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Current representation learning methods in Spiking Neural Networks (SNNs) rely on rate-based encoding, resulting in high spike counts, increased energy consumption, and slower information transmission. In contrast, our proposed method, Weight-Temporally Coded Representation Learning (W-TCRL), utilizes temporally coded inputs, leading to lower spike counts and improved efficiency. To address the challenge of extracting representations from a temporal code with low reconstruction error, we introduce a novel Spike-Timing-Dependent Plasticity (STDP) rule. This rule enables stable learning of relative latencies within the synaptic weight distribution and is locally implemented in space and time, making it compatible with neuromorphic processors. We evaluate the performance of W-TCRL on the MNIST and natural image datasets for image reconstruction tasks. Our results demonstrate relative improvements of 53% for MNIST and 75% for natural images in terms of reconstruction error compared to the SNN state of the art. Additionally, our method achieves significantly higher sparsity, up to 900 times greater, when compared to related work. These findings emphasize the efficacy of W-TCRL in leveraging temporal coding for enhanced representation learning in Spiking Neural Networks.

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Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and in vitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under in vivo conditions, but that background synaptic noise is actually beneficial.

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Both hearing and touch are sensitive to the frequency of mechanical oscillations-sound waves and tactile vibrations, respectively. The mounting evidence of parallels in temporal frequency processing between the two sensory systems led us to directly address the question of perceptual frequency equivalence between touch and hearing using stimuli of simple and more complex temporal features. In a cross-modal psychophysical paradigm, subjects compared the perceived frequency of pulsatile mechanical vibrations to that elicited by pulsatile acoustic (click) trains, and vice versa. Non-invasive pulsatile stimulation designed to excite a fixed population of afferents was used to induce desired temporal spike trains at frequencies spanning flutter up to vibratory hum (>50 Hz). The cross-modal perceived frequency for regular test pulse trains of either modality was a close match to the presented stimulus physical frequency up to 100 Hz. We then tested whether the recently discovered "burst gap" temporal code for frequency, that is shared by the two senses, renders an equivalent cross-modal frequency perception. When subjects compared trains comprising pairs of pulses (bursts) in one modality against regular trains in the other, the cross-sensory equivalent perceptual frequency best corresponded to the silent interval between the successive bursts in both auditory and tactile test stimuli. These findings suggest that identical acoustic and vibrotactile pulse trains, regardless of pattern, elicit equivalent frequencies, and imply analogous temporal frequency computation strategies in both modalities. This perceptual correspondence raises the possibility of employing a cross-modal comparison as a robust standard to overcome the prevailing methodological limitations in psychophysical investigations and strongly encourages cross-modal approaches for transmitting sensory information such as translating pitch into a similar pattern of vibration on the skin.

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The perceived intensity of a vibrotactile stimulus is thought to depend on single-neuron firing rates (rate coding) and the number of active afferents (population coding). Unaddressed until now is whether the temporal relation of individual spikes also conveys information about tactile intensity. We used cutaneous electro-tactile stimulation to investigate how the temporal structure of a fixed number of spikes in a 1-s train influenced the perception of intensity. Four mean spike rates spanning the flutter and vibratory hum range (36 Hz, 60 Hz; 120 Hz, 180 Hz) were tested, with spikes grouped into a regular pattern, or bursts of 2-6 spikes spaced 3 ms apart. To link a putative neural code to perception, perceived intensity was assessed in 16 human participants (aged 20-45; 4 females) using the psychophysical paradigm of magnitude estimation. Compound sensory nerve action potentials were recorded to assess any stimulus variation in afferent recruitment. The temporal structuring of a fixed number of spikes into periodic bursts of multiple spikes altered perceived intensity as a function of burst spike count. The largest increase was seen at 36 Hz, where the bursts of six spikes were rated 2.1 times stronger than the regularly spaced spikes [95% confidence interval (CI): 1.9-2.3]. The true increase is likely larger as temporal structuring of spikes into bursts had some negative effect on afferent recruitment. We conclude that the perceived intensity can be modulated by changing temporal features of afferent discharge even when normalized for the number of recruited afferents.NEW & NOTEWORTHY Structuring a fixed number of spikes into temporal burst patterns evoke gradations of perceived intensity with burst spike count, emphasizing the importance of spike timing in primary afferents for shaping perception. This forms the basis for new strategies in communicating a range of intensity information to users of neural interfaces by simply varying the timing of spikes in nonspecific primary afferents using fixed-charge electric pulses, without requiring alterations in stimulation current or mean pulse frequency.

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In chemical sensation, multiple models have been proposed to explain how odors are represented in the olfactory cortex. One hypothesis is that the combinatorial identity of active neurons within sniff-related time windows is critical, whereas another model proposes that it is the temporal structure of neural activity that is essential for encoding odor information. We find that top-down feedback to the main olfactory bulb dictates the information transmitted to the piriform cortex and switches between these coding strategies. Using a detailed network model, we demonstrate that feedback control of inhibition influences the excitation-inhibition balance in mitral cells, restructuring the dynamics of piriform cortical cells. This results in performance improvement in odor discrimination tasks. These findings present a framework for early olfactory computation, where top-down feedback to the bulb flexibly shapes the temporal structure of neural activity in the piriform cortex, allowing the early olfactory system to dynamically switch between two distinct coding models.

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Sensorimotor transformations are mediated by premotor brain networks where individual neurons represent sensory, cognitive, and movement-related information. Such multiplexing poses a conundrum-how does a decoder know precisely when to initiate a movement if its inputs are active at times when a movement is not desired (e.g., in response to sensory stimulation)? Here, we propose a novel hypothesis: movement is triggered not only by an increase in firing rate but, critically, also by a reliable temporal pattern in the population response. Laminar recordings in the macaque superior colliculus (SC), a midbrain hub of orienting control, and pseudo-population analyses in SC and cortical frontal eye fields (FEFs) corroborated this hypothesis. Specifically, using a measure that captures the fidelity of the population code-here called temporal stability-we show that the temporal structure fluctuates during the visual response but becomes increasingly stable during the movement command. Importantly, we used spatiotemporally patterned microstimulation to causally test the contribution of population temporal stability in gating movement initiation and found that stable stimulation patterns were more likely to evoke a movement. Finally, a spiking neuron model was able to discriminate between stable and unstable input patterns, providing a putative biophysical mechanism for decoding temporal structure. These findings offer new insights into the long-standing debate on motor preparation and generation by situating the movement gating signal in temporal features of activity in shared neural substrates, and they highlight the importance of short-term population history in neuronal communication and behavior.

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Electrical stimulation of the peripheral nerves of human participants provides a unique opportunity to study the neural determinants of perceptual quality using a causal manipulation. A major challenge in the study of neural coding of touch has been to isolate the role of spike timing-at the scale of milliseconds or tens of milliseconds-in shaping the sensory experience. In the present study, we address this question by systematically varying the pulse frequency (PF) of electrical stimulation pulse trains delivered to the peripheral nerves of seven participants with upper and lower extremity limb loss via chronically implanted neural interfaces. We find that increases in PF lead to systematic increases in perceived frequency, up to ∼50 Hz, at which point further changes in PF have little to no impact on sensory quality. Above this transition frequency, ratings of perceived frequency level off, the ability to discriminate changes in PF is abolished, and verbal descriptors selected to characterize the sensation change abruptly. We conclude that sensation quality is shaped by temporal patterns of neural activation, even if these patterns are imposed on a fixed neural population, but this temporal patterning can only be resolved up to ∼50 Hz. These findings highlight the importance of spike timing in shaping the quality of a sensation and will contribute to the development of encoding strategies for conveying touch feedback through bionic hands and feet.SIGNIFICANCE STATEMENT A major challenge in the study of neural coding of touch has been to understand how temporal patterns in neuronal responses shape the sensory experience. We address this question by varying the pulse frequency (PF) of electrical pulse trains delivered through implanted nerve interfaces in seven amputees. We concomitantly vary pulse width to separate the effect of changing PF on sensory quality from its effect on perceived magnitude. We find that increases in PF lead to increases in perceived frequency, a qualitative dimension, up to ∼50 Hz, beyond which changes in PF have little impact on quality. We conclude that temporal patterning in the neuronal response can shape quality and discuss the implications for restoring touch via neural interfaces.

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Brain possesses a complex spatiotemporal architecture for efficient information processing and computing. However, it remains unknown how neural signal propagates to its intended targets brain-wide. Using optogenetics and functional MRI, we arbitrarily initiated various discrete neural activity pulse trains with different temporal patterns and revealed their distinct long-range propagation targets within the well-defined, topographically organized somatosensory thalamo-cortical circuit. We further observed that such neural activity propagation over long range could modulate brain-wide sensory functions. Electrophysiological analysis indicated that distinct propagation pathways arose from system level neural adaptation and facilitation in response to the neural activity temporal characteristics. Together, our findings provide fundamental insights into the long-range information transfer and processing. They directly support that temporal coding underpins the whole brain functional architecture in presence of the vast and relatively static anatomical architecture.

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Ribbon-class synapses in the ear achieve analog to digital transformation of a continuously graded membrane potential to all-or-none spikes. In mammals, several auditory nerve fibres (ANFs) carry information from each inner hair cell (IHC) to the brain in parallel. Heterogeneity of transmission among synapses contributes to the diversity of ANF sound-response properties. In addition to the place code for sound frequency and the rate code for sound level, there is also a temporal code. In series with cochlear amplification and frequency tuning, neural representation of temporal cues over a broad range of sound levels enables auditory comprehension in noisy multi-speaker settings. The IHC membrane time constant introduces a low-pass filter that attenuates fluctuations of the receptor potential above 1-2 kHz. The ANF spike generator adds a high-pass filter via its depolarization-rate threshold that rejects slow changes in the postsynaptic potential and its phasic response property that ensures one spike per depolarization. Synaptic transmission involves several stochastic subcellular processes between IHC depolarization and ANF spike generation, introducing delay and jitter that limits the speed and precision of spike timing. ANFs spike at a preferred phase of periodic sounds in a process called phase-locking that is limited to frequencies below a few kilohertz by both the IHC receptor potential and the jitter in synaptic transmission. During phase-locking to periodic sounds of increasing intensity, faster and facilitated activation of synaptic transmission and spike generation may be offset by presynaptic depletion of synaptic vesicles, resulting in relatively small changes in response phase. Here we review encoding of spike-timing at cochlear ribbon synapses.

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Core auditory cortex (AC) neurons encode slow fluctuations of acoustic stimuli with temporally patterned activity. However, whether temporal encoding is necessary to explain auditory perceptual skills remains uncertain. Here, we recorded from gerbil AC neurons while they discriminated between a 4-Hz amplitude modulation (AM) broadband noise and AM rates >4 Hz. We found a proportion of neurons possessed neural thresholds based on spike pattern or spike count that were better than the recorded session's behavioral threshold, suggesting that spike count could provide sufficient information for this perceptual task. A population decoder that relied on temporal information outperformed a decoder that relied on spike count alone, but the spike count decoder still remained sufficient to explain average behavioral performance. This leaves open the possibility that more demanding perceptual judgments require temporal information. Thus, we asked whether accurate classification of different AM rates between 4 and 12 Hz required the information contained in AC temporal discharge patterns. Indeed, accurate classification of these AM stimuli depended on the inclusion of temporal information rather than spike count alone. Overall, our results compare two different representations of time-varying acoustic features that can be accessed by downstream circuits required for perceptual judgments.

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The amount of information that differentially correlated spikes in a neural ensemble carry is not the same; the information of different types of spikes is associated with different features of the stimulus. By calculating a neural ensemble's information in response to a mixed stimulus comprising slow and fast signals, we show that the entropy of synchronous and asynchronous spikes are different, and their probability distributions are distinctively separable. We further show that these spikes carry a different amount of information. We propose a time-varying entropy (TVE) measure to track the dynamics of a neural code in an ensemble of neurons at each time bin. By applying the TVE to a multiplexed code, we show that synchronous and asynchronous spikes carry information in different time scales. Finally, a decoder based on the Kalman filtering approach is developed to reconstruct the stimulus from the spikes. We demonstrate that slow and fast features of the stimulus can be entirely reconstructed when this decoder is applied to asynchronous and synchronous spikes, respectively. The significance of this work is that the TVE can identify different types of information (for example, corresponding to synchronous and asynchronous spikes) that might simultaneously exist in a neural code.

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Locking of neural firing is ubiquitously observed in the brain and occurs when neurons fire at a particular phase or in synchronization with an external signal. Here we study in detail the locking of single neurons to multiple distinct frequencies at the example of p-type electroreceptor afferents in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus (brown ghost knifefish). We find that electrosensory afferents and pyramidal cells in the electrosensory lateral line lobe (ELL) lock to multiple frequencies, including the electric organ discharge (EOD) frequency, beat, and stimulus itself. We identify key elements necessary for locking to multiple frequencies, study its limits, and provide concise mathematical models reproducing our main findings. Our findings provide another example of how rate and temporal codes can coexist and complement each other in single neurons and demonstrate that sensory coding in p-type electroreceptor afferents provides a much richer representation of the sensory environment than commonly assumed. Since the underlying mechanisms are not specific to the electrosensory system, our results could provide the basis for studying multiple frequency locking in other systems.NEW & NOTEWORTHY Locking of neuronal spikes to external and internal signals is a ubiquitous neurophysiological mechanism that has been extensively studied in several brain areas and species. Using experimental data from the electrosensory system and concise mathematical models, we analyze how a single neuron can simultaneously lock to multiple frequencies. Our findings demonstrate how temporal and rate codes can complement each other and lead to rich neuronal representations of sensory signals.

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Ants who have successfully navigated the long distance between their foraging spot and their nest dozens of times will drastically overshoot their destination if the size of their legs is doubled by the addition of stilts. This observation reflects a navigational strategy called path integration, a strategy also utilized by mammals. Path integration necessitates that animals keep track of their movement speed and use it to precisely and instantly modify where they think they are and where they want to go. Here we review the neural circuitry that has evolved to integrate speed and space. We start with the rate and temporal codes for speed in the hippocampus and work backwards towards the motor and sensory systems. We highlight the need for experiments designed to differentiate the respective contributions of motor efference copy versus sensory inputs. In particular, we discuss the importance of high-resolution tracking of the latency of speed-encoding as a precise way to disentangle the sensory versus motor computations that enable successful spatial navigation at very different speeds.

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Sequences of action potentials, or spikes, carry information in the number of spikes and their timing. Spike timing codes are critical in many sensory systems, but there is now growing evidence that millisecond-scale changes in timing also carry information in motor brain regions, descending decision-making circuits, and individual motor units. Across all of the many signals that control a behavior, how ubiquitous, consistent, and coordinated are spike timing codes? Assessing these open questions ideally involves recording across the whole motor program with spike-level resolution. To do this, we took advantage of the relatively few motor units controlling the wings of a hawk moth, Manduca sexta. We simultaneously recorded nearly every action potential from all major wing muscles and the resulting forces in tethered flight. We found that timing encodes more information about turning behavior than spike count in every motor unit, even though there is sufficient variation in count alone. Flight muscles vary broadly in function as well as in the number and timing of spikes. Nonetheless, each muscle with multiple spikes consistently blends spike timing and count information in a 3:1 ratio. Coding strategies are consistent. Finally, we assess the coordination of muscles using pairwise redundancy measured through interaction information. Surprisingly, not only are all muscle pairs coordinated, but all coordination is accomplished almost exclusively through spike timing, not spike count. Spike timing codes are ubiquitous, consistent, and essential for coordination.

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Harmonic complex tones (HCTs) found in speech, music, and animal vocalizations evoke strong pitch percepts at their fundamental frequencies. The strongest pitches are produced by HCTs that contain harmonics resolved by cochlear frequency analysis, but HCTs containing solely unresolved harmonics also evoke a weaker pitch at their envelope repetition rate (ERR). In the auditory periphery, neurons phase lock to the stimulus envelope, but this temporal representation of ERR degrades and gives way to rate codes along the ascending auditory pathway. To assess the role of the inferior colliculus (IC) in such transformations, we recorded IC neuron responses to HCT and sinusoidally modulated broadband noise (SAMN) with varying ERR from unanesthetized rabbits. Different interharmonic phase relationships of HCT were used to manipulate the temporal envelope without changing the power spectrum. Many IC neurons demonstrated band-pass rate tuning to ERR between 60 and 1,600 Hz for HCT and between 40 and 500 Hz for SAMN. The tuning was not related to the pure-tone best frequency of neurons but was dependent on the shape of the stimulus envelope, indicating a temporal rather than spectral origin. A phenomenological model suggests that the tuning may arise from peripheral temporal response patterns via synaptic inhibition. We also characterized temporal coding to ERR. Some IC neurons could phase lock to the stimulus envelope up to 900 Hz for either HCT or SAMN, but phase locking was weaker with SAMN. Together, the rate code and the temporal code represent a wide range of ERR, providing strong cues for the pitch of unresolved harmonics.NEW & NOTEWORTHY Envelope repetition rate (ERR) provides crucial cues for pitch perception of frequency components that are not individually resolved by the cochlea, but the neural representation of ERR for stimuli containing many harmonics is poorly characterized. Here we show that the pitch of stimuli with unresolved harmonics is represented by both a rate code and a temporal code for ERR in auditory midbrain neurons and propose possible underlying neural mechanisms with a computational model.

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The rate and temporal pattern of neural spiking each have the potential to influence computation. In the cerebellum, it has been hypothesized that the irregularity of interspike intervals in Purkinje cells affects their ability to transmit information to downstream neurons. Accordingly, during oculomotor behavior in mice and rhesus monkeys, mean irregularity of Purkinje cell spiking varied with mean eye velocity. However, moment-to-moment variations revealed a tight correlation between eye velocity and spike rate, with no additional information conveyed by spike irregularity. Moreover, when spike rate and irregularity were independently controlled using optogenetic stimulation, the eye movements elicited were well-described by a linear population rate code with 3-5 ms temporal precision. Biophysical and random-walk models identified biologically realistic parameter ranges that determine whether spike irregularity influences responses downstream. The results demonstrate cerebellar control of movements through a remarkably rapid rate code, with no evidence for an additional contribution of spike irregularity.

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Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing.

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Adaptation of neural responses is ubiquitous in sensory systems and can potentially facilitate many important computational functions. Here we examined this issue with a well-constrained computational model of the early olfactory circuits. In the insect olfactory system, the responses of olfactory receptor neurons (ORNs) on the antennae adapt over time. We found that strong adaptation of sensory input is important for rapidly detecting a fresher stimulus encountered in the presence of other background cues and for faithfully representing its identity. However, when the overlapping odorants were chemically similar, we found that adaptation could alter the representation of these odorants to emphasize only distinguishing features. This work demonstrates novel roles for peripheral neurons during olfactory processing in complex environments. NEW & NOTEWORTHY Olfactory systems face the problem of distinguishing salient information from a complex olfactory environment. The neural representations of specific odor sources should be consistent regardless of the background. How are olfactory representations robust to varying environmental interference? We show that in locusts the extraction of salient information begins in the periphery. Olfactory receptor neurons adapt in response to odorants. Adaptation can provide a computational mechanism allowing novel odorant components to be highlighted during complex stimuli.

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Acuity measures related to overall face size that can be perceived have not been studied quantitatively. Consequently, experimenters use a wide range of sizes (usually large) without always providing a rationale for their choices. I studied thresholds for face discrimination by presenting both long (500 ms)- and short (17, 33, 50 ms)-duration stimuli. Face width threshold for the long presentation was ~0.2°, and thresholds for the flashed stimuli ranged from ~0.3° for the 17-ms flash to ~0.23° for the 33- and 50-ms flashes. Such thresholds indicate that face stimuli used in physiological or psychophysical experiments are often too large to tap human fine spatial capabilities, and thus interpretations of such experiments should take into account face discrimination acuity. The 0.2° threshold found in this study is incompatible with the prevalent view that faces are represented by a population of specialized "face cells" because those cells do not respond to <1° stimuli and are optimally tuned to >4° faces. Also, the ability to discriminate small, high-spatial frequency flashed face stimuli is inconsistent with models suggesting that fixational drift transforms retinal spatial patterns into a temporal code. It seems therefore that the small image motions occurring during fixation do not disrupt our perception, because all relevant processing is over with before those motions can have significant effects. NEW & NOTEWORTHY Although face perception is central to human behavior, the minimally perceived face size is not known. This study shows that humans can discriminate very small (~0.2°) faces. Furthermore, even when flashed for tens of milliseconds, ~0.25° faces can be discriminated. Such fine acuity should impact modeling of physiological mechanisms of face perception. The ability to discriminate flashed faces where there is almost no eye movement indicates that eye drift is not essential for visibility.

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Due to the highly efficient olfactory code, olfactory sensory systems are able to reliably encode enormous numbers of olfactory stimuli. The olfactory code consists of combinatorial activation patterns across sensory neurons, thus its capacity exceeds the number of involved classes of sensory neurons by a manifold. Activation patterns are not static but vary over time, caused by the temporally complex response dynamics of the individual sensory neuron responses. We systematically analyzed the temporal dynamics of olfactory sensory neuron responses to a diverse set of odorants. We find that response dynamics depend on the combination of sensory neuron and odorant and that information about odorant identity can be extracted from the time course of the response. We also show that new response dynamics can arise when mixing two odorants. Our data show that temporal dynamics of odorant responses are able to significantly enhance the coding capacity of olfactory sensory systems.

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