DCM, Conductance Based Models and Clinical Applications

Marreiros, André C.; Pinotsis, Dimitris A.; Brown, Peter; Friston, Karl J.

doi:10.1007/978-3-319-20037-8_3

Cited by 7 publications

(7 citation statements)

References 139 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A related open question is how to produce different band-specific patterns of functional connectivity using a single anatomical connectivity matrix. One promising direction may be to introduce multiple timescales of dynamics into the local model–for example, by introducing additional populations with different intrinsic oscillatory frequencies [ 41 ], having the local effective time constants depend on network properties [ 14 ], or by using a conduction-based neural mass model [ 83 , 84 ] that incorporates multiple timescales through the inclusion of multiple receptor types, each with a different time constant.…”

Section: Discussionmentioning

confidence: 99%

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

et al. 2018

View full text Add to dashboard Cite

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP.

show abstract

Section: Discussionmentioning

confidence: 99%

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

et al. 2018

View full text Add to dashboard Cite

show abstract

“…The DCM framework developed to meet these criteria, with applications in health and neurological disorders (Kiebel et al, 2008;Stephan et al, 2008;Boly et al, 2011;Marreiros et al, 2015). DCMs draw on empirical priors for synaptic time constants and conductances, together with a mean-field forward model.…”

Section: Introductionmentioning

confidence: 99%

“…In six connected regions (locations from Phillips et al, 2015Phillips et al, , 2016, we used a conductance-based mean-field cortical modeling scheme (cf. Moran et al, 2013;Marreiros et al, 2015). For auditory mismatch responses, both thalamocortical and corticocortical connections integrate feedforward sensory inputs and feedback expectations.…”

Section: Introductionmentioning

confidence: 99%

GABA-ergic Dynamics in Human Frontotemporal Networks Confirmed by Pharmaco-Magnetoencephalography

et al. 2020

View full text Add to dashboard Cite

To bridge the gap between preclinical cellular models of disease and in vivo imaging of human cognitive network dynamics, there is a pressing need for informative biophysical models. Here we assess dynamic causal models (DCM) of cortical network responses, as generative models of magnetoencephalographic observations during an auditory oddball roving paradigm in healthy adults. This paradigm induces robust perturbations that permeate frontotemporal networks, including an evoked 'mismatch negativity' response and transiently induced oscillations. Here, we probe GABAergic influences in the networks using double-blind placebo-controlled randomized-crossover administration of the GABA reuptake inhibitor, tiagabine (oral, 10 mg) in healthy older adults. We demonstrate the facility of conductance-based neural mass mean-field models, incorporating local synaptic connectivity, to investigate laminarspecific and GABAergic mechanisms of the auditory response. The neuronal model accurately recapitulated the observed magnetoencephalographic data. Using parametric empirical Bayes for optimal model inversion across both drug sessions, we identify the effect of tiagabine on GABAergic modulation of deep pyramidal and interneuronal cell populations. We found a transition of the main GABAergic drug effects from auditory cortex in standard trials to prefrontal cortex in deviant trials. The successful integration of pharmacomagnetoencephalography with dynamic causal models of frontotemporal networks provides a potential platform on which to evaluate the effects of disease and pharmacological interventions.

show abstract

“…The DCM framework developed to meet these criteria, with applications in health and neurological 62 disorders Stephan et al, 2008;Boly et al, 2011;Marreiros et al, 2015). DCM 63 models draw on empirical priors for synaptic time constants and conductances, together with a 64 mean-field forward model for each major neuronal class.…”

Section: Introduction 52mentioning

confidence: 99%

“…To examine laminar-level dynamics in response to auditory stimuli we used an extended-DCM. In six 80 connected frontotemporal regions (based on Phillips et al, 2015Phillips et al, , 2016, we used a conductance-81 based canonical mean-field cortical modelling scheme (Moran et al, 2013;Marreiros et al, 2015). 82…”

Section: Introduction 52mentioning

confidence: 99%

GABA-ergic dynamics in human frontotemporal networks confirmed by pharmaco-magnetoencephalography

Adams

Hughes

Phillips

et al. 2019

Preprint

View full text Add to dashboard Cite

To bridge the gap between preclinical cellular models of disease and in vivo imaging of human cognitive network dynamics, there is a pressing need for informative biophysical models. Here we assess dynamic causal models (DCM) of cortical network responses, inverted to magnetoencephalographic observations during an auditory oddball roving paradigm in healthy adults. This paradigm induces robust perturbations that permeate frontotemporal networks, including an evoked ‘mismatch negativity’ response and transiently induced oscillations. Here, we probe GABAergic influences of the networks using double-blind placebo-controlled randomised-crossover administration of the GABA re-uptake inhibitor, tiagabine (oral, 10mg) in healthy older adults. We demonstrate the facility of conductance-based neural mass mean-field models, incorporating local synaptic connectivity, to investigate laminar-specific and GABAergic mechanisms of the auditory response. The neuronal model accurately recapitulated the observed magnetoencephalographic data. Using parametric empirical Bayes for optimal model inversion across both sessions, we identify the effect of tiagabine on GABAergic modulation of deep pyramidal and interneuronal cell populations. Moreover, in keeping with the hierarchical coding of beliefs and sensory evidence, we found a transition of the main GABAergic drug effects from auditory cortex in standard trials to prefrontal cortex in deviant trials. The successful integration of pharmaco-magnetoencephalography with dynamic causal models of frontotemporal networks provides a potential platform on which to evaluate the effects of disease and pharmacological interventions.Significance StatementUnderstanding human brain function and developing new treatments require good models of brain function. We tested a detailed generative model of cortical microcircuits that accurately reproduced human magnetoencephalography, to quantify network dynamics and connectivity in frontotemporal cortex. This approach correctly identified the effect of a test drug (tiagabine) on neuronal function (GABA-ergic dynamics), opening the way for psychopharmacological studies in health and disease with the mechanistic precision afforded by generative models of the brain.

show abstract

DCM, Conductance Based Models and Clinical Applications

Cited by 7 publications

References 139 publications

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

GABA-ergic Dynamics in Human Frontotemporal Networks Confirmed by Pharmaco-Magnetoencephalography

GABA-ergic dynamics in human frontotemporal networks confirmed by pharmaco-magnetoencephalography

Contact Info

Product

Resources

About