Felix Hoffstaedter

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

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

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

The rostral cingulate cortex has been associated with a multitude of cognitive control functions. Recent neuroimaging data suggest that the anterior midcingulate cortex (aMCC) has a key role for cognitive aspects of movement generation, i.e., intentional motor control. We here tested the functional connectivity of this area using two complementary approaches: (1) resting‐state connectivity of the aMCC based on fMRI scans obtained in 100 subjects, and (2) functional connectivity in the context of explicit task conditions using meta‐analytic connectivity modeling (MACM) over 656 imaging experiment. Both approaches revealed a convergent functional network architecture of the aMCC with prefrontal, premotor and parietal cortices as well as anterior insula, area 44/45, cerebellum and dorsal striatum. To specifically test the role of the aMCCs task‐based functional connectivity in cognitive motor control, separate MACM analyses were conducted over “cognitive” and “action” related experimental paradigms. Both analyses confirmed the same task‐based connectivity pattern of the aMCC. While the “cognition” domain showed higher convergence of activity in supramodal association areas in prefrontal cortex and anterior insula, “action” related experiments yielded higher convergence in somatosensory and premotor areas. Secondly, to probe the functional specificity of the aMCCs convergent functional connectivity, it was compared with a neural network of intentional movement initiation. This exemplary comparison confirmed the involvement of the state independent FC network of the aMCC in the intentional generation of movements. In summary, the different experiments of the present study suggest that the aMCC constitute a key region in the network realizing intentional motor control. Hum Brain Mapp 35:2741–2753, 2014.

The Modular Neuroarchitecture of Social Judgments on Faces

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.

Dopaminergic modulation of motor network dynamics in Parkinson’s disease

Using connectivity analyses based on functional MRI, Michely et al. investigate dopaminergic modulation of neural network dynamics involved in motor control in Parkinson’s disease. The findings provide insights into the pathophysiology underlying bradykinesia and deficits in executive function, and help to explain why dopaminergic treatments have a greater effect on the former.

Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity

Human subgenual anterior cingulate cortex (sACC) is involved in affective experiences and fear processing. Functional neuroimaging studies view it as a homogeneous cortical entity. However, sACC comprises several distinct cyto- and receptorarchitectonical areas: 25, s24, s32, and the ventral portion of area 33. Thus, we hypothesized that the areas may also be connectionally and functionally distinct. We performed structural post mortem and functional in vivo analyses. We computed probabilistic maps of each area based on cytoarchitectonical analysis of ten post mortem brains. Maps, publicly available via the JuBrain atlas and the Anatomy Toolbox, were used to define seed regions of task-dependent functional connectivity profiles and quantitative functional decoding. sACC areas presented distinct co-activation patterns within widespread networks encompassing cortical and subcortical regions. They shared common functional domains related to emotion, perception and cognition. A more specific analysis of these domains revealed an association of s24 with sadness, and of s32 with fear processing. Both areas were activated during taste evaluation, and co-activated with the amygdala, a key node of the affective network. s32 co-activated with areas of the executive control network, and was associated with tasks probing cognition in which stimuli did not have an emotional component. Area 33 was activated by painful stimuli, and co-activated with areas of the sensorimotor network. These results support the concept of a connectional and functional specificity of the cyto- and receptorarchitectonically defined areas within the sACC, which can no longer be seen as a structurally and functionally homogeneous brain region.

Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression

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.

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

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

Transdiagnostic commonalities and differences in resting state functional connectivity of the default mode network in schizophrenia and major depression

Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculums role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression.

Resting-state network dysfunction in Alzheimer's disease: A systematic review and meta-analysis

We performed a systematic review and meta‐analysis of the Alzheimers disease (AD) literature to examine consistency of functional connectivity alterations in AD dementia and mild cognitive impairment, using resting‐state functional magnetic resonance imaging.

The intrinsic resting state voice network in Parkinson's disease

Over 90 percent of patients with Parkinsons disease experience speech‐motor impairment, namely, hypokinetic dysarthria characterized by reduced pitch and loudness. Resting‐state functional connectivity analysis of blood oxygen level‐dependent functional magnetic resonance imaging is a useful measure of intrinsic neural functioning. We utilized resting‐state functional connectivity modeling to analyze the intrinsic connectivity in patients with Parkinsons disease within a vocalization network defined by a previous meta‐analysis of speech (Brown et al., 2009). Functional connectivity of this network was assessed in 56 patients with Parkinsons disease and 56 gender‐, age‐, and movement‐matched healthy controls. We also had item 5 and 18 of the UPDRS, and the PDQ‐39 Communication subscale available for correlation with the voice network connectivity strength in patients. The within‐group analyses of connectivity patterns demonstrated a lack of subcortical–cortical connectivity in patients with Parkinsons disease. At the cortical level, we found robust (homotopic) interhemispheric connectivity but only inconsistent evidence for many intrahemispheric connections. When directly contrasted to the control group, we found a significant reduction of connections between the left thalamus and putamen, and cortical motor areas, as well as reduced right superior temporal gyrus connectivity. Furthermore, most symptom measures correlated with right putamen, left cerebellum, left superior temporal gyrus, right premotor, and left Rolandic operculum connectivity in the voice network. The results reflect the importance of (right) subcortical nodes and the superior temporal gyrus in Parkinsons disease, enhancing our understanding of the neurobiological underpinnings of vocalization impairment in Parkinsons disease. Hum Brain Mapp 36:1951–1962, 2015.