98%
921
2 minutes
20
The frequent occurrence of uncontrollable negative thoughts and memories is a troubling aspect of depression. Thus, knowledge on the mechanism underlying intentional forgetting of these thoughts and memories is crucial to develop an effective emotion regulation strategy for depressed individuals. Behavioral studies have demonstrated that depressed participants cannot intentionally forget negative memories. However, the neural mechanism underlying this process remains unclear. In this study, participants completed the directed forgetting task in which they were instructed to remember or forget neutral or negative words. Standard univariate analysis based on the General Linear Model showed that the depressed participants have higher activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), superior parietal gyrus (SPG), and inferior temporal gyrus (ITG) than the healthy individuals. The results indicated that depressed participants recruited more frontal and parietal inhibitory control resources to inhibit the TBF items, but the attempt still failed because of negative bias. We also used the Support Vector Machine to perform multivariate pattern classification based on the brain activation during directed forgetting. The pattern of brain activity in directed forgetting of negative words allowed correct group classification with an overall accuracy of 75% (P=0.012). The brain regions which are critical for this discrimination showed abnormal activation when depressed participants were attempting to forget negative words. These results indicated that the abnormal neural circuitry when depressed individuals tried to forget the negative words might provide neurobiological markers for depression.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jad.2015.05.034 | DOI Listing |
IEEE Trans Neural Netw Learn Syst
September 2025
In industrial scenarios, semantic segmentation of surface defects is vital for identifying, localizing, and delineating defects. However, new defect types constantly emerge with product iterations or process updates. Existing defect segmentation models lack incremental learning capabilities, and direct fine-tuning (FT) often leads to catastrophic forgetting.
View Article and Find Full Text PDFCurr Biol
August 2025
Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, 190 Thayer Street, Providence, RI 02912, USA.
Across various types of learning and memory, when a new training session follows a previous one after a certain temporal interval, the previously acquired learning can be disrupted-an effect known as retrograde interference (RI) or catastrophic forgetting. This disruption is thought to result from disrupting interactions between the learning of the first-trained task and the learning of the second-trained task while the former has not yet stabilized. Such destructive interactions have been considered characteristic not only of RI but also of related phenomena.
View Article and Find Full Text PDFR Soc Open Sci
September 2025
Clinical Psychological Science, Faculty of Psychology and neuroscience, Maastricht University, Maastricht, The Netherlands.
Memory distrust, the subjective appraisal of one's memory functioning, comprises two aspects: distrust over omission errors (e.g. forgetting) and distrust over commission errors (e.
View Article and Find Full Text PDFPsychol Res
August 2025
School of Psychology, Northwest Normal University, Lanzhou, People's Republic of China.
Social exclusion has been found to impair inhibitory control and working memory, but its effect on directed forgetting has remained largely unexplored. Using the item-method directed forgetting paradigm, the present study employed both verbal and pictorial materials to investigate how social exclusion affects the directed forgetting of social and non-social information. In Experiment 1, 54 participants (M = 23.
View Article and Find Full Text PDFIEEE Trans Nanobioscience
August 2025
Operant conditioning is a learning mechanism by which animals adapt to its external environment and past experiences. In the field of artificial intelligence, DNA strand displacement (DSD) technology has performed well in various aspects. Chemical reaction networks (CRNs) are constructed using stochastic DSD technology to study operant conditioning, and the simulation results are verified by Visual DSD software.
View Article and Find Full Text PDF