Separate Neural Networks for Gains and Losses in Intertemporal Choice / 神经科学通报·英文版

An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic causal modeling analyses, we investigated the functional interactions between regions involved in the decision-making process while participants performed temporal discounting tasks in both the gains and losses domains. We found two distinct intrinsic valuation systems underlying temporal discounting in the gains and losses domains: gains were specifically evaluated in the medial regions, including the medial prefrontal and orbitofrontal cortices, and losses were evaluated in the lateral dorsolateral prefrontal cortex. In addition, immediate reward or punishment was found to modulate the functional interactions between the dorsolateral prefrontal cortex and distinct regions in both the gains and losses domains: in the gains domain, the mesolimbic regions; in the losses domain, the medial prefrontal cortex, anterior cingulate cortex, and insula. These findings suggest that intertemporal choice of gains and losses might involve distinct valuation systems, and more importantly, separate neural interactions may implement the intertemporal choices of gains and losses. These findings may provide a new biological perspective for understanding the neural mechanisms underlying intertemporal choice of gains and losses.

The primary explore of the damage of the executive control network in major depressive disorder:a dynamic causal model on magnetoencephalography / 中华行为医学与脑科学杂志

Objective To investigate the interconnection of the executive control network in major depressive disorder when they recognized the sad facial stimuli,and to discuss the aberrant mechanism of emotion processing.Methods Twenty major depressive patients and 20 well-matched healthy volunteers participated in the experiment.The brain actions of all subjects were recorded by the magnetoencephalography (MEG) when they were required to distinguish the emotion face.Based on prior knowledge,the interested brain area consisted of the primary visual cortex (V1),the orbitofrontal cortex(OFC),the dorsolateral prefrontal cortex (DLPFC),the anterior cingulated cortex (ACC).Then constructing three competing models to select an optimal model by the method of dynamic causal model(DCM),finally the differences of the effective connections of the optimal model between the depressed patients and healthy controls were analyzed.Results According to the results of Bayesian model selection (BMS),model 1 had the most exceedance probability of 0.80 with the features that there were bidirectional modulatory connections between the OFC,ACC and DLPFC.Given the best model,the parameters of effective connectivity of the optimal model were extracted,and then two-sample t-test over the model 1 was adopted.The modulatory effective connectivity from the OFC to the DLPFC in both hemisphere(t=-2.73,P=0.0096;t=-3.01,P=0.0046) and the OFC to the ACC (t=-2.93,P=0.0057) in the left hemisphere were significantly reduced in MDD.Conclusion There exists abnormal function of executive control network in depressed patients,the decreased effective connections between the OFC and the DLPFC,as well as the OFC and the ACC,may have correlation with the negative

The most optimal effective connections of prefrontal-amygdala during major depressive patients recognizing happy face / 中华行为医学与脑科学杂志

Objective To investigate whether there is exists optimal effective connections of prefrontal-amygdala in patients with major depressive disorder when they recognize dynamic positive face expressions with the technology of magnetoencephalograph (MEG),and discuss the possible aberrant mechanism of emotion processing.Methods Twenty major depressive patients and 20 well-matched healthy volunteer controls participated in the experiment.The regions of interested brain area included the primary visual cortex (V1),the precuneus (PQ),the dorsolateral prefrontal cortex (DLPFC),the anterior cingulate cortex (ACC),the amygdala (AMYG).After constructing three putative models,dynamic causal model was used to select an optimal model,then extracted all the effective connection parameters and conducted t-test under the overall optimal model between-group comparison.Results The bayesian model selection (BMS) indicated that model with top-down modulate connections between DLPFC-ACC,DLPFC-AMYG and ACC-AMYG was the most superior model,whose exceedance probability was 0.41.In the fight hemisphere of patient group,the endogenous connectivity from AMYG to ACC significantly decreased compared to healthy controls (t=-2.21,P=0.033),while the endogenous connectivity from ACC to DLPFC was enhanced significandy (t=2.50,P=0.017),which was the same with the endogenous connectivity from AMYG to DLPFC (t=2.10,P=0.040).Conclusion The effective connections of prefrontal-amygdala in major depressive disorder are exactly impaired,which may indicate that major depressive disorder have a bias toward negative.While depressed patients don' t show abnormality in the modulate connectivity under happy stimulus.