Relationship Between Automatic Thinking And Depressive Symptoms In College Students From The Perspective Of Behavioral Network And Brain Function

Depression is a complex and widespread psychological disease.According to the fifth edition of the Diagnostic and Statistical Manual of mental disorders(DSM-5)issued by the American Psychiatric Association,patients can be diagnosed with depression if they meet five of the nine diagnostic criteria(including at least one of the symptoms of depression or lack of interest).Based on such diagnostic criteria,patients with depression can have different clinical symptom combinations.Two patients with depression may be diagnosed with the same severity but show advantages in different symptoms.Therefore,it has particular clinical value to analyze depression based on the specific symptoms of patients.Automatic thoughts are regarded as the derivatives of beliefs influenced by core beliefs and intermediate beliefs.Patients with depression tend to jump out of their minds uncontrollably and have negative evaluations of themselves.Previous studies have found a relationship between depression and automatic negative thinking.For example,through cognitive behavioral therapy for patients with depression,it is found that automatic thinking can interfere with patients’ attribution of positive events and can significantly predict the severity of depression.However,previous studies focused more on the overall correlation between automatic negative thinking and the degree of depression.Few studies further explore the interaction between the components of automatic negative thinking and different symptoms of depression.Individuals with the same degree of depression may have different symptoms,such as physical symptoms,emotional symptoms and cognitive symptoms,and automatic thinking also has multiple components,such as personal maladjustment and desire for change,negative self-concept and negative expectation,low self-esteem,and helplessness.Furthermore,based on previous studies,the specific relationship between automatic negative thinking and depressive symptoms is unknown.Which symptoms(components)play a relatively important role in their relationship is also unknown.Research meaning: 1.Previous studies often used automatic negative thinking and the total score of depression to explore the relationship between them.This study discusses the relationship between automatic negative thinking and depressive symptoms from the perspective of behavioral network combination.It can explore the relationship between the internal components of the two from a more detailed perspective.Combined with longitudinal behavior tracking and brain image data,the relationship between different symptoms and the representation of brain function was discussed to verify the results’ stability.2.Beck believes that each component of clinical syndrome results from systematic and negative distortion in cognitive content and processing.Based on this theory,the famous cognitive-behavioral therapy(CBT)is proposed,and it has been proved to be an effective method for the treatment of depression.As a CBT,CBGT(cognitive-behavioral group therapy)can change those dysfunctional cognitive structures through cognitive reconstruction.Moreover,the key to finding automatic rational thinking is to reconstruct it automatically.Therefore,if we can find the core component between automatic negative thinking and depression symptoms through research,it will help deepen the understanding and application of clinical psychotherapy.Main research contents: This paper explores the relationship between the behavioral network and brain function of different symptoms of depression and automatic negative thinking at the factor level based on the sample database of college students.The fundamental problem is determining the critical nodes in the interaction between depressive symptoms and automatic negative thinking.Expected goal: find the relationship between automatic negative thinking and network topology,and get evidence support from longitudinal data and brain representation.Sample: a total of1252 college students(882 women,mean age 19.5 years)were selected.All participants were measured with Automatic Thoughts Questionnaire(ATQ)and Beck Depression Inventory(BDI).Part of the participants had two event points of questionnaire measurement(439 people)or functional MRI data(675 people).We know that ATQ and BDI have a total of 7 components through the search of previous literature.The main symptoms of BDI were cognition,affective and somatic.The composition of ATQ:personal maladjustment and desire for change(PMDC),negative self-concept and negative expectations(NSNE),low self-esteem(LSE),helplessness.Main methods and results of study 1: the seven symptoms(components)of ATQ and BDI were used to establish a network model for network analysis.Results negative self-concept,negative expectation,and cognitive symptoms play a cross symptom communication role in the network of negative automatic thinking and depressive symptoms.And the centrality of the node has high stability.To test whether the network structure of the subjects will change with time,the subjects across time(two-time points)are used to do the same network analysis.The analysis results show that the network model is stable in time scale,and there are only differences in global strength.Main methods and results of study 2: the lag cross panel model was used to analyze subjects with two-time point data.The variables were still seven symptoms(components)of ATQ and BDI.The measured variables are all negative variables,so the data at the two-time points are only moderately correlated.However,in the cross-lagged panel model,we further prove the cross-time(two-time points)cross-relationship between negative self-concept,negative expectation,and cognitive symptoms,that is,their scores can affect each other’s scores measured at the next time point.Study 3 main methods and conclusion: for the subjects with image data,the inferior cingulate gyrus was selected as the seed point to establish the whole-brain functional connectivity.At the same time,voxels are correlated with the symptom scores of all subjects,that is,the correlation between voxels and the symptom can be obtained.This step is carried out in the whole brain,that is,to establish the brain symptom function map of each symptom(a total of 7).The results also show that negative self-concept,negative expectation,and cognitive symptoms have more close representation of symptomatic brain function in cross symptom(between negative automatic thinking and depression).That is to say,negative self-concept,negative expectation,and cognitive symptoms are more closely related to each other in functional image data.In conclusion,negative self-concept,negative expectation,and cognitive symptoms play a central role in the interaction between depression and negative automatic thinking.The findings will help traditional psychological interventions such as cognitive-behavioral therapy to play a further role and deepen the understanding of the relationship between negative automatic thinking and depression symptoms.