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The amygdala is a part of the brain that is responsible for emotions and learning. It is made up of four different groups of nuclei. Some disorders such as autism and anxiety are linked to abnormalities in the amygdala function. Although it is crucial for human development, little is known about the structural and functional growth of the amygdala, especially in terms of its nuclei.
Recent studies found that the amygdala's functional development continues through adolescence, but its structural growth is inconsistent. Some studies show no change in the amygdalar volume, while others report a slight increase or different changes between boys and girls. It is suggested that the development of the amygdala's connectivity patterns may be the reason for functional growth.
Studies on non-human primates revealed that the amygdala's maturing connectivity patterns affect its function in the brain. Projections from the amygdala mature well after birth, meaning they are refined as social and emotional development occurs. Animal studies also showed that the four main nucleus groups within the amygdala have diverse functions and connectivity.
Previous neuroimaging research found that the amygdala's nuclei could be estimated in humans but only in adults. It is unknown if the structural connectivity of the amygdala changes through human development and if all the nucleus groups undergo developmental changes in DWI (diffusion weighted imaging) connectivity.
To address this gap, the research team measured developmental changes in the probability of connections between the amygdala's nuclei and the rest of the brain using DWI probabilistic tractography. The team found that the amygdala does become more specific in its DWI connectivity patterns with age. They also discovered that they could predict an individual's age based on the amygdala's connectivity pattern. Finally, they segmented the amygdala into its four main nucleus groups to see which subregion of the amygdala changed during development.
In this study, we aimed to understand how the structure of the human amygdala, a key emotional processing center in the brain, changes during development. To do this, we studied over 150 subjects aged 5 to 30 years, analyzing the amygdala's connections with other regions of the brain using diffusion-weighted imaging(DWI) and a machine-learning approach.
Our results revealedthat the amygdala is initially connected with a broad range of cortical and subcortical regions in children, but becomes increasingly sparser and more targeted in its connections with age. We found that certain regions were highly predictive of age; in particular, younger ages were associated with higheramygdala connectivity to certain occipitotemporal and subcortical/basal ganglia regions, while higher connectivity to the para-hippocampus and hippocampus predicted older ages. These age-related changes were not general to all targets of the brain, but rather were specific to a subset of the amygdala's connectivity pattern.
Interestingly, we also discovered unexpected predictors of age, such as the parietal cortices, which are not commonly considered part of the "affective" or limbic network. Our findings suggest that these connections can be detected with tractography and demonstrate the benefits of using DWI fingerprints combined with machine-learning approaches to explore connectivity patterns in the human brain.
We also observed that while most of the predictive connections decreased with age, some regions, such as the para-hippocampal cortex and hippocampus, showed increased connectivity with the amygdala in adults compared to children. This suggests an increasing role for the amygdala in integrating emotional content during contextual processing and memory encoding.
Our results also revealed that the different nuclei of the amygdala show developmental differences in both connectivity patterns and how those patterns change across development. The basal, lateral, and central nuclei showed the strongest correlations with age and best reflected the changes seen at the level of the whole amygdala, suggesting that the developmental changes observed at the level of the whole amygdala are principally the result of development of these nuclei.
Overall, our findings demonstrate the dynamic developmental trajectory of connectivity with the amygdala and discern the specific anatomical targets whose connectivity changes the most. While non-invasive methods such as DWI have their limitations, they are the only alternative for studying the development of human brain anatomy in both health and illness. Our present findings provide insights into the functional maturation of the amygdala and its connectivity patterns and may have implications for the treatment of emotional disorders.