Brain Mechanism Of Bipolar Depression Based On Functional Magnetic Resonance Imaging

Bipolar disorder is a chronic and severe mental disease with the abnormalities in mood and activity level change between depression and mania or hypomania.Bipolar disorder affects about 1% of the world's population,causes long-term functional impairments to patients and also brings huge burdens on their families and the society.About two-thirds of patients are in depression for the first time,and the first manic episode does not appear within 5 to 9 years on average.Patients with bipolar disorder in major depressive episode(i.e.bipolar depression)are easily to be misdiagnosed as unipolar depression and treated by antidepressants,although mood stabilizers and antipsychotics may be the more effective pharmacological therapy at this time.Therefore,the early and accurate diagnosis of bipolar depression is of great significance.Mental health professors rely on phenomenological based diagnostic systems rather than validated biomarkers for the diagnosis and treatment of bipolar depression.So far,there are no accepted biomarkers for mental diseases,including bipolar depression.Brain image data obtained by magnetic resonance imaging(MRI)are considered to be an endophenotype.Compared with behavioral phenotype,this endophenotype may have simpler genetic structure and is helpful to the study of the pathological mechanism of bipolar depression.Recent functional MRI(f MRI)studies have emphasized the integration of large-scale networks in the brain of health and disease.Large scale networks are integrated by sensory,associative and motor cortex,which are the basis of human complex cognition and behavior.With the help of f MRI technology,this dissertation explores the dysfunction of large-scale brain networks in patients with bipolar depression by using functional connectivity(FC)in frequency,spatial and time domain.In addition,this dissertation also find the difference of large-scale brain network dysfunction between patients with bipolar and unipolar depression.The research content includes the following four parts:1.Using the frequency-specific graph theory method of long-range and short-range functional connectivity density(lrfcd and srfcd,respectively),this part explored the abnormal FC patterns in patients with bipolar depression.The results showed increased srfcd in midline cerebellum and increased lrfcd in left supplementary motor area and right striatum,while the decreased lrfcd in bilateral inferior temporal gyrus and left angular gyrus.In addition,the interaction between disease and frequency were found.Specifically,the increased srfcd in left pre/post-central gyrus and left fusiform gyrus and the lrfcd of left lingual gyrus were observed in the slow-4(0.027-0.073 Hz).While the decreased lrfcd in the left lingual gyrus was observed in the slow-5(0.01-0.027 Hz).After that,the decreased lrfcd in the left angular gyrus was related to the severity of depression and the increased srfcd in the left fusiform gyrus in the slow-4 band was correlated with the duration of the disease.In a word,the abnormalities of striatum,cerebellum and posterior default mode network area and slow-4 specific sensory system regions provided a new biological marker for the pathological mechanism of bipolar depression.2.Using the fine-scale spatial domain information,this part explored the abnormal FC patterns of different subsystems of the default mode network(DMN)in patients with bipolar depression.Specific results were as follows: decreased FCs between the precuneus and seed regions of posterior cingulate cortex(PCC),lateral temporal cortex(LTC),temporal pole(TP),posterior inferior parietal lobe(p IPL),retrosplenial cortex(Rsp)and parahippocampal gyrus(PHG).In addition,the increased FCs were found between PCC seed and lateral orbitofrontal cortex,LTC seed and inferior frontal gyrus,TP seed and sensorimotor network areas,p IPL seed and lingual gyrus and cuneus,Rsp seed and insula and PHG seed and middle occipital gyrus.Moreover,the decreased FC between PCC seed and precuneus was correlated with the degree of pessimism.These results suggested that the decreased FCs within the core area of posterior DMN and MTL subsystem which may indicate that there are functional abnormalities in the simulation and construction of future scenarios in bipolar depression.Moreover,the emotional regulation cortex such as lateral orbitofrontal cortex,inferior frontal gyrus and insula may be related to the abnormal emotional function in bipolar depression.The abnormality of sensoryimotor area may be related to psychomotor symptoms in bipolar depression.These findings may provide new opinions for the pathological mechanism of bipolar depression and future precise treatment for bipolar depression.3.Previous studies reported that there are consistent damage to the white matter of corpus callosum in bipolar depression,suggesting that the FCs between hemispheres may play an important role in the pathological mechanism of bipolar depression.To solve this problem,time-resolved FC method is used to explore the abnormal stability of interhemispheric FCs in patients with bipolar depression.The results demonstrated that the interhemispheric FCs in precuneus and angular gyrus were hyperstable while the interhemispheric FCs of inferior frontal gyrus,superior temporal gyrus,postcentral gyrus,supplementary motor area and cerebellum were unstable.In conclusion,the aberrant interhemispheric dynamic FC supported the results of two parts above.That is to say,posterior DMN areas such as precuneus and angular gyrus,cognitive and emotional control areas such as inferior frontal gyrus and psychomotor areas such as postcentral gyrus and supplementary motor area may play an important role in the pathophysiological mechanism of bipolar depression.4.The fine-scale spatiotemporal analysis methods were combined to solve the clinical problem that patients with bipolar depression are easily to be misdiagnosed as unipolar depression.Specifically,the dynamic FCs of the DMN subsystem regions were used to find the differences in the pathological mechanisms of bipolar and unipolar depression.The results were as follows: compared with unipolar depression and healthy control,the patients in bipolar depression exhibited the increased dynamic FCs between ventromedial prefrontal cortex seed and dorsolateral prefrontal cortex and precuneus.In addition,the dynamic FCs between PCC seed and the internal and external-directed functional network in patients with bipolar depression was also abnormal.Unipolar depression was mainly due to the abnormality of the dynamic networks including dorsomedial prefrontal cortex,insula,LTC and subgenual anterior cingulate cortex.Moreover,these specific differences could classify and predict the emotional and cognitive symptoms of these two diseases.Future confirmation of these results in large sample studies may provide imaging markers for early diagnosis and accurate treatment of bipolar depression.