Abnormalities in the default mode network in late-life depression: A study of resting-state fMRI

A comprehensive systematic review of fMRI studies on brain connectivity in healthy children and adolescents: Current insights and future directions

This systematic review considered evidence of children's and adolescents' typical brain connectivity development studied through resting-state functional magnetic resonance imaging (rs-fMRI). With aim of understanding the state of the art, what has been researched thus far and what remains unknown, this paper reviews 58 studies from 2013 to 2023. Considering the results, rs-fMRI stands out as an appropriate technique for studying language and attention within cognitive domains, and personality traits such as impulsivity and empathy. The most used analyses encompass seed-based, independent component analysis (ICA), the amplitude of the low frequency fluctuations (ALFF), and fractional ALFF (fALFF). The findings highlight key themes, including age-related changes in intrinsic connectivity, sex-specific patterns, and the relevance of the Default Mode Network (DMN). Overall, there is a need for longitudinal approaches to trace the typical developmental trajectory of neural networks from childhood through adolescence with fMRI at rest.

Rationale and design of a double-blinded, randomized placebo-controlled trial of 40 Hz light neurostimulation therapy for depression (FELIX)

BACKGROUND

Major depressive disorder (MDD) is a debilitating condition that affects more than 300 million people worldwide. Current treatments are based on a trial-and-error approach, and reliable biomarkers are needed for more informed and personalized treatment solutions. One of the potential biomarkers, gamma-frequency (30-80 Hz) brainwaves, are hypothesized to originate from the excitatory-inhibitory interaction between the pyramidal cells and interneurons. The imbalance between this interaction is described as a crucial pathological mechanism in neuropsychiatric conditions, including MDD, and the modulation of this pathological interaction has been investigated as a potential target. Previous studies attempted to induce gamma activity in the brain using rhythmic light and sound stimuli (GENUS - Gamma Entrainment Using Sensory stimuli) that resulted in neuroprotective effects in Alzheimer's disease (AD) patients and animal models. Here, we investigate the antidepressant, cognitive, and electrophysiological effects of the novel light therapy approach using 40 Hz masked flickering light for patients diagnosed with MDD.

METHODS AND DESIGN

Sixty patients with a current diagnosis of a major depressive episode will be enrolled in a randomized, double-blinded, placebo-controlled trial. The active treatment group will receive 40 Hz masked flickering light stimulation while the control group will receive continuous light matched in color temperature and brightness. Patients in both groups will get daily light treatment in their own homes and will attend four follow-up visits to assess the symptoms of depression, including depression severity measured by Hamilton Depression Rating Scale (HAM-D17), cognitive function, quality of life and sleep, and electroencephalographic changes. The primary endpoint is the mean change from baseline to week 6 in depression severity (HAM-D6 subscale) between the groups.

Neuroimaging of neuropsychological disturbances following ischaemic stroke (CONNECT): a prospective cohort study protocol

INTRODUCTION

Neuropsychiatric distubance is a common clinical manifestation in acute ischemic stroke. However, it is frequently overlooked by clinicians. This study aimed to explore the possible aetiology and pathogenesis of neuropsychiatric disturbances following ischaemic stroke (NDIS) from an anatomical and functional perspective with the help of neuroimaging methods.

METHOD AND ANALYSIS

CONNECT is a prospective cohort study of neuroimaging and its functional outcome in NDIS. We aim to enrol a minimum of 300 individuals with first-ever stroke. The neuropsychological disturbances involved in this study include depression, anxiety disorder, headache, apathy, insomnia, fatigue and cognitive impairment. Using scales that have been shown to be effective in assessing the above symptoms, the NDIS evaluation battery requires at least 2 hours at baseline. Moreover, all patients will be required to complete 2 years of follow-up, during which the NDIS will be re-evaluated at 3 months, 12 months and 24 months by telephone and 6 months by outpatient interview after the index stroke. The primary outcome of our study is the incidence of NDIS at the 6-month mark. Secondary outcomes are related to the severity of NDIS as well as functional rehabilitation of patients. Functional imaging evaluation will be performed at baseline and 6-month follow-up using specific sequences including resting-state functional MRI, diffusion tensor imaging, T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, arterial spin labelling, quantitative susceptibility mapping and fluid-attenuated inversion recovery imaging. In addition, we collect haematological information from patients to explore potential biological and genetic markers of NDIS through histological analysis.

ETHICS AND DISSEMINATION

The CONNECT Study was approved by the Ethics Review Committee of the First Hospital of the University of Science and Technology of China (2021-ky012) and written informed consent will be obtained from all participants. Results will be disseminated via a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ChiCTR2100043886.

Challenges in Identifying Individualized Brain Biomarkers of Late Life Depression

Research into neuroimaging biomarkers for Late Life Depression (LLD) has identified neural correlates of LLD including increased white matter hyperintensities and reduced hippocampal volume. However, studies into neuroimaging biomarkers for LLD largely fail to converge. This lack of replicability is potentially due to challenges linked to construct variability, etiological heterogeneity, and experimental rigor. We discuss suggestions to help address these challenges, including improved construct standardization, increased sample sizes, multimodal approaches to parse heterogeneity, and the use of individualized analytical models.

Diagnosis of late-life depression using structural equation modeling and dynamic effective connectivity during resting fMRI

BACKGROUND

Late-life depression (LLD) is characterized by cognitive and social impairments. Determining neurobiological alterations in connectivity in LLD by means of fMRI may lead to a better understanding of the neural basis underlying this disorder and more precise diagnostic markers. The primary objective of this paper is to identify a structural model that best explains the dynamic effective connectivity (EC) of the default mode network (DMN) in LLD patients compared to controls.

METHODS

Twenty-seven patients and 29 healthy controls underwent resting-state fMRI during a period of eight minutes. In both groups, jackknife correlation matrices were generated with six ROIs of the DMN that constitute the posterior DMN (pDMN). The different correlation matrices were used as input to estimate each structural equation model (SEM) for each subject in both groups incorporating dynamic effects.

RESULTS

The results show that the proposed LLD diagnosis algorithm achieves perfect accuracy in classifying LLD patients and controls. This differentiation is based on three aspects: the importance of ROIs 4 and 6, which seem to be the most distinctive among the subnetworks; the shape that the specific connections adopt in their networks, or in other words, the directed connections that are established among the ROIs in the pDMN for each group; and the number of dynamic effects that seem to be greater throughout the six ROIs studied [t = 54.346; df = 54; p < .001; 95 % CI difference = 5.486-5.906].

LIMITATIONS

The sample size was moderate, and the participants continued their current medications.

CONCLUSIONS

The network models that we developed describe a pattern of dynamic activation in the pDMN that may be considered a possible biomarker for LLD, which may allow early diagnosis of this disorder.

Neural activity in adults with major depressive disorder differs from that in healthy individuals: A resting-state functional magnetic resonance imaging study

OBJECTIVE

Currently, findings regarding resting-state functional magnetic resonance imaging studies of major depressive disorder (MDD) are inconsistent. In contrast to the previously used a priori seed-based functional connectivity analyses, this study employed whole-brain exploratory analyses and aimed to explore neural activity patterns in Chinese adults with MDD.

MATERIALS AND METHODS

Specifically, this study examined the amplitude of low-frequency fluctuations within the whole brain and adopted a large-scale brain network template to explore the core dysfunctional brain regions in individuals with MDD.

RESULTS

Overall, 32 individuals with MDD and 32 healthy controls were evaluated. Compared to healthy controls, individuals with MDD showed more profound alterations in the amplitude of low-frequency fluctuations in the temporolimbic affective circuit (e.g., middle temporal gyrus and parahippocampus) and default mode network (e.g., precuneus and thalamus). Moreover, functional connectivity between the left mid-insula and parietal regions within the sensorimotor network was weaker in individuals with MDD than in healthy controls.

CONCLUSION

In conclusion, the neural characteristics of MDD correspond to cognitive deficits in self-referential processing and emotional processing and are related to a risk of sensory disorders or psychomotor retardation. These findings present neural markers that may be used to identify MDD, contributing to clinical diagnosis.