Elsevier

NeuroImage

Volume 49, Issue 2, 15 January 2010, Pages 1459-1468
NeuroImage

General indices to characterize the electrical response of the cerebral cortex to TMS

https://doi.org/10.1016/j.neuroimage.2009.09.026Get rights and content

Abstract

Transcranial magnetic stimulation (TMS) combined with simultaneous high-density electroencephalography (hd-EEG) represents a straightforward way to gauge cortical excitability and connectivity in humans. However, the analysis, classification and interpretation of TMS-evoked potentials are hampered by scarce a priori knowledge about the physiological effect of TMS and by lack of an established data analysis framework. Here, we implemented a standardized, data-driven procedure to characterize the electrical response of the cerebral cortex to TMS by means of three synthetic indices: significant current density (SCD), phase-locking (PL) and significant current scattering (SCS). SCD sums up the amplitude of all significant currents induced by TMS, PL reflects the ability of TMS to reset the phase of ongoing cortical oscillations, while SCS measures the average distance of significantly activated sources from the site of stimulation. These indices are aimed at capturing different aspects of brain responsiveness, ranging from global cortical excitability towards global cortical connectivity. We analyzed the EEG responses to TMS of Brodmann's area 19 at increasing intensities in five healthy subjects. The spatial distribution and time course of SCD, PL and SCS revealed a reproducible profile of excitability and connectivity, characterized by a local activation threshold around a TMS-induced electric field of 50 V/m and by a selective propagation of TMS-evoked activation from occipital to ipsilateral frontal areas that reached a maximum at 70–100 ms. These general indices may be used to characterize the effects of TMS on any cortical area and to quantitatively evaluate cortical excitability and connectivity in physiological and pathological conditions.

Introduction

The development of multichannel TMS-compatible EEG amplifiers (Virtanen et al., 1999, Iramina et al., 2003, Thut et al., 2005) has recently opened the possibility of recording the electrical response of the human brain to a direct cortical stimulation. Today, by combining TMS with high-density electroencephalography (hd-EEG), we can directly and non-invasively stimulate virtually any cortical area and measure, with good spatial–temporal resolution, the effects produced by this perturbation in the rest of the thalamocortical system (Ilmoniemi et al., 1997, Komssi and Kähkönen, 2006).

TMS/hd-EEG stimulates and records from the cerebral cortex directly, while by-passing sensory pathways, sub-cortical structures and motor pathways. Thus, at difference with traditional sensory-evoked potentials, event-related metabolic activations and TMS-evoked muscle potentials, this method does not depend on the integrity/status of sensory and motor systems and can be applied to any patient (de-afferentated, paralyzed, unconscious) and to any cortical area (primary and associative). Moreover, TMS/hd-EEG can activate cortical neurons with a wide range of stimulation intensities, without being constrained by the physiology of peripheral receptors and nerves. As a consequence, it can provide full excitability profiles, from threshold to saturation (Komssi et al., 2004, Kähkönen et al., 2005). Finally, by recording the effects produced by the activation of the stimulated neurons on distant cortical sites, TMS/hd-EEG offers an unambiguous measure of effective connectivity (Massimini et al., 2005, Paus, 2005, Morishima et al., 2009). Alterations of cortical excitability and connectivity are the common substrate of most neurological and psychiatric conditions; therefore, the possibility to detect these alterations, in virtually any portion of the human thalamocortical system, has clear clinical implications.

If, on one hand, TMS/hd-EEG allows probing human thalamocortical circuits with unprecedented flexibility, on the other hand, it entails the challenge of dealing with several unknowns. For instance, while in the case of sensory-evoked potentials, a known set of cortical neurons is activated through a narrow afferent channel (such as the median, the optic or the auditory nerve), using TMS/hd-EEG a large number of cortical locations can be arbitrarily selected and directly perturbed, each one with several stimulation parameters (e.g., intensity, time course and orientation of the magnetic field). As a consequence, while the analysis of sensory-evoked potentials can be often restricted to pre-selected waves, peaks and latencies (Chiappa, 1997), little a priori knowledge is available to characterize the brain's reaction to TMS. Yet, this characterization is a prerequisite to define normative values and to take advantage of the potential of TMS/hd-EEG as a research and diagnostic tool. The specific aim of this paper is to develop a standardized, data-driven procedure in order to describe the brain response to TMS through a limited set of informative indices.

The proposed analysis procedure includes four preliminary steps: (i) data pre-processing, to increase signal-to-noise ratio; (ii) source modelling of single-trial EEG recordings, to improve spatial resolution; (iii) non-parametric statistical analysis, to extract statistically significant cortical activations; and (iv) automatic anatomical labelling of individual magnetic resonance images (MRIs), to reduce the dimensionality of data, namely, from thousands of dipolar sources to tens of identifiable cortical sub-regions. Once these steps are taken, we obtain a spatial-temporal matrix that describes “where” and “when” significant TMS-evoked activations occurred within the cerebral cortex. Starting from this matrix we calculate three indices, significant current density (SCD), phase-locking (PL) and significant current scattering (SCS), that are meant to capture different aspects of the cortical response to TMS. By applying this automatic analysis procedure to real TMS/hd-EEG data (stimulation of Brodmann's area, BA19, at increasing TMS intensities) we show that it is possible to detect and represent, in a simple and informative way, basic electrophysiological properties of the stimulated circuits, such as the local activation threshold (excitability) and the specific pattern of activation propagation (connectivity). We argue that this analysis procedure may represent a step towards the development of quantitative TMS/hd-EEG measures.

Section snippets

Experimental protocol

Five healthy adults (two males and three females, age range 23–37 years) were enrolled in the experiment. All participants underwent clinical examinations to rule out history or presence of any relevant medical disorder. Furthermore, a specific neurological screening was administered to exclude any potential adverse effect of TMS. The entire experimental procedure was approved by the Local Ethical Committee of the Hospital “Luigi Sacco” University of Milan. Written informed consent was obtained

Results and discussion

In this section we report and discuss the results obtained by applying the analysis procedure described above to scalp potentials recorded from five healthy volunteers in whom the superior occipital lobule was stimulated at several increasing TMS intensities. Results are reported following a hierarchical order where general indices of global brain responsiveness eventually drive the extraction of more specific and local indices.

Conclusions

In the present work we implemented a data-driven procedure to characterize TMS-evoked cortical potentials. This procedure, based on source modeling, non-parametric statistics and data reduction, outputs a limited set of indices (SCD, PL and SCS) of cortical excitability and connectivity. These general indices can be used to describe synthetically the large-scale effects of TMS on cortical circuits, even when very little a priori knowledge is available. For example, their application to the

Acknowledgments

We thank Giulio Tononi, Leonor Romero, Fabio Ferrarelli and Karina Rabello Casali for their help and comments. This work was supported by European Grant Strep LSHM-CT-2005-51818, by PRIN 2006 and by European Grant Strep ICT- 2007-224328 “Predict AD” (to M. Massimini).

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