Characterizing directed functional pathways in the visual system by multivariate nonlinear coherence of fMRI data

Directed functional connectivity of the default-mode-network of young and older healthy subjects

Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging.

Directed functional connectivity of the sensorimotor system in young and older individuals

Introduction

Studies in the sensorimotor system of older versus young individuals have shown alterations in functional connectivity and organization. Our objective was to explore the implications of these differences in terms of local organizations, and to identify processes that correlate with neuropsychological parameters.

Methods

Using a novel multivariate analysis method on resting-state functional MRI data obtained from 50 young and 31 older healthy individuals, we identified directed 4-node functional pathways within the sensorimotor system and examined their correlations with neuropsychological assessments.

Results

In young individuals, the functional pathways were unidirectional, flowing from the primary motor and sensory cortices to higher motor and visual regions. In older individuals, the functional pathways were more complex. They originated either from the calcarine sulcus or the insula and passed through mutually coupled high-order motor areas before reaching the primary sensory and motor cortices. Additionally, the pathways in older individuals that resembled those found in young individuals exhibited a positive correlation with years of education.

Discussion

The flow pattern of young individuals suggests efficient and fast information transfer. In contrast, the mutual coupling of high-order motor regions in older individuals suggests an inefficient and slow transfer, a less segregated and a more integrated organization. The differences in the number of sensorimotor pathways and of their directionality suggests reduced efferent degenerated pathways and increased afferent compensated pathways. Furthermore, the positive effect of years of education may be associated with the Cognitive Reserve Hypothesis, implying that cognitive reserve could be maintained through specific information transfer pathways.

Brain Functional Imaging Anatomy

Human brain function is an increasingly complex framework that has important implications in clinical medicine. In this review, the anatomy of the most commonly assessed brain functions in clinical neuroradiology, including motor, language, and vision, is discussed. The anatomy and function of the primary and secondary sensorimotor areas are discussed with clinical case examples. Next, the dual stream of language processing is reviewed, as well as its implications in clinical medicine and surgical planning. Last, the authors discuss the striate and extrastriate visual cortex and review the dual stream model of visual processing.

A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data

Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully employed to understand the organisation of the human brain. Typically, the brain is parcellated into regions of interest (ROIs) and modelled as a graph where each ROI represents a node and association measures between ROI-specific blood-oxygen-level-dependent (BOLD) time series are edges. Recently, graph neural networks (GNNs) have seen a surge in popularity due to their success in modelling unstructured relational data. The latest developments with GNNs, however, have not yet been fully exploited for the analysis of rs-fMRI data, particularly with regards to its spatio-temporal dynamics. In this paper, we present a novel deep neural network architecture which combines both GNNs and temporal convolutional networks (TCNs) in order to learn from both the spatial and temporal components of rs-fMRI data in an end-to-end fashion. In particular, this corresponds to intra-feature learning (i.e., learning temporal dynamics with TCNs) as well as inter-feature learning (i.e., leveraging interactions between ROI-wise dynamics with GNNs). We evaluate our model with an ablation study using 35,159 samples from the UK Biobank rs-fMRI database, as well as in the smaller Human Connectome Project (HCP) dataset, both in a unimodal and in a multimodal fashion. We also demonstrate that out architecture contains explainability-related features which easily map to realistic neurobiological insights. We suggest that this model could lay the groundwork for future deep learning architectures focused on leveraging the inherently and inextricably spatio-temporal nature of rs-fMRI data.

Asymmetry of the insula-sensorimotor circuit in Parkinson's disease

Patients with Parkinson's disease (PD) experience motor and non-motor symptoms, suggesting alterations of the motor and/or limbic system or more probably of their communications. We hypothesized that the communication between the insula (part of the limbic system) and sensorimotor cortex in PD is altered and hemispheric asymmetric. Furthermore, that this asymmetry relates to non-motor symptoms, and specifically, that apathy-related asymmetry is unique to PD. To test these hypotheses, we used a novel multivariate time-frequency analysis method applied to resting-state functional magnetic resonance imaging (MRI) data of 28 controls and 25 participants with PD measured in their OFF medication state. The analysis infers directionality of coupling, that is, afferent or efferent, among four anatomical regions, thus defining directed pathways of information flow, which enables the extension of symmetry measures to include directionality. A major right asymmetry reduction of the dorsal-posterior insula efferent and a slight bilateral increase of insula afferent pathways were observed in participants with PD versus controls. Between-group pathways that correlated with mild cognitive impairments combined the central-executive and default-mode networks through the right insula. Apathy-correlated pathways of the posterior insula in participants with PD versus controls exhibited reduced right efferent and increased left afferent. Because apathy scores were comparable between the groups and effects of the other motor and non-motor symptoms were statistically removed by the analysis, the differences in apathy-correlated pathways were suggested as unique to PD. These pathways could be predictors in the pre-symptomatic phase in patients with apathy.

Altered sensorimotor fMRI directed connectivity in Parkinson's disease patients

Dopamine depletion in the axons of Parkinson's disease (PD) patients precedes depletion in cell bodies thus proposing that macroscopic connectivity can be used to understand disease mechanism. A novel multivariate functional connectivity analysis, based on high order coherence among four fMRI BOLD signals was applied on resting-state fMRI data of controls and PD patients (OFF and ON medication states) and unidirectional multiple-region pathways in the sensorimotor system were identified. Pathways were classified as "preserved" (unaffected by the disease), "damaged" (not observed in patients) and "corrected" (observed in controls and in PD-ON state). The majority of all pathways were feedforward, most of them with the pattern "S1→M1→SMA." Of these pathways, 67% were "damaged," 28% "preserved," and 5% "corrected." Prefrontal cortex (PFC) afferent and efferent pathways that corresponded to goal directed and habitual activities corresponded to recurrent circuits. Eighty-one percent of habitual afferent had internal cue (i.e., M1→S1→), of them 79% were "damaged" and the rest "preserved." All goal-directed afferent had external cue (i.e., S1→M1→) with third "damaged," third "preserved," and third "corrected." Corrected pathways were initiated in the dorsolateral PFC. Reduced connectivity of the SMA and PFC resulted from reduced sensorimotor afferent to these regions. Reduced sensorimotor internal cues to the PFC resulted with reduced habitual processes. Levodopa effects were for pathways that started in region reach with dopamine receptors. This methodology can enrich understudying of PD mechanisms in other (e.g., the default mode network) systems.

Functional Brain Anatomy

Knowledge of functional neuroanatomy is essential to design the most appropriate clinical functional MR imaging (fMR imaging) paradigms and to properly interpret fMR imaging study results. The correlation between neuroanatomy and brain function is also useful in general radiologic practice, as it improves the radiologist's ability to read routine brain examinations. Functional MR imaging is used primarily to determine the areas involved in functioning of movements, speech, and vision. Preoperative fMR imaging findings also play a key role in the neurosurgeon's decision to perform a biopsy, a subtotal resection, or a maximal resection using awake craniotomy.

Intrinsic Synchronization Analysis of Brain Activity in Obsessive-compulsive Disorders

Obsessive-compulsive disorder (OCD) is one of the neuropsychiatric disorders qualified by intrusive and iterative annoying thoughts and mental attitudes that are activated by these thoughts. In recent studies, advanced signal processing techniques have been favored to diagnose OCD. This research suggests four different measurements; intrinsic phase-locked value, intrinsic coherence, intrinsic synchronization likelihood, and intrinsic visibility graph similarity that quantifies the synchronization level and complexity in electroencephalography (EEG) signals. This intrinsic synchronization is achieved by utilizing Multivariate Empirical Mode Decomposition (MEMD), a data-driven method that resolves nonlinear and nonstationary data into their intrinsic mode functions. Our intrinsic technique in this study demonstrates that MEMD-based synchronization analysis gives us much more detailed knowledge rather than utilizing the synchronization method alone. Furthermore, the nonlinear synchronization method presents more consistent results considering OCD heterogeneity. Statistical evaluation using sample [Formula: see text]-test and [Formula: see text]-test has shown the significance of such new methodology.