials (MEP) for up to 25 min after stimulation over left primary motor cortex (M1) or parieto-occipital vertex (for control). ITBS-induced increases in MEP amplitudes correlated negatively with movement-related fMRI activity in left M1. Control iTBS had no effect on M1 excitability. Subjects with better response to M1-iTBS featured stronger preinterventional effective connectivity between left premotor areas and left M1. In contrast, resting-state connectivity did not predict iTBS aftereffects. Plasticity-related changes in M1 following brain stimulation seem to depend not only on local factors but also on interconnected brain regions. Predominantly activity-dependent properties of the cortical motor system are indicative of excitability changes following induction of cortical plasticity with rTMS.
Auditory verbal hallucinations (AVH) are a hallmark of psychotic experience. Various mechanisms including misattribution of inner speech and imbalance between bottom-up and top-down factors in auditory perception potentially due to aberrant connectivity between frontal and temporo-parietal areas have been suggested to underlie AVH. Experimental evidence for disturbed connectivity of networks sustaining auditory-verbal processing is, however, sparse. We compared functional resting-state connectivity in 49 psychotic patients with frequent AVH and 49 matched controls. The analysis was seeded from the left middle temporal gyrus (MTG), thalamus, angular gyrus (AG) and inferior frontal gyrus (IFG) as these regions are implicated in extracting meaning from impoverished speech-like sounds. Aberrant connectivity was found for all seeds. Decreased connectivity was observed between the left MTG and its right homotope, between the left AG and the surrounding inferior parietal cortex (IPC) and the left inferior temporal gyrus, between the left thalamus and the right cerebellum, as well as between the left IFG and left IPC, and dorsolateral and ventrolateral prefrontal cortex (DLPFC/VLPFC). Increased connectivity was observed between the left IFG and the supplementary motor area (SMA) and the left insula and between the left thalamus and the left fusiform gyrus/hippocampus. The predisposition to experience AVH might result from decoupling between the speech production system (IFG, insula and SMA) and the self-monitoring system (DLPFC, VLPFC, IPC) leading to misattribution of inner speech. Furthermore, decreased connectivity between nodes involved in speech processing (AG, MTG) and other regions implicated in auditory processing might reflect aberrant top-down influences in AVH.
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.
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.
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.
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.
While the human medial prefrontal cortex (mPFC) is widely believed to be a key node of neural networks relevant for socio-emotional processing, its functional subspecialization is still poorly understood. We thus revisited the often assumed differentiation of the mPFC in social cognition along its ventral-dorsal axis. Our neuroinformatic analysis was based on a neuroimaging meta-analysis of perspective-taking that yielded two separate clusters in the ventral and dorsal mPFC, respectively. We determined each seed regions brain-wide interaction pattern by two complementary measures of functional connectivity: co-activation across a wide range of neuroimaging studies archived in the BrainMap database and correlated signal fluctuations during unconstrained ("resting") cognition. Furthermore, we characterized the functions associated with these two regions using the BrainMap database. Across methods, the ventral mPFC was more strongly connected with the nucleus accumbens, hippocampus, posterior cingulate cortex, and retrosplenial cortex, while the dorsal mPFC was more strongly connected with the inferior frontal gyrus, temporo-parietal junction, and middle temporal gyrus. Further, the ventral mPFC was selectively associated with reward related tasks, while the dorsal mPFC was selectively associated with perspective-taking and episodic memory retrieval. The ventral mPFC is therefore predominantly involved in bottom-up-driven, approach/avoidance-modulating, and evaluation-related processing, whereas the dorsal mPFC is predominantly involved in top-down-driven, probabilistic-scene-informed, and metacognition-related processing in social cognition.
Parkinsons disease (PD) is characterized by typical extrapyramidal motor features and increasingly recognized non-motor symptoms such as working memory (WM) deficits. Using functional magnetic resonance imaging (fMRI), we investigated differences in neuronal activation during a motor WM task in 23 non-demented PD patients and 23 age- and gender-matched healthy controls. Participants had to memorize and retype variably long visuo-spatial stimulus sequences after short or long delays (immediate or delayed serial recall). PD patients showed deficient WM performance compared to controls, which was accompanied by reduced encoding-related activation in WM-related regions. Mirroring slower motor initiation and execution, reduced activation in motor structures such as the basal ganglia and superior parietal cortex was detected for both immediate and delayed recall. Increased activation in limbic, parietal and cerebellar regions was found during delayed recall only. Increased load-related activation for delayed recall was found in the posterior midline and the cerebellum. Overall, our results demonstrate that impairment of WM in PD is primarily associated with a widespread reduction of task-relevant activation, whereas additional parietal, limbic and cerebellar regions become more activated relative to matched controls. While the reduced WM-related activity mirrors the deficient WM performance, the additional recruitment may point to either dysfunctional compensatory strategies or detrimental crosstalk from "default-mode" regions, contributing to the observed impairment.
Emotion in daily life is often expressed in a multimodal fashion. Consequently emotional information from one modality can influence processing in another. In a previous fMRI study we assessed the neural correlates of audio-visual integration and found that activity in the left amygdala is significantly attenuated when a neutral stimulus is paired with an emotional one compared to conditions where emotional stimuli were present in both channels. Here we used dynamic causal modelling to investigate the effective connectivity in the neuronal network underlying this emotion presence congruence effect. Our results provided strong evidence in favor of a model family, differing only in the interhemispheric interactions. All winning models share a connection from the bilateral fusiform gyrus (FFG) into the left amygdala and a non-linear modulatory influence of bilateral posterior superior temporal sulcus (pSTS) on these connections. This result indicates that the pSTS not only integrates multi-modal information from visual and auditory regions (as reflected in our model by significant feed-forward connections) but also gates the influence of the sensory information on the left amygdala, leading to attenuation of amygdala activity when a neutral stimulus is integrated. Moreover, we found a significant lateralization of the FFG due to stronger driving input by the stimuli (faces) into the right hemisphere, whereas such lateralization was not present for sound-driven input into the superior temporal gyrus. In summary, our data provides further evidence for a rightward lateralization of the FFG and in particular for a key role of the pSTS in the integration and gating of audio-visual emotional information.
In our article we considered the nature and the functional anatomy of "urges-for-action," both in the context of everyday behaviors such as yawning, swallowing, and micturition, and in relation to clinical disorders in which the urge-for-action is considered pathological (e.g., Tourette syndrome), and we argued for a key role for the insular and cingulate cortices in experiencing the urge-for-action. Here we seek to address some of the key points raised within several of the interesting commentaries on, and challenges to, our paper.
Over the past two decades, several functional neuroimaging experiments demonstrated changes in neural activity in stroke patients with motor deficits. Conclusions from single experiments are usually constrained by small sample sizes and high variability across studies. Here, we used coordinate-based activation likelihood estimation meta-analyses to provide a quantitative synthesis of the current literature on motor-related neural activity after stroke. Of over 1000 PubMed search results through January 2011, 36 studies reported standardized whole-brain group coordinates. Meta-analyses were performed on 54 experimental contrasts for movements of the paretic upper limb (472 patients, 452 activation foci) and on 20 experiments comparing activation between patients and healthy controls (177 patients, 113 activation foci). We computed voxelwise correlations between activation likelihood and motor impairment, time post-stroke, and task difficulty across samples. Patients showed higher activation likelihood in contralesional primary motor cortex (M1), bilateral ventral premotor cortex and supplementary motor area (SMA) relative to healthy subjects. Activity in contralesional areas was more likely found for active than for passive tasks. Better motor performance was associated with greater activation likelihood in ipsilesional M1, pre-SMA, contralesional premotor cortex and cerebellum. Over time post-stroke, activation likelihood in bilateral premotor areas and medial M1 hand knob decreased. This meta-analysis shows that increased activation in contralesional M1 and bilateral premotor areas is a highly consistent finding after stroke despite high inter-study variance resulting from different fMRI tasks and motor impairment levels. However, a good functional outcome relies on the recruitment of the original functional network rather than on contralesional activity.
Perceiving someone elses gaze shift toward an object can influence how this object will be manipulated by the observer, suggesting a modulatory effect of a gaze-based social context on action control. High-functioning autism (HFA) is characterized by impairments of social interaction, which may be associated with an inability to automatically integrate socially relevant nonverbal cues when generating actions. To explore these hypotheses, we made use of a stimulus-response compatibility paradigm in which a comparison group and patients with HFA were asked to generate spatially congruent or incongruent motor responses to changes in a face, a face-like and an object stimulus. Results demonstrate that while in the comparison group being looked at by a virtual other leads to a reduction of reaction time costs associated with generating a spatially incongruent response, this effect is not present in the HFA group. We suggest that this modulatory effect of social gaze on action control might play an important role in direct social interactions by helping to coordinate ones actions with those of someone else. Future research should focus on these implicit mechanisms of interpersonal alignment (online social cognition), which might be at the very heart of the difficulties individuals with autism experience in everyday social encounters.
Several common neuropsychiatric disorders (e.g., obsessive-compulsive disorder, Tourette syndrome (TS), autistic spectrum disorder) are associated with unpleasant bodily sensations that are perceived as an urge for action. Similarly, many of our everyday behaviors are also characterized by bodily sensations that we experience as urges for action. Where do these urges originate? In this paper, we consider the nature and the functional anatomy of "urges-for-action," both in the context of everyday behaviors such as yawning, swallowing, and micturition, and in relation to clinical disorders in which the urge-for-action is considered pathological and substantially interferes with activities of daily living (e.g., TS). We review previous frameworks for thinking about behavioral urges and demonstrate that there is considerable overlap between the functional anatomy of urges associated with everyday behaviors such as swallowing, yawning, and micturition, and those urges associated with the generation of tics in TS. Specifically, we show that the limbic sensory and motor regions-insula and mid-cingulate cortex-are common to all of these behaviors, and we argue that this "motivation-for-action" network should be considered distinct from an "intentional action" network, associated with regions of premotor and parietal cortex, which may be responsible for the perception of "willed intention" during the execution of goal-directed actions.
When stimulus intensity in simple reaction-time tasks randomly varies across trials, detection speed usually improves after a low-intensity trial. With auditory stimuli, this improvement was often found to be asymmetric, being greater on current low-intensity trials. Our study investigated (1) whether asymmetric sequential intensity adaptation also occurs with visual stimuli; (2) whether these adjustments reflect decision-criterion shifts or, rather, a modulation of perceptual sensitivity; and (3) how sequential intensity adaptation and its underlying mechanisms are affected by mental fatigue induced through prolonged performance. In a continuous speeded detection task with randomly alternating high- and low-intensity visual stimuli, the reaction-time benefit after low-intensity trials was greater on subsequent low- than high-intensity trials. This asymmetry, however, only developed with time on task (TOT). Signal-detection analyses showed that the decision criterion transiently became more liberal after a low-intensity trial, whereas observer sensitivity increased when the preceding and current stimulus were of equal intensity. TOT-induced mental fatigue only affected sensitivity, which dropped more on low- than on high-intensity trials. This differential fatigue-related sensitivity decrease selectively enhanced the impact of criterion down-shifts on low-intensity trials, revealing how the interplay of two perceptual mechanisms and their modulation by fatigue combine to produce the observed overall pattern of asymmetric performance adjustments to varying visual intensity in continuous speeded detection. Our results have implications for similar patterns of sequential demand adaptation in other cognitive domains as well as for real-world prolonged detection performance.
Successful human interaction is based on correct recognition, interpretation, and appropriate reaction to facial affect. In depression, social skill deficits are among the most restraining symptoms leading to social withdrawal, thereby aggravating social isolation and depressive affect. Dysfunctional approach and withdrawal tendencies to emotional stimuli have been documented, but the investigation of their neural underpinnings has received limited attention. We performed an fMRI study including 15 depressive patients and 15 matched, healthy controls. All subjects performed two tasks, an implicit joystick task as well as an explicit rating task, both using happy, neutral, and angry facial expressions. Behavioral data analysis indicated a significant group effect, with depressed patients showing more withdrawal than controls. Analysis of the functional data revealed significant group effects for both tasks. Among other regions, we observed significant group differences in amygdala activation, with patients showing less response particularly during approach to happy faces. Additionally, significant correlations of amygdala activation with psychopathology emerged, suggesting that more pronounced symptoms are accompanied by stronger decreases of amygdala activation. Hence, our results demonstrate that depressed patients show dysfunctional social approach and withdrawal behavior, which in turn may aggravate the disorder by negative social interactions contributing to isolation and reinforcing cognitive biases.
A widely used technique for coordinate-based meta-analysis of neuroimaging data is activation likelihood estimation (ALE), which determines the convergence of foci reported from different experiments. ALE analysis involves modelling these foci as probability distributions whose width is based on empirical estimates of the spatial uncertainty due to the between-subject and between-template variability of neuroimaging data. ALE results are assessed against a null-distribution of random spatial association between experiments, resulting in random-effects inference. In the present revision of this algorithm, we address two remaining drawbacks of the previous algorithm. First, the assessment of spatial association between experiments was based on a highly time-consuming permutation test, which nevertheless entailed the danger of underestimating the right tail of the null-distribution. In this report, we outline how this previous approach may be replaced by a faster and more precise analytical method. Second, the previously applied correction procedure, i.e. controlling the false discovery rate (FDR), is supplemented by new approaches for correcting the family-wise error rate and the cluster-level significance. The different alternatives for drawing inference on meta-analytic results are evaluated on an exemplary dataset on face perception as well as discussed with respect to their methodological limitations and advantages. In summary, we thus replaced the previous permutation algorithm with a faster and more rigorous analytical solution for the null-distribution and comprehensively address the issue of multiple-comparison corrections. The proposed revision of the ALE-algorithm should provide an improved tool for conducting coordinate-based meta-analyses on functional imaging data.
Face-derived information on trustworthiness and attractiveness crucially influences social interaction. It is, however, unclear to what degree the functional neuroanatomy of these complex social judgments on faces reflects genuine social versus basic emotional and cognitive processing. To disentangle social from nonsocial contributions, we assessed commonalities and differences between the functional networks activated by judging social (trustworthiness, attractiveness), emotional (happiness), and cognitive (age) facial traits. Relative to happiness and age evaluations, both trustworthiness and attractiveness judgments selectively activated the dorsomedial prefrontal cortex and inferior frontal gyrus, forming a core social cognition network. Moreover, they also elicited a higher amygdalar response than even the emotional control condition. Both social judgments differed, however, in their top-down modulation of face-sensitive regions: trustworthiness judgments recruited the posterior superior temporal sulcus, whereas attractiveness judgments recruited the fusiform gyrus. Social and emotional judgments converged and, therefore, likely interact in the ventromedial prefrontal cortex. Social and age judgments, on the other hand, commonly engaged the anterior insula, inferior parietal cortex, and dorsolateral prefrontal cortex, which appear to subserve more cognitive aspects in social evaluation. These findings demonstrate the modularity of social judgments on human faces by separating the neural correlates of social, face-specific, emotional, and cognitive processing facets.
Schizophrenia is a neuropsychiatric disorder entailing progressive psychotic, cognitive and affective symptoms. Several imaging studies identified brain structure abnormalities in schizophrenia patients, particularly in fronto-temporal regions and evidence for progressive anatomical changes. Here, we synthesised these findings by quantitative coordinate-based meta-analysis, assessing regions of consistently reported brain structure changes, their physiological functions and the correlation of their likelihood with disease duration. The meta-analysis revealed four significant clusters of convergent grey matter reduction, while one cluster indicated higher grey matter values in patients. A voxel-wise analysis revealed a correlation between grey matter reduction and disease duration in the left anterior insula. Functional characterisation revealed significant association with reward, affective processing and language functions. The current analysis allowed the identification of consistent morphometric changes across a large sample of studies in regions that are associated with neurophysiological functions that are altered as hallmarks of schizophrenia psychopathology. The observation that the location of presumably progressive pathology is functionally linked to language and emotion is well in line with increasing deficits in these domains with disease progression in schizophrenia.
Understanding the organization of the human brain is the fundamental prerequisite for appreciating the neural dysfunctions underlying neurological or psychiatric disorders. One major challenge in this context is the presence of multiple organizational aspects, in particular the regional differentiation in structure and function on one hand and the integration by inter-regional connectivity on the other. We here review these fundamental distinctions and introduce current methods for mapping regional specialization. The main focus of this review is to provide an overview over the different concepts and methods for assessing connections and interactions in the brain, in particular anatomical, functional and effective connectivity. In this context, we focus less on technical details and more on the comparative description of strengths and weaknesses of different aspects of connectivity as well as different methods for examining a particular aspect. This overview closes by raising several open questions on the conceptual and empirical relationship between different approaches towards understanding brain structure, function and connectivity.
An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific mental functions. However, it was recently demonstrated that similar brain networks can be extracted from resting state data and data extracted from thousands of task-based neuroimaging experiments archived in the BrainMap database. Here, we present a full functional explication of these intrinsic connectivity networks at a standard low order decomposition using a neuroinformatics approach based on the BrainMap behavioral taxonomy as well as a stratified, data-driven ordering of cognitive processes. Our results serve as a resource for functional interpretations of brain networks in resting state studies and future investigations into mental operations and the tasks that drive them.
Neuroimaging researchers have developed rigorous community data and metadata standards that encourage meta-analysis as a method for establishing robust and meaningful convergence of knowledge of human brain structure and function. Capitalizing on these standards, the BrainMap project offers databases, software applications, and other associated tools for supporting and promoting quantitative coordinate-based meta-analysis of the structural and functional neuroimaging literature.
Mild cognitive impairment (MCI) is an acquired syndrome characterised by cognitive decline not affecting activities of daily living. Using a quantitative meta-analytic approach, we aimed to identify consistent neuroanatomic correlates of MCI and how they are related to cognitive dysfunction. The meta-analysis enrols 22 studies, involving 917 MCI (848 amnestic MCI) patients and 809 healthy controls. Only studies investigating local changes in grey matter and reporting whole-brain results in stereotactic coordinates were included and analysed using the activation likelihood estimation approach. Probabilistic cytoarchitectonic maps were used to compare the localization of the obtained significant effects to histological areas. A correlation between the probability of grey matter changes and cognitive performance of MCI patients was performed. In MCI patients, the meta-analysis revealed three significant clusters of convergent grey matter atrophy, which were mainly situated in the bilateral amygdala and hippocampus, extending to the left medial temporal pole and thalamus, as well as in the bilateral precuneus. A sub-analysis in only amnestic MCI revealed a similar pattern. A voxel-wise analysis revealed a correlation between grey matter reduction and cognitive decline in the right hippocampus and amygdala as well as in the left thalamus. This study provides convergent evidence of a distinct neuroanatomical pattern in MCI. The correlation analysis with cognitive-mnestic decline further highlights the impact of limbic structures and the linkage with data from a functional neuroimaging database provides additional insight into underlying functions. Although different pathologies are underlying MCI, the observed neuroanatomical pattern of structural changes may reflect the common clinical denominator of cognitive impairment.
The capacity of drug cues to elicit drug-seeking behavior is believed to play a fundamental role in drug dependence; yet the neurofunctional basis of human drug cue-reactivity is not fully understood. We performed a meta-analysis to identify brain regions that are consistently activated by presentation of drug cues. Studies involving treatment-seeking and nontreatment-seeking substance users were contrasted to determine whether there were consistent differences in the neural response to drug cues between these populations. Finally, to assess the neural basis of craving, consistency across studies in brain regions that show correlated activation with craving was assessed.
Psychomotor retardation is a prominent clinical feature of major depression. While several studies investigated these deficits, differences between internally and externally triggered response selection and initiation are less well understood. In the current study, we delineate internally vs. externally driven response selection and initiation in depression and their relation to basic psychomotor functioning.
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