Temperature Modulation of Slow and Fast Cortical Rhythms

A modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets

Neuroscience is moving toward a more integrative discipline where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, and measurement techniques. A remaining challenge on that path is integrating such heterogeneous data into analysis workflows such that consistent and comparable conclusions can be distilled as an experimental basis for models and theories. Here, we propose a solution in the context of slow-wave activity (<1 Hz), which occurs during unconscious brain states like sleep and general anesthesia and is observed across diverse experimental approaches. We address the issue of integrating and comparing heterogeneous data by conceptualizing a general pipeline design that is adaptable to a variety of inputs and applications. Furthermore, we present the Collaborative Brain Wave Analysis Pipeline (Cobrawap) as a concrete, reusable software implementation to perform broad, detailed, and rigorous comparisons of slow-wave characteristics across multiple, openly available electrocorticography (ECoG) and calcium imaging datasets.

Recording physiological and pathological cortical activity and exogenous electric fields using graphene microtransistor arrays in vitro

Graphene-based solution-gated field-effect transistors (gSGFETs) allow the quantification of the brain's full-band signal. Extracellular alternating current (AC) signals include local field potentials (LFP, population activity within a reach of hundreds of micrometers), multiunit activity (MUA), and ultimately single units. Direct current (DC) potentials are slow brain signals with a frequency under 0.1 Hz, and commonly filtered out by conventional AC amplifiers. This component conveys information about what has been referred to as "infraslow" activity. We used gSGFET arrays to record full-band patterns from both physiological and pathological activity generated by the cerebral cortex. To this end, we used an in vitro preparation of cerebral cortex that generates spontaneous rhythmic activity, such as that occurring in slow wave sleep. This examination extended to experimentally induced pathological activities, including epileptiform discharges and cortical spreading depression. Validation of recordings obtained via gSGFETs, including both AC and DC components, was accomplished by cross-referencing with well-established technologies, thereby quantifying these components across different activity patterns. We then explored an additional gSGFET potential application, which is the measure of externally induced electric fields such as those used in therapeutic neuromodulation in humans. Finally, we tested the gSGFETs in human cortical slices obtained intrasurgically. In conclusion, this study offers a comprehensive characterization of gSGFETs for brain recordings, with a focus on potential clinical applications of this emerging technology.

Propagating population activity patterns during spontaneous slow waves in the thalamus of rodents

Slow waves (SWs) represent the most prominent electrophysiological events in the thalamocortical system under anesthesia and during deep sleep. Recent studies have revealed that SWs have complex spatiotemporal dynamics and propagate across neocortical regions. However, it is still unclear whether neuronal activity in the thalamus exhibits similar propagation properties during SWs. Here, we report propagating population activity in the thalamus of ketamine/xylazine-anesthetized rats and mice visualized by high-density silicon probe recordings. In both rodent species, propagation of spontaneous thalamic activity during up-states was most frequently observed in dorsal thalamic nuclei such as the higher order posterior (Po), lateral posterior (LP) or laterodorsal (LD) nuclei. The preferred direction of thalamic activity spreading was along the dorsoventral axis, with over half of the up-states exhibiting a gradual propagation in the ventral-to-dorsal direction. Furthermore, simultaneous neocortical and thalamic recordings collected under anesthesia demonstrated that there is a weak but noticeable interrelation between propagation patterns observed during cortical up-states and those displayed by thalamic population activity. In addition, using chronically implanted silicon probes, we detected propagating activity patterns in the thalamus of naturally sleeping rats during slow-wave sleep. However, in comparison to propagating up-states observed under anesthesia, these propagating patterns were characterized by a reduced rate of occurrence and a faster propagation speed. Our findings suggest that the propagation of spontaneous population activity is an intrinsic property of the thalamocortical network during synchronized brain states such as deep sleep or anesthesia. Additionally, our data implies that the neocortex may have partial control over the formation of propagation patterns within the dorsal thalamus under anesthesia.

Laminar organization of neocortical activities during systemic anoxia

The neocortex is highly susceptible to metabolic dysfunction. When exposed to global ischemia or anoxia, it suffers a slowly propagating wave of collective neuronal depolarization that ultimately impairs its structure and function. While the molecular signature of anoxic depolarization (AD) is well documented, little is known about the brain states that precede and follow AD onset. Here, by means of multisite extracellular local field potentials and intracellular recordings from identified pyramidal cells, we investigated the laminar expression of cortical activities induced by transient anoxia in rat primary somatosensory cortex. Soon after the interruption of brain oxygenation, we observed a well-organized sequence of stereotyped activity patterns across all cortical layers. This sequence included an initial period of beta-gamma activity, rapidly replaced by delta-theta oscillations followed by a decline in all spontaneous activites, marking the entry into a sustained period of electrical silence. Intracellular recordings revealed that cortical pyramidal neurons were depolarized and highly active during high-frequency activity, became inactive and devoid of synaptic potentials during the isoelectric state, and showed subthreshold composite synaptic depolarizations during the low-frequency period. Contrasting with the strong temporal coherence of pre-AD activities along the vertical axis of the cortical column, the onset of AD was not uniform across layers. AD initially occurred in layer 5 or 6 and then propagated bidirectionally in the upward and downward direction. Conversely, the post-anoxic waves that indicated the repolarization of cortical neurons upon brain reoxygenation did not exhibit a specific spatio-temporal profile. Pyramidal neurons from AD initiation site had a more depolarized resting potential and higher spontaneous firing rate compared to superficial cortical cells. We also found that the propagation pattern of AD was reliably reproduced by focal injection of an inhibitor of sodium‑potassium ATPases, suggesting that cortical AD dynamics could reflect layer-dependent variations in cellular metabolic regulations.

M-current modulation of cortical slow oscillations: Network dynamics and computational modeling

The slow oscillation is a synchronized network activity expressed by the cortical network in slow wave sleep and under anesthesia. Waking up requires a transition from this synchronized brain state to a desynchronized one. Cholinergic innervation is critical for the transition from slow-wave-sleep to wakefulness, and muscarinic action is largely exerted through the muscarinic-sensitive potassium current (M-current) block. We investigated the dynamical impact of blocking the M-current on slow oscillations, both in cortical slices and in a cortical network computational model. Blocking M-current resulted in an elongation of Up states (by four times) and in a significant firing rate increase, reflecting an increased network excitability, albeit no epileptiform discharges occurred. These effects were replicated in a biophysical cortical model, where a parametric reduction of the M-current resulted in a progressive elongation of Up states and firing rate. All neurons, and not only those modeled with M-current, increased their firing rates due to network recurrency. Further increases in excitability induced even longer Up states, approaching the microarousals described in the transition towards wakefulness. Our results bridge an ionic current with network modulation, providing a mechanistic insight into network dynamics of awakening.

The role of feedback and modulation in determining temperature resiliency in the lobster cardiac nervous system

Changes in ambient temperature affect all biological processes. However, these effects are process specific and often vary non-linearly. It is thus a non-trivial problem for neuronal circuits to maintain coordinated, functional output across a range of temperatures. The cardiac nervous systems in two species of decapod crustaceans, Homarus americanus and Cancer borealis, can maintain function across a wide but physiologically relevant temperature range. However, the processes that underlie temperature resilience in neuronal circuits and muscle systems are not fully understood. Here, we demonstrate that the non-isolated cardiac nervous system (i.e., the whole heart: neurons, effector organs, intrinsic feedback systems) in the American lobster, H. americanus, is more sensitive to warm temperatures than the isolated cardiac ganglion (CG) that controls the heartbeat. This was surprising as modulatory processes known to stabilize the output from the CG are absent when the ganglion is isolated. One source of inhibitory feedback in the intact cardiac neuromuscular system is nitric oxide (NO), which is released in response to heart contractions. We hypothesized that the greater temperature tolerance observed in the isolated CG is due to the absence of NO feedback. Here, we demonstrate that applying an NO donor to the isolated CG reduces its temperature tolerance. Similarly, we show that the NO synthase inhibitor L-nitroarginine (LNA) increases the temperature tolerance of the non-isolated nervous system. This is sufficient to explain differences in temperature tolerance between the isolated CG and the whole heart. However, in an intact lobster, the heart and CG are modulated by an array of endogenous peptides and hormones, many of which are positive regulators of the heartbeat. Many studies have demonstrated that excitatory modulators increase temperature resilience. However, this neuromuscular system is regulated by both excitatory and inhibitory peptide modulators. Perfusing SGRNFLRFamide, a FLRFamide-like peptide, through the heart increases the non-isolated nervous system’s tolerance to high temperatures. In contrast, perfusing myosuppressin, a peptide that negatively regulates the heartbeat frequency, decreases the temperature tolerance. Our data suggest that, in this nervous system, positive regulators of neural output increase temperature tolerance of the neuromuscular system, while modulators that decrease neural output decrease temperature tolerance.

The rapid developmental rise of somatic inhibition disengages hippocampal dynamics from self-motion

Early electrophysiological brain oscillations recorded in preterm babies and newborn rodents are initially mostly driven by bottom-up sensorimotor activity and only later can detach from external inputs. This is a hallmark of most developing brain areas, including the hippocampus, which, in the adult brain, functions in integrating external inputs onto internal dynamics. Such developmental disengagement from external inputs is likely a fundamental step for the proper development of cognitive internal models. Despite its importance, the developmental timeline and circuit basis for this disengagement remain unknown. To address this issue, we have investigated the daily evolution of CA1 dynamics and underlying circuits during the first two postnatal weeks of mouse development using two-photon calcium imaging in non-anesthetized pups. We show that the first postnatal week ends with an abrupt shift in the representation of self-motion in CA1. Indeed, most CA1 pyramidal cells switch from activated to inhibited by self-generated movements at the end of the first postnatal week, whereas the majority of GABAergic neurons remain positively modulated throughout this period. This rapid switch occurs within 2 days and follows the rapid anatomical and functional surge of local somatic GABAergic innervation. The observed change in dynamics is consistent with a two-population model undergoing a strengthening of inhibition. We propose that this abrupt developmental transition inaugurates the emergence of internal hippocampal dynamics.

Effects of temperature on mating behaviour and mating success: A meta-analysis

In light of global climate change, there is a pressing need to understand how populations will respond to rising temperatures. Understanding the effects of temperature changes on mating behaviour is particularly important, given its implications for population viability. To this end, we performed a meta-analysis of 53 studies to examine how temperature changes influence mating latency, choosiness and mating success. We hypothesized that if higher temperatures make mate searching and mate assessment more costly due to an elevated metabolism, this may lead to a reduction in mating latency and choosiness, thereby increasing overall mating success. We found no evidence for an overall effect of temperature on mating latency, choosiness, or mating success. There was an increase in mating success when animals were exposed to higher temperatures during mating trials but not when they were exposed before mating trials. In addition, in a subset of studies that measured both mating latency and mating success, there was a strong negative relationship between the effect sizes for these traits. This suggests that a decrease in mating latency at higher temperatures was associated with an increase in mating success and vice versa. In sum, our meta-analysis provides new insights into the effects of temperature on mating patterns. The absence of a consistent directional effect of temperature on mating behaviours and mating success suggests it may be difficult to predict changes in the strength of sexual selection in natural populations in a warming world. Nevertheless, there is some evidence that (a) higher temperatures during mating may lead to an increase in mating success and that (b) an increase in mating success is associated with a decrease in mating latency.

GABAb- and GABAa- mediated regulation of Up and Down states across development

KEY POINTS

Slow oscillations (SOs), the EEG hallmark of non-REM sleep, and their cellular counterpart, Up-and-Down states (UDSs), are considered the default activity of the cerebral cortex and reflect the underlying neural connectivity. GABAb- and GABAa- receptor-mediated inhibition play a major role in regulating UDS activity. Although SOs and UDSs exhibit significant alterations as a function of age, it is unknown how developmental changes in inhibition contribute to the developmental profile of this activity. In this study, we reveal for the first time, age-dependent effects of GABAb and GABAa signalling on UDSs. We also document the differential subunit composition of postsynaptic GABAa receptors in young and adult animals, highlighting the α1-subunit as a major component of the age-differentiated regulation of UDSs. These findings help clarify the mechanisms that underlie the maturation of cortical network activity, and enhance our understanding regarding the emergence of neurodevelopmental disorders.

ABSTRACT

Slow oscillations, the hallmark of non-REM sleep, and their cellular counterpart, Up-and-Down states (UDSs), are considered a signature of cortical dynamics that reflect the intrinsic network organization. Although previous studies have explored the role of inhibition in regulating UDSs, little is known about whether this role changes with maturation. This is surprising since both slow oscillations and UDSs exhibit significant age-dependent alterations. To elucidate the developmental impact of GABAb and GABAa receptors on UDS activity, we conducted simultaneous LFP and intracellular recordings ex vivo, in brain slices of young and adult male mice, using selective blockers, CGP and non-saturating concentration of gabazine, respectively. Blockade of both GABAb- and GABAa- signalling showed age-differentiated functions. CGP caused an increase in Down state duration in young animals, but a decrease in adults. Gabazine evoked Spike-and-Wave-Discharges in both ages; however, while young networks became completely epileptic, adults maintained the ability to generate UDSs. Furthermore, voltage clamp recordings of mIPSCs revealed that gabazine selectively blocks phasic currents, particularly involving postsynaptic mechanisms. The latter exhibit clear maturational changes, suggesting a different subunit composition of GABAa receptors in young vs. adult animals. Indeed, subsequent LFP recordings under diazepam (nanomolar or micromolar concentrations) revealed that mechanisms engaging the drug's classical-binding-site, mediated by α1-subunit containing GABAa receptors, have a bigger contribution in Up state initiation in young networks compared to adults. Taken together, these findings help clarify the mechanisms that underlie the maturation of cortical network activity and enhance our understanding regarding the emergence of neurodevelopmental disorders. Abstract figure legend GABAb receptors' participation in Up state termination mechanisms is well-conserved across development. However, regulation of Down-to-Up transitions is age-dependent; GABAb receptors promote them in young while preventing them in adults. Up state maintenance is determined by age-dependent synaptic GABAa receptors' subunit composition and kinetics; α1-GABAa receptors dominate in young while non-α1-GABAa receptors dominate in adults. This article is protected by copyright. All rights reserved.

Slow waves form expanding, memory-rich mesostates steered by local excitability in fading anesthesia

In the arousal process, the brain restores its integrative activity from the synchronized state of slow wave activity (SWA). The mechanisms underpinning this state transition remain, however, to be elucidated. Here we simultaneously probed neuronal assemblies throughout the whole cortex with micro-electrocorticographic recordings in mice. We investigated the progressive shaping of propagating SWA at different levels of isoflurane. We found a form of memory of the wavefront shapes at deep anesthesia, tightly alternating posterior-anterior-posterior patterns. At low isoflurane, metastable patterns propagated in more directions, reflecting an increased complexity. The wandering across these mesostates progressively increased its randomness, as predicted by simulations of a network of spiking neurons, and confirmed in our experimental data. The complexity increase is explained by the elevated excitability of local assemblies with no modifications of the network connectivity. These results shed new light on the functional reorganization of the cortical network as anesthesia fades out.

•

Complexity of isoflurane-induced slow waves reliably determines anesthesia level

•

In deep anesthesia, the propagation strictly alternates between front-back-front patterns

•

In light anesthesia, there is a continuum of directions and faster propagation

•

Local excitability underpins the cortical reorganization in fading anesthesia

The relationship between fasting-induced torpor, sleep, and wakefulness in laboratory mice

STUDY OBJECTIVES

Torpor is a regulated and reversible state of metabolic suppression used by many mammalian species to conserve energy. Whereas the relationship between torpor and sleep has been well-studied in seasonal hibernators, less is known about the effects of fasting-induced torpor on states of vigilance and brain activity in laboratory mice.

METHODS

Continuous monitoring of electroencephalogram (EEG), electromyogram (EMG), and surface body temperature was undertaken in adult, male C57BL/6 mice over consecutive days of scheduled restricted feeding.

RESULTS

All animals showed bouts of hypothermia that became progressively deeper and longer as fasting progressed. EEG and EMG were markedly affected by hypothermia, although the typical electrophysiological signatures of non-rapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, and wakefulness enabled us to perform vigilance-state classification in all cases. Consistent with previous studies, hypothermic bouts were initiated from a state indistinguishable from NREM sleep, with EEG power decreasing gradually in parallel with decreasing surface body temperature. During deep hypothermia, REM sleep was largely abolished, and we observed shivering-associated intense bursts of muscle activity.

CONCLUSIONS

Our study highlights important similarities between EEG signatures of fasting-induced torpor in mice, daily torpor in Djungarian hamsters and hibernation in seasonally hibernating species. Future studies are necessary to clarify the effects on fasting-induced torpor on subsequent sleep.

Impact of GABAA and GABAB Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States

Quantitative estimations of spatiotemporal complexity of cortical activity patterns are used in the clinic as a measure of consciousness levels, but the cortical mechanisms involved are not fully understood. We used a version of the perturbational complexity index (PCI) adapted to multisite recordings from the ferret (either sex) cerebral cortex in vitro (sPCI) to investigate the role of GABAergic inhibition in cortical complexity. We studied two dynamical states: slow-wave activity (synchronous state) and desynchronized activity, that express low and high causal complexity respectively. Progressive blockade of GABAergic inhibition during both regimes revealed its impact on the emergent cortical activity and on sPCI. Gradual GABAA receptor blockade resulted in higher synchronization, being able to drive the network from a desynchronized to a synchronous state, with a progressive decrease of complexity (sPCI). Blocking GABAB receptors also resulted in a reduced sPCI, in particular when in a synchronous, slow wave state. Our findings demonstrate that physiological levels of inhibition contribute to the generation of dynamical richness and spatiotemporal complexity. However, if inhibition is diminished or enhanced, cortical complexity decreases. Using a computational model, we explored a larger parameter space in this relationship and demonstrate a link between excitatory/inhibitory balance and the complexity expressed by the cortical network.SIGNIFICANCE STATEMENT The spatiotemporal complexity of the activity expressed by the cerebral cortex is a highly revealing feature of the underlying network's state. Complexity varies with physiological brain states: it is higher during awake than during sleep states. But it also informs about pathologic states: in disorders of consciousness, complexity is lower in an unresponsive wakefulness syndrome than in a minimally conscious state. What are the network parameters that modulate complexity? Here we investigate how inhibition, mediated by either GABAA or GABAA receptors, influences cortical complexity. And we do this departing from two extreme functional states: a highly synchronous, slow-wave state, and a desynchronized one that mimics wakefulness. We find that there is an optimal level of inhibition in which complexity is highest.

Attractor competition enriches cortical dynamics during awakening from anesthesia

Slow oscillations (≲ 1 Hz), a hallmark of slow-wave sleep and deep anesthesia across species, arise from spatiotemporal patterns of activity whose complexity increases as wakefulness is approached and cognitive functions emerge. The arousal process constitutes an open window to the unknown mechanisms underlying the emergence of such dynamical richness in awake cortical networks. Here, we investigate the changes in network dynamics as anesthesia fades out in the rat visual cortex. Starting from deep anesthesia, slow oscillations gradually increase their frequency, eventually expressing maximum regularity. This stage is followed by the abrupt onset of an infra-slow (~0.2 Hz) alternation between sleep-like oscillations and activated states. A population rate model reproduces this transition driven by an increased excitability that brings it to periodically cross a critical point. Based on our model, dynamical richness emerges as a competition between two metastable attractor states, a conclusion strongly supported by the data.

Up and Down States During Slow Oscillations in Slow-Wave Sleep and Different Levels of Anesthesia

Slow oscillations are a pattern of synchronized network activity generated by the cerebral cortex. They consist of Up and Down states, which are periods of activity interspersed with periods of silence, respectively. However, even when this is a unique dynamic regime of transitions between Up and Down states, this pattern is not constant: there is a range of oscillatory frequencies (0.1-4 Hz), and the duration of Up vs. Down states during the cycles is variable. This opens many questions. Is there a constant relationship between the duration of Up and Down states? How much do they vary across conditions and oscillatory frequencies? Are there different sub regimes within the slow oscillations? To answer these questions, we aimed to explore a concrete aspect of slow oscillations, Up and Down state durations, across three conditions: deep anesthesia, light anesthesia, and slow-wave sleep (SWS), in the same chronically implanted rats. We found that light anesthesia and SWS have rather similar properties, occupying a small area of the Up and Down state duration space. Deeper levels of anesthesia occupy a larger region of this space, revealing that a large variety of Up and Down state durations can emerge within the slow oscillatory regime. In a network model, we investigated the network parameters that can explain the different points within our bifurcation diagram in which slow oscillations are expressed.

Modulation of cortical slow oscillations and complexity across anesthesia levels

The ability of different groups of cortical neurons to engage in causal interactions that are at once differentiated and integrated results in complex dynamic patterns. Complexity is low during periods of unconsciousness (deep sleep, anesthesia, unresponsive wakefulness syndrome) in which the brain tends to generate a stereotypical pattern consisting of alternating active and silent periods of neural activity-slow oscillations- and is high during wakefulness. But how is cortical complexity built up? Is it a continuum? An open question is whether cortical complexity can vary within the same brain state. Here we recorded with 32-channel multielectrode arrays from the cortical surface of the mouse and used both spontaneous dynamics (wave propagation entropy and functional complexity) and a perturbational approach (a variation of the perturbation complexity index) to measure complexity at different anesthesia levels. Variations in anesthesia level within the bistable regime of slow oscillations (0.1-1.5 Hz) resulted in a modulation of the slow oscillation frequency. Both perturbational and spontaneous complexity increased with decreasing anesthesia levels, in correlation with the decrease in coherence of the underlying network. Changes in complexity level are related to, but not dependent on, changes in excitability. We conclude that cortical complexity can vary within a single brain state dominated by slow oscillations, building up to the higher complexity associated with consciousness.

Modulation of cortical slow oscillatory rhythm by GABAB receptors: an in vitro experimental and computational study

KEY POINTS

We confirm that GABAB receptors (GABAB -Rs) are involved in the termination of Up-states; their blockade consistently elongates Up-states. GABAB -Rs also modulate Down-states and the oscillatory cycle, thus having an impact on slow oscillation rhythm and its regularity. The most frequent effect of GABAB -R blockade is elongation of Down-states and subsequent decrease of oscillatory frequency, with an increased regularity. In a quarter of cases, GABAB -R blockade shortened Down-states and increased oscillatory frequency, changes that are independent of firing rates in Up-states. Our computer model provides mechanisms for the experimentally observed dynamics following blockade of GABAB -Rs, for Up/Down durations, oscillatory frequency and regularity. The time course of excitation, inhibition and adaptation can explain the observed dynamics of the network. This study brings novel insights into the role of GABAB -R-mediated slow inhibition on the slow oscillatory activity, which is considered the default activity pattern of the cortical network.

ABSTRACT

Slow wave oscillations (SWOs) dominate cortical activity during deep sleep, anaesthesia and in some brain lesions. SWOs are composed of periods of activity (Up states) interspersed with periods of silence (Down states). The rhythmicity expressed during SWOs integrates neuronal and connectivity properties of the network and is often altered under pathological conditions. Adaptation mechanisms as well as synaptic inhibition mediated by GABAB receptors (GABAB -Rs) have been proposed as mechanisms governing the termination of Up states. The interplay between these two mechanisms is not well understood, and the role of GABAB -Rs controlling the whole cycle of the SWO has not been described. Here we contribute to its understanding by combining in vitro experiments on spontaneously active cortical slices and computational techniques. GABAB -R blockade modified the whole SWO cycle, not only elongating Up states, but also affecting the subsequent Down state duration. Furthermore, while adaptation tends to yield a rather regular behaviour, we demonstrate that GABAB -R activation desynchronizes the SWOs. Interestingly, variability changes could be accomplished in two different ways: by either shortening or lengthening the duration of Down states. Even when the most common observation following GABAB -Rs blocking is the lengthening of Down states, both changes are expressed experimentally and also in numerical simulations. Our simulations suggest that the sluggishness of GABAB -Rs to follow the excitatory fluctuations of the cortical network can explain these different network dynamics modulated by GABAB -Rs.

The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging

In recent years, technical and procedural advances have brought functional magnetic resonance imaging (fMRI) to the field of murine neuroscience. Due to its unique capacity to measure functional activity non-invasively, across the entire brain, fMRI allows for the direct comparison of large-scale murine and human brain functions. This opens an avenue for bidirectional translational strategies to address fundamental questions ranging from neurological disorders to the nature of consciousness. The key challenges of murine fMRI are: (1) to generate and maintain functional brain states that approximate those of calm and relaxed human volunteers, while (2) preserving neurovascular coupling and physiological baseline conditions. Low-dose anesthetic protocols are commonly applied in murine functional brain studies to prevent stress and facilitate a calm and relaxed condition among animals. Yet, current mono-anesthesia has been shown to impair neural transmission and hemodynamic integrity. By linking the current state of murine electrophysiology, Ca2+ imaging and fMRI of anesthetic effects to findings from human studies, this systematic review proposes general principles to design, apply and monitor anesthetic protocols in a more sophisticated way. The further development of balanced multimodal anesthesia, combining two or more drugs with complementary modes of action helps to shape and maintain specific brain states and relevant aspects of murine physiology. Functional connectivity and its dynamic repertoire as assessed by fMRI can be used to make inferences about cortical states and provide additional information about whole-brain functional dynamics. Based on this, a simple and comprehensive functional neurosignature pattern can be determined for use in defining brain states and anesthetic depth in rest and in response to stimuli. Such a signature can be evaluated and shared between labs to indicate the brain state of a mouse during experiments, an important step toward translating findings across species.

GABAB receptors: modulation of thalamocortical dynamics and synaptic plasticity

GABA_B-receptors (GABA_B-Rs) are metabotropic, G protein-coupled receptors for the neurotransmitter GABA. Their activation induces slow inhibitory control of the neuronal excitability mediated by pre- and postsynaptic inhibition. Presynaptically GABA_B-Rs reduce GABA and glutamate release inhibiting presynaptic Ca²⁺ channels in both inhibitory and excitatory synapses while postsynaptic GABA_B-Rs induce robust slow hyperpolarization by the activation of K⁺ channels. GABA_B-Rs are activated by non-synaptic or volume transmission, which requires high levels of GABA release, either by the simultaneous discharge of GABAergic interneurons or very intense discharges in the thalamus or by means of the activation of a neurogliaform interneurons in the cortex. The main receptor subunits GABA_B1a, GABA_B1b and GABA_B2 are strongly expressed in neurons and glial cells throughout the central nervous system and GABA_B-R activation is related to many neuronal processes such as the modulation of rhythmic activity in several brain regions. In the thalamus, GABA_B-Rs modulate the generation of the main thalamic rhythm, spindle waves. In the cerebral cortex, GABA_B-Rs also modulate the most prominent emergent oscillatory activity-slow oscillations-as well as faster oscillations like gamma frequency. Further, recent studies evaluating the complexity expressed by the cortical network, a parameter associated with consciousness levels, have found that GABA_B-Rs enhance this complexity, while their blockade decreases it. This review summarizes the current results on how the activation of GABA_B-Rs affects the interchange of information between brain areas by controlling rhythmicity as well as synaptic plasticity.

Slow Waves in Cortical Slices: How Spontaneous Activity is Shaped by Laminar Structure

Cortical slow oscillations (SO) of neural activity spontaneously emerge and propagate during deep sleep and anesthesia and are also expressed in isolated brain slices and cortical slabs. We lack full understanding of how SO integrate the different structural levels underlying local excitability of cell assemblies and their mutual interaction. Here, we focus on ongoing slow waves (SWs) in cortical slices reconstructed from a 16-electrode array designed to probe the neuronal activity at multiple spatial scales. In spite of the variable propagation patterns observed, we reproducibly found a smooth strip of loci leading the SW fronts, overlapping cortical layers 4 and 5, along which Up states were the longest and displayed the highest firing rate. Propagation modes were uncorrelated in time, signaling a memoryless generation of SWs. All these features could be modeled by a multimodular large-scale network of spiking neurons with a specific balance between local and intermodular connectivity. Modules work as relaxation oscillators with a weakly stable Down state and a peak of local excitability to model layers 4 and 5. These conditions allow for both optimal sensitivity to the network structure and richness of propagation modes, both of which are potential substrates for dynamic flexibility in more general contexts.

Altered Neocortical Dynamics in a Mouse Model of Williams-Beuren Syndrome

Williams-Beuren syndrome (WBS) is a rare neurodevelopmental disorder characterized by moderate intellectual disability and learning difficulties alongside behavioral abnormalities such as hypersociability. Several structural and functional brain alterations are characteristic of this syndrome, as well as disturbed sleep and sleeping patterns. However, the detailed physiological mechanisms underlying WBS are mostly unknown. Here, we characterized the cortical dynamics in a mouse model of WBS previously reported to replicate most of the behavioral alterations described in humans. We recorded the laminar local field potential generated in the frontal cortex during deep anesthesia and characterized the properties of the emergent slow oscillation activity. Moreover, we performed micro-electrocorticogram recordings using multielectrode arrays covering the cortical surface of one hemisphere. We found significant differences between the cortical emergent activity and functional connectivity between wild-type mice and WBS model mice. Slow oscillations displayed Up states with diminished firing rate and lower high-frequency content in the gamma range. Lower firing rates were also recorded in the awake WBS animals while performing a marble burying task and could be associated with the decreased spine density and thus synaptic connectivity in this cortical area. We also found an overall increase in functional connectivity between brain areas, reflected in lower clustering and abnormally high integration, especially in the gamma range. These results expand previous findings in humans, suggesting that the cognitive deficits characterizing WBS might be associated with reduced excitability, plus an imbalance in the capacity to functionally integrate and segregate information.

Cholinergic Switch between Two Types of Slow Waves in Cerebral Cortex

Sleep slow waves are known to participate in memory consolidation, yet slow waves occurring under anesthesia present no positive effects on memory. Here, we shed light onto this paradox, based on a combination of extracellular recordings in vivo, in vitro, and computational models. We find two types of slow waves, based on analyzing the temporal patterns of successive slow-wave events. The first type is consistently observed in natural slow-wave sleep, while the second is shown to be ubiquitous under anesthesia. Network models of spiking neurons predict that the two slow wave types emerge due to a different gain on inhibitory versus excitatory cells and that different levels of spike-frequency adaptation in excitatory cells can account for dynamical distinctions between the two types. This prediction was tested in vitro by varying adaptation strength using an agonist of acetylcholine receptors, which demonstrated a neuromodulatory switch between the two types of slow waves. Finally, we show that the first type of slow-wave dynamics is more sensitive to external stimuli, which can explain how slow waves in sleep and anesthesia differentially affect memory consolidation, as well as provide a link between slow-wave dynamics and memory diseases.

Effects of Small Temperature Differences Detected in Callosal Circuits of the Anterior Cingulate Cortex

We measured the sensitivity of cortical circuit activity to small differences in local cortical environments by studying how temperature affects the trajectory of epileptiform events (EEs). EEs evoked via blockade of GABA-A receptors were recorded extracellularly from mouse coronal brain slices containing both hemispheres of anterior cingulate cortex synaptically connected by corpus callosum axons. Preferentially illuminating one hemisphere with the microscope condenser produced temperature differences of 0.1 °C between the hemispheres. The relatively warmer hemisphere typically initiated the EEs that then propagated to the contralateral side, demonstrating temperature directed propagation. Severing the callosum following one hour of EEs showed that the warmer hemisphere possessed a higher rate of EE generation. Further experiments implied that intact callosal circuits were required for the increased EE generation in the warmer hemisphere. We propose a hypothesis whereby callosal circuits can amplify differences in respective hemispheric activity, promoting this directionality in seizure propagation.

Temperature Rise under Two-Photon Optogenetic Brain Stimulation

In recent decades, optogenetics has been transforming neuroscience research, enabling neuroscientists to drive and read neural circuits. The recent development in illumination approaches combined with two-photon (2P) excitation, either sequential or parallel, has opened the route for brain circuit manipulation with single-cell resolution and millisecond temporal precision. Yet, the high excitation power required for multi-target photostimulation, especially under 2P illumination, raises questions about the induced local heating inside samples. Here, we present and experimentally validate a theoretical model that makes it possible to simulate 3D light propagation and heat diffusion in optically scattering samples at high spatial and temporal resolution under the illumination configurations most commonly used to perform 2P optogenetics: single- and multi-spot holographic illumination and spiral laser scanning. By investigating the effects of photostimulation repetition rate, spot spacing, and illumination dependence of heat diffusion, we found conditions that make it possible to design a multi-target 2P optogenetics experiment with minimal sample heating.

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

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

Control of cortical oscillatory frequency by a closed-loop system

BACKGROUND

We present a closed-loop system able to control the frequency of slow oscillations (SO) spontaneously generated by the cortical network in vitro. The frequency of SO can be controlled by direct current (DC) electric fields within a certain range. Here we set out to design a system that would be able to autonomously bring the emergent oscillatory activity to a target frequency determined by the experimenter.

METHODS

The cortical activity was recorded through an electrode and was analyzed online. Once a target frequency was set, the frequency of the slow oscillation was steered through the injection of DC of variable intensity that generated electric fields of proportional amplitudes in the brain slice. To achieve such closed-loop control, we designed a custom programmable stimulator ensuring low noise and accurate tuning over low current levels. For data recording and analysis, we relied on commercial acquisition and software tools.

RESULTS

The result is a flexible and reliable system that ensures control over SO frequency in vitro. The system guarantees artifact removal, minimal gaps in data acquisition and robustness in spite of slice heterogeneity.

CONCLUSIONS

Our tool opens new possibilities for the investigation of dynamics of cortical slow oscillations-an activity pattern that is associated with cognitive processes such as memory consolidation, and that is altered in several neurological conditions-and also for potential applications of this technology.

Quantification of Signal-to-Noise Ratio in Cerebral Cortex Recordings Using Flexible MEAs With Co-localized Platinum Black, Carbon Nanotubes, and Gold Electrodes

Developing new standardized tools to characterize brain recording devices is critical to evaluate neural probes and for translation to clinical use. The signal-to-noise ratio (SNR) measurement is the gold standard for quantifying the performance of brain recording devices. Given the drawbacks with the SNR measure, our first objective was to devise a new method to calculate the SNR of neural signals to distinguish signal from noise. Our second objective was to apply this new SNR method to evaluate electrodes of three different materials (platinum black, Pt; carbon nanotubes, CNTs; and gold, Au) co-localized in tritrodes to record from the same cortical area using specifically designed multielectrode arrays. Hence, we devised an approach to calculate SNR at different frequencies based on the features of cortical slow oscillations (SO). Since SO consist in the alternation of silent periods (Down states) and active periods (Up states) of neuronal activity, we used these as noise and signal, respectively. The spectral SNR was computed as the power spectral density (PSD) of Up states (signal) divided by the PSD of Down states (noise). We found that Pt and CNTs electrodes have better recording performance than Au electrodes for the explored frequency range (5–1500 Hz). Together with two proposed SNR estimators for the lower and upper frequency limits, these results substantiate our SNR calculation at different frequency bands. Our results provide a new validated SNR measure that provides rich information of the performance of recording devices at different brain activity frequency bands (<1500 Hz).

High-Density Porous Graphene Arrays Enable Detection and Analysis of Propagating Cortical Waves and Spirals

Cortical propagating waves have recently attracted significant attention by the neuroscience community. These travelling waves have been suggested to coordinate different brain areas and play roles in assisting neural plasticity and learning. However, it is extremely challenging to record them with very fine spatial scales over large areas to investigate their effect on neural dynamics or network connectivity changes. In this work, we employ high-density porous graphene microelectrode arrays fabricated using laser pyrolysis on flexible substrates to study the functional network connectivity during cortical propagating waves. The low-impedance porous graphene arrays are used to record cortical potentials during theta oscillations and drug-induced seizures in vivo. Spatiotemporal analysis on the neural recordings reveal that theta oscillations and epileptiform activities have distinct characteristics in terms of both synchronization and resulting propagating wave patterns. To investigate the network connectivity during the propagating waves, we perform network analysis. The results show that the propagating waves are consistent with the functional connectivity changes in the neural circuits, suggesting that the underlying network states are reflected by the cortical potential propagation patterns.

An ultra-compact integrated system for brain activity recording and stimulation validated over cortical slow oscillations in vivo and in vitro

The understanding of brain processing requires monitoring and exogenous modulation of neuronal ensembles. To this end, it is critical to implement equipment that ideally provides highly accurate, low latency recording and stimulation capabilities, that is functional for different experimental preparations and that is highly compact and mobile. To address these requirements, we designed a small ultra-flexible multielectrode array and combined it with an ultra-compact electronic system. The device consists of a polyimide microelectrode array (8 µm thick and with electrodes measuring as low as 10 µm in diameter) connected to a miniaturized electronic board capable of amplifying, filtering and digitalizing neural signals and, in addition, of stimulating brain tissue. To evaluate the system, we recorded slow oscillations generated in the cerebral cortex network both from in vitro slices and from in vivo anesthetized animals, and we modulated the oscillatory pattern by means of electrical and visual stimulation. Finally, we established a preliminary closed-loop algorithm in vitro that exploits the low latency of the electronics (<0.5 ms), thus allowing monitoring and modulating emergent cortical activity in real time to a desired target oscillatory frequency.

A Portable Microscale Cell Culture System with Indirect Temperature Control

A physiologically relevant environment is essential for successful long-term cell culturing in vitro. Precise control of temperature, one of the most crucial environmental parameters in cell cultures, increases the fidelity and repeatability of the experiments. Unfortunately, direct temperature measurement can interfere with the cultures or prevent imaging of the cells. Furthermore, the assessment of dynamic temperature variations in the cell culture area is challenging with the methods traditionally used for measuring temperature in cell culture systems. To overcome these challenges, we integrated a microscale cell culture environment together with live-cell imaging and a precise local temperature control that is based on an indirect measurement. The control method uses a remote temperature measurement and a mathematical model for estimating temperature at the desired area. The system maintained the temperature at 37±0.3 °C for more than 4 days. We also showed that the system precisely controls the culture temperature during temperature transients and compensates for the disturbance when changing the cell cultivation medium, and presented the portability of the heating system. Finally, we demonstrated a successful long-term culturing of human induced stem cell-derived beating cardiomyocytes, and analyzed their beating rates at different temperatures.

Beta and Gamma Oscillations in Prefrontal Cortex During NMDA Hypofunction: An In Vitro Model of Schizophrenia Features

NMDA receptor (NMDAr) hypofunction has been widely used as a schizophrenia model. Decreased activation of NMDAr is associated with a disrupted excitation/inhibition balance in the prefrontal cortex and with alterations in gamma synchronization. Our aim was to investigate whether this phenomenon could be reproduced in the spontaneous oscillatory activity generated by the local prefrontal network in vitro and, if so, to explore the effects of antipsychotics on the resulting activity. Extracellular recordings were obtained from prefrontal cortex slices bathed in in vivo-like ACSF solution. Slow (<1 Hz) oscillations consisting of interspersed Up (active) and Down (silent) states spontaneously emerged. Fast-frequency oscillations (15-90 Hz) occurred during Up states. We explored the effects of the NMDAr antagonist MK-801 on the spontaneously generated activity. Bath-applied MK-801 induced a dose-dependent decrease in Up-state duration and in the frequency of Up states. However, the beta/gamma power during Up states significantly increased; this increase was in turn prevented by the antipsychotic drug clozapine. The increased beta/gamma power with NMDAr blockade implies that NMDAr activation in physiological conditions prevents hypersynchronization in this frequency range. High-frequency hypersynchronization following NMDAr blockade occurring in cortical slices suggests that-at least part of-the underlying mechanisms of this schizophrenia feature persist in the local cortical circuit, even in the absence of long-range cortical or subcortical inputs. The observed action of clozapine decreasing hypersynchronization in the local circuit may be one of the mechanisms of action of clozapine in preventing schizophrenia symptoms derived from NMDA hypofunction.

Neuronal noise as an origin of sleep arousals and its role in sudden infant death syndrome

In addition to regular sleep/wake cycles, humans and animals exhibit brief arousals from sleep. Although much is known about consolidated sleep and wakefulness, the mechanism that triggers arousals remains enigmatic. Here, we argue that arousals are caused by the intrinsic neuronal noise of wake-promoting neurons. We propose a model that simulates the superposition of the noise from a group of neurons, and show that, occasionally, the superposed noise exceeds the excitability threshold and provokes an arousal. Because neuronal noise decreases with increasing temperature, our model predicts arousal frequency to decrease as well. To test this prediction, we perform experiments on the sleep/wake behavior of zebrafish larvae and find that increasing water temperatures lead to fewer and shorter arousals, as predicted by our analytic derivations and model simulations. Our findings indicate a previously unrecognized neurophysiological mechanism that links sleep arousals with temperature regulation, and may explain the origin of the clinically observed higher risk for sudden infant death syndrome with increased ambient temperature.

Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves

Spontaneous slow oscillation-associated slow wave activity represents an internally generated state which is characterized by alternations of network quiescence and stereotypical episodes of neuronal activity - slow wave events. However, it remains unclear which macroscopic signal is related to these active periods of the slow wave rhythm. We used optic fiber-based calcium recordings of local neural populations in cortex and thalamus to detect neurophysiologically defined slow calcium waves in isoflurane anesthetized rats. The individual slow wave events were used for an event-related analysis of simultaneously acquired whole-brain BOLD fMRI. We identified BOLD responses directly related to onsets of slow calcium waves, revealing a cortex-wide BOLD correlate: the entire cortex was engaged in this specific type of slow wave activity. These findings demonstrate a direct relation of defined neurophysiological events to a specific BOLD activity pattern and were confirmed for ongoing slow wave activity by independent component and seed-based analyses.

When a person is in a deep non-dreaming sleep, neurons in their brain alternate slowly between periods of silence and periods of activity. This gives rise to low-frequency brain rhythms called slow waves, which are thought to help stabilize memories. Slow wave activity can be detected on multiple scales, from the pattern of electrical impulses sent by an individual neuron to the collective activity of the brain’s entire outer layer, the cortex. But does slow wave activity in an individual group of neurons in the cortex affect the activity of the rest of the brain?

To find out, Schwalm, Schmid, Wachsmuth et al. took advantage of the fact that slow waves also occur under general anesthesia, and placed anesthetized rats inside miniature whole-brain scanners. A small region of cortex in each rat had been injected with a dye that fluoresces whenever the neurons in that region are active. An optical fiber was lowered into the rat’s brain to transmit the fluorescence signals to a computer. Monitoring these signals while the animals lay inside the scanner revealed that slow-wave activity in any one group of cortical neurons was accompanied by slow-wave activity across the cortex as a whole. This relationship was seen only for slow waves, and not for other brain rhythms.

Slow waves seem to occur in all species of animal with a backbone, and in both healthy and diseased brains. While it is not possible to inject fluorescent dyes into the human brain, it is possible to monitor neuronal activity using electrodes. Comparing local electrode recordings with measures of whole-brain activity from scanners could thus allow similar experiments to be performed in people. There is growing evidence – from animal models and from studies of patients – that slow waves may be altered in Alzheimer’s disease. Further work is required to determine whether detecting these changes could help diagnose disease at earlier stages, and whether reversing them may have therapeutic potential.

Functional Stem Cell Integration into Neural Networks Assessed by Organotypic Slice Cultures

Re-formation or preservation of functional, electrically active neural networks has been proffered as one of the goals of stem cell-mediated neural therapeutics. A primary issue for a cell therapy approach is the formation of functional contacts between the implanted cells and the host tissue. Therefore, it is of fundamental interest to establish protocols that allow us to delineate a detailed time course of grafted stem cell survival, migration, differentiation, integration, and functional interaction with the host. One option for in vitro studies is to examine the integration of exogenous stem cells into an existing active neural network in ex vivo organotypic cultures. Organotypic cultures leave the structural integrity essentially intact while still allowing the microenvironment to be carefully controlled. This allows detailed studies over time of cellular responses and cell-cell interactions, which are not readily performed in vivo. This unit describes procedures for using organotypic slice cultures as ex vivo model systems for studying neural stem cell and embryonic stem cell engraftment and communication with CNS host tissue. © 2017 by John Wiley & Sons, Inc.

Shaping the Default Activity Pattern of the Cortical Network

Slow oscillations have been suggested as the default emergent activity of the cortical network. This is a low complexity state that integrates neuronal, synaptic, and connectivity properties of the cortex. Shaped by variations of physiological parameters, slow oscillations provide information about the underlying healthy or pathological network. We review how this default activity is shaped, how it acts as a powerful attractor, and how getting out of it is necessary for the brain to recover the levels of complexity associated with conscious states. We propose that slow oscillations provide a robust unifying paradigm for the study of cortical function.

Sex differences in endogenous cortical network activity: spontaneously recurring Up/Down states

BACKGROUND

Several molecular and cellular processes in the vertebrate brain exhibit differences between males and females, leading to sexual dimorphism in the formation of neural circuits and brain organization. While studies on large-scale brain networks provide ample evidence for both structural and functional sex differences, smaller-scale local networks have remained largely unexplored. In the current study, we investigate sexual dimorphism in cortical dynamics by means of spontaneous Up/Down states, a type of network activity that is exhibited during slow-wave sleep, quiet wakefulness, and anesthesia and is thought to represent the default activity of the cortex.

METHODS

Up state activity was monitored by local field potential recordings in coronal brain slices of male and female mice across three ages with distinct secretion profiles of sex hormones: (i) pre-puberty (17-21 days old), (ii) 3-9 adult (months old), and (iii) old (19-24 months old).

RESULTS

Female mice of all ages exhibited longer and more frequent Up states compared to aged-matched male mice. Power spectrum analysis revealed sex differences in the relative power of Up state events, with female mice showing reduced power in the delta range (1-4 Hz) and increased power in the theta range (4-8 Hz) compared to male mice. No sex differences were found in the characteristics of Up state peak voltage and latency.

CONCLUSIONS

The present study revealed for the first time sex differences in intracortical network activity, using an ex vivo paradigm of spontaneously occurring Up/Down states. We report significant sex differences in Up state properties that are already present in pre-puberty animals and are maintained through adulthood and old age.

Slow and Fast Neocortical Oscillations in the Senescence-Accelerated Mouse Model SAMP8

The senescence-accelerated mouse prone 8 (SAMP8) model is characterized by accelerated, progressive cognitive decline as well as Alzheimer’s disease (AD)-like neurodegenerative changes, and resembles the etiology of multicausal, sporadic late-onset/age-related AD in humans. Our aim was to find whether these AD-like pathological features, together with the cognitive deficits present in the SAMP8 strain, are accompanied by disturbances in cortical network activity with respect to control mice (SAM resistance 1, SAMR1) and, if so, how the alterations in cortical activity progress with age. For this purpose, we characterized the extracellular spontaneous oscillatory activity in different regions of the cerebral cortex of SAMP8 and SAMR1 mice under ketamine anesthesia at 5 and 7 months of age. Under these conditions, slow oscillations and fast rhythms generated in the cortical network were recorded and different parameters of these oscillations were quantified and compared between SAMP8 and their control, SAMR1 mice. The average frequency of slow oscillations in SAMP8 mice was decreased with respect to the control mice at both studied ages. An elongation of the silent periods or Down states was behind the decreased slow oscillatory frequency while the duration of active or Up states remained stable. SAMP8 mice also presented increased cycle variability and reduced high frequency components during Down states. During Up states, the power peak in the gamma range was displaced towards lower frequencies in all the cortical areas of SAMP8 with respect to control mice suggesting that the spectral profile of SAMP8 animals is shifted towards lower frequencies. This shift is reminiscent to one of the principal hallmarks of electroencephalography (EEG) abnormalities in patients with Alzheimer’s disease, and adds evidence in support of the suitability of the SAMP8 mouse as a model of this disease. Although some of the differences between SAMP8 and control mice were emphasized with age, the evolution of the studied parameters as SAMR1 mice got older indicates that the SAMR1 phenotype tends to converge with that of SAMP8 animals. To our knowledge, this is the first systematic characterization of the cortical slow and fast rhythms in the SAMP8 strain and it provides useful insights about the cellular and synaptic mechanisms underlying the reported alterations.

Different Effects of Sleep Deprivation and Torpor on EEG Slow-Wave Characteristics in Djungarian Hamsters

It has been shown previously in Djungarian hamsters that the initial electroencephalography (EEG) slow-wave activity (power in the 0.5–4.0 Hz band; SWA) in non-rapid eye movement (NREM) sleep following an episode of daily torpor is consistently enhanced, similar to the SWA increase after sleep deprivation (SD). However, it is unknown whether the network mechanisms underlying the SWA increase after torpor and SD are similar. EEG slow waves recorded in the neocortex during sleep reflect synchronized transitions between periods of activity and silence among large neuronal populations. We therefore set out to investigate characteristics of individual cortical EEG slow waves recorded during NREM sleep after 4 h SD and during sleep after emergence from an episode of daily torpor in adult male Djungarian hamsters. We found that during the first hour after both SD and torpor, the SWA increase was associated with an increase in slow-wave incidence and amplitude. However, the slopes of single slow waves during NREM sleep were steeper in the first hour after SD but not after torpor, and, in contrast to sleep after SD, the magnitude of change in slopes after torpor was unrelated to the changes in SWA. Furthermore, slow-wave slopes decreased progressively within the first 2 h after SD, while a progressive increase in slow-wave slopes was apparent during the first 2 h after torpor. The data suggest that prolonged waking and torpor have different effects on cortical network activity underlying slow-wave characteristics, while resulting in a similar homeostatic sleep response of SWA. We suggest that sleep plays an important role in network homeostasis after both waking and torpor, consistent with a recovery function for both states.

Layer-specific optogenetic activation of pyramidal neurons causes beta-gamma entrainment of neonatal networks

Coordinated activity patterns in the developing brain may contribute to the wiring of neuronal circuits underlying future behavioural requirements. However, causal evidence for this hypothesis has been difficult to obtain owing to the absence of tools for selective manipulation of oscillations during early development. We established a protocol that combines optogenetics with electrophysiological recordings from neonatal mice in vivo to elucidate the substrate of early network oscillations in the prefrontal cortex. We show that light-induced activation of layer II/III pyramidal neurons that are transfected by in utero electroporation with a high-efficiency channelrhodopsin drives frequency-specific spiking and boosts network oscillations within beta–gamma frequency range. By contrast, activation of layer V/VI pyramidal neurons causes nonspecific network activation. Thus, entrainment of neonatal prefrontal networks in fast rhythms relies on the activation of layer II/III pyramidal neurons. This approach used here may be useful for further interrogation of developing circuits, and their behavioural readout.

Oscillations in cortical activity during development are important for functional maturation. Here, the authors use optogenetics in neonatal mice to determine a causal role for pyramidal cell firing in different prelimbic cortex layers in generating beta–gamma range activity.

Overexpression of Dyrk1A, a Down Syndrome Candidate, Decreases Excitability and Impairs Gamma Oscillations in the Prefrontal Cortex

The dual-specificity tyrosine phosphorylation-regulated kinase DYRK1A is a serine/threonine kinase involved in neuronal differentiation and synaptic plasticity and a major candidate of Down syndrome brain alterations and cognitive deficits. DYRK1A is strongly expressed in the cerebral cortex, and its overexpression leads to defective cortical pyramidal cell morphology, synaptic plasticity deficits, and altered excitation/inhibition balance. These previous observations, however, do not allow predicting how the behavior of the prefrontal cortex (PFC) network and the resulting properties of its emergent activity are affected. Here, we integrate functional, anatomical, and computational data describing the prefrontal network alterations in transgenic mice overexpressingDyrk1A(TgDyrk1A). Usingin vivoextracellular recordings, we show decreased firing rate and gamma frequency power in the prefrontal network of anesthetized and awakeTgDyrk1Amice. Immunohistochemical analysis identified a selective reduction of vesicular GABA transporter punctae on parvalbumin positive neurons, without changes in the number of cortical GABAergic neurons in the PFC ofTgDyrk1Amice, which suggests that selective disinhibition of parvalbumin interneurons would result in an overinhibited functional network. Using a conductance-based computational model, we quantitatively demonstrate that this alteration could explain the observed functional deficits including decreased gamma power and firing rate. Our results suggest that dysfunction of cortical fast-spiking interneurons might be central to the pathophysiology of Down syndrome.

SIGNIFICANCE STATEMENT

DYRK1Ais a major candidate gene in Down syndrome. Its overexpression results into altered cognitive abilities, explained by defective cortical microarchitecture and excitation/inhibition imbalance. An open question is how these deficits impact the functionality of the prefrontal cortex network. Combining functional, anatomical, and computational approaches, we identified decreased neuronal firing rate and deficits in gamma frequency in the prefrontal cortices of transgenic mice overexpressingDyrk1A We also identified a reduction of vesicular GABA transporter punctae specifically on parvalbumin positive interneurons. Using a conductance-based computational model, we demonstrate that this decreased inhibition on interneurons recapitulates the observed functional deficits, including decreased gamma power and firing rate. Our results suggest that dysfunction of cortical fast-spiking interneurons might be central to the pathophysiology of Down syndrome.

Moderate Cortical Cooling Eliminates Thalamocortical Silent States during Slow Oscillation

Reduction in temperature depolarizes neurons by a partial closure of potassium channels but decreases the vesicle release probability within synapses. Compared with cooling, neuromodulators produce qualitatively similar effects on intrinsic neuronal properties and synapses in the cortex. We used this similarity of neuronal action in ketamine-xylazine-anesthetized mice and non-anesthetized mice to manipulate the thalamocortical activity. We recorded cortical electroencephalogram/local field potential (LFP) activity and intracellular activities from the somatosensory thalamus in control conditions, during cortical cooling and on rewarming. In the deeply anesthetized mice, moderate cortical cooling was characterized by reversible disruption of the thalamocortical slow-wave pattern rhythmicity and the appearance of fast LFP spikes, with frequencies ranging from 6 to 9 Hz. These LFP spikes were correlated with the rhythmic IPSP activities recorded within the thalamic ventral posterior medial neurons and with depolarizing events in the posterior nucleus neurons. Similar cooling of the cortex during light anesthesia rapidly and reversibly eliminated thalamocortical silent states and evoked thalamocortical persistent activity; conversely, mild heating increased thalamocortical slow-wave rhythmicity. In the non-anesthetized head-restrained mice, cooling also prevented the generation of thalamocortical silent states. We conclude that moderate cortical cooling might be used to manipulate slow-wave network activity and induce neuromodulator-independent transition to activated states. Significance statement: In this study, we demonstrate that moderate local cortical cooling of lightly anesthetized or naturally sleeping mice disrupts thalamocortical slow oscillation and induces the activated local field potential pattern. Mild heating has the opposite effect; it increases the rhythmicity of thalamocortical slow oscillation. Our results demonstrate that slow oscillation can be influenced by manipulations to the properties of cortical neurons without changes in neuromodulation.

Modeling the Spatiotemporal Dynamics of Light and Heat Propagation for In Vivo Optogenetics

Despite the increasing use of optogenetics in vivo, the effects of direct light exposure to brain tissue are understudied. Of particular concern is the potential for heat induced by prolonged optical stimulation. We demonstrate that high-intensity light, delivered through an optical fiber, is capable of elevating firing rate locally, even in the absence of opsin expression. Predicting the severity and spatial extent of any temperature increase during optogenetic stimulation is therefore of considerable importance. Here, we describe a realistic model that simulates light and heat propagation during optogenetic experiments. We validated the model by comparing predicted and measured temperature changes in vivo. We further demonstrate the utility of this model by comparing predictions for various wavelengths of light and fiber sizes, as well as testing methods for reducing heat effects on neural targets in vivo.

Brief anesthesia, but not voluntary locomotion, significantly alters cortical temperature

Changes in brain temperature can alter electrical properties of neurons and cause changes in behavior. However, it is not well understood how behaviors, like locomotion, or experimental manipulations, like anesthesia, alter brain temperature. We implanted thermocouples in sensorimotor cortex of mice to understand how cortical temperature was affected by locomotion, as well as by brief and prolonged anesthesia. Voluntary locomotion induced small (∼ 0.1 °C) but reliable increases in cortical temperature that could be described using a linear convolution model. In contrast, brief (90-s) exposure to isoflurane anesthesia depressed cortical temperature by ∼ 2 °C, which lasted for up to 30 min after the cessation of anesthesia. Cortical temperature decreases were not accompanied by a concomitant decrease in the γ-band local field potential power, multiunit firing rate, or locomotion behavior, which all returned to baseline within a few minutes after the cessation of anesthesia. In anesthetized animals where core body temperature was kept constant, cortical temperature was still > 1 °C lower than in the awake animal. Thermocouples implanted in the subcortex showed similar temperature changes under anesthesia, suggesting these responses occur throughout the brain. Two-photon microscopy of individual blood vessel dynamics following brief isoflurane exposure revealed a large increase in vessel diameter that ceased before the brain temperature significantly decreased, indicating cerebral heat loss was not due to increased cerebral blood vessel dilation. These data should be considered in experimental designs recording in anesthetized preparations, computational models relating temperature and neural activity, and awake-behaving methods that require brief anesthesia before experimental procedures.

Functional stem cell integration assessed by organotypic slice cultures

Re-formation or preservation of functional, electrically active neural networks has been proffered as one of the goals of stem cell-mediated neural therapeutics. A primary issue for a cell therapy approach is the formation of functional contacts between the implanted cells and the host tissue. Therefore, it is of fundamental interest to establish protocols that allow us to delineate a detailed time course of grafted stem cell survival, migration, differentiation, integration, and functional interaction with the host. One option for in vitro studies is to examine the integration of exogenous stem cells into an existing active neuronal network in ex vivo organotypic cultures. Organotypic cultures leave the structural integrity essentially intact while still allowing the microenvironment to be carefully controlled. This allows detailed studies over time of cellular responses and cell-cell interactions, which are not readily performed in vivo. This unit describes procedures for using organotypic slice cultures as ex vivo model systems for studying neural stem cell and embryonic stem cell engraftment and communication with CNS host tissue.