Receptive field organization across multiple electrosensory maps. II. Computational analysis of the effects of receptive field size on prey localization

Receptive field sizes and neuronal encoding bandwidth are constrained by axonal conduction delays

Studies on population coding implicitly assume that spikes from the presynaptic cells arrive simultaneously at the integrating neuron. In natural neuronal populations, this is usually not the case-neuronal signaling takes time and populations cover a certain space. The spread of spike arrival times depends on population size, cell density and axonal conduction velocity. Here we analyze the consequences of population size and axonal conduction delays on the stimulus encoding performance in the electrosensory system of the electric fish Apteronotus leptorhynchus. We experimentally locate p-type electroreceptor afferents along the rostro-caudal body axis and relate locations to neurophysiological response properties. In an information-theoretical approach we analyze the coding performance in homogeneous and heterogeneous populations. As expected, the amount of information increases with population size and, on average, heterogeneous populations encode better than the average same-size homogeneous population, if conduction delays are compensated for. The spread of neuronal conduction delays within a receptive field strongly degrades encoding of high-frequency stimulus components. Receptive field sizes typically found in the electrosensory lateral line lobe of A. leptorhynchus appear to be a good compromise between the spread of conduction delays and encoding performance. The limitations imposed by finite axonal conduction velocity are relevant for any converging network as is shown by model populations of LIF neurons. The bandwidth of natural stimuli and the maximum meaningful population sizes are constrained by conduction delays and may thus impact the optimal design of nervous systems.

Coding of object location by heterogeneous neural populations with spatially dependent correlations in weakly electric fish

Understanding how neural populations encode sensory stimuli remains a central problem in neuroscience. Here we performed multi-unit recordings from sensory neural populations in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus in response to stimuli located at different positions along the rostro-caudal axis. Our results reveal that the spatial dependence of correlated activity along receptive fields can help mitigate the deleterious effects that these correlations would otherwise have if they were spatially independent. Moreover, using mathematical modeling, we show that experimentally observed heterogeneities in the receptive fields of neurons help optimize information transmission as to object location. Taken together, our results have important implications for understanding how sensory neurons whose receptive fields display antagonistic center-surround organization encode location. Important similarities between the electrosensory system and other sensory systems suggest that our results will be applicable elsewhere.

Getting the news in milliseconds: The role of early novelty detection in active electrosensory exploration

The pulse emitting weakly electric fish Gymnotus omarorum shows stereotyped "novelty responses" consisting of a transient acceleration of the rhythm of a self-emitted electric organ discharge that carries electrosensory signals. Here we show that rapid increases in electric image amplitude cause a "novelty detection potential" in the first electrosensory relay. This sign precedes and its amplitude predicts, the amplitude of the subsequent behavioral novelty response. Current source density analyses indicates its origin ar the layers of the electrosensory lobe where the main output neurons occur. Two types of units, referred to as "ON" and "OFF". Were recorded there in decerebrated fish. Firing probability of "OFF" units drastically decreased after a stepwise increase in electric image. By contrast, the very first novel stimuli after the increase evoked a sharp peak in firing rate of "ON" units followed by a very fast adaptation phase that contrasted with the slow adaptation observed in previous recordings of primary afferents. The amplitudes of this peak, the novelty detection potential, and the behavioral novelty responses, show the same dependence on the departure of the newest stimulus intensity from the weighted average of preceding ones suggesting that the signals encoded by "ON" neurons underlay the novelty detection potential, propagates through the hierarchical organization of the electromotor control, and finally contribute to accelerate the electric organ discharge rate. This suggests that detecting novelty at the very early processing stage of electrosensory signals is essential to adapt the electrosensory sampling rate to exploration requirements as they change dynamically.

Minimal sensor arrays for localizing objects using an electric sense

Weakly electric fish encode perturbations in a self-generated electric field to sense their environment. Localizing objects using this electric sense requires that distance be decoded from a two-dimensional \emph{electric image} of the field perturbations on their skin. Many studies of object localization by weakly electric fish, and by electric sensing in a generic context, have focused on extracting location information from different features of the electric image. Some of these studies have also considered the additional information gained from sampling the electric image at different times, and from different viewpoints. Here, we take a different perspective and instead consider the information available at a single point in space (i.e. a single sensor or receptor) at a single point in time (i.e. constant field). By combining the information from multiple receptors, we show that an object's distance can be unambiguously encoded by as few as four receptors at specific locations on a sensing surface in a manner that is relatively robust to environmental noise. This provides a lower bound on the information (i.e. receptor array size) required to decode the three-dimensional location of an object using an electric sense.

Distinct neuron phenotypes may serve object feature sensing in the electrosensory lobe of Gymnotus omarorum

Early sensory relay circuits in the vertebrate medulla often adopt a cerebellum-like organization specialized for comparing primary afferent inputs with central expectations. These circuits usually have a dual output, carried by center ON and center OFF neurons responding in opposite ways to the same stimulus at the center of their receptive fields. Here, we show in the electrosensory lateral line lobe of Gymnotiform weakly electric fish that basilar pyramidal neurons, representing 'ON' cells, and non-basilar pyramidal neurons, representing 'OFF' cells, have different intrinsic electrophysiological properties. We used classical anatomical techniques and electrophysiological in vitro recordings to compare these neurons. Basilar neurons are silent at rest, have a high threshold to intracellular stimulation, delayed responses to steady-state depolarization and low pass responsiveness to membrane voltage variations. They respond to low-intensity depolarizing stimuli with large, isolated spikes. As stimulus intensity increases, the spikes are followed by a depolarizing after-potential from which phase-locked spikes often arise. Non-basilar neurons show a pacemaker-like spiking activity, smoothly modulated in frequency by slow variations of stimulus intensity. Spike-frequency adaptation provides a memory of their recent firing, facilitating non-basilar response to stimulus transients. Considering anatomical and functional dimensions, we conclude that basilar and non-basilar pyramidal neurons are clear-cut, different anatomo-functional phenotypes. We propose that, in addition to their role in contrast processing, basilar pyramidal neurons encode sustained global stimuli such as those elicited by large or distant objects while non-basilar pyramidal neurons respond to transient stimuli due to movement of objects with a textured surface.

Novel Functions of Feedback in Electrosensory Processing

Environmental signals act as input and are processed across successive stages in the brain to generate a meaningful behavioral output. However, a ubiquitous observation is that descending feedback projections from more central to more peripheral brain areas vastly outnumber ascending feedforward projections. Such projections generally act to modify how sensory neurons respond to afferent signals. Recent studies in the electrosensory system of weakly electric fish have revealed novel functions for feedback pathways in that their transformation of the afferent input generates neural firing rate responses to sensory signals mediating perception and behavior. In this review, we focus on summarizing these novel and recently uncovered functions and put them into context by describing the more "classical" functions of feedback in the electrosensory system. We further highlight the parallels between the electrosensory system and other systems as well as outline interesting future directions.

Encoding phase spectrum for evaluating 'electric qualia'

The most broadly expressed and studied aspect of sensory transduction is receptor tuning to the power spectral density of the incoming signals. Temporal cues expressed in the phase spectrum are relevant in African and American pulse-emitting electric fish showing electroreceptors sensing the signals carried by the self- and conspecific-generated electric organ discharges. This article concerns the role of electroreceptor phase sensitivity in American pulse Gymnotiformes. These fish show electroreceptors sharply tuned to narrow frequency bands. This led to the common thought that most electrosensory information is contained in the amplitude spectra of the signals. However, behavioral and modeling studies suggest that in their pulses, Gymnotiformes electroreceptors also encode cues embodied in the phase spectrum of natural stimuli. Here, we show that the two main types of tuberous primary afferents of Gymnotus omarorum differentially respond to cues embodied in the amplitude and phase spectra of self-generated electrosensory signals. One afferent type, pulse markers, is mainly driven by the amplitude spectrum, while the other, burst coders, is predominantly sensitive to the phase spectrum. This dual encoding strategy allows the fish to create a sensory manifold where patterns of 'electric color' generated by object impedance and other potential sources of 'colored' images (such as large nearby objects and other electric fish) can be represented.

Spatiotemporal model for depth perception in electric sensing

Electric sensing involves measuring the voltage changes in an actively generated electric field, enabling an environment to be characterized by its electrical properties. It has been applied in a variety of contexts, from geophysics to biomedical imaging. Some species of fish also use an active electric sense to explore their environment in the dark. One of the primary challenges in such electric sensing involves mapping an environment in three-dimensions using voltage measurements that are limited to a two-dimensional sensor array (i.e. a two-dimensional electric image). In some special cases, the distance of simple objects from the sensor array can be estimated by combining properties of the electric image. Here, we describe a novel algorithm for distance estimation based on a single property of the electric image. Our algorithm can be implemented in two simple ways, involving either different electric field strengths or different sensor thresholds, and is robust to changes in object properties and noise.

Neuronal variability and tuning are balanced to optimize naturalistic self-motion coding in primate vestibular pathways

It is commonly assumed that the brain's neural coding strategies are adapted to the statistics of natural stimuli. Specifically, to maximize information transmission, a sensory neuron's tuning function should effectively oppose the decaying stimulus spectral power, such that the neural response is temporally decorrelated (i.e. 'whitened'). However, theory predicts that the structure of neuronal variability also plays an essential role in determining how coding is optimized. Here, we provide experimental evidence supporting this view by recording from neurons in early vestibular pathways during naturalistic self-motion. We found that central vestibular neurons displayed temporally whitened responses that could not be explained by their tuning alone. Rather, computational modeling and analysis revealed that neuronal variability and tuning were matched to effectively complement natural stimulus statistics, thereby achieving temporal decorrelation and optimizing information transmission. Taken together, our findings reveal a novel strategy by which neural variability contributes to optimized processing of naturalistic stimuli.

Population Coding and Correlated Variability in Electrosensory Pathways

The fact that perception and behavior depend on the simultaneous and coordinated activity of neural populations is well established. Understanding encoding through neuronal population activity is however complicated by the statistical dependencies between the activities of neurons, which can be present in terms of both their mean (signal correlations) and their response variability (noise correlations). Here, we review the state of knowledge regarding population coding and the influence of correlated variability in the electrosensory pathways of the weakly electric fish Apteronotus leptorhynchus. We summarize known population coding strategies at the peripheral level, which are largely unaffected by noise correlations. We then move on to the hindbrain, where existing data from the electrosensory lateral line lobe (ELL) shows the presence of noise correlations. We summarize the current knowledge regarding the mechanistic origins of noise correlations and known mechanisms of stimulus dependent correlation shaping in ELL. We finish by considering future directions for understanding population coding in the electrosensory pathways of weakly electric fish, highlighting the benefits of this model system for understanding the origins and impact of noise correlations on population coding.

Optimal dynamic coding by mixed-dimensionality neurons in the head-direction system of bats

Ethologically relevant stimuli are often multidimensional. In many brain systems, neurons with “pure” tuning to one stimulus dimension are found along with “conjunctive” neurons that encode several dimensions, forming an apparently redundant representation. Here we show using theoretical analysis that a mixed-dimensionality code can efficiently represent a stimulus in different behavioral regimes: encoding by conjunctive cells is more robust when the stimulus changes quickly, whereas on long timescales pure cells represent the stimulus more efficiently with fewer neurons. We tested our predictions experimentally in the bat head-direction system and found that many head-direction cells switched their tuning dynamically from pure to conjunctive representation as a function of angular velocity—confirming our theoretical prediction. More broadly, our results suggest that optimal dimensionality depends on population size and on the time available for decoding—which might explain why mixed-dimensionality representations are common in sensory, motor, and higher cognitive systems across species.

Multidimensional stimuli are often represented by neurons encoding only a single dimension and those encoding multiple dimensions. Here, the authors present theoretical and experimental analyses to show that mixed representations are optimal to efficiently encode such stimuli under different behavioral modes.

Weakly electric fish distinguish between envelope stimuli arising from different behavioral contexts

Understanding how sensory information is processed by the brain in order to give rise to behavior remains poorly understood in general. Here, we investigated the behavioral responses of the weakly electric fish Apteronotus albifrons to stimuli arising from different contexts, by measuring changes in the electric organ discharge (EOD) frequency. Specifically, we focused on envelopes, which can arise either because of movement (i.e. motion envelopes) or because of interactions between the electric fields of three of more fish (i.e. social envelopes). Overall, we found that the animal's EOD frequency effectively tracked the detailed time course of both motion and social envelopes. In general, behavioral sensitivity (i.e. gain) decreased while phase lag increased with increasing envelope and carrier frequency. However, changes in gain and phase lag as a function of changes in carrier frequency were more prominent for motion than for social envelopes in general. Importantly, we compared behavioral responses to motion and social envelopes with similar characteristics. Although behavioral sensitivities were similar, we observed an increased response lag for social envelopes, primarily for low carrier frequencies. Thus, our results imply that the organism can, based on behavioral responses, distinguish envelope stimuli resulting from movement from those that instead result from social interactions. We discuss the implications of our results for neural coding of envelopes and propose that behavioral responses to motion and social envelopes are mediated by different neural circuits in the brain.

Differential receptive field organizations give rise to nearly identical neural correlations across three parallel sensory maps in weakly electric fish

Understanding how neural populations encode sensory information thereby leading to perception and behavior (i.e., the neural code) remains an important problem in neuroscience. When investigating the neural code, one must take into account the fact that neural activities are not independent but are actually correlated with one another. Such correlations are seen ubiquitously and have a strong impact on neural coding. Here we investigated how differences in the antagonistic center-surround receptive field (RF) organization across three parallel sensory maps influence correlations between the activities of electrosensory pyramidal neurons. Using a model based on known anatomical differences in receptive field center size and overlap, we initially predicted large differences in correlated activity across the maps. However, in vivo electrophysiological recordings showed that, contrary to modeling predictions, electrosensory pyramidal neurons across all three segments displayed nearly identical correlations. To explain this surprising result, we incorporated the effects of RF surround in our model. By systematically varying both the RF surround gain and size relative to that of the RF center, we found that multiple RF structures gave rise to similar levels of correlation. In particular, incorporating known physiological differences in RF structure between the three maps in our model gave rise to similar levels of correlation. Our results show that RF center overlap alone does not determine correlations which has important implications for understanding how RF structure influences correlated neural activity.

Growing evidence across nervous systems and species shows that the activities of neighboring neurons are not independent but are correlated with one another, which has important implications for neural coding. Such correlations are generally thought to be due to shared input. However, how this shared input is integrated by neurons in order to give rise to correlated activity is not well understood in general. Here we investigated how receptive field structure determines correlations between the activities of electrosensory pyramidal neurons in weakly electric fish. To do so, we used a combination of mathematical modeling of the known antagonistic center-surround RF structure as well as in vivo electrophysiological recordings. Our results show that the amount of receptive field center overlap alone is not sufficient to explain experimentally observed neural correlations in general. This is because our experimental data shows that pyramidal neurons with very different amounts of receptive field center overlap display almost identical correlations between their activities. Further, our modeling shows that both receptive field center and surround play important roles in determining correlated activity, such that very different combinations of relative RF surround strength and size can generate nearly identical correlations between neural activities. We discuss the implications of our results for sensory processing.

Electrosensory neural responses to natural electro-communication stimuli are distributed along a continuum

Neural heterogeneities are seen ubiquitously within the brain and greatly complicate classification efforts. Here we tested whether the responses of an anatomically well-characterized sensory neuron population to natural stimuli could be used for functional classification. To do so, we recorded from pyramidal cells within the electrosensory lateral line lobe (ELL) of the weakly electric fish Apteronotus leptorhynchus in response to natural electro-communication stimuli as these cells can be anatomically classified into six different types. We then used two independent methodologies to functionally classify responses: one relies of reducing the dimensionality of a feature space while the other directly compares the responses themselves. Both methodologies gave rise to qualitatively similar results: while ON and OFF-type cells could easily be distinguished from one another, ELL pyramidal neuron responses are actually distributed along a continuum rather than forming distinct clusters due to heterogeneities. We discuss the implications of our results for neural coding and highlight some potential advantages.

SK channel subtypes enable parallel optimized coding of behaviorally relevant stimulus attributes: A review

Ion channels play essential roles toward determining how neurons respond to sensory input to mediate perception and behavior. Small conductance calcium-activated potassium (SK) channels are found ubiquitously throughout the brain and have been extensively characterized both molecularly and physiologically in terms of structure and function. It is clear that SK channels are key determinants of neural excitability as they mediate important neuronal response properties such as spike frequency adaptation. However, the functional roles of the different known SK channel subtypes are not well understood. Here we review recent evidence from the electrosensory system of weakly electric fish suggesting that the function of different SK channel subtypes is to optimize the processing of independent but behaviorally relevant stimulus attributes. Indeed, natural sensory stimuli frequently consist of a fast time-varying waveform (i.e., the carrier) whose amplitude (i.e., the envelope) varies slowly and independently. We first review evidence showing how somatic SK2 channels mediate tuning and responses to carrier waveforms. We then review evidence showing how dendritic SK1 channels instead determine tuning and optimize responses to envelope waveforms based on their statistics as found in the organism's natural environment in an independent fashion. The high degree of functional homology between SK channels in electric fish and their mammalian orthologs, as well as the many important parallels between the electrosensory system and the mammalian visual, auditory, and vestibular systems, suggest that these functional roles are conserved across systems and species.

Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons

Synchronous activity in populations of neurons potentially encodes special stimulus features. Selective readout of either synchronous or asynchronous activity allows formation of two streams of information processing. Theoretical work predicts that such a synchrony code is a fundamental feature of populations of spiking neurons if they operate in specific noise and stimulus regimes. Here we experimentally test the theoretical predictions by quantifying and comparing neuronal response properties in tuberous and ampullary electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus These related systems show similar levels of synchronous activity, but only in the more irregularly firing tuberous afferents a synchrony code is established, whereas in the more regularly firing ampullary afferents it is not. The mere existence of synchronous activity is thus not sufficient for a synchrony code. Single-cell features such as the irregularity of spiking and the frequency dependence of the neuron's transfer function determine whether synchronous spikes possess a distinct meaning for the encoding of time-dependent signals.

The bioinspiring potential of weakly electric fish

Electric fish are privileged animals for bio-inspiring man-built autonomous systems since they have a multimodal sense that allows underwater navigation, object classification and intraspecific communication. Although there are taxon dependent variations adapted to different environments, this multimodal system can be schematically described as having four main components: active electroreception, passive electroreception, lateral line sense and, proprioception. Amongst these sensory modalities, proprioception and electroreception show 'active' systems that extrct information carried by self generated forms of energy. This ensemble of four sensory modalities is present in African mormyriformes and American gymnotiformes. The convergent evolution of similar imaging, peripheral encoding, and central processing mechanisms suggests that these mechanisms may be the most suitable for dealing with electric images in the context of the other and self generated actions. This review deals with the way in which biological organisms address three of the problems that are faced when designing a bioinspired electroreceptive agent: (a) body shape, material and mobility, (b) peripheral encoding of electric images, and (c) early processing of electrosensory signals. Taking into account biological solutions I propose that the new generation of underwater agents should have electroreceptive arms, use complex peripheral sensors for encoding the images and cerebellum like architecture for image feature extraction and implementing sensory-motor transformations.

Modeling latency code processing in the electric sense: from the biological template to its VLSI implementation

Understanding the coding of sensory information under the temporal constraints of natural behavior is not yet well resolved. There is a growing consensus that spike timing or latency coding can maximally exploit the timing of neural events to make fast computing elements and that such mechanisms are essential to information processing functions in the brain. The electric sense of mormyrid fish provides a convenient biological model where this coding scheme can be studied. The sensory input is a physically ordered spatial pattern of current densities, which is coded in the precise timing of primary afferent spikes. The neural circuits of the processing pathway are well known and the system exhibits the best known illustration of corollary discharge, which provides the reference to decoding the sensory afferent latency pattern. A theoretical model has been constructed from available electrophysiological and neuroanatomical data to integrate the principal traits of the neural processing structure and to study sensory interaction with motor-command-driven corollary discharge signals. This has been used to explore neural coding strategies at successive stages in the network and to examine the simulated network capacity to reproduce output neuron responses. The model shows that the network has the ability to resolve primary afferent spike timing differences in the sub-millisecond range, and that this depends on the coincidence of sensory and corollary discharge-driven gating signals. In the integrative and output stages of the network, corollary discharge sets up a proactive background filter, providing temporally structured excitation and inhibition within the network whose balance is then modulated locally by sensory input. This complements the initial gating mechanism and contributes to amplification of the input pattern of latencies, conferring network hyperacuity. These mechanisms give the system a robust capacity to extract behaviorally meaningful features of the electric image with high sensitivity over a broad working range. Since the network largely depends on spike timing, we finally discuss its suitability for implementation in robotic applications based on neuromorphic hardware.

Enhanced detection performance in electrosense through capacitive sensing

Weakly electric fish emit an AC electric field into the water and use thousands of sensors on the skin to detect field perturbations due to surrounding objects. The fish's active electrosensory system allows them to navigate and hunt, using separate neural pathways and receptors for resistive and capacitive perturbations. We have previously developed a sensing method inspired by the weakly electric fish to detect resistive perturbations and now report on an extension of this system to detect capacitive perturbations as well. In our method, an external object is probed by an AC field over multiple frequencies. We present a quantitative framework that relates the response of a capacitive object at multiple frequencies to the object's composition and internal structure, and we validate this framework with an electrosense robot that implements our capacitive sensing method. We define a metric for comparing the electrosensory range of different underwater electrosense systems. For detecting non-conductive objects, we show that capacitive sensing performs better than resistive sensing by almost an order of magnitude using this measure, while for conductive objects there is a four-fold increase in performance. Capacitive sensing could therefore provide electric fish with extended sensing range for capacitive objects such as prey, and gives artificial electrolocation systems enhanced range for targets that are capacitive.

Temporal decorrelation by SK channels enables efficient neural coding and perception of natural stimuli

It is commonly assumed that neural systems efficiently process natural sensory input. However, the mechanisms by which such efficient processing is achieved, and the consequences for perception and behaviour remain poorly understood. Here we show that small conductance calcium-activated potassium (SK) channels enable efficient neural processing and perception of natural stimuli. Specifically, these channels allow for the high-pass filtering of sensory input, thereby removing temporal correlations or, equivalently, whitening frequency response power. Varying the degree of adaptation through pharmacological manipulation of SK channels reduced efficiency of coding of natural stimuli, which in turn gave rise to predictable changes in behavioural responses that were no longer matched to natural stimulus statistics. Our results thus demonstrate a novel mechanism by which the nervous system can implement efficient processing and perception of natural sensory input that is likely to be shared across systems and species.

Short-term synaptic plasticity across topographic maps in the electrosensory system

The early pathways underlying the active electric sense of the weakly electric fish Apteronotus leptorhynchus involve three parallel processing streams. An array of tuberous electroreceptors distributed over the skin provides inputs to the electrosensory lateral line lobe (ELL), forming the basis for three topographic maps: LS (lateral segment), CLS (centrolateral segment), and CMS (centromedial segment). In addition, each map receives topographically preserved inputs from a direct feedback pathway. How this feedback contributes to the distinct spatiotemporal filtering properties of ELL pyramidal neurons across maps is not clear. We used an in vitro approach to characterize short-term plasticity (STP) in the direct feedback synapses onto pyramidal neurons in each map. Our findings indicated that the dynamics of STP varied across maps in a manner that was consistent with the temporal filtering properties of pyramidal neurons in vivo. Using a modeling approach, we found that the STP of direct feedback synapses in CMS was best described by a simple facilitation-depression model. On the other hand, STP in LS was best described by synaptic facilitation with a use-dependent recovery rate. These results suggest that differential regulation of overlapping STP processes in feedback pathways can contribute to the functional specialization of topographic sensory maps.

Weak signal amplification and detection by higher-order sensory neurons

Sensory systems must extract behaviorally relevant information and therefore often exhibit a very high sensitivity. How the nervous system reaches such high sensitivity levels is an outstanding question in neuroscience. Weakly electric fish (Apteronotus leptorhynchus/albifrons) are an excellent model system to address this question because detailed background knowledge is available regarding their behavioral performance and its underlying neuronal substrate. Apteronotus use their electrosense to detect prey objects. Therefore, they must be able to detect electrical signals as low as 1 μV while using a sensory integration time of <200 ms. How these very weak signals are extracted and amplified by the nervous system is not yet understood. We studied the responses of cells in the early sensory processing areas, namely, the electroreceptor afferents (EAs) and pyramidal cells (PCs) of the electrosensory lobe (ELL), the first-order electrosensory processing area. In agreement with previous work we found that EAs cannot encode very weak signals with a spike count code. However, PCs can encode prey mimic signals by their firing rate, revealing a huge signal amplification between EAs and PCs and also suggesting differences in their stimulus encoding properties. Using a simple leaky integrate-and-fire (LIF) model we predict that the target neurons of PCs in the midbrain torus semicircularis (TS) are able to detect very weak signals. In particular, TS neurons could do so by assuming biologically plausible convergence rates as well as very simple decoding strategies such as temporal integration, threshold crossing, and combining the inputs of PCs.

Balanced ionotropic receptor dynamics support signal estimation via voltage-dependent membrane noise

Encoding behaviorally relevant stimuli in a noisy background is critical for animals to survive in their natural environment. We identify core biophysical and synaptic mechanisms that permit the encoding of low-frequency signals in pyramidal neurons of the weakly electric fish Apteronotus leptorhynchus, an animal that can accurately encode even miniscule amplitude modulations of its self-generated electric field. We demonstrate that slow NMDA receptor (NMDA-R)-mediated excitatory postsynaptic potentials (EPSPs) are able to summate over many interspike intervals (ISIs) of the primary electrosensory afferents (EAs), effectively eliminating the baseline EA ISI correlations from the pyramidal cell input. Together with a dynamic balance of NMDA-R and GABA-A-R currents, this permits stimulus-evoked changes in EA spiking to be transmitted efficiently to target electrosensory lobe (ELL) pyramidal cells, for encoding low-frequency signals. Interestingly, AMPA-R activity is depressed and appears to play a negligible role in the generation of action potentials. Instead, we hypothesize that cell-intrinsic voltage-dependent membrane noise supports the encoding of perithreshold sensory input; this noise drives a significant proportion of pyramidal cell spikes. Together, these mechanisms may be sufficient for the ELL to encode signals near the threshold of behavioral detection.

Cryptic laminar and columnar organization in the dorsolateral pallium of a weakly electric fish

In the weakly electric gymnotiform fish, Apteronotus leptorhynchus, the dorsolateral pallium (DL) receives diencephalic inputs representing electrosensory input utilized for communication and navigation. Cell counts reveal that, similar to thalamocortical projections, many more cells are present in DL than in the diencephalic nucleus that provides it with sensory input. DL is implicated in learning and memory and considered homologous to medial and/or dorsal pallium. The gymnotiform DL has an apparently simple architecture with a random distribution of simple multipolar neurons. We used multiple neurotracer injections in order to study the microcircuitry of DL. Surprisingly, we demonstrated that the intrinsic connectivity of DL is highly organized. It consists of orthogonal laminar and vertical excitatory synaptic connections. The laminar synaptic connections are symmetric sparse, random, and drop off exponentially with distance; they parcellate DL into narrow (60 μm) overlapping cryptic layers. At distances greater than 100 μm, the laminar connections generate a strongly connected directed graph architecture within DL. The vertical connectivity suggests that DL is also organized into cryptic columns; these connections are highly asymmetric, with superficial DL cells preferentially projecting towards deeper cells. Our experimental analyses suggest that the overlapping cryptic columns have a width of 100 μm, in agreement with the minimal distance for strong connectivity. The architecture of DL and the expansive representation of its input, taken together with the strong expression of N-methyl-D-aspartate (NMDA) receptors by its cells, are consistent with theoretical ideas concerning the cortical computations of pattern separation and memory storage via bump attractors.

Neural heterogeneities determine response characteristics to second-, but not first-order stimulus features

Neural heterogeneities are seen ubiquitously, but how they determine neural response properties remains unclear. Here we show that heterogeneities can either strongly, or not at all, influence neural responses to a given stimulus feature. Specifically, we recorded from peripheral electroreceptor neurons, which display strong heterogeneities in their resting discharge activity, in response to naturalistic stimuli consisting of a fast time-varying waveform (i.e., first-order) whose amplitude (i.e., second-order or envelope) varied slowly in the weakly electric fish Apteronotus leptorhynchus. Although electroreceptors displayed relatively homogeneous responses to first-order stimulus features, further analysis revealed two subpopulations with similar sensitivities that were excited or inhibited by increases in the envelope, respectively, for stimuli whose frequency content spanned the natural range. We further found that a linear-nonlinear cascade model incorporating the known linear response characteristics to first-order features and a static nonlinearity accurately reproduced experimentally observed responses to both first- and second-order features for all stimuli tested. Importantly, this model correctly predicted that the response magnitude is independent of either the stimulus waveform's or the envelope's frequency content. Further analysis of our model led to the surprising prediction that the mean discharge activity can be used to determine whether a given neuron is excited or inhibited by increases in the envelope. This prediction was validated by our experimental data. Thus, our results provide key insight as to how neural heterogeneities can determine response characteristics to some, but not other, behaviorally relevant stimulus features.

Decoding stimulus duration from neural responses in the auditory midbrain

Neurons with responses selective for the duration of an auditory stimulus are called duration-tuned neurons (DTNs). Temporal specificity in their spiking suggests that one function of DTNs is to encode stimulus duration; however, the efficacy of duration encoding by DTNs has yet to be investigated. Herein, we characterize the information content of individual cells and a population of DTNs from the mammalian inferior colliculus (IC) by measuring the stimulus-specific information (SSI) and estimated Fisher information (FI) of spike count responses. We found that SSI was typically greatest for those stimulus durations that evoked maximum spike counts, defined as best duration (BD) stimuli, and that FI was maximal for stimulus durations off BD where sensitivity to a change in duration was greatest. Using population data, we demonstrate that a maximum likelihood estimator (MLE) can accurately decode stimulus duration from evoked spike counts. We also simulated a two-alternative forced choice task by having MLE models decide whether two durations were the same or different. With this task we measured the just-noticeable difference threshold for stimulus duration and calculated the corresponding Weber fractions across the stimulus domain. Altogether, these results demonstrate that the spiking responses of DTNs from the mammalian IC contain sufficient information for the CNS to encode, decode, and discriminate behaviorally relevant auditory signal durations.

The slow pathway in the electrosensory lobe of Gymnotus omarorum: field potentials and unitary activity

This is a first communication on the self-activation pattern of the electrosensory lobe in the pulse weakly electric fish Gymnotus omarorum. Field potentials in response to the fish's own electric organ discharge (EOD) were recorded along vertical tracks (50μm step) and on a transversal lattice array across the electrosensory lobe (resolution 50μm×100μm). The unitary activity of 82 neurons was recorded in the same experiments. Field potential analysis indicates that the slow electrosensory path shows a characteristic post-EOD pattern of activity marked by three main events: (i) a small and early component at about 7ms, (ii) an intermediate peak about 13ms and (iii) a late broad component peaking after 20ms. Unit firing rate showed a wide range of latencies between 3 and 30ms and a variable number of spikes (median 0.28units/EOD). Conditional probability analysis showed monomodal and multimodal post-EOD histograms, with the peaks of unit activity histograms often matching the timing of the main components of the field potentials. Monomodal responses were sub-classified as phase locked monomodal (variance smaller than 1ms), early monomodal (intermediate variance, often firing in doublets, peaking range 10-17ms) and late monomodal (large variance, often firing two spikes separated about 10ms, peaking beyond 17ms). The responses of multimodal units showed that their firing probability was either enhanced, or depressed just after the EOD. In this last (depressed) subtype of unit the probability stepped down just after the EOD. Early inhibition and the presence of early phase locked units suggest that the observed pattern may be influenced by a fast feed forward inhibition. We conclude that the ELL in pulse gymnotiformes is activated in a complex sequence of events that reflects the ELL network connectivity.

Motion processing across multiple topographic maps in the electrosensory system

Animals can efficiently process sensory stimuli whose attributes vary over orders of magnitude by devoting specific neural pathways to process specific features in parallel. Weakly electric fish offer an attractive model system as electrosensory pyramidal neurons responding to amplitude modulations of their self‐generated electric field are organized into three parallel maps of the body surface. While previous studies have shown that these fish use parallel pathways to process stationary stimuli, whether a similar strategy is used to process motion stimuli remains unknown to this day. We recorded from electrosensory pyramidal neurons in the weakly electric fish Apteronotus leptorhynchus across parallel maps of the body surface (centromedial, centrolateral, and lateral) in response to objects moving at velocities spanning the natural range. Contrary to previous observations made with stationary stimuli, we found that all cells responded in a similar fashion to moving objects. Indeed, all cells showed a stronger directionally nonselective response when the object moved at a larger velocity. In order to explain these results, we built a mathematical model incorporating the known antagonistic center–surround receptive field organization of these neurons. We found that this simple model could quantitatively account for our experimentally observed differences seen across E and I‐type cells across all three maps. Our results thus provide strong evidence against the hypothesis that weakly electric fish use parallel neural pathways to process motion stimuli and we discuss their implications for sensory processing in general.

Neuromodulation of early electrosensory processing in gymnotiform weakly electric fish

Sensory neurons continually adapt their processing properties in response to changes in the sensory environment or the brain's internal state. Neuromodulators are thought to mediate such adaptation through a variety of receptors and their action has been implicated in processes such as attention, learning and memory, aggression, reproductive behaviour and state-dependent mechanisms. Here, we review recent work on neuromodulation of electrosensory processing by acetylcholine and serotonin in the weakly electric fish Apteronotus leptorhynchus. Specifically, our review focuses on how experimental application of these neuromodulators alters excitability and responses to sensory input of pyramidal cells within the hindbrain electrosensory lateral line lobe. We then discuss current hypotheses on the functional roles of these two neuromodulatory pathways in regulating electrosensory processing at the organismal level and the need for identifying the natural behavioural conditions that activate these pathways.

Dendritic SK channels convert NMDA-R-dependent LTD to burst timing-dependent plasticity

Feedback and descending projections from higher to lower brain centers play a prominent role in all vertebrate sensory systems. Feedback might be optimized for the specific sensory processing tasks in their target brain centers, but it has been difficult to connect the properties of feedback synapses to sensory tasks. Here, we use the electrosensory system of a gymnotiform fish ( Apteronotus leptorhynchus) to address this problem. Cerebellar feedback to pyramidal cells in the first central electrosensory processing region, the electrosensory lateral line lobe (ELL), is critical for canceling spatially and temporally redundant electrosensory input. The ELL contains four electrosensory maps, and we have previously analyzed the synaptic and network bases of the redundancy reduction mechanism in a map (centrolateral segment; CLS) believed to guide electrolocation behavior. In the CLS, only long-term depression was induced by pairing feedback presynaptic and pyramidal cell postsynaptic bursts. In this paper, we turn to an ELL map (lateral segment; LS) known to encode electrocommunication signals. We find remarkable differences in synaptic plasticity of the morphologically identical cerebellar feedback input to the LS. In the LS, pyramidal cell SK channels permit long-term potentiation (LTP) of feedback synapses when pre- and postsynaptic bursts occur at the same time. We hypothesize that LTP in this map is required for enhancing the encoding of weak electrocommunication signals. We conclude that feedback inputs that appear morphologically identical in sensory maps dedicated to different tasks, nevertheless display different synaptic plasticity rules contributing to differential sensory processing in these maps.

Neural maps in the electrosensory system of weakly electric fish

The active electrosense of weakly electric fish is evolutionarily and developmentally related to passive electrosensation and the lateral line system. It shows the most highly differentiated topographic maps of the receptor array of all these senses. It is organized into three maps in the hindbrain that are, in turn, composed of columns, each consisting of six pyramidal cell classes. The cells in each column have different spatiotemporal processing properties yielding a total of 18 topographic representations of the body surface. The differential filtering by the hindbrain maps is used by superimposed maps in the multi-layered midbrain electrosensory region to extract specific stimulus features related to communication and foraging. At levels beyond the midbrain, topographic mapping of the body surface appears to be lost.

Sensory flow shaped by active sensing: sensorimotor strategies in electric fish

Goal-directed behavior in most cases is composed of a sequential order of elementary motor patterns shaped by sensorimotor contingencies. The sensory information acquired thus is structured in both space and time. Here we review the role of motion during the generation of sensory flow focusing on how animals actively shape information by behavioral strategies. We use the well-studied examples of vision in insects and echolocation in bats to describe commonalities of sensory-related behavioral strategies across sensory systems, and evaluate what is currently known about comparable active sensing strategies in electroreception of electric fish. In this sensory system the sensors are dispersed across the animal's body and the carrier source emitting energy used for sensing, the electric organ, is moved while the animal moves. Thus ego-motions strongly influence sensory dynamics. We present, for the first time, data of electric flow during natural probing behavior in Gnathonemus petersii (Mormyridae), which provide evidence for this influence. These data reveal a complex interdependency between the physical input to the receptors and the animal's movements, posture and objects in its environment. Although research on spatiotemporal dynamics in electrolocation is still in its infancy, the emerging field of dynamical sensory systems analysis in electric fish is a promising approach to the study of the link between movement and acquisition of sensory information.

Development of a method to present wide-view visual stimuli in MRI for peripheral visual studies

We developed a novel wide-view visual presentation system for fMRI studies. Computer-generated images were projected onto a hemispheric, translucent screen inside the MRI bore and were then back-projected onto a 52mm diameter screen. To achieve a wide field view, a spherical screen with a curvature radius of 30mm was placed 30mm away from the subjects' eyes. The subjects wore contact lenses that enabled them to focus on the screen, and the resulting visual field reached 120°. To evaluate the clarity and quality of the MRI images, a signal-to-noise ratio valuation experiment was performed. In addition, we successfully applied this visual presentation system to studies of visual retinotopic mapping and object perception neural function in the peripheral visual field. Our study demonstrated that the system is compatible with the MRI environment. Based on the wide-field mapping results, this system was more effective at mapping a checkerboard stimuli in V1-V3 from the central to peripheral visual fields. In higher-level visual areas, we successfully located several classical category-selective areas, including the face-selective area (FFA), occipital face area (OFA), house-selective area (PPA), transverse occipital sulcus (TOS), lateral occipital complex (LOC) and posterior fusiform area (pFs). In these areas, we found that the response amplitudes exhibited different decreasing trends with increasing eccentricity. In conclusion, we developed a simple, effective method for presenting wide-view visual stimuli within the MRI environment that can be applied to many kinds of fMRI studies of peripheral vision.

Active sensing via movement shapes spatiotemporal patterns of sensory feedback

Previous work has shown that animals alter their locomotor behavior to increase sensing volumes. However, an animal's own movement also determines the spatial and temporal dynamics of sensory feedback. Because each sensory modality has unique spatiotemporal properties, movement has differential and potentially independent effects on each sensory system. Here we show that weakly electric fish dramatically adjust their locomotor behavior in relation to changes of modality-specific information in a task in which increasing sensory volume is irrelevant. We varied sensory information during a refuge-tracking task by changing illumination (vision) and conductivity (electroreception). The gain between refuge movement stimuli and fish tracking responses was functionally identical across all sensory conditions. However, there was a significant increase in the tracking error in the dark (no visual cues). This was a result of spontaneous whole-body oscillations (0.1 to 1 Hz) produced by the fish. These movements were costly: in the dark, fish swam over three times further when tracking and produced more net positive mechanical work. The magnitudes of these oscillations increased as electrosensory salience was degraded via increases in conductivity. In addition, tail bending (1.5 to 2.35 Hz), which has been reported to enhance electrosensory perception, occurred only during trials in the dark. These data show that both categories of movements - whole-body oscillations and tail bends - actively shape the spatiotemporal dynamics of electrosensory feedback.

Cellular and circuit properties supporting different sensory coding strategies in electric fish and other systems

Neural codes often seem tailored to the type of information they must carry. Here we contrast the encoding strategies for two different communication signals in electric fish and describe the underlying cellular and network properties that implement them. We compare an aggressive signal that needs to be quickly detected, to a courtship signal whose quality needs to be evaluated. The aggressive signal is encoded by synchronized bursts and a predictive feedback input is crucial in separating background noise from the communication signal. The courtship signal is accurately encoded through a heterogenous population response allowing the discrimination of signal differences. Most importantly we show that the same strategies are used in other systems arguing that they evolved similar solutions because they faced similar tasks.

Preparing for the unpredictable: adaptive feedback enhances the response to unexpected communication signals

To interact with the environment efficiently, the nervous system must generate expectations about redundant sensory signals and detect unexpected ones. Neural circuits can, for example, compare a prediction of the sensory signal that was generated by the nervous system with the incoming sensory input, to generate a response selective to novel stimuli. In the first-order electrosensory neurons of a gymnotiform electric fish, a negative image of low-frequency redundant communication signals is subtracted from the neural response via feedback, allowing unpredictable signals to be extracted. Here we show that the cancelling feedback not only suppresses the predictable signal but also actively enhances the response to the unpredictable communication signal. A transient mismatch between the predictive feedback and incoming sensory input causes both to be positive: the soma is suddenly depolarized by the unpredictable input, whereas the neuron's apical dendrites remain depolarized by the lagging cancelling feedback. The apical dendrites allow the backpropagation of somatic spikes. We show that backpropagation is enhanced when the dendrites are depolarized, causing the unpredictable excitatory input to evoke spike bursts. As a consequence, the feedback driven by a predictable low-frequency signal not only suppresses the response to a redundant stimulus but also induces a bursting response triggered by unpredictable communication signals.

Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish

While peripheral sensory neurons respond to natural stimuli with a broad range of spatiotemporal frequencies, central neurons instead respond sparsely to specific features in general. The nonlinear transformations leading to this emergent selectivity are not well understood. Here we characterized how the neural representation of stimuli changes across successive brain areas, using the electrosensory system of weakly electric fish as a model system. We found that midbrain torus semicircularis (TS) neurons were on average more selective in their responses than hindbrain electrosensory lateral line lobe (ELL) neurons. Further analysis revealed two categories of TS neurons: dense coding TS neurons that were ELL-like and sparse coding TS neurons that displayed selective responses. These neurons in general responded to preferred stimuli with few spikes and were mostly silent for other stimuli. We further investigated whether information about stimulus attributes was contained in the activities of ELL and TS neurons. To do so, we used a spike train metric to quantify how well stimuli could be discriminated based on spiking responses. We found that sparse coding TS neurons performed poorly even when their activities were combined compared with ELL and dense coding TS neurons. In contrast, combining the activities of as few as 12 dense coding TS neurons could lead to optimal discrimination. On the other hand, sparse coding TS neurons were better detectors of whether their preferred stimulus occurred compared with either dense coding TS or ELL neurons. Our results therefore suggest that the TS implements parallel detection and estimation of sensory input.

Efficient computation via sparse coding in electrosensory neural networks

The electric sense combines spatial aspects of vision and touch with temporal features of audition. Its accessible neural architecture shares similarities with mammalian sensory systems and allows for recordings from successive brain areas to test hypotheses about neural coding. Further, electrosensory stimuli encountered during prey capture, navigation, and communication, can be readily synthesized in the laboratory. These features enable analyses of the neural circuitry that reveal general principles of encoding and decoding, such as segregation of information into separate streams and neural response sparsification. A systems level understanding arises via linkage between cellular differentiation and network architecture, revealed by in vitro and in vivo analyses, while computational modeling reveals how single cell dynamics and connectivity shape the sparsification process.

Inhibition of SK and M channel-mediated currents by 5-HT enables parallel processing by bursts and isolated spikes

Although serotonergic innervation of sensory brain areas is ubiquitous, its effects on sensory information processing remain poorly understood. We investigated these effects in pyramidal neurons within the electrosensory lateral line lobe (ELL) of weakly electric fish. Surprisingly, we found that 5-HT is present at different levels across the different ELL maps; the presence of 5-HT fibers was highest in the map that processes intraspecies communication signals. Electrophysiological recordings revealed that 5-HT increased excitability and burst firing through a decreased medium afterhyperpolarization resulting from reduced small-conductance calcium-activated (SK) currents as well as currents mediated by an M-type potassium channel. We next investigated how 5-HT alters responses to sensory input. 5-HT application decreased the rheobase current, increased the gain, and decreased first spike latency. Moreover, it reduced discriminability between different stimuli, as quantified by the mutual information rate. We hypothesized that 5-HT shifts pyramidal neurons into a burst-firing mode where bursts, when considered as events, can detect the presence of particular stimulus features. We verified this hypothesis using signal detection theory. Our results indeed show that serotonin-induced bursts of action potentials, when considered as events, could detect specific stimulus features that were distinct from those detected by isolated spikes. Moreover, we show the novel result that isolated spikes transmit more information after 5-HT application. Our results suggest a novel function for 5-HT in that it enables differential processing by action potential patterns in response to current injection.

Neural heterogeneity and efficient population codes for communication signals

Efficient sensory coding implies that populations of neurons should represent information-rich aspects of a signal with little redundancy. Recent studies have shown that neural heterogeneity in higher brain areas enhances the efficiency of encoding by reducing redundancy across the population. Here, we study how neural heterogeneity in the early stages of sensory processing influences the efficiency of population codes. Through the analysis of in vivo recordings, we contrast the encoding of two types of communication signals of electric fishes in the most peripheral sensory area of the CNS, the electrosensory lateral line lobe (ELL). We show that communication signals used during courtship (big chirps) and during aggressive encounters (small chirps) are encoded by different populations of ELL pyramidal cells, namely I-cells and E-cells, respectively. Most importantly, we show that the encoding strategy differs for the two signals and we argue that these differences allow these cell types to encode specifically information-rich features of the signals. Small chirps are detected, and their timing is accurately signaled through stereotyped spike bursts, whereas the shape of big chirps is accurately represented by variable increases in firing rate. Furthermore, we show that the heterogeneity across I-cells enhances the efficiency of the population code and thus permits the accurate discrimination of different quality courtship signals. Our study shows the importance of neural heterogeneity early in a sensory system and that it initiates the sparsification of sensory representation thereby contributing to the efficiency of the neural code.

3-Dimensional Scene Perception during Active Electrolocation in a Weakly Electric Pulse Fish

Weakly electric fish use active electrolocation for object detection and orientation in their environment even in complete darkness. The African mormyrid Gnathonemus petersii can detect object parameters, such as material, size, shape, and distance. Here, we tested whether individuals of this species can learn to identify 3-dimensional objects independently of the training conditions and independently of the object's position in space (rotation-invariance; size-constancy). Individual G. petersii were trained in a two-alternative forced-choice procedure to electrically discriminate between a 3-dimensional object (S+) and several alternative objects (S−). Fish were then tested whether they could identify the S+ among novel objects and whether single components of S+ were sufficient for recognition. Size-constancy was investigated by presenting the S+ together with a larger version at different distances. Rotation-invariance was tested by rotating S+ and/or S− in 3D. Our results show that electrolocating G. petersii could (1) recognize an object independently of the S− used during training. When only single components of a complex S+ were offered, recognition of S+ was more or less affected depending on which part was used. (2) Object-size was detected independently of object distance, i.e. fish showed size-constancy. (3) The majority of the fishes tested recognized their S+ even if it was rotated in space, i.e. these fishes showed rotation-invariance. (4) Object recognition was restricted to the near field around the fish and failed when objects were moved more than about 4 cm away from the animals. Our results indicate that even in complete darkness our G. petersii were capable of complex 3-dimensional scene perception using active electrolocation.

Kinetics of fast short-term depression are matched to spike train statistics to reduce noise

Short-term depression (STD) is observed at many synapses of the CNS and is important for diverse computations. We have discovered a form of fast STD (FSTD) in the synaptic responses of pyramidal cells evoked by stimulation of their electrosensory afferent fibers (P-units). The dynamics of the FSTD are matched to the mean and variance of natural P-unit discharge. FSTD exhibits switch-like behavior in that it is immediately activated with stimulus intervals near the mean interspike interval (ISI) of P-units (approximately 5 ms) and recovers immediately after stimulation with the slightly longer intervals (>7.5 ms) that also occur during P-unit natural and evoked discharge patterns. Remarkably, the magnitude of evoked excitatory postsynaptic potentials appear to depend only on the duration of the previous ISI. Our theoretical analysis suggests that FSTD can serve as a mechanism for noise reduction. Because the kinetics of depression are as fast as the natural spike statistics, this role is distinct from previously ascribed functional roles of STD in gain modulation, synchrony detection or as a temporal filter.

Neural heterogeneities and stimulus properties affect burst coding in vivo

Many neurons tend to fire clusters of action potentials called bursts followed by quiescence in response to sensory input. While the mechanisms that underlie burst firing are generally well understood in vitro, the functional role of these bursts in generating behavioral responses to sensory input in vivo are less clear. Pyramidal cells within the electrosensory lateral line lobe (ELL) of weakly electric fish offer an attractive model system for studying the coding properties of burst firing, because the anatomy and physiology of the electrosensory circuitry are well understood, and the burst mechanism of ELL pyramidal cells has been thoroughly characterized in vitro. We investigated the coding properties of bursts generated by these cells in vivo in response to mimics of behaviorally relevant sensory input. We found that heterogeneities within the pyramidal cell population had quantitative but not qualitative effects on burst coding for the low frequency components of broadband time varying input. Moreover, spatially localized stimuli mimicking, for example, prey tended to elicit more bursts than spatially global stimuli mimicking conspecific-related stimuli. We also found small but significant correlations between burst attributes such as the number of spikes per burst or the interspike interval during the burst and stimulus attributes such as stimulus amplitude or slope. These correlations were much weaker in magnitude than those observed in vitro. More surprisingly, our results show that correlations between burst and stimulus attributes actually decreased in magnitude when we used low frequency stimuli that are expected to promote burst firing. We propose that this discrepancy is attributable to differences between ELL pyramidal cell burst firing under in vivo and in vitro conditions.