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Activity-dependent changes of synapse strength have been extensively characterized at chemical synapses, but the relationship between physiological forms of activity and strength at electrical synapses remains poorly characterized and understood. For mammalian electrical synapses comprising hexamers of connexin36, physiological forms of neuronal activity in coupled pairs have thus far only been linked to long-term depression; activity that results in strengthening of electrical synapses has not yet been identified. Here, we performed dual whole-cell current-clamp recordings in acute slices of P11-P15 Sprague-Dawley rats of electrically coupled neurons of the thalamic reticular nucleus (TRN), a central brain area that regulates cortical input from and attention to the sensory surround. Using TTA-A2 to limit bursting, we show that tonic spiking in one neuron of a pair results in long-term potentiation of electrical synapses. We use experiments and computational modeling to show that the magnitude of plasticity expressed alters the functionality of the synapse. Potentiation is expressed asymmetrically, indicating that regulation of connectivity depends on the direction of use. Furthermore, calcium pharmacology and imaging indicate that potentiation depends on calcium flux. We thus propose a calcium-based activity rule for bidirectional plasticity of electrical synapse strength. Because electrical synapses dominate intra-TRN connectivity, these synapses and their activity-dependent modifications are key dynamic regulators of thalamic attention circuitry. More broadly, we speculate that bidirectional modifications of electrical synapses may be a widespread and powerful principle for ongoing, dynamic reorganization of neuronal circuitry across the brain.NEW & NOTEWORTHY This work reveals a physiologically relevant form of activity pairing in coupled neurons that results in long-term potentiation of mammalian electrical synapses. These findings, in combination with previous work, allow the authors to propose a bidirectional calcium-based rule for plasticity of electrical synapses, similar to those demonstrated for chemical synapses. These new insights inform the field on how electrical synapse plasticity may modify the neural circuits that incorporate them.

Two distinct types of neuronal activity result in long-term depression (LTD) of electrical synapses, with overlapping biochemical intracellular signaling pathways that link activity to synaptic strength, in electrically coupled neurons of the thalamic reticular nucleus (TRN). Because components of both signaling pathways can also be modulated by GABAB receptor activity, here we examined the impact of GABAB receptor activation on the two established inductors of LTD in electrical synapses. Recording from patched pairs of coupled rat neurons in vitro, we show that GABAB receptor inactivation itself induces a modest depression of electrical synapses and occludes LTD induction by either paired bursting or metabotropic glutamate receptor (mGluR) activation. GABAB activation also occludes LTD from either paired bursting or mGluR activation. Together, these results indicate that afferent sources of GABA, such as those from the forebrain or substantia nigra to the reticular nucleus, gate the induction of LTD from either neuronal activity or afferent glutamatergic receptor activation. These results add to a growing body of evidence that the regulation of thalamocortical transmission and sensory attention by TRN is modulated and controlled by other brain regions. Significance: We show that electrical synapse plasticity is gated by GABAB receptors in the thalamic reticular nucleus. This effect is a novel way for afferent GABAergic input from the basal ganglia to modulate thalamocortical relay and is a possible mediator of intra-TRN inhibitory effects.

Electrical synapses couple inhibitory neurons across the brain, underlying a variety of functions that are modifiable by activity. Despite recent advances, many basic functions and contributions of electrical synapses within neural circuitry remain underappreciated. Among these is the source and impact of electrical synapse asymmetry. Using multi-compartmental models of neurons coupled through dendritic electrical synapses, we investigated intrinsic factors that contribute to synaptic asymmetry and that result in modulation of spike time between coupled cells. We show that electrical synapse location along a dendrite, input resistance, internal dendritic resistance, or directional conduction of the electrical synapse itself each alter asymmetry as measured by coupling between cell somas. Conversely, true synapse asymmetry can be masked by each of these properties. Furthermore, we show that asymmetry alters the spiking timing and latency of coupled cells by up to tens of milliseconds, depending on direction of conduction or dendritic location of the electrical synapse. These simulations illustrate that causes of asymmetry are multifactorial, may not be apparent in somatic measurements of electrical coupling, influence dendritic processing, and produce a variety of outcomes on spike timing of coupled cells. Our findings highlight aspects of electrical synapses that should be considered in experimental demonstrations of coupling, and when assembling networks containing electrical synapses.

Electrical synapses couple inhibitory neurons across the brain, underlying a variety of functions that are modifiable by activity. Despite recent advances, many functions and contributions of electrical synapses within neural circuitry remain underappreciated. Among these are the sources and impacts of electrical synapse asymmetry. Using multi-compartmental models of neurons coupled through dendritic electrical synapses, we investigated intrinsic factors that contribute to effective synaptic asymmetry and that result in modulation of spike timing and synchrony between coupled cells. We show that electrical synapse location along a dendrite, input resistance, internal dendritic resistance, or directional conduction of the electrical synapse itself each alter asymmetry as measured by coupling between cell somas. Conversely, we note that asymmetrical gap junction (GJ) conductance can be masked by each of these properties. Furthermore, we show that asymmetry modulates spike timing and latency of coupled cells by up to tens of milliseconds, depending on direction of conduction or dendritic location of the electrical synapse. Coordination of rhythmic activity between two cells also depends on asymmetry. These simulations illustrate that causes of asymmetry are diverse, may not be apparent in somatic measurements of electrical coupling, influence dendritic processing, and produce a variety of outcomes on spiking and synchrony of coupled cells. Our findings highlight aspects of electrical synapses that should always be included in experimental demonstrations of coupling, and when assembling simulated networks containing electrical synapses.

Key points Electrical synapses are modified by various forms of activity, including paired activity in coupled neurons and tetanization of the input to coupled neurons. We show that plasticity of electrical synapses that results from paired spiking activity in coupled neurons depends on calcium influx and calcium-initiated signalling pathways. Plasticity that results from tetanization of input fibres does not depend on calcium influx or dynamics. These results imply that electrically coupled neurons have distinct sets of mechanisms for adjusting coupling according to the specific type of activity they experience. Abstract Recent results have demonstrated modification of electrical synapse strength by varied forms of neuronal activity. However, the mechanisms underlying plasticity induction in central mammalian neurons are unclear. Here we show that the two established inductors of plasticity at electrical synapses in the thalamic reticular nucleus - paired burst spiking in coupled neurons, and mGluR-dependent tetanization of synaptic input - are separate pathways that converge at a common downstream endpoint. Using occlusion experiments and pharmacology in patched pairs of coupled neurons in vitro, we show that burst-induced depression depends on calcium entry via voltage-gated channels, is blocked by BAPTA chelation, and recruits intracellular calcium release on its way to activation of phosphatase activity. In contrast, mGluR-dependent plasticity is independent of calcium entry or calcium dynamics. Together, these results show that the spiking-initiated mechanisms underlying electrical synapse plasticity are similar to those that induce plasticity at chemical synapses, and offer the possibility that calcium-regulated mechanisms may also lead to alternate outcomes, such as potentiation. Because these mechanistic elements are widely found in mature neurons, we expect them to apply broadly to electrical synapses across the brain, acting as the crucial link between neuronal activity and electrical synapse strength.

As information about the world traverses the brain, the signals exchanged between neurons are passed and modulated by synapses, or specialized contacts between neurons. While neurotransmitter-based synapses tend to exert either excitatory or inhibitory pulses of influence on the postsynaptic neuron, electrical synapses, composed of plaques of gap junction channels, continuously transmit signals that can either excite or inhibit a coupled neighbor. A growing body of evidence indicates that electrical synapses, similar to their chemical counterparts, are modified in strength during physiological neuronal activity. The synchronizing role of electrical synapses in neuronal oscillations has been well established, but their impact on transient signal processing in the brain is much less understood. Here we constructed computational models based on the canonical feedforward neuronal circuit and included electrical synapses between inhibitory interneurons. We provided discrete closely-timed inputs to the circuits, and characterize the influence of electrical synapse strength on both subthreshold summation and spike trains in the output neuron. Our simulations highlight the diverse and powerful roles that electrical synapses play even in simple circuits. Because these canonical circuits are represented widely throughout the brain, we expect that these are general principles for the influence of electrical synapses on transient signal processing across the brain., Author summary The roles that electrical synapses play in neural oscillations, network synchronization and rhythmicity are well established, but their roles in neuronal processing of transient inputs are much less understood. Here, we used computational models of canonical feedforward circuits and networks to investigate how electrical synapses regulate the flow of transient signals passing through those circuits. We show that because the influence of electrical synapses on coupled neighbors can be either inhibitory or excitatory, their role in network information processing is heterogeneous, and powerful. Because electrical synapses between interneurons are widespread across the brain, and in addition to a growing body of evidence for their activity-dependent plasticity, we expect the effects we describe here to play a substantial role in how the brain processes incoming sensory inputs.

Many forms of behavior require selective amplification of neuronal representations of relevant environmental signals. Following emotional learning, sensory stimuli drive enhanced responses in the sensory cortex. However, the brain circuits that underlie emotionally driven control of the sensory representations remain poorly understood. Here we identify a novel pathway between the basolateral amygdala (BLA), an emotional learning center in the mouse brain, and the inhibitory nucleus of the thalamus (TRN). We demonstrate that activation of this pathway amplifies sound-evoked activity in the central auditory pathway. Optogenetic activation of BLA suppressed spontaneous, but not tone-evoked activity in the auditory cortex (AC), effectively amplifying tone-evoked responses in AC. Anterograde and retrograde viral tracing identified robust BLA projections terminating at TRN. Optogenetic activation of amygdala-TRN pathway mimicked the effect of direct BLA activation, amplifying tone-evoked responses in the auditory thalamus and cortex. The results are explained by a computational model of the thalamocortical circuitry. In our model, activation of TRN by BLA suppresses spontaneous activity in thalamocortical cells, and as a result, thalamocortical neurons are primed to relay relevant sensory input. These results demonstrate a novel circuit mechanism for shining a neural spotlight on behaviorally relevant signals and provide a potential target for treatment of neuropsychological disorders, in which emotional control of sensory processing is disrupted.

As information about the world traverses the brain, the signals exchanged between neurons are passed and modulated by synapses, or specialized contacts between neurons. While neurotransmitter-based synapses tend to be either relay excitatory or inhibitory pulses of influence on the postsynaptic neuron, electrical synapses, composed of plaques of gap junction channels, are always-on transmitters that can either excite or inhibit a coupled neighbor. A growing body of evidence indicates that electrical synapses, similar to their chemical counterparts, are modified in strength during physiological neuronal activity. The synchronizing role of electrical synapses in neuronal oscillations has been well established, but their impact on transient signal processing in the brain is much less understood. Here we constructed computational models based on the canonical feedforward neuronal circuit, and included electrical synapses between inhibitory interneurons. We provided discrete closely-timed inputs to the circuits, and characterize the influence of electrical synapses on both the subthreshold summation and spike trains in the output neuron. Our simulations highlight the diverse and powerful roles that electrical synapses play even in simple circuits. Because these canonical circuits are represented widely throughout the brain, we expect that these are general principles for the influence of electrical synapses on transient signal processing across the brain.Author SummaryThe role that electrical synapses play in neural oscillations, network synchronization and rhythmicity is well established, but their role neuronal processing of transient inputs is much less understood. Here we used computational models of canonical feedforward circuits and networks to investigate how the strength of electrical synapses regulates the flow of transient signals passing through those circuits. We show that because the influence of electrical synapses on coupled neighbors can be either inhibitory or excitatory, their role in network information processing is heterogeneous.. Because of the widespread existence of electrical synapses between interneurons as well as a growing body of evidence for their plasticity, we expect such effects play a significant role in how the brain processes transient inputs.

As multimodal sensory information proceeds to the cortex, it is intercepted and processed by the nuclei of the thalamus. The main source of inhibition within thalamus is the reticular nucleus (TRN), which collects signals both from thalamocortical relay neurons and from thalamocortical feedback. Within the reticular nucleus, neurons are densely interconnected by connexin36-based gap junctions, known as electrical synapses. Electrical synapses have been shown to coordinate neuronal rhythms, including thalamocortical spindle rhythms, but their role in shaping or modulating transient activity is less understood. We constructed a four-cell model of thalamic relay and TRN neurons, and used it to investigate the impact of electrical synapses on closely timed inputs delivered to thalamic relay cells. We show that the electrical synapses of the TRN assist cortical discrimination of these inputs through effects of truncation, delay or inhibition of thalamic spike trains. We expect that these are principles whereby electrical synapses play similar roles in regulating the processing of transient activity in excitatory neurons across the brain.

As multimodal sensory information proceeds to the cortex, it is intercepted and processed by the nuclei of the thalamus. The main source of inhibition within thalamus is the reticular nucleus (TRN), which collects signals both from thalamocortical relay neurons and from thalamocortical feedback. Within the reticular nucleus, neurons are densely interconnected by connexin36-based gap junctions, known as electrical synapses. Electrical synapses have been shown to coordinate neuronal rhythms, including thalamocortical spindle rhythms, but their role in shaping or modulating transient activity is less understood. We constructed a four-cell model of thalamic relay and TRN neurons, and used it to investigate the impact of electrical synapses on closely timed inputs delivered to thalamic relay cells. We show that the electrical synapses of the TRN assist cortical discrimination of these inputs through effects of truncation, delay or inhibition of thalamic spike trains. We expect that these are principles whereby electrical synapses play similar roles in processing of transient activity in excitatory neurons across the brain.

SUMMARY Many forms of behavior require selective amplification of neuronal representations of relevant environmental signals. Emotional learning enhances sensory responses in the sensory cortex, yet the underlying circuits remain poorly understood. We identify a pathway between the basolateral amygdala (BLA), an emotional learning center in the mouse brain, and the inhibitory reticular nucleus of the thalamus (TRN). Optogenetic activation of BLA suppressed spontaneous, but not tone-evoked, activity in the auditory cortex (AC), amplifying tone-evoked responses. Viral tracing identified BLA projections terminating at TRN. Optogenetic activation of amygdala-TRN projections further amplified tone-evoked responses in the auditory thalamus and cortex. The results are explained by a computational model of the thalamocortical circuitry, in which activation of TRN by BLA primes thalamocortical neurons to relay relevant sensory input. This circuit mechanism shines a neural spotlight on behaviorally relevant signals and provides a potential target for the treatment of neuropsychological disorders., Graphical Abstract, In Brief Aizenberg et al. show that the projection from the emotional center of the brain, the basolateral amygdala, to the auditory thalamic control area, the thalamic reticular nucleus, gates sensory processing in the cortex.

Gap junctions mediate electrical synaptic transmission between neurons. While the actions of neurotransmitter modulators on the conductance of gap junctions have been extensively documented, increasing evidence indicates they can also be influenced by the ongoing activity of neural networks, in most cases via local interactions with nearby glutamatergic synapses. We review here early evidence for the existence of activity-dependent regulatory mechanisms as well recent examples reported in mammalian brain. The ubiquitous distribution of both neuronal connexins and the molecules involved suggest this phenomenon is widespread and represents a property of electrical transmission in general.

Throughout the brain, neurons encode information in fundamental units of spikes. Each spike represents the combined thresholding of synaptic inputs and intrinsic neuronal dynamics. Here, we address a basic question of spike train formation: how do perithreshold synaptic inputs perturb the output of a spiking neuron? We recorded from single entorhinal principal cells in vitro and drove them to spike steadily at ∼5 Hz (theta range) with direct current injection, then used a dynamic-clamp to superimpose strong excitatory conductance inputs at varying rates. Neurons spiked most reliably when the input rate matched the intrinsic neuronal firing rate. We also found a striking tendency of neurons to preserve their rates and coefficients of variation, independently of input rates. As mechanisms for this rate maintenance, we show that the efficacy of the conductance inputs varied with the relationship of input rate to neuronal firing rate, and with the arrival time of the input within the natural period. Using a novel method of spike classification, we developed a minimal Markov model that reproduced the measured statistics of the output spike trains and thus allowed us to identify and compare contributions to the rate maintenance and resonance. We suggest that the strength of rate maintenance may be used as a new categorization scheme for neuronal response and note that individual intrinsic spiking mechanisms may play a significant role in forming the rhythmic spike trains of activated neurons; in the entorhinal cortex, individual pacemakers may dominate production of the regional theta rhythm.

Electrical synapses, like chemical synapses, mediate intraneuronal communication. Electrical synapses are typically quantified by subthreshold measurements of coupling, which fall short in describing their impact on spiking activity in coupled neighbors. Here, we describe a novel measurement for electrical synapse strength that directly evaluates the effect of synaptically transmitted activity on spike timing. This method, also applicable to neurotransmitter-based synapses, communicates the considerable strength of electrical synapses. For electrical synapses measured in rodent slices of the thalamic reticular nucleus and in simple model neurons, spike timing is modulated by tens of ms by activity in a coupled neighbor.

Actions of inhibitory interneurons organize and modulate many neuronal processes, yet the mechanisms and consequences of plasticity of inhibitory synapses remain poorly understood. We report on spike-timing-dependent plasticity of inhibitory synapses in the entorhinal cortex. After pairing presynaptic stimulations at time tpre with evoked postsynaptic spikes at time tpost under pharmacological blockade of excitation we found, via whole cell recordings, an asymmetrical timing rule for plasticity of the remaining inhibitory responses. Strength of response varied as a function of the time interval Δ t = tpost − tpre: for Δ t > 0 inhibitory responses potentiated, peaking at a delay of 10 ms. For Δ t < 0, the synaptic coupling depressed, again with a maximal effect near 10 ms of delay. We also show that changes in synaptic strength depend on changes in intracellular calcium concentrations and demonstrate that the calcium enters the postsynaptic cell through voltage-gated channels. Using network models, we demonstrate how this novel form of plasticity can sculpt network behavior efficiently and with remarkable flexibility.

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

While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical findings concerning the rules of spike timing-dependent inhibitory plasticity and their putative network function. This is a summary of a workshop at the COSYNE conference 2012.

Changes in synaptic strength resulting from neuronal activity have been described in great detail for chemical synapses, but the relationship between natural forms of activity and the strength of electrical synapses had previously not been investigated. The thalamic reticular nucleus (TRN), a brain area rich in gap junctional (electrical) synapses, regulates cortical attention, initiates sleep spindles, and participates in shifts between states of arousal. Plasticity of electrical synapses in the TRN may be a key mechanism underlying these processes. Recently, we demonstrated a novel activity-dependent form of long-term depression of electrical synapses in the TRN (Haas et al., 2011). Here we provide an overview of those findings and discuss them in broader context. Because gap junctional proteins are widely expressed in the mammalian brain, modification of synaptic strength is likely to be a widespread and powerful mechanism at electrical synapses throughout the brain.

THALAMIC NEURONS FLUCTUATE BETWEEN TWO STATES: a hyperpolarized state associated with burst firing and sleep spindles, and a depolarized state associated with tonic firing and rapid, reliable information transmission between the sensory periphery and cortex. The thalamic reticular nucleus (TRN) plays a central role in thalamocortical processing by providing feed-forward and feedback inhibition to thalamic relay cells; TRN cells participate in the generation of sleep spindles, and have been suggested to focus the neural "searchlight" of attention. The mechanisms underlying synchrony in the TRN during different behavioral states are largely unknown. TRN cells are densely interconnected by electrical synapses. Here we show that activation of the persistent sodium current (I(NaP)) by depolarization causes up to fourfold changes in electrical synaptic efficacy between TRN neurons. We further show that amplification of electrical synaptic responses strongly enhances tonic spike synchrony but, surprisingly, does not affect burst coordination. We use a Hodgkin-Huxley model to gain insight into the differences between the effects of burstlets, spikelets, and amplification on burst and spike times.

Use-dependent forms of synaptic plasticity have been extensively characterized at chemical synapses, but a relationship between natural activity and strength at electrical synapses remains elusive. The thalamic reticular nucleus (TRN), a brain area rich in gap-junctional (electrical) synapses, regulates cortical attention to the sensory surround and participates in shifts between arousal states; plasticity of electrical synapses may be a key mechanism underlying these processes. We observed long-term depression resulting from coordinated burst firing in pairs of coupled TRN neurons. Changes in gap-junctional communication were asymmetrical, indicating that regulation of connectivity depends on the direction of use. Modification of electrical synapses resulting from activity in coupled neurons is likely to be a widespread and powerful mechanism for dynamic reorganization of electrically coupled neuronal networks.

Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals. In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods., Comment: 15 pages, 17 figures, 30 references Changes: Abstract corrected, one Figure and one Section in Appendix added, plus some minor corrections (Final Version)

Measuring the degree of synchrony between two or more neuronal spike trains is an important tool in order to address issues such as neuronal coding, information transmission and model validation. Another prominent application is to measure the reliability of the response of individual neurons upon repeated presentations of the same stimulus. A number of both multivariate and bivariate measures have been proposed to address this issue. Multivariate approaches include the reliability measures by Hunter and Milton [1] and by Tiesinga [2], while bivariate approaches comprise the Victor-Purpura [3] and the van Rossum [4] distance, as well as the similarity measure proposed by Schreiber et al. [5], and, the most recent proposal, the ISI-distance [6], a method based on relative instantaneous firing rates. These approaches can be applied to multivariate data in a pairwise fashion, e.g., reliability can be defined as the average over all pairwise similarities. ... ...

Estimating the degree of synchrony or reliability between two or more spike trains is a frequent task in both experimental and computational neuroscience. In recent years, many different methods have been proposed that typically compare the timing of spikes on a certain time scale to be fixed beforehand. Here, we propose the ISI-distance, a simple complementary approach that extracts information from the interspike intervals by evaluating the ratio of the instantaneous frequencies. The method is parameter free, time scale independent and easy to visualize as illustrated by an application to real neuronal spike trains obtained in vitro from rat slices. In a comparison with existing approaches on spike trains extracted from a simulated Hindemarsh-Rose network, the ISI-distance performs as well as the best time-scale-optimized measure based on spike timing., 11 pages, 13 figures; v2: minor modifications; v3: minor modifications, added link to webpage that includes the Matlab Source Code for the method (http://inls.ucsd.edu/~kreuz/Source-Code/Spike-Sync.html)

Stellate cells (SCs) of the entorhinal cortex generate prominent subthreshold oscillations that are believed to be important contributors to the hippocampal theta rhythm. The slow inward rectifier Ih is expressed prominently in SCs and has been suggested to be a dominant factor in their integrative properties. We studied the input-output relationships in stellate cells (SCs) of the entorhinal cortex, both in control conditions and in the presence of the Ih antagonist ZD7288. Our results show that Ih is responsible for SCs' subthreshold resonance, and contributes to enhanced spiking reliability to theta-rich stimuli. However, SCs still exhibit other traits of rhythmicity, such as subthreshold oscillations, under Ih blockade. To clarify the effects of Ih on SC spiking, we used a generalized form of principal component analysis to show that SCs select particular features with relevant temporal signatures from stimuli. The spike-selected mix of those features varies with the frequency content of the stimulus, emphasizing the inherent nonlinearity of SC responses. A number of controls confirmed that this selectivity represents a stimulus-induced change in the cellular input-output relationship rather than an artifact of the analysis technique. Sensitivity to slow features remained statistically significant in ZD7288. However, with Ih blocked, slow stimulus features were less predictive of spikes and spikes conveyed less information about the stimulus over long time scales. Together, these results suggest that Ih is an important contributor to the input-output relationships expressed by SCs, but that other factors in SCs also contribute to subthreshold oscillations and nonlinear selectivity to slow features.

Understanding the mechanistic bases of neuronal synchronization is a current challenge in quantitative neuroscience. We studied this problem in two putative cellular pacemakers of the mammalian hippocampal theta rhythm: glutamatergic stellate cells (SCs) of the medial entorhinal cortex and GABAergic oriens-lacunosum-moleculare (O-LM) interneurons of hippocampal region CA1. We used two experimental methods. First, we measured changes in spike timing induced by artificial synaptic inputs applied to individual neurons. We then measured responses of free-running hybrid neuronal networks, consisting of biological neurons coupled (via dynamic clamp) to biological or virtual counterparts. Results from the single-cell experiments predicted network behaviors well and are compatible with previous model-based predictions of how specific membrane mechanisms give rise to empirically measured synchronization behavior. Both cell types phase lock stably when connected via homogeneous excitatory-excitatory (E-E) or inhibitory-inhibitory (I-I) connections. Phase-locked firing is consistently synchronous for either cell type with E-E connections and nearly anti-synchronous with I-I connections. With heterogeneous connections (e.g., excitatory-inhibitory, as might be expected if members of a given population had heterogeneous connections involving intermediate interneurons), networks often settled into phase locking that was either stable or unstable, depending on the order of firing of the two cells in the hybrid network. Our results imply that excitatory SCs, but not inhibitory O-LM interneurons, are capable of synchronizing in phase via monosynaptic mutual connections of the biologically appropriate polarity. Results are largely independent of synaptic strength and synaptic kinetics, implying that our conclusions are robust and largely unaffected by synaptic plasticity.

A crucial issue in the study of the nervous system is the determination of how biophysical noise from probabilistic voltage-dependent and synaptic processes acts to limit neuronal reliability. Experimental and computational work provides indirect evidence that synaptic noise is the major noise source in many cases, but that intrinsic noise from voltage-gated channels makes important contributions in some cells. Rigorous evaluation of the effects and importance of biological noise sources requires one to block the natural noise source pharmacologically, then replace it with an accurate artificial analog. Using this method, which the authors call stochastic dynamic clamping, one can manipulate levels of artificial noise to measure unequivocally the effects of each noise source on neuronal dynamics, excitability, and reliability. The authors are currently developing such systems using two approaches: one that depends on a dedicated digital signal processing card, and one that uses Real-Time Linux.

Electrophysiologically, stellate cells (SCs) from layer II of the medial entorhinal cortex (MEC) are distinguished by intrinsic 4- to 12-Hz subthreshold oscillations. These oscillations are thought to impose a pattern of slow periodic firing that may contribute to the parahippocampal theta rhythm in vivo. Using stimuli with systematically differing frequency content, we examined supra- and subthreshold responses in SCs with the goal of understanding how their distinctive characteristics shape these responses. In reaction to repeated presentations of identical, pseudo-random stimuli, the reliability (repeatability) of the spiking response in SCs depends critically on the frequency content of the stimulus. Reliability is optimal for stimuli with a greater proportion of power in the 4- to 12-Hz range. The simplest mechanistic explanation of these results is that rhythmogenic subthreshold membrane mechanisms resonate with inputs containing significant power in the 4- to 12-Hz band, leading to larger subthreshold excursions and thus enhanced reliability. However, close examination of responses rules out this explanation: SCs do show clear subthreshold resonance (i.e., selective amplification of inputs with particular frequency content) in response to sinusoidal stimuli, while simultaneously showing a lack of subthreshold resonance in response to the pseudo-random stimuli used in reliability experiments. Our results support a model with distinctive input-output relationships under subthreshold and suprathreshold conditions. For suprathreshold stimuli, SC spiking seems to best reflect the amount of input power in the theta (4–12 Hz) frequency band. For subthreshold stimuli, we hypothesize that the magnitude of subthreshold theta-range oscillations in SCs reflects the total power, across all frequencies, of the input.

For the last few years, our laboratory has used experimental and computational techniques to study the biophysical underpinnings of both normal and abnormal synchronous activity in the hippocampal formation and other regions of the brain. Among our findings: 1) Robust synchronous activity occurs most readily when one or more biophysical processes (e.g., the dynamics of particular voltage- or ligand-gated ion channels) serve as a rate-limiting step, with a time scale that matches the rhythm in question. Specifically, we have shown that slow voltage-gated channels in neurons of the entorhinal cortex may contribute to the theta rhythm (White et al., 1995); and that the time constant with which chemical inhibition decays is crucial for stabilizing the gamma rhythm within its particular range of frequencies (Chow et al., 1998, White et al., 1998). 2) Electrical noise from flicker in the conductance states of voltage-gated ion channels interacts with intrinsic cellular nonlinear dynamics to provide novel mechanisms for synchronization (Acker, 2000; White et al., 1998; White et al., 2000). 3) Ionotropic chemical inhibition within the hippocampus is known to have at least two time scales (Banks et al., 2000). Modeling studies (White et al., 2000) indicate that these two time scales of inhibition may contribute to the mixed gamma and theta rhythms seen in vivo.

Recently a novel form of spike timing dependent plasticity (STDP) was observed in GABAergic synaptic couplings in layer II of the entorhinal cortex. Depending on the relative timing of pre-synaptic input at time tpre and postsynaptic excitation at time tpost the synapse is strengthened (Δt = tpost-tpre>0) or weakened (Δt 40 Hz), a frequency range important for several vital neuronal tasks. In this work we study the influence of this novel STDP of inhibitory synapses on the synchronization of two mutually coupled interneurons (MCI) in the presence of heterogeneity and noise. We demonstrate analytically how this synchronization is brought about by defining the spike response curve (SRC), which measures the nonlinear response of neuron to pre-synaptic input. We present simulation results to demonstrate how the unique features of the STDP increase the robustness of synchronization even in the presence of heterogeneity and noise.

Estimating the degree of synchrony or reliability between two or more spike trains is a frequent task in both experi- mental and computational neuroscience. In recent years, many different methods have been proposed that typi- cally compare the timing of spikes on a certain time scale to be fixed beforehand. In this study [1], we propose the ISI-distance, a simple complementary approach that extracts information from the interspike intervals by eval- uating the ratio of the instantaneous frequencies. The method is parameter free, time scale independent and easy to visualize as illustrated by an application to real neuronal spike trains obtained in vitro from rat slices (cf. [2]). We compare the method with six existing approaches (two spike train metrics [3,4], a correlation measure [2,5], a similarity measure [6], and event synchronization [7]) using spike trains extracted from a simulated Hinde- marsh-Rose network [8]. In this comparison the ISI-dis- tance performs as well as the best time-scale-optimized measure based on spike timing, without requiring an externally determined time scale for interaction or com- parison.