TMS-Evoked Responses Are Driven by Recurrent Large-Scale Network Dynamics

Griffiths, John; Momi, Davide; Wang, Zheng

doi:10.1101/2022.06.09.494069

Cited by 7 publications

(15 citation statements)

References 72 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, Momi, Wang and Griffiths (51) used whole-brain connectome-based computational modelling to reconstruct individual responses to TMS in vitro and highlighted the role of GABAergic neural populations and cortical excitability. Our results align with this previous research (23,24,(49)(50)(51) and support the hypothesis that the complexity of the response following perturbation can be inferred solely based on resting-state activity.…”

Section: Discussionsupporting

confidence: 92%

Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia

Maschke,

O’Byrne,

Colombo

et al. 2023

Preprint

View full text Add to dashboard Cite

1AbstractConsciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects’ PCI (i.e., PCImax) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness.2Significance StatementComplexity has long been of interest in consciousness science and had a fundamental impact on many of today’s theories of consciousness. The perturbational complexity index (PCI) uses the complexity of the brain’s response to cortical perturbations to quantify the presence of consciousness. We propose criticality as a unifying framework underlying maximal complexity and sensitivity to perturbation in the conscious brain. We demonstrate that criticality measures derived from resting-state electroencephalography can distinguish conscious from unconscious states, using propofol, xenon and ketamine anesthesia, and from these measures we were able to predict the PCI with a mean error below 7%. Our results support the hypothesis that critical brain dynamics are implicated in the emergence of consciousness and may provide new directions for the assessment of consciousness.

show abstract

Section: Discussionsupporting

confidence: 92%

Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia

Maschke,

O’Byrne,

Colombo

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Along the same lines, a more recent study in humans showed that TMS-EPs can propagate in the network for hundreds of milliseconds, and that such responses highly resemble the EPs generated by delivering ES to the same area 28 . These findings support the notion that TMS responses are not due to peripheral activations, but rather due to recurrent interactions across different regions 29 . Indeed, ES directly excites nearby neurons that cause secondary responses in connected neuronal populations 7,30 .…”

Section: Introductionsupporting

confidence: 87%

Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans

Russo,

Claar,

Marks

et al. 2024

Preprint

View full text Add to dashboard Cite

Cortical stimulation with single electrical or magnetic pulses is a popular technique in clinical practice and research. However, we still do not understand the extent to which non-cortical circuits contribute to the associated evoked potentials (EPs). Here we optogenetically dissect the underlying circuit in mice, demonstrating that the late component of this EP depends critically on thalamic hyperpolarization and rebound. The magnitude of this late component correlates with the bursting frequency and synchronicity of thalamic neurons, modulated by the subject’s behavioral state and by the cortico-thalamic synaptic connectivity profile. A simulation of the thalamo-cortical circuit highlights that both thalamic intrinsic currents as well as cortical GABAergic neurons contribute to this response profile. We find a remarkably similar EP in humans, with a late component similarly modulated by subject’s behavioral state. It is therefore likely that the mechanisms underlying these evoked potentials are preserved across different species and stimulation modalities.Graphical abstract

show abstract

“…This study used our recent approach 25 and combined novel analytical techniques and subject-specific mathematical models of brain stimulation. Using combined iES and simultaneous recordings of sEEG and scalp hd-EEG, we mapped the response properties of seven canonical RSNs across 323 stimulation sessions from 36 patients.…”

Section: Introductionmentioning

confidence: 99%

Stimulation mapping and whole-brain modeling reveal gradients of excitability and recurrence in cortical networks

Momi,

Wang,

Parmigiani

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

The human brain exhibits a modular and hierarchical structure, spanning low-order sensorimotor to high-order cognitive/affective systems. What is the causal significance of this organization for brain dynamics and information processing properties? We investigated this question using rare simultaneous multimodal electrophysiology (stereotactic and scalp EEG) recordings in patients during presurgical intracerebral electrical stimulation (iES). Our analyses revealed an anatomical gradient of excitability across the cortex, with stronger iES-evoked EEG responses in high-order compared to low-order regions. Mathematical modeling further showed that this variation in excitability levels results from a differential dependence of recurrent feedback from non-stimulated regions across the anatomical hierarchy, and could be extinguished by suppressing those connections in-silico. High-order brain regions/networks thus show a more functionally integrated processing style than low-order ones, which manifests as a spatial gradient of excitability that is emergent from, and causally dependent on, the underlying hierarchical network structure.

show abstract

TMS-Evoked Responses Are Driven by Recurrent Large-Scale Network Dynamics

Cited by 7 publications

References 72 publications

Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia

Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia

Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans

Stimulation mapping and whole-brain modeling reveal gradients of excitability and recurrence in cortical networks

Contact Info

Product

Resources

About