PT - JOURNAL ARTICLE AU - Natalie E. Adams AU - Laura E. Hughes AU - Holly N. Phillips AU - Alexander D. Shaw AU - Alexander G. Murley AU - David Nesbitt AU - Thomas E. Cope AU - W. Richard Bevan-Jones AU - Luca Passamonti AU - James B. Rowe TI - GABA-ergic dynamics in human frontotemporal networks confirmed by pharmaco-magnetoencephalography AID - 10.1523/JNEUROSCI.1689-19.2019 DP - 2020 Jan 08 TA - The Journal of Neuroscience PG - 1689-19 4099 - http://www.jneurosci.org/content/early/2020/01/08/JNEUROSCI.1689-19.2019.short 4100 - http://www.jneurosci.org/content/early/2020/01/08/JNEUROSCI.1689-19.2019.full AB - 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 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 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 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 identified the effect of a test drug (GABA-reuptake inhibitor, 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.