Physiologically driven avian vocal synthesizer

Journal ArticleIn this work, we build an electronic syrinx, i.e., a programmable electronic device capable of integrating biomechanical model equations for the avian vocal organ in order to synthesize song. This vocal prosthesis is controlled by the bird's neural instructions to respiratory and the syringeal motor systems, thus opening great potential for studying motor control and its modification by sensory feedback mechanisms. Furthermore, a well-functioning subject-controlled vocal prosthesis can lay the foundation for similar devices in humans and thus provide directly health-related data and procedures

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 timelocked tomovement 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 tomodel the neural decision of “when” to move in a task where there is no specific temporal cue, but only a general imperative to produce amovement 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 tomovement 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

Electromagnetic Brain Stimulation in Patients With Disorders of Consciousness

Severe brain injury is a common cause of coma. In some cases, despite vigilance improvement, disorders of consciousness (DoC) persist. Several states of impaired consciousness have been defined, according to whether the patient exhibits only reflexive behaviors as in the vegetative state/unresponsive wakefulness syndrome (VS/UWS) or purposeful behaviors distinct from reflexes as in the minimally conscious state (MCS). Recently, this clinical distinction has been enriched by electrophysiological and neuroimaging data resulting from a better understanding of the physiopathology of DoC. However, therapeutic options, especially pharmacological ones, remain very limited. In this context, electroceuticals, a new category of therapeutic agents which act by targeting the neural circuits with electromagnetic stimulations, started to develop in the field of DoC. We performed a systematic review of the studies evaluating therapeutics relying on the direct or indirect electro-magnetic stimulation of the brain in DoC patients. Current evidence seems to support the efficacy of deep brain stimulation (DBS) and non-invasive brain stimulation (NIBS) on consciousness in some of these patients. However, while the latter is non-invasive and well tolerated, the former is associated with potential major side effects. We propose that all chronic DoC patients should be given the possibility to benefit from NIBS, and that transcranial direct current stimulation (tDCS) should be preferred over repetitive transcranial magnetic stimulation (rTMS), based on the literature and its simple use. Surgical techniques less invasive than DBS, such as vagus nerve stimulation (VNS) might represent a good compromise between efficacy and invasiveness but still need to be further investigated

Unifying turbulent dynamics framework distinguishes different brain states.

peer reviewedSignificant advances have been made by identifying the levels of synchrony of the underlying dynamics of a given brain state. This research has demonstrated that non-conscious dynamics tend to be more synchronous than in conscious states, which are more asynchronous. Here we go beyond this dichotomy to demonstrate that different brain states are underpinned by dissociable spatiotemporal dynamics. We investigated human neuroimaging data from different brain states (resting state, meditation, deep sleep and disorders of consciousness after coma). The model-free approach was based on Kuramoto's turbulence framework using coupled oscillators. This was extended by a measure of the information cascade across spatial scales. Complementarily, the model-based approach used exhaustive in silico perturbations of whole-brain models fitted to these measures. This allowed studying of the information encoding capabilities in given brain states. Overall, this framework demonstrates that elements from turbulence theory provide excellent tools for describing and differentiating between brain states

Predicting the loss of responsiveness when falling asleep in humans

International audienceFalling asleep is a dynamical process that is poorly defined. The period preceding sleep, characterized by the progressive alteration of behavioral responses to the environment, which may last several minutes, has no electrophysiological definition, and is embedded in the first stage of sleep (N1). We aimed at better characterizing this drowsiness period looking for neurophysiological predictors of responsiveness using electro and magneto-encephalography. Healthy participants were recorded when falling asleep, while they were presented with continuous auditory stimulations and asked to respond to deviant sounds. We analysed brain responses to sounds and markers of ongoing activity, such as information and connectivity measures, in relation to rapid fluctuations of brain rhythms observed at sleep onset and participants’ capabilities to respond. Results reveal a drowsiness period distinct from wakefulness and sleep, from alpha rhythms to the first sleep spindles, characterized by diverse and transient brain states that come on and off at the scale of a few seconds and closely reflects, mainly through neural processes in alpha and theta bands, decreasing probabilities to be responsive to external stimuli. Results also show that the global P300 was only present in responsive trials, regardless of vigilance states. A better consideration of the drowsiness period through a formalized classification and its specific brain markers such as described here should lead to significant advances in vigilance assessment in the future, in medicine and ecological environments

Predicting the loss of responsiveness when falling asleep in humans.

Falling asleep is a dynamical process that is poorly defined. The period preceding sleep, characterized by the progressive alteration of behavioral responses to the environment, which may last several minutes, has no electrophysiological definition, and is embedded in the first stage of sleep (N1). We aimed at better characterizing this drowsiness period looking for neurophysiological predictors of responsiveness using electro and magneto-encephalography. Healthy participants were recorded when falling asleep, while they were presented with continuous auditory stimulations and asked to respond to deviant sounds. We analysed brain responses to sounds and markers of ongoing activity, such as information and connectivity measures, in relation to rapid fluctuations of brain rhythms observed at sleep onset and participants' capabilities to respond. Results reveal a drowsiness period distinct from wakefulness and sleep, from alpha rhythms to the first sleep spindles, characterized by diverse and transient brain states that come on and off at the scale of a few seconds and closely reflects, mainly through neural processes in alpha and theta bands, decreasing probabilities to be responsive to external stimuli. Results also show that the global P300 was only present in responsive trials, regardless of vigilance states. A better consideration of the drowsiness period through a formalized classification and its specific brain markers such as described here should lead to significant advances in vigilance assessment in the future, in medicine and ecological environments

Sensory target detection at local and global timescales reveals a hierarchy of supramodal dynamics in the human cortex

To ensure survival in a dynamic environment, the human neocortex monitors input streams from different sensory organs for important sensory events. Which principles govern whether different senses share common or modality-specific brain networks for sensory target detection? We examined whether complex targets evoke sustained supramodal activity while simple targets rely on modality-specific networks with short-lived supramodal contributions. In a series of hierarchical multisensory target detection studies (n = 77, of either sex) using EEG, we applied a temporal cross-decoding approach to dissociate supramodal and modality-specific cortical dynamics elicited by rule-based global and feature-based local sensory deviations within and between the visual, somatosensory, and auditory modality. Our data show that each sense implements a cortical hierarchy orchestrating supramodal target detection responses, which operate at local and global timescales in successive processing stages. Across different sensory modalities, simple feature-based sensory deviations presented in temporal vicinity to a monotonous input stream triggered a mismatch negativity-like local signal which decayed quickly and early, whereas complex rule-based targets tracked across time evoked a P3b-like global neural response which generalized across a late time window. Converging results from temporal cross-modality decoding analyses across different datasets, we reveal that global neural responses are sustained in a supramodal higher-order network, whereas local neural responses canonically thought to rely on modality-specific regions evolve into short-lived supramodal activity. Together, our findings demonstrate that cortical organization largely follows a gradient in which short-lived modality-specific as well as supramodal processes dominate local responses, whereas higher-order processes encode temporally extended abstract supramodal information fed forward from modality-specific cortices

Why the P3b is still a plausible correlate of conscious access? A commentary on Silverstein et al., 2015

International audienceWe read with interest the article by Silverstein and colleagues (Silverstein, Snodgrass, Shevrin, & Kushwaha, 2015) who questioned the putative specificity of the P3b event-related potentials (ERP) component as a neural signature of conscious access to a visual representation. Prior to this new study, numerous empirical reports revealed that a brain response peaking ∼300 msec after stimulus onset and maximally distributed over parietal electrodes – the so called P3b – is closely related to subjective visibility (Sergent et al., 2005 and Vogel et al., 1998). These experimental findings provided the bases to develop neuronal and computational theories of consciousness such as the global workspace model (Dehaene and Changeux, 2011, Dehaene et al., 2006 and Dehaene and Naccache, 2001). Silverstein and colleagues used a ‘passive attentive’ version of a masked visual odd-ball paradigm while recording scalp ERPs. In each trial, subjects were presented with either the masked word ‘LEFT’ (in 80% or 20% of trials) or the masked word ‘RIGHT’ (in 20% or 80% of trials). Word frequency was balanced across subjects, who were asked to carefully attend to the masked sequence. Not only were they instructed that this sequence contained a masked word, but also that: “however implausible it might seem, our prior data suggested that the stimuli would nonetheless be unconsciously perceived and produce brain wave effects – but only if they maintained their attention”. When contrasting ERPs elicited by rare and frequent masked words, Silverstein and colleagues identified a P3b ERP component followed by a late, and sustained, slow wave (LSW). Given that participants subjectively reported the absence of conscious perception of words, and that they performed at chance-level in a stimulus detection task performed after the main experiment, Silverstein and colleagues concluded that a P3b can be observed during unconscious perception. If valid, their interpretation would then simply invalidate the P3b as a possible candidate neural signature of conscious access.This original and provocative study, however, raises both methodological and conceptual concerns which need to be addressed before one can adopt Silverstein and colleagues' interpretation

Cortical activity is more stable when sensory stimuli are consciously perceived

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