Matteo Fecchio

Stratification of unresponsive patients by an independently validated index of brain complexity

Validating objective, brain‐based indices of consciousness in behaviorally unresponsive patients represents a challenge due to the impossibility of obtaining independent evidence through subjective reports. Here we address this problem by first validating a promising metric of consciousness—the Perturbational Complexity Index (PCI)—in a benchmark population who could confirm the presence or absence of consciousness through subjective reports, and then applying the same index to patients with disorders of consciousness (DOCs).

Bistability breaks-off deterministic responses to intracortical stimulation during non-REM sleep

During non-rapid eye movement (NREM) sleep (stage N3), when consciousness fades, cortico-cortical interactions are impaired while neurons are still active and reactive. Why is this? We compared cortico-cortical evoked-potentials recorded during wakefulness and NREM by means of time-frequency analysis and phase-locking measures in 8 epileptic patients undergoing intra-cerebral stimulations/recordings for clinical evaluation. We observed that, while during wakefulness electrical stimulation triggers a chain of deterministic phase-locked activations in its cortical targets, during NREM the same input induces a slow wave associated with an OFF-period (suppression of power>20Hz), possibly reflecting a neuronal down-state. Crucially, after the OFF-period, cortical activity resumes to wakefulness-like levels, but the deterministic effects of the initial input are lost, as indicated by a sharp drop of phase-locked activity. These findings suggest that the intrinsic tendency of cortical neurons to fall into a down-state after a transient activation (i.e. bistability) prevents the emergence of stable patterns of causal interactions among cortical areas during NREM. Besides sleep, the same basic neurophysiological dynamics may play a role in pathological conditions in which thalamo-cortical information integration and consciousness are impaired in spite of preserved neuronal activity.

Quantifying Cortical EEG Responses to TMS in (Un)consciousness

We normally assess another individual’s level of consciousness based on her or his ability to interact with the surrounding environment and communicate. Usually, if we observe purposeful behavior, appropriate responses to sensory inputs, and, above all, appropriate answers to questions, we can be reasonably sure that the person is conscious. However, we know that consciousness can be entirely within the brain, even in the absence of any interaction with the external world; this happens almost every night, while we dream. Yet, to this day, we lack an objective, dependable measure of the level of consciousness that is independent of processing sensory inputs and producing appropriate motor outputs. Theoretically, consciousness is thought to require the joint presence of functional integration and functional differentiation, otherwise defined as brain complexity. Here we review a series of recent studies in which Transcranial Magnetic Stimulation combined with electroencephalography (TMS/EEG) has been employed to quantify brain complexity in wakefulness and during physiological (sleep), pharmacological (anesthesia) and pathological (brain injury) loss of consciousness. These studies invariably show that the complexity of the cortical response to TMS collapses when consciousness is lost during deep sleep, anesthesia and vegetative state following severe brain injury, while it recovers when consciousness resurges in wakefulness, during dreaming, in the minimally conscious state or locked-in syndrome. The present paper will also focus on how this approach may contribute to unveiling the pathophysiology of disorders of consciousness affecting brain-injured patients. Finally, we will underline some crucial methodological aspects concerning TMS/EEG measurements of brain complexity.

Assessing the Effects of Electroconvulsive Therapy on Cortical Excitability by Means of Transcranial Magnetic Stimulation and Electroencephalography

Electroconvulsive therapy (ECT) has significant short-term antidepressant effects on drug-resistant patients with severe major depression. Animal studies have demonstrated that electroconvulsive seizures produce potentiation-like synaptic remodeling in both sub-cortical and frontal cortical circuits. However, the electrophysiological effects of ECT in the human brain are not known. In this work, we evaluated whether ECT induces a measurable change in the excitability of frontal cortical circuits in humans. Electroencephalographic (EEG) potentials evoked by transcranial magnetic stimulation (TMS) were collected before and after a course of ECT in eight patients with severe major depression. Cortical excitability was measured from the early and local EEG response to TMS. Clinical assessment confirmed the beneficial effects of ECT on depressive symptoms at the group level. TMS/EEG measurements revealed a clear-cut increase of frontal cortical excitability after ECT as compared to baseline, that was significant in each and every patient. The present findings corroborate in humans the idea that ECT may produce synaptic potentiation, as previously observed in animal studies. Moreover, results suggest that TMS/EEG may be employed in depressed patients to monitor longitudinally the electrophysiological effects of different therapeutic neuromodulators, e.g. ECT, repetitive TMS, and sleep deprivation. To the extent that depression involves an alteration of frontal cortical excitability, these measurements may be used to guide and evaluate treatment progression over time at the single-patient level.

Changes of cortical excitability as markers of antidepressant response in bipolar depression: preliminary data obtained by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG)

It is still unclear which biological changes are needed to recover from a major depressive episode. Current perspectives focus on cortical synaptic neuroplasticity. Measures of cortical responses evoked by transcranial magnetic stimulation (TMS) change with sleep homeostasic pressure in humans and approximate measures of synaptic strength in animal models. Using repeated total sleep deprivation as a model of antidepressant treatment, we aimed to correlate recovery from depression with these measures of cortical excitability.

Shared reduction of oscillatory natural frequencies in bipolar disorder, major depressive disorder and schizophrenia.

INTRODUCTION Recent studies have demonstrated that cortical brain areas tend to oscillate at a specific natural frequency when directly perturbed by transcranial magnetic stimulation (TMS). Fast electroencephalographic (EEG) oscillations, which typically originate from frontal regions, have been reported to be markedly reduced in schizophrenia. METHODS Here we employed TMS/EEG to assess the natural frequency of the premotor area in a sample of 48 age-matched participants (12 each in major depression disorder (MDD)), bipolar disorder (BPD), schizophrenia (SCZ) and healthy controls. Event related spectral perturbations (ERSP) were obtained for each study participant using wavelet decomposition. RESULTS TMS resulted in a significant activation of the beta/gamma band response (21-50 Hz) to frontal cortical perturbation in healthy control subjects. By contrast, the main frequencies of frontal EEG responses to TMS were significantly reduced in patients with BPD, MDD and SCZ (11-27 Hz) relative to healthy subjects. CONCLUSIONS Patients with bipolar disorder, major depression and schizophrenia showed a significantly lower natural frequency of frontal cortico-thalamocortical circuits compared to healthy controls. These results suggest a common neurobiological mechanism of corticothalamic impairment. The most likely candidates include dysfunction of GABAergic circuits. LIMITATIONS Further studies are needed to consider other biological markers, gene variants, and their interaction with clinical variables.

The spectral features of EEG responses to transcranial magnetic stimulation of the primary motor cortex depend on the amplitude of the motor evoked potentials

Transcranial magnetic stimulation (TMS) of the primary motor cortex (M1) can excite both cortico-cortical and cortico-spinal axons resulting in TMS-evoked potentials (TEPs) and motor-evoked potentials (MEPs), respectively. Despite this remarkable difference with other cortical areas, the influence of motor output and its amplitude on TEPs is largely unknown. Here we studied TEPs resulting from M1 stimulation and assessed whether their waveform and spectral features depend on the MEP amplitude. To this aim, we performed two separate experiments. In experiment 1, single-pulse TMS was applied at the same supra-threshold intensity on primary motor, prefrontal, premotor and parietal cortices and the corresponding TEPs were compared by means of local mean field power and time-frequency spectral analysis. In experiment 2 we stimulated M1 at resting motor threshold in order to elicit MEPs characterized by a wide range of amplitudes. TEPs computed from high-MEP and low-MEP trials were then compared using the same methods applied in experiment 1. In line with previous studies, TMS of M1 produced larger TEPs compared to other cortical stimulations. Notably, we found that only TEPs produced by M1 stimulation were accompanied by a late event-related desynchronization (ERD—peaking at ~300 ms after TMS), whose magnitude was strongly dependent on the amplitude of MEPs. Overall, these results suggest that M1 produces peculiar responses to TMS possibly reflecting specific anatomo-functional properties, such as the re-entry of proprioceptive feedback associated with target muscle activation.

The impact of GABAergic drugs on TMS-induced brain oscillations in human motor cortex

&NA; Brain responses to transcranial magnetic stimulation (TMS) as measured with electroencephalography (EEG) have so far been assessed either by TMS‐evoked EEG potentials (TEPs), mostly reflecting phase‐locked neuronal activity, or time‐frequency‐representations (TFRs), reflecting oscillatory power arising from a mixture of both evoked (i.e., phase‐locked) and induced (i.e., non‐phase‐locked) responses. Single‐pulse TMS of the human primary motor cortex induces a specific pattern of oscillatory changes, characterized by an early (30–200 ms after TMS) synchronization in the &agr;‐ and &bgr;‐bands over the stimulated sensorimotor cortex and adjacent lateral frontal cortex, followed by a late (200–400 ms) &agr;‐ and &bgr;‐desynchronization over the stimulated and contralateral sensorimotor cortex. As GABAergic inhibition plays an important role in shaping oscillatory brain activity, we sought here to understand if GABAergic inhibition contributes to these TMS‐induced oscillations. We tested single oral doses of alprazolam, diazepam, zolpidem (positive modulators of the GABAA receptor), and baclofen (specific GABAB receptor agonist). Diazepam and zolpidem enhanced, and alprazolam tended to enhance while baclofen decreased the early &agr;‐synchronization. Alprazolam and baclofen enhanced the early &bgr;‐synchronization. Baclofen enhanced the late &agr;‐desynchronization, and alprazolam, diazepam and baclofen enhanced the late &bgr;‐desynchronization. The observed GABAergic drug effects on TMS‐induced &agr;‐ and &bgr;‐band oscillations were not explained by drug‐induced changes on corticospinal excitability, muscle response size, or resting‐state EEG power. Our results provide first insights into the pharmacological profile of TMS‐induced oscillatory responses of motor cortex. HighlightsThe response to TMS of M1 is composed of evoked and induced oscillatory activity.TMS induced early &agr;‐/&bgr;‐synchronization and late &agr;‐/&bgr;‐desynchronization in M1.GABAAergic vs. GABABergic drugs had opposite effects on early &agr;‐synchronization.GABAAergic and GABABergic drugs enhanced the late &bgr;‐desynchronization.

Sleep-like bistability, loss of causality and complexity in the brain of Unresponsive Wakefulness Syndrome patients

Unresponsiveness Wakefulness Syndrome (UWS) patients may retain intact portions of the thalamocortical system that are spontaneously active and responsive to sensory stimuli. In these patients, Transcranial Magnetic Stimulation combined with electroencephalography (TMS/EEG) also reveals preserved cortical reactivity, but in most cases, the residual thalamocortical circuits fail to engage complex causal interactions, as assessed by the perturbational complexity index (PCI). Another condition during which thalamocortical circuits are intact, active and reactive, yet unable to generate complex responses, is physiological non-rapid eye movement (NREM) sleep. The underlying mechanism is bistability: the tendency of cortical neurons to fall into a silent period (OFF-period) upon receiving an input. Here we tested whether a pathological form of bistability may be responsible for loss of brain complexity in UWS patients. Time-frequency decomposition analysis of TMS/EEG responses in UWS patients revealed the occurrence of OFF-periods (detected as a transient suppression of high-frequency oscillations in the EEG) similar to the ones evoked by TMS in the cortex of healthy sleeping subjects. Pathological OFF-periods were detected in any cortical area, significantly impaired local causal interactions (as measured by PLF) and prevented the buildup of global complexity (as measured by PCI) in the brain of UWS patients. Our results draw a first link between neuronal events (OFF-periods) and global brain dynamics (complexity) in UWS patients. To the extent that sleep-like bistability represents the common functional endpoint of loss of complexity, detecting its presence and tracking its evolution over time, may offer a valuable read-out to devise, guide and titrate therapeutic strategies aimed at restoring consciousness.

A fast and general method to empirically estimate the complexity of distributed causal interactions in the brain

A novel metric, called Perturbational Complexity Index (PCI), was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. Once validated and calibrated in a large benchmark, PCI showed high accuracy in detecting consciousness in brain injured patients. In its original formulation, the index was computed by stimulating the brain with transcranial magnetic stimulation (TMS) and using the Lempel-Ziv algorithm to quantify the spatiotemporal complexity of cortical responses, as derived by the inverse solution of high-density EEG (hd-EEG). Despite its accuracy in assessing consciousness, the original formulation of PCI was limited by its reliance on source estimation, which not only renders its calculation timeconsuming, dependent on elaborate experimental setups and offline processing, but also restricts its extension to other types of brain signals beyond TMS/hd-EEG recordings. Here, we address these limitations and introduce PCIST, a fast and simple method for estimating perturbational complexity of any given brain response signal. Our approach combines dimensionality reduction with a novel metric of complexity derived from recurrence quantification analysis, in which state transitions (ST) present in the signal’s principal components are quantified in order to estimate spatiotemporal complexity directly at the sensors level. PCIST was tested on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 patients with brain injuries, and also applied to sparse intracranial recordings of 9 patients undergoing intra-cerebral single-pulse electrical stimulation. The new method performs with the same accuracy as the original formulation, but the index can be computed in less than a second, requires a simpler setup and can be generalized to sparse intracranial recordings. PCIST advances towards the development of a clinical bedside index of consciousness and can be used as a general tool to study the brain’s complexity across scales, experimental models and species.Background: The Perturbational Complexity Index (PCI) was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain injured patients, PCI depends on elaborate experimental setups and offline processing and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG) recordings. Objective: We aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. Methods: PCIST is based on dimensionality reduction and state transitions (ST) quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain injured patients, and tested on sparse intracranial recordings (SEEG) of 9 patients undergoing intra-cerebral single-pulse electrical stimulation (SPES). Results: When calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracerebral complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. Conclusions: PCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.