Rapid neocortical dynamics: cellular and network mechanisms

NMDA Receptors Multiplicatively Scale Visual Signals and Enhance Directional Motion Discrimination in Retinal Ganglion Cells

Postsynaptic responses in many CNS neurons are typically small and variable, often making it difficult to distinguish physiologically relevant signals from background noise. To extract salient information, neurons are thought to integrate multiple synaptic inputs and/or selectively amplify specific synaptic activation patterns. Here, we present evidence for a third strategy: directionally selective ganglion cells (DSGCs) in the mouse retina multiplicatively scale visual signals via a mechanism that requires both nonlinear NMDA receptor (NMDAR) conductances in DSGC dendrites and directionally tuned inhibition provided by the upstream retinal circuitry. Postsynaptic multiplication enables DSGCs to discriminate visual motion more accurately in noisy visual conditions without compromising directional tuning. These findings demonstrate a novel role for NMDARs in synaptic processing and provide new insights into how synaptic and network features interact to accomplish physiologically relevant neural computations.

Membrane Potential Dynamics of Spontaneous and Visually Evoked Gamma Activity in V1 of Awake Mice

Cortical gamma activity (30–80 Hz) is believed to play important functions in neural computation and arises from the interplay of parvalbumin-expressing interneurons (PV) and pyramidal cells (PYRs). However, the subthreshold dynamics underlying its emergence in the cortex of awake animals remain unclear. Here, we characterized the intracellular dynamics of PVs and PYRs during spontaneous and visually evoked gamma activity in layers 2/3 of V1 of awake mice using targeted patch-clamp recordings and synchronous local field potentials (LFPs). Strong gamma activity patterned in short bouts (one to three cycles), occurred when PVs and PYRs were depolarizing and entrained their membrane potential dynamics regardless of the presence of visual stimulation. PV firing phase locked unconditionally to gamma activity. However, PYRs only phase locked to visually evoked gamma bouts. Taken together, our results indicate that gamma activity corresponds to short pulses of correlated background synaptic activity synchronizing the output of cortical neurons depending on external sensory drive.

Gamma activity, an important component of brain dynamics, is driven by synaptic background activity and synchronizes distinct cortical cell types differently depending on visual input.

The neocortex is the main substrate of cognitive activity of the mammalian brain. During active wakefulness, it exhibits an oscillatory activity in the gamma range (30–80Hz), which is believed to play an important functional role and is altered in schizophrenic patients. Experimental studies have shown that gamma activity arises from the interaction of excitatory pyramidal neurons, the main neuronal type of the cortex, and local inhibitory neurons expressing the protein parvalbumin (PV). However, how these neuronal types behave during gamma activity remains largely unknown. Here, we recorded the intracellular activity of pyramidal and PV-expressing neurons in the visual cortex of awake mice while acquiring Local Field Potentials (LFPs)—extracellular voltage fluctuations within a small volume of the cortex—to monitor gamma activity. We found that gamma activity arises when PV-expressing neurons synchronize their output in response to a correlated input, reflecting the general activation of the local cortical network. This happens even in the absence of visual input. On the other hand, the output of pyramidal neurons only becomes entrained to gamma activity when the mice are exposed to visual stimulation. Thus, our results suggest that gamma activity synchronizes pyramidal neurons specifically when the cortex is engaged in processing external inputs.

The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

Fast Learning with Weak Synaptic Plasticity

New sensory stimuli can be learned with a single or a few presentations. Similarly, the responses of cortical neurons to a stimulus have been shown to increase reliably after just a few repetitions. Long-term memory is thought to be mediated by synaptic plasticity, but in vitro experiments in cortical cells typically show very small changes in synaptic strength after a pair of presynaptic and postsynaptic spikes. Thus, it is traditionally thought that fast learning requires stronger synaptic changes, possibly because of neuromodulation. Here we show theoretically that weak synaptic plasticity can, in fact, support fast learning, because of the large number of synapses N onto a cortical neuron. In the fluctuation-driven regime characteristic of cortical neurons in vivo, the size of membrane potential fluctuations grows only as √N, whereas a single output spike leads to potentiation of a number of synapses proportional to N. Therefore, the relative effect of a single spike on synaptic potentiation grows as √N. This leverage effect requires precise spike timing. Thus, the large number of synapses onto cortical neurons allows fast learning with very small synaptic changes. Significance statement: Long-term memory is thought to rely on the strengthening of coactive synapses. This physiological mechanism is generally considered to be very gradual, and yet new sensory stimuli can be learned with just a few presentations. Here we show theoretically that this apparent paradox can be solved when there is a tight balance between excitatory and inhibitory input. In this case, small synaptic modifications applied to the many synapses onto a given neuron disrupt that balance and produce a large effect even for modifications induced by a single stimulus. This effect makes fast learning possible with small synaptic changes and reconciles physiological and behavioral observations.

Altered intrinsic and network properties of neocortical neurons in the Ts65Dn mouse model of Down syndrome

All individuals with Down syndrome (DS) have a varying but significant degree of cognitive disability. Although hippocampal deficits clearly play an important role, behavioral studies also suggest that deficits within the neocortex contribute to somatosensory deficits and impaired cognition in DS. Using thalamocortical slices from the Ts65Dn mouse model of DS, we investigated the intrinsic and network properties of regular spiking neurons within layer 4 of the somatosensory cortex. In these neurons, the membrane capacitance was increased and specific membrane resistance decreased in slices from Ts65Dn mice. Examination of combined active and passive membrane properties suggests that trisomic layer 4 neurons are less excitable than those from euploid mice. The frequencies of excitatory and inhibitory spontaneous synaptic activities were also reduced in Ts65Dn neurons. With respect to network activity, spontaneous network oscillations (Up states) were shorter and less numerous in the neocortex from Ts65Dn mice when compared to euploid. Up states evoked by electrical stimulation of the ventrobasal nucleus (VBN) of the thalamus were similarly affected in Ts65Dn mice. Additionally, monosynaptic EPSCs and polysynaptic IPSCs evoked by VBN stimulation were significantly delayed in layer 4 regular spiking neurons from Ts65Dn mice. These results indicate that, in the Ts65Dn model of DS, the overall electrophysiological properties of neocortical neurons are altered leading to aberrant network activity within the neocortex. Similar changes in DS individuals may contribute to sensory and cognitive dysfunction and therefore may implicate new targets for cognitive therapies in this developmental disorder.

Relationships between Pupil Diameter and Neuronal Activity in the Locus Coeruleus, Colliculi, and Cingulate Cortex

Changes in pupil diameter that reflect effort and other cognitive factors are often interpreted in terms of the activity of norepinephrine-containing neurons in the brainstem nucleus locus coeruleus (LC), but there is little direct evidence for such a relationship. Here, we show that LC activation reliably anticipates changes in pupil diameter that either fluctuate naturally or are driven by external events during near fixation, as in many psychophysical tasks. This relationship occurs on as fine a temporal and spatial scale as single spikes from single units. However, this relationship is not specific to the LC. Similar relationships, albeit with delayed timing and different reliabilities across sites, are evident in the inferior and superior colliculus and anterior and posterior cingulate cortex. Because these regions are interconnected with the LC, the results suggest that non-luminance-mediated changes in pupil diameter might reflect LC-mediated coordination of neuronal activity throughout some parts of the brain.

Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans

Sleep, specifically non-rapid eye movement (NREM) sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5–1.0Hz) and thalamic spindles (12–15Hz), have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem) increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

Persistent Interneuronopathy in the Prefrontal Cortex of Young Adult Offspring Exposed to Ethanol In Utero

Gestational exposure to ethanol has been reported to alter the disposition of tangentially migrating GABAergic cortical interneurons, but much remains to be elucidated. Here we first established the migration of interneurons as a proximal target of ethanol by limiting ethanol exposure in utero to the gestational window when tangential migration is at its height. We then asked whether the aberrant tangential migration of GABAergic interneurons persisted as an enduring interneuronopathy in the medial prefrontal cortex (mPFC) later in the life of offspring prenatally exposed to ethanol. Time pregnant mice with Nkx2.1Cre/Ai14 embryos harboring tdTomato-fluorescent medial ganglionic eminence (MGE)-derived cortical GABAergic interneurons were subjected to a 3 day binge-type 5% w/w ethanol consumption regimen from embryonic day (E) 13.5-16.5, spanning the peak of corticopetal interneuron migration in the fetal brain. Our binge-type regimen increased the density of MGE-derived interneurons in the E16.5 mPFC. In young adult offspring exposed to ethanol in utero, this effect persisted as an increase in the number of mPFC layer V parvalbumin-immunopositive interneurons. Commensurately, patch-clamp recording in mPFC layer V pyramidal neurons uncovered enhanced GABA-mediated spontaneous and evoked synaptic transmission, shifting the inhibitory/excitatory balance toward favoring inhibition. Furthermore, young adult offspring exposed to the 3 day binge-type ethanol regimen exhibited impaired reversal learning in a modified Barnes maze, indicative of decreased PFC-dependent behavioral flexibility, and heightened locomotor activity in an open field arena. Our findings underscore that aberrant neuronal migration, inhibitory/excitatory imbalance, and thus interneuronopathy contribute to indelible abnormal cortical circuit form and function in fetal alcohol spectrum disorders.

SIGNIFICANCE STATEMENT

The significance of this study is twofold. First, we demonstrate that a time-delimited binge-type ethanol exposure in utero during early gestation alters corticopetal tangential migration of GABAergic interneurons in the fetal brain. Second, our study is the first to integrate neuroanatomical, electrophysiological, and behavioral evidence that this "interneuronopathy" persists in the young adult offspring and contributes to enduring changes in (1) the distribution of parvalbumin-expressing GABAergic cortical interneurons in the medial prefrontal cortex, (2) GABA-mediated synaptic transmission that resulted in an inhibitory/excitatory synaptic imbalance, and (3) behavioral flexibility. These findings alert women of child-bearing age that fetal alcohol spectrum disorders can be rooted very early in fetal brain development, and reinforce evidence-based counseling against binge drinking even at the earliest stages of pregnancy.

Characterizing VIP Neurons in the Barrel Cortex of VIPcre/tdTomato Mice Reveals Layer-Specific Differences

Neocortical GABAergic interneurons have a profound impact on cortical circuitry and its information processing capacity. Distinct subgroups of inhibitory interneurons can be distinguished by molecular markers, such as parvalbumin, somatostatin, and vasoactive intestinal polypeptide (VIP). Among these, VIP-expressing interneurons sparked a substantial interest since these neurons seem to operate disinhibitory circuit motifs found in all major neocortical areas. Several of these recent studies used transgenic Vip-ires-cre mice to specifically target the population of VIP-expressing interneurons. This makes it necessary to elucidate in detail the sensitivity and specificity of Cre expression for VIP neurons in these animals. Thus, we quantitatively compared endogenous tdTomato with Vip fluorescence in situ hybridization and αVIP immunohistochemistry in the barrel cortex of VIPcre/tdTomato mice in a layer-specific manner. We show that VIPcre/tdTomato mice are highly sensitive and specific for the entire population of VIP-expressing neurons. In the barrel cortex, approximately 13% of all GABAergic neurons are VIP expressing. Most VIP neurons are found in layer II/III (∼60%), whereas approximately 40% are found in the other layers of the barrel cortex. Layer II/III VIP neurons are significantly different from VIP neurons in layers IV–VI in several morphological and membrane properties, which suggest layer-dependent differences in functionality.

Constructing Precisely Computing Networks with Biophysical Spiking Neurons

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation.

SIGNIFICANCE STATEMENT

We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks including irregular, Poisson-like spike times, and a tight balance between excitation and inhibition. These results significantly increase the biological plausibility of the spike-based approach to network computation, and uncover how several components of biological networks may work together to efficiently carry out computation.

Nonlinear transfer of signal and noise correlations in cortical networks

Signal and noise correlations, a prominent feature of cortical activity, reflect the structure and function of networks during sensory processing. However, in addition to reflecting network properties, correlations are also shaped by intrinsic neuronal mechanisms. Here we show that spike threshold transforms correlations by creating nonlinear interactions between signal and noise inputs; even when input noise correlation is constant, spiking noise correlation varies with both the strength and correlation of signal inputs. We characterize these effects systematically in vitro in mice and demonstrate their impact on sensory processing in vivo in gerbils. We also find that the effects of nonlinear correlation transfer on cortical responses are stronger in the synchronized state than in the desynchronized state, and show that they can be reproduced and understood in a model with a simple threshold nonlinearity. Since these effects arise from an intrinsic neuronal property, they are likely to be present across sensory systems and, thus, our results are a critical step toward a general understanding of how correlated spiking relates to the structure and function of cortical networks.

Generalized periodic discharges: Pathophysiology and clinical considerations

Generalized periodic discharges (GPDs) are commonly encountered in metabolic encephalopathy and cerebral hypoxia/ischemia. The clinical significance of this EEG pattern is indistinct, and it is unclear whether treatment with antiepileptic drugs is beneficial. In this study, we discuss potential pathophysiological mechanisms. Based on the literature, supplemented with simulations in a minimal computational model, we conclude that selective synaptic failure or neuronal damage of inhibitory interneurons, leading to disinhibition of excitatory pyramidal cells, presumably plays a critical role. Reversibility probably depends on the potential for functional recovery of these interneurons. Whether antiepileptic drugs are helpful for regaining function is unclear. This article is part of a Special Issue entitled "Status Epilepticus".

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation.

Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states.

Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods.

Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

Task-sensitive reconfiguration of corticocortical 6-20 Hz oscillatory coherence in naturalistic human performance

Electrophysiological oscillatory coherence between brain regions has been proposed to facilitate functional long-range connectivity within neurocognitive networks. This notion is supported by intracortical recordings of coherence in singled-out corticocortical connections in the primate cortex. However, the manner in which this operational principle manifests in the task-sensitive connectivity that supports human naturalistic performance remains undercharacterized. Here, we demonstrate task-sensitive reconfiguration of global patterns of coherent connectivity in association with a set of easier and more demanding naturalistic tasks, ranging from picture comparison to speech comprehension and object manipulation. Based on whole-cortex neuromagnetic recording in healthy behaving individuals, the task-sensitive component of long-range corticocortical coherence was mapped at spectrally narrow-band oscillatory frequencies between 6 and 20 Hz (theta to alpha and low-beta bands). This data-driven cortical mapping unveiled markedly distinct and topologically task-relevant spatiospectral connectivity patterns for the different tasks. The results demonstrate semistable oscillatory states relevant for neurocognitive processing. The present findings decisively link human behavior to corticocortical coherence at oscillatory frequencies that are widely thought to convey long-range, feedback-type neural interaction in cortical functional networks.

Closed-loop and activity-guided optogenetic control

Advances in optical manipulation and observation of neural activity have set the stage for widespread implementation of closed-loop and activity-guided optical control of neural circuit dynamics. Closing the loop optogenetically (i.e., basing optogenetic stimulation on simultaneously observed dynamics in a principled way) is a powerful strategy for causal investigation of neural circuitry. In particular, observing and feeding back the effects of circuit interventions on physiologically relevant timescales is valuable for directly testing whether inferred models of dynamics, connectivity, and causation are accurate in vivo. Here we highlight technical and theoretical foundations as well as recent advances and opportunities in this area, and we review in detail the known caveats and limitations of optogenetic experimentation in the context of addressing these challenges with closed-loop optogenetic control in behaving animals.

Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease

Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this article, we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low-frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders-including Parkinson's disease, autism, depression, schizophrenia, and anxiety-are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural gray or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states or their treatment are a product of how these physical processes affect dynamic network communication.

Oscillations and neuronal dynamics in schizophrenia: the search for basic symptoms and translational opportunities

A considerable body of work over the last 10 years combining noninvasive electrophysiology (electroencephalography/magnetoencephalography) in patient populations with preclinical research has contributed to the conceptualization of schizophrenia as a disorder associated with aberrant neural dynamics and disturbances in excitation/inhibition balance. This complements previous research that has largely focused on the identification of abnormalities in circumscribed brain regions and on disturbances of dopaminergic mechanisms as a cause of positive symptoms and executive deficits. In the current review, we provide an update on studies focusing on aberrant neural dynamics. First, we discuss the role of rhythmic activity in neural dynamics and in the coordination of distributed neuronal activity into organized neural states. This is followed by an overview on the current evidence for impaired neural oscillations and synchrony in schizophrenia and associated abnormalities in gamma-aminobutyric acidergic and glutamatergic neurotransmission. Finally, we discuss the distinction between fundamental symptoms, which are reflected in cognitive deficits, and psychotic, accessory symptoms, the latter likely constituting a compensatory response for aberrant neuronal dynamics.

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.

Optogenetic stimulation of infralimbic PFC reproduces ketamine's rapid and sustained antidepressant actions

Ketamine produces rapid and sustained antidepressant actions in depressed patients, but the precise cellular mechanisms underlying these effects have not been identified. Here we determined if modulation of neuronal activity in the infralimbic prefrontal cortex (IL-PFC) underlies the antidepressant and anxiolytic actions of ketamine. We found that neuronal inactivation of the IL-PFC completely blocked the antidepressant and anxiolytic effects of systemic ketamine in rodent models and that ketamine microinfusion into IL-PFC reproduced these behavioral actions of systemic ketamine. We also found that optogenetic stimulation of the IL-PFC produced rapid and long-lasting antidepressant and anxiolytic effects and that these effects are associated with increased number and function of spine synapses of layer V pyramidal neurons. The results demonstrate that ketamine infusions or optogenetic stimulation of IL-PFC are sufficient to produce long-lasting antidepressant behavioral and synaptic responses similar to the effects of systemic ketamine administration.

State-dependent population coding in primary auditory cortex

Sensory function is mediated by interactions between external stimuli and intrinsic cortical dynamics that are evident in the modulation of evoked responses by cortical state. A number of recent studies across different modalities have demonstrated that the patterns of activity in neuronal populations can vary strongly between synchronized and desynchronized cortical states, i.e., in the presence or absence of intrinsically generated up and down states. Here we investigated the impact of cortical state on the population coding of tones and speech in the primary auditory cortex (A1) of gerbils, and found that responses were qualitatively different in synchronized and desynchronized cortical states. Activity in synchronized A1 was only weakly modulated by sensory input, and the spike patterns evoked by tones and speech were unreliable and constrained to a small range of patterns. In contrast, responses to tones and speech in desynchronized A1 were temporally precise and reliable across trials, and different speech tokens evoked diverse spike patterns with extremely weak noise correlations, allowing responses to be decoded with nearly perfect accuracy. Restricting the analysis of synchronized A1 to activity within up states yielded similar results, suggesting that up states are not equivalent to brief periods of desynchronization. These findings demonstrate that the representational capacity of A1 depends strongly on cortical state, and suggest that cortical state should be considered as an explicit variable in all studies of sensory processing.

Facilitation of epileptic activity during sleep is mediated by high amplitude slow waves

Epileptic discharges in focal epilepsy are frequently activated during non-rapid eye movement sleep. Sleep slow waves are present during this stage and have been shown to include a deactivated ('down', hyperpolarized) and an activated state ('up', depolarized). The 'up' state enhances physiological rhythms, and we hypothesize that sleep slow waves and particularly the 'up' state are the specific components of non-rapid eye movement sleep that mediate the activation of epileptic activity. We investigated eight patients with pharmaco-resistant focal epilepsies who underwent combined scalp-intracerebral electroencephalography for diagnostic evaluation. We analysed 259 frontal electroencephalographic channels, and manually marked 442 epileptic spikes and 8487 high frequency oscillations during high amplitude widespread slow waves, and during matched control segments with low amplitude widespread slow waves, non-widespread slow waves or no slow waves selected during the same sleep stages (total duration of slow wave and control segments: 49 min each). During the slow waves, spikes and high frequency oscillations were more frequent than during control segments (79% of spikes during slow waves and 65% of high frequency oscillations, both P ∼ 0). The spike and high frequency oscillation density also increased for higher amplitude slow waves. We compared the density of spikes and high frequency oscillations between the 'up' and 'down' states. Spike and high frequency oscillation density was highest during the transition from the 'up' to the 'down' state. Interestingly, high frequency oscillations in channels with normal activity expressed a different peak at the transition from the 'down' to the 'up' state. These results show that the apparent activation of epileptic discharges by non-rapid eye movement sleep is not a state-dependent phenomenon but is predominantly associated with specific events, the high amplitude widespread slow waves that are frequent, but not continuous, during this state of sleep. Both epileptic spikes and high frequency oscillations do not predominate, like physiological activity, during the 'up' state but during the transition from the 'up' to the 'down' state of the slow wave, a period of high synchronization. Epileptic discharges appear therefore more associated with synchronization than with excitability. Furthermore, high frequency oscillations in channels devoid of epileptic activity peak differently during the slow wave cycle from those in channels with epileptic activity. This property may allow differentiating physiological from pathological high frequency oscillations, a problem that is unresolved until now.

Differential modulation of repetitive firing and synchronous network activity in neocortical interneurons by inhibition of A-type K(+) channels and Ih

GABAergic interneurons provide the main source of inhibition in the neocortex and are important in regulating neocortical network activity. In the presence 4-aminopyridine (4-AP), CNQX, and D-APV, large amplitude GABAA-receptor mediated depolarizing responses were observed in the neocortex. GABAergic networks are comprised of several types of interneurons, each with its own protein expression pattern, firing properties, and inhibitory role in network activity. Voltage-gated ion channels, especially A-type K(+) channels, differentially regulate passive membrane properties, action potential (AP) waveform, and repetitive firing properties in interneurons depending on their composition and localization. HCN channels are known modulators of pyramidal cell intrinsic excitability and excitatory network activity. Little information is available regarding how HCN channels functionally modulate excitability of individual interneurons and inhibitory networks. In this study, we examined the effect of 4-AP on intrinsic excitability of fast-spiking basket cells (FS-BCs) and Martinotti cells (MCs). 4-AP increased the duration of APs in both FS-BCs and MCs. The repetitive firing properties of MCs were differentially affected compared to FS-BCs. We also examined the effect of Ih inhibition on synchronous GABAergic depolarizations and synaptic integration of depolarizing IPSPs. ZD 7288 enhanced the amplitude and area of evoked GABAergic responses in both cell types. Similarly, the frequency and area of spontaneous GABAergic depolarizations in both FS-BCs and MCs were increased in presence of ZD 7288. Synaptic integration of IPSPs in MCs was significantly enhanced, but remained unaltered in FS-BCs. These results indicate that 4-AP differentially alters the firing properties of interneurons, suggesting MCs and FS-BCs may have unique roles in GABAergic network synchronization. Enhancement of GABAergic network synchronization by ZD 7288 suggests that HCN channels attenuate inhibitory network activity.

Cell Type-Specific Control of Spike Timing by Gamma-Band Oscillatory Inhibition

Many lines of theoretical and experimental investigation have suggested that gamma oscillations provide a temporal framework for cortical information processing, acting to either synchronize neuronal firing, restrict neuron's relative spike times, and/or provide a global reference signal to which neurons encode input strength. Each theory has been disputed and some believe that gamma is an epiphenomenon. We investigated the biophysical plausibility of these theories by performing in vitro whole-cell recordings from 6 cortical neuron subtypes and examining how gamma-band and slow fluctuations in injected input affect precision and phase of spike timing. We find that gamma is at least partially able to restrict the spike timing in all subtypes tested, but to varying degrees. Gamma exerts more precise control of spike timing in pyramidal neurons involved in cortico-cortical versus cortico-subcortical communication and in inhibitory neurons that target somatic versus dendritic compartments. We also find that relatively few subtypes are capable of phase-based information coding. Using simple neuron models and dynamic clamp, we determine which intrinsic differences lead to these variations in responsiveness and discuss both the flexibility and confounds of gamma-based spike-timing systems.

Asymmetry and modulation of spike timing in electrically coupled neurons

Electrical coupling mediates interactions between neurons of the thalamic reticular nucleus (TRN), which play a critical role in regulating thalamocortical and corticothalamic communication by inhibiting thalamic relay cells. Accumulating evidence has shown that asymmetry of electrical synapses is a fundamental and dynamic property, but the effect of asymmetry on coupled networks is unexplored. Recording from patched pairs in rat brain slices, we investigate asymmetry in the subthreshold regime and show that electrical synapses can exert powerful effects on the spike times of coupled neighbors. Electrical synaptic signaling modulates spike timing by 10–20 ms, in an effect that also exhibits asymmetry. Furthermore, we show through modeling that coupling asymmetry expands the set of outputs for pairs of coupled neurons through enhanced regions of synchrony and reversals of spike order. These results highlight the power and specificity of signaling exerted by electrical synapses, which contribute to information flow across the brain.

On the functions, mechanisms, and malfunctions of intracortical contextual modulation

A broad neuron-centric conception of contextual modulation is reviewed and re-assessed in the light of recent neurobiological studies of amplification, suppression, and synchronization. Behavioural and computational studies of perceptual and higher cognitive functions that depend on these processes are outlined, and evidence that those functions and their neuronal mechanisms are impaired in schizophrenia is summarized. Finally, we compare and assess the long-term biological functions of contextual modulation at the level of computational theory as formalized by the theories of coherent infomax and free energy reduction. We conclude that those theories, together with the many empirical findings reviewed, show how contextual modulation at the neuronal level enables the cortex to flexibly adapt the use of its knowledge to current circumstances by amplifying and grouping relevant activities and by suppressing irrelevant activities.

Keeping time: could quantum beating in microtubules be the basis for the neural synchrony related to consciousness?

This paper discusses the possibility of quantum coherent oscillations playing a role in neuronal signaling. Consciousness correlates strongly with coherent neural oscillations, however the mechanisms by which neurons synchronize are not fully elucidated. Recent experimental evidence of quantum beats in light-harvesting complexes of plants (LHCII) and bacteria provided a stimulus for seeking similar effects in important structures found in animal cells, especially in neurons. We argue that microtubules (MTs), which play critical roles in all eukaryotic cells, possess structural and functional characteristics that are consistent with quantum coherent excitations in the aromatic groups of their tryptophan residues. Furthermore we outline the consequences of these findings on neuronal processes including the emergence of consciousness.

Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli

Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming sensory information. The mechanistic and functional relationship between these two basic neurophysiological signatures of working memory remains elusive. We propose that match signals are generated as a result of transient changes in local network excitability brought about by persistent activity. Neurons more active will be more excitable, and thus more responsive to external inputs. Accordingly, network responses are jointly determined by the incoming stimulus and the ongoing pattern of persistent activity. Using a spiking model network, we show that this mechanism is able to reproduce most of the experimental phenomenology of match effects as exposed by single-cell recordings during delayed-response tasks. The model provides a unified, parsimonious mechanistic account of the main neuronal correlates of working memory, makes several experimentally testable predictions, and demonstrates a new functional role for persistent activity.

Over short time periods, memories are stored by sustained patterns of spiking activity which, once initiated by the stimulus, persist over the entire retention interval. How the information stored by such persistent activity is later retrieved is presently unclear. Here we propose that, besides temporarily storing memories, persistent activity is also instrumental in their retrieval by transiently modifying the tuning properties of the underlying neuronal networks. We show that the mechanism proposed parsimoniously recapitulates the extensive experimental phenomenology on match effects observed in delayed-response tasks, where the information held in memory has to be compared with incoming, sensory-related information to act appropriately. The theory makes very specific, straightforwardly testable predictions.

Spatiotemporal conditional inference and hypothesis tests for neural ensemble spiking precision

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatiotemporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatiotemporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis-testing adjustments and design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peristimulus time histogram or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable to other areas of neurostatistical analysis.

Amyloid-β disrupts ongoing spontaneous activity in sensory cortex

The effect of Alzheimer's disease pathology on activity of individual neocortical neurons in the intact neural network remains obscure. Ongoing spontaneous activity, which constitutes most of neocortical activity, is the background template on which further evoked-activity is superimposed. We compared in vivo intracellular recordings and local field potentials (LFP) of ongoing activity in the barrel cortex of APP/PS1 transgenic mice and age-matched littermate CONTROLS, following significant amyloid-β (Aβ) accumulation and aggregation. We found that membrane potential dynamics of neurons in Aβ-burdened cortex significantly differed from those of nontransgenic

CONTROLS

durations of the depolarized state were considerably shorter, and transitions to that state frequently failed. The spiking properties of APP/PS1 neurons showed alterations from those of

CONTROLS

both firing patterns and spike shape were changed in the APP/PS1 group. At the population level, LFP recordings indicated reduced coherence within neuronal assemblies of APP/PS1 mice. In addition to the physiological effects, we show that morphology of neurites within the barrel cortex of the APP/PS1 model is altered compared to CONTROLS. These results are consistent with a process where the effect of Aβ on spontaneous activity of individual neurons amplifies into a network effect, reducing network integrity and leading to a wide cortical dysfunction.

Response-dependent dynamics of cell-specific inhibition in cortical networks in vivo

In the visual cortex, inhibitory neurons alter the computations performed by target cells via combination of two fundamental operations, division and subtraction. The origins of these operations have been variously ascribed to differences in neuron classes, synapse location or receptor conductances. Here, by utilizing specific visual stimuli and single optogenetic probe pulses, we show that the function of parvalbumin-expressing and somatostatin-expressing neurons in mice in vivo is governed by the overlap of response timing between these neurons and their targets. In particular, somatostatin-expressing neurons respond at longer latencies to small visual stimuli compared with their target neurons and provide subtractive inhibition. With large visual stimuli, however, they respond at short latencies coincident with their target cells and switch to provide divisive inhibition. These results indicate that inhibition mediated by these neurons is a dynamic property of cortical circuits rather than an immutable property of neuronal classes.

Cation-chloride cotransporters in neuronal development, plasticity and disease

Electrical activity in neurons requires a seamless functional coupling between plasmalemmal ion channels and ion transporters. Although ion channels have been studied intensively for several decades, research on ion transporters is in its infancy. In recent years, it has become evident that one family of ion transporters, cation-chloride cotransporters (CCCs), and in particular K(+)-Cl(-) cotransporter 2 (KCC2), have seminal roles in shaping GABAergic signalling and neuronal connectivity. Studying the functions of these transporters may lead to major paradigm shifts in our understanding of the mechanisms underlying brain development and plasticity in health and disease.

High baseline activity in inferior temporal cortex improves neural and behavioral discriminability during visual categorization

Spontaneous firing is a ubiquitous property of neural activity in the brain. Recent literature suggests that this baseline activity plays a key role in perception. However, it is not known how the baseline activity contributes to neural coding and behavior. Here, by recording from the single neurons in the inferior temporal cortex of monkeys performing a visual categorization task, we thoroughly explored the relationship between baseline activity, the evoked response, and behavior. Specifically we found that a low-frequency (<8 Hz) oscillation in the spike train, prior and phase-locked to the stimulus onset, was correlated with increased gamma power and neuronal baseline activity. This enhancement of the baseline activity was then followed by an increase in the neural selectivity and the response reliability and eventually a higher behavioral performance.

Acetylcholine, GABA and neuronal networks: a working hypothesis for compensations in the dystrophic brain

Duchenne muscular dystrophy (DMD), a genetic disease arising from a mutation in the dystrophin gene, is characterized by muscle failure and is often associated with cognitive deficits. Studies of the dystrophic brain on the murine mdx model of DMD provide evidence of morphological and functional alterations in the central nervous system (CNS) possibly compatible with the cognitive impairment seen in DMD. However, while some of the alterations reported are a direct consequence of the absence of dystrophin, others seem to be associated only indirectly. In this review we reevaluate the literature in order to formulate a possible explanation for the cognitive impairments associated with DMD. We present a working hypothesis, demonstrated as an integrated neuronal network model, according to which within the cascade of events leading to cognitive impairments there are compensatory mechanisms aimed to maintain functional stability via perpetual adjustments of excitatory and inhibitory components. Such ongoing compensatory response creates continuous perturbations that disrupt neuronal functionality in terms of network efficiency. We have theorized that in this process acetylcholine and network oscillations play a central role. A better understating of these mechanisms could provide a useful diagnostic index of the disease's progression and, perhaps, the correct counterbalance of this process might help to prevent deterioration of the CNS in DMD. Furthermore, the involvement of compensatory mechanisms in the CNS could be extended beyond DMD and possibly help to clarify other physio-pathological processes of the CNS.

Single-cell genetic expression of mutant GABAA receptors causing Human genetic epilepsy alters dendritic spine and GABAergic bouton formation in a mutation-specific manner

Mutations in genes encoding for GABA_A receptor subunits is a well-established cause of genetic generalized epilepsy. GABA neurotransmission is implicated in several developmental processes including neurite outgrowth and synapse formation. Alteration in excitatory/inhibitory synaptic activities plays a critical role in epilepsy, thus here we investigated whether mutations in α1 subunit of GABA_A receptor may affect dendritic spine and GABAergic bouton formation. In particular, we examined the effects of three mutations of the GABRA1 gene (D219N, A322D and K353delins18X) that were found in a cohort of French Canadian families with genetic generalized epilepsy. We used a novel single-cell genetic approach, by preparing cortical organotypic cultures from GABRA1^flox/flox mice and simultaneously inactivating endogenous GABRA1 and transfecting mutant α1 subunits in single glutamatergic pyramidal cells and basket GABAergic interneurons by biolistic transfection. We found that GABRA1^−/− GABAergic cells showed reduced innervation field, which was rescued by co-expressing α1-A322D and α1-WT but not α1-D219N. We further found that the expression of the most severe GABRA1 missense mutation (α1-A322D) induced a striking increase of spine density in pyramidal cells along with an increase in the number of mushroom-like spines. In addition, α1-A322D expression in GABAergic cells slightly increased perisomatic bouton density, whereas other mutations did not alter bouton formation. All together, these results suggest that the effects of different GABA_AR mutations on GABAergic bouton and dendritic spine formation are specific to the mutation and cannot be always explained by a simple loss-of-function gene model. The use of single cell genetic manipulation in organotypic cultures may provide a better understanding of the specific and distinct neural circuit alterations caused by different GABA_A receptor subunit mutations and will help define the pathophysiology of genetic generalized epilepsy syndromes.

Neural control of brain state

How the brain takes in information, makes a decision, and acts on this decision is strongly influenced by the ongoing and constant fluctuations of state. Understanding the nature of these brain states and how they are controlled is critical to making sense of how the nervous system operates, both normally and abnormally. While broadly projecting neuromodulatory systems acting through metabotropic pathways have long been appreciated to be critical for determining brain state, more recent investigations have revealed a prominent role for fast acting neurotransmitter pathways for temporally and spatially precise control of neural processing. Corticocortical and thalamocortical glutamatergic projections can rapidly and precisely control brain state by changing both the nature of ongoing activity and by controlling the gain and precision of neural responses.

Neuromodulation of the conscious state following severe brain injuries

Disorders of consciousness (DOC) following severe structural brain injuries globally affect the conscious state and the expression of goal-directed behaviors. In some subjects, neuromodulation with medications or electrical stimulation can markedly improve the impaired conscious state present in DOC. We briefly review recent studies and provide an organizing framework for considering the apparently widely disparate collection of medications and approaches that may modulate the conscious state in subjects with DOC. We focus on neuromodulation of the anterior forebrain mesocircuit in DOC and briefly compare mechanisms supporting recovery from structural brain injuries to those underlying facilitated emergence from unconsciousness produced by anesthesia. We derive some general principles for approaching the problem of restoration of consciousness after severe structural brain injuries, and suggest directions for future research.

TIDAL WAVES: Network mechanisms in the neuroendocrine control of prolactin release

Neuroendocrine tuberoinfundibular dopamine (TIDA) neurons tonically inhibit pituitary release of the hormone, prolactin. Through the powerful actions of prolactin in promoting lactation and maternal behaviour while suppressing sexual drive and fertility, TIDA neurons play a key role in reproduction. We summarize insights from recent in vitro studies into the membrane properties and network behaviour of TIDA neurons including the observations that TIDA neurons exhibit a robust oscillation that is synchronized between cells and depends on intact gap junction communication. Comparisons are made with phasic firing patterns in other neuronal populations. Modulators involved in the control of lactation - including serotonin, thyrotropin-releasing hormone and prolactin itself - have been shown to change the electrical behaviour of TIDA cells. We propose that TIDA discharge mode may play a central role in tuning the amount of dopamine delivered to the pituitary and hence circulating prolactin concentrations in different reproductive states and pathological conditions.

Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks

It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in promoting/arresting the population activity. For this purpose, we consider a standard neuronal network model, with short-term synaptic plasticity, whose population activity is characterized by bursting behavior. The addition of developmentally inspired constraints and correlations in the distribution of the neuronal connectivities and excitabilities leads to the emergence of functional hub neurons, whose stimulation/deletion is critical for the network activity. Functional hubs form a clique, where a precise sequential activation of the neurons is essential to ignite collective events without any need for a specific topological architecture. Unsupervised time-lagged firings of supra-threshold cells, in connection with coordinated entrainments of near-threshold neurons, are the key ingredients to orchestrate population activity.

To which extent a single neuron can influence brain circuits/networks dynamics? Why only a few neurons display such a strong power? These open questions are inspired by recent experimental observations in developing and adult neuronal circuits, as well as by classical debates within the framework of the single neuron doctrine. In this work we identify and present a mechanism which can explain in neuronal circuits, at some early stage of their development, how and why only a few specific neurons can exhibit such power. For this purpose, we consider a standard neuronal network model whose population activity is characterized by bursting behavior. The introduction of a distribution of correlated neuronal excitabilities and degrees, inspired by the simultaneous presence of younger and older neurons in the network, leads to the emergence of functional hub neurons. These critical cells, whenever perturbed, are capable of suppressing network synchronization. Notably, we show that their strong influence on the population dynamics is not related to their structural properties, but to their operational and structural integration into a clique. These results highlight how network-wide effects can be induced by single neurons without any need for a specific topological architecture.

Boosting visual cortex function and plasticity with acetylcholine to enhance visual perception

The cholinergic system is a potent neuromodulatory system that plays critical roles in cortical plasticity, attention and learning. In this review, we propose that the cellular effects of acetylcholine (ACh) in the primary visual cortex during the processing of visual inputs might induce perceptual learning; i.e., long-term changes in visual perception. Specifically, the pairing of cholinergic activation with visual stimulation increases the signal-to-noise ratio, cue detection ability and long-term facilitation in the primary visual cortex. This cholinergic enhancement would increase the strength of thalamocortical afferents to facilitate the treatment of a novel stimulus while decreasing the cortico-cortical signaling to reduce recurrent or top-down modulation. This balance would be mediated by different cholinergic receptor subtypes that are located on both glutamatergic and GABAergic neurons of the different cortical layers. The mechanisms of cholinergic enhancement are closely linked to attentional processes, long-term potentiation (LTP) and modulation of the excitatory/inhibitory balance. Recently, it was found that boosting the cholinergic system during visual training robustly enhances sensory perception in a long-term manner. Our hypothesis is that repetitive pairing of cholinergic and sensory stimulation over a long period of time induces long-term changes in the processing of trained stimuli that might improve perceptual ability. Various non-invasive approaches to the activation of the cholinergic neurons have strong potential to improve visual perception.

Goal-directed control with cortical units that are gated by both top-down feedback and oscillatory coherence

The brain is able to flexibly select behaviors that adapt to both its environment and its present goals. This cognitive control is understood to occur within the hierarchy of the cortex and relies strongly on the prefrontal and premotor cortices, which sit at the top of this hierarchy. Pyramidal neurons, the principal neurons in the cortex, have been observed to exhibit much stronger responses when they receive inputs at their soma/basal dendrites that are coincident with inputs at their apical dendrites. This corresponds to inputs from both lower-order regions (feedforward) and higher-order regions (feedback), respectively. In addition to this, coherence between oscillations, such as gamma oscillations, in different neuronal groups has been proposed to modulate and route communication in the brain. In this paper, we develop a simple, but novel, neural mass model in which cortical units (or ensembles) exhibit gamma oscillations when they receive coherent oscillatory inputs from both feedforward and feedback connections. By forming these units into circuits that can perform logic operations, we identify the different ways in which operations can be initiated and manipulated by top-down feedback. We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units. With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation. Finally, we explore how different network properties affect top-down control and processing in large networks. Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention.

The dynamics of cortical neuronal activity in the first minutes after spontaneous awakening in rats and mice

STUDY OBJECTIVE

Upon awakening from sleep, a fully awake brain state is not reestablished immediately, but the origin and physiological properties of the distinct brain state during the first min after awakening are unclear. To investigate whether neuronal firing immediately upon arousal is different from the remaining part of the waking episode, we recorded and analyzed the dynamics of cortical neuronal activity in the first 15 min after spontaneous awakenings in freely moving rats and mice.

DESIGN

Intracortical recordings of the local field potential and neuronal activity in freely-moving mice and rats.

SETTING

Basic sleep research laboratory.

PATIENTS OR PARTICIPANTS

WKY adult male rats, C57BL/6 adult male mice.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

In both species the average population spiking activity upon arousal was initially low, though substantial variability in the dynamics of firing activity was apparent between individual neurons. A distinct population of neurons was found that was virtually silent in the first min upon awakening. The overall lower population spiking initially after awakening was associated with the occurrence of brief periods of generalized neuronal silence (OFF periods), whose frequency peaked immediately after awakening and then progressively declined. OFF periods incidence upon awakening was independent of ongoing locomotor activity but was sensitive to immediate preceding sleep/wake history. Notably, in both rats and mice if sleep before a waking episode was enriched in rapid eye movement sleep, the incidence of OFF periods was initially higher as compared to those waking episodes preceded mainly by nonrapid eye movement sleep.

CONCLUSION

We speculate that an intrusion of sleep-like patterns of cortical neuronal activity into the wake state immediately after awakening may account for some of the changes in the behavior and cognitive function typical of what is referred to as sleep inertia.

CITATION

Vyazovskiy VV, Cui N, Rodriguez AV, Funk C, Cirelli C, Tononi G. The dynamics of cortical neuronal activity in the first minutes after spontaneous awakening in rats and mice.

Impaired excitability of somatostatin- and parvalbumin-expressing cortical interneurons in a mouse model of Dravet syndrome

Haploinsufficiency of the voltage-gated sodium channel NaV1.1 causes Dravet syndrome, an intractable developmental epilepsy syndrome with seizure onset in the first year of life. Specific heterozygous deletion of NaV1.1 in forebrain GABAergic-inhibitory neurons is sufficient to cause all the manifestations of Dravet syndrome in mice, but the physiological roles of specific subtypes of GABAergic interneurons in the cerebral cortex in this disease are unknown. Voltage-clamp studies of dissociated interneurons from cerebral cortex did not detect a significant effect of the Dravet syndrome mutation on sodium currents in cell bodies. However, current-clamp recordings of intact interneurons in layer V of neocortical slices from mice with haploinsufficiency in the gene encoding the NaV1.1 sodium channel, Scn1a, revealed substantial reduction of excitability in fast-spiking, parvalbumin-expressing interneurons and somatostatin-expressing interneurons. The threshold and rheobase for action potential generation were increased, the frequency of action potentials within trains was decreased, and action-potential firing within trains failed more frequently. Furthermore, the deficit in excitability of somatostatin-expressing interneurons caused significant reduction in frequency-dependent disynaptic inhibition between neighboring layer V pyramidal neurons mediated by somatostatin-expressing Martinotti cells, which would lead to substantial disinhibition of the output of cortical circuits. In contrast to these deficits in interneurons, pyramidal cells showed no differences in excitability. These results reveal that the two major subtypes of interneurons in layer V of the neocortex, parvalbumin-expressing and somatostatin-expressing, both have impaired excitability, resulting in disinhibition of the cortical network. These major functional deficits are likely to contribute synergistically to the pathophysiology of Dravet syndrome.

Balanced cortical microcircuitry for spatial working memory based on corrective feedback control

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory-inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory.

High-frequency oscillations and the neurobiology of schizophrenia

Neural oscillations at low- and high-frequency ranges are a fundamental feature of large-scale networks. Recent evidence has indicated that schizophrenia is associated with abnormal amplitude and synchrony of oscillatory activity, in particular, at high (beta/gamma) frequencies. These abnormalities are observed during task-related and spontaneous neuronal activity which may be important for understanding the pathophysiology of the syndrome. In this paper, we shall review the current evidence for impaired beta/gamma-band oscillations and their involvement in cognitive functions and certain symptoms of the disorder. In the first part, we will provide an update on neural oscillations during normal brain functions and discuss underlying mechanisms. This will be followed by a review of studies that have examined high-frequency oscillatory activity in schizophrenia and discuss evidence that relates abnormalities of oscillatory activity to disturbed excitatory/inhibitory (E/I) balance. Finally, we shall identify critical issues for future research in this area.

Equalizing excitation-inhibition ratios across visual cortical neurons

The relationship between synaptic excitation and inhibition (E/I ratio), two opposing forces in the mammalian cerebral cortex, affects many cortical functions like feature selectivity and gain^1,2. Individual pyramidal cells show stable E/I ratios in time despite fluctuating cortical activity levels because when excitation increases, inhibition increases proportionally through the increased recruitment of inhibitory neurons, a phenomenon referred to as excitation-inhibition balance^3–9. However, little is known about the distribution of E/I ratios across pyramidal cells. Through their highly divergent axons inhibitory neurons indiscriminately contact most neighboring pyramidal cells^10,11. Is inhibition homogeneously distributed or is it individually matched to the different amounts of excitation received by distinct pyramidal cells? Here we discover that pyramidal cells in layer 2/3 of mouse primary visual cortex (V1) each receive inhibition in a similar proportion to their excitation. As a consequence E/I ratios are equalized across pyramidal cells. This matched inhibition is mediated by parvalbumin-expressing (PV) but not somatostatin-expressing (SOM) inhibitory neurons and results from the independent adjustment of synapses originating from the same PV cell but targeting different pyramidal cells. Furthermore, this match is activity-dependent as it is disrupted by perturbing pyramidal cell activity. Thus, the equalization of E/I ratios across pyramidal cells reveals an unexpected degree of order in the spatial distribution of synaptic strengths and indicates that the relationship between cortex’s two opposing forces is stabilized not only in time but also in space.