Simultaneous invasive and non-invasive recordings in humans: a novel Rosetta stone for deciphering brain activity.

Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.

New stimulation procedures for language mapping in stereo-EEG.

OBJECTIVE: Cortical intracerebral electrical stimulation is an important tool for language mapping in the presurgical work-up of patients with drug-resistant focal epilepsy. Language mapping with stereo-electroencephalography (EEG) is usually performed by high-frequency stimulations (HFS: 50 Hz), whereas low-frequency stimulations (LFS: 1 Hz) are usually considered useful for primary cortices mapping. Little is known in literature about "intermediate" frequencies (IFS: 6-15 Hz). Our objective is to explore the clinical usefulness of IFS in language mapping and identify factors, beyond the electrical parameters, that impact the mapping. METHODS: We studied 23 patients submitted to stereo-EEG for presurgical evaluation. Language mapping was performed in the anterior, posterior and/or basal language region of the dominant hemisphere for language. We included all contact positions within these regions stimulated by HFS (50 Hz, 5 s, 1-3 mA) and IFS (6-15 Hz, 15 s, 5 mA). We compared the capability of both stimulation methods to induce a language deficit without afterdischarges (ADs), and we analyzed factors related to clinical examination, region, and stimulation technique by multivariate analysis. RESULTS: A total of 211 stimulations (98 HFS, 113 IFS) in 70 cortical sites within the anterior (84 stimulations), posterior (137), and basal language region (60) were included. IFS induced more frequently language deficits not associated to AD compared to HFS (37.1% vs 25.7%, p = .0043), whereas HFS provoked more diffuse AD (34.7% vs 15.0%, p = .001). Investigating multiple language functions increased the probability of revealing a deficit (odds ratio [OR] 3.16, p = .0016), independently of the stimulation method. SIGNIFICANCE: IFS are valuable for language mapping, thereby improving the probability of inducing a clinical deficit not accompanied by an AD. The completeness of the clinical examination independently affects the sensitivity of the mapping. IFS are a new tool with potential usefulness for the cortical mapping of other associative cortical regions.

An integrative, multiscale view on neural theories of consciousness.

How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other. Instead, several of them may converge on fundamental neuronal mechanisms and be partly compatible and complementary, so that multiple theories can simultaneously contribute to our understanding. Here, we consider unifying, integration-oriented approaches that have so far been largely neglected, seeking to combine valuable elements from various theories.

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

Cortical stimulation with single pulses is a common technique in clinical practice and research. However, we still do not understand the extent to which it engages subcortical circuits which contribute to the associated evoked potentials (EPs). Here we find that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the subject's behavioral state. We optogenetically dissect the underlying circuit in mice, demonstrating that the late component of these EPs is caused by a 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. A simulation of the thalamo-cortical circuit highlights that both intrinsic thalamic currents as well as cortical and thalamic GABAergic neurons contribute to this response profile. We conclude that the cortical stimulation engages cortico-thalamo-cortical circuits highly preserved across different species and stimulation modalities.

Adaptation Shapes Local Cortical Reactivity: From Bifurcation Diagram and Simulations to Human Physiological and Pathological Responses.

Human studies employing intracerebral and transcranial perturbations suggest that the input-output properties of cortical circuits are dramatically affected during sleep in healthy subjects as well as in awake patients with multifocal and focal brain injury. In all these conditions, cortical circuits react to direct stimulation with an initial activation followed by suppression of activity (Off-period) that disrupts the build-up of sustained causal interactions typically observed in healthy wakefulness. The transition to this stereotypical response has important clinical implications, being associated with loss of consciousness or loss of functions. Here, we provide a mechanistic explanation of these findings by means of simulations of a cortical-like module endowed with activity-dependent adaptation and mean-field theory. First, we show that fundamental aspects of the local responses elicited in humans by direct cortical stimulation can be replicated by systematically varying the relationships between adaptation strength and excitation level in the network. Then, we reveal a region in the adaptation-excitation parameter space of crucial relevance for both physiological and pathologic conditions, where spontaneous activity and responses to perturbation diverge in their ability to reveal Off-periods. Finally, we substantiate through simulations of connected cortical-like modules the role of adaptation mechanisms in preventing cortical neurons from engaging in reciprocal causal interactions, as suggested by empirical studies. These modeling results provide a general theoretical framework and a mechanistic interpretation for a body of neurophysiological measurements that bears critical relevance for physiological states as well as for the assessment and rehabilitation of brain-injured patients.

An in-vivo validation of ESI methods with focal sources.

Electrophysiological source imaging (ESI) aims at reconstructing the precise origin of brain activity from measurements of the electric field on the scalp. Across laboratories/research centers/hospitals, ESI is performed with different methods, partly due to the ill-posedness of the underlying mathematical problem. However, it is difficult to find systematic comparisons involving a wide variety of methods. Further, existing comparisons rarely take into account the variability of the results with respect to the input parameters. Finally, comparisons are typically performed using either synthetic data, or in-vivo data where the ground-truth is only roughly known. We use an in-vivo high-density EEG dataset recorded during intracranial single pulse electrical stimulation, in which the true sources are substantially dipolar and their locations are precisely known. We compare ten different ESI methods, using their implementation in the MNE-Python package: MNE, dSPM, LORETA, sLORETA, eLORETA, LCMV beamformers, irMxNE, Gamma Map, SESAME and dipole fitting. We perform comparisons under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of such parameters on the localization performance. Best reconstructions often fall within 1 cm from the true source, with most accurate methods hitting an average localization error of 1.2 cm and outperforming least accurate ones erring by 2.5 cm. As expected, dipolar and sparsity-promoting methods tend to outperform distributed methods. For several distributed methods, the best regularization parameter turned out to be the one in principle associated with low SNR, despite the high SNR of the available dataset. Depth weighting played no role for two out of the six methods implementing it. Sensitivity to input parameters varied widely between methods. While one would expect high variability being associated with low localization error at the best solution, this is not always the case, with some methods producing highly variable results and high localization error, and other methods producing stable results with low localization error. In particular, recent dipolar and sparsity-promoting methods provide significantly better results than older distributed methods. As we repeated the tests with "conventional" (32 channels) and dense (64, 128, 256 channels) EEG recordings, we observed little impact of the number of channels on localization accuracy; however, for distributed methods denser montages provide smaller spatial dispersion. Overall findings confirm that EEG is a reliable technique for localization of point sources and therefore reinforce the importance that ESI may have in the clinical context, especially when applied to identify the surgical target in potential candidates for epilepsy surgery.

Neocortical and medial temporal seizures have distinct impacts on brain responsiveness.

Focal epileptic seizures are characterized by abnormal neuronal discharges that can spread to other cortical areas and interfere with brain activity, thereby altering the patient's experience and behavior. The origin of these pathological neuronal discharges encompasses various mechanisms that converge toward similar clinical manifestations. Recent studies have suggested that medial temporal lobe (MTL) and neocortical (NC) seizures are often underpinned by two characteristic onset patterns, which, respectively, affect and spare synaptic transmission in cortical slices. However, these synaptic alterations and their effects have never been confirmed or studied in intact human brains. To fill this gap, we here evaluate whether responsiveness of MTL and NC are differentially affected by focal seizures, using a unique data set of cortico-cortical evoked potentials (CCEPs) collected during seizures triggered by single-pulse electrical stimulation (SPES). We find that responsiveness is abruptly reduced by the onset of MTL seizures, despite increased spontaneous activity, whereas it is preserved in the case of NC seizures. The present results provide an extreme example of dissociation between responsiveness and activity and show that brain networks are diversely affected by the onset of MTL and NC seizures, thus extending at the whole brain level the evidence of synaptic alteration found in vitro.

The vision of haptics tunes the somatosensory threshold.

The interaction between different sensory modalities represents a crucial issue in the neuroscience of consciousness: when the processing of one modality is deficient, the concomitant presentation of stimuli of other spared modalities may sustain the restoration of the damaged sensory functions. In this regard, visual enhancement of touch may represent a viable tool in rehabilitating tactile disorders, yet the specific visual features mostly modulating the somatosensory experience remain unsettled. In this study, healthy subjects underwent a tactile detection task during the observation of videos displaying different contents, including static gratings, meaningless motions and natural or point-lights reach-to-grasp-and-manipulate actions. Concurrently, near-threshold stimuli were delivered to the median nerve at different time-points. The subjective report was collected after each trial; the sensory detection rate was computed and compared across video conditions. Our results indicate that the specific presence of haptic contents (i.e., the vision of manipulation), either fully displayed or implied by point-lights, magnifies tactile sensitivity. The notion that such stimuli prompt a conscious tactile experience opens to novel rehabilitation approaches for tactile consciousness disorders.

Tonic somatosensory responses and deficits of tactile awareness converge in the parietal operculum.

Although clinical neuroscience and the neuroscience of consciousness have long sought mechanistic explanations of tactile-awareness disorders, mechanistic insights are rare, mainly because of the difficulty of depicting the fine-grained neural dynamics underlying somatosensory processes. Here, we combined the stereo-EEG responses to somatosensory stimulation with the lesion mapping of patients with a tactile-awareness disorder, namely tactile extinction. Whereas stereo-EEG responses present different temporal patterns, including early/phasic and long-lasting/tonic activities, tactile-extinction lesion mapping co-localizes only with the latter. Overlaps are limited to the posterior part of the perisylvian regions, suggesting that tonic activities may play a role in sustaining tactile awareness. To assess this hypothesis further, we correlated the prevalence of tonic responses with the tactile-extinction lesion mapping, showing that they follow the same topographical gradient. Finally, in parallel with the notion that visuotactile stimulation improves detection in tactile-extinction patients, we demonstrated an enhancement of tonic responses to visuotactile stimuli, with a strong voxel-wise correlation with the lesion mapping. The combination of these results establishes tonic responses in the parietal operculum as the ideal neural correlate of tactile awareness.

A comparative study between state-of-the-art MRI deidentification and AnonyMI, a new method combining re-identification risk reduction and geometrical preservation.

Deidentifying MRIs constitutes an imperative challenge, as it aims at precluding the possibility of re-identification of a research subject or patient, but at the same time it should preserve as much geometrical information as possible, in order to maximize data reusability and to facilitate interoperability. Although several deidentification methods exist, no comprehensive and comparative evaluation of deidentification performance has been carried out across them. Moreover, the possible ways these methods can compromise subsequent analysis has not been exhaustively tested. To tackle these issues, we developed AnonyMI, a novel MRI deidentification method, implemented as a user-friendly 3D Slicer plugin-in, which aims at providing a balance between identity protection and geometrical preservation. To test these features, we performed two series of analyses on which we compared AnonyMI to other two state-of-the-art methods, to evaluate, at the same time, how efficient they are at deidentifying MRIs and how much they affect subsequent analyses, with particular emphasis on source localization procedures. Our results show that all three methods significantly reduce the re-identification risk but AnonyMI provides the best geometrical conservation. Notably, it also offers several technical advantages such as a user-friendly interface, multiple input-output capabilities, the possibility of being tailored to specific needs, batch processing and efficient visualization for quality assurance.

Thalamic and neocortical differences in the relationship between the time course of delta and sigma power during NREM sleep in humans.

Sleep spindles and slow waves are the hallmarks of non-rapid eye movement (NREM) sleep and are produced by the dynamic interplay between thalamic and cortical regions. Several studies in both human and animal models have focused their attention on the relationship between electroencephalographic (EEG) spindles and slow waves during NREM, using the power in the sigma and delta bands as a surrogate for the production of spindles and slow waves. A typical report is an overall inverse relationship between the time course of sigma and delta power as measured by a single correlation coefficient both within and across NREM episodes. Here we analysed stereotactically implanted intracerebral electrode (Stereo-EEG [SEEG]) recordings during NREM simultaneously acquired from thalamic and from several neocortical sites in six neurosurgical patients. We investigated the relationship between the time course of delta and sigma power and found that, although at the cortical level it shows the expected inverse relationship, these two frequency bands follow a parallel time course at the thalamic level. Both these observations were consistent across patients and across different cortical as well as thalamic regions. These different temporal dynamics at the neocortical and thalamic level are discussed, considering classical as well as more recent interpretations of the neurophysiological determinants of sleep spindles and slow waves. These findings may also help understanding the regulatory mechanisms of these fundamental sleep EEG graphoelements across different brain compartments.

Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods.

Precisely localizing the sources of brain activity as recorded by EEG is a fundamental procedure and a major challenge for both research and clinical practice. Even though many methods and algorithms have been proposed, their relative advantages and limitations are still not well established. Moreover, these methods involve tuning multiple parameters, for which no principled way of selection exists yet. These uncertainties are emphasized due to the lack of ground-truth for their validation and testing. Here we present the Localize-MI dataset, which constitutes the first open dataset that comprises EEG recorded electrical activity originating from precisely known locations inside the brain of living humans. High-density EEG was recorded as single-pulse biphasic currents were delivered at intensities ranging from 0.1 to 5 mA through stereotactically implanted electrodes in diverse brain regions during pre-surgical evaluation of patients with drug-resistant epilepsy. The uses of this dataset range from the estimation of in vivo tissue conductivity to the development, validation and testing of forward and inverse solution methods.

A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations.

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 intracranial single-pulse electrical stimulation (SPES) during wakefulness and sleep. 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 intracranial 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.

Assessing recurrent interactions in cortical networks: Modeling EEG response to transcranial magnetic stimulation.

BACKGROUND: The basic mechanisms underlying the electroencephalograpy (EEG) response to transcranial magnetic stimulation (TMS) of the human cortex are not well understood. NEW METHOD: A state-space modeling methodology is developed to gain insight into the network nature of the TMS/EEG response. Cortical activity is modeled using a multivariariate autoregressive model with exogenous stimulation parameters representing the effect of TMS. An observation equation models EEG measurement of cortical activity. An expectation-maximization algorithm is developed to estimate the model parameters. RESULTS: The methodology is used to assess two different hypotheses for the mechanisms underlying TMS/EEG in wakefulness and sleep. The integrated model hypothesizes that recurrent interactions between cortical regions are the source of TMS/EEG, while the segregated model hypothesizes that the TMS/EEG results from excitation of independent cortical oscillators. The results show that the relatively simple EEG response to TMS recorded during non-rapid-eye-movement sleep is described equally well by either the integrated or segregated model. However, the integrated model fits the more complex TMS/EEG of wakefulness much better than the segregated model. COMPARISON WITH EXISTING METHOD(S): Existing methods are limited to small numbers of cortical regions of interest or do not represent the effect of TMS. Our results are consistent with previous studies contrasting the complexity of TMS/EEG in wakefulness and sleep. CONCLUSION: The new method strongly suggests that effective feedback connections between cortical regions are required to produce the TMS/EEG in wakefulness.

Sleep as a model to understand neuroplasticity and recovery after stroke: Observational, perturbational and interventional approaches.

Our own experiences with disturbances to sleep demonstrate its crucial role in the recovery of cognitive functions. This importance is likely enhanced in the recovery from stroke; both in terms of its physiology and cognitive abilities. Decades of experimental research have highlighted which aspects and mechanisms of sleep are likely to underlie these forms of recovery. Conversely, damage to certain areas of the brain, as well as the indirect effects of stroke, may disrupt sleep. However, only limited research has been conducted which seeks to directly explore this bidirectional link between both the macro and micro-architecture of sleep and stroke. Here we describe a series of semi-independent approaches that aim to establish this link through observational, perturbational, and interventional experiments. Our primary aim is to describe the methodology for future clinical and translational research needed to delineate competing accounts of the current data. At the observational level we suggest the use of high-density EEG recording, combined analysis of macro and micro-architecture of sleep, detailed analysis of the stroke lesion, and sensitive measures of functional recovery. The perturbational approach attempts to find the causal links between sleep and stroke. We promote the use of transcranial magnetic stimulation combined with EEG to examine the cortical dynamics of the peri-infarct stroke area. Translational research should take this a step further using optogenetic techniques targeting more specific cell populations. The interventional approach focuses on how the same clinical and translational perturbational techniques can be adapted to influence long-term recovery of function.

Bistability, Causality, and Complexity in Cortical Networks: An In Vitro Perturbational Study.

Measuring the spatiotemporal complexity of cortical responses to direct perturbations provides a reliable index of the brain's capacity for consciousness in humans under both physiological and pathological conditions. Upon loss of consciousness, the complex pattern of causal interactions observed during wakefulness collapses into a stereotypical slow wave, suggesting that cortical bistability may play a role. Bistability is mainly expressed in the form of slow oscillations, a default pattern of activity that emerges from cortical networks in conditions of functional or anatomical disconnection. Here, we employ an in vitro model to understand the relationship between bistability and complexity in cortical circuits. We adapted the perturbational complexity index applied in humans to electrically stimulated cortical slices under different neuromodulatory conditions. At this microscale level, we demonstrate that perturbational complexity can be effectively modulated by pharmacological reduction of bistability and, albeit to a lesser extent, by enhancement of excitability, providing mechanistic insights into the macroscale measurements performed in humans.