Distribution of Kv1-like potassium channels in the electromotor and electrosensory systems of the weakly electric fish Apteronotus leptorhynchus

The electromotor and electrosensory systems of the weakly electric fish Apteronotus leptorhynchus are model systems for studying mechanisms of high-frequency motor pattern generation and sensory processing. Voltage-dependent ionic currents, including low-threshold potassium currents, influence excitability of neurons in these circuits and thereby regulate motor output and sensory filtering. Although Kv1-like potassium channels are likely to carry low-threshold potassium currents in electromotor and electrosensory neurons, the distribution of Kv1 alpha subunits in A. leptorhynchus is unknown. In this study, we used immunohistochemistry with six different antibodies raised against specific mammalian Kv1 alpha subunits (Kv1.1-Kv1.6) to characterize the distribution of Kv1-like channels in electromotor and electrosensory structures. Each Kv1 antibody labeled a distinct subset of neurons, fibers, and/or dendrites in electromotor and electrosensory nuclei. Kv1-like immunoreactivity in the electrosensory lateral line lobe (ELL) and pacemaker nucleus are particularly relevant in light of previous studies suggesting that potassium currents carried by Kv1 channels regulate neuronal excitability in these regions. Immunoreactivity of pyramidal cells in the ELL with several Kv1 antibodies is consistent with Kv1 channels carrying low-threshold outward currents that regulate spike waveform in these cells (Fernandez et al., J Neurosci 2005;25:363-371). Similarly, Kv1-like immunoreactivity in the pacemaker nucleus is consistent with a role of Kv1 channels in spontaneous high-frequency firing in pacemaker neurons. Robust Kv1-like immunoreactivity in several other structures, including the dorsal torus semicircularis, tuberous electroreceptors, and the electric organ, indicates that Kv1 channels are broadly expressed and are likely to contribute significantly to generating the electric organ discharge and processing electrosensory inputs.     

Synchronization and sensitivity enhancement of the Hodgkin-Huxley neurons due to inhibitory inputs

Recent experimental results imply that inhibitory postsynaptic potentials can play a functional role in realizing synchronization of neuronal firing in the brain. In order to examine the relation between inhibition and synchronous firing of neurons theoretically, we analyze possible effects of synchronization and sensitivity enhancement caused by inhibitory inputs to neurons with a biologically realistic model of the Hodgkin-Huxley equations. The result shows that, after an inhibitory spike, the firing probability of a single postsynaptic neuron exposed to random excitatory background activity oscillates with time. The oscillation of the firing probability can be related to synchronous firing of neurons receiving an inhibitory spike simultaneously. Further, we show that when an inhibitory spike input precedes an excitatory spike input, the presence of such preceding inhibition raises the firing probability peak of the neuron after the excitatory input. The result indicates that an inhibitory spike input can enhance the sensitivity of the postsynaptic neuron to the following excitatory spike input. Two neural network models based on these effects on postsynaptic neurons caused by inhibitory inputs are proposed to demonstrate possible mechanisms of detecting particular spatiotemporal spike patterns. Received: 15 April 1999 /Accepted in revised form: 25 November 1999     

Time disparity sensitive behavior and its neural substrates of a pulse-type gymnotiform electric fish, Brachyhypopomus gauderio

Roles of the time coding electrosensory system in the novelty responses of a pulse-type gymnotiform electric fish, Brachyhypopomus, were examined behaviorally, physiologically, and anatomically. Brachyhypopomus responded with the novelty responses to small changes (100 μs) in time difference between electrosensory stimulus pulses applied to different parts of the body, as long as these pulses were given within a time period of ~500 μs. Physiological recording revealed neurons in the hindbrain and midbrain that fire action potentials time-locked to stimulus pulses with short latency (500–900 μs). These time-locked neurons, along with other types of neurons, were labeled with intracellular and extracellular marker injection techniques. Light and electron microscopy of the labeled materials revealed neural connectivity within the time coding system. Two types of time-locked neurons, the pear-shaped cells and the large cells converge onto the small cells in a hypertrophied structure, the mesencephalic magnocellular nucleus. The small cells receive a calyx synapse from a large cell at their somata and an input from a pear-shaped cell at the tip of their dendrites via synaptic islands. The small cells project to the torus semicircularis. We hypothesized that the time-locked neural signals conveyed by the pear-shaped cells and the large cells are decoded by the small cells for detection of time shifts occurring across body areas.     

Design principles of sensory processing in cerebellum-like structures

Cerebellum-like structures are compared for two sensory systems: electrosensory and auditory. The electrosensory lateral line lobe of mormyrid electric fish is reviewed and the neural representation of electrosensory objects in this structure is modeled and discussed. The dorsal cochlear nucleus in the auditory brainstem of mammals is reviewed and new data are presented that characterize the responses of neurons in this structure in the mouse. Similarities between the electrosensory and auditory cerebellum-like structures are shown, in particular adaptive processes that may reduce responses to predictable stimuli. We suggest that the differences in the types of sensory objects may drive the differences in the anatomical and physiological characteristics of these two cerebellum-like structures.     

Role of active dendritic conductances in subthreshold input integration

Dendrites of many types of neurons contain voltage-dependent conductances that are active at subthreshold membrane potentials. To understand the computations neurons perform it is key to understand the role of active dendrites in the subthreshold processing of synaptic inputs. We examine systematically how active dendritic conductances affect the time course of postsynaptic potentials propagating along dendrites, and how they affect the interaction between such signals. Voltage-dependent currents can be classified into two types that have qualitatively different effects on subthreshold input responses: regenerative dendritic currents boost and broaden EPSPs, while restorative currents attenuate and narrow EPSPs. Importantly, the effects of active dendritic currents on EPSP shape increase as the EPSP travels along the dendrite. The effectiveness of active currents in modulating the EPSP shape is determined by their activation time constant: the faster it is, the stronger the effect on EPSP amplitude, while the largest effects on EPSP width occur when it is comparable to the membrane time constant. We finally demonstrate that the two current types can differentially improve precision and robustness of neural computations: restorative currents enhance coincidence detection of dendritic inputs, whereas direction selectivity to sequences of dendritic inputs is enhanced by regenerative dendritic currents.     

Binocular visual processing in the owl's telencephalon.

Single neurons recorded from the owl's visual Wulst are surprisingly similar to those found in mammalian striate cortex. The receptive fields of Wulst neurons are elaborated, in an apparently hierarchical fashion, from those of their monocular, concentrically organized inputs to produce binocular interneurons with increasingly sophisticated requirements for stimulus orientation, movement and binocular disparity. Output neurons located in the superficial laminae of the Wulst are the most sophisticated of all, with absolute requirements for a combination of stimuli, which include binocular presentation at a particular horizontal binocular disparity, and with no response unless all of the stimulus conditions are satisfied simultaneously. Such neurons have the properties required for 'global stereopsis', including a receptive field size many times larger than their optimal stimulus, which is more closely matched to the receptive fields of the simpler, disparity-selective interneurons. These marked similarities in functional organization between the avian and mammalian systems exist in spite of a number of structural differences which reflect their separate evoluntionary origins. Discussion therefore includes the possibility that there may exist for nervous systems only a very small number of possible solutions, perhaps a unique one, to the problem of stereopsis.     

The Spatial Structure of Stimuli Shapes the Timescale of Correlations in Population Spiking Activity

Throughout the central nervous system, the timescale over which pairs of neural spike trains are correlated is shaped by stimulus structure and behavioral context. Such shaping is thought to underlie important changes in the neural code, but the neural circuitry responsible is largely unknown. In this study, we investigate a stimulus-induced shaping of pairwise spike train correlations in the electrosensory system of weakly electric fish. Simultaneous single unit recordings of principal electrosensory cells show that an increase in the spatial extent of stimuli increases correlations at short () timescales while simultaneously reducing correlations at long () timescales. A spiking network model of the first two stages of electrosensory processing replicates this correlation shaping, under the assumptions that spatially broad stimuli both saturate feedforward afferent input and recruit an open-loop inhibitory feedback pathway. Our model predictions are experimentally verified using both the natural heterogeneity of the electrosensory system and pharmacological blockade of descending feedback projections. For weak stimuli, linear response analysis of the spiking network shows that the reduction of long timescale correlation for spatially broad stimuli is similar to correlation cancellation mechanisms previously suggested to be operative in mammalian cortex. The mechanism for correlation shaping supports population-level filtering of irrelevant distractor stimuli, thereby enhancing the population response to relevant prey and conspecific communication inputs.     

In vitro studies of closed-loop feedback and electrosensory processing in Apteronotus leptorhynchus

Electrosensory systems comprise extensive feedback pathways. It is also well known that these pathways exhibit synaptic plasticity on a wide-range of time scales. Recent in vitro brain slice studies have characterized synaptic plasticity in the two main feedback pathways to the electrosensory lateral line lobe (ELL), a primary electrosensory nucleus in Apteronotus leptorhynchus. Currently-used slice preparations, involving networks in open-loop conditions, allow feedback inputs to be studied in isolation, a critical step in determining their synaptic properties. However, to fully understand electrosensory processing, we must understand how dynamic feedback modulates neuronal responses under closed-loop conditions. To bridge the gap between current in vitro approaches and more complex in vivo work, we present two new in vitro approaches for studying the roles of closed-loop feedback in electrosensory processing. The first involves a hybrid-network approach using dynamic clamp, and the second involves a new slice preparation that preserves one of the feedback pathways to ELL in a closed-loop condition.     

Detection of multiple stimulus features forces a trade-off in the pyramidal cell network of a gymnotiform electric fish's electrosensory lateral line lobe

Modification of an existing neural structure to support a second function will produce a trade-off between the two functions if they are in some way incompatible. The trade-off between two such sensory functions is modeled here in pyramidal neurons of the gymnotiform electric fish's medullar electrosensory lateral line lobe (ELL). These neurons detect two electric stimulus features produced when a nearby object interferes with the fish's autogenous electric field: (1) amplitude modulation across a cell's entire receptive field and (2) amplitude variation within a cell's receptive field produced by an object's edge. A model of sensory integration shows that detection of amplitude modulation and enhancement of spatial contrast involve an inherent mechanistic trade-off and that the severity of the trade-off depends on the particular algorithm of sensory integration. Electrophysiology data indicate that of the two algorithms for sensory integration modeled here for the gymnotiform fish Brachyhypopomus pinnicaudatus, the algorithm with the better trade-off function is used. Further, the intrinsic trade-off within single cells has been surmounted by the replication of ELL into multiple electrosensory map segments, each specialized to emphasize different sensory features. Accepted: 14 June 1997     

Stereoscopic Vision in the Absence of the Lateral Occipital Cortex

Both dorsal and ventral cortical visual streams contain neurons sensitive to binocular disparities, but the two streams may underlie different aspects of stereoscopic vision. Here we investigate stereopsis in the neurological patient D.F., whose ventral stream, specifically lateral occipital cortex, has been damaged bilaterally, causing profound visual form agnosia. Despite her severe damage to cortical visual areas, we report that DF''s stereo vision is strikingly unimpaired. She is better than many control observers at using binocular disparity to judge whether an isolated object appears near or far, and to resolve ambiguous structure-from-motion. DF is, however, poor at using relative disparity between features at different locations across the visual field. This may stem from a difficulty in identifying the surface boundaries where relative disparity is available. We suggest that the ventral processing stream may play a critical role in enabling healthy observers to extract fine depth information from relative disparities within one surface or between surfaces located in different parts of the visual field.     

Modelling Feedback Excitation,Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity

What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition.     

Exclusive-OR function of single arborized neuron

We designed four arborized neurons which are able to evaluate the exclusive-or (XOR) function from two inputs. The input neurons form exclusively excitatory synapses on a dendritic tree which is a patchwork of passive (ohmic) and active cable segments. The active segments are described by the Hodgkin-Huxley model. The dynamics of the neurons and their output are obtained by numerical integration of the cable equation. In neurons 1 and 2 the XOR function is based on the annihilation of colliding action potentials. In neuron No. 3 the design takes advantage of the refractory period of action potentials. In neuron No. 4 voltage inversion is used as it occurs for inactivated sodium conductance in the Hodgkin-Huxley model. In all cases the XOR function depends critically on an appropriate timing of the input signals and on delays of the voltage transients in different branches of the dendrite.     

Pre-attentive segmentation and correspondence in stereo

Traditional stereo grouping models have focused on the problem of stereo correspondence between monocular inputs. Recent physiological data revealed that the disparity selective V2 cells increase their responses when (random-dot stereograms) stimuli within their receptive fields are at or near the boundary of a depth surface. Such highlights to depth (non-luminance) edges are seemingly not computationally required for the correspondence problem. Computationally, these highlights make the boundaries of a depth surface more salient, serving pre-attentive segmentation (between depth planes) and attracting visual attention. In special cases, they enable the psychophysically observed perceptual pop-out of a target from a background of visually identical distractors at a different depth. To achieve the highlights, mutual inhibition between disparity selective cells that are tuned to the same or similar depths is required. However, such mutual inhibition would impede the computation for the correspondence problem, which requires mutual excitation between the same cells. In this work, I introduce a computational model that, I believe, is the first to address both stereo correspondence and pre-attentive stereo segmentation. The computational mechanisms in the model are based on intracortical interactions in V2. I will demonstrate that the model captures the following physiological and psychophysical phenomena: (i) depth-edge highlighting; (ii) disparity capture; (iii) pop-out; and (iv) transparency.     

Inhibitory synchrony as a mechanism for attentional gain modulation

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing rate of the neuron can change and there can be an increase in the coherence between spikes and the local field potential (LFP) in the gamma-frequency range (30-50 Hz). The hypothesis explored here is that these observed effects of attention could be a consequence of changes in the synchrony of local interneuron networks. We performed computer simulations of a Hodgkin-Huxley type neuron driven by a constant depolarizing current, I, representing visual stimulation and a modulatory inhibitory input representing the effects of attention via local interneuron networks. We observed that the neuron's firing rate and the coherence of its output spike train with the synaptic inputs was modulated by the degree of synchrony of the inhibitory inputs. When inhibitory synchrony increased, the coherence of spiking model neurons with the synaptic input increased, but the firing rate either increased or remained the same. The mean number of synchronous inhibitory inputs was a key determinant of the shape of the firing rate versus current (f-I) curves. For a large number of inhibitory inputs (approximately 50), the f-I curve saturated for large I and an increase in input synchrony resulted in a shift of sensitivity-the model neuron responded to weaker inputs I. For a small number (approximately 10), the f-I curves were non-saturating and an increase in input synchrony led to an increase in the gain of the response-the firing rate in response to the same input was multiplied by an approximately constant factor. The firing rate modulation with inhibitory synchrony was highest when the input network oscillated in the gamma frequency range. Thus, the observed changes in firing rate and coherence of neurons in the visual cortex could be controlled by top-down inputs that regulated the coherence in the activity of a local inhibitory network discharging at gamma frequencies.     

Neural control of interlimb oscillations

How do humans and other animals accomplish coordinated movements? How are novel combinations of limb joints rapidly assembled into new behavioral units that move together in in-phase or anti-phase movement patterns during complex movement tasks? A neural central pattern generator (CPG) model simulates data from human bimanual coordination tasks. As in the data, anti-phase oscillations at low frequencies switch to in-phase oscillations at high frequencies, in-phase oscillations occur at both low and high frequencies, phase fluctuations occur at the anti-phase in-phase transition, a “seagull effect” of larger errors occurs at intermediate phases, and oscillations slip toward in-phase and anti-phase when driven at intermediate phases. These oscillations and bifurcations are emergent properties of the CPG model in response to volitional inputs. The CPG model is a version of the Ellias-Grossberg oscillator. Its neurons obey Hodgkin-Huxley type equations whose excitatory signals operate on a faster time scale than their inhibitory signals in a recurrent on-center off-surround anatomy. When an equal command or GO signal activates both model channels, the model CPG can generate both in-phase and anti-phase oscillations at different GO amplitudes. Phase transitions from either in-phase to anti-phase oscillations, or from anti-phase to in-phase oscillations, can occur in different parameter ranges, as the GO signal increases. Received: 22 August 1994 / Accepted in revised form: 13 May 1997     

Vertical Binocular Disparity is Encoded Implicitly within a Model Neuronal Population Tuned to Horizontal Disparity and Orientation

Primary visual cortex is often viewed as a “cyclopean retina”, performing the initial encoding of binocular disparities between left and right images. Because the eyes are set apart horizontally in the head, binocular disparities are predominantly horizontal. Yet, especially in the visual periphery, a range of non-zero vertical disparities do occur and can influence perception. It has therefore been assumed that primary visual cortex must contain neurons tuned to a range of vertical disparities. Here, I show that this is not necessarily the case. Many disparity-selective neurons are most sensitive to changes in disparity orthogonal to their preferred orientation. That is, the disparity tuning surfaces, mapping their response to different two-dimensional (2D) disparities, are elongated along the cell''s preferred orientation. Because of this, even if a neuron''s optimal 2D disparity has zero vertical component, the neuron will still respond best to a non-zero vertical disparity when probed with a sub-optimal horizontal disparity. This property can be used to decode 2D disparity, even allowing for realistic levels of neuronal noise. Even if all V1 neurons at a particular retinotopic location are tuned to the expected vertical disparity there (for example, zero at the fovea), the brain could still decode the magnitude and sign of departures from that expected value. This provides an intriguing counter-example to the common wisdom that, in order for a neuronal population to encode a quantity, its members must be tuned to a range of values of that quantity. It demonstrates that populations of disparity-selective neurons encode much richer information than previously appreciated. It suggests a possible strategy for the brain to extract rarely-occurring stimulus values, while concentrating neuronal resources on the most commonly-occurring situations.     

Sensory processing in the fast electrosensory pathway of pulse gymnotids studied at multiple integrative levels

Pulse gymnotids extract information about the environment using the pulsed discharge of an electric organ. Cutaneous electroreceptor organs transduce and encode the changes that objects imprint on the self-generated transcutaneous electric field. This review deals with the role of a neural circuit, the fast electrosensory path of pulse gymnotids, in the streaming of self generated electrosensory signals. The activation of this path triggers a low-responsiveness window slightly shorter than the interval between electric organ discharges. This phenomenon occurs at the electrosensory lateral line lobe where primary afferent terminals project on the somata of spherical neurons. The main subservient mechanism of the low-responsiveness window rely on the intrinsic properties of spherical neurons (dominated by a voltage dependent, low-threshold, non-inactivating and slowly-deactivating K(+) conductance) determining the cell to respond with a single spike followed by a long refractory period. Externally generated signals that randomly occur within the interval between self-generated discharges are likely blocked by the low responsiveness window. Repetitive signals, as those emitted by conspecifics with a slightly lower rate, occur progressively at longer delays beyond the duration of the low responsiveness window. Transient increases of the discharge rate relocate the interference within the low-responsiveness window. We propose that this combination of sensory filtering and electromotor control favors the self-generated signals in detriment of other, securing the continuity of the electrolocation stream.     

The inferior temporal cortex: Architecture, computation, and representation

Neurons in the inferior temporal cortex (IT), an area crucially involved in visual object recognition in monkeys, show the visual response properties and anatomical/chemical nature which are distinct from those in the cortical areas that feed visual inputs to the IT. Earlier physiological studies showed that IT neurons have large receptive fields covering the center and contralateral (often bilateral) visual fields, stimulus selectivity for images of complex objects or shapes, and translation invariance of the stimulus selectivity. Recent studies have revealed new aspects of their properties such as invariant selectivity for shapes despite drastic changes in various physical attributes of stimuli, latent excitatory inputs masked by stimulus-specific GABAergic inhibition, selectivity for binocular disparity and 3-dimensional surface structures, profound effects of learning on the stimulus selectivity, and columnar clustering of neurons with similarstimulus selectivity for shapes and other object features. Another line of research using histological techniques have revealed that pyramidal neurons in the IT are larger in the size of dendritic arbors, in the number of dendritic branches and spines, and in the size and distribution of horizontal axonal arbors than those in the earlier areas, allowing them to integrate a larger population of afferents and process more diverse inputs. The concentration of several neurochemicals including those related to synaptic transmission or plasticity changes systematically towards the IT along the occipitotemporal pathway. Many of the characteristics of IT neurons parallel or explain certain aspects of visual object perception, although the behavioral relevance has yet to be addressed experimentally.     

Response properties and biological function of the skate electrosensory system during ontogeny

This study examined the response properties of skate electrosensory primary afferent neurons of pre-hatch embryo (8–11 weeks), post-hatch juvenile (1–8 months), and adult (>2 year) clearnose skates (Raja eglanteria) to determine whether encoding of electrosensory information changes with age, and if the electro-sense is adapted to encode natural bioelectric stimuli across life history stages. During ontogeny, electrosensory primary afferents increase resting discharge rate, spike regularity, and sensitivity at best frequency. Best frequency was at 1–2 Hz for embryos, showed an upwards shift to 5 Hz in juveniles, and a downward shift to 2–3 Hz in adults. Encapsulated embryos exhibit ventilatory movements that are interrupted by a “freeze response”” when presented with weak uniform fields at 0.5 and 1 Hz. This phasic electric stimulus contains spectral information found in potentials produced by natural fish predators, and therefore indicates that the embryo electrosense can efficiently mediate predator detection and avoidance. In contrast, reproductively active adult clearnose skates discharge their electric organs at rates near the peak frequency sensitivity of the adult electrosensory system, which; facilitates electric communication during social behavior. We suggest that life-history-dependent functions such as these may shape the evolution of the low-frequency response properties for the elasmobranch electrosensory system. Accepted: 19 February 1998