Brain network connectivity associated with anticipatory postural control in children and adults

Evaluation of a multimodal diagnostic algorithm for prediction of cognitive impairment in elderly patients with dizziness

BACKGROUND

The current diagnostic workup for chronic dizziness in elderly patients often neglects neuropsychological assessment, thus missing a relevant proportion of patients, who perceive dizziness as a subjective chief complaint of a concomitant cognitive impairment. This study aimed to establish risk prediction models for cognitive impairment in chronic dizzy patients based on data sources routinely collected in a dizziness center.

METHODS

One hundred patients (age: 74.7 ± 7.1 years, 41.0% women) with chronic dizziness were prospectively characterized by (1) neuro-otological testing, (2) quantitative gait assessment, (3) graduation of focal brain atrophy and white matter lesion load, and (4) cognitive screening (MoCA). A linear regression model was trained to predict patients' total MoCA score based on 16 clinical features derived from demographics, vestibular testing, gait analysis, and imaging scales. Additionally, we trained a binary logistic regression model on the same data sources to identify those patients with a cognitive impairment (i.e., MoCA < 25).

RESULTS

The linear regression model explained almost half of the variance of patients' total MoCA score (R2 = 0.49; mean absolute error: 1.7). The most important risk-predictors of cognitive impairment were age (β = - 0.75), pathological Romberg's sign (β = - 1.05), normal caloric test results (β = - 0.8), slower timed-up-and-go test (β = - 0.67), frontal (β = - 0.6) and temporal (β = - 0.54) brain atrophy. The binary classification yielded an area under the curve of 0.84 (95% CI 0.70-0.98) in distinguishing between cognitively normal and impaired patients.

CONCLUSIONS

The need for cognitive testing in patients with chronic dizziness can be efficiently approximated by available data sources from routine diagnostic workup in a dizziness center.

Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity

Although many deep learning models-based medical applications are performance-driven, i.e., accuracy-oriented, their explainability is more critical. This is especially the case with neuroimaging, where we are often interested in identifying biomarkers underlying brain development or disorders. Herein we propose an explainable deep learning approach by elucidating the information transmission mechanism between two layers of a deep network with a joint feature selection strategy that considers several shallow-layer explainable machine learning models and sparse learning of the deep network. At the end, we apply and validate the proposed approach to the analysis of dynamic brain functional connectivity (FC) from fMRI in a brain development study. Our approach can identify the differences within and between functional brain networks over age during development. The results indicate that the brain network transits from undifferentiated structures to more specialized and organized ones, and the information processing ability becomes more efficient as age increases. In addition, we detect two developmental patterns in the brain network: the FCs in regions related to visual and sound processing and mental regulation become weakened, while those between regions corresponding to emotional processing and cognitive activities are enhanced.

Developmental dyslexia, developmental coordination disorder and comorbidity discrimination using multimodal structural and functional neuroimaging

Developmental dyslexia (DD) and developmental coordination disorder (DCD) are two common neurodevelopmental disorders with a high co-occurrence rate. This led several authors to postulate that the two disorders share, at least partially, similar neural underpinning. However, even though several studies examined brain differences between typically developing (TD) children and children with either DD or DCD, no previous study directly compared DD, DCD and children with both disorders (COM) using neuroimaging. We acquired structural and resting-state functional MRI images of 136 children (TD = 42, DD = 45, DCD = 20, COM = 29). Difference between TD children and the other groups was assessed using univariate analysis of structural indexes including grey and white matter volumes and functional indexes quantifying activity (fraction of the amplitude of the low frequency fluctuations), local and global connectivity. Regional differences in structural and functional brain indexes were then used to train machine learning models to discriminate among DD, DCD and COM and to find the most discriminant regions. While no imaging index alone discriminated between the three groups, grouping grey and white matter volumes (structural model) or activity, local and global connectivity (functional model) made possible to discriminate among the DD, DCD and COM groups. The most important discrimination was obtained using the functional model, with regions in the cerebellum and the temporal lobe being the most discriminant for DCD and DD children, respectively. Results further showed that children with both DD and DCD have subtle but identifiable brain differences that can only be captured using several imaging indexes pertaining to both brain structure and function.

Differences in brain functional networks for audiovisual integration during reading between children and adults

Building robust letter-to-sound correspondences is a prerequisite for developing reading capacity. However, the neural mechanisms underlying the development of audiovisual integration for reading are largely unknown. This study used functional magnetic resonance imaging in a lexical decision task to investigate functional brain networks that support audiovisual integration during reading in developing child readers (10-12 years old) and skilled adult readers (20-28 years old). The results revealed enhanced connectivity in a prefrontal-superior temporal network (including the right medial frontal gyrus, right superior frontal gyrus, and left superior temporal gyrus) in adults relative to children, reflecting the development of attentional modulation of audiovisual integration involved in reading processing. Furthermore, the connectivity strength of this brain network was correlated with reading accuracy. Collectively, this study, for the first time, elucidates the differences in brain networks of audiovisual integration for reading between children and adults, promoting the understanding of the neurodevelopment of multisensory integration in high-level human cognition.

An increase in relative contribution of compensatory postural adjustments during voluntary movement while standing in adolescents and young adults with bilateral spastic cerebral palsy

Previous studies have revealed several deficits in anticipatory postural adjustments (APAs) during voluntary movements while standing in individuals with bilateral spastic cerebral palsy (BSCP). However, it remains unclear whether compensatory postural adjustments (CPAs) during movement increase to compensate for APA deficits. We investigated the anticipatory and compensatory activities of postural muscles during voluntary movement while standing in adolescents and young adults with BSCP. The study included seven participants with BSCP with level II on the Gross Motor Function Classification System (GMFCS), seven with BSCP with level III on the GMFCS, and fourteen healthy controls. The participants stood on a force platform and lifted a load under two weight conditions (light and heavy). The electromyographic activities of postural muscles were analyzed at time intervals typical for APAs and CPAs. The percentage of muscle activity in the CPA time epoch against the total muscle activity during the APA and CPA time epochs was higher in the two BSCP groups than in the control group. In the control group, a load-related modulation was observed only in the APA time epoch, whereas in the BSCP-II group, the load-related increase was observed in both the APA and CPA time epochs. No load-related modulations were observed in the BSCP-III group. These findings suggest that adolescents and young adults with BSCP exhibit an increase in the relative contribution of CPAs during voluntary movement and that there exist severity-related differences in the modulation of APAs and CPAs.

Age-related changes in the activation timing of postural muscles to the prime mover muscle for bilateral arm flexion during standing

Background

We aimed to obtain the standard values of age-related changes in the activation timing of postural muscles to the prime mover muscle (anterior deltoid [AD]) for bilateral arm flexion during standing.

Methods

The study participants were 276 children (aged 3–14 years) and 32 adults (aged 20–26 years). In response to a visual stimulus, participants raised both arms from a fully extended position as quickly as possible, stopped their arms voluntarily at a horizontal level at the shoulder, and maintained that position for 2 s. Ten test trials were performed. By using surface electromyography, the duration from the burst onset of the postural muscles to that of AD was measured as the starting time of the postural muscles (rectus abdominis [RA], erector spinae [ES], rectus femoris [RF], biceps femoris [BF], tibialis anterior [TA], gastrocnemius medialis [GcM], and soleus [SOL]). The starting time was presented as a negative value when the burst onset of the postural muscles preceded that of AD, which was defined as the preceding activation. A positive value for the starting time was defined as delayed activation.

Results

In adults, the burst onsets of ES and BF significantly preceded that of AD. In ES, the starting time preceded the onset of AD in those aged ≥ 5–6 years; no difference with adults was found at age 13–14 years. On the other hand, in BF, significant delayed activation was found at ages 3–4 to 11–12 years. While the starting time decreased with age, no significant preceding activation similar to adults was found, even at age 13–14 years. In TA, no significant difference with the onset of AD was found at age 3–6 years, and significant delayed activation was found at age ≥ 7–8 years. Significant delayed activation in GcM, SOL, RA, and RF was observed in all age groups, and no age-related changes were observed in children.

Conclusion

These findings could provide standard values from childhood to adolescence for age-related changes in anticipatory postural muscle activity during voluntary movement while standing and contribute to applications in the fields of sports and rehabilitation.

Resting state functional networks predict different aspects of postural control in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disorder causing postural control impairments. Postural control involves multiple domains, such as control of postural sway in stance, automatic postural responses (APRs) and anticipatory postural adjustments (APAs). We hypothesize that impairments in each postural domain is associated with resting-state functional connectivity (rsFC), accounted by predictive modeling and that cortical and cerebellar networks would predict postural control in people with PD (PwPD).

OBJECTIVE

To determine whether rsFC can predict three domains of postural control independently in PwPD and older adults (OA) based on predictive accuracy of models.

METHODS

The cohort consisted of 65 PwPD (67.7 +8.1 age) tested in their OFF-state and 42 OA (69.7 +8.2 age). Six body-worn, inertial sensors measured postural sway area while standing on foam, step length of APRs to a backward push-and-release perturbation, and magnitude of lateral APAs prior to voluntary gait initiation. Resting state-fMRI data was reported on 384 regions of interest that were grouped into 13 functional brain networks. Associations between rsFC and postural metrics were characterized using predictive modeling, with an independent training (n = 67) and validation (n = 40) dataset. Models were trained in the training sample and performance of the best model was validated in the independent test dataset.

RESULTS

rsFC of different brain networks predicted each domain of postural control in PD: Frontoparietal and Ventral Attention rsFC for APAs; Cerebellar-Subcortical and Visual rsFC and Auditory and Cerebellar-Subcortical rsFC for APRs; Ventral Attention and Ventral Multimodal rsFC for postural sway. In OA, CinguloOpercular and Somatomotor rsFC predicted APAs.

CONCLUSIONS

Our findings suggest that cortical networks predict postural control in PD and there is little overlap in brain network connectivities that predict different domains of postural control, given the rsFC methodology used. PwPD use different cortical networks for APAs compared to OA.

Neurodevelopment of Posture-movement Coordination from Late Childhood to Adulthood as Assessed From Bimanual Load-lifting Task: An Event-related Potential Study

In a bimanual task, proprioception provides information about position and movement of upper arms. Developmental studies showed improvement of proprioceptive accuracy and timing adjustments of muscular events from childhood to adulthood in bimanual tasks. However, the cortical maturational changes related to bimanual coordination is not fully understood. The aim of this study was to investigate cortical correlates underlying motor planning and upper limb stabilization performance at left (C3) and right (C4) sensorimotor cortices using event-related potential (ERP) analyses. We recruited 46 participants divided into four groups (12 children: 8-10 years, 13 early adolescents: 11-13 years, 11 late adolescents: 14-16 years and 10 young adults: 20-35 years). Participants performed a bimanual load-lifting task, where the left postural arm supported the load and the right motor arm lifted the load. Maximal amplitude of elbow rotation (MA%) of the postural arm, reaction time (RT) and EMG activity of biceps brachii bilaterally were computed. Laplacian-transformed ERPs of the electroencephalographic (EEG) signal response-locked to motor arm biceps EMG activity onset were analyzed over C3 and C4. We found a developmental effect for behavioral and EEG data denoted by significant decrease of MA% and RT with age, earlier inhibition of the biceps brachii of the postural arm in adults and earlier EEG activation/inhibition onset at C3/C4. Amplitude of the negative wave at C4 was higher in children and early adolescents compared to the other groups. In conclusion, we found a maturational process in cortical correlates related to motor planning and upper limb stabilization performance with interhemispheric lateralization appearing during adolescence. Findings may serve documenting bimanual performance in children with neurodevelopmental disorders.

Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study

Recently, the focus of functional connectivity analysis of human brain has shifted from merely revealing the inter-regional functional correlation over the entire scan duration to capturing the time-varying information of brain networks and characterizing time-resolved reoccurring patterns of connectivity. Much effort has been invested into developing approaches that can track changes in re-occurring patterns of functional connectivity over time. In this paper, we propose a sparse deep dictionary learning method to characterize the essential differences of reoccurring patterns of time-varying functional connectivity between different age groups. The proposed method combines both the interpretability of sparse dictionary learning and the capability of extracting sparse nonlinear higher-level features in the latent space of sparse deep autoencoder. In other words, it learns a sparse dictionary of the original data by considering the nonlinear representation of the data in the encoder layer based on a sparse deep autoencoder. In this way, the nonlinear structure and higher-level features of the data can be captured by deep dictionary learning. The proposed method is applied to the analysis of the Philadelphia Neurodevelopmental Cohort. It shows that there exist essential differences in the reoccurrence patterns of function connectivity between child and young adult groups. Specially, children have more diffusive functional connectivity patterns while young adults possess more focused functional connectivity patterns, and the brain function transits from undifferentiated systems to specialized neural networks with the growth.

Development of temporal and spatial characteristics of anticipatory postural adjustments during gait initiation in children aged 3-10 years

This study aimed to analyze the development of direction specificities of temporal and spatial control and the coordination pattern of anticipatory postural adjustment (APA) along the anteroposterior (AP) and mediolateral (ML) directions during gait initiation (GI) in children aged 3-10 years. This study included 72 healthy children aged 3-10 years and 14 young adults. The child population was divided into four groups by age: 3-4, 5-6, 7-8, and 9-10 years. The GI task included GI using the dominant limb. The peak center of feet pressure (COP) shifts during APAs (APA_peak), initiation time of COP shifts (APA_onset), and the COP vectors in the horizontal plane were calculated to evaluate the direction specificity of spatial, temporal, and coordination control, respectively. A difference in direction specificity development was found for the APA_peak. The APA_peak in the mediolateral axis, but not in the anteroposterior axis, was significantly higher in the 7-8 years age group than in other groups. Although APA_onset was not found for direction specificity, a significant difference between the adult and children groups (5-6 years, 7-8 years, and 9-10 years) was observed in the direction of the COP vector. In conclusion, the developmental process of the spatial, temporal, and coordination control of APAs during GI varied with age. Furthermore, the spatial control and coordination pattern of APAs was found to be direction specific. All components of APAs, namely temporal and spatial control, coordination pattern, and direction specificities, should be analyzed to capture the developmental process of anticipatory postural control.

Functional MRI-Specific Alterations in Executive Control Network in Mild Cognitive Impairment: An ALE Meta-Analysis

Background: Mild cognitive impairment (MCI) is regarded as a transitional stage between normal aging and Alzheimer's disease (AD) dementia. MCI individuals with deficits in executive function are at higher risk for progressing to AD dementia. Currently, there is no consistent result for alterations in the executive control network (ECN) in MCI, which makes early prediction of AD conversion difficult. The aim of the study was to find functional MRI-specific alterations in ECN in MCI patients by expounding on the convergence of brain regions with functional abnormalities in ECN.

Methods: We searched PubMed, Embase, and Web of Science to identify neuroimaging studies using methods including the amplitude of low frequency fluctuation/fractional amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity in MCI patients. Based on the Activation Likelihood Estimation algorithm, the coordinate-based meta-analysis and functional meta-analytic connectivity modeling were conducted.

Results: A total of 25 functional imaging studies with MCI patients were included in a quantitative meta-analysis. By summarizing the included articles, we obtained specific brain region changes, mainly including precuneus, cuneus, lingual gyrus, middle frontal gyrus, posterior cingulate cortex, and cerebellum posterior lobe, in the ECN based on these three methods. The specific abnormal brain regions indicated that there were interactions between the ECN and other networks.

Conclusions: This study confirms functional imaging specific abnormal markers in ECN and its interaction with other networks in MCI. It provides novel targets and pathways for individualized and precise interventions to delay the progression of MCI to AD.

Weighted Brain Network Metrics for Decoding Action Intention Understanding Based on EEG

Background: Understanding the action intentions of others is important for social and human-robot interactions. Recently, many state-of-the-art approaches have been proposed for decoding action intention understanding. Although these methods have some advantages, it is still necessary to design other tools that can more efficiently classify the action intention understanding signals.

New Method: Based on EEG, we first applied phase lag index (PLI) and weighted phase lag index (WPLI) to construct functional connectivity matrices in five frequency bands and 63 micro-time windows, then calculated nine graph metrics from these matrices and subsequently used the network metrics as features to classify different brain signals related to action intention understanding.

Results: Compared with the single methods (PLI or WPLI), the combination method (PLI+WPLI) demonstrates some overwhelming victories. Most of the average classification accuracies exceed 70%, and some of them approach 80%. In statistical tests of brain network, many significantly different edges appear in the frontal, occipital, parietal, and temporal regions.

Conclusions: Weighted brain networks can effectively retain data information. The integrated method proposed in this study is extremely effective for investigating action intention understanding. Both the mirror neuron and mentalizing systems participate as collaborators in the process of action intention understanding.

Intrinsic Cortico-Subcortical Functional Connectivity in Developmental Dyslexia and Developmental Coordination Disorder

Developmental dyslexia (DD) and developmental coordination disorder (DCD) are distinct diagnostic disorders. However, they also frequently co-occur and may share a common etiology. It was proposed conceptually a neural network framework that explains differences and commonalities between DD and DCD through impairments of distinct or intertwined cortico-subcortical connectivity pathways. The present study addressed this issue by exploring intrinsic cortico-striatal and cortico-cerebellar functional connectivity in a large (n = 136) resting-state fMRI cohort study of 8–12-year-old children with typical development and with DD and/or DCD. We delineated a set of cortico-subcortical functional circuits believed to be associated with the brain’s main functions (visual, somatomotor, dorsal attention, ventral attention, limbic, frontoparietal control, and default-mode). Next, we assessed, using general linear and multiple kernel models, whether and which circuits distinguished between the groups. Findings revealed that somatomotor cortico-cerebellar and frontoparietal cortico-striatal circuits are affected in the presence of DCD, including abnormalities in cortico-cerebellar connections targeting motor-related regions and cortico-striatal connections mapping onto posterior parietal cortex. Thus, DCD but not DD may be considered as an impairment of cortico-subcortical functional circuits.

Positive verbal suggestion optimizes postural control

Balance is a very important function that allows maintaining a stable stance needed for many daily life activities and for preventing falls. We investigated whether balance control could be improved by a placebo procedure consisting of verbal suggestion. Thirty healthy volunteers were randomized in two groups (placebo and control) and asked to perform a single-leg stance task in which they had to stand as steadily as possible on the dominant leg. The task was repeated in three sessions (T0, T1, T2). At T1 and T2 an inert treatment was applied on the leg, by informing the placebo group that it was effective in improving balance. The control group was overtly told that treatment was inert. An accelerometer applied on participants’ leg allowed to measure body sways in different directions. Subjective parameters, like perception of stability, were also collected. Results showed that the placebo group had less body sways than the control group at T2, both in the three-dimensional space and in the anterior-posterior direction. Furthermore, the placebo group perceived to be more stable than the control group. This study represents the first evidence that placebo effect optimizes posture, with a potential translational impact in patients with postural and gait disturbances.