Timo Hofsähs, Marius Pille, Lucas Kern, Anuja Negi, Jil Mona Meier, Petra Ritter
4 min
Major depressive disorder (MDD) is often associated with increased amplitudes in transcranial magnetic stimulation evoked potentials (TEPs), a phenomenon thought to reflect an underlying imbalance in cortical excitation and inhibition. However, the exact mechanistic link between GABAergic neurotransmitter deficits and these larger TEP amplitudes remains unclear. This study uses whole-brain computational modeling to investigate whether simulating GABAergic deficits can reproduce the pathological TEP patterns observed in MDD.
The researchers utilized 'The Virtual Brain' (TVB) platform to create individualized whole-brain models of 20 healthy subjects. They employed the Jansen and Rit neural mass model to simulate regional brain activity and optimized structural connectivity to match empirical TEP data. To mimic MDD-like impaired inhibition, the authors systematically manipulated two key inhibitory parameters: the inhibitory synaptic decay rate (b) and the number of inhibitory synapses (C4). They then quantified the global mean field amplitude (GMFA) of the simulated TEPs to assess the impact of these parameter changes.
The simulations revealed that both the inhibitory synaptic decay rate and the number of inhibitory synapses have a strong, predictable relationship with TEP amplitude. Specifically, reducing these inhibitory parameters led to a significant increase in the global mean field amplitude, successfully mimicking the TEP patterns reported in clinical MDD studies. The researchers found that these local inhibitory changes resulted in global network-level alterations, suggesting that the increased cortical excitability seen in MDD may be a direct consequence of specific disruptions in inhibitory signaling dynamics.
This work provides a mechanistic explanation for the observed TEP abnormalities in MDD, bridging the gap between molecular GABAergic deficits and macroscopic electrophysiological markers. By demonstrating that these TEP changes can be generated in silico through targeted parameter manipulation, the study highlights the potential of whole-brain modeling as a tool for personalized psychiatry. These findings suggest that specific GABAergic pathways could serve as therapeutic targets and that computational models may eventually help optimize stimulation parameters for individual patients undergoing rTMS treatment.
Abstract Transcranial magnetic stimulation evoked potentials (TEPs) show promise as a biomarker in major depressive disorder (MDD), but the origin of the increased TEP amplitude in these patients remains unclear. Gamma aminobutyric acid (GABA) may be involved, as TEP peak amplitude is known to increase with GABAergic activity in healthy controls. We employed a computational modeling approach to investigate this phenomenon. Whole-brain simulations in ‘The Virtual Brain’ (thevirtualbrain.org), employing the Jansen and Rit neural mass model, were optimized to simulate TEPs of healthy individuals (Nsubs = 20, 14 females, 24.5 ± 4.9 years). To mimic MDD-like impaired inhibition, a GABAergic deficit was introduced to the simulations by altering one of two selected inhibitory parameters, the inhibitory synaptic decay rate b or the number of inhibitory synapses C4. The TEP amplitude was quantified and compared for all simulations. The inhibitory synaptic decay rate showed a quadratic correlation (r = 0.99, p < 0.001) and the number of inhibitory synapses a negative exponential correlation (r = 0.99, p < 0.001) with the TEP amplitude. Moreover, significant correlations between these simulation-derived values and all TEP peaks and troughs were detected (p < 0.001). Thus, under local parameter changes, we were able to alter the TEP amplitude toward pathological levels, that is, creating an MDD-like increase of the global mean field amplitude in line with empirical results. Our model suggests specific GABAergic deficits as the cause of increased TEP amplitude in MDD patients, which may serve as therapeutic targets. This work highlights the potential of whole-brain simulations in the investigation of neuropsychiatric diseases.
Sam: So the finding is closer to "GABAergic deficits are sufficient to produce this effect in the model," not "they're the only thing that could."
Alex: Right, and that's the honest scope of the claim. The other limitation is that these are inferential parameters, not measured ones. A clinician can record an elevated evoked potential in a patient. They cannot currently observe synaptic decay rates or synapse density directly in a living brain to check whether the model's inference actually holds for that individual.
Sam: There's also the question of uniformity. The perturbations here are applied roughly homogeneously across the cortex, correct? Real inhibitory pathology in depression is unlikely to be that evenly distributed.
Alex: That's a fair pushback, and the authors treat this as a simplification rather than a claim about biological reality. It's a proof of mechanism, not a map of where in the cortex the deficit actually sits.
Sam: So what does this buy the field, if it's not a diagnostic and not a direct measurement?
Alex: It converts a black-box biomarker into a testable physiological hypothesis. Before this, "elevated TEP amplitude" was just a pattern clinicians observed without a clear mechanistic story attached. Now there's a specific, falsifiable account — reduced inhibitory decay efficiency or synapse loss — that could in principle be probed with pharmacological challenges or paired with other imaging measures of inhibitory tone. [[RP_SECTION:future-research-directions|Future research directions]]
Sam: And the natural next step would be personalizing the connectome rather than starting from a healthy average.
Alex: That's exactly the direction the authors point toward — integrating individual patient connectomes and heterogeneous neurotransmitter distributions, so the simulation reflects a specific person's cortex rather than a generic healthy one. That's what would let this move from an in silico mechanism toward something with predictive value for treatment response, including for rTMS itself.
Sam: It's a modest but genuine step, then — less a diagnosis, more a hypothesis with a testable shape.
Alex: That's the right way to hold it. It doesn't prove GABAergic deficits are the sole cause of the amplitude increase in real patients, but it does show the mechanism is physiologically plausible and gives researchers a concrete parameter to go chase down in vivo. Thanks for listening to ResearchPod.