The influence of inter-regional delays in generating large-scale brain networks of phase synchronization

被引:3
作者
Williams, N. [1 ,2 ,9 ]
Ojanpera, A. [3 ]
Siebenhuhner, F. [4 ,5 ]
Toselli, B.
Palva, S.
Arnulfo, G. [4 ,6 ]
Kaski, S. [8 ]
Palva, J. M. [4 ,7 ]
机构
[1] Aalto Univ, Helsinki Inst Informat Technol, Dept Comp Sci, Helsinki, Finland
[2] Aalto Univ, Dept Neurosci & Biomed Engn, Espoo, Finland
[3] Aalto Univ, Dept Comp Sci, Espoo, Finland
[4] Univ Helsinki, Helsinki Inst Life Sci, Neurosci Ctr, Helsinki, Finland
[5] HUS, BioMag Lab, Med Imaging Ctr, Helsinki, Finland
[6] Univ Genoa, Dept Informat Bioengn Robot & Syst Engn, Genoa, Italy
[7] Univ Glasgow, Ctr Cognit Neuroimaging, Sch Neurosci & Psychol, Glasgow, Scotland
[8] Univ Manchester, Dept Comp Sci, Manchester, England
[9] Aalto Univ, Helsinki Inst Informat Technol HIIT, Dept Comp Sci, Konemiehentie 2, Espoo 02150, Finland
基金
芬兰科学院;
关键词
Biophysical Network Models (BNMs); Magnetoencephalography (MEG) resting -state; Axonal conduction delays; Phase synchronization; Approximate Bayesian Computation (ABC); Bayesian optimization for Likelihood -Free; Inference (BOLFI); CONDUCTION VELOCITIES; NEURONAL SYNCHRONY; QUALITY ASSESSMENT; CORTICAL ACTIVITY; MEG; DYNAMICS; TRACTOGRAPHY; RHYTHMS; MODEL; COMMUNICATION;
D O I
10.1016/j.neuroimage.2023.120318
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Large-scale networks of phase synchronization are considered to regulate the communication between brain regions fundamental to cognitive function, but the mapping to their structural substrates, i.e., the structure -function relationship, remains poorly understood. Biophysical Network Models (BNMs) have demonstrated the influences of local oscillatory activity and inter-regional anatomical connections in generating alpha-band (8-12 Hz) networks of phase synchronization observed with Electroencephalography (EEG) and Magnetoencephalog-raphy (MEG). Yet, the influence of inter-regional conduction delays remains unknown. In this study, we compared a BNM with standard "distance-dependent delays", which assumes constant conduction velocity, to BNMs with delays specified by two alternative methods accounting for spatially varying conduction velocities, "isochronous delays" and "mixed delays". We followed the Approximate Bayesian Computation (ABC) workflow, i) specifying neurophysiologically informed prior distributions of BNM parameters, ii) verifying the suitability of the prior distributions with Prior Predictive Checks, iii) fitting each of the three BNMs to alpha-band MEG resting-state data (N = 75) with Bayesian optimization for Likelihood-Free Inference (BOLFI), and iv) choosing between the fitted BNMs with ABC model comparison on a separate MEG dataset (N = 30). Prior Predictive Checks revealed the range of dynamics generated by each of the BNMs to encompass those seen in the MEG data, suggesting the suitability of the prior distributions. Fitting the models to MEG data yielded reliable posterior distributions of the parameters of each of the BNMs. Finally, model comparison revealed the BNM with "distance -dependent delays", as the most probable to describe the generation of alpha-band networks of phase synchro-nization seen in MEG. These findings suggest that distance-dependent delays might contribute to the neocortical architecture of human alpha-band networks of phase synchronization. Hence, our study illuminates the role of inter-regional delays in generating the large-scale networks of phase synchronization that might subserve the communication between regions vital to cognition.
引用
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页数:22
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