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Updated: May 10, 2026
Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design
Published on: December 3, 2020
The relationship between positive and negative automatic thought and activity in the prefrontal and temporal
Shunsuke Koseki1, Takamasa Noda, Satoshi Yokoyama
1Department of School Education, Aichi University of Education, Hirosawa, Kariya, Aichi 448-8542, Japan. skoseki@auecc.aichi-edu.ac.jp
Background:
Recently, neurobiological studies of the cognitive model of depression have become vastly more important, and a growing number of such studies are being reported. However, the relationship between the proportion of positive and negative automatic thought and activity in the prefrontal and temporal cortices has not yet been explored. We examined the relationship between brain activity and the proportion of positive and negative automatic thought in patients with major depressive disorder (MDD), using multi-channel near-infrared spectroscopy (NIRS).
Methods:
We recruited 75 individuals with MDD (36 females; mean age=39.23 ± 12.49). They completed the Hamilton Rating Scale for Depression, Automatic Thoughts Questionnaire-Revised, Japanese version of the National Adult Reading Test, and the State-Trait Anxiety Inventory. Brain activation was measured by 52-channel NIRS.
Results:
We found that activation in the vicinity of the right superior temporal gyrus is related to a deviation to negative of the proportion of positive and negative thoughts in individuals with MDD. Left dorsolateral prefrontal cortex activity was higher in the group with comparatively frequent positive thought.
Limitations:
Our participants were patients taking antidepressant medication, which is known to influence brain activity. Second, the poor spatial resolution of NIRS increases the difficulty of identifying the measurement position.
Conclusions:
We found that activation of the prefrontal and temporal cortices is related to the proportion of automatic thoughts in the cognitive model of depression.
