Differential mechanisms underlie trace and delay conditioning in Drosophila.

Two forms of associative learning-delay conditioning and trace conditioning-have been widely investigated in humans and higher-order mammals1. In delay conditioning, an unconditioned stimulus (for example, an electric shock) is introduced in the final moments of a conditioned stimulus (for example, a tone), with both ending at the same time. In trace conditioning, a 'trace' interval separates the conditioned stimulus and the unconditioned stimulus. Trace conditioning therefore relies on maintaining a neural representation of the conditioned stimulus after its termination (hence making distraction possible2), to learn the conditioned stimulus-unconditioned stimulus contingency3; this makes it more cognitively demanding than delay conditioning4. Here, by combining virtual-reality behaviour with neurogenetic manipulations and in vivo two-photon brain imaging, we show that visual trace conditioning and delay conditioning in Drosophila mobilize R2 and R4m ring neurons in the ellipsoid body. In trace conditioning, calcium transients during the trace interval show increased oscillations and slower declines over repeated training, and both of these effects are sensitive to distractions. Dopaminergic activity accompanies signal persistence in ring neurons, and this is decreased by distractions solely during trace conditioning. Finally, dopamine D1-like and D2-like receptor signalling in ring neurons have different roles in delay and trace conditioning; dopamine D1-like receptor 1 mediates both forms of conditioning, whereas the dopamine D2-like receptor is involved exclusively in sustaining ring neuron activity during the trace interval of trace conditioning. These observations are similar to those previously reported in mammals during arousal5, prefrontal activation6 and high-level cognitive learning7,8.

Valence opponency in peripheral olfactory processing.

A hallmark of complex sensory systems is the organization of neurons into functionally meaningful maps, which allow for comparison and contrast of parallel inputs via lateral inhibition. However, it is unclear whether such a map exists in olfaction. Here, we address this question by determining the organizing principle underlying the stereotyped pairing of olfactory receptor neurons (ORNs) in Drosophila sensory hairs, wherein compartmentalized neurons inhibit each other via ephaptic coupling. Systematic behavioral assays reveal that most paired ORNs antagonistically regulate the same type of behavior. Such valence opponency is relevant in critical behavioral contexts including place preference, egg laying, and courtship. Odor-mixture experiments show that ephaptic inhibition provides a peripheral means for evaluating and shaping countervailing cues relayed to higher brain centers. Furthermore, computational modeling suggests that this organization likely contributes to processing ratio information in odor mixtures. This olfactory valence map may have evolved to swiftly process ethologically meaningful odor blends without involving costly synaptic computation.

Thalamocortical and intracortical laminar connectivity determines sleep spindle properties.

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.

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.

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.

Homeostatic role of heterosynaptic plasticity: models and experiments.

Homosynaptic Hebbian-type plasticity provides a cellular mechanism of learning and refinement of connectivity during development in a variety of biological systems. In this review we argue that a complimentary form of plasticity-heterosynaptic plasticity-represents a necessary cellular component for homeostatic regulation of synaptic weights and neuronal activity. The required properties of a homeostatic mechanism which acutely constrains the runaway dynamics imposed by Hebbian associative plasticity have been well-articulated by theoretical and modeling studies. Such mechanism(s) should robustly support the stability of operation of neuronal networks and synaptic competition, include changes at non-active synapses, and operate on a similar time scale to Hebbian-type plasticity. The experimentally observed properties of heterosynaptic plasticity have introduced it as a strong candidate to fulfill this homeostatic role. Subsequent modeling studies which incorporate heterosynaptic plasticity into model neurons with Hebbian synapses (utilizing an STDP learning rule) have confirmed its ability to robustly provide stability and competition. In contrast, properties of homeostatic synaptic scaling, which is triggered by extreme and long lasting (hours and days) changes of neuronal activity, do not fit two crucial requirements for a hypothetical homeostatic mechanism needed to provide stability of operation in the face of on-going synaptic changes driven by Hebbian-type learning rules. Both the trigger and the time scale of homeostatic synaptic scaling are fundamentally different from those of the Hebbian-type plasticity. We conclude that heterosynaptic plasticity, which is triggered by the same episodes of strong postsynaptic activity and operates on the same time scale as Hebbian-type associative plasticity, is ideally suited to serve a homeostatic role during on-going synaptic plasticity.

Learning modifies odor mixture processing to improve detection of relevant components.

Honey bees have a rich repertoire of olfactory learning behaviors, and they therefore are an excellent model to study plasticity in olfactory circuits. Recent behavioral, physiological, and molecular evidence suggested that the antennal lobe, the first relay of the olfactory system in insects and analog to the olfactory bulb in vertebrates, is involved in associative and nonassociative olfactory learning. Here we use calcium imaging to reveal how responses across antennal lobe projection neurons change after association of an input odor with appetitive reinforcement. After appetitive conditioning to 1-hexanol, the representation of an odor mixture containing 1-hexanol becomes more similar to this odor and less similar to the background odor acetophenone. We then apply computational modeling to investigate how changes in synaptic connectivity can account for the observed plasticity. Our study suggests that experience-dependent modulation of inhibitory interactions in the antennal lobe aids perception of salient odor components mixed with behaviorally irrelevant background odors.

The impact of cortical deafferentation on the neocortical slow oscillation.

Slow oscillation is the main brain rhythm observed during deep sleep in mammals. Although several studies have demonstrated its neocortical origin, the extent of the thalamic contribution is still a matter of discussion. Using electrophysiological recordings in vivo on cats and computational modeling, we found that the local thalamic inactivation or the complete isolation of the neocortical slabs maintained within the brain dramatically reduced the expression of slow and fast oscillations in affected cortical areas. The slow oscillation began to recover 12 h after thalamic inactivation. The slow oscillation, but not faster activities, nearly recovered after 30 h and persisted for weeks in the isolated slabs. We also observed an increase of the membrane potential fluctuations recorded in vivo several hours after thalamic inactivation. Mimicking this enhancement in a network computational model with an increased postsynaptic activity of long-range intracortical afferents or scaling K(+) leak current, but not several other Na(+) and K(+) intrinsic currents was sufficient for recovering the slow oscillation. We conclude that, in the intact brain, the thalamus contributes to the generation of cortical active states of the slow oscillation and mediates its large-scale synchronization. Our study also suggests that the deafferentation-induced alterations of the sleep slow oscillation can be counteracted by compensatory intracortical mechanisms and that the sleep slow oscillation is a fundamental and intrinsic state of the neocortex.

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.

Interneuron-mediated inhibition synchronizes neuronal activity during slow oscillation.

The signature of slow-wave sleep in the electroencephalogram (EEG) is large-amplitude fluctuation of the field potential, which reflects synchronous alternation of activity and silence across cortical neurons. While initiation of the active cortical states during sleep slow oscillation has been intensively studied, the biological mechanisms which drive the network transition from an active state to silence remain poorly understood. In the current study, using a combination of in vivo electrophysiology and thalamocortical network simulation, we explored the impact of intrinsic and synaptic inhibition on state transition during sleep slow oscillation. We found that in normal physiological conditions, synaptic inhibition controls the duration and the synchrony of active state termination. The decline of interneuron-mediated inhibition led to asynchronous downward transition across the cortical network and broke the regular slow oscillation pattern. Furthermore, in both in vivo experiment and computational modelling, we revealed that when the level of synaptic inhibition was reduced significantly, it led to a recovery of synchronized oscillations in the form of seizure-like bursting activity. In this condition, the fast active state termination was mediated by intrinsic hyperpolarizing conductances. Our study highlights the significance of both intrinsic and synaptic inhibition in manipulating sleep slow rhythms.

Temporal coding of intensity of NaCl and HCl in the nucleus of the solitary tract of the rat.

Sensory neurons are generally tuned to a subset of stimulus qualities within their sensory domain and manifest this tuning by the relative size of their responses to stimuli of equal intensity. However, response size alone cannot unambiguously signal stimulus quality, since response size also depends on stimulus intensity. Thus a common problem faced by sensory systems is that response size (e.g., spike count) confounds stimulus quality and intensity. Here, using the gustatory system as a model, we asked whether temporal firing characteristics could disambiguate these axes. To address this question, we recorded taste responses of single neurons in the nucleus of the solitary tract (NTS, the first central gustatory relay) in anesthetized rats to a range of concentrations of NaCl and HCl and their binary mixtures. To assess the contribution of the temporal characteristics of the response to discrimination among tastants, a family of metrics that quantifies the similarity of two spike trains in terms of spike count and spike timing was used. Results showed that the spike count produced by different taste qualities and different concentrations overlapped in most cells, implying that information conveyed by spike count is imprecise. Multidimensional scaling analysis of taste responses using similarity of temporal characteristics showed that different taste qualities, intensities, and mixtures formed distinct clusters in this "temporal coding" taste space and were arranged in a logical order. Thus the temporal structure of taste responses in single cells in the NTS can simultaneously convey information about both taste quality and intensity.

A simulation study investigating the impact of dendritic morphology and synaptic topology on neuronal firing patterns.

In the brain, complex information interactions among neurons span several spatial and temporal scales, making it extremely difficult to identify the principles governing neural information processing. In this study, we used computational models to investigate the impact of dendritic morphology and synaptic topology on patterns of neuronal firing. We first constructed Hodgkin-Huxley-type neuron models that possessed dendrites with different morphological features. We then simulated the responses of these neurons to a number of spatiotemporal input patterns. The similarity between neuronal responses to different patterned inputs was effectively evaluated by a novel combination of metric space analysis and multidimensional scaling analyses. The results showed that neurons with different morphological or anatomical features exhibit differences in stimulus-specific temporal encoding and firing reliability. These findings support the idea that in addition to biophysical membrane properties, the dendritic morphology and the synaptic topology of a neuron can play a significant role in neuronal information processing and may directly contribute to various brain functions.

Quality time: representation of a multidimensional sensory domain through temporal coding.

Receptive fields of sensory neurons in the brain are usually restricted to a portion of the entire stimulus domain. At all levels of the gustatory neuraxis, however, there are many cells that are broadly tuned, i.e., they respond well to each of the basic taste qualities (sweet, sour, salty, and bitter). Although it might seem that this broad tuning precludes a major role for these cells in representing taste space, here we show the opposite--namely, that the tastant-specific temporal aspects (firing rate envelope and spike timing) of their responses enable each cell to represent the entire stimulus domain. Specifically, we recorded the response patterns of cells in the nucleus of the solitary tract (NTS) to representatives of four basic taste qualities and their binary mixtures. We analyzed the temporal aspects of these responses, and used their similarities and differences to construct the taste space represented by each neuron. We found that for the more broadly tuned neurons in the NTS, the taste space is a systematic representation of the entire taste domain. That is, the taste space of these broadly tuned neurons is three dimensional, with basic taste qualities widely separated and binary mixtures placed close to their components. Further, the way that taste quality is represented by the firing rate envelope is consistent across the population of cells. Thus, the temporal characteristics of responses in the population of NTS neurons, especially those that are more broadly tuned, produce a comprehensive and logical representation of the taste world.

Responses to binary taste mixtures in the nucleus of the solitary tract: neural coding with firing rate.

The contribution of gustation to the perception of food requires an understanding of how neurons represent mixtures of taste qualities. In the periphery, separate groups of fibers, labeled by the stimulus that evokes the best (largest) response, appear to respond to each component of a mixture. In the brain, identification of analogous groups of neurons is hampered by trial-to-trial variability in response magnitude. In addition, convergence of different fiber types onto central neurons may complicate the classification scheme. To investigate these issues, electrophysiological responses to four tastants: sucrose, NaCl, HCl, and quinine, and their binary mixtures were recorded from 56 cells in the nucleus of the solitary tract (NTS, the 1st synapse in the central gustatory pathway) of the anesthetized rat. For 36 of these cells, all 10 stimuli were repeated at least five times (range: 5-23; median = 10). Results showed that 39% of these cells changed their best stimulus across stimulus repetitions, suggesting that response magnitude (firing rate) on any given trial produces an ambiguous message. Averaged across replicate trials, mixture responses most often approximated the response to the more effective component of the mixture. Cells that responded best to a taste mixture rather than any single-component tastant were identified. These cells were more broadly tuned than were cells that responded best to single-component stimuli and showed evidence of convergence from more than one best stimulus fiber type. Functionally, mixture-best cells may amplify the neural signal produced by unique configurations of basic taste qualities.

Variability in responses and temporal coding of tastants of similar quality in the nucleus of the solitary tract of the rat.

In the nucleus of the solitary tract (NTS), electrophysiological responses to taste stimuli representing four basic taste qualities (sweet, sour, salty, or bitter) can often be discriminated by spike count, although in units for which the number of spikes is variable across identical stimulus presentations, spike timing (i.e., temporal coding) can also support reliable discrimination. The present study examined the contribution of spike count and spike timing to the discrimination of stimuli that evoke the same taste quality but are of different chemical composition. Responses to between 3 and 21 repeated presentations of two pairs of quality-matched tastants were recorded from 38 single cells in the NTS of urethane-anesthetized rats. Temporal coding was assessed in 24 cells, most of which were tested with salty and sour tastants, using an information-theoretic approach. Within a given cell, responses to tastants of similar quality were generally closer in magnitude than responses to dissimilar tastants; however, tastants of similar quality often reversed their order of effectiveness across replicate sets of trials. Typically, discrimination between tastants of dissimilar qualities could be made by spike count. Responses to tastants of similar quality typically evoked more similar response magnitudes but were more frequently, and to a proportionally greater degree, distinguishable based on temporal information. Results showed that nearly every taste-responsive NTS cell has the capacity to generate temporal features in evoked spike trains that can be used to distinguish between stimuli of different qualities and chemical compositions.