Altered activation of the dorsal anterior cingulate cortex during oddball performance in individuals at risk for Alzheimer's disease.

INTRODUCTION: The neural mechanisms underlying neurodegenerative disorders in the elderly remain elusive, despite extensive neuroimaging research in recent decades. Amnestic type mild cognitive impairment (aMCI) and late-life major depressive disorder (MDD) are two such conditions characterized by intersecting cognitive and affective symptomatology, and they are at a higher risk for Alzheimer's disease. MATERIALS AND METHODS: This study analyzed the neural underpinnings of cognitive and depressive symptoms in a cohort comprising 12 aMCI subjects, 24 late-life MDD patients, and 26 healthy controls (HCs). Participants underwent a detailed neuropsychological assessment and completed a visual attentional oddball task during functional magnetic resonance imaging (fMRI), with evaluations at baseline and at 2-year follow-up. RESULTS: Initial findings showed that aMCI subjects had reduced dACC activation during oddball (target) stimulus detection, a pattern that persisted in longitudinal analyses and correlated with cognitive functioning measures. For HCs, subsequent dACC activation was linked to depression scores. Furthermore, in the affective-cognitive altered groups, later dACC activation correlated with oddball and memory performance. CONCLUSIONS: These findings enhance our comprehension of the neurobiological basis of cognitive and depressive disturbances in aging, indicating that dACC activation in response to a visual attentional oddball task could serve as a neural marker for assessing cognitive impairment and depression in conditions predisposing to Alzheimer's disease.

Effective connectivity of the locus coeruleus in patients with late-life Major Depressive Disorder or mild cognitive impairment.

INTRODUCTION: We compared effective connectivity from the locus coeruleus (LC) during the resting-state in patients with late-life Major Depressive Disorder (MDD), individuals with amnestic Mild Cognitive Impairment (aMCI), and Healthy Controls (HCs). PARTICIPANTS: 23 patients with late-life MDD, 22 patients with aMCI, and 28 HCs. MATERIAL AND METHODS: Participants were assessed in two time-points, 2 years apart. They underwent a resting-state functional magnetic resonance imaging and a high-resolution anatomical acquisition, as well as clinical assessments. Functional imaging data were analyzed with dynamic causal modeling, and parametric empirical Bayes model was used to map effective connectivity between 7 distinct nodes: 4 from the locus coeruleus and 3 regions displaying gray matter decreases during the two-year follow-up period. RESULTS: Longitudinal analysis of structural data identified three clusters of larger over-time gray matter volume reduction in patients (MDD+aMCI vs. HCs): the right precuneus, and the visual association and parahippocampal cortices. aMCI patients showed decreased effective connectivity from the left rostral to caudal portions of the LC, while connectivity from the left rostral LC to the parahippocampal cortex increased. In MDD, there was a decline in effective connectivity across LC caudal seeds, and increased connectivity from the left rostral to the left caudal LC seed over time. Connectivity alterations with cortical regions involved cross-hemisphere increases and same-hemisphere decreases. CONCLUSIONS: Our discoveries provide insight into the dynamic changes in effective connectivity in individuals with late-life MDD and aMCI, also shedding light on the mechanisms potentially contributing to the onset of neurodegenerative disorders.

Trait anxiety is associated with attentional brain networks.

Trait anxiety is a well-established risk factor for anxiety and depressive disorders, yet its neural correlates are not clearly understood. In this study, we investigated the neural correlates of trait anxiety in a large sample (n = 179) of individuals who completed the trait and state versions of the State-Trait Anxiety Inventory and underwent resting-state functional magnetic resonance imaging. We used independent component analysis to characterize individual resting-state networks (RSNs), and multiple regression analyses to assess the relationship between trait anxiety and intrinsic connectivity. Trait anxiety was significantly associated with intrinsic connectivity in different regions of three RSNs (dorsal attention network, default mode network, and auditory network) when controlling for state anxiety. These RSNs primarily support attentional processes. Notably, when state anxiety was not controlled for, a different pattern of results emerged, highlighting the importance of considering this factor in assessing the neural correlates of trait anxiety. Our findings suggest that trait anxiety is uniquely associated with resting-state brain connectivity in networks mainly supporting attentional processes. Moreover, controlling for state anxiety is crucial when assessing the neural correlates of trait anxiety. These insights may help refine current neurobiological models of anxiety and identify potential targets for neurobiologically-based interventions.

Development and Validation of a Smartphone-Based App for the Longitudinal Assessment of Anxiety in Daily Life.

Current methods to assess human anxiety often ignore that anxiety is a dynamic process and have limitations such as high recall bias and low generalizability to real life. Smartphone apps using ecological momentary assessment (EMA) may overcome such limitations. We developed a smartphone app for the longitudinal evaluation of anxiety symptoms using EMA. We assessed the feasibility (retention and compliance) and psychometric properties (reliability and validity) of the app over 6 months in a sample of 99 participants with different levels of anxiety. The EMA-based smartphone app was highly feasible. It showed excellent within-person and between-person reliability, high convergent and moderate discriminant validity, and significant incremental validity. Assessing anxiety longitudinally using a smartphone and following EMA principles is feasible and can be reliable and valid. Studies combining EMA-based anxiety longitudinal assessments with other assessment methods deserve further research and may offer novel insights into human anxiety.