Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain

Over the past two decades, the study of resting-state functional magnetic resonance imaging (fMRI) has revealed the existence of multiple brain areas displaying synchronous functional blood oxygen level-dependent signals (BOLD) - resting-state networks (RSNs). The variation in functional connectivity between the different areas of a resting-state network or between multiple networks, have been extensively studied and linked to cognitive states and pathologies. However, the white matter connections supporting each network remain only partially described. In this work, we developed a data-driven method to systematically map the white and grey matter contributing to resting-state networks. Using the Human Connectome Project, we generated an atlas of 30 resting-state networks, each with two maps: white matter and grey matter. By integrating structural and functional neuroimaging data, this method builds an atlas that unlocks the joint anatomical exploration of white and grey matter to resting-state networks. The method also allows highlighting the overlap between networks, which revealed that most (89%) of the brain's white matter is shared amongst multiple networks, with 16% shared by at least 7 resting-state networks. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the correlations and the communication within resting-state networks. We provide an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage on RSNs.

Focal neural perturbations reshape low-dimensional trajectories of brain activity supporting cognitive performance

The emergence of distributed patterns of neural activity supporting brain functions and behavior can be understood by study of the brain’s low-dimensional topology. Functional neuroimaging demonstrates that brain activity linked to adaptive behavior is constrained to low-dimensional manifolds. In human participants, we tested whether these low-dimensional constraints preserve working memory performance following local neuronal perturbations. We combined multi-session functional magnetic resonance imaging, non-invasive transcranial magnetic stimulation (TMS), and methods translated from the fields of complex systems and computational biology to assess the functional link between changes in local neural activity and the reshaping of task-related low dimensional trajectories of brain activity. We show that specific reconfigurations of low-dimensional trajectories of brain activity sustain effective working memory performance following TMS manipulation of local activity on, but not off, the space traversed by these trajectories. We highlight an association between the multi-scale changes in brain activity underpinning cognitive function.

Limb Preference in Animals: New Insights into the Evolution of Manual Laterality in Hominids

Until the 1990s, the notion of brain lateralization—the division of labor between the two hemispheres—and its more visible behavioral manifestation, handedness, remained fiercely defined as a human specific trait. Since then, many studies have evidenced lateralized functions in a wide range of species, including both vertebrates and invertebrates. In this review, we highlight the great contribution of comparative research to the understanding of human handedness’ evolutionary and developmental pathways, by distinguishing animal forelimb asymmetries for functionally different actions—i.e., potentially depending on different hemispheric specializations. Firstly, lateralization for the manipulation of inanimate objects has been associated with genetic and ontogenetic factors, with specific brain regions’ activity, and with morphological limb specializations. These could have emerged under selective pressures notably related to the animal locomotion and social styles. Secondly, lateralization for actions directed to living targets (to self or conspecifics) seems to be in relationship with the brain lateralization for emotion processing. Thirdly, findings on primates’ hand preferences for communicative gestures accounts for a link between gestural laterality and a left-hemispheric specialization for intentional communication and language. Throughout this review, we highlight the value of functional neuroimaging and developmental approaches to shed light on the mechanisms underlying human handedness.

The Role of the Angular Gyrus in Semantic Cognition – A Synthesis of Five Functional Neuroimaging Studies

Semantic knowledge is central to human cognition. The angular gyrus (AG) is widely considered a key brain region for semantic cognition. However, the role of the AG in semantic processing is controversial. Key controversies concern response polarity (activation vs. deactivation) and its relation to task difficulty, lateralization (left vs. right AG), and functional-anatomical subdivision (PGa vs. PGp subregions). Here, we combined the fMRI data of five studies on semantic processing (n = 172) and analyzed the response profiles from the same anatomical regions-of-interest for left and right PGa and PGp. We found that the AG was consistently deactivated during non-semantic conditions, whereas response polarity during semantic conditions was inconsistent. However, the AG consistently showed relative response differences between semantic and non-semantic conditions, and between different semantic conditions. A combined analysis across all studies revealed that AG responses could be best explained by independent effects of both task difficulty and semantic processing demand. Task difficulty effects were stronger in PGa than PGp, regardless of hemisphere. Semantic effects were stronger in left than right AG, regardless of subregion. These results suggest that the AG is independently engaged in both domain-general task-difficulty-related processes and domain-specific semantic processes. In semantic processing, we propose that left AG acts as a “multimodal convergence zone” that binds different semantic features associated with the same concept, enabling efficient access to task-relevant features.

Evidence for the Concreteness of Abstract Language: A Meta-Analysis of Neuroimaging Studies

The neural mechanisms subserving the processing of abstract concepts remain largely debated. Even within the embodiment theoretical framework, most authors suggest that abstract concepts are coded in a linguistic propositional format, although they do not completely deny the role of sensorimotor and emotional experiences in coding it. To our knowledge, only one recent proposal puts forward that the processing of concrete and abstract concepts relies on the same mechanisms, with the only difference being in the complexity of the underlying experiences. In this paper, we performed a meta-analysis using the Activation Likelihood Estimates (ALE) method on 33 functional neuroimaging studies that considered activations related to abstract and concrete concepts. The results suggest that (1) concrete and abstract concepts share the recruitment of the temporo-fronto-parietal circuits normally involved in the interactions with the physical world, (2) processing concrete concepts recruits fronto-parietal areas better than abstract concepts, and (3) abstract concepts recruit Broca’s region more strongly than concrete ones. Based on anatomical and physiological evidence, Broca’s region is not only a linguistic region mainly devoted to speech production, but it is endowed with complex motor representations of different biological effectors. Hence, we propose that the stronger recruitment of this region for abstract concepts is expression of the complex sensorimotor experiences underlying it, rather than evidence of a purely linguistic format of its processing.

A Review of Functional Neuroimaging in People with Down Syndrome with and without Dementia

<b><i>Background:</i></b> Individuals with Down syndrome (DS) are at high risk of dementia which is difficult to diagnose in DS. Neuroimaging has been identified as a potential tool to aid diagnosis by detecting changes in brain function. We carried out a review comparing functional neuroimaging in DS individuals with and without dementia. <b><i>Summary:</i></b> A literature search was conducted using PubMed to identify relevant studies. In DS subjects with dementia, fluorodeoxyglucose-positron emission tomography (PET) studies showed glucose hypometabolism particularly in the parietal and/or temporal regions whilst magnetic resonance spectroscopy studies showed increased myoinositol and decreased N-acetylaspartate. Ligand-based PET studies revealed significant Pittsburgh compound B binding in DS subjects over the age of 40, particularly if they had dementia. <b><i>Key Messages:</i></b> Neuroimaging may aid the early detection of dementia in DS; however, further longitudinal studies are required.

The role of the angular gyrus in semantic cognition – A synthesis of five functional neuroimaging studies

Semantic knowledge is central to human cognition. The angular gyrus (AG) is widely considered a key brain region for semantic cognition. However, the role of the AG in semantic processing is controversial. Key controversies concern response polarity (activation vs. deactivation) and its relation to task difficulty, lateralization (left vs. right AG), and functional-anatomical subdivision (PGa vs. PGp subregions). Here, we combined the fMRI data of five studies on semantic processing (n = 172) and analyzed the response profiles from the same anatomical regions-of-interest for left and right PGa and PGp. We found that the AG was consistently deactivated during non-semantic conditions, whereas response polarity during semantic conditions was inconsistent. However, the AG consistently showed relative response differences between semantic and non-semantic conditions, and between different semantic conditions. A combined analysis across all studies revealed that AG responses could be best explained by independent effects of both task difficulty and semantic processing demand. Task difficulty effects were stronger in PGa than PGp, regardless of hemisphere. Semantic effects were stronger in left than right AG, regardless of subregion. These results suggest that the AG is independently engaged in both domain-general task-difficulty-related processes and domain-specific semantic processes. In semantic processing, we propose that left AG acts as a "multimodal convergence zone" that binds different semantic features associated with the same concept, enabling efficient access to task-relevant features.

Interpreting models interpreting brain dynamics

Brain dynamics are highly complex and yet hold the key to understanding brain function and dysfunction. The dynamics captured by resting-state functional magnetic resonance imaging data are noisy, high-dimensional, and not readily interpretable. The typical approach of reducing this data to low-dimensional features and focusing on the most predictive features comes with strong assumptions and can miss essential aspects of the underlying dynamics. In contrast, introspection of discriminatively trained deep learning models may uncover disorder-relevant elements of the signal at the level of individual time points and spatial locations. Yet, the difficulty of reliable training on high-dimensional low sample size datasets and the unclear relevance of the resulting predictive markers prevent the widespread use of deep learning in functional neuroimaging. In this work, we introduce a deep learning framework to learn from high-dimensional dynamical data while maintaining stable, ecologically valid interpretations. Results successfully demonstrate that the proposed framework enables learning the dynamics of resting-state fMRI directly from small data and capturing compact, stable interpretations of features predictive of function and dysfunction.

An fMRI Study Using a Combined Task of Interval Discrimination and Oddball Could Reveal Common Brain Circuits of Cognitive Change

Recent functional neuroimaging studies suggest that the brain networks responsible for time processing are involved during other cognitive processes, leading to a hypothesis that time-related processing is needed to perform a range of tasks across various cognitive functions. To examine this hypothesis, we analyze whether, in healthy subjects, the brain structures activated or deactivated during performance of timing and oddball-detection type tasks coincide. To this end, we conducted two independent signed differential mapping (SDM) meta-analyses of functional magnetic resonance imaging (fMRI) studies assessing the cerebral generators of the responses elicited by tasks based on timing and oddball-detection paradigms. Finally, we undertook a multimodal meta-analysis to detect brain regions common to the findings of the two previous meta-analyses. We found that healthy subjects showed significant activation in cortical areas related to timing and salience networks. The patterns of activation and deactivation corresponding to each task type partially coincided. We hypothesize that there exists a time and change-detection network that serves as a common underlying resource used in a broad range of cognitive processes.