The parcellation of cingulate cortex in neonatal period based on resting-state functional MRI.

The human cingulate cortex (CC) is a complex region that is characterized by heterogeneous cytoarchitecture, connectivity, and function, and it is associated with various cognitive functions. The adult CC has been divided into various subregions, and this subdivision is highly consistent with its functional differentiation. However, only a few studies have focused on the function of neonatal CC. The aim of this study was to describe the cingulate segregation and the functional connectivity of each subdivision in full-term neonates (n = 60) based on resting-state functional magnetic resonance imaging. The neonatal CC was divided into three subregions, and each subregion showed specific connectivity patterns. The anterior cingulate cortex was mainly correlated with brain regions related to the salience (affected) network and default mode network (DMN), the midcingulate cortex was related to motor areas, and the posterior cingulate cortex was coupled with DMN. Moreover, we found that the cingulate subregions showed distinct functional profiles with major brain networks, which were defined using independent component analysis, and exhibited functional lateralization. This study provided new insights into the understanding of the functional specialization of neonatal CC, and these findings may have significant clinical implications, especially in predicting neurological disorder.

Microstructural alterations in white matter and related neurobiology based on the new clinical subtypes of Parkinson's disease.

Background and objectives: The advent of new clinical subtyping systems for Parkinson's disease (PD) has led to the classification of patients into distinct groups: mild motor predominant (PD-MMP), intermediate (PD-IM), and diffuse malignant (PD-DM). Our goal was to evaluate the efficacy of diffusion tensor imaging (DTI) in the early diagnosis, assessment of clinical progression, and prediction of prognosis of these PD subtypes. Additionally, we attempted to understand the pathological mechanisms behind white matter damage using single-photon emission computed tomography (SPECT) and cerebrospinal fluid (CSF) analyses. Methods: We classified 135 de novo PD patients based on new clinical criteria and followed them up after 1 year, along with 45 healthy controls (HCs). We utilized tract-based spatial statistics to assess the microstructural changes of white matter at baseline and employed multiple linear regression to examine the associations between DTI metrics and clinical data at baseline and after follow-up. Results: Compared to HCs, patients with the PD-DM subtype demonstrated reduced fractional anisotropy (FA), increased axial diffusivity (AD), and elevated radial diffusivity (RD) at baseline. The FA and RD values correlated with the severity of motor symptoms, with RD also linked to cognitive performance. Changes in FA over time were found to be in sync with changes in motor scores and global composite outcome measures. Furthermore, baseline AD values and their rate of change were related to alterations in semantic verbal fluency. We also discovered the relationship between FA values and the levels of α-synuclein and ß-amyloid. Reduced dopamine transporter uptake in the left putamen correlated with RD values in superficial white matter, motor symptoms, and autonomic dysfunction at baseline as well as cognitive impairments after 1 year. Conclusions: The PD-DM subtype is characterized by severe clinical symptoms and a faster progression when compared to the other subtypes. DTI, a well-established technique, facilitates the early identification of white matter damage, elucidates the pathophysiological mechanisms of disease progression, and predicts cognitively related outcomes. The results of SPECT and CSF analyses can be used to explain the specific pattern of white matter damage in patients with the PD-DM subtype.