A perturbational approach for evaluating the brain's capacity for consciousness

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Abstract

How do we evaluate a brain's capacity to sustain conscious experience if the subject does not manifest purposeful behaviour and does not respond to questions and commands? What should we measure in this case? An emerging idea in theoretical neuroscience is that what really matters for consciousness in the brain is not activity levels, access to sensory inputs or neural synchronization per se, but rather the ability of different areas of the thalamocortical system to interact causally with each other to form an integrated whole. In particular, the information integration theory of consciousness (IITC) argues that consciousness is integrated information and that the brain should be able to generate consciousness to the extent that it has a large repertoire of available states (information), yet it cannot be decomposed into a collection of causally independent subsystems (integration). To evaluate the ability to integrate information among distributed cortical regions, it may not be sufficient to observe the brain in action. Instead, it is useful to employ a perturbational approach and examine to what extent different regions of the thalamocortical system can interact causally (integration) and produce specific responses (information). Thanks to a recently developed technique, transcranial magnetic stimulation and high-density electroencephalography (TMS/hd-EEG), one can record the immediate reaction of the entire thalamocortical system to controlled perturbations of different cortical areas. In this chapter, using sleep as a model of unconsciousness, we show that TMS/hd-EEG can detect clear-cut changes in the ability of the thalamocortical system to integrate information when the level of consciousness fluctuates across the sleep–wake cycle. Based on these results, we discuss the potential applications of this novel technique to evaluate objectively the brain's capacity for consciousness at the bedside of brain-injured patients.

Section snippets

Evaluating a subject's level of consciousness

The bedside evaluation of patients affected by disorders of consciousness (DOC) relies on repeated behavioural observation by trained personnel. During the examination, spontaneous and elicited behaviour in response to multisensory stimulation is recorded in accordance with specific scales (Giacino et al., 2004; Gill-Thwaites and Munday, 2004; Kalmar and Giacino, 2005; Shiel et al., 2000). Regardless of the scale employed, the examiner typically looks for (1) evidence of awareness of the self

Evaluating a brain's capacity for consciousness

In this chapter, we propose an additional level at which consciousness can be studied even when no communication whatsoever (behavioural or neural) can be established with the subject. This paradigm does not aim at probing the subject in order to elicit wilfull behaviours or neural activations; rather, it involves probing directly the subject's brain to gauge core properties that are theoretically relevant for consciousness. This option requires (1) starting from a theory that suggests which

Theoretical guidelines: the integrated information theory of consciousness

The IITC takes its start from phenomenology and, by making a critical use of thought experiments, argues that subjective experience is integrated information. Therefore, according to the IITC, any physical system will have subjective experience to the extent that it is capable of integrating information. In this view, experience, i.e. information integration, is a fundamental quantity that is, in principle, measurable, just as mass or energy is. Information and integration are, on the other

Employing TMS/hd-EEG to evaluate thalamocortical integration and information capacity

Different methods have been proposed in order to infer on a subject's level of consciousness solely based on brain activity. Some of these methods, such as spectral analysis (Berthomier et al., 2007) and the proprietary “bispectral index” (Myles et al., 2004), seem to correlate empirically with consciousness but have no clear theoretical foundation. Other measures, such as neural complexity (Tononi et al., 1994) and causal density (Seth, 2005), are theoretically motivated (Seth et al., 2008)

TMS/hd-EEG detects changes in the brain's capacity for integrated information during sleep

Sleep is the only time when healthy humans regularly lose consciousness. Subjects awakened during slow-wave sleep early in the night may report short, thought-like fragments of experience, or often nothing at all (Hobson et al., 2000). Sleep also exposes several interesting paradoxes about the relationships between consciousness and the brain. For instance, it was thought that the fading of consciousness during sleep was due to the brain shutting down. However, while metabolic rates decrease in

TMS/EEG in DOC patients: some predictions

Given the variety of brain lesions and conditions that are associated to DOC (Laureys et al. (2004), Laureys et al. (2009)), it is very difficult to predict what kind of results TMS/hd-EEG might give in individual DOC patients. However, an informed guess can be adopted at least in some specific cases. For instance, it is conceivable that TMS-evoked activations similar to the ones described during slow-wave sleep may also be found in patients that are in a coma caused by a lesion in the

Future perspectives

We attempted at identifying an objective marker of consciousness that is theoretically grounded and practically measurable. The core message of this chapter is that using by TMS/hd-EEG it is possible to detect clear-cut changes in the capacity of human thalamocortical circuits to integrate information, a theoretical requirement to generate conscious experience, when the level of consciousness fluctuates across the sleep–wake cycle. The implication of this finding is that TMS/hd-EEG may be

Acknowledgements

This work was supported by European grant STREP LSHM-CT-2205-51818 to Marcello Massimini. Melanie Boly is Research Fellow at the Belgian National Fund for Scientific Research (FNRS). We thank Andrea Soddu, Silvia Casarotto and Fabio Ferrarelli for their help and comments.

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