Impact of Cortical Network Activity on Short-term Synaptic Depression

A simple MATLAB toolbox for analyzing calcium imaging data in vitro and in vivo

BACKGROUND

Fluorescence imaging of calcium dynamics in neuronal populations is powerful because it offers a way of relating the activity of individual cells to the broader population of nearby cells. The method's growth across neuroscience has particularly been driven by the introduction of sophisticated mathematical techniques related to motion correction, image registration, cell detection, spike estimation, and population characterization. However, for many researchers, making good use of these techniques has been difficult because they have been devised by different workers and impose differing - and sometimes stringent - technical requirements on those who seek to use them.

NEW METHOD

We have built a simple toolbox of analysis routines that encompass the complete workflow for analyzing calcium imaging data. The workflow begins with preprocessing of data, includes motion correction and longitudinal image registration, detects active cells using constrained non-negative matrix factorization, and offers multiple options for estimating spike times and characterizing population activity. The routines can be navigated through a simple graphical user interface. Although written in MATLAB, a standalone version for researchers who do not have access to MATLAB is included.

RESULTS

We have used the toolbox on two very different preparations: spontaneously active brain slices and microendoscopic imaging from deep structures in awake behaving mice. In both cases, the toolbox offered a seamless flow from raw data all the way through to prepared graphs.

CONCLUSION

The field of calcium imaging has benefited from the development of numerous innovative mathematical techniques. Here we offer a simple toolbox that allows ordinary researchers to fully exploit these techniques.

Multiple distinct timescales of rapid sensory adaptation in the thalamocortical circuit

Numerous studies have shown that neuronal representations in sensory pathways are far from static but are instead strongly shaped by the complex properties of the sensory inputs they receive. Adaptation dynamically shapes the neural signaling that underlies our perception of the world yet remains poorly understood. We investigated rapid adaptation across timescales from hundreds of milliseconds to seconds through simultaneous multi-electrode recordings from the ventro-posteromedial nucleus of the thalamus (VPm) and layer 4 of the primary somatosensory cortex (S1) in male and female anesthetized mice in response to controlled, persistent whisker stimulation. Observations in VPm and S1 reveal a degree of adaptation that progresses through the pathway. Signatures of two distinct timescales of rapid adaptation in the firing rates of both thalamic and cortical neuronal populations were revealed, also reflected in the synchrony of the thalamic population and in the thalamocortical synaptic efficacy that was measured in putatively monosynaptically connected thalamocortical pairs. Controlled optogenetic activation of VPm further demonstrated that the longer timescale adaptation observed in S1 is likely inherited from slow decreases in thalamic firing rate and synchrony. Despite the degraded sensory responses, adaptation resulted in a shift in coding strategy that favors theoretical discrimination over detection across the observed timescales of adaptation. Overall, although multiple mechanisms contribute to rapid adaptation at distinct timescales, they support a unifying framework on the role of adaptation in sensory processing.

Classical-Contextual Interactions in V1 May Rely on Dendritic Computations

A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange "contextual" information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by "asking" natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The "answer" was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the "multiplicative" center-flanker interactions previously reported in V1 neurons (Kapadia et al., 1995, 2000; Polat et al., 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed by NMDAR-dependent spatial synaptic interactions within PN dendrites - the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.

Brivaracetam Modulates Short-Term Synaptic Activity and Low-Frequency Spontaneous Brain Activity by Delaying Synaptic Vesicle Recycling in Two Distinct Rodent Models of Epileptic Seizures

Brivaracetam (BRV) is an anti-seizure drug for the treatment of focal and generalized epileptic seizures shown to augment short-term synaptic fatigue by slowing down synaptic vesicle recycling rates in control animals. In this study, we sought to investigate whether altered short-term synaptic activities could be a pathological hallmark during the interictal periods of epileptic seizures in two well-established rodent models, as well as to reveal BRV's therapeutic roles in altered short-term synaptic activities and low-frequency band spontaneous brain hyperactivity in these models. In our study, the electrophysiological field excitatory post-synaptic potential (fEPSP) recordings were performed in rat hippocampal brain slices from the CA1 region by stimulation of the Schaffer collateral/commissural pathway with or without BRV (30 μM for 3 h) in control or epileptic seizure (induced by pilocarpine (PILO) or high potassium (h-K⁺)) models. Short-term synaptic activities were induced by 5, 10, 20, and 40-Hz stimulation sequences. The effects of BRV on pre-synaptic vesicle mobilization were visually assessed by staining the synaptic vesicles with FM1-43 dye followed by imaging with a two-photon microscope. In the fEPSP measurements, short-term synaptic fatigue was found in the control group, while short-term synaptic potentiation (STP) was detected in both PILO and h-K⁺ models. STP was decreased after the slices were treated with BRV (30 μM) for 3 h. BRV also exhibited its therapeutic benefits by decreasing abnormal peak power (frequency range of 8-13 Hz, 31% of variation for PILO model, 25% of variation for h-K⁺ model) and trough power (frequency range of 1-4 Hz, 66% of variation for PILO model, 49% of variation for h-K⁺ model), and FM1-43 stained synaptic vesicle mobility (64% of the variation for PILO model, 45% of the variation for h-K⁺ model) in these epileptic seizure models. To the best of our knowledge, this was the first report that BRV decreased the STP and abnormal low-frequency brain activities during the interictal phase of epileptic seizures by slowing down the mobilization of synaptic vesicles in two rodent models. These mechanistic findings would greatly advance our understanding of BRV's pharmacological role in pathomechanisms of epileptic seizures and its treatment strategy optimization to avoid or minimize BRV-induced possible adverse side reactions.

Feedforward mechanisms of cross-orientation interactions in mouse V1

Sensory neurons are modulated by context. For example, in mouse primary visual cortex (V1), neuronal responses to the preferred orientation are modulated by the presence of superimposed orientations ("plaids"). The effects of this modulation are diverse; some neurons are suppressed, while others have larger responses to a plaid than its components. We investigated whether this diversity could be explained by a unified circuit mechanism. We report that this masking is maintained during suppression of cortical activity, arguing against cortical mechanisms. Instead, the heterogeneity of plaid responses is explained by an interaction between stimulus geometry and orientation tuning. Highly selective neurons are uniformly suppressed by plaids, whereas the effects in weakly selective neurons depend on the spatial configuration of the stimulus, transitioning systematically between suppression and facilitation. Thus, the diverse responses emerge as a consequence of the spatial structure of feedforward inputs, with no need to invoke cortical interactions.

Top-down influence affects the response adaptation of V1 neurons in cats

The visual system lowers its perceptual sensitivity to a prolonged presentation of the same visual signal. This brain plasticity, called visual adaptation, is generally attributed to the response adaptation of neurons in the visual cortex. Although well-studied in the neurons of the primary visual cortex (V1), the contribution of high-level visual cortical regions to the response adaptation of V1 neurons is unclear. In the present study, we measured the response adaptation strength of V1 neurons before and after the top-down influence of the area 21a (A21a), a higher-order visual cortex homologous to the primate V4 area, was modulated with a noninvasive tool of transcranial direct current stimulation (tDCS). Our results showed that the response adaptation of V1 neurons enhanced significantly after applying anode (a-) tDCS in A21a when compared with that before a-tDCS, whereas the response adaptation of V1 neurons weakened after cathode (c-) tDCS relative to before c-tDCS in A21a. By contrast, sham (s-) tDCS in A21a had no significant impact on the response adaptation of V1 neurons. Further analysis indicated that a-tDCS in A21a significantly increased both the initial response (IR) of V1 neurons to the first several (five) trails of visual stimulation and the plateau response (PR) to the prolonged visual stimulation; the increase in PR was lower than in IR, which caused an enhancement in response adaptation. Conversely, c-tDCS significantly decreased both IR and PR of V1 neurons; the reduction in PR was smaller than in IR, which resulted in a weakness in response adaptation. Furthermore, the tDCS-induced changes of V1 neurons in response and response adaptation could recover after tDCS effect vanished, but did not occur after the neuronal activity in A21a was silenced by electrolytic lesions. These results suggest that the top-down influence of A21a may alter the response adaptation of V1 neurons through activation of local inhibitory circuitry, which enhances network inhibition in the V1 area upon an increased top-down input, weakens inhibition upon a decreased top-down input, and thus maintains homeostasis of V1 neurons in response to the long-presenting visual signals.

Frequency-dependent gating of feedforward inhibition in thalamofrontal synapses

Thalamic recruitment of feedforward inhibition is known to enhance the fidelity of the receptive field by limiting the temporal window during which cortical neurons integrate excitatory inputs. Feedforward inhibition driven by the mediodorsal nucleus of the thalamus (MD) has been previously observed, but its physiological function and regulation remain unknown. Accumulating evidence suggests that elevated neuronal activity in the prefrontal cortex is required for the short-term storage of information. Furthermore, the elevated neuronal activity is supported by the reciprocal connectivity between the MD and the medial prefrontal cortex (mPFC). Therefore, detailed knowledge about the synaptic connections during high-frequency activity is critical for understanding the mechanism of short-term memory. In this study, we examined how feedforward inhibition of thalamofrontal connectivity is modulated by activity frequency. We observed greater short-term synaptic depression during disynaptic inhibition than in thalamic excitatory synapses during high-frequency activities. The strength of feedforward inhibition became weaker as the stimulation continued, which, in turn, enhanced the range of firing jitter in a frequency-dependent manner. We postulated that this phenomenon was primarily due to the increased failure rate of evoking action potentials in parvalbumin-expressing inhibitory neurons. These findings suggest that the MD-mPFC pathway is dynamically regulated by an excitatory-inhibitory balance in an activity-dependent manner. During low-frequency activities, excessive excitations are inhibited, and firing is restricted to a limited temporal range by the strong feedforward inhibition. However, during high-frequency activities, such as during short-term memory, the activity can be transferred in a broader temporal range due to the decreased feedforward inhibition.

Spatio-temporal properties of sleep slow waves and implications for development

Objective sleep quality can be measured by electroencephalography (EEG), a non-invasive technique to quantify electrical activity generated by the brain. With EEG, sleep depth is measured by appearance and an increase in slow wave activity (scalp-SWA). EEG slow waves (scalp-SW) are the manifestation of underlying synchronous membrane potential transitions between silent (DOWN) and active (UP) states. This bistable periodic rhythm is defined as slow oscillation (SO). During its "silent state" cortical neurons are hyperpolarized and appear inactive, while during its "active state" cortical neurons are depolarized, fire spikes and exhibit continuous synaptic activity, excitatory and inhibitory. In adults, data from high-density EEG revealed that scalp-SW propagate across the cortical mantle in complex patterns. However, scalp-SW propagation undergoes modifications across development. We present novel data from children, indicating that scalp-SW originate centro-parietally, and emerge more frontally by adolescence. Based on the concept that SO and SW could actively modify neuronal connectivity, we discuss whether they fulfill a key purpose in brain development by actively conveying modifications of the maturing brain.

Disparities in Short-Term Depression Among Prefrontal Cortex Synapses Sustain Persistent Activity in a Balanced Network

Persistent activity of cue-representing neurons in the prefrontal cortex (PFC) is regarded as a neural basis for working memory. The contribution of short-term synaptic plasticity (STP) at different types of synapses comprising the cortical network to persistent activity, however, remains unclear. Characterizing STP at synapses of the rat PFC layer 5 network, we found that PFC synapses exhibit distinct STP patterns according to presynaptic and postsynaptic identities. Excitatory postsynaptic currents (EPSCs) from corticopontine (Cpn) neurons were well sustained throughout continued activity, with stronger depression at synapses onto fast-spiking interneurons than those onto pyramidal cells. Inhibitory postsynaptic currents (IPSCs) were sustained at a weaker level compared with EPSC from Cpn synapses. Computational modeling of a balanced network incorporating empirically observed STP revealed that little depression at recurrent excitatory synapses, combined with stronger depression at other synapses, could provide the PFC with a unique synaptic mechanism for the generation and maintenance of persistent activity.

Temporal Contingencies Determine Whether Adaptation Strengthens or Weakens Normalization

A fundamental and nearly ubiquitous feature of sensory encoding is that neuronal responses are strongly influenced by recent experience, or adaptation. Theoretical and computational studies have proposed that many adaptation effects may result in part from changes in the strength of normalization signals. Normalization is a "canonical" computation in which a neuron's response is modulated (normalized) by the pooled activity of other neurons. Here, we test whether adaptation can alter the strength of cross-orientation suppression, or masking, a paradigmatic form of normalization evident in primary visual cortex (V1). We made extracellular recordings of V1 neurons in anesthetized male macaques and measured responses to plaid stimuli composed of two overlapping, orthogonal gratings before and after prolonged exposure to two distinct adapters. The first adapter was a plaid consisting of orthogonal gratings and led to stronger masking. The second adapter presented the same orthogonal gratings in an interleaved manner and led to weaker masking. The strength of adaptation's effects on masking depended on the orientation of the test stimuli relative to the orientation of the adapters, but was independent of neuronal orientation preference. Changes in masking could not be explained by altered neuronal responsivity. Our results suggest that normalization signals can be strengthened or weakened by adaptation depending on the temporal contingencies of the adapting stimuli. Our findings reveal an interplay between two widespread computations in cortical circuits, adaptation and normalization, that enables flexible adjustments to the structure of the environment, including the temporal relationships among sensory stimuli.SIGNIFICANCE STATEMENT Two fundamental features of sensory responses are that they are influenced by adaptation and that they are modulated by the activity of other nearby neurons via normalization. Our findings reveal a strong interaction between these two aspects of cortical computation. Specifically, we show that cross-orientation masking, a form of normalization, can be strengthened or weakened by adaptation depending on the temporal contingencies between sensory inputs. Our findings support theoretical proposals that some adaptation effects may involve altered normalization and offer a network-based explanation for how cortex adjusts to current sensory demands.

Mechanisms of Orientation Selectivity in the Primary Visual Cortex

The mechanisms underlying the emergence of orientation selectivity in the visual cortex have been, and continue to be, the subjects of intense scrutiny. Orientation selectivity reflects a dramatic change in the representation of the visual world: Whereas afferent thalamic neurons are generally orientation insensitive, neurons in the primary visual cortex (V1) are extremely sensitive to stimulus orientation. This profound change in the receptive field structure along the visual pathway has positioned V1 as a model system for studying the circuitry that underlies neural computations across the neocortex. The neocortex is characterized anatomically by the relative uniformity of its circuitry despite its role in processing distinct signals from region to region. A combination of physiological, anatomical, and theoretical studies has shed some light on the circuitry components necessary for generating orientation selectivity in V1. This targeted effort has led to critical insights, as well as controversies, concerning how neural circuits in the neocortex perform computations.

Prominent facilitation at beta and gamma frequency range revealed with physiological calcium concentration in adult mouse piriform cortex in vitro

Neuronal activity is characterized by a diversity of oscillatory phenomena that are associated with multiple behavioral and cognitive processes, yet the functional consequences of these oscillations are not fully understood. Our aim was to determine whether and how these different oscillatory activities affect short-term synaptic plasticity (STP), using the olfactory system as a model. In response to odorant stimuli, the olfactory bulb displays a slow breathing rhythm as well as beta and gamma oscillations. Since the firing of olfactory bulb projecting neurons is phase-locked with beta and gamma oscillations, structures downstream from the olfactory bulb should be driven preferentially at these frequencies. We examined STP exhibited by olfactory bulb inputs in slices of adult mouse piriform cortex maintained in vitro in an in vivo-like ACSF (calcium concentration: 1.1 mM). We replaced the presynaptic neuronal firing rate by repeated electrical stimulation (frequency between 3.125 and 100 Hz) applied to the lateral olfactory tract. Our results revealed a considerable enhancement of postsynaptic response amplitude for stimulation frequencies in the beta and gamma range. A phenomenological model of STP fitted to the data suggests that the experimental results can be explained by the interplay between three mechanisms: a short-term facilitation mechanism (time constant ≈160 msec), and two short-term depression mechanisms (recovery time constants <20 msec and ≈140 msec). Increasing calcium concentration (2.2 mM) resulted in an increase in the time constant of facilitation and in a strengthening of the slowest depression mechanism. As a result, response enhancement was reduced and its peak shifted toward the low beta and alpha ranges while depression became predominant in the gamma band. Using environmental conditions corresponding to those that prevail in vivo, our study shows that STP in the lateral olfactory tract to layer Ia synapse allows amplification of olfactory bulb inputs at beta and gamma frequencies.

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.

Sleep slow oscillation and plasticity

It is well documented that sleep contributes to memory consolidation and it is also accepted that long-term synaptic plasticity plays a critical role in memory formation. The mechanisms of this sleep-dependent memory formation are unclear. Two main hypotheses are proposed. According to the first one, synapses are potentiated during wake; and during sleep they are scaled back to become available for the learning tasks in the next day. The other hypothesis is that sleep slow oscillations potentiate synapses that were depressed due to persistent activities during the previous day and that potentiation provides physiological basis for memory consolidation. The objective of this review is to group information on whether cortical synapses are up-scaled or down-scaled during sleep. We conclude that the majority of cortical synapses are up-regulated by sleep slow oscillation.

Potential Role of Synaptic Activity to Inhibit LTD Induction in Rat Visual Cortex

Long-term depression (LTD), a widely studied form of activity-dependent synaptic plasticity, is typically induced by prolonged low-frequency stimulation (LFS). Interestingly, LFS is highly effective in eliciting LTD in vitro, but much less so under in vivo conditions; the reasons for the resistance of the intact brain to express LTD are not well understood. We examined if levels of background electrocorticographic (ECoG) activity influence LTD induction in the thalamocortical visual system of rats under very deep urethane anesthesia, inducing a brain state of reduced spontaneous cortical activity. Under these conditions, LFS applied to the lateral geniculate nucleus resulted in LTD of field postsynaptic potentials (fPSPs) recorded in the primary visual cortex (V1). Pairing LFS with stimulation of the brainstem (pedunculopontine) reticular formation resulted in the appearance of faster, more complex activity in V1 and prevented LTD induction, an effect that did not require muscarinic or nicotinic receptors. Reticular stimulation alone (without LFS) had no effect on cortical fPSPs. These results show that excitation of the brainstem activating system blocks the induction of LTD in V1. Thus, higher levels of neural activity may inhibit depression at cortical synapses, a hypothesis that could explain discrepancies regarding LTD induction in previous in vivo and in vitro work.

Cardiac Arrest-Induced Global Brain Hypoxia-Ischemia during Development Affects Spontaneous Activity Organization in Rat Sensory and Motor Thalamocortical Circuits during Adulthood

Normal maturation of sensory information processing in the cortex requires patterned synaptic activity during developmentally regulated critical periods. During early development, spontaneous synaptic activity establishes required patterns of synaptic input, and during later development it influences patterns of sensory experience-dependent neuronal firing. Thalamocortical neurons occupy a critical position in regulating the flow of patterned sensory information from the periphery to the cortex. Abnormal thalamocortical inputs may permanently affect the organization and function of cortical neuronal circuits, especially if they occur during a critical developmental window. We examined the effect of cardiac arrest (CA)-associated global brain hypoxia-ischemia in developing rats on spontaneous and evoked firing of somatosensory thalamocortical neurons and on large-scale correlations in the motor thalamocortical circuit. The mean spontaneous and sensory-evoked firing rate activity and variability were higher in CA injured rats. Furthermore, spontaneous and sensory-evoked activity and variability were correlated in uninjured rats, but not correlated in neurons from CA rats. Abnormal activity patterns of ventroposterior medial nucleus (VPm) neurons persisted into adulthood. Additionally, we found that neurons in the entopeduncular nucleus (EPN) in the basal ganglia had lower firing rates yet had higher variability and higher levels of burst firing after injury. Correlated levels of power in local field potentials (LFPs) between the EPN and the motor cortex (MCx) were also disrupted by injury. Our findings indicate that hypoxic-ischemic injury during development leads to abnormal spontaneous and sensory stimulus-evoked input patterns from thalamus to cortex. Abnormal thalamic inputs likely permanently and detrimentally affect the organization of cortical circuitry and processing of sensory information. Hypoxic-ischemic injury also leads to abnormal single neuron and population level activity in the basal ganglia that may contribute to motor dysfunction after injury. Combination of deficits in sensory and motor thalamocortical circuit function may negatively impact sensorimotor integration in CA survivors. Modulation of abnormal activity patterns post-injury may represent a novel therapeutic target to improve neurologic function in survivors.

Presynaptic Adenosine Receptor-Mediated Regulation of Diverse Thalamocortical Short-Term Plasticity in the Mouse Whisker Pathway

Short-term synaptic plasticity (STP) sets the sensitivity of a synapse to incoming activity and determines the temporal patterns that it best transmits. In “driver” thalamocortical (TC) synaptic populations, STP is dominated by depression during stimulation from rest. However, during ongoing stimulation, lemniscal TC connections onto layer 4 neurons in mouse barrel cortex express variable STP. Each synapse responds to input trains with a distinct pattern of depression or facilitation around its mean steady-state response. As a result, in common with other synaptic populations, lemniscal TC synapses express diverse rather than uniform dynamics, allowing for a rich representation of temporally varying stimuli. Here, we show that this STP diversity is regulated presynaptically. Presynaptic adenosine receptors of the A1R type, but not kainate receptors (KARs), modulate STP behavior. Blocking the receptors does not eliminate diversity, indicating that diversity is related to heterogeneous expression of multiple mechanisms in the pathway from presynaptic calcium influx to neurotransmitter release.

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.

Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model

Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural) is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

Open-loop organization of thalamic reticular nucleus and dorsal thalamus: a computational model

The thalamic reticular nucleus (TRN) is a shell of GABAergic neurons that surrounds the dorsal thalamus. Previous work has shown that TRN neurons send GABAergic projections to thalamocortical (TC) cells to form reciprocal, closed-loop circuits. This has led to the hypothesis that the TRN is responsible for oscillatory phenomena, such as sleep spindles and absence seizures. However, there is emerging evidence that open-loop circuits are also found between TRN and TC cells. The implications of open-loop configurations are not yet known, particularly when they include time-dependent nonlinearities in TC cells such as low-threshold bursting. We hypothesized that low-threshold bursting in an open-loop circuit could be a mechanism by which the TRN could paradoxically enhance TC activation, and that enhancement would depend on the relative timing of TRN vs. TC cell stimulation. To test this, we modeled small circuits containing TC neurons, TRN neurons, and layer 4 thalamorecipient cells in both open- and closed-loop configurations. We found that open-loop TRN stimulation, rather than universally depressing TC activation, increased cortical output across a broad parameter space, modified the filter properties of TC neurons, and altered the mutual information between input and output in a frequency-dependent and T-type calcium channel-dependent manner. Therefore, an open-loop model of TRN-TC interactions, rather than suppressing transmission through the thalamus, creates a tunable filter whose properties may be modified by outside influences onto the TRN. These simulations make experimentally testable predictions about the potential role for the TRN for flexible enhancement of cortical activation.

NMDA receptors are the basis for persistent network activity in neocortex slices

During behavioral quiescence the neocortex generates spontaneous slow oscillations that consist of Up and Down states. Up states are short epochs of persistent activity, but their underlying source is unclear. In neocortex slices of adult mice, we monitored several cellular and network variables during the transition between a traditional buffer, which does not cause Up states, and a lower-divalent cation buffer, which leads to the generation of Up states. We found that the resting membrane potential and input resistance of cortical cells did not change with the development of Up states. The synaptic efficacy of excitatory postsynaptic potentials mediated by non-NMDA receptors was slightly reduced, but this is unlikely to facilitate the generation of Up states. On the other hand, we identified two variables that are associated with the generation of Up states: an enhancement of the intrinsic firing excitability of cortical cells and an enhancement of NMDA-mediated responses evoked by electrical or optogenetic stimulation. The fact that blocking NMDA receptors abolishes Up states indicates that the enhancement in intrinsic firing excitability alone is insufficient to generate Up states. NMDA receptors have a crucial role in the generation of Up states in neocortex slices.

Gain modulation of synaptic inputs by network state in auditory cortex in vivo

The cortical network recurrent circuitry generates spontaneous activity organized into Up (active) and Down (quiescent) states during slow-wave sleep or anesthesia. These different states of cortical activation gain modulate synaptic transmission. However, the reported modulation that Up states impose on synaptic inputs is disparate in the literature, including both increases and decreases of responsiveness. Here, we tested the hypothesis that such disparate observations may depend on the intensity of the stimulation. By means of intracellular recordings, we studied synaptic transmission during Up and Down states in rat auditory cortex in vivo. Synaptic potentials were evoked either by auditory or electrical (thalamocortical, intracortical) stimulation while randomly varying the intensity of the stimulus. Synaptic potentials evoked by the same stimulus intensity were compared in Up/Down states. Up states had a scaling effect on the stimulus-evoked synaptic responses: the amplitude of weaker responses was potentiated whereas that of larger responses was maintained or decreased with respect to the amplitude during Down states. We used a computational model to explore the potential mechanisms explaining this nontrivial stimulus-response relationship. During Up/Down states, there is different excitability in the network and the neuronal conductance varies. We demonstrate that the competition between presynaptic recruitment and the changing conductance might be the central mechanism explaining the experimentally observed stimulus-response relationships. We conclude that the effect that cortical network activation has on synaptic transmission is not constant but contingent on the strength of the stimulation, with a larger modulation for stimuli involving both thalamic and cortical networks.

Effects of surround suppression on response adaptation of V1 neurons to visual stimuli

The influence of intracortical inhibition on the response adaptation of visual cortical neurons remains in debate. To clarify this issue, in the present study the influence of surround suppression evoked through the local inhibitory interneurons on the adaptation effects of neurons in the primary visual cortex (V1) were observed. Moreover, the adaptations of V1 neurons to both the high-contrast visual stimuli presented in the classical receptive field (CRF) and to the costimulation presented in the CRF and the surrounding nonclassical receptive field (nCRF) were compared. The intensities of surround suppression were modulated with different sized grating stimuli. The results showed that the response adaptation of V1 neurons decreased significantly with the increase of surround suppression and this adaptation decrease was due to the reduction of the initial response of V1 neurons to visual stimuli. However, the plateau response during adaptation showed no significant changes. These findings indicate that the adaptation effects of V1 neurons may not be directly affected by surround suppression, but may be dynamically regulated by a negative feedback network and be finely adjusted by its initial spiking response to stimulus. This adaptive regulation is not only energy efficient for the central nervous system, but also beneficially acts to maintain the homeostasis of neuronal response to long-presenting visual signals.

Diverse thalamocortical short-term plasticity elicited by ongoing stimulation

To produce sensation, neuronal pathways must transmit and process stimulus patterns that unfold over time. This behavior is determined by short-term synaptic plasticity (STP), which shapes the temporal filtering properties of synapses in a pathway. We explored STP variability across thalamocortical (TC) synapses, measuring whole-cell responses to stimulation of TC fibers in layer 4 neurons of mouse barrel cortex in vitro. As expected, STP during stimulation from rest was dominated by depression. However, STP during ongoing stimulation was strikingly diverse across TC connections. Diversity took the form of variable tuning to the latest interstimulus interval: some connections responded weakly to shorter intervals, while other connections were facilitated. These behaviors did not cluster into categories but formed a continuum. Diverse tuning did not require disynaptic inhibition. Hence, monosynaptic excitatory lemniscal TC connections onto layer 4 do not behave uniformly during ongoing stimulation. Each connection responds differentially to particular stimulation intervals, enriching the ability of the pathway to convey complex, temporally fluctuating information.

Integration over multiple timescales in primary auditory cortex

Speech and other natural vocalizations are characterized by large modulations in their sound envelope. The timing of these modulations contains critical information for discrimination of important features, such as phonemes. We studied how depression of synaptic inputs, a mechanism frequently reported in cortex, can contribute to the encoding of envelope dynamics. Using a nonlinear stimulus-response model that accounted for synaptic depression, we predicted responses of neurons in ferret primary auditory cortex (A1) to stimuli with natural temporal modulations. The depression model consistently performed better than linear and second-order models previously used to characterize A1 neurons, and it produced more biologically plausible fits. To test how synaptic depression can contribute to temporal stimulus integration, we used nonparametric maximum a posteriori decoding to compare the ability of neurons showing and not showing depression to reconstruct the stimulus envelope. Neurons showing evidence for depression reconstructed stimuli over a longer range of latencies. These findings suggest that variation in depression across the cortical population supports a rich code for representing the temporal dynamics of natural sounds.

Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neurons

Synaptic noise is thought to be a limiting factor for computational efficiency in the brain. In visual cortex (V1), ongoing activity is present in vivo, and spiking responses to simple stimuli are highly unreliable across trials. Stimulus statistics used to plot receptive fields, however, are quite different from those experienced during natural visuomotor exploration. We recorded V1 neurons intracellularly in the anaesthetized and paralyzed cat and compared their spiking and synaptic responses to full field natural images animated by simulated eye-movements to those evoked by simpler (grating) or higher dimensionality statistics (dense noise). In most cells, natural scene animation was the only condition where high temporal precision (in the 10–20 ms range) was maintained during sparse and reliable activity. At the subthreshold level, irregular but highly reproducible membrane potential dynamics were observed, even during long (several 100 ms) “spike-less” periods. We showed that both the spatial structure of natural scenes and the temporal dynamics of eye-movements increase the signal-to-noise ratio by a non-linear amplification of the signal combined with a reduction of the subthreshold contextual noise. These data support the view that the sparsening and the time precision of the neural code in V1 may depend primarily on three factors: (1) broadband input spectrum: the bandwidth must be rich enough for recruiting optimally the diversity of spatial and time constants during recurrent processing; (2) tight temporal interplay of excitation and inhibition: conductance measurements demonstrate that natural scene statistics narrow selectively the duration of the spiking opportunity window during which the balance between excitation and inhibition changes transiently and reversibly; (3) signal energy in the lower frequency band: a minimal level of power is needed below 10 Hz to reach consistently the spiking threshold, a situation rarely reached with visual dense noise.

Transcranial alternating current stimulation modulates large-scale cortical network activity by network resonance

Transcranial direct current stimulation (tDCS) has emerged as a potentially safe and effective brain stimulation modality that alters cortical excitability by passing a small, constant electric current through the scalp. tDCS creates an electric field that weakly modulates the membrane voltage of a large number of cortical neurons. Recent human studies have suggested that sine-wave stimulation waveforms [transcranial alternating current stimulation (tACS)] represent a more targeted stimulation paradigm for the enhancement of cortical oscillations. Yet, the underlying mechanisms of how periodic, weak global perturbations alter the spatiotemporal dynamics of large-scale cortical network dynamics remain a matter of debate. Here, we simulated large-scale networks of spiking neuron models to address this question in endogenously rhythmic networks. We identified distinct roles of the depolarizing and hyperpolarizing phases of tACS in entrainment, which entailed moving network activity toward and away from a strong nonlinearity provided by the local excitatory coupling of pyramidal cells. Together, these mechanisms gave rise to resonance dynamics characterized by an Arnold tongue centered on the resonance frequency of the network. We then performed multichannel extracellular recordings of multiunit firing activity during tACS in anesthetized ferrets (Mustela putoris furo), a model species with a gyrencephalic brain, to verify that weak global perturbations can selectively enhance oscillations at the applied stimulation frequency. Together, these results provide a detailed mechanistic understanding of tACS at the level of large-scale network dynamics and support the future design of activity-dependent feedback tACS paradigms that dynamically tailor stimulation frequency to the spectral peak of ongoing brain activity.

Extensive excitatory network interactions shape temporal processing of communication signals in a model sensory system

Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.

Mechanisms of neuronal computation in mammalian visual cortex

Orientation selectivity in the primary visual cortex (V1) is a receptive field property that is at once simple enough to make it amenable to experimental and theoretical approaches and yet complex enough to represent a significant transformation in the representation of the visual image. As a result, V1 has become an area of choice for studying cortical computation and its underlying mechanisms. Here we consider the receptive field properties of the simple cells in cat V1--the cells that receive direct input from thalamic relay cells--and explore how these properties, many of which are highly nonlinear, arise. We have found that many receptive field properties of V1 simple cells fall directly out of Hubel and Wiesel's feedforward model when the model incorporates realistic neuronal and synaptic mechanisms, including threshold, synaptic depression, response variability, and the membrane time constant.

Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex

Short-term synaptic depression (STD) is a form of synaptic plasticity that has a large impact on network computations. Experimental results suggest that STD is modulated by cortical activity, decreasing with activity in the network and increasing during silent states. Here, we explored different activity-modulation protocols in a biophysical network model for which the model displayed less STD when the network was active than when it was silent, in agreement with experimental results. Furthermore, we studied how trains of synaptic potentials had lesser decay during periods of activity (UP states) than during silent periods (DOWN states), providing new experimental predictions. We next tackled the inverse question of what is the impact of modifying STD parameters on the emergent activity of the network, a question difficult to answer experimentally. We found that synaptic depression of cortical connections had a critical role to determine the regime of rhythmic cortical activity. While low STD resulted in an emergent rhythmic activity with short UP states and long DOWN states, increasing STD resulted in longer and more frequent UP states interleaved with short silent periods. A still higher synaptic depression set the network into a non-oscillatory firing regime where DOWN states no longer occurred. The speed of propagation of UP states along the network was not found to be modulated by STD during the oscillatory regime; it remained relatively stable over a range of values of STD. Overall, we found that the mutual interactions between synaptic depression and ongoing network activity are critical to determine the mechanisms that modulate cortical emergent patterns.

Developmental shift of short-term synaptic plasticity in cortical organotypic slices

Although short-term synaptic plasticity (STP) is ubiquitous in neocortical synapses its functional role in neural computations is not well understood. Critical to elucidating the function of STP will be to understand how STP itself changes with development and experience. Previous studies have reported developmental changes in STP using acute slices. It is not clear, however, to what extent the changes in STP are a function of local ontogenetic programs or the result of the many different sensory and experience-dependent changes that accompany development in vivo. To address this question we examined the in vitro development of STP in organotypic slices cultured for up to 4 weeks. Paired recordings were performed in L5 pyramidal neurons at different stages of in vitro development. We observed a shift in STP in the form of a decrease in the paired-pulse ratio (PPR) (less depression) from the second to fourth week in vitro. This shift in STP was not accompanied by a change in initial excitatory postsynaptic potential (EPSP) amplitude. Fitting STP to a quantitative model indicated that the developmental shift is consistent with presynaptic changes. Importantly, despite the change in the PPR we did not observe changes in the time constant governing STP. Since these experiments were conducted in vitro our results indicate that the shift in STP does not depend on in vivo sensory experience. Although sensory experience may shape STP, we suggest that developmental shifts in STP are at least in part ontogenetically determined.

A cortical attractor network with Martinotti cells driven by facilitating synapses

The population of pyramidal cells significantly outnumbers the inhibitory interneurons in the neocortex, while at the same time the diversity of interneuron types is much more pronounced. One acknowledged key role of inhibition is to control the rate and patterning of pyramidal cell firing via negative feedback, but most likely the diversity of inhibitory pathways is matched by a corresponding diversity of functional roles. An important distinguishing feature of cortical interneurons is the variability of the short-term plasticity properties of synapses received from pyramidal cells. The Martinotti cell type has recently come under scrutiny due to the distinctly facilitating nature of the synapses they receive from pyramidal cells. This distinguishes these neurons from basket cells and other inhibitory interneurons typically targeted by depressing synapses. A key aspect of the work reported here has been to pinpoint the role of this variability. We first set out to reproduce quantitatively based on in vitro data the di-synaptic inhibitory microcircuit connecting two pyramidal cells via one or a few Martinotti cells. In a second step, we embedded this microcircuit in a previously developed attractor memory network model of neocortical layers 2/3. This model network demonstrated that basket cells with their characteristic depressing synapses are the first to discharge when the network enters an attractor state and that Martinotti cells respond with a delay, thereby shifting the excitation-inhibition balance and acting to terminate the attractor state. A parameter sensitivity analysis suggested that Martinotti cells might, in fact, play a dominant role in setting the attractor dwell time and thus cortical speed of processing, with cellular adaptation and synaptic depression having a less prominent role than previously thought.

Synaptic properties of corticocortical connections between the primary and secondary visual cortical areas in the mouse

Despite the importance of corticocortical connections, few published studies have investigated the functional, synaptic properties of such connections in any species, because most studies have been purely anatomical or aimed at functional features other than synaptic properties. We recently published a study of synaptic properties of connections between the primary and secondary cortical auditory areas in brain slices from the mouse, and, in the present study, we aimed to extend this by performing analogous studies of the primary and secondary visual areas (V1 and V2). We found effectively the same results. That is, connections between V1 and V2 in both directions were quite similar; in each case, the glutamatergic inputs could be classified as one of two types, Class 1B (formerly "driver") and Class 2 (formerly "modulator"). There is a clear laminar correlation for these different inputs, in terms of both the laminae of origin and those in which the recorded cells were located. Our data suggest a common pattern to the functional organization of corticocortical connectivity in the mouse cortex.

Developmental changes in short-term plasticity at the rat calyx of Held synapse

The calyx of Held synapse of the medial nucleus of the trapezoid body functions as a relay synapse in the auditory brainstem. In vivo recordings have shown that this synapse displays low release probability and that the average size of synaptic potentials does not depend on recent history. We used a ventral approach to make in vivo extracellular recordings from the calyx of Held synapse in rats aged postnatal day 4 (P4) to P29 to study the developmental changes that allow this synapse to function as a relay. Between P4 and P8, we observed evidence for the presence of large short-term depression, which was counteracted by short-term facilitation at short intervals. Major changes occurred in the last few days before the onset of hearing for air-borne sounds, which happened at P13. The bursting pattern changed into a primary-like pattern, the amount of depression and facilitation decreased strongly, and the decay of facilitation became much faster. Whereas short-term plasticity was the most important cause of variability in the size of the synaptic potentials in immature animals, its role became minor around hearing onset and afterward. Similar developmental changes were observed during stimulation experiments both in brain slices and in vivo following cochlear ablation. Our data suggest that the strong reduction in release probability and the speedup of the decay of synaptic facilitation that happen just before hearing onset are important events in the transformation of the calyx of Held synapse into an auditory relay synapse.

Striatal fast-spiking interneurons: from firing patterns to postsynaptic impact

In the striatal microcircuit, fast-spiking (FS) interneurons have an important role in mediating inhibition onto neighboring medium spiny (MS) projection neurons. In this study, we combined computational modeling with in vitro and in vivo electrophysiological measurements to investigate FS cells in terms of their discharge properties and their synaptic efficacies onto MS neurons. In vivo firing of striatal FS interneurons is characterized by a high firing variability. It is not known, however, if this variability results from the input that FS cells receive, or if it is promoted by the stuttering spike behavior of these neurons. Both our model and measurements in vitro show that FS neurons that exhibit random stuttering discharge in response to steady depolarization do not show the typical stuttering behavior when they receive fluctuating input. Importantly, our model predicts that electrically coupled FS cells show substantial spike synchronization only when they are in the stuttering regime. Therefore, together with the lack of synchronized firing of striatal FS interneurons that has been reported in vivo, these results suggest that neighboring FS neurons are not in the stuttering regime simultaneously and that in vivo FS firing variability is more likely determined by the input fluctuations. Furthermore, the variability in FS firing is translated to variability in the postsynaptic amplitudes in MS neurons due to the strong synaptic depression of the FS-to-MS synapse. Our results support the idea that these synapses operate over a wide range from strongly depressed to almost fully recovered. The strong inhibitory effects that FS cells can impose on their postsynaptic targets, and the fact that the FS-to-MS synapse model showed substantial depression over extended periods of time might indicate the importance of cooperative effects of multiple presynaptic FS interneurons and the precise orchestration of their activity.

Factors controlling the input-output relationship of spherical bushy cells in the gerbil cochlear nucleus

Despite the presence of large endbulb inputs, the spherical bushy cells (SBCs) of the rostral anteroventral cochlear nucleus do not function as simple auditory relays. We used the good signal-to-noise ratio of juxtacellular recordings to dissect the intrinsic and network mechanisms controlling the input-output relationship of SBCs in anesthetized gerbils. The SBCs generally operated close to action potential (AP) threshold and showed no evidence for synaptic depression, suggesting that the endbulbs of Held have low release probability in vivo. Analysis of the complex waveforms suggested that in the absence of auditory stimulation, postsynaptic spike depression and stochastic fluctuations in EPSP size were the main factors determining jitter and reliability of the endbulb synapse. During auditory stimulation, progressively larger EPSPs were needed to trigger APs at increasing sound intensities. Simulations suggested hyperpolarizing inhibition could explain the observed decrease in EPSP efficacy. Synaptic inhibition showed a delayed onset and generally had a higher threshold than excitatory inputs, but otherwise inhibition and excitation showed mostly overlapping frequency-response areas. The recruitment of synaptic inhibition caused postsynaptic spikes to be preferentially triggered by well-timed, large EPSPs, resulting in improved phase locking despite more variable EPSP-AP latencies. Our results suggest that the lack of synaptic depression, caused by low release probability, and the apparent absence of sound-evoked synaptic inhibition at low sound intensity maximize sensitivity of SBCs. At higher sound intensities, the recruitment of synaptic inhibition constrains their firing rate and optimizes their temporal precision.

Synaptic short-term plasticity in auditory cortical circuits

The auditory system must be able to adapt to changing acoustic environment and still maintain accurate representation of signals. Mechanistically, this is a difficult task because the responsiveness of a large heterogeneous population of interconnected neurons must be adjusted properly and precisely. Synaptic short-term plasticity (STP) is widely regarded as a viable mechanism for adaptive processes. Although the cellular mechanism for STP is well characterized, the overall effect on information processing at the network level is poorly understood. The main challenge is that there are many cell types in auditory cortex, each of which exhibit different forms and degrees of STP. In this article, I will review the basic properties of STP in auditory cortical circuits and discuss the possible impact on signal processing.

Power-law input-output transfer functions explain the contrast-response and tuning properties of neurons in visual cortex

We develop a unified model accounting simultaneously for the contrast invariance of the width of the orientation tuning curves (OT) and for the sigmoidal shape of the contrast response function (CRF) of neurons in the primary visual cortex (V1). We determine analytically the conditions for the structure of the afferent LGN and recurrent V1 inputs that lead to these properties for a hypercolumn composed of rate based neurons with a power-law transfer function. We investigate what are the relative contributions of single neuron and network properties in shaping the OT and the CRF. We test these results with numerical simulations of a network of conductance-based model (CBM) neurons and we demonstrate that they are valid and more robust here than in the rate model. The results indicate that because of the acceleration in the transfer function, described here by a power-law, the orientation tuning curves of V1 neurons are more tuned, and their CRF is steeper than those of their inputs. Last, we show that it is possible to account for the diversity in the measured CRFs by introducing heterogeneities either in single neuron properties or in the input to the neurons. We show how correlations among the parameters that characterize the CRF depend on these sources of heterogeneities. Comparison with experimental data suggests that both sources contribute nearly equally to the diversity of CRF shapes observed in V1 neurons.

Both the response and membrane potential of neurons in the primary visual cortex (V1) are selective to the orientation of elongated stimuli. The widths of the tuning curves, which characterize this selectivity, hardly depend on stimulus contrast whereas their amplitude does. The contrast dependence of this amplitude, the contrast response function (CRF), has a sigmoidal shape. Saturation of the spike response is substantially lower than the neurons' maximal firing rate. These well established facts constrain the possible mechanisms for orientation selectivity in V1. Furthermore, the single neuron CRFs in V1 display a broad diversity in their shape. This adds other constraints. Many theoretical works have tried to elaborate mechanisms of orientation selectivity that are compatible with the contrast invariant tuning widths. However, these mechanisms are usually incompatible with sigmoidal CRFs. We propose a mechanism which accounts simultaneously for contrast invariant tuning width for both rate and voltage response and for the shape and diversity of the CRFs. This mechanism relies on the interplay between power-law frequency-current transfer functions of single neurons, as measured in vivo in cortex, and on the recurrent interactions in the cortical circuit.

Neuronal plasticity and thalamocortical sleep and waking oscillations

Throughout life, thalamocortical (TC) network alternates between activated states (wake or rapid eye movement sleep) and slow oscillatory state dominating slow-wave sleep. The patterns of neuronal firing are different during these distinct states. I propose that due to relatively regular firing, the activated states preset some steady state synaptic plasticity and that the silent periods of slow-wave sleep contribute to a release from this steady state synaptic plasticity. In this respect, I discuss how states of vigilance affect short-, mid-, and long-term synaptic plasticity, intrinsic neuronal plasticity, as well as homeostatic plasticity. Finally, I suggest that slow oscillation is intrinsic property of cortical network and brain homeostatic mechanisms are tuned to use all forms of plasticity to bring cortical network to the state of slow oscillation. However, prolonged and profound shift from this homeostatic balance could lead to development of paroxysmal hyperexcitability and seizures as in the case of brain trauma.

Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials

During anesthesia, slow-wave sleep and quiet wakefulness, neuronal membrane potentials collectively switch between de- and hyperpolarized levels, the cortical UP and DOWN states. Previous studies have shown that these cortical UP/DOWN states affect the excitability of individual neurons in response to sensory stimuli, indicating that a significant amount of the trial-to-trial variability in neuronal responses can be attributed to ongoing fluctuations in network activity. However, as intracellular recordings are frequently not available, it is important to be able to estimate their occurrence purely from extracellular data. Here, we combine in vivo whole cell recordings from single neurons with multi-site extracellular microelectrode recordings, to quantify the performance of various approaches to predicting UP/DOWN states from the deep-layer local field potential (LFP). We find that UP/DOWN states in deep cortical layers of rat primary auditory cortex (A1) are predictable from the phase of LFP at low frequencies (< 4 Hz), and that the likelihood of a given state varies sinusoidally with the phase of LFP at these frequencies. We introduce a novel method of detecting cortical state by combining information concerning the phase of the LFP and ongoing multi-unit activity.

Sequential Reinstatement of Neocortical Activity during Slow Oscillations Depends on Cells' Global Activity

During Slow Wave Sleep (SWS), cortical activity is dominated by endogenous processes modulated by slow oscillations (0.1–1 Hz): cell ensembles fluctuate between states of sustained activity (UP states) and silent epochs (DOWN states). We investigate here the temporal structure of ensemble activity during UP states by means of multiple single unit recordings in the prefrontal cortex of naturally sleeping rats. As previously shown, the firing rate of each PFC cell peaks at a distinct time lag after the DOWN/UP transition in a consistent order. We show here that, conversely, the latency of the first spike after the UP state onset depends primarily on the session-averaged firing rates of cells (which can be considered as an indirect measure of their intrinsic excitability). This latency can be explained by a simple homogeneous process (Poisson model) of cell firing, with sleep averaged firing rates employed as parameters. Thus, at DOWN/UP transitions, neurons are affected both by a slow process, possibly originating in the cortical network, modulating the time course of firing for each cell, and by a fast, relatively stereotyped reinstatement of activity, related mostly to global activity levels.

The slow (<1 Hz) rhythm of non-REM sleep: a dialogue between three cardinal oscillators

The slow (<1 Hz) rhythm, the most important electroencephalogram (EEG) signature of non-rapid eye movement (NREM) sleep, is generally viewed as originating exclusively from neocortical networks. Here we argue that the full manifestation of this fundamental sleep oscillation in a corticothalamic module requires the dynamic interaction of three cardinal oscillators: one predominantly synaptically based cortical oscillator and two intrinsic, conditional thalamic oscillators. The functional implications of this hypothesis are discussed in relation to other EEG features of NREM sleep, with respect to coordinating activities in local and distant neuronal assemblies and in the context of facilitating cellular and network plasticity during slow-wave sleep.

Reliability and precision of the mouse calyx of Held synapse

Traditionally, the calyx of Held synapse is viewed as a highly reliable relay in the sound localization circuit of the auditory brainstem, with every presynaptic action potential triggering a postsynaptic action potential in vivo. However, this view is at odds with slice recordings that report large short-term depression (STD). To investigate the reliability and precision of this synapse, we compared slice and in vivo recordings from medial nucleus of the trapezoid body neurons of young adult mice. We show that the extracellularly recorded complex waveform can be used to estimate both presynaptic release and postsynaptic excitability. Whereas under standard slice conditions the synapse underwent large STD, both extracellular and whole-cell recordings indicated that in vivo the size of the EPSPs was independent of recent history. The estimated quantal content was typically <20 in vivo, much lower than in the resting synapse under standard slice conditions. However, due to the large quantal size and summation of EPSPs, the safety factor of this synapse was generally still sufficiently large and postsynaptic failures were observed only infrequently in vivo. When present, failures were typically due to stochastic fluctuations in EPSP size or postsynaptic spike depression. In vivo, the calyx of Held synapse thus functions as a tonic synapse. The price it pays for its low release probability is an increase in jitter and synaptic latency and occasional postsynaptic failures.

Neural coding and contextual influences in the whisker system

A fundamental problem in neuroscience, to which Prof. Segundo has made seminal contributions, is to understand how action potentials represent events in the external world. The aim of this paper is to review the issue of neural coding in the context of the rodent whiskers, an increasingly popular model system. Key issues we consider are: the role of spike timing; mechanisms of spike timing; decoding and context-dependence. Significant insight has come from the development of rigorous, information theoretic frameworks for tackling these questions, in conjunction with suitably designed experiments. We review both the theory and experimental studies. In contrast to the classical view that neurons are noisy and unreliable, it is becoming clear that many neurons in the subcortical whisker pathway are remarkably reliable and, by virtue of spike timing with millisecond-precision, have high bandwidth for conveying sensory information. In this way, even small (approximately 200 neuron) subcortical modules are able to support the sensory processing underlying sophisticated whisker-dependent behaviours. Future work on neural coding in cortex will need to consider new findings that responses are highly dependent on context, including behavioural and internal states.

Rapid neocortical dynamics: cellular and network mechanisms

The highly interconnected local and large-scale networks of the neocortical sheet rapidly and dynamically modulate their functional connectivity according to behavioral demands. This basic operating principle of the neocortex is mediated by the continuously changing flow of excitatory and inhibitory synaptic barrages that not only control participation of neurons in networks but also define the networks themselves. The rapid control of neuronal responsiveness via synaptic bombardment is a fundamental property of cortical dynamics that may provide the basis of diverse behaviors, including sensory perception, motor integration, working memory, and attention.