Study subnetwork developing pattern of autism children by non-negative matrix factorization.

Researchers studied brain wave patterns in autistic children compared to typical children using advanced computer analysis. They found differences in how the left and right sides of autistic children's brains work together, particularly in specific brain wave frequencies. These differences were linked to thinking skills and development in opposite ways between autistic and typical children, suggesting the autistic brain develops and functions differently.

This study used non-negative matrix factorization (NMF) to analyze brain network patterns in autistic children compared to typically developing children using magnetoencephalography data. The researchers decomposed brain association matrices to identify subnetworks and examined their expression through energy and entropy measures. Key findings included a left-lateralized alpha band subnetwork showing opposite correlations with cognitive indices between groups, and a right hemisphere gamma band subnetwork showing negative correlations with development indices in the autism group. The study suggests these patterns may relate to mirror neuron dysfunction and weakened high-frequency neural processing in autism.

Results suggest autistic children show distinct brain network development patterns, particularly in lateralization and high-frequency processing. These findings may inform understanding of cognitive and developmental differences, though clinical applications require validation in larger, well-characterized samples.

Sample size not reported. Study type unclear. Findings are largely correlational without causal inference. Limited generalizability without demographic details. Cross-sectional design cannot establish developmental trajectories despite discussing development patterns.

As a developmental disorder, the brain networks of autism children show abnormal patterns compared with that of typically developing. The differences between them are not stable due to the developing progress of children. It has become a choice to study the differences of developing trajectories between autistic and typically developing children by investigating the change of each group respectively. Related researches studied the developing of brain network by analyzing the relationship between network indices of the entire or sub brain networks and the cognitive developing scores.

As a matrix decomposition algorithm, non-negative matrix factorization (NMF) was applied to decompose the association matrices of brain networks. By NMF, we can obtain subnetworks in an unsupervised way. The association matrices of autism and control children were estimated by their magnetoencephalography data. NMF was applied to decompose the matrices to obtain common subnetworks of both groups.

Then we calculated the expression of each subnetwork in each child's brain network by two indices, energy and entropy. The relationship between the expression and the cognitive and development indices were investigated. We found a subnetwork with left lateralization pattern in α band showed different expression tendency in two groups. The expression indices of two groups were correlated with cognitive indices in autism and control group in an opposite way.

In γ band, a subnetwork with strong connections on right hemisphere of brain showed a negative correlation between the expression indices and development indices in autism group. NMF algorithm can effectively decompose brain network to meaningful subnetworks. The finding of α band subnetworks confirms the results of abnormal lateralization of autistic children mentioned in relevant studies. We assume the results of decrease of expression of the subnetwork may relate to the dysfunction of mirror neuron.

The decrease expression of γ subnetwork of autism may be related to the weaken process of high-frequency neurons in the neurotrophic competition.