Circuit mechanism for suppression of frontal cortical ignition during NREM sleep.

Conscious perception is greatly diminished during sleep, but the underlying circuit mechanism is poorly understood. We show that cortical ignition-a brain process shown to be associated with conscious awareness in humans and non-human primates-is strongly suppressed during non-rapid-eye-movement (NREM) sleep in mice due to reduced cholinergic modulation and rapid inhibition of cortical responses. Brain-wide functional ultrasound imaging and cell-type-specific calcium imaging combined with optogenetics showed that activity propagation from visual to frontal cortex is markedly reduced during NREM sleep due to strong inhibition of frontal pyramidal neurons. Chemogenetic activation and inactivation of basal forebrain cholinergic neurons powerfully increased and decreased visual-to-frontal activity propagation, respectively. Furthermore, although multiple subtypes of dendrite-targeting GABAergic interneurons in the frontal cortex are more active during wakefulness, soma-targeting parvalbumin-expressing interneurons are more active during sleep. Chemogenetic manipulation of parvalbumin interneurons showed that sleep/wake-dependent cortical ignition is strongly modulated by perisomatic inhibition of pyramidal neurons.

From structure to clinic: Design of a muscarinic M1 receptor agonist with potential to treatment of Alzheimer's disease.

Current therapies for Alzheimer's disease seek to correct for defective cholinergic transmission by preventing the breakdown of acetylcholine through inhibition of acetylcholinesterase, these however have limited clinical efficacy. An alternative approach is to directly activate cholinergic receptors responsible for learning and memory. The M1-muscarinic acetylcholine (M1) receptor is the target of choice but has been hampered by adverse effects. Here we aimed to design the drug properties needed for a well-tolerated M1-agonist with the potential to alleviate cognitive loss by taking a stepwise translational approach from atomic structure, cell/tissue-based assays, evaluation in preclinical species, clinical safety testing, and finally establishing activity in memory centers in humans. Through this approach, we rationally designed the optimal properties, including selectivity and partial agonism, into HTL9936-a potential candidate for the treatment of memory loss in Alzheimer's disease. More broadly, this demonstrates a strategy for targeting difficult GPCR targets from structure to clinic.

An Amygdala-Hippocampus Subnetwork that Encodes Variation in Human Mood.

Human brain networks that encode variation in mood on naturalistic timescales remain largely unexplored. Here we combine multi-site, semi-chronic, intracranial electroencephalography recordings from the human limbic system with machine learning methods to discover a brain subnetwork that correlates with variation in individual subjects' self-reported mood over days. First we defined the subnetworks that influence intrinsic brain dynamics by identifying regions that showed coordinated changes in spectral coherence. The most common subnetwork, found in 13 of 21 subjects, was characterized by ß-frequency coherence (13-30 Hz) between the amygdala and hippocampus. Increased variability of this subnetwork correlated with worsening mood across these 13 subjects. Moreover, these subjects had significantly higher trait anxiety than the 8 of 21 for whom this amygdala-hippocampus subnetwork was absent. These results demonstrate an approach for extracting network-behavior relationships from complex datasets, and they reveal a conserved subnetwork associated with a psychological trait that significantly influences intrinsic brain dynamics and encodes fluctuations in mood.

Inferring Macroscale Brain Dynamics via Fusion of Simultaneous EEG-fMRI.

Advances in the instrumentation and signal processing for simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) have enabled new ways to observe the spatiotemporal neural dynamics of the human brain. Central to the utility of EEG-fMRI neuroimaging systems are the methods for fusing the two data streams, with machine learning playing a key role. These methods can be dichotomized into those that are symmetric and asymmetric in terms of how the two modalities inform the fusion. Studies using these methods have shown that fusion yields new insights into brain function that are not possible when each modality is acquired separately. As technology improves and methods for fusion become more sophisticated, the future of EEG-fMRI for noninvasive measurement of brain dynamics includes mesoscale mapping at ultrahigh magnetic resonance fields, targeted perturbation-based neuroimaging, and using deep learning to uncover nonlinear representations that link the electrophysiological and hemodynamic measurements.

Sleep and circadian rhythmicity as entangled processes serving homeostasis.

Sleep is considered essential for the brain and body. A predominant concept is that sleep is regulated by circadian rhythmicity and sleep homeostasis, processes that were posited to be functionally and mechanistically separate. Here we review and re-evaluate this concept and its assumptions using findings from recent human and rodent studies. Alterations in genes that are central to circadian rhythmicity affect not only sleep timing but also putative markers of sleep homeostasis such as electroencephalogram slow-wave activity (SWA). Perturbations of sleep change the rhythmicity in the expression of core clock genes in tissues outside the central clock. The dynamics of recovery from sleep loss vary across sleep variables: SWA and immediate early genes show an early response, but the recovery of non-rapid eye movement and rapid eye movement sleep follows slower time courses. Changes in the expression of many genes in response to sleep perturbations outlast the effects on SWA and time spent asleep. These findings are difficult to reconcile with the notion that circadian- and sleep-wake-driven processes are mutually independent and that the dynamics of sleep homeostasis are reflected in a single variable. Further understanding of how both sleep and circadian rhythmicity contribute to the homeostasis of essential physiological variables may benefit from the assessment of multiple sleep and molecular variables over longer time scales.

Neurophysiological mechanisms of error monitoring in human and non-human primates.

Performance monitoring is an important executive function that allows us to gain insight into our own behaviour. This remarkable ability relies on the frontal cortex, and its impairment is an aspect of many psychiatric diseases. In recent years, recordings from the macaque and human medial frontal cortex have offered a detailed understanding of the neurophysiological substrate that underlies performance monitoring. Here we review the discovery of single-neuron correlates of error monitoring, a key aspect of performance monitoring, in both species. These neurons are the generators of the error-related negativity, which is a non-invasive biomarker that indexes error detection. We evaluate a set of tasks that allows the synergistic elucidation of the mechanisms of cognitive control across the two species, consider differences in brain anatomy and testing conditions across species, and describe the clinical relevance of these findings for understanding psychopathology. Last, we integrate the body of experimental facts into a theoretical framework that offers a new perspective on how error signals are computed in both species and makes novel, testable predictions.

Kinase signalling in excitatory neurons regulates sleep quantity and depth.

Progress has been made in the elucidation of sleep and wakefulness regulation at the neurocircuit level1,2. However, the intracellular signalling pathways that regulate sleep and the neuron groups in which these intracellular mechanisms work remain largely unknown. Here, using a forward genetics approach in mice, we identify histone deacetylase 4 (HDAC4) as a sleep-regulating molecule. Haploinsufficiency of Hdac4, a substrate of salt-inducible kinase 3 (SIK3)3, increased sleep. By contrast, mice that lacked SIK3 or its upstream kinase LKB1 in neurons or with a Hdac4S245A mutation that confers resistance to phosphorylation by SIK3 showed decreased sleep. These findings indicate that LKB1-SIK3-HDAC4 constitute a signalling cascade that regulates sleep and wakefulness. We also performed targeted manipulation of SIK3 and HDAC4 in specific neurons and brain regions. This showed that SIK3 signalling in excitatory neurons located in the cerebral cortex and the hypothalamus positively regulates EEG delta power during non-rapid eye movement sleep (NREMS) and NREMS amount, respectively. A subset of transcripts biased towards synaptic functions was commonly regulated in cortical glutamatergic neurons through the expression of a gain-of-function allele of Sik3 and through sleep deprivation. These findings suggest that NREMS quantity and depth are regulated by distinct groups of excitatory neurons through common intracellular signals. This study provides a basis for linking intracellular events and circuit-level mechanisms that control NREMS.

A Motor Theory of Sleep-Wake Control: Arousal-Action Circuit.

Wakefulness, rapid eye movement (REM) sleep, and non-rapid eye movement (NREM) sleep are characterized by distinct electroencephalogram (EEG), electromyogram (EMG), and autonomic profiles. The circuit mechanism coordinating these changes during sleep-wake transitions remains poorly understood. The past few years have witnessed rapid progress in the identification of REM and NREM sleep neurons, which constitute highly distributed networks spanning the forebrain, midbrain, and hindbrain. Here we propose an arousal-action circuit for sleep-wake control in which wakefulness is supported by separate arousal and action neurons, while REM and NREM sleep neurons are part of the central somatic and autonomic motor circuits. This model is well supported by the currently known sleep and wake neurons. It can also account for the EEG, EMG, and autonomic profiles of wake, REM, and NREM states and several key features of their transitions. The intimate association between the sleep and autonomic/somatic motor control circuits suggests that a primary function of sleep is to suppress motor activity.

Cognitive Motor Dissociation in Disorders of Consciousness.

BACKGROUND: Patients with brain injury who are unresponsive to commands may perform cognitive tasks that are detected on functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). This phenomenon, known as cognitive motor dissociation, has not been systematically studied in a large cohort of persons with disorders of consciousness. METHODS: In this prospective cohort study conducted at six international centers, we collected clinical, behavioral, and task-based fMRI and EEG data from a convenience sample of 353 adults with disorders of consciousness. We assessed the response to commands on task-based fMRI or EEG in participants without an observable response to verbal commands (i.e., those with a behavioral diagnosis of coma, vegetative state, or minimally conscious state-minus) and in participants with an observable response to verbal commands. The presence or absence of an observable response to commands was assessed with the use of the Coma Recovery Scale-Revised (CRS-R). RESULTS: Data from fMRI only or EEG only were available for 65% of the participants, and data from both fMRI and EEG were available for 35%. The median age of the participants was 37.9 years, the median time between brain injury and assessment with the CRS-R was 7.9 months (25% of the participants were assessed with the CRS-R within 28 days after injury), and brain trauma was an etiologic factor in 50%. We detected cognitive motor dissociation in 60 of the 241 participants (25%) without an observable response to commands, of whom 11 had been assessed with the use of fMRI only, 13 with the use of EEG only, and 36 with the use of both techniques. Cognitive motor dissociation was associated with younger age, longer time since injury, and brain trauma as an etiologic factor. In contrast, responses on task-based fMRI or EEG occurred in 43 of 112 participants (38%) with an observable response to verbal commands. CONCLUSIONS: Approximately one in four participants without an observable response to commands performed a cognitive task on fMRI or EEG as compared with one in three participants with an observable response to commands. (Funded by the James S. McDonnell Foundation and others.).

A closed-loop auditory stimulation approach selectively modulates alpha oscillations and sleep onset dynamics in humans.

Alpha oscillations play a vital role in managing the brain's resources, inhibiting neural activity as a function of their phase and amplitude, and are changed in many brain disorders. Developing minimally invasive tools to modulate alpha activity and identifying the parameters that determine its response to exogenous modulators is essential for the implementation of focussed interventions. We introduce Alpha Closed-Loop Auditory Stimulation (αCLAS) as an EEG-based method to modulate and investigate these brain rhythms in humans with specificity and selectivity, using targeted auditory stimulation. Across a series of independent experiments, we demonstrate that αCLAS alters alpha power, frequency, and connectivity in a phase, amplitude, and topography-dependent manner. Using single-pulse-αCLAS, we show that the effects of auditory stimuli on alpha oscillations can be explained within the theoretical framework of oscillator theory and a phase-reset mechanism. Finally, we demonstrate the functional relevance of our approach by showing that αCLAS can interfere with sleep onset dynamics in a phase-dependent manner.

Attention to audiovisual speech shapes neural processing through feedback-feedforward loops between different nodes of the speech network.

Selective attention-related top-down modulation plays a significant role in separating relevant speech from irrelevant background speech when vocal attributes separating concurrent speakers are small and continuously evolving. Electrophysiological studies have shown that such top-down modulation enhances neural tracking of attended speech. Yet, the specific cortical regions involved remain unclear due to the limited spatial resolution of most electrophysiological techniques. To overcome such limitations, we collected both electroencephalography (EEG) (high temporal resolution) and functional magnetic resonance imaging (fMRI) (high spatial resolution), while human participants selectively attended to speakers in audiovisual scenes containing overlapping cocktail party speech. To utilise the advantages of the respective techniques, we analysed neural tracking of speech using the EEG data and performed representational dissimilarity-based EEG-fMRI fusion. We observed that attention enhanced neural tracking and modulated EEG correlates throughout the latencies studied. Further, attention-related enhancement of neural tracking fluctuated in predictable temporal profiles. We discuss how such temporal dynamics could arise from a combination of interactions between attention and prediction as well as plastic properties of the auditory cortex. EEG-fMRI fusion revealed attention-related iterative feedforward-feedback loops between hierarchically organised nodes of the ventral auditory object related processing stream. Our findings support models where attention facilitates dynamic neural changes in the auditory cortex, ultimately aiding discrimination of relevant sounds from irrelevant ones while conserving neural resources.

Multisensory perceptual and causal inference is largely preserved in medicated post-acute individuals with schizophrenia.

Hallucinations and perceptual abnormalities in psychosis are thought to arise from imbalanced integration of prior information and sensory inputs. We combined psychophysics, Bayesian modeling, and electroencephalography (EEG) to investigate potential changes in perceptual and causal inference in response to audiovisual flash-beep sequences in medicated individuals with schizophrenia who exhibited limited psychotic symptoms. Seventeen participants with schizophrenia and 23 healthy controls reported either the number of flashes or the number of beeps of audiovisual sequences that varied in their audiovisual numeric disparity across trials. Both groups balanced sensory integration and segregation in line with Bayesian causal inference rather than resorting to simpler heuristics. Both also showed comparable weighting of prior information regarding the signals' causal structure, although the schizophrenia group slightly overweighted prior information about the number of flashes or beeps. At the neural level, both groups computed Bayesian causal inference through dynamic encoding of independent estimates of the flash and beep counts, followed by estimates that flexibly combine audiovisual inputs. Our results demonstrate that the core neurocomputational mechanisms for audiovisual perceptual and causal inference in number estimation tasks are largely preserved in our limited sample of medicated post-acute individuals with schizophrenia. Future research should explore whether these findings generalize to unmedicated patients with acute psychotic symptoms.

Impaired motor-to-sensory transformation mediates auditory hallucinations.

Distinguishing reality from hallucinations requires efficient monitoring of agency. It has been hypothesized that a copy of motor signals, termed efference copy (EC) or corollary discharge (CD), suppresses sensory responses to yield a sense of agency; impairment of the inhibitory function leads to hallucinations. However, how can the sole absence of inhibition yield positive symptoms of hallucinations? We hypothesize that selective impairments in functionally distinct signals of CD and EC during motor-to-sensory transformation cause the positive symptoms of hallucinations. In an electroencephalography (EEG) experiment with a delayed articulation paradigm in schizophrenic patients with (AVHs) and without auditory verbal hallucinations (non-AVHs), we found that preparing to speak without knowing the contents (general preparation) did not suppress auditory responses in both patient groups, suggesting the absent of inhibitory function of CD. Whereas, preparing to speak a syllable (specific preparation) enhanced the auditory responses to the prepared syllable in non-AVHs, whereas AVHs showed enhancement in responses to unprepared syllables, opposite to the observations in the normal population, suggesting that the enhancement function of EC is not precise in AVHs. A computational model with a virtual lesion of an inhibitory inter-neuron and disproportional sensitization of auditory cortices fitted the empirical data and further quantified the distinct impairments in motor-to-sensory transformation in AVHs. These results suggest that "broken" CD plus "noisy" EC causes erroneous monitoring of the imprecise generation of internal auditory representation and yields auditory hallucinations. Specific impairments in functional granularity of motor-to-sensory transformation mediate positivity symptoms of agency abnormality in mental disorders.

Dog-human vocal interactions match dogs' sensory-motor tuning.

Within species, vocal and auditory systems presumably coevolved to converge on a critical temporal acoustic structure that can be best produced and perceived. While dogs cannot produce articulated sounds, they respond to speech, raising the question as to whether this heterospecific receptive ability could be shaped by exposure to speech or remains bounded by their own sensorimotor capacity. Using acoustic analyses of dog vocalisations, we show that their main production rhythm is slower than the dominant (syllabic) speech rate, and that human-dog-directed speech falls halfway in between. Comparative exploration of neural (electroencephalography) and behavioural responses to speech reveals that comprehension in dogs relies on a slower speech rhythm tracking (delta) than humans' (theta), even though dogs are equally sensitive to speech content and prosody. Thus, the dog audio-motor tuning differs from humans', and we hypothesise that humans may adjust their speech rate to this shared temporal channel as means to improve communication efficacy.

Leader-follower dynamics during early social interactions matter for infant word learning.

We know little about the mechanisms through which leader-follower dynamics during dyadic play shape infants' language acquisition. We hypothesized that infants' decisions to visually explore a specific object signal focal increases in endogenous attention, and that when caregivers respond to these proactive behaviors by naming the object it boosts infants' word learning. To examine this, we invited caregivers and their 14-mo-old infants to play with novel objects, before testing infants' retention of the novel object-label mappings. Meanwhile, their electroencephalograms were recorded. Results showed that infants' proactive looks toward an object during play associated with greater neural signatures of endogenous attention. Furthermore, when caregivers named objects during these episodes, infants showed greater word learning, but only when caregivers also joined their focus of attention. Our findings support the idea that infants' proactive visual explorations guide their acquisition of a lexicon.

The time course of person perception from voices in the brain.

When listeners hear a voice, they rapidly form a complex first impression of who the person behind that voice might be. We characterize how these multivariate first impressions from voices emerge over time across different levels of abstraction using electroencephalography and representational similarity analysis. We find that for eight perceived physical (gender, age, and health), trait (attractiveness, dominance, and trustworthiness), and social characteristics (educatedness and professionalism), representations emerge early (~80 ms after stimulus onset), with voice acoustics contributing to those representations between ~100 ms and 400 ms. While impressions of person characteristics are highly correlated, we can find evidence for highly abstracted, independent representations of individual person characteristics. These abstracted representationse merge gradually over time. That is, representations of physical characteristics (age, gender) arise early (from ~120 ms), while representations of some trait and social characteristics emerge later (~360 ms onward). The findings align with recent theoretical models and shed light on the computations underpinning person perception from voices.

The time course of feature-selective attention inside and outside the focus of spatial attention.

Research on attentional selection of stimulus features has yielded seemingly contradictory results. On the one hand, many experiments in humans and animals have observed a "global" facilitation of attended features across the entire visual field, even when spatial attention is focused on a single location. On the other hand, several event-related potential studies in humans reported that attended features are enhanced at the attended location only. The present experiment demonstrates that these conflicting results can be explained by differences in the timing of attentional allocation inside and outside the spatial focus of attention. Participants attended to fields of either red or blue randomly moving dots on either the left or right side of fixation with the task of detecting brief coherent motion targets. Recordings of steady-state visual evoked potentials elicited by the flickering stimuli allowed concurrent measurement of the time course of feature-selective attention in visual cortex on both the attended and the unattended sides. The onset of feature-selective attentional modulation on the attended side occurred around 150 ms earlier than on the unattended side. This finding that feature-selective attention is not spatially global from the outset but extends to unattended locations after a temporal delay resolves previous contradictions between studies finding global versus hierarchical selection of features and provides insight into the fundamental relationship between feature-based and location-based (spatial) attention mechanisms.

Information structure in Makhuwa: Electrophysiological evidence for a universal processing account.

There is evidence from both behavior and brain activity that the way information is structured, through the use of focus, can up-regulate processing of focused constituents, likely to give prominence to the relevant aspects of the input. This is hypothesized to be universal, regardless of the different ways in which languages encode focus. In order to test this universalist hypothesis, we need to go beyond the more familiar linguistic strategies for marking focus, such as by means of intonation or specific syntactic structures (e.g., it-clefts). Therefore, in this study, we examine Makhuwa-Enahara, a Bantu language spoken in northern Mozambique, which uniquely marks focus through verbal conjugation. The participants were presented with sentences that consisted of either a semantically anomalous constituent or a semantically nonanomalous constituent. Moreover, focus on this particular constituent could be either present or absent. We observed a consistent pattern: Focused information generated a more negative N400 response than the same information in nonfocus position. This demonstrates that regardless of how focus is marked, its consequence seems to result in an upregulation of processing of information that is in focus.

Interoceptive signals shape the earliest markers and neural pathway to awareness at the visual threshold.

Variations in interoceptive signals from the baroreceptors (BRs) across the cardiac and respiratory cycle can modulate cortical excitability and so affect awareness. It remains debated at what stages of processing they affect awareness-related event-related potentials (ERPs) in different sensory modalities. We investigated the influence of the cardiac (systole/diastole) and the respiratory (inhalation/exhalation) phase on awareness-related ERPs. Subjects discriminated visual threshold stimuli while their electroencephalogram, electrocardiogram, and respiration were simultaneously recorded. We compared ERPs and their intracranial generators for stimuli classified correctly with and without awareness as a function of the cardiac and respiratory phase. Cyclic variations of interoceptive signals from the BRs modulated both the earliest electrophysiological markers and the trajectory of brain activity when subjects became aware of the stimuli: an early sensory component (P1) was the earliest marker of awareness for low (diastole/inhalation) and a perceptual component (visual awareness negativity) for high (systole/exhalation) BR activity, indicating that BR signals interfere with the sensory processing of the visual input. Likewise, activity spread from the primary visceral cortex (posterior insula) to posterior parietal cortices during high and from associative interoceptive centers (anterior insula) to the prefrontal cortex during low BR activity. Consciousness is thereby resolved in cognitive/associative regions when BR is low and in perceptual centers when it is high. Our results suggest that cyclic fluctuations of BR signaling affect both the earliest markers of awareness and the brain processes underlying conscious awareness.

Cortical miR-709 links glutamatergic signaling to NREM sleep EEG slow waves in an activity-dependent manner.

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression that have been implicated in a plethora of neuronal processes. Nevertheless, their role in regulating brain activity in the context of sleep has so far received little attention. To test their involvement, we deleted mature miRNAs in post-mitotic neurons at two developmental ages, i.e., in early adulthood using conditional Dicer knockout (cKO) mice and in adult mice using an inducible conditional Dicer cKO (icKO) line. In both models, electroencephalographic (EEG) activity was affected and the response to sleep deprivation (SD) altered; while the rapid-eye-movement sleep (REMS) rebound was compromised in both, the increase in EEG delta (1 to 4 Hz) power during non-REMS (NREMS) was smaller in cKO mice and larger in icKO mice compared to controls. We subsequently investigated the effects of SD on the forebrain miRNA transcriptome and found that the expression of 48 miRNAs was affected, and in particular that of the activity-dependent miR-709. In vivo inhibition of miR-709 in the brain increased EEG power during NREMS in the slow-delta (0.75 to 1.75 Hz) range, particularly after periods of prolonged wakefulness. Transcriptome analysis of primary cortical neurons in vitro revealed that miR-709 regulates genes involved in glutamatergic neurotransmission. A subset of these genes was also affected in the cortices of sleep-deprived, miR-709-inhibited mice. Our data implicate miRNAs in the regulation of EEG activity and indicate that miR-709 links neuronal activity during wakefulness to brain synchrony during sleep through the regulation of glutamatergic signaling.