Chronotype and diurnal patterns of positive affect and affective neural circuitry in primary insomnia
While insomnia is a well‐established risk factor for the initial onset, recurrence or relapse of affective disorders, the specific characteristics of insomnia that confer risk remain unclear. Patients with insomnia with an evening chronotype may be one particularly high‐risk group, perhaps due to alterations in positive affect and its related affective circuitry. We explored this possibility by comparing diurnal patterns of positive affect and the activity of positive affect‐related brain regions in morning‐ and evening‐types with insomnia. We assessed diurnal variation in brain activity via the relative regional cerebral metabolic rate of glucose uptake by using [18F]fluorodeoxyglucose‐positron emission tomography during morning and evening wakefulness. We focused on regions in the medial prefrontal cortex and striatum, which have been consistently linked with positive affect and reward processing. As predicted, chronotypes differed in their daily patterns in both self‐reported positive affect and associated brain regions. Evening‐types displayed diurnal patterns of positive affect characterized by phase delay and smaller amplitude compared with those of morning‐types with insomnia. In parallel, evening‐types showed a reduced degree of diurnal variation in the metabolism of both the medial prefrontal cortex and the striatum, as well as lower overall metabolism in these regions across both morning and evening wakefulness. Taken together, these preliminary findings suggest that alterations in the diurnal activity of positive affect‐related neural structures may underlie differences in the phase and amplitude of self‐reported positive affect between morning and evening chronotypes, and may constitute one mechanism for increased risk of mood disorders among evening‐type insomniacs.
Document Type: Research Article
Affiliations: 1: Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA 2: Department of Statistics, University of Pittsburgh, Pittsburgh, PA,USA 3: Department of Radiology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA 4: Department of Biostatistics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
Publication date: 2012-10-01