Jacobo D. Sitt

An accumulator model for spontaneous neural activity prior to self-initiated movement

A gradual buildup of neuronal activity known as the “readiness potential” reliably precedes voluntary self-initiated movements, in the average time locked to movement onset. This buildup is presumed to reflect the final stages of planning and preparation for movement. Here we present a different interpretation of the premovement buildup. We used a leaky stochastic accumulator to model the neural decision of “when” to move in a task where there is no specific temporal cue, but only a general imperative to produce a movement after an unspecified delay on the order of several seconds. According to our model, when the imperative to produce a movement is weak, the precise moment at which the decision threshold is crossed leading to movement is largely determined by spontaneous subthreshold fluctuations in neuronal activity. Time locking to movement onset ensures that these fluctuations appear in the average as a gradual exponential-looking increase in neuronal activity. Our model accounts for the behavioral and electroencephalography data recorded from human subjects performing the task and also makes a specific prediction that we confirmed in a second electroencephalography experiment: Fast responses to temporally unpredictable interruptions should be preceded by a slow negative-going voltage deflection beginning well before the interruption itself, even when the subject was not preparing to move at that particular moment.

Disruption of hierarchical predictive coding during sleep

Significance Sleeping disrupts the conscious awareness of external sounds. We investigated the stage of processing at which this disruption occurs. In the awake brain, when a regular sequence of sounds is presented, a hierarchy of brain areas uses the available regularities to predict forthcoming sounds and to respond with a series of “prediction error” signals when these predictions are violated. Using simultaneous recordings of electroencephalography and magnetoencephalography signals, we discovered that both short-term and long-term brain responses to auditory prediction errors are disrupted during non-rapid eye movement and rapid eye movement sleep; however, the brain still exhibits detectable auditory responses and a capacity to habituate to frequently repeated sounds. Thus, sleep appears to selectively affect the brain’s prediction and error detection systems. When presented with an auditory sequence, the brain acts as a predictive-coding device that extracts regularities in the transition probabilities between sounds and detects unexpected deviations from these regularities. Does such prediction require conscious vigilance, or does it continue to unfold automatically in the sleeping brain? The mismatch negativity and P300 components of the auditory event-related potential, reflecting two steps of auditory novelty detection, have been inconsistently observed in the various sleep stages. To clarify whether these steps remain during sleep, we recorded simultaneous electroencephalographic and magnetoencephalographic signals during wakefulness and during sleep in normal subjects listening to a hierarchical auditory paradigm including short-term (local) and long-term (global) regularities. The global response, reflected in the P300, vanished during sleep, in line with the hypothesis that it is a correlate of high-level conscious error detection. The local mismatch response remained across all sleep stages (N1, N2, and REM sleep), but with an incomplete structure; compared with wakefulness, a specific peak reflecting prediction error vanished during sleep. Those results indicate that sleep leaves initial auditory processing and passive sensory response adaptation intact, but specifically disrupts both short-term and long-term auditory predictive coding.

Cortical activity is more stable when sensory stimuli are consciously perceived

Significance Recently, a reduction in the variability of neural activity across trials has been proposed as a general property of sensory perception. However, in order for this increased reliability in the neuronal response to be relevant for perception it must be present at the single-trial level. Here we show that the within-trial stability of the activity evoked by a threshold-level visual stimulus is a reliable and specific indicator of whether or not the stimulus was reported as “seen.” This within-trial difference in stability coincides in time with a difference in variability across trials. We also show that the same neural stability can be used to discriminate the conscious state of brain-injured patients. These findings validate the relevance of transient neural stability for conscious perception. According to recent evidence, stimulus-tuned neurons in the cerebral cortex exhibit reduced variability in firing rate across trials, after the onset of a stimulus. However, in order for a reduction in variability to be directly relevant to perception and behavior, it must be realized within trial—the pattern of activity must be relatively stable. Stability is characteristic of decision states in recurrent attractor networks, and its possible relevance to conscious perception has been suggested by theorists. However, it is difficult to measure on the within-trial time scales and broadly distributed spatial scales relevant to perception. We recorded simultaneous magneto- and electroencephalography (MEG and EEG) data while subjects observed threshold-level visual stimuli. Pattern-similarity analyses applied to the data from MEG gradiometers uncovered a pronounced decrease in variability across trials after stimulus onset, consistent with previous single-unit data. This was followed by a significant divergence in variability depending upon subjective report (seen/unseen), with seen trials exhibiting less variability. Applying the same analysis across time, within trial, we found that the latter effect coincided in time with a difference in the stability of the pattern of activity. Stability alone could be used to classify data from individual trials as “seen” or “unseen.” The same metric applied to EEG data from patients with disorders of consciousness exposed to auditory stimuli diverged parametrically according to clinically diagnosed level of consciousness. Differences in signal strength could not account for these results. Conscious perception may involve the transient stabilization of distributed cortical networks, corresponding to a global brain-scale decision.

Neural detection of complex sound sequences or of statistical regularities in the absence of consciousness

Sir, We read with interest the article by Tzovara et al. (2015), recently published in Brain . In this study the authors adapted a paradigm we previously designed (Bekinschtein et al. , 2009) to probe the EEG of comatose patients in response to two types of violations of auditory regularities. Unfortunately, several important problems mitigate the reliability of their conclusions. In the local-global paradigm, local auditory irregularities correspond to a change of sound within a trial, whereas global irregularities correspond to a change of sound sequence across trials. The authors showed with a decoding algorithm a significant difference in EEG responses to global violations in 10 of 24 comatose patients. Observing such a global effect in unconscious subjects challenges our previous conclusion that this global effect can only be observed in conscious and attentive subjects (Bekinschtein et al. , 2009; Wacongne et al. , 2012; El Karoui et al. , 2014) and systematically disappears in inattentive subjects (Bekinschtein et al. , 2009; King et al. , 2013), sleeping subjects (Strauss et al. , 2015), and clinically unconscious patients in vegetative state (Faugeras et al. , 2011, 2012). Converging findings from multiple functional brain imaging tools [high-density EEG, magnetoencephalography (MEG), intracranial stereoelectroencephalography (SEEG), functional MRI] demonstrated that the global effect is characterized by a late (>300 ms after violation onset) and sustained brain response (King et al. , 2014) typical of conscious access (Dehaene and Naccache 2001; Dehaene et al. , 2011). In our data, the only two patients in a vegetative state showing a late global effect recovered clinical signs of minimally conscious state within the next …

Bedside quantitative electroencephalography improves assessment of consciousness in comatose subarachnoid hemorrhage patients.

Accurate behavioral assessments of consciousness carry tremendous significance in guiding management, but are extremely challenging in acutely brain‐injured patients. We evaluated whether electroencephalography (EEG) and multimodality monitoring parameters may facilitate assessment of consciousness in patients with subarachnoid hemorrhage.

Reply: Replicability and impact of statistics in the detection of neural responses of consciousness

Sir, We read with interest the letter by Gabriel and colleagues (2016) addressing the major issue of replicability when probing conscious processing in non-communicating patients. This question—as well as the choice of the optimal statistical methodology—concerns the whole field of functional brain imaging in cognitive neuroscience (Kriegeskorte et al. , 2009), but its importance obviously culminates in single-subject analyses of non-communicating patients (see for instance the recent debate in Cruse et al. , 2011, 2013; Goldfine et al. , 2012). Gabriel et al. reacted to a recent discussion (Naccache et al. , 2015; Tzovara et al. , 2015 a , b ) following a report by Tzovara et al. (2015 a ), who adapted our auditory ‘local-global’ bedside EEG test (Bekinschtein et al. , 2009) to test comatose patients. Briefly, in the local-global paradigm two levels of regularities are manipulated: local auditory irregularities correspond to a change of sound within a trial, whereas global irregularities correspond to a change of sound sequence across trials. When analysing data according to the local irregularities, one can typically extract a mismatch negativity response observable even in unconscious states. In sharp contrast, when analysing event-related potentials (ERPs) to violations of global irregularities, we previously showed that a late global effect was present only in conscious or minimally conscious patients (Bekinschtein et al. , 2009; Faugeras et al. , 2011, 2012). Two problems emerged from the study of Tzovara et al. (2015 a ), first, this ERP global effect was found positive in the vast majority of conscious controls we tested at two distinct sites using high-density EEG: 18/18 (100%) in Paris, France (with 256 electrodes), and 7 to 10/10 (70 to 100%) with the monaural and binaural versions of the task, respectively in Cambridge, UK …

Ripples of consciousness

Casali et al. recently showed that the complexity of the electrophysiological brain response to a transcranial magnetic stimulation pulse distinguishes conscious from unconscious humans in a variety of conditions. In addition to its theoretical implications, this novel method paves the way to a quantitative assessment of the states of consciousness.

Probing consciousness in a sensory-disconnected paralyzed patient

ABSTRACT Background: Diagnosis of consciousness can be very challenging in some clinical situations such as severe sensory-motor impairments. Case study: We report the case study of a patient who presented a total “locked-in syndrome” associated with and a multi-sensory deafferentation (visual, auditory and tactile modalities) following a protuberantial infarction. Result: In spite of this severe and extreme disconnection from the external world, we could detect reliable evidence of consciousness using a multivariate analysis of his high-density resting state electroencephalogram. This EEG-based diagnosis was eventually confirmed by the clinical evolution of the patient. Conclusion: This approach illustrates the potential importance of functional brain-imaging data to improve diagnosis of consciousness and of cognitive abilities in critical situations in which the behavioral channel is compromised such as deafferented locked-in syndrome.

Brain-heart interactions reveal consciousness in non-communicating patients

We here aimed at characterizing heart–brain interactions in patients with disorders of consciousness. We tested how this information impacts data‐driven classification between unresponsive and minimally conscious patients.

Bedside quantitative EEG improves assessment of consciousness in comatose subarachnoid hemorrhage patients

Accurate behavioral assessments of consciousness carry tremendous significance in guiding management, but are extremely challenging in acutely brain‐injured patients. We evaluated whether electroencephalography (EEG) and multimodality monitoring parameters may facilitate assessment of consciousness in patients with subarachnoid hemorrhage.