Mood disorders: neurocognitive models

Malhi, Gin S; Byrow, Yulisha; Fritz, Kristina; Das, Pritha; Baune, Bernhard T.; Porter, Richard; Outhred, Tim

doi:10.1111/bdi.12353

Cited by 51 publications

(48 citation statements)

References 97 publications

(156 reference statements)

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“…29 Maladaptive cognition is the primary target in cognitive behavioral therapy for mood disorders. In depression, the cognitive model proposed by Beck is grounded in the theory that depressed individuals have maladaptive schemas that is beliefs about oneself involving hopelessness, rejection, failure, and worthlessness.…”

Section: Depression and Cognitive Functionmentioning

confidence: 99%

“…29 These are not neurobiological cognitive impairments per se, but instead dysfunctional thought patterns sustained by mood, congruent with prevailing emotions. An alternative concept is that of emotion regulation, which recognizes cognition as an important con- Implicit regulation is characterized by the absence of an explicit instruction and conscious monitoring and can happen without insight and awareness.…”

Section: Depression and Cognitive Functionmentioning

confidence: 99%

“…29 These models rely on a number of cognitive processes involved in mood disorders, such as reappraisal and suppression, attention, and rumination.…”

Section: Depression and Cognitive Functionmentioning

confidence: 99%

“…29 On the other hand, the attempt to control the emotional response by inhibiting the expression of emotion rather than to change its value is defined as suppression. 29 In the field of mood disorders, attention can be conceptualized as two separate but related components: attentional deployment and attentional control. Attentional deployment refers to the allocation of attention with the aim of influencing an emotional state or response.…”

Section: Depression and Cognitive Functionmentioning

confidence: 99%

“…Patients with mood disorders selectively attend to negatively valenced stimuli. 29 The top-down regulation of attention (attentional control) is central for attention shifting from emotional to non-emotional stimuli. 29 Attention deficits are likely to contribute to the extended processing of negative information in depressed patients.…”

Section: Depression and Cognitive Functionmentioning

confidence: 99%

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Differential diagnosis, discerning depression from cognition

Portaccio

2016

Acta Neurol Scand

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Cognitive impairment is common in multiple sclerosis (MS), affecting up to 70% of patients. One of the most important possible confounders to cognitive assessment is the occurrence of depression, a common consequence of MS. Cognition and depression have been linked in recent neuropsychiatric research that proposed a number of neurocognitive models of mood disorders. According to these models, primary failure of key brain regions of emotional processing and regulation or abnormal connectivity between them contributes to the adoption of maladaptive cognitive strategies and the development of mood disorders. In MS, a similar interplay between cognitive function and depression has been reported. In particular, depression seems to alter attentional capacity in terms of deficits in working memory and, more specifically, deficits in the executive control. However, cognitive impairment in MS does exist also in the absence of depression and it is more likely that depression exacerbates existing cognitive difficulties rather than cause them per se. On the other hand, it is possible that a dysexecutive syndrome secondary to MS might in turn precipitate depression.

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Section: Depression and Cognitive Functionmentioning

confidence: 99%

Section: Depression and Cognitive Functionmentioning

confidence: 99%

“…29 These models rely on a number of cognitive processes involved in mood disorders, such as reappraisal and suppression, attention, and rumination.…”

Section: Depression and Cognitive Functionmentioning

confidence: 99%

Section: Depression and Cognitive Functionmentioning

confidence: 99%

Section: Depression and Cognitive Functionmentioning

confidence: 99%

See 3 more Smart Citations