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

Effective connectivity of working memory performance: a DCM study of MEG data

Visual working memory (WM) engages several nodes of a large-scale network that includes frontal, parietal, and visual regions; however, little is understood about how these regions interact to support WM behavior. In particular, it is unclear whether network dynamics during WM maintenance primarily represent feedforward or feedback connections. This question has important implications for current debates about the relative roles of frontoparietal and visual regions in WM maintenance. In the current study, we investigated the network activity supporting WM using MEG data acquired while healthy subjects performed a multi-item delayed estimation WM task. We used computational modeling of behavior to discriminate correct responses (high accuracy trials) from two different types of incorrect responses (low accuracy and swap trials), and dynamic causal modeling of MEG data to measure effective connectivity. We observed behaviorally dependent changes in effective connectivity in a brain network comprising frontoparietal and early visual areas. In comparison with high accuracy trials, frontoparietal and frontooccipital networks showed disrupted signals depending on type of behavioral error. Low accuracy trials showed disrupted feedback signals during early portions of WM maintenance and disrupted feedforward signals during later portions of maintenance delay, while swap errors showed disrupted feedback signals during the whole delay period. These results support a distributed model of WM that emphasizes the role of visual regions in WM storage and where changes in large scale network configurations can have important consequences for memory-guided behavior.

Neural alterations underlying executive dysfunction in Parkinson's disease: A systematic review and coordinate-based meta-analysis of functional neuroimaging studies

Parkinson's Disease's (PD) neuropsychological profile is often characterized by altered performance in executive functions (EF) tasks, with a remarkable impact on patients' quality of life. To date, the available neuroimaging literature lacks conclusive evidence about neural patterns underlying EF deficits in PD. Here, we aimed to synthesize the results of PET/fMRI studies examining the differences in brain activation between PD patients and controls during EF tasks, focusing on the three main EF sub-components: cognitive flexibility, working memory, and response inhibition. We conducted a coordinate-based meta-analysis to assess the converging alterations in brain activity in PD patients compared to controls. We assessed the association between aberrant patterns of activity and the EF sub-domains. We found a significant association between hypoactivation patterns in PD converging at the level of the right inferior frontal gyrus in response inhibition tasks, whereas hypoactivation in the left inferior frontal gyrus was found in association with the cognitive flexibility domain. Our results confirm the existence of neural alterations in PD patients in relation to specific EF sub-domains.

Methods for decoding cortical gradients of functional connectivity

Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.

A strategy of model space search for dynamic causal modeling in task fMRI data exploratory analysis

Dynamic causal modeling (DCM) is a tool used for effective connectivity (EC) estimation in neuroimage analysis. But it is a model-driven analysis method, and the structure of the EC network needs to be determined in advance based on a large amount of prior knowledge. This characteristic makes it difficult to apply DCM to the exploratory brain network analysis. The exploratory analysis of DCM can be realized from two perspectives: one is to reduce the computational cost of the model; the other is to reduce the model space. From the perspective of model space reduction, a model space exploration strategy is proposed, including two algorithms. One algorithm, named GreedyEC, starts with reducing EC from full model, and the other, named GreedyROI, start with adding EC from one node model. Then the two algorithms were applied to the task state functional magnetic resonance imaging (fMRI) data of visual object recognition and selected the best DCM model from the perspective of model comparison based on Bayesian model compare method. Results show that combining the results of the two algorithms can further improve the effect of DCM exploratory analysis. For convenience in application, the algorithms were encapsulated into MATLAB function based on SPM to help neuroscience researchers to analyze the brain causal information flow network. The strategy provides a model space exploration tool that may obtain the best model from the perspective of model comparison and lower the threshold of DCM analysis.

The ability of patients with Parkinson's disease to recognize masked faces during the COVID-19 pandemic

Patients with Parkinson's disease (PwP) have face recognition difficulties.

Objective

This study aimed to evaluate the difficulties of PwP in recognizing masked faces during the COVID-19 pandemic.

Methods

A total of 64 PwP, 58 age-matched older healthy controls (OHCs), and 61 younger healthy controls (YHCs) were included in the study. The Benton Face Recognition Test - short form (BFRT-sf) and the 13-item questionnaire on face recognition difficulties due to masks during the pandemic developed by the authors were applied to all three study groups.

Results

Both the PwP and OHC groups scored worse in BFRT-sf when compared with the YHC group (p<0.001 and p<0.001, respectively). The number of those who had difficulty in recognizing people seen every day and the number of those who asked people to remove their masks because they did not recognize them were higher in the PWP group (p=0.026 and p=0.002, respectively). The number of individuals who looked at the posture and gait of people when they did not recognize their masked faces and those who stated that this difficulty affected their daily lives were higher in the OHC group (p=0.002 and p=0.009, respectively). The number of participants whose difficulty in recognizing masked faces decreased over time was higher in the YHC group (p=0.003).

Conclusions

The PwP group demonstrated similar performance to their peers but differed from the YHC group in recognizing masked faces. Knowing difficulties experienced by elderly people in recognizing people who are masked can increase awareness on this issue and enhance their social interaction in pandemic conditions through measures to be taken.

Contributions of the Right Prefrontal and Parietal Cortices to the Attentional Blink: A tDCS Study

The AB refers to the performance impairment that occurs when visual selective attention is overloaded through the very rapid succession of two targets (T1 and T2) among distractors by using the rapid serial visual presentation task (RSVP). Under these conditions, performance is typically impaired when T2 is presented within 200–500 ms from T1 (AB). Based on neuroimaging studies suggesting a role of top-down attention and working memory brain hubs in the AB, here we potentiated via anodal or sham tDCS the activity of the right DLPFC (F4) and of the right PPC (P4) during an AB task. The findings showed that anodal tDCS over the F4 and over P4 had similar effects on the AB. Importantly, potentiating the activity of the right frontoparietal network via anodal tDCS only benefitted poor performers, reducing the AB, whereas in good performers it accentuated the AB. The contribution of the present findings is twofold: it shows both top-down and bottom-up contributions of the right frontoparietal network in the AB, and it indicates that there is an optimal level of excitability of this network, resulting from the individual level of activation and the intensity of current stimulation.

An Ontological Framework to Facilitate Early Detection of 'Radicalization' (OFEDR)-A Three World Perspective

This paper presents an ontology that involves using information from various sources from different disciplines and combining it in order to predict whether a given person is in a radicalization process. The purpose of the ontology is to improve the early detection of radicalization in persons, thereby contributing to increasing the extent to which the unwanted escalation of radicalization processes can be prevented. The ontology combines findings related to existential anxiety that are related to political radicalization with well-known criminal profiles or radicalization findings. The software Protégé, delivered by the technical field at Stanford University, including the SPARQL tab, is used to develop and test the ontology. The testing, which involved five models, showed that the ontology could detect individuals according to "risk profiles" for subjects based on existential anxiety. SPARQL queries showed an average detection probability of 5% including only a risk population and 2% on a whole test population. Testing by using machine learning algorithms proved that inclusion of less than four variables in each model produced unreliable results. This suggest that the Ontology Framework to Facilitate Early Detection of 'Radicalization' (OFEDR) ontology risk model should consist of at least four variables to reach a certain level of reliability. Analysis shows that use of a probability based on an estimated risk of terrorism may produce a gap between the number of subjects who actually have early signs of radicalization and those found by using probability estimates for extremely rare events. It is reasoned that an ontology exists as a world three object in the real world.

Attentional and cognitive monitoring brain networks in long-term meditators depend on meditation states and expertise

Meditation practice is suggested to engage training of cognitive control systems in the brain. To evaluate the functional involvement of attentional and cognitive monitoring processes during meditation, the present study analysed the electroencephalographic synchronization of fronto-parietal (FP) and medial-frontal (MF) brain networks in highly experienced meditators during different meditation states (focused attention, open monitoring and loving kindness meditation). The aim was to assess whether and how the connectivity patterns of FP and MF networks are modulated by meditation style and expertise. Compared to novice meditators, (1) highly experienced meditators exhibited a strong theta synchronization of both FP and MF networks in left parietal regions in all mediation styles, and (2) only the connectivity of lateralized beta MF networks differentiated meditation styles. The connectivity of intra-hemispheric theta FP networks depended non-linearly on meditation expertise, with opposite expertise-dependent patterns found in the left and the right hemisphere. In contrast, inter-hemispheric FP connectivity in faster frequency bands (fast alpha and beta) increased linearly as a function of expertise. The results confirm that executive control systems play a major role in maintaining states of meditation. The distinctive lateralized involvement of FP and MF networks appears to represent a major functional mechanism that supports both generic and style-specific meditation states. The observed expertise-dependent effects suggest that functional plasticity within executive control networks may underpin the emergence of unique meditation states in expert meditators.

Diabetic patients are deficient in intentional visuospatial learning and show different learning-related patterns of theta and gamma EEG activity

Introduction: We hypothesized that diabetic patients without mild cognitive impairment would present deficiencies in visuospatial incidental/intentional memory processing and alterations in the underlying EEG alpha, theta and gamma patterns.Methods: Non-diabetic, diabetic-controlled, and diabetic-uncontrolled patients underwent a visuospatial incidental-intentional memory test under simultaneous recording of temporal, parietal, and frontal EEG. The test required patients to solve a maze, with eight objects irrelevant to the task, embedded in it, after an interference instruction, participants were asked to recall the positions of the objects (incidental test). Finally, the participants were explicitly told to study the object positions, and then were asked to recall the objects again (intentional test). Power from baseline, incidental learning, incidental memory, and intentional learning conditions was obtained in alpha, theta, and low-gamma bands. Comparisons were made across groups and conditions for each band, with age, sex, and years from the diagnosis as covariates (ANCOVA with blocking).Results: Diabetic patients showed spared incidental but deficient intentional visuospatial learning. Uncontrolled patients showed a more profound intentional learning deficit as they scored similar numbers of correct positions under incidental and intentional conditions; whereas, non-diabetic and diabetic-controlled patients increased their number after the intentional study. Non-diabetic participants showed increased power during intentional learning compared with the baseline condition in frontal theta, frontoparietal gamma (Fp2 and P4) and frontal alpha (F4) bands; whereas in diabetic patients the power increased in the theta band, in T5 (uncontrolled) and T5 and F7 (controlled).Conclusions: Diabetic patients without mild cognitive impairment show deficient intentional visuospatial learning which was worse in uncontrolled patients. Theta and gamma power increased in healthy participants during intentional learning principally in frontal areas. These EEG power changes were absent in diabetic patients. The reduced accuracy of diabetic patients in intentional visuospatial learning was associated with different EEG learning-related patterns.

Neural signatures of prosocial behaviors

Prosocial behaviors are hypothesized to require socio-cognitive and empathic abilities-engaging brain regions attributed to the mentalizing and empathy brain networks. Here, we tested this hypothesis with a coordinate-based meta-analysis of 600 neuroimaging studies on prosociality, mentalizing and empathy (∼12,000 individuals). We showed that brain areas recruited by prosocial behaviors only partially overlap with the mentalizing (dorsal posterior cingulate cortex) and empathy networks (middle cingulate cortex). Additionally, the dorsolateral and ventromedial prefrontal cortices were preferentially activated by prosocial behaviors. Analyses on the functional connectivity profile and functional roles of the neural patterns underlying prosociality revealed that in addition to socio-cognitive and empathic processes, prosocial behaviors further involve evaluation processes and action planning, likely to select the action sequence that best satisfies another person's needs. By characterizing the multidimensional construct of prosociality at the neural level, we provide insights that may support a better understanding of normal and abnormal social cognition (e.g., psychopathy).

The effect of transcranial random noise stimulation (tRNS) over bilateral posterior parietal cortex on divergent and convergent thinking

Creativity pervades many areas of everyday life and is considered highly relevant in several human living domains. Previous literature suggests that the posterior parietal cortex (PPC) is related to creativity. However, none of previous studies have compared the effect of transcranial random noise stimulation (tRNS) over bilateral PPC on both verbal and visual divergent thinking (DT) and Remote Associates Test (RAT) in the same experimental design. Forty healthy participants were randomly assigned to tRNS (100–500 Hz) over bilateral PPC or sham group, for 15 min and current was set at 1.5 mA. Participants’ creativity skills were assessed before and after brain stimulation with the Unusual Uses and the Picture Completion subtests from the Torrance Test of Creative Thinking and the RAT. ANCOVA (baseline scores as covariate) results indicated that tRNS group had significantly higher scores at post-test in RAT and visual originality compared to sham group. Unusual Uses, on the other hand, was not significant. Improvement in RAT suggests the involvement of PPC during via insight solution which may reflect internally directed attention that helps the recombination of remotely associated information. The improvement in visual originality dimension from DT may be due to a higher internally directed attention while reducing externally oriented attention.

Evolutional and developmental anatomical architecture of the left inferior frontal gyrus

The left inferior frontal gyrus (IFG) including Broca's area is involved in the processing of many language subdomains, and thus, research on the evolutional and human developmental characteristics of the left IFG will shed light on how language emerges and maturates. In this study, we used diffusion magnetic resonance imaging (dMRI) and resting-state functional MRI (fMRI) to investigate the evolutional and developmental patterns of the left IFG in humans (age 6-8, age 11-13, and age 16-18 years) and macaques. Tractography-based parcellation was used to define the subcomponents of left IFG and consistently identified four subregions in both humans and macaques. This parcellation scheme for left IFG in human was supported by specific coactivation patterns and functional characterization for each subregion. During evolution and development, we found increased functional balance, amplitude of low frequency fluctuations, functional integration, and functional couplings. We also observed higher fractional anisotropy values, i.e. better myelination of dorsal and ventral white matter language pathways during evolution and development. We assume that the resting-state functional connectivity and task-related coactivation mapping are associated with hierarchical language processing. Our findings have shown the evolutional and human developmental patterns of left IFG, and will contribute to the understanding of how the human language evolves and how atypical language developmental disorders may occur.

The emerging neuroscience of social punishment: Meta-analytic evidence

Social punishment (SOP)-third-party punishment (TPP) and second-party punishment (SPP)-sanctions norm-deviant behavior. The hierarchical punishment model (HPM) posits that TPP is an extension of SPP and both recruit common processes engaging large-scale domain-general brain networks. Here, we provided meta-analytic evidence to the HPM by combining the activation likelihood estimation approach with connectivity analyses and hierarchical clustering analyses. Although both forms of SOP engaged the dorsolateral prefrontal cortex and bilateral anterior insula (AI), a functional differentiation also emerged with TPP preferentially engaging social cognitive regions (temporoparietal junction) and SPP affective regions (AI). Further, although both TPP and SPP recruit domain-general networks (salience, default-mode, and central-executive networks), some specificity in network organization was observed. By revealing differences and commonalities of the neural networks consistently activated by different types of SOP, our findings contribute to a better understanding of the neuropsychological mechanisms of social punishment behavior--one of the most peculiar human behaviors.

Functional Segregation of the Middle Temporal Visual Motion Area Revealed With Coactivation-Based Parcellation

Traditionally, the visual motion area (MT) is considered as a brain region specialized for visual motion perception. However, accumulating evidence showed that MT is also related to various functions, suggesting that it is a complex functional area and different functional subregions might exist in this area. To delineate functional subregions of this area, left and right masks of MT were defined using meta-analysis in the BrainMap database, and coactivation-based parcellation was then performed on these two masks. Two dorsal subregions (Cl1 and Cl2) and one ventral subregion (Cl3) of left MT, as well as two dorsal-anterior subregions (Cl1 and Cl2), one ventral-anterior subregion (Cl3), and an additional posterior subregion (Cl4) of right MT were identified. In addition to vision motion, distinct and specific functions were identified in different subregions characterized by task-dependent functional connectivity mapping and forward/reverse inference on associated functions. These results not only were in accordance with the previous findings of a hemispheric asymmetry of MT, but also strongly confirmed the existence of subregions in this region with distinct and specific functions. Furthermore, our results extend the special role of visual motion perception on this area and might facilitate future cognitive study.

Forced conceptual thought induced by electrical stimulation of the left prefrontal gyrus involves widespread neural networks

BACKGROUND

Early accounts of forced thought were reported at the onset of a focal seizure, and characterized as vague, repetitive, and involuntary intellectual auras distinct from perceptual or psychic hallucinations or illusions. Here, we examine the neural underpinnings involved in conceptual thought by presenting a series of 3 patients with epilepsy reporting intrusive thoughts during electrical stimulation of the left lateral prefrontal cortex (PFC) during invasive surgical evaluation. We illustrate the widespread networks involved through two independent brain imaging modalities: resting state functional magnetic resonance imaging (fMRI) (rs-fMRI) and task-based meta-analytic connectivity modeling (MACM).

METHODS

We report the clinical and stimulation characteristics of three patients with left hemispheric language dominance who demonstrate forced thought with functional mapping. To examine the brain networks underlying this phenomenon, we used the regions of interest (ROI) centered at the active electrode pairs. We modeled functional networks using two approaches: (1) rs-fMRI functional connectivity analysis, representing 81 healthy controls and (2) meta-analytic connectivity modeling (MACM), representing 8260 healthy subjects. We also determined the overlapping regions between these three subjects' rs-fMRI and MACM networks through a conjunction analysis.

RESULTS

We identified that left PFC was associated with a large-scale functional network including frontal, temporal, and parietal regions, a network that has been associated with multiple cognitive functions including semantics, speech, attention, working memory, and explicit memory.

CONCLUSIONS

We illustrate the neural networks involved in conceptual thought through a unique patient population and argue that PFC supports this function through activation of a widespread network.

Functional Characterization of Atrophy Patterns Related to Cognitive Impairment

Introduction: Mild cognitive impairment (MCI) is a heterogenous syndrome considered as a risk factor for developing dementia. Previous work examining morphological brain changes in MCI has identified a temporo-parietal atrophy pattern that suggests a common neuroanatomical denominator of cognitive impairment. Using functional connectivity analyses of structurally affected regions in MCI, we aimed to investigate and characterize functional networks formed by these regions that appear to be particularly vulnerable to disease-related disruptions.

Methods: Areas of convergent atrophy in MCI were derived from a quantitative meta-analysis and encompassed left and right medial temporal (i.e., hippocampus, amygdala), as well as parietal regions (precuneus), which were defined as seed regions for connectivity analyses. Both task-based meta-analytical connectivity modeling (MACM) based on the BrainMap database and task-free resting-state functional MRI in a large cohort of older adults from the 1000BRAINS study were applied. We additionally assessed behavioral characteristics associated with the seed regions using BrainMap meta-data and investigated correlations of resting-state connectivity with age.

Results: The left temporal seed showed stronger associations with a fronto-temporal network, whereas the right temporal atrophy cluster was more linked to cortico-striatal regions. In accordance with this, behavioral analysis indicated an emphasis of the left temporal seed on language generation, and the right temporal seed was associated with the domains of emotion and attention. Task-independent co-activation was more pronounced in the parietal seed, which demonstrated stronger connectivity with a frontoparietal network and associations with introspection and social cognition. Correlation analysis revealed both decreasing and increasing functional connectivity with higher age that may add to pathological processes but also indicates compensatory mechanisms of functional reorganization with increasing age.

Conclusion: Our findings provide an important pathophysiological link between morphological changes and the clinical relevance of major structural damage in MCI. Multimodal analysis of functional networks related to areas of MCI-typical atrophy may help to explain cognitive decline and behavioral alterations not tractable by a mere anatomical interpretation and therefore contribute to prognostic evaluations.

Frontoparietal Network Connectivity During an N-Back Task in Adults With Autism Spectrum Disorder

BACKGROUND

Short-term and working memory (STM and WM) deficits have been demonstrated in individuals with autism spectrum disorder (ASD) and may emerge through atypical functional activity and connectivity of the frontoparietal network, which exerts top-down control necessary for successful STM and WM processes. Little is known regarding the spectral properties of the frontoparietal network during STM or WM processes in ASD, although certain neural frequencies have been linked to specific neural mechanisms.

METHODS

We analysed magnetoencephalographic data from 39 control adults (26 males; 27.15 ± 5.91 years old) and 40 adults with ASD (26 males; 27.17 ± 6.27 years old) during a 1-back condition (STM) of an n-back task, and from a subset of this sample during a 2-back condition (WM). We performed seed-based connectivity analyses using regions of the frontoparietal network. Interregional synchrony in theta, alpha, and beta bands was assessed with the phase difference derivative and compared between groups during periods of maintenance and recognition.

RESULTS

During maintenance of newly presented vs. repeated stimuli, the two groups did not differ significantly in theta, alpha, or beta phase synchrony for either condition. Adults with ASD showed alpha-band synchrony in a network containing the right dorsolateral prefrontal cortex, bilateral inferior parietal lobules (IPL), and precuneus in both 1- and 2-back tasks, whereas controls demonstrated alpha-band synchrony in a sparser set of regions, including the left insula and IPL, in only the 1-back task. During recognition of repeated vs. newly presented stimuli, adults with ASD exhibited decreased theta-band connectivity compared to controls in a network with hubs in the right inferior frontal gyrus and left IPL in the 1-back condition. Whilst there were no group differences in connectivity in the 2-back condition, adults with ASD showed no frontoparietal network recruitment during recognition, whilst controls activated networks in the theta and beta bands.

CONCLUSIONS

Our findings suggest that since adults with ASD performed well on the n-back task, their appropriate, but effortful recruitment of alpha-band mechanisms in the frontoparietal network to maintain items in STM and WM may compensate for atypical modulation of this network in the theta band to recognise previously presented items in STM.

Functional brain alterations in acute sleep deprivation: An activation likelihood estimation meta-analysis

Sleep deprivation (SD) is a common problem in modern societies, which leads to cognitive dysfunctions including attention lapses, impaired working memory, hindering decision making, impaired emotional processing, and motor vehicle accidents. Numerous neuroimaging studies have investigated the neural correlates of SD, but these studies have reported inconsistent results. Thus, we aimed to identify convergent patterns of abnormal brain functions due to acute SD. Based on the preferred reporting for systematic reviews and meta-analyses statement, we searched the PubMed database and performed reference tracking and finally retrieved 31 eligible functional neuroimaging studies. Then, we applied activation estimation likelihood meta-analysis and found reduced activity mainly in the right intraparietal sulcus and superior parietal lobule. The functional decoding analysis using the BrainMap database indicated that this region is mostly related to visuospatial perception, memory and reasoning. The significant co-activation of this region using the BrainMap database were found in the left superior parietal lobule, intraparietal sulcus, bilateral occipital cortex, left fusiform gyrus and thalamus. This region also connected with the superior parietal lobule, intraparietal sulcus, insula, inferior frontal gyrus, precentral, occipital and cerebellum through resting-state functional connectivity in healthy subjects. Taken together, our findings highlight the role of superior parietal cortex in SD.

Human Pregenual Anterior Cingulate Cortex: Structural, Functional, and Connectional Heterogeneity

The human pregenual anterior cingulate cortex (pACC) encompasses 7 distinct cyto- and receptorarchitectonic areas. We lack a detailed understanding of the functions in which they are involved, and stereotaxic maps are not available. We present an integrated structural/functional map of pACC based on probabilistic cytoarchitectonic mapping and meta-analytic connectivity modeling and quantitative functional decoding. Due to the restricted spatial resolution of functional imaging data relative to the microstructural parcellation, areas p24a of the callosal sulcus and p24b on the surface of the cingulate gyrus were merged into a "gyral component" (p24ab) of area p24, and areas pv24c, pd24cv, and pd24cd, located within the cingulate sulcus were merged into a "sulcal component" (p24c) for meta-analytic analysis. Area p24ab was specifically associated with interoception, p24c with the inhibition of action, and p32, which was also activated by emotion induction tasks pertaining negatively valenced stimuli, with the ability to experience empathy. Thus, area p32 could be classified as cingulate association cortex playing a crucial role in the cognitive regulation of emotion. By this spectrum of functions, pACC is a structurally and functionally heterogeneous region, clearly differing from other parts of the anterior and middle cingulate cortex.

Load effects on spatial working memory performance are linked to distributed alpha and beta oscillations

Increasing spatial working memory (SWM) load is generally associated with declines in behavioral performance, but the neural correlates of load-related behavioral effects remain poorly understood. Herein, we examine the alterations in oscillatory activity that accompany such performance changes in 22 healthy adults who performed a two- and four-load SWM task during magnetoencephalography (MEG). All MEG data were transformed into the time-frequency domain and significant oscillatory responses were imaged separately per load using a beamformer. Whole-brain correlation maps were computed using the load-related beamformer difference images and load-related accuracy effects on the SWM task. The results indicated that load-related differences in left inferior frontal alpha activity during encoding and maintenance were negatively correlated with load-related accuracy differences on the SWM task. That is, individuals who had more substantial decreases in prefrontal alpha during high-relative to low-load SWM trials tended to have smaller performance decrements on the high-load condition (i.e., they performed more accurately). The same pattern of neurobehavioral correlations was observed during the maintenance period for right superior temporal alpha activity and right superior parietal beta activity. Importantly, this is the first study to employ a voxel-wise whole-brain approach to significantly link load-related oscillatory differences and load-related SWM performance differences.

A lack of consistent brain alterations in insomnia disorder: An activation likelihood estimation meta-analysis

Insomnia disorder is a prevalent sleep disorder, which affects about 10% of general population. However, its neural mechanisms are poorly understood. Recently, several structural and functional neuroimaging studies have been conducted in patients with insomnia disorder, but these studies have yielded diverse findings. Here, we aimed to identify consistent patterns of abnormal brain alterations in insomnia disorder by performing a quantitative coordinate-based meta-analysis. Following the preferred reporting for systematic reviews and meta-analyses statement, we searched PubMed database and used reference tracking and finally retrieved 19 eligible studies (six task-based functional magnetic resonance imaging, eight resting-state functional magnetic resonance imaging, three voxel-based morphometry, and two positron emission tomography). We extracted peak coordinates from these studies and tested for convergence using the activation likelihood estimation method. Using this method, we found no significant convergent evidence for combination of structural atrophy and functional disturbances across previous studies (p = 0.914). Inconsistencies across these studies might be related to heterogonous clinical populations, the explorative nature of these studies in combination with small sample sizes, different experimental designs, and various preprocessing and statistical approaches. Future neuroimaging studies on insomnia disorder should include larger well-characterized samples, as well as standard imaging and analysis protocols.

Three-stage processing of category and variation information by entangled interactive mechanisms of peri-occipital and peri-frontal cortices

Object recognition has been a central question in human vision research. The general consensus is that the ventral and dorsal visual streams are the major processing pathways undertaking objects' category and variation processing. This overlooks mounting evidence supporting the role of peri-frontal areas in category processing. Yet, many aspects of visual processing in peri-frontal areas have remained unattended including whether these areas play role only during active recognition and whether they interact with lower visual areas or process information independently. To address these questions, subjects were presented with a set of variation-controlled object images while their EEG were recorded. Considerable amounts of category and variation information were decodable from occipital, parietal, temporal and prefrontal electrodes. Using information-selectivity indices, phase and Granger causality analyses, three processing stages were identified showing distinct directions of information transaction between peri-frontal and peri-occipital areas suggesting their parallel yet interactive role in visual processing. A brain-plausible model supported the possibility of interactive mechanisms in peri-occipital and peri-frontal areas. These findings, while promoting the role of prefrontal areas in object recognition, extend their contributions from active recognition, in which peri-frontal to peri-occipital pathways are activated by higher cognitive processes, to the general sensory-driven object and variation processing.

Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance

The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.

Cognitive benefit and cost of acute stress is differentially modulated by individual brain state

Acute stress is associated with beneficial as well as detrimental effects on cognition in different individuals. However, it is not yet known how stress can have such opposing effects. Stroop-like tasks typically show this dissociation: stress diminishes speed, but improves accuracy. We investigated accuracy and speed during a stroop-like task of 120 healthy male subjects after an experimental stress induction or control condition in a randomized, counter-balanced cross-over design; we assessed brain–behavior associations and determined the influence of individual brain connectivity patterns on these associations, which may moderate the effect and help identify stress resilience factors. In the mean, stress was associated to increase in accuracy, but decrease in speed. Accuracy was associated to brain activation in a distributed set of brain regions overlapping with the executive control network (ECN) and speed to temporo-parietal activation. In line with a stress-related large-scale network reconfiguration, individuals showing an upregulation of the salience and down-regulation of the executive-control network under stress displayed increased speed, but decreased performance. In contrast, individuals who upregulate their ECN under stress show improved performance. Our results indicate that the individual large-scale brain network balance under acute stress moderates cognitive consequences of threat.

Functional Hemispheric (A)symmetries in the Aged Brain-Relevance for Working Memory

Functional hemispheric asymmetries have been described in different cognitive processes, such as decision-making and motivation. Variations in the pattern of left/right activity have been associated with normal brain functioning, and with neuropsychiatric diseases. Such asymmetries in brain activity evolve throughout life and are thought to decrease with aging, but clear associations with cognitive function have never been established. Herein, we assessed functional laterality during a working memory task (N-Back) in a healthy aging cohort (over 50 years old) and associated these asymmetries with performance in the test. Activity of lobule VI of the cerebellar hemisphere and angular gyrus was found to be lateralized to the right hemisphere, while the precentral gyrus presented left > right activation during this task. Interestingly, 1-Back accuracy was positively correlated with left > right superior parietal lobule activation, which was mostly due to the influence of the left hemisphere. In conclusion, although regions were mostly symmetrically activated during the N-Back task, performance in working memory in aged individuals seems to benefit from lateralized involvement of the superior parietal lobule.

How neuroscience can inform the study of individual differences in cognitive abilities

Theories of human mental abilities should be consistent with what is known in neuroscience. Currently, tests of human mental abilities are modeled by cognitive constructs such as attention, working memory, and speed of information processing. These constructs are in turn related to a single general ability. However, brains are very complex systems and whether most of the variability between the operations of different brains can be ascribed to a single factor is questionable. Research in neuroscience suggests that psychological processes such as perception, attention, decision, and executive control are emergent properties of interacting distributed networks. The modules that make up these networks use similar computational processes that involve multiple forms of neural plasticity, each having different time constants. Accordingly, these networks might best be characterized in terms of the information they process rather than in terms of abstract psychological processes such as working memory and executive control.

Definition and characterization of an extended multiple-demand network

Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands.

Neural correlates of formal thought disorder: An activation likelihood estimation meta-analysis

Formal thought disorder (FTD) refers to a psychopathological dimension characterized by disorganized and incoherent speech. Whether symptoms of FTD arise from aberrant processing in language-related regions or more general cognitive networks, however, remains debated. Here, we addressed this question by a quantitative meta-analysis of published functional neuroimaging studies on FTD. The revised Activation Likelihood Estimation (ALE) algorithm was used to test for convergent aberrant activation changes in 18 studies (30 experiments) investigating FTD, of which 17 studies comprised schizophrenia patients and one study healthy subjects administered to S-ketamine. Additionally, we analyzed task-dependent and task-independent (resting-state) functional connectivity (FC) of brain regions showing convergence in activation changes. Subsequent functional characterization was performed for the initial clusters and the delineated connectivity networks by reference to the BrainMap database. Consistent activation changes were found in the left superior temporal gyrus (STG) and two regions within the left posterior middle temporal gyrus (p-MTG), ventrally (vp-MTG) and dorsally (dp-MTG). Functional characterization revealed a prominent functional association of ensuing clusters from our ALE meta-analysis with language and speech processing, as well as auditory perception in STG and with social cognition in dp-MTG. FC analysis identified task-dependent and task-independent networks for all three seed regions, which were mainly related to language and speech processing, but showed additional involvement in higher order cognitive functions. Our findings suggest that FTD is mainly characterized by abnormal activation in brain regions of the left hemisphere that are associated with language and speech processing, but also extend to higher order cognitive functions. Hum Brain Mapp 38:4946-4965, 2017. © 2017 Wiley Periodicals, Inc.

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

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

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

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

Cross-cultural consistency and diversity in intrinsic functional organization of Broca's Region

As a core language area, Broca's region was consistently activated in a variety of language studies even across different language systems. Moreover, a high degree of structural and functional heterogeneity in Broca's region has been reported in many studies. This raised the issue of how the intrinsic organization of Broca's region effects by different language experiences in light of its subdivisions. To address this question, we used multi-center resting-state fMRI data to explore the cross-cultural consistency and diversity of Broca's region in terms of its subdivisions, connectivity patterns and modularity organization in Chinese and German speakers. A consistent topological organization of the 13 subdivisions within the extended Broca's region was revealed on the basis of a new in-vivo parcellation map, which corresponded well to the previously reported receptorarchitectonic map. Based on this parcellation map, consistent functional connectivity patterns and modularity organization of these subdivisions were found. Some cultural difference in the functional connectivity patterns was also found, for instance stronger connectivity in Chinese subjects between area 6v2 and the motor hand area, as well as higher correlations between area 45p and middle frontal gyrus. Our study suggests that a generally invariant organization of Broca's region, together with certain regulations of different language experiences on functional connectivity, might exists to support language processing in human brain.

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

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

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

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

Synchronization of fronto-parietal beta and theta networks as a signature of visual awareness in neglect

In the neglect syndrome, the perceptual deficit for contra-lesional hemi-space is increasingly viewed as a dysfunction of fronto-parietal cortical networks, the disruption of which has been described in neuroanatomical and hemodynamic studies. Here we exploit the superior temporal resolution of electroencephalography (EEG) to study dynamic transient connectivity of fronto-parietal circuits at early stages of visual perception in neglect. As reflected by inter-regional phase synchronization in a full-field attention task, two functionally distinct fronto-parietal networks, in beta (15-25Hz) and theta (4-8Hz) frequency bands, were related to stimulus discrimination within the first 200 ms of visual processing. Neglect pathology was specifically associated with significant suppressions of both beta and theta networks engaging right parietal regions. These connectivity abnormalities occurred in a pattern that was distinctly different from what was observed in right-hemisphere lesion patients without neglect. Also, both beta and theta abnormalities contributed additively to visual awareness decrease, quantified in the Behavioural Inattention Test. These results provide evidence for the impairment of fast dynamic fronto-parietal interactions during early stages of visual processing in neglect pathology. Also, they reveal that different modes of fronto-parietal dysfunction contribute independently to deficits in visual awareness at the behavioural level.

Situating the default-mode network along a principal gradient of macroscale cortical organization

Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface-and are precisely equidistant-from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.

Implementation errors in the GingerALE Software: Description and recommendations

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

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

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

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.

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

•

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

•

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

•

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

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

Functional Segregation of the Human Dorsomedial Prefrontal Cortex

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

Large-scale brain network abnormalities in Huntington's disease revealed by structural covariance

Huntington's disease (HD) is a progressive neurodegenerative disorder that can be diagnosed with certainty decades before symptom onset. Studies using structural MRI have identified grey matter (GM) loss predominantly in the striatum, but also involving various cortical areas. So far, voxel-based morphometric studies have examined each brain region in isolation and are thus unable to assess the changes in the interrelation of brain regions. Here, we examined the structural covariance in GM volumes in pre-specified motor, working memory, cognitive flexibility, and social-affective networks in 99 patients with manifest HD (mHD), 106 presymptomatic gene mutation carriers (pre-HD), and 108 healthy controls (HC). After correction for global differences in brain volume, we found that increased GM volume in one region was associated with increased GM volume in another. When statistically comparing the groups, no differences between HC and pre-HD were observed, but increased positive correlations were evident for mHD, relative to pre-HD and HC. These findings could be explained by a HD-related neuronal loss heterogeneously affecting the examined network at the pre-HD stage, which starts to dominate structural covariance globally at the manifest stage. Follow-up analyses identified structural connections between frontoparietal motor regions to be linearly modified by disease burden score (DBS). Moderator effects of disease load burden became significant at a DBS level typically associated with the onset of unequivocal HD motor signs. Together with existing findings from functional connectivity analyses, our data indicates a critical role of these frontoparietal regions for the onset of HD motor signs.

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

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

Multimodal connectivity of motor learning-related dorsal premotor cortex

The dorsal premotor cortex (dPMC) is a key region for motor learning and sensorimotor integration, yet we have limited understanding of its functional interactions with other regions. Previous work has started to examine functional connectivity in several brain areas using resting state functional connectivity (RSFC) and meta-analytical connectivity modelling (MACM). More recently, structural covariance (SC) has been proposed as a technique that may also allow delineation of functional connectivity. Here, we applied these three approaches to provide a comprehensive characterization of functional connectivity with a seed in the left dPMC that a previous meta-analysis of functional neuroimaging studies has identified as playing a key role in motor learning. Using data from two sources (the Rockland sample, containing resting state data and anatomical scans from 132 participants, and the BrainMap database, which contains peak activation foci from over 10,000 experiments), we conducted independent whole-brain functional connectivity mapping analyses of a dPMC seed. RSFC and MACM revealed similar connectivity maps spanning prefrontal, premotor, and parietal regions, while the SC map identified more widespread frontal regions. Analyses indicated a relatively consistent pattern of functional connectivity between RSFC and MACM that was distinct from that identified by SC. Notably, results indicate that the seed is functionally connected to areas involved in visuomotor control and executive functions, suggesting that the dPMC acts as an interface between motor control and cognition.

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.