A quantitative description of short-term plasticity at excitatory synapses in layer 2/3 of rat primary visual cortex

Amplitude and phase-locking adaptation of neural oscillation in the rat auditory cortex in response to tone sequence

Sensory adaptation allows stimulus sensitivity to be dynamically modulated according to stimulus statistics and plays pivotal roles in efficient neural computation. Here, it is hypothesized that in the auditory cortex, phase locking of local field potentials (LFPs) to test tones exhibits an adaptation property, i.e., phase-locking adaptation, which is distinct from the amplitude adaptation of oscillatory components. Series of alternating tone sequences were applied in which the inter-tone interval (ITI) and frequency difference (ΔF) between successive tones were varied. Then, adaptation was characterized by the temporal evolution of the band-specific amplitude and phase locking evoked by the test tones. Differences as well as similarities were revealed between amplitude and phase-locking adaptations. First, both amplitude and phase-locking adaptations were enhanced by short ITIs and small ΔFs. Second, the amplitude adaptation was more effective in a higher frequency band, while the phase-locking adaptation was more effective in a lower frequency band. Third, as with the adaptation of multiunit activities (MUAs), the amplitude adaptation occurred mainly within a second, while the phase-locking showed multi-second adaptation specifically in the gamma band for short ITI and small ΔF conditions. Fourth, the amplitude adaptation and phase-locking adaptation were co-modulated in a within-second time scale, while this co-modulation was not observed in a multi-second time scale. These findings suggest that the amplitude and phase-locking adaptations have different mechanisms and functions. The phase-locking adaptation is likely to play more crucial roles in encoding a temporal structure of stimulus than the amplitude adaptation.

Temporal binding of sound emerges out of anatomical structure and synaptic dynamics of auditory cortex

The ability to represent and recognize naturally occuring sounds such as speech depends not only on spectral analysis carried out by the subcortical auditory system but also on the ability of the cortex to bind spectral information over time. In primates, these temporal binding processes are mirrored as selective responsiveness of neurons to species-specific vocalizations. Here, we used computational modeling of auditory cortex to investigate how selectivity to spectrally and temporally complex stimuli is achieved. A set of 208 microcolumns were arranged in a serial core-belt-parabelt structure documented in both humans and animals. Stimulus material comprised multiple consonant-vowel (CV) pseudowords. Selectivity to the spectral structure of the sounds was commonly found in all regions of the model (N = 122 columns out of 208), and this selectivity was only weakly affected by manipulating the structure and dynamics of the model. In contrast, temporal binding was rarer (N = 39), found mostly in the belt and parabelt regions. Thus, the serial core-belt-parabelt structure of auditory cortex is necessary for temporal binding. Further, adaptation due to synaptic depression-rendering the cortical network malleable by stimulus history-was crucial for the emergence of neurons sensitive to the temporal structure of the stimuli. Both spectral selectivity and temporal binding required that a sufficient proportion of the columns interacted in an inhibitory manner. The model and its structural modifications had a small-world structure (i.e., columns formed clusters and were within short node-to-node distances from each other). However, simulations showed that a small-world structure is not a necessary condition for spectral selectivity and temporal binding to emerge. In summary, this study suggests that temporal binding arises out of (1) the serial structure typical to the auditory cortex, (2) synaptic adaptation, and (3) inhibitory interactions between microcolumns.

A realistic neural mass model of the cortex with laminar-specific connections and synaptic plasticity - evaluation with auditory habituation

In this work we propose a biologically realistic local cortical circuit model (LCCM), based on neural masses, that incorporates important aspects of the functional organization of the brain that have not been covered by previous models: (1) activity dependent plasticity of excitatory synaptic couplings via depleting and recycling of neurotransmitters and (2) realistic inter-laminar dynamics via laminar-specific distribution of and connections between neural populations. The potential of the LCCM was demonstrated by accounting for the process of auditory habituation. The model parameters were specified using Bayesian inference. It was found that: (1) besides the major serial excitatory information pathway (layer 4 to layer 2/3 to layer 5/6), there exists a parallel "short-cut" pathway (layer 4 to layer 5/6), (2) the excitatory signal flow from the pyramidal cells to the inhibitory interneurons seems to be more intra-laminar while, in contrast, the inhibitory signal flow from inhibitory interneurons to the pyramidal cells seems to be both intra- and inter-laminar, and (3) the habituation rates of the connections are unsymmetrical: forward connections (from layer 4 to layer 2/3) are more strongly habituated than backward connections (from Layer 5/6 to layer 4). Our evaluation demonstrates that the novel features of the LCCM are of crucial importance for mechanistic explanations of brain function. The incorporation of these features into a mass model makes them applicable to modeling based on macroscopic data (like EEG or MEG), which are usually available in human experiments. Our LCCM is therefore a valuable building block for future realistic models of human cognitive function.

Modulation of synaptic depression of the calyx of Held synapse by GABA(B) receptors and spontaneous activity

The calyx of Held synapse of the medial nucleus of the trapezoid body is a giant axosomatic synapse in the auditory brainstem, which acts as a relay synapse showing little dependence of its synaptic strength on firing frequency. The main mechanism that is responsible for its resistance to synaptic depression is its large number of release sites with low release probability. Here, we investigated the contribution of presynaptic GABA(B) receptors and spontaneous activity to release probability both in vivo and in vitro in young-adult mice. Maximal activation of presynaptic GABA(B) receptors by baclofen reduced synaptic output by about 45% in whole-cell voltage clamp slice recordings, which was accompanied by a reduction in short-term depression. A similar reduction in transmission was observed when baclofen was applied in vivo by microiontophoresis during juxtacellular recordings using piggyback electrodes. No significant change in synaptic transmission was observed during application of the GABA(B) receptor antagonist CGP54626 both during in vivo and slice recordings, suggesting a low ambient GABA concentration. Interestingly, we observed that synapses with a high spontaneous frequency showed almost no synaptic depression during auditory stimulation, whereas synapses with a low spontaneous frequency did depress during noise bursts. Our data thus suggest that spontaneous firing can tonically reduce release probability in vivo. In addition, our data show that the ambient GABA concentration in the auditory brainstem is too low to activate the GABA(B) receptor at the calyx of Held significantly, but that activation of GABA(B) receptors can reduce sound-evoked synaptic depression.

Mechanisms contributing to the induction and storage of Pavlovian fear memories in the lateral amygdala

The relative contributions of plasticity in the amygdala vs. its afferent pathways to conditioned fear remain controversial. Some believe that thalamic and cortical neurons transmitting information about the conditioned stimulus (CS) to the lateral amygdala (LA) serve a relay function. Others maintain that thalamic and/or cortical plasticity is critically involved in fear conditioning. To address this question, we developed a large-scale biophysical model of the LA that could reproduce earlier findings regarding the cellular correlates of fear conditioning in LA. We then conducted model experiments that examined whether fear memories depend on (1) training-induced increases in the responsiveness of thalamic and cortical neurons projecting to LA, (2) plasticity at the synapses they form in LA, and/or (3) plasticity at synapses between LA neurons. These tests revealed that training-induced increases in the responsiveness of afferent neurons are required for fear memory formation. However, once the memory has been formed, this factor is no longer required because the efficacy of the synapses that thalamic and cortical neurons form with LA cells has augmented enough to maintain the memory. In contrast, our model experiments suggest that plasticity at synapses between LA neurons plays a minor role in maintaining the fear memory.

Adenosine A1 receptor activation mediates the developmental shift at layer 5 pyramidal cell synapses and is a determinant of mature synaptic strength

During the first postnatal month glutamatergic synapses between layer 5 pyramidal cells in the rodent neocortex switch from an immature state exhibiting a high probability of neurotransmitter release, large unitary amplitude and synaptic depression to a mature state with decreased probability of release, smaller unitary amplitude and synaptic facilitation. Using paired recordings, we demonstrate that the developmental shift in release probability at synapses between rat somatosensory layer 5 thick-tufted pyramidal cells is mediated by a higher and more heterogeneous activation of presynaptic adenosine A₁ receptors. Immature synapses under control conditions exhibited distributions of coefficient of variation, failure rate and release probability that were almost coincident with the A₁ receptor blocked condition; however, mature synapses under control conditions exhibited much broader distributions that spanned those of both the A₁ receptor agonized and antagonized conditions. Immature and mature synapses expressed A₁ receptors with no observable difference in functional efficacy and therefore the heterogeneous A₁ receptor activation seen in the mature neocortex appears due to increased adenosine concentrations that vary between synapses. Given the central role demonstrated for A₁ receptor activation in determining synaptic amplitude and the statistics of transmission between mature layer 5 pyramidal cells, the emplacement of adenosine sources and sinks near the synaptic terminal could constitute a novel form of long-term synaptic plasticity.

The impact of short term synaptic depression and stochastic vesicle dynamics on neuronal variability

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data.

Effects of Neonatal C-Fiber Depletion on Interaction between Neocortical Short-Term and Long-Term Plasticity

INTRODUCTION

The primary somatosensory cortex has an important role in nociceptive sensory-discriminative processing. Altered peripheral inputs produced by deafferentation or by long-term changes in levels of afferent stimulation can result in plasticity of cortex. Capsaicin-induced depletion of C-fiber afferents results in plasticity of the somatosensory system. Plasticity includes short-term and long-term changes in synaptic strength. We studied the interaction between paired-pulse facilitation, as one form of short-term plasticity, with long-term potentiation (LTP) in the neocortex of normal and C-fiber depleted freely moving rat.

METHODS

Neonatally capsaicin-treated rats and their controls were allowed to mature until they reached a weight between 250 and 300g. Then animals were anesthetized with ketamine and xylazine. For recording and stimulation, twisted teflon-coated stainless steel wires were implanted into somatosensory cortex or corpus callusom. In experiments for LTP induction, after two weeks of recovery period, 30 high frequency pulse trains were delivered once per day for 12 days. Paired-pulse ratio (PPR) was monitored before and after the induction of LTP in capsaicin-treated and control rats.

RESULTS

Paired-pulse stimulation affected all field potential components at intervals < 200 ms. The largest changes occurred at intervals between 20-30 ms. C-fiber depletion postponed the development of LTP, whereas it had no effect on PPR.

DISCUSSION

This finding provides further evidence that the expression of this form of LTP is postsynaptic. Furthermore, these results suggest that the effect of C-fiber depletion on cortical LTP is also postsynaptic and, therefore, is not caused by a decrease in neurotransmitter release.

A fast model of voltage-dependent NMDA receptors

NMDA receptors are among the crucial elements of central nervous system models. Recent studies show that both conductance and kinetics of these receptors are changing voltage-dependently in some parts of the brain. Therefore, several models have been introduced to simulate their current. However, on the one hand, kinetic models-which are able to simulate these voltage-dependent phenomena-are computationally expensive for modeling of large neural networks. On the other hand, classic exponential models, which are computationally less expensive, are not able to simulate the voltage-dependency of these receptors, accurately. In this study, we have modified these classic models to endow them with the voltage-dependent conductance and time constants. Temperature sensitivity and desensitization of these receptors are also taken into account. We show that, it is possible to simulate the most important physiological aspects of NMDA receptor's behavior using only three to four differential equations, which is significantly smaller than the previous kinetic models. Consequently, it seems that our model is both fast and physiologically plausible and therefore is a suitable candidate for the modeling of large neural networks.

Stimulus-specific adaptation, habituation and change detection in the gaze control system

This prospect article addresses the neurobiology of detecting and responding to changes or unexpected events. Change detection is an ongoing computational task performed by the brain as part of the broader process of saliency mapping and selection of the next target for attention. In the optic tectum (OT) of the barn owl, the probability of the stimulus has a dramatic influence on the neural response to that stimulus; rare or deviant stimuli induce stronger responses compared to common stimuli. This phenomenon, known as stimulus-specific adaptation, has recently attracted scientific interest because of its possible role in change detection. In the barn owl's OT, it may underlie the ability to orient specifically to unexpected events and is therefore opening new directions for research on the neurobiology of fundamental psychological phenomena such as habituation, attention, and surprise.

Modeling the generation of output by the cerebellar nuclei

Functional aspects of network integration in the cerebellar cortex have been studied experimentally and modeled in much detail ever since the early work by theoreticians such as Marr, Albus and Braitenberg more than 40 years ago. In contrast, much less is known about cerebellar processing at the output stage, namely in the cerebellar nuclei (CN). Here, input from Purkinje cells converges to control CN neuron spiking via GABAergic inhibition, before the output from the CN reaches cerebellar targets such as the brainstem and the motor thalamus. In this article we review modeling studies that address how the CN may integrate cerebellar cortical inputs, and what kind of signals may be transmitted. Specific hypotheses in the literature contrast rate coding and temporal coding of information in the spiking output from the CN. One popular hypothesis states that post-inhibitory rebound spiking may be an important mechanism by which Purkinje cell inhibition is turned into CN output spiking, but this hypothesis remains controversial. Rate coding clearly does take place, but in what way it may be augmented by temporal codes remains to be more clearly established. Several candidate mechanisms distinct from rebound spiking are discussed, such as the significance of spike time correlations between Purkinje cell pools to determine CN spike timing, irregularity of Purkinje cell spiking as a determinant of CN firing rate, and shared brief pauses between Purkinje cell pools that may trigger individual CN spikes precisely.

Short-term synaptic depression and stochastic vesicle dynamics reduce and shape neuronal correlations

Correlated neuronal activity is an important feature in many neural codes, a neural correlate of a variety of cognitive states, as well as a signature of several disease states in the nervous system. The cellular and circuit mechanics of neural correlations is a vibrant area of research. Synapses throughout the cortex exhibit a form of short-term depression where increased presynaptic firing rates deplete neurotransmitter vesicles, which transiently reduces synaptic efficacy. The release and recovery of these vesicles are inherently stochastic, and this stochasticity introduces variability into the conductance elicited by depressing synapses. The impact of spiking and subthreshold membrane dynamics on the transfer of neuronal correlations has been studied intensively, but an investigation of the impact of short-term synaptic depression and stochastic vesicle dynamics on correlation transfer is lacking. We find that short-term synaptic depression and stochastic vesicle dynamics can substantially reduce correlations, shape the timescale over which these correlations occur, and alter the dependence of spiking correlations on firing rate. Our results show that short-term depression and stochastic vesicle dynamics need to be taken into account when modeling correlations in neuronal populations.

STD-dependent and independent encoding of input irregularity as spike rate in a computational model of a cerebellar nucleus neuron

Neurons in the cerebellar nuclei (CN) receive inhibitory inputs from Purkinje cells in the cerebellar cortex and provide the major output from the cerebellum, but their computational function is not well understood. It has recently been shown that the spike activity of Purkinje cells is more regular than previously assumed and that this regularity can affect motor behaviour. We use a conductance-based model of a CN neuron to study the effect of the regularity of Purkinje cell spiking on CN neuron activity. We find that increasing the irregularity of Purkinje cell activity accelerates the CN neuron spike rate and that the mechanism of this recoding of input irregularity as output spike rate depends on the number of Purkinje cells converging onto a CN neuron. For high convergence ratios, the irregularity induced spike rate acceleration depends on short-term depression (STD) at the Purkinje cell synapses. At low convergence ratios, or for synchronised Purkinje cell input, the firing rate increase is independent of STD. The transformation of input irregularity into output spike rate occurs in response to artificial input spike trains as well as to spike trains recorded from Purkinje cells in tottering mice, which show highly irregular spiking patterns. Our results suggest that STD may contribute to the accelerated CN spike rate in tottering mice and they raise the possibility that the deficits in motor control in these mutants partly result as a pathological consequence of this natural form of plasticity.

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.

Activity-dependent energy budget for neocortical signaling: effect of short-term synaptic plasticity on the energy expended by spiking and synaptic activity

The available estimate of the energy expended for signaling in rat neocortex is refined to examine the separate contribution of spiking and synaptic activity as a function of average neuronal firing rate. By taking into account a phenomenological model of short-term synaptic plasticity, we show that the transition from low to high cortical activity is accompanied by a substantial increase in relative energy consumed by action potentials vs. synaptic potentials. This consideration might be important for a deeper understanding of how information is represented in the cortex and which metabolic pathways are upregulated to sustain cortical activity.

Short term synaptic depression imposes a frequency dependent filter on synaptic information transfer

Depletion of synaptic neurotransmitter vesicles induces a form of short term depression in synapses throughout the nervous system. This plasticity affects how synapses filter presynaptic spike trains. The filtering properties of short term depression are often studied using a deterministic synapse model that predicts the mean synaptic response to a presynaptic spike train, but ignores variability introduced by the probabilistic nature of vesicle release and stochasticity in synaptic recovery time. We show that this additional variability has important consequences for the synaptic filtering of presynaptic information. In particular, a synapse model with stochastic vesicle dynamics suppresses information encoded at lower frequencies more than information encoded at higher frequencies, while a model that ignores this stochasticity transfers information encoded at any frequency equally well. This distinction between the two models persists even when large numbers of synaptic contacts are considered. Our study provides strong evidence that the stochastic nature neurotransmitter vesicle dynamics must be considered when analyzing the information flow across a synapse.

The temporal course of recovery from brief (sub-second) adaptations to spatial contrast

Visual adaptation is a critical and ubiquitous mechanism that occurs for any stimulus feature and involves a continuous adjustment of the neuronal contrast gain. These adjustments prevent our visual system from dropping in sensitivity for the prevailing ranges of stimulus features that are processed at a given time. In addition to the classical adaptation, which arises over several seconds to minutes, a number of psychophysical, electrophysiological and interference studies have documented a much faster form of adaptation occurring with motion stimuli. This faster adaptation operates on a sub-second scale. In the present study, we investigated whether a fast form of adaptation also exists for spatial contrast and whether its characteristics (e.g., dependence on the duration of adaptation, time course of recovery) are similar to the classical, slower contrast adaptation. We found that a fast form of adaptation does exist and is maximal at intervals of 16-50 ms after the offset of the adapting stimulus. Similar to what previous studies have found regarding the classical contrast adaptation, the initial threshold elevation of this study did not depend on the duration of the adapting stimulus, but only on its contrast. Our results showed that the function which best describes the decay of brief adaptations to high-contrast stimuli was a double exponential decay function, whereas the best function for describing adaptation to low-contrast stimuli was a single exponential decay function with a very fast recovery rate. Thus, adapting contrast influences both the threshold elevation, which rises with increasing adapting contrast, and the time course of recovery from adaptation. Overall, our data suggest the presence of a mechanism that is similar to the classical contrast adaptation involved in longer adaptations, but it operates over much shorter timescales.

The influences of dark rearing on the transmission characteristics of layer II/III pyramidal cells during the critical period

The characteristics of synaptic plasticity on layer II/III pyramidal cells in different ages of rats have been studied extensively, and dark rearing is one of the important impact factors. To systematically analyze the influence of dark rearing on synaptic plasticity during the critical period of visual development, we studied the characteristics of short-term and long-term synaptic plasticities of layer II/III pyramidal cells of rats in three rearing conditions during P14 to P37. The paired-pulse ratio (PPR) of inhibitory postsynaptic currents (IPSCs) of layer II/III pyramidal cells was effected by both ages and rearing conditions, but the PPR of excitatory postsynaptic currents (EPSCs) did not change obviously. Moreover, long-term synaptic plasticity of rats in the dark rearing condition did not significantly change with age, while it was elevated during P16 and P21 for rats in the normal rearing condition. These results suggest that visual experience can affect the characteristics of short-term and long-term synaptic plasticities. The IPSC/EPSC ratio increased gradually with aging for NR rats, but the ratio slightly decreased for DR rats, which indicates the relative increase of inhibitory components during the critical period of visual development. The characteristics during P35 and P37 of the 30-day dark-reared (30D×N) group had similar trends with the normal-reared rats during P16 and P21, which emphasizes that dark rearing can postpone the timing of the critical period.

Theory of correlation in a network with synaptic depression

Synaptic depression affects not only the mean responses of neurons but also the correlation of response variability in neural populations. Although previous studies have constructed a theory of correlation in a spiking neuron model by using the mean-field theory framework, synaptic depression has not been taken into consideration. We expanded the previous theoretical framework in this study to spiking neuron models with short-term synaptic depression. On the basis of this theory we analytically calculated neural correlations in a ring attractor network with Mexican-hat-type connectivity, which was used as a model of the primary visual cortex. The results revealed that synaptic depression reduces neural correlation, which could be beneficial for sensory coding. Furthermore, our study opens the way for theoretical studies on the effect of interaction change on the linear response function in large stochastic networks.

A computational model of cellular mechanisms of temporal coding in the medial geniculate body (MGB)

Acoustic stimuli are often represented in the early auditory pathway as patterns of neural activity synchronized to time-varying features. This phase-locking predominates until the level of the medial geniculate body (MGB), where previous studies have identified two main, largely segregated response types: Stimulus-synchronized responses faithfully preserve the temporal coding from its afferent inputs, and Non-synchronized responses, which are not phase locked to the inputs, represent changes in temporal modulation by a rate code. The cellular mechanisms underlying this transformation from phase-locked to rate code are not well understood. We use a computational model of a MGB thalamocortical neuron to test the hypothesis that these response classes arise from inferior colliculus (IC) excitatory afferents with divergent properties similar to those observed in brain slice studies. Large-conductance inputs exhibiting synaptic depression preserved input synchrony as short as 12.5 ms interclick intervals, while maintaining low firing rates and low-pass filtering responses. By contrast, small-conductance inputs with Mixed plasticity (depression of AMPA-receptor component and facilitation of NMDA-receptor component) desynchronized afferent inputs, generated a click-rate dependent increase in firing rate, and high-pass filtered the inputs. Synaptic inputs with facilitation often permitted band-pass synchrony along with band-pass rate tuning. These responses could be tuned by changes in membrane potential, strength of the NMDA component, and characteristics of synaptic plasticity. These results demonstrate how the same synchronized input spike trains from the inferior colliculus can be transformed into different representations of temporal modulation by divergent synaptic properties.

Tell me something interesting: context dependent adaptation in somatosensory cortex

It is widely accepted that through a process of adaptation cells adjust their sensitivity in accordance with prevailing stimulus conditions. However, in two recent studies exploring adaptation in the rodent inferior colliculus and somatosensory cortex, neurons did not adapt towards global mean, but rather became most sensitive to inputs that were located towards the edge of the stimulus distribution with greater intensity than the mean. We re-examined electrophysiological data from the somatosensory study with the purpose of exploring the underlying encoding strategies. We found that neural gain tended to decrease as stimulus variance increased. Following adaptation to changes in global mean, neuronal output was scaled such that the relationship between firing rate and local, rather than global, differences in stimulus intensity was maintained. The majority of cells responded to large, positive deviations in stimulus amplitude; with a small number responding to both positive and negative changes in stimulus intensity. Adaptation to global mean was replicated in a model neuron by incorporating both spike-rate adaptation and tonic-inhibition, which increased in proportion to stimulus mean. Adaptation to stimulus variance was replicated by approximating the output of a population of neurons adapted to global mean and using it to drive a layer of recurrently connected depressing synapses. Within the barrel cortex, adaptation ensures that neurons are able to encode both overall levels of variance and large deviations in the input. This is achieved through a combination of gain modulation and a shift in sensitivity to intensity levels that are greater than the mean.

Relating the sequential dynamics of excitatory neural networks to synaptic cellular automata

We have developed a new approach for the description of sequential dynamics of excitatory neural networks. Our approach is based on the dynamics of synapses possessing the short-term plasticity property. We suggest a model of such synapses in the form of a second-order system of nonlinear ODEs. In the framework of the model two types of responses are realized-the fast and the slow ones. Under some relations between their timescales a cellular automaton (CA) on the graph of connections is constructed. Such a CA has only a finite number of attractors and all of them are periodic orbits. The attractors of the CA determine the regimes of sequential dynamics of the original neural network, i.e., itineraries along the network and the times of successive firing of neurons in the form of bunches of spikes. We illustrate our approach on the example of a Morris-Lecar neural network.

Dynamical changes in neurons during seizures determine tonic to clonic shift

A tonic-clonic seizure transitions from high frequency asynchronous activity to low frequency coherent oscillations, yet the mechanism of transition remains unknown. We propose a shift in network synchrony due to changes in cellular response. Here we use phase-response curves (PRC) from Morris-Lecar (M-L) model neurons with synaptic depression and gradually decrease input current to cells within a network simulation. This method effectively decreases firing rates resulting in a shift to greater network synchrony illustrating a possible mechanism of the transition phenomenon. PRCs are measured from the M-L conductance based model cell with a range of input currents within the limit cycle. A large network of 3000 excitatory neurons is simulated with a network topology generated from second-order statistics which allows a range of population synchrony. The population synchrony of the oscillating cells is measured with the Kuramoto order parameter, which reveals a transition from tonic to clonic phase exhibited by our model network. The cellular response shift mechanism for the tonic-clonic seizure transition reproduces the population behavior closely when compared to EEG data.

Exponential transient propagating oscillations in a ring of spiking neurons with unidirectional slow inhibitory synaptic coupling

Transient oscillations in a ring of spiking neuron models unidirectionally coupled with slow inhibitory synapses are studied. There are stable spatially fixed steady firing-resting states and unstable symmetric propagating firing-resting states. In transients, firing-resting patterns rotate in the direction of coupling (propagating oscillations), the duration of which increases exponentially with the number of neurons (exponential transients). Further, the duration of randomly generated transient propagating oscillations is distributed in a power law form and spatiotemporal noise of intermediate strength sustains propagating oscillations. These properties agree with those of transient propagating waves in a ring of sigmoidal neuron models.

The effect of neural adaptation on population coding accuracy

Most neurons in the primary visual cortex initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. The functional consequences of adaptation are unclear. Typically a reduction of firing rate would reduce single neuron accuracy as less spikes are available for decoding, but it has been suggested that on the population level, adaptation increases coding accuracy. This question requires careful analysis as adaptation not only changes the firing rates of neurons, but also the neural variability and correlations between neurons, which affect coding accuracy as well. We calculate the coding accuracy using a computational model that implements two forms of adaptation: spike frequency adaptation and synaptic adaptation in the form of short-term synaptic plasticity. We find that the net effect of adaptation is subtle and heterogeneous. Depending on adaptation mechanism and test stimulus, adaptation can either increase or decrease coding accuracy. We discuss the neurophysiological and psychophysical implications of the findings and relate it to published experimental data.

A neuronally based model of contrast gain adaptation in fly motion vision

Motion-sensitive neurons in the visual systems of many species, including humans, exhibit a depression of motion responses immediately after being exposed to rapidly moving images. This motion adaptation has been extensively studied in flies, but a neuronal mechanism that explains the most prominent component of adaptation, which occurs regardless of the direction of motion of the visual stimulus, has yet to be proposed. We identify a neuronal mechanism, namely frequency-dependent synaptic depression, which explains a number of the features of adaptation in mammalian motion-sensitive neurons and use it to model fly motion adaptation. While synaptic depression has been studied mainly in spiking cells, we use the same principles to develop a simple model for depression in a graded synapse. By incorporating this synaptic model into a neuronally based model for elementary motion detection, along with the implementation of a center-surround spatial band-pass filtering stage that mimics the interactions among a subset of visual neurons, we show that we can predict with remarkable success most of the qualitative features of adaptation observed in electrophysiological experiments. Our results support the idea that diverse species share common computational principles for processing visual motion and suggest that such principles could be neuronally implemented in very similar ways.

Neural field model of binocular rivalry waves

We present a neural field model of binocular rivalry waves in visual cortex. For each eye we consider a one-dimensional network of neurons that respond maximally to a particular feature of the corresponding image such as the orientation of a grating stimulus. Recurrent connections within each one-dimensional network are assumed to be excitatory, whereas connections between the two networks are inhibitory (cross-inhibition). Slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We derive an analytical expression for the speed of a binocular rivalry wave as a function of various neurophysiological parameters, and show how properties of the wave are consistent with the wave-like propagation of perceptual dominance observed in recent psychophysical experiments. In addition to providing an analytical framework for studying binocular rivalry waves, we show how neural field methods provide insights into the mechanisms underlying the generation of the waves. In particular, we highlight the important role of slow adaptation in providing a "symmetry breaking mechanism" that allows waves to propagate.

Short-term plasticity impacts information transfer at glutamate synapses onto parvocellular neuroendocrine cells in the paraventricular nucleus of the hypothalamus

Glutamatergic synaptic inputs onto parvocellular neurosecretory cells (PNCs) in the paraventricular nucleus of the hypothalamus (PVN) regulate the hypothalamic-pituitary-adrenal (HPA) axis responses to stress and undergo stress-dependent changes in their capacity to transmit information. In spite of their pivotal role in regulating PNCs, relatively little is known about the fundamental rules that govern transmission at these synapses. Furthermore, since salient information in the nervous system is often transmitted in bursts, it is also important to understand the short-term dynamics of glutamate transmission under basal conditions. To characterize these properties, we obtained whole-cell patch clamp recordings from PNCs in brain slices from postnatal day 21-35 male Sprague-Dawley rats and examined EPSCs. EPSCs were elicited by electrically stimulating glutamatergic afferents along the periventricular aspect. In response to a paired-pulse stimulation protocol, EPSCs generally displayed a robust short-term depression that recovered within 5 s. Similarly, trains of synaptic stimuli (5-50 Hz) resulted in a frequency-dependent depression until a near steady state was achieved. Application of inhibitors of AMPA receptor (AMPAR) desensitization or the low-affinity, competitive AMPAR antagonist failed to affect the depression due to paired-pulse and trains of synaptic stimulation indicating that this use-dependent short-term synaptic depression has a presynaptic locus of expression. We used cumulative amplitude profiles during trains of stimulation and variance-mean analysis to estimate synaptic parameters. Finally, we report that these properties contribute to hamper the efficiency with which high frequency synaptic inputs generate spikes in PNCs, indicating that these synapses operate as effective low-pass filters in basal conditions.

A transgenic mouse model for Alzheimer's disease has impaired synaptic gain but normal synaptic dynamics

The chronic accumulation of amyloid beta (Aβ) peptides is thought to underlie much of the pathology of Alzheimer's disease (AD), and transgenic mice overexpressing Aβ show both behavioral defects and impairments in hippocampal synaptic transmission. In the present study, we examined excitatory transmission at the Schaffer collateral synapse in acute hippocampal slices from APP(Swe)/PS-1(A246E) transgenic mice to determine whether the synaptic impairment in these mice is due to a reduction in the activity-independent synaptic gain, or to a change in the activity-dependent synaptic dynamics. We observed a strong reduction in synaptic transmission in slices from APP(Swe)/PS-1(A246E) mice compared to those from their wildtype littermates. However, there was no resolvable change in the synaptic dynamics observed in response to either simple or complex stimulus trains. We conclude that the chronic accumulation of Aβ impairs synaptic transmission through a reduction in the synaptic gain, while preserving the synaptic dynamics.

Influence of a subtype of inhibitory interneuron on stimulus-specific responses in visual cortex

Inhibition modulates receptive field properties and integrative responses of neurons in cortical circuits. The contribution of specific interneuron classes to cortical circuits and emergent responses is unknown. Here, we examined neuronal responses in primary visual cortex (V1) of adult Dlx1(-/-) mice, which have a selective reduction in cortical dendrite-targeting interneurons (DTIs) that express calretinin, neuropeptide Y, and somatostatin. The V1 neurons examined in Dlx1(-/-) mice have reduced orientation selectivity and altered firing rates, with elevated late responses, suggesting that local inhibition at dendrites has a specific role in modulating neuronal computations. We did not detect overt changes in the physiological properties of thalamic relay neurons and features of thalamocortical projections, such as retinotopic maps and eye-specific inputs, in the mutant mice, suggesting that the defects are cortical in origin. These experimental results are well explained by a computational model that integrates broad tuning from dendrite-targeting and narrower tuning from soma-targeting interneuron subclasses. Our findings suggest a key role for DTIs in the fine-tuning of stimulus-specific cortical responses.

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.

Depressing synapse as a detector of frequency change

In this article we discuss the short-term synaptic depression using a mathematical model. We derive the model of synaptic depression caused by the depletion of synaptic vesicles for the case of infinitely short stimulation time and show that the analytical formulas for the postsynaptic potential (PSP) and kinetic functions take simple closed form. A solution in this form allows an analysis of the characteristics of depression as a function of the models parameters and the derivation of analytic formulas for measures of short time synaptic depression commonly used in experimental studies. Those formulas are used to validate the model by fitting it to two types of synapses described in the literature. Given the fitted parameters we discuss the behavior of the synapse in situations involving frequency change. We also indicate a possible role of depressing synapses in information processing as not only a filter of high frequency input but as a detector of the return from high frequency stimulation to the stimulation within frequency band specific for a given synapse.

Dynamic modulation of short-term synaptic plasticity in the auditory cortex: the role of norepinephrine

Norepinephrine (NE) is an important modulator of neuronal activity in the auditory cortex. Using patch-clamp recording and a pair pulse protocol on an auditory cortex slice preparation we recently demonstrated that NE affects cortical inhibition in a layer-specific manner, by decreasing apical but increasing basal inhibition onto layer II/III pyramidal cell dendrites. In the present study we used a similar protocol to investigate the dependence of noradrenergic modulation of inhibition on stimulus frequency, using 1s-long train pulses at 5, 10, and 20 Hz. The study was conducted using pharmacologically isolated inhibitory postsynaptic currents (IPSCs) evoked by electrical stimulation of axons either in layer I (LI-eIPSCs) or in layer II/III (LII/III-eIPSCs). We found that: 1) LI-eIPSC display less synaptic depression than LII/III-eIPSCs at all the frequencies tested, 2) in both type of synapses depression had a presynaptic component which could be altered manipulating [Ca²+]₀, 3) NE modestly altered short-term synaptic plasticity at low or intermediate (5-10 Hz) frequencies, but selectively enhanced synaptic facilitation in LI-eIPSCs while increasing synaptic depression of LII/III-eIPSCs in the latest (>250 ms) part of the response, at high stimulation frequency (20 Hz). We speculate that these mechanisms may limit the temporal window for top-down synaptic integration as well as the duration and intensity of stimulus-evoked gamma-oscillations triggered by complex auditory stimuli during alertness.

Estimating network parameters from combined dynamics of firing rate and irregularity of single neurons

High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV(2)) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV(2) is widely distributed from quasi-regular to irregular (CV(2) = 0.3-1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV(2) neurons to move to the excitation-dominated region as well as to an increase of EPSP size.

Determinants of multiple semantic priming: a meta-analysis and spike frequency adaptive model of a cortical network

Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current models requires a quantifiable and reliable account of the simplest case of multiple priming resulting from two primes on a target. The meta-analytic approach offers a better understanding of the experimental data from studies on multiple priming regarding the additivity pattern of priming. The meta-analysis points to the effects of prime-target stimuli onset asynchronies on the pattern of underadditivity, overadditivity, or strict additivity of converging activation from multiple primes. The modeling approach is then constrained by results of the meta-analysis. We propose a model of a cortical network embedding spike frequency adaptation, which allows frequency and time-dependent modulation of neural activity. Model results give a comprehensive understanding of the meta-analysis results in terms of dynamics of neuron populations. They also give predictions regarding how stimuli intensities, association strength, and spike frequency adaptation influence multiple priming effects.

Synaptic filtering of rate-coded information

In this paper, we analytically examine the influence of synaptic short-term plasticity (STP) on the transfer of rate-coded information through synapses. STP endows each presynaptic input spike with an amplitude that depends on previous input spikes. We develop a method to calculate the spectral statistics of this amplitude modulated spike train (postsynaptic input) for the case of an inhomogeneous Poisson process. We derive in particular analytical approximations for cross-spectra, power spectra, and for the coherence function between the postsynaptic input and the time-dependent rate modulation for a specific model. We give simple expressions for the coherence in the limiting cases of pure facilitation and pure depression. Using our analytical results and extensive numerical simulations, we study the spectral coherence function for postsynaptic input resulting from a single synapse or from a group of synapses. For a single synapse, we find that the synaptic coherence function is largely independent of frequency indicating broadband information transmission. This effect is even more pronounced for a large number of synapses. However, additional noise gives rise to frequency-dependent information filtering.

Adaptive integration in the visual cortex by depressing recurrent cortical circuits

Neurons in the visual cortex receive a large amount of input from recurrent connections, yet the functional role of these connections remains unclear. Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter. This allows the visual system to respond reliably to deteriorated stimuli yet quickly to high-quality stimuli. For low-contrast stimuli, the model predicts long response latencies, whereas latencies are short for high-contrast stimuli. This is consistent with physiological data showing that in higher visual areas, latencies can increase more than 100 ms at low contrast compared to high contrast. Moreover, when presented with briefly flashed stimuli, the model predicts stereotypical responses that outlast the stimulus, again consistent with physiological findings. The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal signals such that processing is as fast as possible while maintaining reliability.

Sensory neural codes using multiplexed temporal scales

Determining how neuronal activity represents sensory information is central for understanding perception. Recent work shows that neural responses at different timescales can encode different stimulus attributes, resulting in a temporal multiplexing of sensory information. Multiplexing increases the encoding capacity of neural responses, enables disambiguation of stimuli that cannot be discriminated at a single response timescale, and makes sensory representations stable to the presence of variability in the sensory world. Thus, as we discuss here, temporal multiplexing could be a key strategy used by the brain to form an information-rich and stable representation of the environment.

Uncovering bifurcation patterns in cortical synapses

Individual cortical synapses are known to exhibit a very complex short-time dynamic behaviour in response to simple "naturalistic" stimulation. We describe a computational study of the experimentally obtained excitatory post-synaptic potential trains of individual cortical synapses. By adopting a new nonlinear modelling scheme we construct robust and repeatable models of the underlying dynamics. These models suggest that cortical synapses exhibit a wide range of either periodic or chaotic dynamics. For stimulus at a fixed rate our models predict that the response of the individual synapse will vary from a fixed point to periodic and chaotic, depending on the frequency of stimulus. Dynamics for individual synapses vary widely, suggesting that the individual behaviour of synapses is highly tuned and that the dynamic behaviour of even a small network of synapse-coupled neurons could be extremely varied.

Differences in the time course of short-term depression across receptive fields are correlated with directional selectivity in electrosensory neurons

Directional selectivity, in which neurons respond preferentially to one direction of movement ("preferred") over the opposite direction ("null"), is a critical computation that is found in the nervous systems of many animals. Here we show the first experimental evidence for a correlation between differences in short-term depression and direction-selective responses to moving objects. As predicted by quantitative models, the observed differences in the time courses of short-term depression at different locations within receptive fields were correlated with measures of direction selectivity in awake, behaving weakly electric fish (Apteronotus leptorhynchus). Because short-term depression is ubiquitous in the central nervous systems of vertebrate animals, it may be a common mechanism used for the generation of directional selectivity and other spatiotemporal computations.

Direct activation of sparse, distributed populations of cortical neurons by electrical microstimulation

For over a century, electrical microstimulation has been the most direct method for causally linking brain function with behavior. Despite this long history, it is still unclear how the activity of neural populations is affected by stimulation. For example, there is still no consensus on where activated cells lie or on the extent to which neural processes such as passing axons near the electrode are also activated. Past studies of this question have proven difficult because microstimulation interferes with electrophysiological recordings, which in any case provide only coarse information about the location of activated cells. We used two-photon calcium imaging, an optical method, to circumvent these hurdles. We found that microstimulation sparsely activates neurons around the electrode, sometimes as far as millimeters away, even at low currents. Our results indicate that the pattern of activated neurons likely arises from the direct activation of axons in a volume tens of microns in diameter.

Short-term synaptic plasticity in the nociceptive thalamic-anterior cingulate pathway

Background

Although the mechanisms of short- and long-term potentiation of nociceptive-evoked responses are well known in the spinal cord, including central sensitization, there has been a growing body of information on such events in the cerebral cortex. In view of the importance of anterior cingulate cortex (ACC) in chronic pain conditions, this review considers neuronal plasticities in the thalamocingulate pathway that may be the earliest changes associated with such syndromes.

Results

A single nociceptive electrical stimulus to the sciatic nerve induced a prominent sink current in the layer II/III of the ACC in vivo, while high frequency stimulation potentiated the response of this current. Paired-pulse facilitation by electrical stimulation of midline, mediodorsal and intralaminar thalamic nuclei (MITN) suggesting that the MITN projection to ACC mediates the nociceptive short-term plasticity. The short-term synaptic plasticities were evaluated for different inputs in vitro where the medial thalamic and contralateral corpus callosum afferents were compared. Stimulation of the mediodorsal afferent evoked a stronger short-term synaptic plasticity and effectively transferred the bursting thalamic activity to cingulate cortex that was not true for contralateral stimulation. This short-term enhancement of synaptic transmission was mediated by polysynaptic pathways and NMDA receptors. Layer II/III neurons of the ACC express a short-term plasticity that involves glutamate and presynaptic calcium influx and is an important mechanism of the short-term plasticity.

Conclusion

The potentiation of ACC neuronal activity induced by thalamic bursting suggest that short-term synaptic plasticities enable the processing of nociceptive information from the medial thalamus and this temporal response variability is particularly important in pain because temporal maintenance of the response supports cortical integration and memory formation related to noxious events. Moreover, these modifications of cingulate synapses appear to regulate afferent signals that may be important to the transition from acute to chronic pain conditions associated with persistent peripheral noxious stimulation. Enhanced and maintained nociceptive activities in cingulate cortex, therefore, can become adverse and it will be important to learn how to regulate such changes in thalamic firing patterns that transmit nociceptive information to ACC in early stages of chronic pain.

BDNF and NT-3 increase excitatory input connectivity in rat hippocampal cultures

The neurotrophic factors brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3) have been shown to promote excitatory and inhibitory synapse development. However, a quantitative analysis of their influence on connectivity has proven in general difficult to achieve. In this work we use a novel experimental approach based on percolation concepts that provides a quantification of the average number of connections per neuron. In combination with electrophysiological measurements, we characterize the changes in network connectivity induced by BDNF and NT-3 in rat hippocampal cultures. We show that, on the one hand, BDNF and NT-3 accelerate the maturation of connectivity in the network by about 17 h. On the other hand, BDNF and NT-3 increase the number of excitatory input connections by a factor of about two, but without modifying the number of inhibitory input connections. This scenario of a dominant effect on the excitation is supported by the analysis of spontaneous population bursts in cultures treated with either BDNF or NT-3, which show burst amplitudes that are insensitive to the blockade of inhibition. A leaky integrate-and-fire model reproduces the experimental results well.

Low level postnatal methylmercury exposure in vivo alters developmental forms of short-term synaptic plasticity in the visual cortex of rat

Methylmercury (MeHg) has been previously shown to affect neurotransmitter release. Short-term synaptic plasticity (STP) is primarily related to changes in the probability of neurotransmitter release. To determine if MeHg affects STP development, we examined STP forms in the visual cortex of rat following in vivo MeHg exposure. Neonatal rats received 0 (0.9% NaCl), 0.75 or 1.5 mg/kg/day MeHg subcutaneously for 15 or 30 days beginning on postnatal day 5, after which visual cortical slices were prepared for field potential recordings. In slices prepared from rats treated with vehicle, field excitatory postsynaptic potentials (fEPSPs) evoked by paired-pulse stimulation at 20-200 ms inter-stimulus intervals showed a depression (PPD) of the second fEPSP (fEPSP2). PPD was also seen in slices prepared from rats after 15 day treatment with 0.75 or 1.5 mg/kg/day MeHg. However, longer duration treatment (30 days) with either dose of MeHg resulted in paired-pulse facilitation (PPF) of fEPSP2 in the majority of slices examined. PPF remained observable in slices prepared from animals in which MeHg exposure had been terminated for 30 days after completion of the initial 30 day MeHg treatment, whereas slices from control animals still showed PPD. MeHg did not cause any frequency- or region-preferential effect on STP. Manipulations of [Ca2+](e) or application of the GABA(A) receptor antagonist bicuculline could alter the strength and polarity of MeHg-induced changes in STP. Thus, these data suggest that low level postnatal MeHg exposure interferes with the developmental transformation of STP in the visual cortex, which is a long-lasting effect.