General indices to characterize the electrical response of the cerebral cortex to TMS
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).
References (50)
- et al.
A fast method for forward computation of multiple-shell spherical head models
Electroencephalogr. Clin. Neurophysiol.
(1994) - et al.
Changes in effective connectivity of the primary motor cortex in stroke patients after rehabilitative therapy
Exp. Neurol.
(2006) - et al.
Evaluation of different measures of functional connectivity using a neural mass model
NeuroImage
(2004) - et al.
Diffusion tensor MRI-based estimation of the influence of brain tissue anisotropy on the effects of transcranial magnetic stimulation
NeuroImage
(2007) - et al.
Wavelet analysis of the EEG during the neurocognitive evaluation of invalidly cued targets
Brain Res.
(2008) - et al.
Classical and Bayesian inference in neuroimaging: theory
NeuroImage
(2002) The elusive concept of brain connectivity
NeuroImage
(2003)- et al.
Prefrontal transcranial magnetic stimulation produces intensity-dependent EEG responses in humans
NeuroImage
(2005) - et al.
The novelty value of the combined use of electroencephalography and transcranial magnetic stimulation for neuroscience research
Brain Res. Rev.
(2006) - et al.
The distinct modes of vision offered by feedforward and recurrent processing
Trends Neurosci.
(2000)
Impaired effective cortical connectivity in vegetative state: preliminary investigation using PET
NeuroImage
Restoration of thalamocortical connectivity after recovery from persistent vegetative state
Lancet
“Pray or Prey?” dissociation of semantic memory retrieval from episodic memory processes using positron emission tomography and a novel homophone task
NeuroImage
An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets
NeuroImage
Precentral gyrus discrepancy in electronic versions of the Talairach atlas
NeuroImage
MEG source localization under multiple constraints: an extended Bayesian framework
NeuroImage
An empirical Bayesian solution to the source reconstruction problem in EEG
NeuroImage
Analysis of interhemispheric asymmetries of somatosensory evoked magnetic fields to right and left median nerve stimulation
Electroencephalogr. Clin. Neurophysiol.
Gabor filters: an informative way for analyzing event-related brain activity
J. Neurosci. Methods
A new device and protocol for combining TMS and online recordings of EEG and evoked potentials
J. Neurosci. Methods
Detection of muscle artefact in the normal human awake EEG
Electr. Clin. Neurophysiol.
Modeling of magnetic field stimulation of bent neurons
IEEE Trans. Biomed. Eng.
Evoked potentials in clinical medicine
Topographical organization of cortical afferents to extrastriate visual area PO in the macaque: a dual tracer study
J. Comp. Neurol.
Time-dependent changes in effective connectivity measured with PET
Hum. Brain Mapp.
Cited by (116)
Towards real-time identification of large-scale brain states for improved brain state-dependent stimulation
2024, Clinical NeurophysiologySpatial characteristics of closed-loop TMS-EEG with occipital alpha-phase synchronized
2023, Biomedical Signal Processing and ControlTMS combined with EEG: Recommendations and open issues for data collection and analysis
2023, Brain Stimulation