Neurocognitive Markers of Depression

Kaiser, Roselinde H.

doi:10.1016/j.biopsych.2016.11.007

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…However, when such research is conducted exclusively using categorical case-control designs, it could be insufficient for understanding individual differences in attention bias. Depression is a complex and heterogeneous family of disorders, with varying symptom presentations, etiologies, and functional impairments exhibited across individuals (Kaiser, 2017). Thus, attention biases may not characterize different depressed individuals to the same extent.…”

Section: Attention Bias Across Clinical Phenotypes: Rumination and Dementioning

confidence: 99%

Attention Bias in Rumination and Depression: Cognitive Mechanisms and Brain Networks

Kaiser

Snyder

Goer

et al. 2018

Clinical Psychological Science

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Depressed individuals exhibit biased attention to negative emotional information. However, much remains unknown about (1) the neurocognitive mechanisms of attention bias (e.g., qualities of negative information that evoke attention bias, or functional brain network dynamics that may reflect a propensity for biased attention) and (2) distinctions in the types of attention bias related to different dimensions of depression (e.g., ruminative depression). Here, in 50 women, clinical depression was associated with facilitated processing of negative information only when such information was self-descriptive and task-relevant. However, among depressed individuals, trait rumination was associated with biases towards negative self-descriptive information regardless of task goals, especially when negative self-descriptive material was paired with self-referential images that should be ignored. Attention biases in ruminative depression were mediated by dynamic variability in frontoinsular resting-state functional connectivity. These findings highlight potential cognitive and functional network mechanisms of attention bias specifically related to the ruminative dimension of depression.

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Section: Attention Bias Across Clinical Phenotypes: Rumination and Dementioning

confidence: 99%

Attention Bias in Rumination and Depression: Cognitive Mechanisms and Brain Networks

Kaiser

Snyder

Goer

et al. 2018

Clinical Psychological Science

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“…Specifically, adult depression was characterized by increased and more variable resting-state functional connectivity between regions of medial prefrontal cortex and insula, and these frontoinsular abnormalities were associated with the tendency towards negative, repetitive introspection (i.e., rumination) [13] and attention biases towards negative, self-referential information [14]. This evidence has motivated a neurocognitive model of depression in which abnormalities in frontoinsular circuits linking insula with lateral and medial prefrontal systems in the FN and DN, are proposed to contribute to deficits regulating internally-oriented attention, which are cardinal to depression [15,16].…”

Section: Introductionmentioning

confidence: 99%

Abnormal frontoinsular-default network dynamics in adolescent depression and rumination: a preliminary resting-state co-activation pattern analysis

Kaiser

Kang

Lew

et al. 2019

Neuropsychopharmacol.

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Clinical depression commonly emerges in adolescence, which is also a time of developing cognitive ability and related large-scale functional brain networks implicated in depression. In depressed adults, abnormalities in the dynamic functioning of frontoinsular networks, in particular, have been observed and linked to negative rumination. Thus, network dynamics may provide new insight into teen pathophysiology. Here, adolescents (n = 45, ages 13-19) with varying severity of depressive symptoms completed a resting-state functional MRI scan. Functional networks were evaluated using co-activation pattern analysis to identify whole-brain states of spatial co-activation that recurred across participants and time. Measures included: dwell time (proportion of scan spent in that network state), persistence (volume-to-volume maintenance of a network state), and transitions (frequency of moving from state A to state B). Analyses tested associations between depression or trait rumination and dynamics of network states involving frontoinsular and default network systems. Results indicated that adolescents showing increased dwell time in, and persistence of, a frontoinsular-default network state involving insula, dorsolateral and medial prefrontal cortex, and posterior regions of default network, reported more severe symptoms of depression. Further, adolescents who transitioned more frequently between the frontoinsular-default state and a prototypical default network state reported higher depression. Increased dominance and transition frequency of frontoinsular-default network states were also associated with higher rumination, and rumination mediated the associations between network dynamics and depression. Findings support a model in which abnormal frontoinsular dynamics confer vulnerability to maladaptive introspection, which in turn contributes to symptoms of adolescent depression.

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