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.

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.

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.

A quantitative meta-analysis and review of motor learning in the human brain.

Neuroimaging studies have improved our understanding of which brain structures are involved in motor learning. Despite this, questions remain regarding the areas that contribute consistently across paradigms with different task demands. For instance, sensorimotor tasks focus on learning novel movement kinematics and dynamics, while serial response time task (SRTT) variants focus on sequence learning. These differing task demands are likely to elicit quantifiably different patterns of neural activity on top of a potentially consistent core network. The current study identified consistent activations across 70 motor learning experiments using activation likelihood estimation (ALE) meta-analysis. A global analysis of all tasks revealed a bilateral cortical-subcortical network consistently underlying motor learning across tasks. Converging activations were revealed in the dorsal premotor cortex, supplementary motor cortex, primary motor cortex, primary somatosensory cortex, superior parietal lobule, thalamus, putamen and cerebellum. These activations were broadly consistent across task specific analyses that separated sensorimotor tasks and SRTT variants. Contrast analysis indicated that activity in the basal ganglia and cerebellum was significantly stronger for sensorimotor tasks, while activity in cortical structures and the thalamus was significantly stronger for SRTT variants. Additional conjunction analyses then indicated that the left dorsal premotor cortex was activated across all analyses considered, even when controlling for potential motor confounds. The highly consistent activation of the left dorsal premotor cortex suggests it is a critical node in the motor learning network.

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.

Activation likelihood estimation meta-analysis of motor-related neural activity after stroke.

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.

Alternate-form reliability of the Montreal cognitive assessment screening test in a clinical setting.

AIMS: The Montreal Cognitive Assessment (MoCA) has gained recognition for its validity in detecting cognitive impairment in several clinical populations. For serial assessments, alternate forms are needed to overcome possible practice effects. Our objective was to investigate the reliability of two German MoCA alternate forms for longitudinal assessment applications. METHODS: The original and one of two alternate forms of the MoCA were administered within a 60-min interval of a clinical interview in a counterbalanced order to 100 healthy elderly controls, 30 patients with mild cognitive impairment (MCI) and 30 patients with Alzheimer's disease (AD). The diagnosis of the majority of patients was supported by in vivo AD pathology biomarkers. RESULTS: There was a strong correlation between the alternate forms and the original MoCA in all groups, but particularly in the clinical samples. Total mean scores did not differ significantly between the MoCA versions, even taking into account the presentation order. As in previous studies, age and education influenced performance in the MoCA. The same pattern of group differences (controls > MCI > AD) was observed for each of the versions. CONCLUSION: All three forms can be reliably and interchangeably used in serial cognitive assessment, confirming the MoCA's applicability in research and clinical longitudinal approaches.

Comparison of functional and cytoarchitectonic maps of human visual areas V1, V2, V3d, V3v, and V4(v).

Cytoarchitectonic maps of human striate and extrastriate visual cortex based upon post-mortem brains can be correlated with functionally defined cortical areas using, for example, fMRI. We here assess the correspondence of anatomical maps of the visual cortex with functionally defined in vivo visual areas using retinotopic mapping. To this end, anatomical maximum probability maps (aMPM) derived from individual cytoarchitectonic maps of striate and extrastriate visual areas were compared with functional localisers for the early visual areas. Using fMRI, we delineated dorsal and ventral human retinotopic areas V1, V2, and V3, as well as a quarter-field visual field representation lateral to V3v, V4(v), in 24 healthy subjects. Based on these individual definitions, a functional maximum probability map (fMPM) was then computed in analogy to the aMPM. Functional and anatomical MPMs were highly correlated at group level: 78.5% of activated voxels in the fMPM were correctly assigned by the aMPM. The group aMPM was less effective in predicting functional retinotopic areas in the individual brain due to the large inter-individual variability in the location and extent of visual areas (mean overlap 32-69%). We conclude that cytoarchitectonic maps of striate and extrastriate visual areas may provide a valuable method for assigning functional group activations and thus add valuable a priori knowledge to the analysis of functional imaging data of the visual cortex.

Organizational principles of human visual cortex revealed by receptor mapping.

This receptorarchitectonic study of the human visual cortex investigated interareal differences in mean receptor concentrations and laminar distribution patterns of 16 neurotransmitter receptors in the dorsal and ventral parts of areas V1, V2, V3 as well as in adjoining areas V4 (ventrally) and V3A (dorsally). Both the functional hierarchy of these areas and a distinction between dorsal and ventral visual cortices were reflected by significant receptorarchitectonic differences. The observation that dorso-ventral differences existed in all extrastriate areas (including V2) is particularly important for the discussion about the relationship between dorsal and ventral V3 as it indicates that a receptorarchitectonic distinction between the ventral and dorsal visual cortices is present in but not specific to V3. This molecular specificity is mirrored by previously reported differences in retinal microstructure and functional differences as revealed in behavioral experiments demonstrating differential advantages for stimulus processing in the upper and lower visual fields. We argue that these anatomical and functional differences may be regarded as the result of an evolutionary optimization adapting to the processing of the most relevant stimuli occurring in the upper and lower visual fields.

Interindividual differences in cognitive flexibility: influence of gray matter volume, functional connectivity and trait impulsivity.

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.

Specific and disease stage-dependent episodic memory-related brain activation patterns in Alzheimer's disease: a coordinate-based meta-analysis.

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.

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.

Cytoarchitectonic mapping of the human dorsal extrastriate cortex.

The dorsal visual stream consists of several functionally specialized areas, but most of their cytoarchitectonic correlates have not yet been identified in the human brain. The cortex adjacent to Brodmann area 18/V2 was therefore analyzed in serial sections of ten human post-mortem brains using morphometrical and multivariate statistical analyses for the definition of areal borders. Two previously unknown cytoarchitectonic areas (hOc3d, hOc4d) were detected. They occupy the medial and, to a smaller extent, lateral surface of the occipital lobe. The larger area, hOc3d, is located dorso-lateral to area V2 in the region of superior and transverse occipital, as well as parieto-occipital sulci. Area hOc4d was identified rostral to hOc3d; it differed from the latter by larger pyramidal cells in lower layer III, thinner layers V and VI, and a sharp cortex-white-matter borderline. The delineated areas were superimposed in the anatomical MNI space, and probabilistic maps were calculated. They show a relatively high intersubject variability in volume and position. Based on their location and neighborhood relationship, areas hOc3d and hOc4d are putative anatomical substrates of functionally defined areas V3d and V3a, a hypothesis that can now be tested by comparing probabilistic cytoarchitectonic maps and activation studies of the living human brain.

Diminished activation of motor working-memory networks in Parkinson's disease.

Parkinson's 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.

Laminar distribution and co-distribution of neurotransmitter receptors in early human visual cortex.

The laminar distributions of 16 neurotransmitter receptor binding sites were analysed in visual cortical areas V1-V3 by quantitative in vitro receptor autoradiography. For each receptor (glutamatergic: AMPA, kainate, NMDA; cholinergic: M1, M2, M3, nicotinic; GABAergic: GABAA, GABAB, benzodiazepine binding-sites; adrenergic: alpha1, alpha2; serotoninergic: 5-HT1A, 5-HT2; dopaminergic: D1; Adenosine: A1), density profiles extracted perpendicular to the cortical surface were compared to cyto- and myeloarchitectonic profiles sampled at corresponding cortical sites. When testing for differences in laminar distribution patterns, all receptor-density profiles differed significantly from the cyto- and myeloarchitectonic ones. These results indicate that receptor distribution is an independent feature of the cortical architecture not predictable by densities of cell bodies or myelinated fibres. Receptor co-distribution was studied by cluster analyses, revealing several groups of receptors, which showed similar laminar distribution patterns across all analysed areas (V1-V3). Other receptors were co-distributed in extrastriate but not primary visual cortex. Finally, some receptors were not co-distributed with any of the analysed other ones. A comparison of the laminar patterns of receptor binding sites in the human visual cortex with those reported for non-human primates and other mammals showed that the laminar distributions of cholinergic and glutamatergic receptors seem largely preserved, while serotoninergic and adrenergic receptors appear to be more variable between different species.

Ventral visual cortex in humans: cytoarchitectonic mapping of two extrastriate areas.

The extrastriate visual cortex forms a complex system enabling the analysis of visually presented objects. To gain deeper insight into the anatomical basis of this system, we cytoarchitectonically mapped the ventral occipital cortex lateral to BA 18/V2 in 10 human postmortem brains. The anatomical characterization of this part of the ventral stream was performed by examination of cell-body-stained histological sections using quantitative cytoarchitectonic analysis. First, the gray level index (GLI) was measured in the ventral occipital lobe. Cytoarchitectonic borders, i.e., significant changes in the cortical lamination pattern, were then identified using an observer-independent algorithm based on multivariate analysis of GLI profiles. Two distinct cytoarchitectonic areas (hOC3v, hOC4v) were characterized in the ventral extrastriate cortex lateral to BA 18/V2. Area hOC3v was found in the collateral sulcus. hOC4v was located in this sulcus and also covered the fusiform gyrus in more occipital sections. Topographically, these areas thus seem to represent the anatomical substrates of functionally defined areas, VP/V3v and V4/V4v. Following histological analysis, the delineated cytoarchitectonic areas were transferred to 3D reconstructions of the respective postmortem brains, which in turn were spatially normalized to the Montreal Neurological Institute reference space. A probabilistic map was generated for each area which describes how many brains had a representation of this area in a particular voxel. These maps can now be used to identify the anatomical correlates of functional activations observed in neuroimaging experiments to enable a more informed investigation into the many open questions regarding the organization of the human visual cortex.