Deep brain stimulation of the nucleus basalis of Meynert modulates hippocampal-frontoparietal networks in patients with advanced Alzheimer’s disease

Background:Deep brain stimulation(DBS)of the nucleus basalis of Meynert(NBM)has shown potential for the treatment of mild-to-moderate Alzheimer’s disease(AD).However,there is little evidence of whether NBM-DBS can improve cognitive functioning in patients with advanced AD.In addition,the mechanisms underlying the modulation of brain networks remain unclear.This study was aimed to assess the cognitive function and the resting-state connectivity following NBM-DBS in patients with advanced AD.Methods:Eight patients with advanced AD underwent bilateral NBM-DBS and were followed up for 12 months.Clinical outcomes were assessed by neuropsychological examinations using the Mini-Mental State Examination(MMSE)and Alzheimer’s Disease Assessment Scale.Resting-state functional magnetic resonance imaging and positron emis-sion tomography data were also collected.Results:The cognitive functioning of AD patients did not change from baseline to the 12-month follow-up.Interestingly,the MMSE score indicated clinical efficacy at 1 month of follow-up.At this time point,the connectivity between the hippocampal network and frontoparietal network tended to increase in the DBS-on state compared to the DBS-off state.Additionally,the increased functional connectivity between the parahippocampal gyrus(PHG)and the parietal cortex was associated with cognitive improvement.Further dynamic functional network analysis showed that NBM-DBS increased the proportion of the PHG-related connections,which was related to improved cognitive performance.Conclusion:The results indicated that NBM-DBS improves short-term cognitive performance in patients with advanced AD,which may be related to the modulation of multi-network connectivity patterns,and the hippocampus plays an important role within these networks.

Dynamic trial-by-trial re-coding of task-set representations in frontoparietal cortex mediates behavioral flexibility

How our flexible behavior was supported by the dynamic(re)coding in fronto parietal was explored by the research group led by Prof.Chen Antao(陈安涛)from the Faculty of Psychology,Southwest University with the collaboration of Prof.Tobias Egner from Duke University.The study was supported by the National Natural Science Foundation of China,and was recently published in Journal of Neuroscience(2017,0935-17).

Abnormal characterization of dynamic functional connectivity in Alzheimer’s disease

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer’s disease(AD)or amnestic mild cognitive impairment(aMCI).However,most studies examined traditional resting state functional connections,ignoring the instantaneous connection mode of the whole brain.In this case-control study,we used a new method called dynamic functional connectivity(DFC)to look for abnormalities in patients with AD and aMCI.We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant,and then used a support vector machine to classify AD patients and normal controls.Finally,we highlighted brain regions and brain networks that made the largest contributions to the classification.We found differences in dynamic function connectivity strength in the left precuneus,default mode network,and dorsal attention network among normal controls,aMCI patients,and AD patients.These abnormalities are potential imaging markers for the early diagnosis of AD.

Personality–brain connection:Based on resting-state functional magnetic resonance imaging data-driven exploration

Background:The personality-brain association mechanism has been a topic of interest in the field of neuroscience.Usually,the previous research strategy was to first group the population based on different personality traits,and then explore the brain mechanisms corresponding to different personality groups.At present,a“brain-first”research strategy,which uses data-driven approaches instead of personality traits to first group the population,has been adopted to further enhance study objectivity.Methods:Here,we used a data-driven approach following the“brain-first”research strategy to deeply mine the resting-state brain functional magnetic resonance imaging data of 119 healthy participants,classified subjects into different groups based on brain image characteristics,and used the Sixteen Personality Factor Questionnaire to explain the variabilities of resting-state brain characteristics between different groups.Results:We have identified 3 personality–brain connections,including the privateness–left frontoparietal network,liveliness–sensory–motor network,and vigilance–sensory–motor network.Conclusion:We conclude that the above-mentioned three personality factors are based on brain neural activity,independent of the subjective experience of the personality scale creator,and have stronger explanatory power of brain imaging features.

Altered cerebral activities and functional connectivity in depression:a systematic review of fMRI studies

Background:As one of the leading causes of global disability,major depressive disorder(MDD)places a noticeable burden on individuals and society.Despite the great expectation on finding accurate biomarkers and effective treatment targets of MDD,studies in applying functional magnetic resonance imaging(fMRI)are still faced with challenges,including the representational ambiguity,small sample size,low statistical power,relatively high false positive rates,etc.Thus,reviewing studies with solid methodology may help achieve a consensus on the pathology of MDD.Methods:In this systematic review,we screened fMRI studies on MDD through strict criteria to focus on reliable studies with sufficient sample size,adequate control of head motion,and a proper multiple comparison control strategy.Results:We found consistent evidence regarding the dysfunction within and among the default mode network(DMN),the frontoparietal network(FPN),and other brain regions.However,controversy remains,probably due to the heterogeneity of participants and data processing strategies.Conclusion:Future studies are recommended to apply a comprehensive set of neuro-behavioral measurements,consider the heterogeneity of MDD patients and other potentially confounding factors,apply surface-based neuroscientific network fMRI approaches,and advance research transparency and open science by applying state-ofthe-art pipelines along with open data sharing.