Plasticity of Response Properties of Mouse Visual Cortex Neurons Induced by Optogenetic Tetanization In Vivo.

Heterosynaptic plasticity, along with Hebbian homosynaptic plasticity, is an important mechanism ensuring the stable operation of learning neuronal networks. However, whether heterosynaptic plasticity occurs in the whole brain in vivo, and what role(s) in brain function in vivo it could play, remains unclear. Here, we used an optogenetics approach to apply a model of intracellular tetanization, which was established and employed to study heterosynaptic plasticity in brain slices, to study the plasticity of response properties of neurons in the mouse visual cortex in vivo. We show that optogenetically evoked high-frequency bursts of action potentials (optogenetic tetanization) in the principal neurons of the visual cortex induce long-term changes in the responses to visual stimuli. Optogenetic tetanization had distinct effects on responses to different stimuli, as follows: responses to optimal and orthogonal orientations decreased, responses to null direction did not change, and responses to oblique orientations increased. As a result, direction selectivity of the neurons decreased and orientation tuning became broader. Since optogenetic tetanization was a postsynaptic protocol, applied in the absence of sensory stimulation, and, thus, without association of presynaptic activity with bursts of action potentials, the observed changes were mediated by mechanisms of heterosynaptic plasticity. We conclude that heterosynaptic plasticity can be induced in vivo and propose that it may play important homeostatic roles in operation of neural networks by helping to prevent runaway dynamics of responses to visual stimuli and to keep the tuning of neuronal responses within the range optimized for the encoding of multiple features in population activity.

Altered Heterosynaptic Plasticity Impairs Visual Discrimination Learning in Adenosine A1 Receptor Knock-Out Mice.

Theoretical and modeling studies demonstrate that heterosynaptic plasticity-changes at synapses inactive during induction-facilitates fine-grained discriminative learning in Hebbian-type systems, and helps to achieve a robust ability for repetitive learning. A dearth of tools for selective manipulation has hindered experimental analysis of the proposed role of heterosynaptic plasticity in behavior. Here we circumvent this obstacle by testing specific predictions about the behavioral consequences of the impairment of heterosynaptic plasticity by experimental manipulations to adenosine A1 receptors (A1Rs). Our prior work demonstrated that the blockade of adenosine A1 receptors impairs heterosynaptic plasticity in brain slices and, when implemented in computer models, selectively impairs repetitive learning on sequential tasks. Based on this work, we predict that A1R knock-out (KO) mice will express (1) impairment of heterosynaptic plasticity and (2) behavioral deficits in learning on sequential tasks. Using electrophysiological experiments in slices and behavioral testing of animals of both sexes, we show that, compared with wild-type controls, A1R KO mice have impaired synaptic plasticity in visual cortex neurons, coupled with significant deficits in visual discrimination learning. Deficits in A1R knockouts were seen specifically during relearning, becoming progressively more apparent with learning on sequential visual discrimination tasks of increasing complexity. These behavioral results confirm our model predictions and provide the first experimental evidence for a proposed role of heterosynaptic plasticity in organism-level learning. Moreover, these results identify heterosynaptic plasticity as a new potential target for interventions that may help to enhance new learning on a background of existing memories.SIGNIFICANCE STATEMENT Understanding how interacting forms of synaptic plasticity mediate learning is fundamental for neuroscience. Theory and modeling revealed that, in addition to Hebbian-type associative plasticity, heterosynaptic changes at synapses that were not active during induction are necessary for stable system operation and fine-grained discrimination learning. However, lacking tools for selective manipulation prevented behavioral analysis of heterosynaptic plasticity. Here we circumvent this barrier: from our prior experimental and computational work we predict differential behavioral consequences of the impairment of Hebbian-type versus heterosynaptic plasticity. We show that, in adenosine A1 receptor knock-out mice, impaired synaptic plasticity in visual cortex neurons is coupled with specific deficits in learning sequential, increasingly complex visual discrimination tasks. This provides the first evidence linking heterosynaptic plasticity to organism-level learning.

Mechanism of Pacemaker Activity in Zebrafish DC2/4 Dopaminergic Neurons.

Zebrafish models are used increasingly to study the molecular pathogenesis of Parkinson's disease (PD), owing to the extensive array of techniques available for their experimental manipulation and analysis. The ascending dopaminergic projection from the posterior tuberculum (TPp; diencephalic populations DC2 and DC4) to the subpallium is considered the zebrafish correlate of the mammalian nigrostriatal projection, but little is known about the neurophysiology of zebrafish DC2/4 neurons. This is an important knowledge gap, because autonomous activity in mammalian substantia nigra (SNc) dopaminergic neurons contributes to their vulnerability in PD models. Using a new transgenic zebrafish line to label living dopaminergic neurons, and a novel brain slice preparation, we conducted whole-cell patch clamp recordings of DC2/4 neurons from adult zebrafish of both sexes. Zebrafish DC2/4 neurons share many physiological properties with mammalian dopaminergic neurons, including the cell-autonomous generation of action potentials. However, in contrast to mammalian dopaminergic neurons, the pacemaker driving intrinsic rhythmic activity in zebrafish DC2/4 neurons does not involve calcium conductances, hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, or sodium leak currents. Instead, voltage clamp recordings and computational models show that interactions between three components - a small, predominantly potassium, leak conductance, voltage-gated sodium channels, and voltage-gated potassium channels - are sufficient for pacemaker activity in zebrafish DC2/4 neurons. These results contribute to understanding the comparative physiology of the dopaminergic system and provide a conceptual basis for interpreting data derived from zebrafish PD models. The findings further suggest new experimental opportunities to address the role of dopaminergic pacemaker activity in the pathogenesis of PD.SIGNIFICANCE STATEMENT Posterior tuberculum (TPp) DC2/4 dopaminergic neurons are considered the zebrafish correlate of mammalian substantia nigra (SNc) neurons, whose degeneration causes the motor signs of Parkinson's disease (PD). Our study shows that DC2/4 and SNc neurons share a number of electrophysiological properties, including depolarized membrane potential, high input resistance, and continual, cell-autonomous pacemaker activity, that strengthen the basis for the increasing use of zebrafish models to study the molecular pathogenesis of PD. The mechanisms driving pacemaker activity differ between DC2/4 and SNc neurons, providing: (1) experimental opportunities to dissociate the contributions of intrinsic activity and underlying pacemaker currents to pathogenesis; and (2) essential information for the design and interpretation of studies using zebrafish PD models.

When cats need to see to step accurately?

Locomotion on complex terrains often requires vision. However, how vision serves locomotion is not well understood. Here, we asked when visual information necessary for accurate stepping is collected and how its acquisition relates to the step cycle. In cats of both sexes, we showed that a brief (200-400 ms) interruption of visual input can rapidly influence cat's walking along a horizontal ladder. Depending on the phase within the step cycle, a 200 ms period of darkness could be tolerated fully without any changes to the strides or could lead to minor increases of stride duration. The effects of 300-400 ms of visual input denial, which typically prolonged stances and/or swings, also depended on the phase of the darkness onset. The increase of the duration of strides was always shorter than the duration of darkness. We conclude that visual information for planning a swing is collected starting from the middle of the preceding stance until the beginning of the current swing. For a stance (and/or a swing of the other paw), visual information is collected starting from the end of the previous stance and until the middle of the current stance. Acquisition of visual information during these windows is not uniform but depends on the phase of the step cycle. Notably, both the extension of these windows and their non-homogeneity are closely related to the pattern of gaze behaviour in cats, described previously. This new knowledge will help to guide research and understanding of neuronal mechanisms of visuomotor integration and modulation of visual function by strides during locomotion. KEY POINTS: Cats, like humans, rely on vision to navigate in complex environments. In cats walking along a horizontally placed ladder, we show that visual information required for accurate stepping is collected in a non-uniform manner throughout the stride cycle. Brief denial of visual input during a swing prolongs the next stance of that forelimb. Denial of visual input during a stance prolongs this stance, as well as the next swing and stance. Denial during the first half of a stance has a greater effect than during the second half. The phase dependence of the use of vision for accurate stepping and the pattern of affected swings and stances are closely related to the previously described pattern of gaze behaviour in cats. This new knowledge opens new perspectives for research into neuronal mechanisms of visuomotor coordination and visual function during walking and for understanding related disorders.

Distinct Heterosynaptic Plasticity in Fast Spiking and Non-Fast-Spiking Inhibitory Neurons in Rat Visual Cortex.

Inhibition in neuronal networks of the neocortex serves a multitude of functions, such as balancing excitation and structuring neuronal activity in space and time. Plasticity of inhibition is mediated by changes at both inhibitory synapses, as well as excitatory synapses on inhibitory neurons. Using slices from visual cortex of young male rats, we describe a novel form of plasticity of excitatory synapses on inhibitory neurons, weight-dependent heterosynaptic plasticity. Recordings from connected pyramid-to-interneuron pairs confirm that postsynaptic activity alone can induce long-term changes at synapses that were not presynaptically active during the induction, i.e., heterosynaptic plasticity. Moreover, heterosynaptic changes can accompany homosynaptic plasticity induced in inhibitory neurons by conventional spike-timing-dependent plasticity protocols. In both fast-spiking (FS) and non-FS neurons, heterosynaptic changes were weight-dependent, because they correlated with initial paired-pulse ratio (PPR), indicative of initial strength of a synapse. Synapses with initially high PPR, indicative of low release probability ("weak" synapses), had the tendency to be potentiated, while synapses with low initial PPR ("strong" synapses) tended to depress or did not change. Interestingly, the net outcome of heterosynaptic changes was different in FS and non-FS neurons. FS neurons expressed balanced changes, with gross average (n = 142) not different from control. Non-FS neurons (n = 66) exhibited net potentiation. This difference could be because of higher initial PPR in the non-FS neurons. We propose that weight-dependent heterosynaptic plasticity may counteract runaway dynamics of excitatory inputs imposed by Hebbian-type learning rules and contribute to fine-tuning of distinct aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.SIGNIFICANCE STATEMENT Dynamic balance of excitation and inhibition is fundamental for operation of neuronal networks. Fine-tuning of such balance requires synaptic plasticity. Knowledge about diverse forms of plasticity operating in excitatory and inhibitory neurons is necessary for understanding normal function and causes of dysfunction of the nervous system. Here we show that excitatory inputs to major archetypal classes of neocortical inhibitory neurons, fast-spiking (FS) and non-fast-spiking (non-FS), express a novel type of plasticity, weight-dependent heterosynaptic plasticity, which accompanies the induction of Hebbian-type changes. This novel form of plasticity may counteract runaway dynamics at excitatory synapses to inhibitory neurons imposed by Hebbian-type learning rules and contribute to fine-tuning of diverse aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.

Adenosine Shifts Plasticity Regimes between Associative and Homeostatic by Modulating Heterosynaptic Changes.

Endogenous extracellular adenosine level fluctuates in an activity-dependent manner and with sleep-wake cycle, modulating synaptic transmission and short-term plasticity. Hebbian-type long-term plasticity introduces intrinsic positive feedback on synaptic weight changes, making them prone to runaway dynamics. We previously demonstrated that co-occurring, weight-dependent heterosynaptic plasticity can robustly prevent runaway dynamics. Here we show that at neocortical synapses in slices from rat visual cortex, adenosine modulates the weight dependence of heterosynaptic plasticity: blockade of adenosine A1 receptors abolished weight dependence, while increased adenosine level strengthened it. Using model simulations, we found that the strength of weight dependence determines the ability of heterosynaptic plasticity to prevent runaway dynamics of synaptic weights imposed by Hebbian-type learning. Changing the weight dependence of heterosynaptic plasticity within an experimentally observed range gradually shifted the operating point of neurons between an unbalancing regime dominated by associative plasticity and a homeostatic regime of tightly constrained synaptic changes. Because adenosine tone is a natural correlate of activity level (activity increases adenosine tone) and brain state (elevated adenosine tone increases sleep pressure), modulation of heterosynaptic plasticity by adenosine represents an endogenous mechanism that translates changes of the brain state into a shift of the regime of synaptic plasticity and learning. We speculate that adenosine modulation may provide a mechanism for fine-tuning of plasticity and learning according to brain state and activity.SIGNIFICANCE STATEMENT Associative learning depends on brain state and is impaired when the subject is sleepy or tired. However, the link between changes of brain state and modulation of synaptic plasticity and learning remains elusive. Here we show that adenosine regulates weight dependence of heterosynaptic plasticity: adenosine strengthened weight dependence of heterosynaptic plasticity; blockade of adenosine A1 receptors abolished it. In model neurons, such changes of the weight dependence of heterosynaptic plasticity shifted their operating point between regimes dominated by associative plasticity or by synaptic homeostasis. Because adenosine tone is a natural correlate of activity level and brain state, modulation of plasticity by adenosine represents an endogenous mechanism for translation of brain state changes into a shift of the regime of synaptic plasticity and learning.

Estimating short-term synaptic plasticity from pre- and postsynaptic spiking.

Short-term synaptic plasticity (STP) critically affects the processing of information in neuronal circuits by reversibly changing the effective strength of connections between neurons on time scales from milliseconds to a few seconds. STP is traditionally studied using intracellular recordings of postsynaptic potentials or currents evoked by presynaptic spikes. However, STP also affects the statistics of postsynaptic spikes. Here we present two model-based approaches for estimating synaptic weights and short-term plasticity from pre- and postsynaptic spike observations alone. We extend a generalized linear model (GLM) that predicts postsynaptic spiking as a function of the observed pre- and postsynaptic spikes and allow the connection strength (coupling term in the GLM) to vary as a function of time based on the history of presynaptic spikes. Our first model assumes that STP follows a Tsodyks-Markram description of vesicle depletion and recovery. In a second model, we introduce a functional description of STP where we estimate the coupling term as a biophysically unrestrained function of the presynaptic inter-spike intervals. To validate the models, we test the accuracy of STP estimation using the spiking of pre- and postsynaptic neurons with known synaptic dynamics. We first test our models using the responses of layer 2/3 pyramidal neurons to simulated presynaptic input with different types of STP, and then use simulated spike trains to examine the effects of spike-frequency adaptation, stochastic vesicle release, spike sorting errors, and common input. We find that, using only spike observations, both model-based methods can accurately reconstruct the time-varying synaptic weights of presynaptic inputs for different types of STP. Our models also capture the differences in postsynaptic spike responses to presynaptic spikes following short vs long inter-spike intervals, similar to results reported for thalamocortical connections. These models may thus be useful tools for characterizing short-term plasticity from multi-electrode spike recordings in vivo.

Partial Breakdown of Input Specificity of STDP at Individual Synapses Promotes New Learning.

UNLABELLED: Hebbian-type learning rules, which underlie learning and refinement of neuronal connectivity, postulate input specificity of synaptic changes. However, theoretical analyses have long appreciated that additional mechanisms, not restricted to activated synapses, are needed to counteract positive feedback imposed by Hebbian-type rules on synaptic weight changes and to achieve stable operation of learning systems. The biological basis of such mechanisms has remained elusive. Here we show that, in layer 2/3 pyramidal neurons from slices of visual cortex of rats, synaptic changes induced at individual synapses by spike timing-dependent plasticity do not strictly follow the input specificity rule. Spike timing-dependent plasticity is accompanied by changes in unpaired synapses: heterosynaptic plasticity. The direction of heterosynaptic changes is weight-dependent, with balanced potentiation and depression, so that the total synaptic input to a cell remains preserved despite potentiation or depression of individual synapses. Importantly, this form of heterosynaptic plasticity is induced at unpaired synapses by the same pattern of postsynaptic activity that induces homosynaptic changes at paired synapses. In computer simulations, we show that experimentally observed heterosynaptic plasticity can indeed serve the theoretically predicted role of robustly preventing runaway dynamics of synaptic weights and activity. Moreover, it endows model neurons and networks with essential computational features: enhancement of synaptic competition, facilitation of the development of specific intrinsic connectivity, and the ability for relearning. We conclude that heterosynaptic plasticity is an inherent property of plastic synapses, crucial for normal operation of learning systems. SIGNIFICANCE STATEMENT: We show that spike timing-dependent plasticity in L2/L3 pyramids from rat visual cortex is accompanied by plastic changes in unpaired synapses. These heterosynaptic changes are weight-dependent and balanced: individual synapses expressed significant LTP or LTD, but the average over all synapses did not change. Thus, the rule of input specificity breaks down at individual synapses but holds for responses averaged over many inputs. In model neurons and networks, this experimentally characterized form of heterosynaptic plasticity prevents runaway dynamics of synaptic weights and activity, enhances synaptic competition, facilitates development of specific intrinsic connectivity, and enables relearning. This new form of heterosynaptic plasticity represents the cellular basis of a theoretically postulated mechanism, which is additional to Hebbian-type rules, and is necessary for stable operation of learning systems.

Very low concentrations of ethanol suppress excitatory synaptic transmission in rat visual cortex.

Ethanol is one of the most commonly used substances in the world. Behavioral effects of alcohol are well described, however, cellular mechanisms of its action are poorly understood. There is an apparent contradiction between measurable behavioral changes produced by low concentrations of ethanol, and lack of evidence of synaptic changes at these concentrations. Furthermore, effects of ethanol on synaptic transmission in the neocortex are poorly understood. Here, we set to determine effects of ethanol on excitatory synaptic transmission in the neocortex. We show that 1-50 mm ethanol suppresses excitatory synaptic transmission to layer 2/3 pyramidal neurons in rat visual cortex in a concentration-dependent manner. To the best of our knowledge, this is the first demonstration of the effects of very low concentrations of ethanol (from 1 mm) on synaptic transmission in the neocortex. We further show that a selective antagonist of A1 adenosine receptors, 8-cyclopentyl-1,3-dipropylxanthine (DPCPX), blocks effects of 1-10 mm ethanol on synaptic transmission. However, the reduction in excitatory postsynaptic potential amplitude by 50 mm ethanol was not affected by DPCPX. We propose that ethanol depresses excitatory synaptic transmission in the neocortex by at least two mechanisms, engaged at different concentrations: low concentrations of ethanol reduce synaptic transmission via A1 R-dependent mechanism and involve presynaptic changes, while higher concentrations activate additional, adenosine-independent mechanisms with predominantly postsynaptic action. Involvement of adenosine signaling in mediating effects of low concentrations of ethanol may have important implications for understanding alcohol's effects on brain function, and provide a mechanistic explanation to the interaction between alcohol and caffeine.

Neural spike-timing patterns vary with sound shape and periodicity in three auditory cortical fields.

Mammals perceive a wide range of temporal cues in natural sounds, and the auditory cortex is essential for their detection and discrimination. The rat primary (A1), ventral (VAF), and caudal suprarhinal (cSRAF) auditory cortical fields have separate thalamocortical pathways that may support unique temporal cue sensitivities. To explore this, we record responses of single neurons in the three fields to variations in envelope shape and modulation frequency of periodic noise sequences. Spike rate, relative synchrony, and first-spike latency metrics have previously been used to quantify neural sensitivities to temporal sound cues; however, such metrics do not measure absolute spike timing of sustained responses to sound shape. To address this, in this study we quantify two forms of spike-timing precision, jitter, and reliability. In all three fields, we find that jitter decreases logarithmically with increase in the basis spline (B-spline) cutoff frequency used to shape the sound envelope. In contrast, reliability decreases logarithmically with increase in sound envelope modulation frequency. In A1, jitter and reliability vary independently, whereas in ventral cortical fields, jitter and reliability covary. Jitter time scales increase (A1 < VAF < cSRAF) and modulation frequency upper cutoffs decrease (A1 > VAF > cSRAF) with ventral progression from A1. These results suggest a transition from independent encoding of shape and periodicity sound cues on short time scales in A1 to a joint encoding of these same cues on longer time scales in ventral nonprimary cortices.

Identifying and tracking simulated synaptic inputs from neuronal firing: insights from in vitro experiments.

Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes.

Adenosine effects on inhibitory synaptic transmission and excitation-inhibition balance in the rat neocortex.

KEY POINTS: Adenosine might be the most widespread neuromodulator in the brain, but its effects on inhibitory transmission in the neocortex are not understood. Here we report that adenosine suppresses inhibitory transmission to layer 2/3 pyramidal neurons via activation of presynaptic A1 receptors. We present evidence for functional A2A receptors, which have a weak modulatory effect on the A1-mediated suppression, at about 50% of inhibitory synapses at pyramidal neurons. Adenosine suppresses excitatory and inhibitory transmission to a different extent, and can change the excitation-inhibition balance at a set of synapses bidirectionally, but on average the balance was maintained during application of adenosine. These results suggest that changes of adenosine concentration may lead to differential modulation of excitatory-inhibitory balance in pyramidal neurons, and thus redistribution of local spotlights of activity in neocortical circuits, while preserving the balanced state of the whole network. ABSTRACT: Adenosine might be the most widespread neuromodulator in the brain: as a metabolite of ATP it is present in every neuron and glial cell. However, how adenosine affects operation of neurons and networks in the neocortex is poorly understood, mostly because modulation of inhibitory transmission by adenosine has been so little studied. To clarify adenosine's role at inhibitory synapses, and in excitation-inhibition balance in pyramidal neurons, we recorded pharmacologically isolated inhibitory responses, compound excitatory-inhibitory responses and spontaneous events in layer 2/3 pyramidal neurons in slices from rat visual cortex. We show that adenosine (1-150 µm) suppresses inhibitory transmission to these neurons in a concentration-dependent and reversible manner. The suppression was mediated by presynaptic A1 receptors (A1Rs) because it was blocked by a selective A1 antagonist, DPCPX, and associated with changes of release indices: paired-pulse ratio, inverse coefficient of variation and frequency of miniature events. At some synapses (12 out of 24) we found evidence for A2ARs: their blockade led to a small but significant increase of the magnitude of adenosine-mediated suppression. This effect of A2AR blockade was not observed when A1Rs were blocked, suggesting that A2ARs do not have their own effect on transmission, but can modulate the A1R-mediated suppression. At both excitatory and inhibitory synapses, the magnitude of A1R-mediated suppression and A2AR-A1R interaction expressed high variability, suggesting high heterogeneity of synapses in the sensitivity to adenosine. Adenosine could change the balance between excitation and inhibition at a set of inputs to a neuron bidirectionally, towards excitation or towards inhibition. On average, however, these bidirectional changes cancelled each other, and the overall balance of excitation and inhibition was maintained during application of adenosine. These results suggest that changes of adenosine concentration may lead to differential modulation of excitatory-inhibitory balance in pyramidal neurons, and thus redistribution of local spotlights of activity in neocortical circuits, while preserving the balanced state of the whole network.

Fast computations in cortical ensembles require rapid initiation of action potentials.

The abilities of neuronal populations to encode rapidly varying stimuli and respond quickly to abrupt input changes are crucial for basic neuronal computations, such as coincidence detection, grouping by synchrony, and spike-timing-dependent plasticity, as well as for the processing speed of neuronal networks. Theoretical analyses have linked these abilities to the fast-onset dynamics of action potentials (APs). Using a combination of whole-cell recordings from rat neocortical neurons and computer simulations, we provide the first experimental evidence for this conjecture and prove its validity for the case of distal AP initiation in the axon initial segment (AIS), typical for cortical neurons. Neocortical neurons with fast-onset APs in the soma can phase-lock their population firing to signal frequencies up to ∼300-400 Hz and respond within 1-2 ms to subtle changes of input current. The ability to encode high frequencies and response speed were dramatically reduced when AP onset was slowed by experimental manipulations or was intrinsically slow due to immature AP generation mechanisms. Multicompartment conductance-based models reproducing the initiation of spikes in the AIS could encode high frequencies only if AP onset was fast at the initiation site (e.g., attributable to cooperative gating of a fraction of sodium channels) but not when fast onset of somatic AP was produced solely by backpropagation. We conclude that fast-onset dynamics is a genuine property of cortical AP generators. It enables fast computations in cortical circuits that are rich in recurrent connections both within each region and across the hierarchy of areas.

Heterosynaptic plasticity prevents runaway synaptic dynamics.

Spike timing-dependent plasticity (STDP) and other conventional Hebbian-type plasticity rules are prone to produce runaway dynamics of synaptic weights. Once potentiated, a synapse would have higher probability to lead to spikes and thus to be further potentiated, but once depressed, a synapse would tend to be further depressed. The runaway synaptic dynamics can be prevented by precisely balancing STDP rules for potentiation and depression; however, experimental evidence shows a great variety of potentiation and depression windows and magnitudes. Here we show that modifications of synapses to layer 2/3 pyramidal neurons from rat visual and auditory cortices in slices can be induced by intracellular tetanization: bursts of postsynaptic spikes without presynaptic stimulation. Induction of these heterosynaptic changes depended on the rise of intracellular calcium, and their direction and magnitude correlated with initial state of release mechanisms. We suggest that this type of plasticity serves as a mechanism that stabilizes the distribution of synaptic weights and prevents their runaway dynamics. To test this hypothesis, we develop a cortical neuron model implementing both homosynaptic (STDP) and heterosynaptic plasticity with properties matching the experimental data. We find that heterosynaptic plasticity effectively prevented runaway dynamics for the tested range of STDP and input parameters. Synaptic weights, although shifted from the original, remained normally distributed and nonsaturated. Our study presents a biophysically constrained model of how the interaction of different forms of plasticity--Hebbian and heterosynaptic--may prevent runaway synaptic dynamics and keep synaptic weights unsaturated and thus capable of further plastic changes and formation of new memories.

Ethanol Differentially Affects Excitatory and Inhibitory Synaptic Transmission in Visual Cortex of Wild-type and Adenosine A1R Knock-out Mice.

Ethanol is one of the most commonly used and abused substances in the world. While the behavioral effects of ethanol are well characterized, mechanisms of its action on neurons and synapses remain elusive. Prior research suggested that ethanol could affect neurons by interfering with metabolism of biologically active molecules, such as adenosine. Here, we explored the involvement of adenosine A1 receptors (A1R) in mediating ethanol's effects on synaptic transmission to layer 2/3 pyramidal neurons of visual cortex using wild type (WT) and A1R knock-out (KO) mice. Ethanol differentially affected excitatory and inhibitory transmission in WT and KO mice. In slices from WT mice ethanol had heterogeneous effects on excitatory transmission (facilitation, suppression or no change), with no net change. Ethanol's effects remained heterogeneous during acute blockade of A1Rs with a selective antagonist DPCPX. However, in A1RKO mice ethanol consistently suppressed excitatory transmission, with no cases of enhancement observed. Inhibitory transmission was suppressed by ethanol in both WT and A1RKO mice. At both excitatory and inhibitory synapses, changes of response amplitude correlated with changes of paired-pulse ratio, suggesting involvement of presynaptic mechanisms. We conclude that A1Rs are not involved in mediating effects of ethanol on synaptic transmission in mouse visual cortex. However, A1Rs are necessary for development of mechanisms mediating facilitation at some excitatory synapses. Our results add evidence for the diversity of ethanol's effects and mechanisms of action on synaptic transmission in different brain structures, and even in the same brain area (visual cortex) in different species, rats vs mice.

Energy-efficient encoding by shifting spikes in neocortical neurons.

The speed of computations in neocortical networks critically depends on the ability of populations of spiking neurons to rapidly detect subtle changes in the input and translate them into firing rate changes. However, high sensitivity to perturbations may lead to explosion of noise and increased energy consumption. Can neuronal networks reconcile the requirements for high sensitivity, operation in a low-noise regime, and constrained energy consumption? Using intracellular recordings in slices from the rat visual cortex, we show that layer 2/3 pyramidal neurons are highly sensitive to minor input perturbations. They can change their population firing rate in response to small artificial excitatory postsynaptic currents (aEPSCs) immersed in fluctuating noise very quickly, within 2-2.5 ms. These quick responses were mediated by the generation of new, additional action potentials (APs), but also by shifting spikes into the response peak. In that latter case, the spike count increase during the peak and the decrease after the peak cancelled each other, thus producing quick responses without increases in total spike count and associated energy costs. The contribution of spikes from one or the other source depended on the aEPSCs timing relative to the waves of depolarization produced by ongoing activity. Neurons responded by shifting spikes to aEPSCs arriving at the beginning of a depolarization wave, but generated additional spikes in response to aEPSCs arriving towards the end of a wave. We conclude that neuronal networks can combine high sensitivity to perturbations and operation in a low-noise regime. Moreover, certain patterns of ongoing activity favor this combination and energy-efficient computations.

Response retention and apparent motion effect in visual cortex models.

Apparent motion is a visual illusion in which stationary stimuli, flashing in distinct spatial locations at certain time intervals, are perceived as one stimulus moving between these locations. In the primary visual cortex, apparent-motion stimuli produce smooth spatio-temporal patterns of activity similar to those produced by continuously moving stimuli. An important prerequisite for producing such activity patterns is prolongation of responses to brief stimuli. Indeed, a brief stimulus can evoke in the visual cortex a long response, outlasting the stimulus by hundreds of milliseconds. Here we use firing-rate based models with simple ring structure, and biologically-detailed conductance-based refractory density (CBRD) model with retinotopic space representation to analyze the response retention and the origin of smooth profiles of activity in response to apparent-motion stimuli. We show that the strength of recurrent connectivity is the major factor that endorses neuronal networks with the ability for response retention. The same strengths of recurrent connections mediate the appearance of bump attractor in the ring models. Factors such as synaptic depression, NMDA receptor mediated currents, and conductances regulating spike adaptation influence response retention, but cannot substitute for the weakness of recurrent connections to reproduce response retention in models with weak connectivity. However, the weakness of lateral recurrent connections can be compensated by layering: in multi-layer models even with weaker connections the activity retains due to its feedforward propagation from layer to layer. Using CBRD model with retinotopic space representation we further show that smooth spatio-temporal profiles of activity in response to apparent-motion stimuli are produced in the models expressing response retention, but not in the models that fail to produce response retention. Together, these results demonstrate a link between response retention and the ability of neuronal networks to generate spatio-temporal patterns of activity, which are compatible with perception of apparent motion.

Ultrafast population encoding by cortical neurons.

The processing speed of the brain depends on the ability of neurons to rapidly relay input changes. Previous theoretical and experimental studies of the timescale of population firing rate responses arrived at controversial conclusions, some advocating an ultrafast response scale but others arguing for an inherent disadvantage of mean encoded signals for rapid detection of the stimulus onset. Here we assessed the timescale of population firing rate responses of neocortical neurons in experiments performed in the time domain and the frequency domain in vitro and in vivo. We show that populations of neocortical neurons can alter their firing rate within 1 ms in response to somatically delivered weak current signals presented on a fluctuating background. Signals with amplitudes of miniature postsynaptic currents can be robustly and rapidly detected in the population firing. We further show that population firing rate of neurons of rat visual cortex in vitro and cat visual cortex in vivo can reliably encode weak signals varying at frequencies up to ∼200-300 Hz, or ∼50 times faster than the firing rate of individual neurons. These results provide coherent evidence for the ultrafast, millisecond timescale of cortical population responses. Notably, fast responses to weak stimuli are limited to the mean encoding. Rapid detection of current variance changes requires extraordinarily large signal amplitudes. Our study presents conclusive evidence showing that cortical neurons are capable of rapidly relaying subtle mean current signals. This provides a vital mechanism for the propagation of rate-coded information within and across brain areas.

Properties of slow oscillation during slow-wave sleep and anesthesia in cats.

Deep anesthesia is commonly used as a model of slow-wave sleep (SWS). Ketamine-xylazine anesthesia reproduces the main features of sleep slow oscillation: slow, large-amplitude waves in field potential, which are generated by the alternation of hyperpolarized and depolarized states of cortical neurons. However, direct quantitative comparison of field potential and membrane potential fluctuations during natural sleep and anesthesia is lacking, so it remains unclear how well the properties of sleep slow oscillation are reproduced by the ketamine-xylazine anesthesia model. Here, we used field potential and intracellular recordings in different cortical areas in the cat to directly compare properties of slow oscillation during natural sleep and ketamine-xylazine anesthesia. During SWS cortical activity showed higher power in the slow/delta (0.1-4 Hz) and spindle (8-14 Hz) frequency range, whereas under anesthesia the power in the gamma band (30-100 Hz) was higher. During anesthesia, slow waves were more rhythmic and more synchronous across the cortex. Intracellular recordings revealed that silent states were longer and the amplitude of membrane potential around transition between active and silent states was bigger under anesthesia. Slow waves were mostly uniform across cortical areas under anesthesia, but in SWS, they were most pronounced in associative and visual areas but smaller and less regular in somatosensory and motor cortices. We conclude that, although the main features of the slow oscillation in sleep and anesthesia appear similar, multiple cellular and network features are differently expressed during natural SWS compared with ketamine-xylazine anesthesia.

Heterosynaptic plasticity induced by intracellular tetanization in layer 2/3 pyramidal neurons in rat auditory cortex.

Associative Hebbian-type synaptic plasticity underlies the mechanisms of learning and memory; however, Hebbian learning rules lead to runaway dynamics of synaptic weights and lack mechanisms for synaptic competition.Heterosynaptic plasticity may solve these problems by complementing plasticity at synapses that were active during the induction, with opposite-sign changes at non-activated synapses. In visual cortex, a potential candidate mechanism for normalization is plasticity induced by a purely postsynaptic protocol, intracellular tetanization. Here we asked if intracellular tetanization can induce long-term plasticity in auditory cortex. We recorded excitatory postsynaptic potentials (EPSPs) of regular (n =76) and all-or-none (n =24) type in layer 2/3 pyramidal cells in slices from rat auditory cortex. After intracellular tetanization, 32 of 76 regular inputs (42%) showed long-term depression, 21 inputs (28%) showed potentiation and 23 inputs (30%) did not change. The direction of plasticity correlated with the initial release probability: inputs with initially low release probability tended to be potentiated, while inputs with high release probability tended to be depressed. Thus, intracellular tetanization had a normalizing effect on synaptic efficacy. Induction of plasticity by intracellular tetanization required a rise of intracellular [Ca(2+)], because it was impaired by chelating intracellular calcium with EGTA. The long-term changes induced by intracellular tetanization involved both pre and postsynaptic mechanisms. EPSP amplitude changes were correlated with changes of release indices: paired-pulse ratio and the inverse of the coefficient of variation (CV(-2)). Furthermore at some all-or-none synapses, changes of averaged response amplitude were correlated with a change of the failure rate, without a change of the synaptic potency, measured as averaged amplitude of successful responses. Presynaptic components of plastic changes were abolished in experiments with blockade of NO-synthesis and spread, indicating involvement of NO signalling. These results demonstrate that the ability of purely postsynaptic challenges to induce plasticity is a general property of pyramidal neurons of both auditory and visual cortices.