Spontaneous high-frequency (10-80 Hz) oscillations during up states in the cerebral cortex in vitro

Study of the Synchronization and Transmission of Intracellular Signaling Oscillations in Cells Using Bispectral Analysis

The oscillation synchronization analysis in biological systems will expand our knowledge about the response of living systems to changes in environmental conditions. This knowledge can be used in medicine (diagnosis, therapy, monitoring) and agriculture (increasing productivity, resistance to adverse effects). Currently, the search is underway for an informative, accurate and sensitive method for analyzing the synchronization of oscillatory processes in cell biology. It is especially pronounced in analyzing the concentration oscillations of intracellular signaling molecules in electrically nonexcitable cells. The bispectral analysis method could be applied to assess the characteristics of synchronized oscillations of intracellular mediators. We chose endothelial cells from mouse microvessels as model cells. Concentrations of well-studied calcium and nitric oxide (NO) were selected for study in control conditions and well-described stress: heating to 40 °C and hyperglycemia. The bispectral analysis allows us to accurately evaluate the proportion of synchronized cells, their synchronization degree, and the amplitude and frequency of synchronized calcium and NO oscillations. Heating to 40 °C increased cell synchronization for calcium but decreased for NO oscillations. Hyperglycemia abolished this effect. Heating to 40 °C changed the frequencies and increased the amplitudes of synchronized oscillations of calcium concentration and the NO synthesis rate. The first part of this paper describes the principles of the bispectral analysis method and equations and modifications of the method we propose. In the second part of this paper, specific examples of the application of bispectral analysis to assess the synchronization of living cells in vitro are presented. The discussion compares the capabilities of bispectral analysis with other analytical methods in this field.

Endogenous noise of neocortical neurons correlates with atypical sensory response variability in the Fmr1-/y mouse model of autism

Excessive neural variability of sensory responses is a hallmark of atypical sensory processing in autistic individuals with cascading effects on other core autism symptoms but unknown neurobiological substrate. Here, by recording neocortical single neuron activity in a well-established mouse model of Fragile X syndrome and autism, we characterized atypical sensory processing and probed the role of endogenous noise sources in exaggerated response variability in males. The analysis of sensory stimulus evoked activity and spontaneous dynamics, as well as neuronal features, reveals a complex cellular and network phenotype. Neocortical sensory information processing is more variable and temporally imprecise. Increased trial-by-trial and inter-neuronal response variability is strongly related to key endogenous noise features, and may give rise to behavioural sensory responsiveness variability in autism. We provide a novel preclinical framework for understanding the sources of endogenous noise and its contribution to core autism symptoms, and for testing the functional consequences for mechanism-based manipulation of noise.

Human acute microelectrode array recordings with broad cortical access, single-unit resolution, and parallel behavioral monitoring

There are vast gaps in our understanding of the organization and operation of the human nervous system at the level of individual neurons and their networks. Here, we report reliable and robust acute multichannel recordings using planar microelectrode arrays (MEAs) implanted intracortically in awake brain surgery with open craniotomies that grant access to large parts of the cortical hemisphere. We obtained high-quality extracellular neuronal activity at the microcircuit, local field potential level and at the cellular, single-unit level. Recording from the parietal association cortex, a region rarely explored in human single-unit studies, we demonstrate applications on these complementary spatial scales and describe traveling waves of oscillatory activity as well as single-neuron and neuronal population responses during numerical cognition, including operations with uniquely human number symbols. Intraoperative MEA recordings are practicable and can be scaled up to explore cellular and microcircuit mechanisms of a wide range of human brain functions.

The psychotomimetic ketamine disrupts the transfer of late sensory information in the corticothalamic network

In prodromal and early schizophrenia, disorders of attention and perception are associated with structural and chemical brain abnormalities and with dysfunctional corticothalamic networks exhibiting disturbed brain rhythms. The underlying mechanisms are elusive. The non-competitive NMDA receptor antagonist ketamine simulates the symptoms of prodromal and early schizophrenia, including disturbances in ongoing and task & sensory-related broadband beta-/gamma-frequency (17-29 Hz/30-80 Hz) oscillations in corticothalamic networks. In normal healthy subjects and rodents, complex integration processes, like sensory perception, induce transient, large-scale synchronised beta/gamma oscillations in a time window of a few hundred ms (200-700 ms) after the presentation of the object of attention (e.g., sensory stimulation). Our goal was to use an electrophysiological multisite network approach to investigate, in lightly anesthetised rats, the effects of a single psychotomimetic dose (2.5 mg/kg, subcutaneous) of ketamine on sensory stimulus-induced oscillations. Ketamine transiently increased the power of baseline beta/gamma oscillations and decreased sensory-induced beta/gamma oscillations. In addition, it disrupted information transferability in both the somatosensory thalamus and the related cortex and decreased the sensory-induced thalamocortical connectivity in the broadband gamma range. The present findings support the hypothesis that NMDA receptor antagonism disrupts the transfer of perceptual information in the somatosensory cortico-thalamo-cortical system.

Deterministic and Stochastic Components of Cortical Down States: Dynamics and Modulation

Slow oscillations are an emergent activity of the cerebral cortex network consisting of alternating periods of activity (Up states) and silence (Down states). Up states are periods of persistent cortical activity that share properties with that of underlying wakefulness. However, the occurrence of Down states is almost invariably associated with unconsciousness, both in animal models and clinical studies. Down states have been attributed relevant functions, such as being a resetting mechanism or breaking causal interactions between cortical areas. But what do Down states consist of? Here, we explored in detail the network dynamics (e.g., synchronization and phase) during these silent periods in vivo (male mice), in vitro (ferrets, either sex), and in silico, investigating various experimental conditions that modulate them: anesthesia levels, excitability (electric fields), and excitation/inhibition balance. We identified metastability as two complementary phases composing such quiescence states: a highly synchronized "deterministic" period followed by a low-synchronization "stochastic" period. The balance between these two phases determines the dynamical properties of the resulting rhythm, as well as the responsiveness to incoming inputs or refractoriness. We propose detailed Up and Down state cycle dynamics that bridge cortical properties emerging at the mesoscale with their underlying mechanisms at the microscale, providing a key to understanding unconscious states.SIGNIFICANCE STATEMENT The cerebral cortex expresses slow oscillations consisting of Up (active) and Down (silent) states. Such activity emerges not only in slow wave sleep, but also under anesthesia and in brain lesions. Down states functionally disconnect the network, and are associated with unconsciousness. Based on a large collection of data, novel data analysis approaches and computational modeling, we thoroughly investigate the nature of Down states. We identify two phases: a highly synchronized "deterministic" period, followed by a low-synchronization "stochastic" period. The balance between these two phases determines the dynamic properties of the resulting rhythm and responsiveness to incoming inputs. This finding reconciles different theories of slow rhythm generation and provides clues about how the brain switches from conscious to unconscious brain states.

Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity

Metamemory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical stimulation (tES) during sleep, but evidence for improvements to metamemory sensitivity is limited. Applying tES can enhance sleep-dependent memory consolidation, which along with metamemory requires the coordination of activity across distributed neural systems, suggesting that examining functional connectivity is important for understanding these processes. Nevertheless, little research has examined how functional connectivity modulations relate to overnight changes in metamemory sensitivity. Here, we developed a closed-loop short-duration tES method, time-locked to up-states of ongoing slow-wave oscillations, to cue specific memory replays in humans. We measured electroencephalographic (EEG) coherence changes following stimulation pulses, and characterized network alterations with graph theoretic metrics. Using machine learning techniques, we show that pulsed tES elicited network changes in multiple frequency bands, including increased connectivity in the theta band and increased efficiency in the spindle band. Additionally, stimulation-induced changes in beta-band path length were predictive of overnight changes in metamemory sensitivity. These findings add new insights into the growing literature investigating increases in memory performance through brain stimulation during sleep, and highlight the importance of examining functional connectivity to explain its effects.

Numerous studies have demonstrated a clear link between sleep and memory—namely, memories are consolidated during sleep, leading to more stable and long-lasting representations. We have previously shown that tagging episodes with specific patterns of brain stimulation during encoding and replaying those patterns during sleep can enhance this consolidation process to improve confidence and decision-making of memories (metamemory). Here, we extend this work to examine network-level brain changes that occur following stimulation during sleep that predict metamemory improvements. Using graph theoretic and machine-learning methods, we found that stimulation-induced changes in beta-band path length predicted overnight improvements in metamemory. This novel finding sheds new light on the neural mechanisms of memory consolidation and suggests potential applications for improving metamemory.

The essential role of hippocampo-cortical connections in temporal coordination of spindles and ripples

The predominant activity of slow wave sleep is cortical slow oscillations (SOs), thalamic spindles and hippocampal sharp wave ripples. While the precise temporal nesting of these rhythms was shown to be essential for memory consolidation, the coordination mechanism is poorly understood. Here we develop a minimal hippocampo-cortico-thalamic network that can explain the mechanism underlying the SO-spindle-ripple coupling indicating of the succession of regional neuronal interactions. Further we verify the model predictions experimentally in naturally sleeping rodents showing our simple model provides a quantitative match to several experimental observations including the nesting of ripples in the spindle troughs and larger duration but lower amplitude of the ripples co-occurring with spindles or SOs compared to the isolated ripples. The model also predicts that the coupling of ripples to SOs and spindles monotonically enhances by increasing the strength of hippocampo-cortical connections while it is stronger at intermediate values of the cortico-hippocampal projections.

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.

Medium spiny neurons activity reveals the discrete segregation of mouse dorsal striatum

Behavioral studies differentiate the rodent dorsal striatum (DS) into lateral and medial regions; however, anatomical evidence suggests that it is a unified structure. To understand striatal dynamics and basal ganglia functions, it is essential to clarify the circuitry that supports this behavioral-based segregation. Here, we show that the mouse DS is made of two non-overlapping functional circuits divided by a boundary. Combining in vivo optopatch-clamp and extracellular recordings of spontaneous and evoked sensory activity, we demonstrate different coupling of lateral and medial striatum to the cortex together with an independent integration of the spontaneous activity, due to particular corticostriatal connectivity and local attributes of each region. Additionally, we show differences in slow and fast oscillations and in the electrophysiological properties between striatonigral and striatopallidal neurons. In summary, these results demonstrate that the rodent DS is segregated in two neuronal circuits, in homology with the caudate and putamen nuclei of primates.

Early Disruption of Cortical Sleep-Related Oscillations in a Mouse Model of Dementia With Lewy Bodies (DLB) Expressing Human Mutant (A30P) Alpha-Synuclein

Changes in sleep behavior and sleep-related cortical activity have been reported in conditions associated with abnormal alpha-synuclein (α-syn) expression, in particular Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). Notably, changes can occur in patients years before the onset of cognitive decline. Sleep-related network oscillations play a key role in memory function, but how abnormal α-syn impacts the generation of such activity is currently unclear. To determine whether early changes in sleep-related network activity could also be observed, prior to any previously reported cognitive dysfunction, we used mice that over-express human mutant α-syn (A30P). Recordings in vivo were performed under urethane anesthesia in the medial prefrontal cortex (mPFC) and CA1 region of the hippocampus in young male (2.5 – 4 months old) A30P and age-matched wild type (WT) mice. We found that the slow oscillation (SO) < 1 Hz frequency was significantly faster in both the mPFC and hippocampus in A30P mice, and Up-state-associated fast oscillations at beta (20 – 30 Hz) and gamma (30 – 80 Hz) frequencies were delayed relative to the onset of the Up-state. Spindle (8 – 15 Hz) activity in the mPFC was also altered in A30P mice, as spindles were shorter in duration and had reduced density compared to WT. These changes demonstrate that dysregulation of sleep-related oscillations occurs in young A30P mice long before the onset of cognitive dysfunction. Our data suggest that, as seen in patients, changes in sleep-related oscillations are an early consequence of abnormal α-syn aggregation in A30P mice.

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.

Effect of interpopulation spike-timing-dependent plasticity on synchronized rhythms in neuronal networks with inhibitory and excitatory populations

We consider a two-population network consisting of both inhibitory (I) interneurons and excitatory (E) pyramidal cells. This I-E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation spike-timing-dependent plasticity (STDP). In previous works without STDPs, fast sparsely synchronized rhythms, related to diverse cognitive functions, were found to appear in a range of noise intensity D for static synaptic strengths. Here, by varying D, we investigate the effect of interpopulation STDPs on fast sparsely synchronized rhythms that emerge in both the I- and the E-populations. Depending on values of D, long-term potentiation (LTP) and long-term depression (LTD) for population-averaged values of saturated interpopulation synaptic strengths are found to occur. Then, the degree of fast sparse synchronization varies due to effects of LTP and LTD. In a broad region of intermediate D, the degree of good synchronization (with higher synchronization degree) becomes decreased, while in a region of large D, the degree of bad synchronization (with lower synchronization degree) gets increased. Consequently, in each I- or E-population, the synchronization degree becomes nearly the same in a wide range of D (including both the intermediate and the large D regions). This kind of "equalization effect" is found to occur via cooperative interplay between the average occupation and pacing degrees of spikes (i.e., the average fraction of firing neurons and the average degree of phase coherence between spikes in each synchronized stripe of spikes in the raster plot of spikes) in fast sparsely synchronized rhythms. Finally, emergences of LTP and LTD of interpopulation synaptic strengths (leading to occurrence of equalization effect) are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic spike times.

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.

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.

Bridging Single Neuron Dynamics to Global Brain States

Biological neural networks produce information backgrounds of multi-scale spontaneous activity that become more complex in brain states displaying higher capacities for cognition, for instance, attentive awake versus asleep or anesthetized states. Here, we review brain state-dependent mechanisms spanning ion channel currents (microscale) to the dynamics of brain-wide, distributed, transient functional assemblies (macroscale). Not unlike how microscopic interactions between molecules underlie structures formed in macroscopic states of matter, using statistical physics, the dynamics of microscopic neural phenomena can be linked to macroscopic brain dynamics through mesoscopic scales. Beyond spontaneous dynamics, it is observed that stimuli evoke collapses of complexity, most remarkable over high dimensional, asynchronous, irregular background dynamics during consciousness. In contrast, complexity may not be further collapsed beyond synchrony and regularity characteristic of unconscious spontaneous activity. We propose that increased dimensionality of spontaneous dynamics during conscious states supports responsiveness, enhancing neural networks' emergent capacity to robustly encode information over multiple scales.

Dopamine receptor antagonists effects on low-dimensional attractors of local field potentials in optogenetic mice

The goal of this study was to investigate the effects of acute cocaine injection or dopamine (DA) receptor antagonists on the medial prefrontal cortex (mPFC) gamma oscillations and their relationship to short term neuroadaptation that may mediate addiction. For this purpose, optogenetically evoked local field potentials (LFPs) in response to a brief 10 ms laser light pulse were recorded from 17 mice. D1-like receptor antagonist SCH 23390 or D2-like receptor antagonist sulpiride, or both, were administered either before or after cocaine. A Euclidian distance-based dendrogram classifier separated the 100 trials for each animal in disjoint clusters. When baseline and DA receptor antagonists trials were combined in a single trial, a minimum of 20% overlap occurred in some dendrogram clusters, which suggests a possible common, invariant, dynamic mechanism shared by both baseline and DA receptor antagonists data. The delay-embedding method of neural activity reconstruction was performed using the correlation time and mutual information to determine the lag/correlation time of LFPs and false nearest neighbors to determine the embedding dimension. We found that DA receptor antagonists applied before cocaine cancels out the effect of cocaine and leaves the lag time distributions at baseline values. On the other hand, cocaine applied after DA receptor antagonists shifts the lag time distributions to longer durations, i.e. increase the correlation time of LFPs. Fourier analysis showed that a reasonable accurate decomposition of the LFP data can be obtained with a relatively small (less than ten) Fourier coefficients.

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.

Kainate receptors have different modulatory effect in seizure-like events and slow rhythmic activity in entorhinal cortex ex vivo

In the neocortex, neurons form functional networks, the members of which exhibit a variable degree of synchronization. Slow rhythmic activity may be regarded as a balanced interplay of excitatory and inhibitory neuronal network activity, which is essential in learning and memory consolidation. On the other hand, seizures may be considered as hypersynchronized network states occurring in epileptic diseases. The brain slice method and multi-electrode array (MEA) systems offer a good opportunity for the modelling of cortical spontaneous activities by examining their initiation and propagation. Our main goals were to characterise and compare spontaneous activities developing in different conditions and cortical network states. The role of kainate receptors in these processes was also tested. According to our results, there are demonstrable dissimilarities between slow rhythmic activities vs. seizure-like events developing in the rat entorhinal cortex ex vivo in normal vs. epileptic conditions. Propagation velocity, time scale, activity pattern and pharmacological sensitivity are all different. Kainate receptors play a role in network activity in entorhinal cortex, they are capable to prolong the duration of the events of epileptiform activity. Their regulatory effect is more prominent under epileptic than under normal conditions.

Distribution of GABAergic Neurons and VGluT1 and VGAT Immunoreactive Boutons in the Ferret (Mustela putorius) Piriform Cortex and Endopiriform Nucleus. Comparison With Visual Areas 17, 18 and 19

We studied the cellular organization of the piriform network [comprising the piriform cortex (PC) and endopiriform nucleus (EP)] of the ferret (Mustela putorius)-a highly excitable region prone to seizures-and, more specifically, the distribution and morphology of different types of gamma-aminobutyric acid (GABA)ergic neurons, and the distribution and ratio of glutamatergic and GABAergic boutons, and we compared our findings to those in primary visual area 17, and secondary areas 18 and 19. We accomplished this by using cytochrome oxidase and immunohistochemistry for mature neuronal nuclei (NeuN), GABAergic neurons [glutamic acid decarboxylase-67 (GAD67), calretinin (CR) and parvalbumin (PV)], and for excitatory (vesicular glutamate transporter 1; VGluT1) and inhibitory (vesicular GABA transporter; VGAT) boutons. In the ferret, the cellular organization of the piriform network is similar to that described in other species such as cats, rats and opossums although some differences also exist. GABAergic immunolabeling showed similarities between cortical layers I-III of the PC and visual areas, such as the relative distribution of GABAergic neurons and the density and area of VGluT1- and VGAT-immunoreactive boutons. However, multiple differences between the piriform network and visual areas (layers I-VI) were found, such as the percentage of GABAergic neurons with respect to the total number of neurons and the ratio of VGluT1- and VGAT-immunoreactive boutons. These findings are relevant to better understand the high excitability of the piriform network.

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).

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.

Optogenetic Modulation of a Minor Fraction of Parvalbumin-Positive Interneurons Specifically Affects Spatiotemporal Dynamics of Spontaneous and Sensory-Evoked Activity in Mouse Somatosensory Cortex in Vivo

Parvalbumin (PV) positive interneurons exert strong effects on the neocortical excitatory network, but it remains unclear how they impact the spatiotemporal dynamics of sensory processing in the somatosensory cortex. Here, we characterized the effects of optogenetic inhibition and activation of PV interneurons on spontaneous and sensory-evoked activity in mouse barrel cortex in vivo. Inhibiting PV interneurons led to a broad-spectrum power increase both in spontaneous and sensory-evoked activity. Whisker-evoked responses were significantly increased within 20 ms after stimulus onset during inhibition of PV interneurons, demonstrating high temporal precision of PV-shaped inhibition. Multiunit activity was strongly enhanced in neighboring cortical columns, but not at the site of transduction, supporting a central and highly specific role of PV interneurons in lateral inhibition. Inversely, activating PV interneurons drastically decreased spontaneous and whisker-evoked activity in the principal column and exerted strong lateral inhibition. Histological assessment of transduced cells combined with quantitative modeling of light distribution and spike sorting revealed that only a minor fraction (~10%) of the local PV population comprising no more than a few hundred neurons is optogenetically modulated, mediating the observed prominent and widespread effects on neocortical processing.

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.

Cocaine-Induced Changes in Low-Dimensional Attractors of Local Field Potentials in Optogenetic Mice

Optogenetically evoked local field potential (LFP) recorded from the medial prefrontal cortex (mPFC) of mice during basal conditions and following a systemic cocaine administration were analyzed. Blue light stimuli were delivered to mPFC through a fiber optic every 2 s and each trial was repeated 100 times. As in the previous study, we used a surrogate data method to check that nonlinearity was present in the experimental LFPs and only used the last 1.5 s of steady activity to measure the LFPs phase resetting induced by the brief 10 ms light stimulus. We found that the steady dynamics of the mPFC in response to light stimuli could be reconstructed in a three-dimensional phase space with topologically similar "8"-shaped attractors across different animals. Therefore, cocaine did not change the complexity of the recorded nonlinear data compared to the control case. The phase space of the reconstructed attractor is determined by the LFP time series and its temporally shifted versions by a multiple of some lag time. We also compared the change in the attractor shape between cocaine-injected and control using (1) dendrogram clustering and (2) Frechet distance. We found about 20% overlap between control and cocaine trials when classified using dendrogram method, which suggest that it may be possible to describe mathematically both data sets with the same model and slightly different model parameters. We also found that the lag times are about three times shorter for cocaine trials compared to control. As a result, although the phase space trajectories for control and cocaine may look similar, their dynamics is significantly different.

New functions of Semaphorin 3E and its receptor PlexinD1 during developing and adult hippocampal formation

The development and maturation of cortical circuits relies on the coordinated actions of long and short range axonal guidance cues. In this regard, the class 3 semaphorins and their receptors have been seen to be involved in the development and maturation of the hippocampal connections. However, although the role of most of their family members have been described, very few data about the participation of Semaphorin 3E (Sema3E) and its receptor PlexinD1 during the development and maturation of the entorhino-hippocampal (EH) connection are available. In the present study, we focused on determining their roles both during development and in adulthood. We determined a relevant role for Sema3E/PlexinD1 in the layer-specific development of the EH connection. Indeed, mice lacking Sema3E/PlexinD1 signalling showed aberrant layering of entorhinal axons in the hippocampus during embryonic and perinatal stages. In addition, absence of Sema3E/PlexinD1 signalling results in further changes in postnatal and adult hippocampal formation, such as numerous misrouted ectopic mossy fibers. More relevantly, we describe how subgranular cells express PlexinD1 and how the absence of Sema3E induces a dysregulation of the proliferation of dentate gyrus progenitors leading to the presence of ectopic cells in the molecular layer. Lastly, Sema3E mutant mice displayed increased network excitability both in the dentate gyrus and the hippocampus proper.

Induced cortical oscillations in turtle cortex are coherent at the mesoscale of population activity, but not at the microscale of the membrane potential of neurons

Bursts of oscillatory neural activity have been hypothesized to be a core mechanism by which remote brain regions can communicate. Such a hypothesis raises the question to what extent oscillations are coherent across spatially distant neural populations. To address this question, we obtained local field potential (LFP) and membrane potential recordings from the visual cortex of turtle in response to visual stimulation of the retina. The time-frequency analysis of these recordings revealed pronounced bursts of oscillatory neural activity and a large trial-to-trial variability in the spectral and temporal properties of the observed oscillations. First, local bursts of oscillations varied from trial to trial in both burst duration and peak frequency. Second, oscillations of a given recording site were not autocoherent; i.e., the phase did not progress linearly in time. Third, LFP oscillations at spatially separate locations within the visual cortex were more phase coherent in the presence of visual stimulation than during ongoing activity. In contrast, the membrane potential oscillations from pairs of simultaneously recorded pyramidal neurons showed smaller phase coherence, which did not change when switching from black screen to visual stimulation. In conclusion, neuronal oscillations at distant locations in visual cortex are coherent at the mesoscale of population activity, but coherence is largely absent at the microscale of the membrane potential of neurons.NEW & NOTEWORTHY Coherent oscillatory neural activity has long been hypothesized as a potential mechanism for communication across locations in the brain. In this study we confirm the existence of coherent oscillations at the mesoscale of integrated cortical population activity. However, at the microscopic level of neurons, we find no evidence for coherence among oscillatory membrane potential fluctuations. These results raise questions about the applicability of the communication through coherence hypothesis to the level of the membrane potential.

UP-DOWN cortical dynamics reflect state transitions in a bistable network

In the idling brain, neuronal circuits transition between periods of sustained firing (UP state) and quiescence (DOWN state), a pattern the mechanisms of which remain unclear. Here we analyzed spontaneous cortical population activity from anesthetized rats and found that UP and DOWN durations were highly variable and that population rates showed no significant decay during UP periods. We built a network rate model with excitatory (E) and inhibitory (I) populations exhibiting a novel bistable regime between a quiescent and an inhibition-stabilized state of arbitrarily low rate. Fluctuations triggered state transitions, while adaptation in E cells paradoxically caused a marginal decay of E-rate but a marked decay of I-rate in UP periods, a prediction that we validated experimentally. A spiking network implementation further predicted that DOWN-to-UP transitions must be caused by synchronous high-amplitude events. Our findings provide evidence of bistable cortical networks that exhibit non-rhythmic state transitions when the brain rests.

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.

High-Throughput Analysis of in-vitro LFP Electrophysiological Signals: A validated workflow/software package

Synchronized brain activity in the form of alternating epochs of massive persistent network activity and periods of generalized neural silence, has been extensively studied as a fundamental form of circuit dynamics, important for many cognitive functions including short-term memory, memory consolidation, or attentional modulation. A key element in such studies is the accurate determination of the timing and duration of those network events. The local field potential (LFP) is a particularly attractive method for recording network activity, because it allows for long and stable recordings from multiple sites, allowing researchers to estimate the functional connectivity of local networks. Here, we present a computational method for the automatic detection and quantification of in-vitro LFP events, aiming to overcome the limitations of current approaches (e.g. slow analysis speed, arbitrary threshold-based detection and lack of reproducibility across and within experiments). The developed method is based on the implementation of established signal processing and machine learning approaches, is fully automated and depends solely on the data. In addition, it is fast, highly efficient and reproducible. The performance of the software is compared against semi-manual analysis and validated by verification of prior biological knowledge.

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.

Dorsal vs. ventral differences in fast Up-state-associated oscillations in the medial prefrontal cortex of the urethane-anesthetized rat

We demonstrate, in the urethane-anesthetized rat, that within the medial prefrontal cortex (mPFC) there are clear subregional differences in the fast network oscillations associated with the slow oscillation Up-state. These differences, particularly between the dorsal and ventral subregions of the mPFC, may reflect the different functions and connectivity of these subregions.

Cortical slow oscillations (0.1–1 Hz), which may play a role in memory consolidation, are a hallmark of non-rapid eye movement (NREM) sleep and also occur under anesthesia. During slow oscillations the neuronal network generates faster oscillations on the active Up-states and these nested oscillations are particularly prominent in the PFC. In rodents the medial prefrontal cortex (mPFC) consists of several subregions: anterior cingulate cortex (ACC), prelimbic (PrL), infralimbic (IL), and dorsal peduncular cortices (DP). Although each region has a distinct anatomy and function, it is not known whether slow or fast network oscillations differ between subregions in vivo. We have simultaneously recorded slow and fast network oscillations in all four subregions of the rodent mPFC under urethane anesthesia. Slow oscillations were synchronous between the mPFC subregions, and across the hemispheres, with no consistent amplitude difference between subregions. Delta (2–4 Hz) activity showed only small differences between subregions. However, oscillations in the spindle (6–15 Hz)-, beta (20–30 Hz), gamma (30–80 Hz)-, and high-gamma (80–150 Hz)-frequency bands were consistently larger in the dorsal regions (ACC and PrL) compared with ventral regions (IL and DP). In dorsal regions the peak power of spindle, beta, and gamma activity occurred early after onset of the Up-state. In the ventral regions, especially the DP, the oscillatory power in the spindle-, beta-, and gamma-frequency ranges peaked later in the Up-state. These results suggest variations in fast network oscillations within the mPFC that may reflect the different functions and connectivity of these subregions.

NEW & NOTEWORTHY We demonstrate, in the urethane-anesthetized rat, that within the medial prefrontal cortex (mPFC) there are clear subregional differences in the fast network oscillations associated with the slow oscillation Up-state. These differences, particularly between the dorsal and ventral subregions of the mPFC, may reflect the different functions and connectivity of these subregions.

Synchronized gamma-frequency inhibition in neocortex depends on excitatory-inhibitory interactions but not electrical synapses

Synaptic inhibition plays a crucial role in the precise timing of spiking activity in the cerebral cortex. Synchronized, rhythmic inhibitory activity in the gamma (30-80 Hz) range is thought to be especially important for the active, information-processing neocortex, but the circuit mechanisms that give rise to synchronized inhibition are uncertain. In particular, the relative contributions of reciprocal inhibitory connections, excitatory-inhibitory interactions, and electrical synapses to precise spike synchrony among inhibitory interneurons are not well understood. Here we describe experiments on mouse barrel cortex in vitro as it spontaneously generates slow (<1 Hz) oscillations (Up and Down states). During Up states, inhibitory postsynaptic currents (IPSCs) are generated at gamma frequencies and are more synchronized than excitatory postsynaptic currents (EPSCs) among neighboring pyramidal cells. Furthermore, spikes in homotypic pairs of interneurons are more synchronized than in pairs of pyramidal cells. Comparing connexin36 knockout and wild-type animals, we found that electrical synapses make a minimal contribution to synchronized inhibition during Up states. Estimations of the delays between EPSCs and IPSCs in single pyramidal cells showed that excitation often preceded inhibition by a few milliseconds. Finally, tonic optogenetic activation of different interneuron subtypes in the absence of excitation led to only weak synchrony of IPSCs in pairs of pyramidal neurons. Our results suggest that phasic excitatory inputs are indispensable for synchronized spiking in inhibitory interneurons during Up states and that electrical synapses play a minimal role.

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.

High-Affinity Nicotinic Receptors Modulate Spontaneous Cortical Up States In Vitro

Nicotinic acetylcholine receptors (nAChRs) play an important role in the modulation of many cognitive functions but their role in integrated network activity remains unclear. This is at least partly because of the complexity of the cholinergic circuitry and the difficulty in comparing results from in vivo studies obtained under diverse experimental conditions and types of anesthetics. Hence the role of nAChRs in the synchronization of cortical activity during slow-wave sleep is still controversial, with some studies showing they are involved in ACh-dependent EEG desynchronization, and others suggesting that this effect is mediated exclusively by muscarinic receptors. Here we use an in vitro model of endogenous network activity, in the form of recurring self-maintained depolarized states (Up states), which allows us to examine the role of high-affinity nAChRs on network dynamics in a simpler form of the cortical microcircuit. We find that mice lacking nAChRs containing the β2-subunit (β2-nAChRs) have longer and more frequent Up states, and that this difference is eliminated when β2-nAChRs in wild-type mice are blocked. We further show that endogenously released ACh can modulate Up/Down states through the activation of both β2- and α7-containing nAChRs, but through distinct mechanisms: α7-nAChRs affect only the termination of spontaneous Up states, while β2-nAChRs also regulate their generation. Finally we provide evidence that the effects of β2-subunit-containing, but not α7-subunit-containing nAChRs, are mediated through GABAB receptors. To our knowledge this is the first study documenting direct nicotinic modulation of Up/Down state activity.

SIGNIFICANCE STATEMENT

Through our experiments we were able to uncover a clear and previously disputed effect of nicotinic signaling in synchronized activity of neuronal networks of the cortex. We show that both high-affinity receptors (containing the β2-subunit, β2-nAChRs) and low-affinity receptors (containing the α7-subunit, α7-nAChRs) can regulate cortical network function exhibited in the form of Up/Down states. We further show that the effects of β2-nAChRs, but not α7-nAChRs, are mediated through the activation of GABAB receptors. These results suggest a possible synthesis of seemingly contradictory results in the literature and could be valuable for informing computational models of cortical function and for guiding the search for therapeutic interventions.

Spontaneous Up states in vitro: a single-metric index of the functional maturation and regional differentiation of the cerebral cortex

Understanding the development and differentiation of the neocortex remains a central focus of neuroscience. While previous studies have examined isolated aspects of cellular and synaptic organization, an integrated functional index of the cortical microcircuit is still lacking. Here we aimed to provide such an index, in the form of spontaneously recurring periods of persistent network activity -or Up states- recorded in mouse cortical slices. These coordinated network dynamics emerge through the orchestrated regulation of multiple cellular and synaptic elements and represent the default activity of the cortical microcircuit. To explore whether spontaneous Up states can capture developmental changes in intracortical networks we obtained local field potential recordings throughout the mouse lifespan. Two independent and complementary methodologies revealed that Up state activity is systematically modified by age, with the largest changes occurring during early development and adolescence. To explore possible regional heterogeneities we also compared the development of Up states in two distinct cortical areas and show that primary somatosensory cortex develops at a faster pace than primary motor cortex. Our findings suggest that in vitro Up states can serve as a functional index of cortical development and differentiation and can provide a baseline for comparing experimental and/or genetic mouse models.

The role of REM sleep theta activity in emotional memory

While non-REM (NREM) sleep has been strongly implicated in the reactivation and consolidation of memory traces, the role of rapid-eye movement (REM) sleep remains unclear. A growing body of research on humans and animals provide behavioral evidence for a role of REM sleep in the strengthening and modulation of emotional memories. Theta activity-which describes low frequency oscillations in the local field potential within the hippocampus, amygdala and neocortex-is a prominent feature of both wake and REM sleep in humans and rodents. Theta coherence between the hippocampus and amygdala drives large-scale pontine-geniculo-occipital (PGO) waves, the density of which predicts increases in plasticity-related gene expression. This could potentially facilitate the processing of emotional memory traces within the hippocampus during REM sleep. Further, the timing of hippocampal activity in relation to theta phase is vital in determining subsequent potentiation of neuronal activity. This could allow the emotionally modulated strengthening of novel and gradual weakening of consolidated hippocampal memory traces during REM sleep. Hippocampal theta activity is also correlated with REM sleep levels of achetylcholine - which is thought to reduce hippocampal inputs in the neocortex. The additional low levels of noradrenaline during REM sleep, which facilitate feedback within the neocortex, could allow the integration of novel memory traces previously consolidated during NREM sleep. We therefore propose that REM sleep mediates the prioritized processing of emotional memories within the hippocampus, the integration of previously consolidated memory traces within the neocortex, as well as the disengagement of consolidated neocortical memory traces from the hippocampus.

Impact of membrane bistability on dynamical response of neuronal populations

Neurons in many brain areas can develop a pronounced depolarized state of membrane potential (up state) in addition to the normal hyperpolarized state near the resting potential. The influence of the up state on signal encoding, however, is not well investigated. Here we construct a one-dimensional bistable neuron model and calculate the linear dynamical response to noisy oscillatory inputs analytically. We find that with the appearance of an up state, the transmission function is enhanced by the emergence of a local maximum at some optimal frequency and the phase lag relative to the input signal is reduced. We characterize the dependence of the enhancement of frequency response on intrinsic dynamics and on the occupancy of the up state.

Synaptic Mechanisms of Tight Spike Synchrony at Gamma Frequency in Cerebral Cortex

During the generation of higher-frequency (e.g., gamma) oscillations, cortical neurons can exhibit pairwise tight (<10 ms) spike synchrony. To understand how synaptic currents contribute to rhythmic activity and spike synchrony, we performed dual whole-cell recordings in mouse entorhinal cortical slices generating periodic activity (the slow oscillation). This preparation exhibited a significant amount of gamma-coherent spike synchrony during the active phase of the slow oscillation (Up state), particularly among fast-spiking inhibitory interneurons. IPSCs arriving in pairs of either pyramidal or fast-spiking neurons during the Up state were highly synchronized and exhibited significant coherence at frequencies from 10 to 100 Hz, peaking at ∼40 Hz, suggesting both synchronous discharge of, and synaptic divergence from, nearby inhibitory neurons. By inferring synaptic currents related to spike generation in simultaneously recorded pyramidal or fast-spiking neurons, we detected a decay of inhibition ∼20 ms before spiking. In fast-spiking interneurons, this was followed by an even larger excitatory input immediately before spike generation. Consistent with an important role for phasic excitation in driving spiking, we found that the correlation of excitatory inputs was highly predictive of spike synchrony in pairs of fast-spiking interneurons. Interestingly, spike synchrony in fast-spiking interneurons was not related to the strength of gap junctional coupling, and was still prevalent in connexin 36 knock-out animals. Our results support the pyramidal-interneuron gamma model of fast rhythmic oscillation in the cerebral cortex and suggest that spike synchrony and phase preference arises from the precise interaction of excitatory-inhibitory postsynaptic currents.

SIGNIFICANCE STATEMENT

We dissected the cellular and synaptic basis of spike synchrony occurring at gamma frequency (30-80 Hz). We used simultaneous targeted whole-cell recordings in an active slice preparation and analyzed the relationships between synaptic inputs and spike generation. We found that both pyramidal and fast-spiking neurons receive large, coherent inhibitory synaptic inputs at gamma frequency. In addition, we found that fast-spiking interneurons receive large, phasic excitatory synaptic inputs immediately before spike generation followed shortly by synaptic inhibition. These data support the principal-interneuron gamma generation model, and reveal how the synaptic connectivity between excitatory and inhibitory neurons supports the generation of gamma oscillations and spike synchrony.

A distinct class of slow (~0.2-2 Hz) intrinsically bursting layer 5 pyramidal neurons determines UP/DOWN state dynamics in the neocortex

During sleep and anesthesia, neocortical neurons exhibit rhythmic UP/DOWN membrane potential states. Although UP states are maintained by synaptic activity, the mechanisms that underlie the initiation and robust rhythmicity of UP states are unknown. Using a physiologically validated model of UP/DOWN state generation in mouse neocortical slices whereby the cholinergic tone present in vivo is reinstated, we show that the regular initiation of UP states is driven by an electrophysiologically distinct subset of morphologically identified layer 5 neurons, which exhibit intrinsic rhythmic low-frequency burst firing at ~0.2-2 Hz. This low-frequency bursting is resistant to block of glutamatergic and GABAergic transmission but is absent when slices are maintained in a low Ca(2+) medium (an alternative, widely used model of cortical UP/DOWN states), thus explaining the lack of rhythmic UP states and abnormally prolonged DOWN states in this condition. We also characterized the activity of various other pyramidal and nonpyramidal neurons during UP/DOWN states and found that an electrophysiologically distinct subset of layer 5 regular spiking pyramidal neurons fires earlier during the onset of network oscillations compared with all other types of neurons recorded. This study, therefore, identifies an important role for cell-type-specific neuronal activity in driving neocortical UP states.

Brain state dependent activity in the cortex and thalamus

Cortical and thalamocortical activity is highly state dependent, varying between patterns that are conducive to accurate sensory-motor processing, to states in which the brain is largely off-line and generating internal rhythms irrespective of the outside world. The generation of rhythmic activity occurs through the interaction of stereotyped patterns of connectivity together with intrinsic membrane and synaptic properties. One common theme in the generation of rhythms is the interaction of a positive feedback loop (e.g., recurrent excitation) with negative feedback control (e.g., inhibition, adaptation, or synaptic depression). The operation of these state-dependent activities has wide ranging effects from enhancing or blocking sensory-motor processing to the generation of pathological rhythms associated with psychiatric or neurological disorders.

The impact of cortical deafferentation on the neocortical slow oscillation

Slow oscillation is the main brain rhythm observed during deep sleep in mammals. Although several studies have demonstrated its neocortical origin, the extent of the thalamic contribution is still a matter of discussion. Using electrophysiological recordings in vivo on cats and computational modeling, we found that the local thalamic inactivation or the complete isolation of the neocortical slabs maintained within the brain dramatically reduced the expression of slow and fast oscillations in affected cortical areas. The slow oscillation began to recover 12 h after thalamic inactivation. The slow oscillation, but not faster activities, nearly recovered after 30 h and persisted for weeks in the isolated slabs. We also observed an increase of the membrane potential fluctuations recorded in vivo several hours after thalamic inactivation. Mimicking this enhancement in a network computational model with an increased postsynaptic activity of long-range intracortical afferents or scaling K(+) leak current, but not several other Na(+) and K(+) intrinsic currents was sufficient for recovering the slow oscillation. We conclude that, in the intact brain, the thalamus contributes to the generation of cortical active states of the slow oscillation and mediates its large-scale synchronization. Our study also suggests that the deafferentation-induced alterations of the sleep slow oscillation can be counteracted by compensatory intracortical mechanisms and that the sleep slow oscillation is a fundamental and intrinsic state of the neocortex.

On how correlations between excitatory and inhibitory synaptic inputs maximize the information rate of neuronal firing

Cortical neurons receive barrages of excitatory and inhibitory inputs which are not independent, as network structure and synaptic kinetics impose statistical correlations. Experiments in vitro and in vivo have demonstrated correlations between inhibitory and excitatory synaptic inputs in which inhibition lags behind excitation in cortical neurons. This delay arises in feed-forward inhibition (FFI) circuits and ensures that coincident excitation and inhibition do not preclude neuronal firing. Conversely, inhibition that is too delayed broadens neuronal integration times, thereby diminishing spike-time precision and increasing the firing frequency. This led us to hypothesize that the correlation between excitatory and inhibitory synaptic inputs modulates the encoding of information of neural spike trains. We tested this hypothesis by investigating the effect of such correlations on the information rate (IR) of spike trains using the Hodgkin-Huxley model in which both synaptic and membrane conductances are stochastic. We investigated two different synaptic input regimes: balanced synaptic conductances and balanced currents. Our results show that correlations arising from the synaptic kinetics, τ, and millisecond lags, δ, of inhibition relative to excitation strongly affect the IR of spike trains. In the regime of balanced synaptic currents, for short time lags (δ ~ 1 ms) there is an optimal τ that maximizes the IR of the postsynaptic spike train. Given the short time scales for monosynaptic inhibitory lags and synaptic decay kinetics reported in cortical neurons under physiological contexts, we propose that FFI in cortical circuits is poised to maximize the rate of information transfer between cortical neurons. Our results also provide a possible explanation for how certain drugs and genetic mutations affecting the synaptic kinetics can deteriorate information processing in the brain.

Circuit reactivation dynamically regulates synaptic plasticity in neocortex

Circuit reactivations involve a stereotyped sequence of neuronal firing and have been behaviourally linked to memory consolidation. Here we use multiphoton imaging and patch-clamp recording, and observe sparse and stereotyped circuit reactivations that correspond to UP states within active neurons. To evaluate the effect of the circuit on synaptic plasticity, we trigger a single spike-timing-dependent plasticity (STDP) pairing once per circuit reactivation. The pairings reliably fall within a particular epoch of the circuit sequence and result in long-term potentiation. During reactivation, the amplitude of plasticity significantly correlates with the preceding 20-25 ms of membrane depolarization rather than the depolarization at the time of pairing. This circuit-dependent plasticity provides a natural constraint on synaptic potentiation, regulating the inherent instability of STDP in an assembly phase-sequence model. Subthreshold voltage during endogenous circuit reactivations provides a critical informative context for plasticity and facilitates the stable consolidation of a spatiotemporal sequence.

Regulation of epileptiform discharges in rat neocortex by HCN channels

Hyperpolarization-activated, cyclic nucleotide-gated, nonspecific cation (HCN) channels have a well-characterized role in regulation of cellular excitability and network activity. The role of these channels in control of epileptiform discharges is less thoroughly understood. This is especially pertinent given the altered HCN channel expression in epilepsy. We hypothesized that inhibition of HCN channels would enhance bicuculline-induced epileptiform discharges. Whole cell recordings were obtained from layer (L)2/3 and L5 pyramidal neurons and L1 and L5 GABAergic interneurons. In the presence of bicuculline (10 μM), HCN channel inhibition with ZD 7288 (20 μM) significantly increased the magnitude (defined as area) of evoked epileptiform events in both L2/3 and L5 neurons. We recorded activity associated with epileptiform discharges in L1 and L5 interneurons to test the hypothesis that HCN channels regulate excitatory synaptic inputs differently in interneurons versus pyramidal neurons. HCN channel inhibition increased the magnitude of epileptiform events in both L1 and L5 interneurons. The increased magnitude of epileptiform events in both pyramidal cells and interneurons was due to an increase in network activity, since holding cells at depolarized potentials under voltage-clamp conditions to minimize HCN channel opening did not prevent enhancement in the presence of ZD 7288. In neurons recorded with ZD 7288-containing pipettes, bath application of the noninactivating inward cationic current (Ih) antagonist still produced increases in epileptiform responses. These results show that epileptiform discharges in disinhibited rat neocortex are modulated by HCN channels.