Control of spatiotemporal coherence of a thalamic oscillation by corticothalamic feedback

Auditory evoked delta brushes involve stimulus-specific cortical networks in preterm infants

During the third trimester of gestation in humans, the auditory cortex displays spontaneous and auditory-evoked EEG patterns of intermittent local oscillatory activity nested in delta waves - delta brushes (DBs). To test whether the spatiotemporal dynamics of evoked DBs depends on stimulus type, we studied auditory evoked responses (AERs) to voice and "click" using 32-electrode EEG in 30 healthy neonates aged 30 to 38 post-menstrual weeks. Both stimuli elicited two peaks at approximately 250 ms and 600 ms, the second corresponding to the first principal components of the AER and the evoked DB. The DB showed stimulus-specific topography, temporal posterior and mid-temporal for "click", and mid-temporal and pre-central inferior for voice, and contained theta to gamma oscillations more widespread for the "click"response. Gamma oscillations increased with age. AERs predominated on the right but shifted toward the left with age for voice response. Auditory evoked DBs may therefore underlie specific auditory processing during fetal development.

Infant sleep EEG features at 4 months as biomarkers of neurodevelopment at 18 months

BACKGROUND

Sleep parameters evolve in parallel with neurodevelopment. Sleep participates in synaptic homeostasis and memory consolidation and infant sleep parameters correlate with later aspects of early childhood cognition.

METHODS

Typically developing, term-born infants had a diurnal sleep-EEG at 4 months and Griffiths III developmental assessment at 18 months. EEG analysis included sleep macrostructure (i.e. durations of total sleep and sleep stages, and latencies to sleep and REM), sleep spindle features, and quantitative EEG features (qEEG): interhemispheric connectivity and spectral power. We assessed the correlations between these EEG features and Griffiths III quotients.

RESULTS

Sleep recordings from 92 infants were analyzed. Sleep latency was positively associated with the Griffiths III Foundations of Learning subscale and N3 sleep duration was positively correlated with the Personal-Social-Emotional subscale. Sleep spindle synchrony was negatively associated with Eye and Hand Coordination, Personal-Social-Emotional, Gross Motor, and General Development quotients. Sleep spindle duration was negatively associated with the Personal-Social-Emotional and Gross Motor subscales. In some sleep states, delta 1 and 2 EEG spectral power and interhemispheric coherence measures were correlated with subscale quotients.

CONCLUSION

Certain sleep features in the EEG of 4-month-old infants are associated with neurodevelopment at 18 months and may be useful early biomarkers of neurodevelopment.

IMPACT

This study shows that the EEG during infant sleep may provide insights into later neurodevelopmental outcomes. We have examined novel EEG sleep spindle features and shown that spindle duration and synchrony may help predict neurodevelopmental outcomes. Sleep macrostructure elements such as latency to sleep, N3 duration, and qEEG features such as interhemispheric coherence and spectral power measures at 4 months may be useful for the assessment of future neurodevelopmental outcomes. Due to exceptional neuroplasticity in infancy, EEG biomarkers of neurodevelopment may support early and targeted intervention to optimize outcomes.

Dynamical properties and mechanisms of metastability: A perspective in neuroscience

Metastability, characterized by a variability of regimes in time, is a ubiquitous type of neural dynamics. It has been formulated in many different ways in the neuroscience literature, however, which may cause some confusion. In this Perspective, we discuss metastability from the point of view of dynamical systems theory. We extract from the literature a very simple but general definition through the concept of metastable regimes as long-lived but transient epochs of activity with unique dynamical properties. This definition serves as an umbrella term that encompasses formulations from other works, and readily connects to concepts from dynamical systems theory. This allows us to examine general dynamical properties of metastable regimes, propose in a didactic manner several dynamics-based mechanisms that generate them, and discuss a theoretical tool to characterize them quantitatively. This Perspective leads to insights that help to address issues debated in the literature and also suggests pathways for future research.

Role of short-term plasticity and slow temporal dynamics in enhancing time series prediction with a brain-inspired recurrent neural network

Typical reservoir networks are based on random connectivity patterns that differ from brain circuits in two important ways. First, traditional reservoir networks lack synaptic plasticity among recurrent units, whereas cortical networks exhibit plasticity across all neuronal types and cortical layers. Second, reservoir networks utilize random Gaussian connectivity, while cortical networks feature a heavy-tailed distribution of synaptic strengths. It is unclear what are the computational advantages of these features for predicting complex time series. In this study, we integrated short-term plasticity (STP) and lognormal connectivity into a novel recurrent neural network (RNN) framework. The model exhibited rich patterns of population activity characterized by slow coordinated fluctuations. Using graph spectral decomposition, we show that weighted networks with lognormal connectivity and STP yield higher complexity than several graph types. When tested on various tasks involving the prediction of complex time series data, the RNN model outperformed a baseline model with random connectivity as well as several other network architectures. Overall, our results underscore the potential of incorporating brain-inspired features such as STP and heavy-tailed connectivity to enhance the robustness and performance of artificial neural networks in complex data prediction and signal processing tasks.

Complementary Organization of Mouse Driver and Modulator Cortico-thalamo-cortical Circuits

Corticocortical (CC) projections in the visual system facilitate hierarchical processing of sensory information. In addition to direct CC connections, indirect cortico-thalamo-cortical (CTC) pathways through the pulvinar nucleus of the thalamus can relay sensory signals and mediate cortical interactions according to behavioral demands. While the pulvinar connects extensively to the entire visual cortex, it is unknown whether transthalamic pathways link all cortical areas or whether they follow systematic organizational rules. Because mouse pulvinar neurons projecting to different areas are spatially intermingled, their input/output relationships have been difficult to characterize using traditional anatomical methods. To determine the organization of CTC circuits, we mapped the higher visual areas (HVAs) of male and female mice with intrinsic signal imaging and targeted five pulvinar→HVA pathways for projection-specific rabies tracing. We aligned postmortem cortical tissue to in vivo maps for precise quantification of the areas and cell types projecting to each pulvinar→HVA population. Layer 5 corticothalamic (L5CT) "driver" inputs to the pulvinar originate predominantly from primary visual cortex (V1), consistent with the CC hierarchy. L5CT inputs from lateral HVAs specifically avoid driving reciprocal connections, consistent with the "no-strong-loops" hypothesis. Conversely, layer 6 corticothalamic (L6CT) "modulator" inputs are distributed across areas and are biased toward reciprocal connections. Unlike previous studies in primates, we find that every HVA receives disynaptic input from the superior colliculus. CTC circuits in the pulvinar thus depend on both target HVA and input cell type, such that driving and modulating higher-order pathways follow complementary connection rules similar to those governing first-order CT circuits.

Does fragmented sleep mediate the relationship between deficits in sleep spindles and memory consolidation in schizophrenia?

Study Objectives

Sleep spindles, defining electroencephalographic oscillations of nonrapid eye movement (NREM) stage 2 sleep (N2), mediate sleep-dependent memory consolidation (SDMC). Spindles are also thought to protect sleep continuity by suppressing thalamocortical sensory relay. Schizophrenia is characterized by spindle deficits and a correlated reduction of SDMC. We investigated whether this relationship is mediated by sleep fragmentation.

Methods

We detected spindles (12-15 Hz) during N2 at central electrodes in overnight polysomnography records from 56 participants with chronic schizophrenia and 59 healthy controls. Our primary measures of sleep continuity were the sleep fragmentation index and, in a subset of the data, visually scored arousals. SDMC was measured as overnight improvement on the finger-tapping motor sequence task.

Results

Participants with schizophrenia showed reductions of both spindle density (#/min) and SDMC in the context of normal sleep continuity and architecture. Spindle density predicted SDMC in both groups. In contrast, neither increased sleep fragmentation nor arousals predicted lower spindle density or worse SDMC in either group.

Conclusions

Our findings fail to support the hypothesis that sleep fragmentation accounts for spindle deficits, impaired SDMC, or their relationship in individuals with chronic schizophrenia. Instead, our findings are consistent with the hypothesis that spindle deficits directly impair memory consolidation in schizophrenia. Since sleep continuity and architecture are intact in this population, research aimed at developing interventions should instead focus on understanding dysfunction within the thalamocortical-hippocampal circuitry that both generates spindles and synchronizes them with other NREM oscillations to mediate SDMC.

Thalamic spindles and Up states coordinate cortical and hippocampal co-ripples in humans

In the neocortex, ~90 Hz ripples couple to ~12 Hz sleep spindles on the ~1 Hz Down-to-Up state transition during non-rapid eye movement sleep. This conjunction of sleep waves is critical for the consolidation of memories into long-term storage. The widespread co-occurrences of ripples ("co-ripples") may integrate information across the neocortex and hippocampus to facilitate consolidation. While the thalamus synchronizes spindles and Up states in the cortex for memory, it is not known whether it may also organize co-ripples. Using human intracranial recordings during NREM sleep, we investigated whether cortico-cortical co-ripples and hippocampo-cortical co-ripples are either: (1) driven by directly projected thalamic ripples; or (2) coordinated by propagating thalamic spindles or Up states. We found ripples in the anterior and posterior thalamus, with similar characteristics as hippocampal and cortical ripples, including having a center frequency of ~90 Hz and coupling to local spindles on the Down-to-Up state transition. However, thalamic ripples rarely co-occur or phase-lock with cortical or hippocampal ripples. By contrast, spindles and Up states that propagate from the thalamus strongly coordinate co-ripples in the cortex and hippocampus. Thus, thalamo-cortical spindles and Up states, rather than thalamic ripples, may provide input facilitating spatially distributed co-rippling that integrates information for memory consolidation during sleep in humans.

Temporal dynamics of negative emotional memory reprocessing during sleep

Memory reprocessing during sleep is a well-established phenomenon in numerous studies. However, it is unclear whether the intensity of memory reprocessing is consistently maintained throughout the night or exhibits dynamic changes. This study investigates the temporal dynamics of negative emotional memory reprocessing during sleep, with a specific focus on slow oscillation (SO)-spindle coupling and its role in memory reprocessing. In the first experiment (N = 40, mean age = 22.5 years), we detected the negative emotional memory reprocessing strength in each sleep cycle, we found that the 2nd sleep cycle after negative emotional memory learning constitute the most sensitive window for memory reprocessing, furthermore, SO-spindle coupling signals in this window plays a role in stabilizing negative emotional memory. To verify the role of SO-spindle coupling in negative emotional memory reprocessing, we utilized transcranial alternating current stimulation (tACS) to disrupt SO-spindle coupling during the 2nd sleep cycle (N = 21, mean age = 19.3 years). Notably, the outcomes of the tACS intervention demonstrated a significant reduction in the recognition of negative emotional memories. These findings offer new insights into the mechanisms that regulate emotional memory consolidation during sleep and may have implications for addressing psychiatric disorders associated with pathological emotional memory.

Sensory gating and gaining in sleep: the balance between the protection of sleep and the safeness of life (a review)

Sleep is a brain state characterised by a low vigilance level and diminished consciousness. Reaction to and processing of external stimuli is attenuated in sleep. During sleep, the reticular thalamic nucleus reduces the flow of sensory activity to the cerebral cortex through inhibition of the thalamus. This sensory gating process facilitates sleep. After reaching the afferent layers of primary cortex, the reduced sensory flow is adjusted, gained, and processed within various cortical layers before being transferred by the corticofugal system back to appropriate subdivisions of the thalamus as feedback. Thalamic subdivisions then dispatch this sensory information to related areas of the cerebral cortex, where it is (sub)consciously perceived. When necessary, a sleeping individual can be awakened by a wake-up call, either by stimuli indicating danger, or by personally meaningful stimuli. It is safe for a sleeping individual that it can be aroused when necessary. Evidently, there are two processes by which the brain adjusts the response to sensory stimuli before entering (sub)consciousness. Firstly 'sensory gating', a process favourable to the maintenance of sleep by reducing the sensory input to the brain through the reticular thalamic nucleus and secondly 'sensory gaining', a process implying that the gained preserved sensory input is continuously analysed by the corticofugal system to detect dangerous and relevant environmental elements, indispensable for safeness and well-being of the sleeper.

Spindle chirp and other sleep oscillatory features in young children with autism

OBJECTIVES

To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism.

METHODS

Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD).

RESULTS

Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient.

CONCLUSIONS

For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.

Motor Control of Distinct Layer 6 Corticothalamic Feedback Circuits

Layer 6 corticothalamic (L6 CT) neurons provide massive input to the thalamus, and these feedback connections enable the cortex to influence its own sensory input by modulating thalamic excitability. However, the functional role(s) feedback serves during sensory processing is unclear. One hypothesis is that CT feedback is under the control of extrasensory signals originating from higher-order cortical areas, yet we know nothing about the mechanisms of such control. It is also unclear whether such regulation is specific to CT neurons with distinct thalamic connectivity. Using mice (either sex) combined with in vitro electrophysiology techniques, optogenetics, and retrograde labeling, we describe studies of vibrissal primary motor cortex (vM1) influences on different CT neurons in the vibrissal primary somatosensory cortex (vS1) with distinct intrathalamic axonal projections. We found that vM1 inputs are highly selective, evoking stronger postsynaptic responses in CT neurons projecting to the dual ventral posterior medial nucleus (VPm) and posterior medial nucleus (POm) located in lower L6a than VPm-only-projecting CT cells in upper L6a. A targeted analysis of the specific cells and synapses involved revealed that the greater responsiveness of Dual CT neurons was due to their distinctive intrinsic membrane properties and synaptic mechanisms. These data demonstrate that vS1 has at least two discrete L6 CT subcircuits distinguished by their thalamic projection patterns, intrinsic physiology, and functional connectivity with vM1. Our results also provide insights into how a distinct CT subcircuit may serve specialized roles specific to contextual modulation of tactile-related sensory signals in the somatosensory thalamus during active vibrissa movements.

Motor Control of Distinct Layer 6 Corticothalamic Feedback Circuits

Layer 6 corticothalamic (L6 CT) neurons provide massive input to the thalamus, and these feedback connections enable the cortex to influence its own sensory input by modulating thalamic excitability. However, the functional role(s) feedback serves during sensory processing is unclear. One hypothesis is that CT feedback is under the control of extra-sensory signals originating from higher-order cortical areas, yet we know nothing about the mechanisms of such control. It is also unclear whether such regulation is specific to CT neurons with distinct thalamic connectivity. Using mice (either sex) combined with in vitro electrophysiology techniques, optogenetics, and retrograde labeling, we describe studies of vibrissal primary motor cortex (vM1) influences on different CT neurons in the vibrissal primary somatosensory cortex (vS1) with distinct intrathalamic axonal projections. We found that vM1 inputs are highly selective, evoking stronger postsynaptic responses in Dual ventral posterior medial nucleus (VPm) and posterior medial nucleus (POm) projecting CT neurons located in lower L6a than VPm-only projecting CT cells in upper L6a. A targeted analysis of the specific cells and synapses involved revealed that the greater responsiveness of Dual CT neurons was due to their distinctive intrinsic membrane properties and synaptic mechanisms. These data demonstrate that vS1 has at least two discrete L6 CT subcircuits distinguished by their thalamic projection patterns, intrinsic physiology, and functional connectivity with vM1. Our results also provide insights into how a distinct CT subcircuit may serve specialized roles specific to contextual modulation of tactile-related sensory signals in the somatosensory thalamus during active vibrissa movements.

Characterization of the neural circuitry of the auditory thalamic reticular nucleus and its potential role in salicylate-induced tinnitus

Introduction

Subjective tinnitus, the perception of sound without an external acoustic source, is often subsequent to noise-induced hearing loss or ototoxic medications. The condition is believed to result from neuroplastic alterations in the auditory centers, characterized by heightened spontaneous neural activities and increased synchrony due to an imbalance between excitation and inhibition. However, the role of the thalamic reticular nucleus (TRN), a structure composed exclusively of GABAergic neurons involved in thalamocortical oscillations, in the pathogenesis of tinnitus remains largely unexplored.

Methods

We induced tinnitus in mice using sodium salicylate and assessed tinnitus-like behaviors using the Gap Pre-Pulse Inhibition of the Acoustic Startle (GPIAS) paradigm. We utilized combined viral tracing techniques to identify the neural circuitry involved and employed immunofluorescence and confocal imaging to determine cell types and activated neurons.

Results

Salicylate-treated mice exhibited tinnitus-like behaviors. Our tracing clearly delineated the inputs and outputs of the auditory-specific TRN. We discovered that chemogenetic activation of the auditory TRN significantly reduced the salicylate-evoked rise in c-Fos expression in the auditory cortex.

Discussion

This finding posits the TRN as a potential modulatory target for tinnitus treatment. Furthermore, the mapped sensory inputs to the auditory TRN suggest possibilities for employing optogenetic or sensory stimulations to manipulate thalamocortical activities. The precise mapping of the auditory TRN-mediated neural pathways offers a promising avenue for designing targeted interventions to alleviate tinnitus symptoms.

Primate neocortex performs balanced sensory amplification

The sensory cortex amplifies relevant features of external stimuli. This sensitivity and selectivity arise through the transformation of inputs by cortical circuitry. We characterize the circuit mechanisms and dynamics of cortical amplification by making large-scale simultaneous measurements of single cells in awake primates and testing computational models. By comparing network activity in both driven and spontaneous states with models, we identify the circuit as operating in a regime of non-normal balanced amplification. Incoming inputs are strongly but transiently amplified by strong recurrent feedback from the disruption of excitatory-inhibitory balance in the network. Strong inhibition rapidly quenches responses, thereby permitting the tracking of time-varying stimuli.

Alpha and SSVEP power outperform gamma power in capturing attentional modulation in human EEG

Attention typically reduces power in the alpha (8-12 Hz) band and increases power in gamma (>30 Hz) band in brain signals, as reported in macaque local field potential (LFP) and human electro/magneto-encephalogram (EEG/MEG) studies. In addition, EEG studies often use flickering stimuli that produce a specific measure called steady-state-visually-evoked-potential (SSVEP), whose power also increases with attention. However, effectiveness of these neural measures in capturing attentional modulation is unknown since stimuli and task paradigms vary widely across studies. In a recent macaque study, attentional modulation was more salient in the gamma band of the LFP, compared to alpha or SSVEP. To compare this with human EEG, we designed an orientation change detection task where we presented both static and counterphasing stimuli of matched difficulty levels to 26 subjects and compared attentional modulation of various measures under similar conditions. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, non-foveal stimuli produced weak gamma despite various stimulus optimizations and showed negligible attentional modulation although full-screen gratings showed robust gamma activity. Our results are useful for brain-machine-interfacing studies where suitable features are used for decoding attention, and also provide clues about spatial scales of neural mechanisms underlying attention.

Spindle Chirp and other Sleep Oscillatory Features in Young Children with Autism

Objectives

To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism.

Methods

Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD).

Results

Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient.

Conclusions

For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.

Electrophysiological findings in migraine may reflect abnormal synaptic plasticity mechanisms: A narrative review

BACKGROUND

The cyclical brain disorder of sensory processing accompanying migraine phases lacks an explanatory unified theory.

METHODS

We searched Pubmed for non-invasive neurophysiological studies on migraine and related conditions using transcranial magnetic stimulation, electroencephalography, visual and somatosensory evoked potentials. We summarized the literature, reviewed methods, and proposed a unified theory for the pathophysiology of electrophysiological abnormalities underlying migraine recurrence.

RESULTS

All electrophysiological modalities have determined specific changes in brain dynamics across the different phases of the migraine cycle. Transcranial magnetic stimulation studies show unbalanced recruitment of inhibitory and excitatory circuits, more consistently in aura, which ultimately results in a substantially distorted response to neuromodulation protocols. Electroencephalography investigations highlight a steady pattern of reduced alpha and increased slow rhythms, largely located in posterior brain regions, which tends to normalize closer to the attacks. Finally, non-painful evoked potentials suggest dysfunctions in habituation mechanisms of sensory cortices that revert during ictal phases.

CONCLUSION

Electrophysiology shows dynamic and recurrent functional alterations within the brainstem-thalamus-cortex loop varies continuously and recurrently in migraineurs. Given the central role of these structures in the selection, elaboration, and learning of sensory information, these functional alterations suggest chronic, probably genetically determined dysfunctions of the synaptic short- and long-term learning mechanisms.

Sleep Disturbance and Severe Hydrocephalus in a Normally Behaving Wistar Rat With Traumatic Brain Injury

We report on a case study of a Wistar rat that was investigated in detail because it exhibited no N3 sleep in electroencephalography (EEG) after lateral fluid-percussion injury (FPI)-induced traumatic brain injury (TBI). The rat (#112) belonged to a cohort of 28 adult Wistar rats exposed to lateral FPI. Rats were monitored by continuous video EEG for 30 days to follow-up on the evolution of sleep disturbances. The beam walking test was used to measure post-TBI functional recovery. Severity of the cortical lesion area, total brain volume, and cortical volume were measured from histological brain sections. Rat #112 had a normal body and skull appearance. Its baseline body weight did not differ from that of the rest of the cohort. At baseline, rat #112 crossed the beam in 6.3 sec (score range for the rest of the cohort, 4.7-44.3) and showed no evident slipping of the paws, scoring a 5.3 (score range for the rest of cohort, 4.3-6.0). On day 30 post-TBI, however, rat #112 was the only rat with a score of 0 on the beam. Histological analysis at 30 days post-TBI revealed a small 0.6-mm² post-TBI lesion in the somatosensory cortex (lesion size range for the rest of the cohort, 1.2-10.9). The brain volume of rat #112 was 2-fold larger than the mean volume of the rest of the cohort (1592 vs. 758 mm³), the ventricles were remarkably enlarged, and the layered cerebral cortex was very thin. Analysis of the sleep EEG revealed that rat #112 had rapid eye movement sleep and wakefulness, but no N3 sleep, during the 72-h EEG epoch analyzed. This case report demonstrates that brain abnormalities presumably unrelated to the impact-induced cortical lesion, such as presumed pre-existing hydrocephalus, may worsen TBI-induced behavioral and electrographical outcome measures and complicate the assessment of the cause of the abnormalities.

Functional MRI reveals brain-wide actions of thalamically-initiated oscillatory activities on associative memory consolidation

As a key oscillatory activity in the brain, thalamic spindle activities are long believed to support memory consolidation. However, their propagation characteristics and causal actions at systems level remain unclear. Using functional MRI (fMRI) and electrophysiology recordings in male rats, we found that optogenetically-evoked somatosensory thalamic spindle-like activities targeted numerous sensorimotor (cortex, thalamus, brainstem and basal ganglia) and non-sensorimotor limbic regions (cortex, amygdala, and hippocampus) in a stimulation frequency- and length-dependent manner. Thalamic stimulation at slow spindle frequency (8 Hz) and long spindle length (3 s) evoked the most robust brain-wide cross-modal activities. Behaviorally, evoking these global cross-modal activities during memory consolidation improved visual-somatosensory associative memory performance. More importantly, parallel visual fMRI experiments uncovered response potentiation in brain-wide sensorimotor and limbic integrative regions, especially superior colliculus, periaqueductal gray, and insular, retrosplenial and frontal cortices. Our study directly reveals that thalamic spindle activities propagate in a spatiotemporally specific manner and that they consolidate associative memory by strengthening multi-target memory representation.

Propofol disrupts alpha dynamics in functionally distinct thalamocortical networks during loss of consciousness

During propofol-induced general anesthesia, alpha rhythms measured using electroencephalography undergo a striking shift from posterior to anterior, termed anteriorization, where the ubiquitous waking alpha is lost and a frontal alpha emerges. The functional significance of alpha anteriorization and the precise brain regions contributing to the phenomenon are a mystery. While posterior alpha is thought to be generated by thalamocortical circuits connecting nuclei of the sensory thalamus with their cortical partners, the thalamic origins of the propofol-induced alpha remain poorly understood. Here, we used human intracranial recordings to identify regions in sensory cortices where propofol attenuates a coherent alpha network, distinct from those in the frontal cortex where it amplifies coherent alpha and beta activities. We then performed diffusion tractography between these identified regions and individual thalamic nuclei to show that the opposing dynamics of anteriorization occur within two distinct thalamocortical networks. We found that propofol disrupted a posterior alpha network structurally connected with nuclei in the sensory and sensory associational regions of the thalamus. At the same time, propofol induced a coherent alpha oscillation within prefrontal cortical areas that were connected with thalamic nuclei involved in cognition, such as the mediodorsal nucleus. The cortical and thalamic anatomy involved, as well as their known functional roles, suggests multiple means by which propofol dismantles sensory and cognitive processes to achieve loss of consciousness.

The Feature of Sleep Spindle Deficits in Patients With Schizophrenia With and Without Auditory Verbal Hallucinations

BACKGROUND

Previous sleep electroencephalography studies have detected abnormalities in sleep architecture and sleep spindle deficits in schizophrenia (SCZ), but the consistency of these results was not robust, which might be due to the small sample size and the influence of clinical factors such as the various medication therapies and symptom heterogeneity. This study aimed to regard auditory verbal hallucinations (AVHs) as a pointcut to downscale the heterogeneity of SCZ and explore whether some sleep architecture and spindle parameters were more severely impaired in SCZ patients with AVHs compared with those without AVHs.

METHODS

A total of 90 SCZ patients with AVHs, 92 SCZ patients without AVHs, and 91 healthy control subjects were recruited, and parameters of sleep architecture and spindle activities were compared between groups. The correlation between significant sleep parameters and clinical indicators was analyzed.

RESULTS

Deficits of sleep spindle activities at prefrontal electrodes and intrahemispheric spindle coherence were observed in both AVH and non-AVH groups, several of which were more serious in the AVH group. In addition, deficits of spindle activities at central and occipital electrodes and interhemispheric spindle coherence mainly manifested accompanying AVH symptoms, most of which were retained in the medication-naive first-episode patients, and were associated with Auditory Hallucination Rating Scale scores.

CONCLUSIONS

Our results suggest that the underlying mechanism of spindle deficits might be different between SCZ patients with and without AVHs. In the future, the sleep feature of SCZ patients with different symptoms and the influence of clinical factors, such as medication therapy, should be further illustrated.

John EK, Potesta CV, Gallagher MJ, Macdonald RL, Zhou C. Sleep slow-wave oscillations trigger seizures in a genetic epilepsy model of Dravet syndrome

Sleep is the preferential period when epileptic spike-wave discharges appear in human epileptic patients, including genetic epileptic seizures such as Dravet syndrome with multiple mutations including SCN1A mutation and GABAA receptor γ2 subunit Gabrg2Q390X mutation in patients, which presents more severe epileptic symptoms in female patients than male patients. However, the seizure onset mechanism during sleep still remains unknown. Our previous work has shown that the sleep-like state-dependent homeostatic synaptic potentiation can trigger epileptic spike-wave discharges in one transgenic heterozygous Gabrg2+/Q390X knock-in mouse model.1 Here, using this heterozygous knock-in mouse model, we hypothesized that slow-wave oscillations themselves in vivo could trigger epileptic seizures. We found that epileptic spike-wave discharges in heterozygous Gabrg2+/Q390X knock-in mice exhibited preferential incidence during non-rapid eye movement sleep period, accompanied by motor immobility/facial myoclonus/vibrissal twitching and more frequent spike-wave discharge incidence appeared in female heterozygous knock-in mice than male heterozygous knock-in mice. Optogenetically induced slow-wave oscillations in vivo significantly increased epileptic spike-wave discharge incidence in heterozygous Gabrg2+/Q390X knock-in mice with longer duration of non-rapid eye movement sleep or quiet-wakeful states. Furthermore, suppression of slow-wave oscillation-related homeostatic synaptic potentiation by 4-(diethylamino)-benzaldehyde injection (i.p.) greatly attenuated spike-wave discharge incidence in heterozygous knock-in mice, suggesting that slow-wave oscillations in vivo did trigger seizure activity in heterozygous knock-in mice. Meanwhile, sleep spindle generation in wild-type littermates and heterozygous Gabrg2+/Q390X knock-in mice involved the slow-wave oscillation-related homeostatic synaptic potentiation that also contributed to epileptic spike-wave discharge generation in heterozygous Gabrg2+/Q390X knock-in mice. In addition, EEG spectral power of delta frequency (0.1-4 Hz) during non-rapid eye movement sleep was significantly larger in female heterozygous Gabrg2+/Q390X knock-in mice than that in male heterozygous Gabrg2+/Q390X knock-in mice, which likely contributes to the gender difference in seizure incidence during non-rapid eye movement sleep/quiet-wake states of human patients. Overall, all these results indicate that slow-wave oscillations in vivo trigger the seizure onset in heterozygous Gabrg2+/Q390X knock-in mice, preferentially during non-rapid eye movement sleep period and likely generate the sex difference in seizure incidence between male and female heterozygous Gabrg2+/Q390X knock-in mice.

The space-time profiles of sleep spindles and their coordination with slow oscillations on the electrode manifold

Sleep spindles are important for sleep quality and cognitive functions, with their coordination with slow oscillations (SOs) potentially organizing cross-region reactivation of memory traces. Here, we describe the organization of spindles on the electrode manifold and their relation to SOs. We analyzed the sleep night EEG of 34 subjects and detected spindles and SOs separately at each electrode. We compared spindle properties (frequency, duration, and amplitude) in slow wave sleep (SWS) and Stage 2 sleep (S2); and in spindles that coordinate with SOs or are uncoupled. We identified different topographical spindle types using clustering analysis that grouped together spindles co-detected across electrodes within a short delay (±300 ms). We then analyzed the properties of spindles of each type, and coordination to SOs. We found that SWS spindles are shorter than S2 spindles, and spindles at frontal electrodes have higher frequencies in S2 compared to SWS. Furthermore, S2 spindles closely following an SO (about 10% of all spindles) show faster frequency, shorter duration, and larger amplitude than uncoupled ones. Clustering identified Global, Local, Posterior, Frontal-Right and Left spindle types. At centro-parietal locations, Posterior spindles show faster frequencies compared to other types. Furthermore, the infrequent SO-spindle complexes are preferentially recruiting Global SO waves coupled with fast Posterior spindles. Our results suggest a non-uniform participation of spindles to complexes, especially evident in S2. This suggests the possibility that different mechanisms could initiate an SO-spindle complex compared to SOs and spindles separately. This has implications for understanding the role of SOs-spindle complexes in memory reactivation.

Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load

Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of sleep rhythms? To answer this question, we adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves in high-noise settings for analysis of neural recordings in sleep. We then studied sleep spindles in non-human primate electrocorticography (ECoG), human electroencephalogram (EEG), and clinical intracranial electroencephalogram (iEEG) recordings in the human. Within each recording type, we find widespread spindles occur much more frequently than previously reported. We then analyzed the spatiotemporal patterns of these large-scale, multi-area spindles and, in the EEG recordings, how spindle patterns change following a visual memory task. Our results reveal a potential role for widespread, multi-area spindles in consolidation of memories in networks widely distributed across primate cortex.

The brain processes memories as we sleep, generating rhythms of electrical activity called ‘sleep spindles’. Sleep spindles were long thought to be a state where the entire brain was fully synchronized by this rhythm. This was based on EEG recordings, short for electroencephalogram, a technique that uses electrodes on the scalp to measure electrical activity in the outermost layer of the brain, the cortex. But more recent intracranial recordings of people undergoing brain surgery have challenged this idea and suggested that sleep spindles may not be a state of global brain synchronization, but rather localised to specific areas.

Mofrad et al. sought to clarify the extent to which spindles co-occur at multiple sites in the brain, which could shed light on how networks of neurons coordinate memory storage during sleep. To analyse highly variable brain wave recordings, Mofrad et al. adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves. The resulting algorithm, designed to more sensitively detect spindles amongst other brain activity, was then applied to a range of sleep recordings from humans and macaque monkeys.

The analyses revealed that widespread and complex patterns of spindle rhythms, spanning multiple areas in the cortex of the brain, actually appear much more frequently than previously thought. This finding was consistent across all the recordings analysed, even recordings under the skull, which provide the clearest window into brain circuits. Further analyses found that these multi-area spindles occurred more often in sleep after people had completed tasks that required holding many visual scenes in memory, as opposed to control conditions with fewer visual scenes.

In summary, Mofrad et al. show that neuroscientists had previously not appreciated the complex and dynamic patterns in this sleep rhythm. These patterns in sleep spindles may be able to adapt based on the demands needed for memory storage, and this will be the subject of future work. Moreover, the findings support the idea that sleep spindles help coordinate the consolidation of memories in brain circuits that stretch across the cortex. Understanding this mechanism may provide insights into how memory falters in aging and sleep-related diseases, such as Alzheimer’s disease. Lastly, the algorithm developed by Mofrad et al. stands to be a useful tool for analysing other rhythmic waveforms in noisy recordings.

Dyscoordination of non-rapid eye movement sleep oscillations in autism spectrum disorder

Study Objectives

Converging evidence from neuroimaging, sleep, and genetic studies suggest that dysregulation of thalamocortical interactions mediated by the thalamic reticular nucleus (TRN) contribute to autism spectrum disorder (ASD). Sleep spindles assay TRN function, and their coordination with cortical slow oscillations (SOs) indexes thalamocortical communication. These oscillations mediate memory consolidation during sleep. In the present study, we comprehensively characterized spindles and their coordination with SOs in relation to memory and age in children with ASD.

Methods

Nineteen children and adolescents with ASD, without intellectual disability, and 18 typically developing (TD) peers, aged 9–17, completed a home polysomnography study with testing on a spatial memory task before and after sleep. Spindles, SOs, and their coordination were characterized during stages 2 (N2) and 3 (N3) non-rapid eye movement sleep.

Results

ASD participants showed disrupted SO-spindle coordination during N2 sleep. Spindles peaked later in SO upstates and their timing was less consistent. They also showed a spindle density (#/min) deficit during N3 sleep. Both groups showed significant sleep-dependent memory consolidation, but their relations with spindle density differed. While TD participants showed the expected positive correlations, ASD participants showed the opposite.

Conclusions

The disrupted SO-spindle coordination and spindle deficit provide further evidence of abnormal thalamocortical interactions and TRN dysfunction in ASD. The inverse relations of spindle density with memory suggest a different function for spindles in ASD than TD. We propose that abnormal sleep oscillations reflect genetically mediated disruptions of TRN-dependent thalamocortical circuit development that contribute to the manifestations of ASD and are potentially treatable.

EEG sleep macrostructure and sleep spindles in early infancy

Study Objectives

Sleep features in infancy are potential biomarkers for brain maturation but poorly characterized. We describe normative values for sleep macrostructure and sleep spindles at 4–5 months of age.

Methods

Healthy term infants were recruited at birth and had daytime sleep electroencephalograms (EEGs) at 4–5 months. Sleep staging was performed and five features were analyzed. Sleep spindles were annotated and seven quantitative features were extracted. Features were analyzed across sex, recording time (am/pm), infant age, and from first to second sleep cycles.

Results

We analyzed sleep recordings from 91 infants, 41% females. Median (interquartile range [IQR]) macrostructure results: sleep duration 49.0 (37.8–72.0) min (n = 77); first sleep cycle duration 42.8 (37.0–51.4) min; rapid eye movement (REM) percentage 17.4 (9.5–27.7)% (n = 68); latency to REM 36.0 (30.5–41.1) min (n = 66). First cycle median (IQR) values for spindle features: number 241.0 (193.0–286.5), density 6.6 (5.7–8.0) spindles/min (n = 77); mean frequency 13.0 (12.8–13.3) Hz, mean duration 2.9 (2.6–3.6) s, spectral power 7.8 (4.7–11.4) µV², brain symmetry index 0.20 (0.16–0.29), synchrony 59.5 (53.2–63.8)% (n = 91). In males, spindle spectral power (µV²) was 24.5% lower (p = .032) and brain symmetry index 24.2% higher than females (p = .011) when controlling for gestational and postnatal age and timing of the nap. We found no other significant associations between studied sleep features and sex, recording time (am/pm), or age. Spectral power decreased (p < .001) on the second cycle.

Conclusion

This normative data may be useful for comparison with future studies of sleep dysfunction and atypical neurodevelopment in infancy.

Clinical Trial Registration: BABY SMART (Study of Massage Therapy, Sleep And neurodevelopMenT) (BabySMART)

URL: https://clinicaltrials.gov/ct2/show/results/NCT03381027?view=results.

ClinicalTrials.gov Identifier: NCT03381027

Brain Structural and Functional Connectivity: A Review of Combined Works of Diffusion Magnetic Resonance Imaging and Electro-Encephalography

Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.

The Engram's Dark Horse: How Interneurons Regulate State-Dependent Memory Processing and Plasticity

Brain states such as arousal and sleep play critical roles in memory encoding, storage, and recall. Recent studies have highlighted the role of engram neurons-populations of neurons activated during learning-in subsequent memory consolidation and recall. These engram populations are generally assumed to be glutamatergic, and the vast majority of data regarding the function of engram neurons have focused on glutamatergic pyramidal or granule cell populations in either the hippocampus, amygdala, or neocortex. Recent data suggest that sleep and wake states differentially regulate the activity and temporal dynamics of engram neurons. Two potential mechanisms for this regulation are either via direct regulation of glutamatergic engram neuron excitability and firing, or via state-dependent effects on interneuron populations-which in turn modulate the activity of glutamatergic engram neurons. Here, we will discuss recent findings related to the roles of interneurons in state-regulated memory processes and synaptic plasticity, and the potential therapeutic implications of understanding these mechanisms.

Corticothalamic Pathways From Layer 5: Emerging Roles in Computation and Pathology

Large portions of the thalamus receive strong driving input from cortical layer 5 (L5) neurons but the role of this important pathway in cortical and thalamic computations is not well understood. L5-recipient "higher-order" thalamic regions participate in cortico-thalamo-cortical (CTC) circuits that are increasingly recognized to be (1) anatomically and functionally distinct from better-studied "first-order" CTC networks, and (2) integral to cortical activity related to learning and perception. Additionally, studies are beginning to elucidate the clinical relevance of these networks, as dysfunction across these pathways have been implicated in several pathological states. In this review, we highlight recent advances in understanding L5 CTC networks across sensory modalities and brain regions, particularly studies leveraging cell-type-specific tools that allow precise experimental access to L5 CTC circuits. We aim to provide a focused and accessible summary of the anatomical, physiological, and computational properties of L5-originating CTC networks, and outline their underappreciated contribution in pathology. We particularly seek to connect single-neuron and synaptic properties to network (dys)function and emerging theories of cortical computation, and highlight information processing in L5 CTC networks as a promising focus for computational studies.

Differential effect of sleep deprivation on place cell representations, sleep architecture, and memory in young and old mice

Poor sleep quality is associated with age-related cognitive decline, and whether reversal of these alterations is possible is unknown. In this study, we report how sleep deprivation (SD) affects hippocampal representations, sleep patterns, and memory in young and old mice. After training in a hippocampus-dependent object-place recognition (OPR) task, control animals sleep ad libitum, although experimental animals undergo 5 h of SD, followed by recovery sleep. Young controls and old SD mice exhibit successful OPR memory, whereas young SD and old control mice are impaired. Successful performance is associated with two cellular phenotypes: (1) "context" cells, which remain stable throughout training and testing, and (2) "object configuration" cells, which remap when objects are introduced to the context and during testing. Additionally, effective memory correlates with spindle counts during non-rapid eye movement (NREM)/rapid eye movement (REM) sigma transitions. These results suggest SD may serve to ameliorate age-related memory deficits and allow hippocampal representations to adapt to changing environments.

Role of corpus callosum in sleep spindle synchronization and coupling with slow waves

Sleep spindles of non-REM sleep are transient, waxing-and-waning 10–16 Hz EEG oscillations, whose cortical synchronization depends on the engagement of thalamo-cortical loops. However, previous studies in animal models lacking the corpus callosum due to agenesis or total callosotomy and in humans with agenesis of the corpus callosum suggested that cortico-cortical connections may also have a relevant role in cortical (inter-hemispheric) spindle synchronization. Yet, most of these works did not provide direct quantitative analyses to support their observations. By studying a rare sample of callosotomized, split-brain patients, we recently demonstrated that the total resection of the corpus callosum is associated with a significant reduction in the inter-hemispheric propagation of non-REM slow waves. Interestingly, sleep spindles are often temporally and spatially grouped around slow waves (0.5–4 Hz), and this coordination is thought to have an important role in sleep-dependent learning and memory consolidation. Given these premises, here we set out to investigate whether total callosotomy may affect the generation and spreading of sleep spindles, as well as their coupling with sleep slow waves. To this aim, we analysed overnight high-density EEG recordings (256 electrodes) collected in five patients who underwent total callosotomy due to drug-resistant epilepsy (age 40–53, two females), three non-callosotomized neurological patients (age 44–66, two females), and in a sample of 24 healthy adult control subjects (age 20–47, 13 females). Individual sleep spindles were automatically detected using a validated algorithm and their properties and topographic distributions were computed. All analyses were performed with and without a regression-based adjustment accounting for inter-subject age differences. The comparison between callosotomized patients and healthy subjects did not reveal systematic variations in spindle density, amplitude or frequency. However, callosotomized patients were characterized by a reduced spindle duration, which could represent the result of a faster desynchronization of spindle activity across cortical areas of the two hemispheres. In contrast with our previous findings regarding sleep slow waves, we failed to detect in callosotomized patients any clear, systematic change in the inter-hemispheric synchronization of sleep spindles. In line with this, callosotomized patients were characterized by a reduced extension of the spatial association between temporally coupled spindles and slow waves. Our findings are consistent with a dependence of spindles on thalamo-cortical rather than cortico-cortical connections in humans, but also revealed that, despite their temporal association, slow waves and spindles are independently regulated in terms of topographic expression.

The effects of eszopiclone on sleep spindles and memory consolidation in schizophrenia: a randomized clinical trial

Sleep spindles, defining oscillations of stage 2 non-rapid eye movement sleep (N2), mediate memory consolidation. Schizophrenia is characterized by reduced spindle activity that correlates with impaired sleep-dependent memory consolidation. In a small, randomized, placebo-controlled pilot study of schizophrenia, eszopiclone (Lunesta®), a nonbenzodiazepine sedative hypnotic, increased N2 spindle density (number/minute) but did not significantly improve memory. This larger double-blind crossover study that included healthy controls investigated whether eszopiclone could both increase N2 spindle density and improve memory. Twenty-six medicated schizophrenia outpatients and 29 healthy controls were randomly assigned to have a placebo or eszopiclone (3 mg) sleep visit first. Each visit involved two consecutive nights of high density polysomnography with training on the Motor Sequence Task (MST) on the second night and testing the following morning. Patients showed a widespread reduction of spindle density and, in both groups, eszopiclone increased spindle density but failed to enhance sleep-dependent procedural memory consolidation. Follow-up analyses revealed that eszopiclone also affected cortical slow oscillations: it decreased their amplitude, increased their duration, and rendered their phase locking with spindles more variable. Regardless of group or visit, the density of coupled spindle-slow oscillation events predicted memory consolidation significantly better than spindle density alone, suggesting that they are a better biomarker of memory consolidation. In conclusion, sleep oscillations are promising targets for improving memory consolidation in schizophrenia, but enhancing spindles is not enough. Effective therapies also need to preserve or enhance cortical slow oscillations and their coordination with thalamic spindles, an interregional dialog that is necessary for sleep-dependent memory consolidation.

Gender differences in adolescent sleep neurophysiology: a high-density sleep EEG study

During adolescence, differences between males and females in physiology, behavior and risk for psychopathology are accentuated. The goal of the current study was to examine gender differences in sleep neurophysiology using high-density sleep EEG in early adolescence. We examined gender differences in sleep EEG power and coherence across frequency bands for both NREM and REM sleep in a sample of 61 adolescents (31 girls and 30 boys; mean age = 12.48; SD = 1.34). In addition, sleep spindles were individually detected and characterized. Compared to boys, girls had significantly greater spindle activity, as reflected in higher NREM sigma power, spindle amplitude, spindle frequency and spindle density over widespread regions. Furthermore, power in higher frequency bands (16.2–44 Hz) was larger in girls than boys in a state independent manner. Oscillatory activity across frequency bands and sleep states was generally more coherent in females as compared to males, suggesting greater connectivity in females. An exception to this finding was the alpha band during NREM and REM sleep, where coherence was higher (NREM) or not different (REM) in boys compared to girls. Sleep spindles are generated through thalamocortical circuits, and thus, the greater spindle activity across regions in females may represent a stronger thalamocortical circuit in adolescent females as compared to males. Moreover, greater global connectivity in females may reflect functional brain differences with implications for cognition and mental health. Given the pronounced gender differences, our study highlights the importance of taking gender into account when designing and interpreting studies of sleep neurophysiology.

Impaired State-Dependent Potentiation of GABAergic Synaptic Currents Triggers Seizures in a Genetic Generalized Epilepsy Model

Epileptic activity in genetic generalized epilepsy (GGE) patients preferentially appears during sleep and its mechanism remains unknown. Here, we found that sleep-like slow-wave oscillations (0.5 Hz SWOs) potentiated excitatory and inhibitory synaptic currents in layer V cortical pyramidal neurons from wild-type (wt) mouse brain slices. In contrast, SWOs potentiated excitatory, but not inhibitory, currents in cortical neurons from a heterozygous (het) knock-in (KI) Gabrg2+Q/390X model of Dravet epilepsy syndrome. This created an imbalance between evoked excitatory and inhibitory currents to effectively prompt neuronal action potential firings. Similarly, physiologically similar up-/down-state induction (present during slow-wave sleep) in cortical neurons also potentiated excitatory synaptic currents within brain slices from wt and het KI mice. Moreover, this state-dependent potentiation of excitatory synaptic currents entailed some signaling pathways of homeostatic synaptic plasticity. Consequently, in het KI mice, in vivo SWO induction (using optogenetic methods) triggered generalized epileptic spike-wave discharges (SWDs), being accompanied by sudden immobility, facial myoclonus, and vibrissa twitching. In contrast, in wt littermates, SWO induction did not cause epileptic SWDs and motor behaviors. To our knowledge, this is the first mechanism to explain why epileptic SWDs preferentially happen during non rapid eye-movement sleep and quiet-wakefulness in human GGE patients.

Glial Modulation of Electrical Rhythms in a Neuroglial Network Model of Epilepsy

OBJECTIVE

An important EEG-based biomarker for epilepsy is the phase-amplitude cross-frequency coupling (PAC) of electrical rhythms; however, the underlying pathways of these pathologic markers are not always clear. Since glial cells have been shown to play an active role in neuroglial networks, it is likely that some of these PAC markers are modulated via glial effects.

METHODS

We developed a 4-unit hybrid model of a neuroglial network, consisting of 16 sub-units, that combines a mechanistic representation of neurons with an oscillator-based Cognitive Rhythm Generator (CRG) representation of glial cells-astrocytes and microglia. The model output was compared with recorded generalized tonic-clonic patient data, both in terms of PAC features, and state classification using an unsupervised hidden Markov model (HMM).

RESULTS

The neuroglial model output showed PAC features similar to those observed in epileptic seizures. These generated PAC features were able to accurately identify spontaneous epileptiform discharges (SEDs) as seizure-like states, as well as a postictal-like state following the long-duration SED, when applied to the HMM machine learning algorithm trained on patient data. The evolution profile of the maximal PAC during the SED compared well with patient data, showing similar association with the duration of the postictal state.

CONCLUSION

The hybrid neuroglial network model was able to generate PAC features similar to those observed in ictal and postictal epileptic states, which has been used for state classification and postictal state duration prediction.

SIGNIFICANCE

Since PAC biomarkers are important for epilepsy research and postictal state duration has been linked with risk of sudden unexplained death in epilepsy, this model suggests glial synaptic effects as potential targets for further analysis and treatment.

Sleep spindle activity in childhood onset schizophrenia: Diminished and associated with clinical symptoms

Neuroimaging studies of childhood onset schizophrenia (COS), a rare yet severe form of schizophrenia with an onset before the age of 13 years, have shown continuity with adult onset schizophrenia. Previous research in adult patients has shown reduced sleep spindle activity, transient oscillations in the sleep electroencephalogram (EEG) generated through thalamocortical loops. The current study examines sleep spindle activity in patients with COS. Seventeen children and adolescents with COS (16 years ±6.6) underwent overnight sleep EEG recordings. Sleep spindle activity was compared between patients with COS and age and gender matched controls and correlated with clinical symptom severity. We found pronounced deficits in sleep spindle amplitude, duration, density and frequency in patients with COS (effect size = 0.61 to 1.96; dependent on metric and EEG derivation). Non-rapid eye movement (NREM) sleep EEG power and coherence in the sigma band (11-16 Hz) corresponding to spindle activity were also markedly diminished in patients with COS as compared to controls. Furthermore, the degree of deficit in power and coherence of spindles was strongly associated with clinician rated hallucinations and positive symptoms over widespread cortical regions. Our finding of diminished spindle activity and its association with hallucinations likely reflect dysfunction of the thalamocortical circuits in children and adolescents with COS. Given the relative ease of sleep EEG recordings in vulnerable populations, this study highlights the potential of such recordings to characterize brain function in schizophrenia.

Facilitating the propagation of spiking activity in feedforward networks by including feedback

Transient oscillations in network activity upon sensory stimulation have been reported in different sensory areas of the brain. These evoked oscillations are the generic response of networks of excitatory and inhibitory neurons (EI-networks) to a transient external input. Recently, it has been shown that this resonance property of EI-networks can be exploited for communication in modular neuronal networks by enabling the transmission of sequences of synchronous spike volleys (’pulse packets’), despite the sparse and weak connectivity between the modules. The condition for successful transmission is that the pulse packet (PP) intervals match the period of the modules’ resonance frequency. Hence, the mechanism was termed communication through resonance (CTR). This mechanism has three severe constraints, though. First, it needs periodic trains of PPs, whereas single PPs fail to propagate. Second, the inter-PP interval needs to match the network resonance. Third, transmission is very slow, because in each module, the network resonance needs to build up over multiple oscillation cycles. Here, we show that, by adding appropriate feedback connections to the network, the CTR mechanism can be improved and the aforementioned constraints relaxed. Specifically, we show that adding feedback connections between two upstream modules, called the resonance pair, in an otherwise feedforward modular network can support successful propagation of a single PP throughout the entire network. The key condition for successful transmission is that the sum of the forward and backward delays in the resonance pair matches the resonance frequency of the network modules. The transmission is much faster, by more than a factor of two, than in the original CTR mechanism. Moreover, it distinctly lowers the threshold for successful communication by synchronous spiking in modular networks of weakly coupled networks. Thus, our results suggest a new functional role of bidirectional connectivity for the communication in cortical area networks.

The cortex is organized as a modular system, with the modules (cortical areas) communicating via weak long-range connections. It has been suggested that the intrinsic resonance properties of population activities in these areas might contribute to enabling successful communication. A module’s intrinsic resonance appears in the damped oscillatory response to an incoming spike volley, enabling successful communication during the peaks of the oscillation. Such communication can be exploited in feedforward networks, provided the participating networks have similar resonance frequencies. This, however, is not necessarily true for cortical networks. Moreover, the communication is slow, as it takes several oscillation cycles to build up the response in the downstream network. Also, only periodic trains of spikes volleys (and not single volleys) with matching intervals can propagate. Here, we present a novel mechanism that alleviates these shortcomings and enables propagation of synchronous spiking across weakly connected networks with not necessarily identical resonance frequencies. In this framework, an individual spike volley can propagate by local amplification through reverberation in a loop between two successive networks, connected by feedforward and feedback connections: the resonance pair. This overcomes the need for activity build-up in downstream networks, causing the volley to propagate distinctly faster and more reliably.

The subcortical belly of sleep: New possibilities in neuromodulation of basal ganglia?

Early studies posited a relationship between sleep and the basal ganglia, but this relationship has received little attention recently. It is timely to revisit this relationship, given new insights into the functional anatomy of the basal ganglia and the physiology of sleep, which has been made possible by modern techniques such as chemogenetic and optogenetic mapping of neural circuits in rodents and intracranial recording, functional imaging, and a better understanding of human sleep disorders. We discuss the functional anatomy of the basal ganglia, and review evidence implicating their role in sleep. Whilst these studies are in their infancy, we suggest that the basal ganglia may play an integral role in the sleep-wake cycle, specifically by contributing to a thalamo-cortical-basal ganglia oscillatory network in slow-wave sleep which facilitates neural plasticity, and an active state during REM sleep which enables the enactment of cognitive and emotional networks. A better understanding of sleep mechanisms may pave the way for more effective neuromodulation strategies for sleep and basal ganglia disorders.

A mechanism for learning with sleep spindles

Spindles are ubiquitous oscillations during non-rapid eye movement (NREM) sleep. A growing body of evidence points to a possible link with learning and memory, and the underlying mechanisms are now starting to be unveiled. Specifically, spindles are associated with increased dendritic activity and high intracellular calcium levels, a situation favourable to plasticity, as well as with control of spiking output by feed-forward inhibition. During spindles, thalamocortical networks become unresponsive to inputs, thus potentially preventing interference between memory-related internal information processing and extrinsic signals. At the system level, spindles are co-modulated with other major NREM oscillations, including hippocampal sharp wave-ripples (SWRs) and neocortical slow waves, both previously shown to be associated with learning and memory. The sequential occurrence of reactivation at the time of SWRs followed by neuronal plasticity-promoting spindles is a possible mechanism to explain NREM sleep-dependent consolidation of memories. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Perspective on the Multiple Pathways to Changing Brain States

In this review article, we highlight several disparate ideas that are linked to changes in brain state (i.e., sleep to arousal, Down to Up, synchronized to de-synchronized). In any discussion of the brain state, we propose that the cortical pyramidal neuron has a central position. EEG recordings, which typically assess brain state, predominantly reflect the activity of cortical pyramidal neurons. This means that the dominant rhythmic activity that characterizes a particular brain state ultimately has to manifest globally across the pyramidal neuron population. During state transitions, it is the long-range connectivity of these neurons that broadcast the resultant changes in activity to many subcortical targets. Structures like the thalamus, brainstem/hypothalamic neuromodulatory systems, and respiratory systems can also strongly influence brain state, and for many decades we have been uncovering bidirectional pathways that link these structures to state changes in the cerebral cortex. More recently, movement and active behaviors have emerged as powerful drivers of state changes. Each of these systems involve different circuits distributed across the brain. Yet, for a system-wide change in brain state, there must be a collaboration between these circuits that reflects and perhaps triggers the transition between brain states. As we expand our understanding of how brain state changes, our current challenge is to understand how these diverse sets of circuits and pathways interact to produce the changes observed in cortical pyramidal neurons.

A sleep spindle framework for motor memory consolidation

Sleep spindle activity has repeatedly been found to contribute to brain plasticity and consolidation of both declarative and procedural memories. Here we propose a framework for motor memory consolidation that outlines the essential contribution of the hierarchical and multi-scale periodicity of spindle activity, as well as of the synchronization and interaction of brain oscillations during this sleep-dependent process. We posit that the clustering of sleep spindles in 'trains', together with the temporally organized alternation between spindles and associated refractory periods, is critical for efficient reprocessing and consolidation of motor memories. We further argue that the long-term retention of procedural memories relies on the synchronized (functional connectivity) local reprocessing of new information across segregated, but inter-connected brain regions that are involved in the initial learning process. Finally, we propose that oscillatory synchrony in the spindle frequency band may reflect the cross-structural reactivation, reorganization and consolidation of motor, and potentially declarative, memory traces within broader subcortical-cortical networks during sleep. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Arousal State-Dependent Alterations in VTA-GABAergic Neuronal Activity

Decades of research have implicated the ventral tegmental area (VTA) in motivation, learning and reward processing. We and others recently demonstrated that it also serves as an important node in sleep/wake regulation. Specifically, VTA-dopaminergic neuron activation is sufficient to drive wakefulness and necessary for the maintenance of wakefulness. However, the role of VTA-GABAergic neurons in arousal regulation is not fully understood. It is still unclear whether VTA-GABAergic neurons predictably alter their activity across arousal states, what is the nature of interactions between VTA-GABAergic activity and cortical oscillations, and how activity in VTA-GABAergic neurons relates to VTA-dopaminergic neurons in the context of sleep/wake regulation. To address these, we simultaneously recorded population activity from VTA subpopulations and electroencephalography/electromyography (EEG/EMG) signals during spontaneous sleep/wake states and in the presence of salient stimuli in freely-behaving mice. We found that VTA-GABAergic neurons exhibit robust arousal-state-dependent alterations in population activity, with high activity and transients during wakefulness and REM sleep. During wakefulness, population activity of VTA-GABAergic neurons, but not VTA-dopaminergic neurons, was positively correlated with EEG γ power and negatively correlated with θ power. During NREM sleep, population activity in both VTA-GABAergic and VTA-dopaminergic neurons negatively correlated with δ, θ, and σ power bands. Salient stimuli, with both positive and negative valence, activated VTA-GABAergic neurons. Together, our data indicate that VTA-GABAergic neurons, like their dopaminergic counterparts, drastically alter their activity across sleep-wake states. Changes in their activity predicts cortical oscillatory patterns reflected in the EEG, which are distinct from EEG spectra associated with dopaminergic neural activity.

Signal Propagation via Open-Loop Intrathalamic Architectures: A Computational Model

Propagation of signals across the cerebral cortex is a core component of many cognitive processes and is generally thought to be mediated by direct intracortical connectivity. The thalamus, by contrast, is considered to be devoid of internal connections and organized as a collection of parallel inputs to the cortex. Here, we provide evidence that "open-loop" intrathalamic pathways involving the thalamic reticular nucleus (TRN) can support propagation of oscillatory activity across the cortex. Recent studies support the existence of open-loop thalamo-reticulo-thalamic (TC-TRN-TC) synaptic motifs in addition to traditional closed-loop architectures. We hypothesized that open-loop structural modules, when connected in series, might underlie thalamic and, therefore cortical, signal propagation. Using a supercomputing platform to simulate thousands of permutations of a thalamocortical network based on physiological data collected in mice, rats, ferrets, and cats and in which select synapses were allowed to vary both by class and individually, we evaluated the relative capacities of closed-loop and open-loop TC-TRN-TC synaptic configurations to support both propagation and oscillation. We observed that (1) signal propagation was best supported in networks possessing strong open-loop TC-TRN-TC connectivity; (2) intrareticular synapses were neither primary substrates of propagation nor oscillation; and (3) heterogeneous synaptic networks supported more robust propagation of oscillation than their homogeneous counterparts. These findings suggest that open-loop, heterogeneous intrathalamic architectures might complement direct intracortical connectivity to facilitate cortical signal propagation.

Brain Rhythms During Sleep and Memory Consolidation: Neurobiological Insights

Sleep can benefit memory consolidation. The characterization of brain regions underlying memory consolidation during sleep, as well as their temporal interplay, reflected by specific patterns of brain electric activity, is surfacing. Here, we provide an overview of recent concepts and results on the mechanisms of sleep-related memory consolidation. The latest studies strongly impacting future directions of research in this field are highlighted.

Typical and Aberrant Functional Brain Flexibility: Lifespan Development and Aberrant Organization in Traumatic Brain Injury and Dyslexia

Intrinsic functional connectivity networks derived from different neuroimaging methods and connectivity estimators have revealed robust developmental trends linked to behavioural and cognitive maturation. The present study employed a dynamic functional connectivity approach to determine dominant intrinsic coupling modes in resting-state neuromagnetic data from 178 healthy participants aged 8-60 years. Results revealed significant developmental trends in three types of dominant intra- and inter-hemispheric neuronal population interactions (amplitude envelope, phase coupling, and phase-amplitude synchronization) involving frontal, temporal, and parieto-occipital regions. Multi-class support vector machines achieved 89% correct classification of participants according to their chronological age using dynamic functional connectivity indices. Moreover, systematic temporal variability in functional connectivity profiles, which was used to empirically derive a composite flexibility index, displayed an inverse U-shaped curve among healthy participants. Lower flexibility values were found among age-matched children with reading disability and adults who had suffered mild traumatic brain injury. The importance of these results for normal and abnormal brain development are discussed in light of the recently proposed role of cross-frequency interactions in the fine-grained coordination of neuronal population activity.

Sleep Spindles: Mechanisms and Functions

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

Association between depressive symptoms and sleep neurophysiology in early adolescence

BACKGROUND

Depression is highly prevalent among adolescents, and depressive symptoms rise rapidly during early adolescence. Depression is often accompanied by subjective sleep complaints and alterations in sleep neurophysiology. In this study, we examine whether depressive symptoms, measured on a continuum, are associated with subjective and objective (sleep architecture and neurophysiology) measures of sleep in early adolescence.

METHODS

High-density sleep EEG, actigraphy, and self-reported sleep were measured in 52 early adolescents (12.31 years; SD: 1.121; 25 female). Depressive symptoms were measured on a continuum using the Center for Epidemiological Studies Depression Scale (CES-D). The association between depressive symptoms and 2 weeks of actigraphy, self-reported sleep, sleep architecture, and sleep neurophysiology (slow wave activity and sigma power) was determined via multiple linear regression with factors age, sex, and pubertal status.

RESULTS

Despite no association between polysomnography measures of sleep quality and depressive symptoms, individuals with more depressive symptoms manifested worse actigraphically measured sleep. Less sleep spindle activity, as reflected in nonrapid eye movement sleep sigma power, was associated with more depressive symptoms over a large cluster encompassing temporal, parietal, and occipital regions. Furthermore, worse subjectively reported sleep quality was also associated with less sigma power over these same areas. Puberty, age, and sex did not impact this association.

CONCLUSIONS

Sleep spindles have been hypothesized to protect sleep against environmental disturbances. Thus, diminished spindle power may be a subtle sign of disrupted sleep and its association with depressive symptoms in early adolescence may signal vulnerability for depression.