Characterization of whole-brain task-modulated functional connectivity in response to nociceptive pain: A multisensory comparison study

Language and sensory characteristics are reflected in voice-evoked responses in low birth weight children

BACKGROUND

Children born with very low birth weight (VLBW) are at higher risk for cognitive impairment, including language deficits and sensorimotor difficulties. Voice-evoked response (P1m), which has been suggested as a language development biomarker in young children, remains unexplored for its efficacy in VLBW children. Furthermore, the relation between P1m and sensory difficulties in VLBW children remains unclear.

METHODS

40 children with VLBW were recruited at 5-to-6 years old (26 male, 14 female, mean age of months ± SD, 80.0 ± 4.9). We measured their voice-evoked brain response using child-customized magnetoencephalography (MEG) and examined the relation between P1m and language conceptual inference ability and sensory characteristics.

RESULTS

The final sample comprised 36 children (23 boys, 13 girls; ages 61-86 months; gestational ages 24-36 weeks). As a result of multiple regression analysis, voice-evoked P1m in the left hemisphere was correlated significantly with language ability (β = 0.414 P = 0.015) and sensory hypersensitivity (β = 0.471 P = 0.005).

CONCLUSION

Our findings indicate that the relation between P1m and language conceptual inference ability observed in term children in earlier studies is replicated in VLBW children, and suggests P1m intensity as a biomarker of sensory sensitivity characteristics.

IMPACT

We investigated brain functions related to language development and sensory problems in very low birth-weight children. In very low birth weight children at early school age, brain responses to human voices are associated with language conceptual inference ability and sensory hypersensitivity. These findings promote a physiological understanding of both language development and sensory characteristics in very low birth weight children.

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

How Discrimination Gets Under the Skin: Biological Determinants of Discrimination Associated With Dysregulation of the Brain-Gut Microbiome System and Psychological Symptoms

BACKGROUND

Discrimination is associated with negative health outcomes as mediated in part by chronic stress, but a full understanding of the biological pathways is lacking. Here we investigate the effects of discrimination involved in dysregulating the brain-gut microbiome (BGM) system.

METHODS

A total of 154 participants underwent brain magnetic resonance imaging to measure functional connectivity. Fecal samples were obtained for 16S ribosomal RNA profiling and fecal metabolites and serum for inflammatory markers, along with questionnaires. The Everyday Discrimination Scale was administered to measure chronic and routine experiences of unfair treatment. A sparse partial least squares-discriminant analysis was conducted to predict BGM alterations as a function of discrimination, controlling for sex, age, body mass index, and diet. Associations between discrimination-related BGM alterations and psychological variables were assessed using a tripartite analysis.

RESULTS

Discrimination was associated with anxiety, depression, and visceral sensitivity. Discrimination was associated with alterations of brain networks related to emotion, cognition and self-perception, and structural and functional changes in the gut microbiome. BGM discrimination-related associations varied by race/ethnicity. Among Black and Hispanic individuals, discrimination led to brain network changes consistent with psychological coping and increased systemic inflammation. For White individuals, discrimination was related to anxiety but not inflammation, while for Asian individuals, the patterns suggest possible somatization and behavioral (e.g., dietary) responses to discrimination.

CONCLUSIONS

Discrimination is attributed to changes in the BGM system more skewed toward inflammation, threat response, emotional arousal, and psychological symptoms. By integrating diverse lines of research, our results demonstrate evidence that may explain how discrimination contributes to health inequalities.

Multisensory sensitivity differentiates between multiple chronic pain conditions and pain-free individuals

ABSTRACT

Multisensory sensitivity (MSS) to nonpainful stimuli has been identified as a risk factor for the presence of coexisting chronic pain conditions. However, it remains unclear whether MSS can differentiate pain phenotypes involving different levels of central sensitivity. Both pain-free and those with chronic pain, particularly fibromyalgia (FM), migraine, or low back pain (LBP) were recruited, with pain comorbidities assessed. MSS was highest in FM, followed by migraine, then LBP, and lowest in pain-free individuals (adjusted between condition Cohen d = 0.32-1.2, P ≤ 0.0007). However, when secondly grouping patients by the total number of pain comorbidities reported, those with a single pain condition (but not FM) did not have significantly elevated MSS vs pain-free individuals (adj d= 0.17, P = 0.18). Elevated MSS scores produced increased odds of having 2 or more pain comorbidities; OR [95% CI] =2.0 [1.15, 3.42], without, and 5.6 [2.74, 11.28], with FM ( P ≤ 0.0001). Furthermore, those with low MSS levels were 55% to 87% less likely to have ≥ 2 pain comorbidities with or without FM (OR 0.45 [0.22, 0.88]-0.13 [0.05, 0.39]; P ≤ 0.0001). Our findings support that MSS can differentiate between pain phenotypes with different degrees of expected central mechanism involvement and also serve as a risk and resilience marker for total coexisting chronic pain conditions. This supports the use of MSS as a marker of heightened central nervous system processing and thus may serve as a clinically feasible assessment to better profile pain phenotypes with the goal of improving personalized treatment.

EEG emotion recognition based on cross-frequency granger causality feature extraction and fusion in the left and right hemispheres

EEG emotion recognition based on Granger causality (GC) brain networks mainly focus on the EEG signal from the same-frequency bands, however, there are still some causality relationships between EEG signals in the cross-frequency bands. Considering the functional asymmetric of the left and right hemispheres to emotional response, this paper proposes an EEG emotion recognition scheme based on cross-frequency GC feature extraction and fusion in the left and right hemispheres. Firstly, we calculate the GC relationship of EEG signals according to the frequencies and hemispheres, and mainly focus on the causality of the cross-frequency EEG signals in left and right hemispheres. Then, to remove the redundant connections of the GC brain network, an adaptive two-stage decorrelation feature extraction scheme is proposed under the condition of maintaining the best emotion recognition performance. Finally, a multi-GC feature fusion scheme is designed to balance the recognition accuracy and feature number of each GC feature, which comprehensively considers the influence of the recognition accuracy and computational complexity. Experimental results on the DEAP emotion dataset show that the proposed scheme can achieve an average accuracy of 84.91% for four classifications, which improved the classification accuracy by up to 8.43% compared with that of the traditional same-frequency band GC features.

Interconnected sub-networks of the macaque monkey gustatory connectome

Macroscopic taste processing connectivity was investigated using functional magnetic resonance imaging during the presentation of sour, salty, and sweet tastants in anesthetized macaque monkeys. This examination of taste processing affords the opportunity to study the interactions between sensory regions, central integrators, and effector areas. Here, 58 brain regions associated with gustatory processing in primates were aggregated, collectively forming the gustatory connectome. Regional regression coefficients (or β-series) obtained during taste stimulation were correlated to infer functional connectivity. This connectivity was then evaluated by assessing its laterality, modularity and centrality. Our results indicate significant correlations between same region pairs across hemispheres in a bilaterally interconnected scheme for taste processing throughout the gustatory connectome. Using unbiased community detection, three bilateral sub-networks were detected within the graph of the connectome. This analysis revealed clustering of 16 medial cortical structures, 24 lateral structures, and 18 subcortical structures. Across the three sub-networks, a similar pattern was observed in the differential processing of taste qualities. In all cases, the amplitude of the response was greatest for sweet, but the network connectivity was strongest for sour and salty tastants. The importance of each region in taste processing was computed using node centrality measures within the connectome graph, showing centrality to be correlated across hemispheres and, to a smaller extent, region volume. Connectome hubs exhibited varying degrees of centrality with a prominent leftward increase in insular cortex centrality. Taken together, these criteria illustrate quantifiable characteristics of the macaque monkey gustatory connectome and its organization as a tri-modular network, which may reflect the general medial-lateral-subcortical organization of salience and interoception processing networks.