Subthreshold Responses Research Articles

Firing frequency response to current and conductance periodic inputs in a Ih/INap biophysical neuron model

Various neurons exhibit membrane potential (or subthreshold) resonance [1], a peak in the subthreshold voltage amplitude response to oscillatory current inputs at a certain preferred (resonant) input frequency. Previous theoretical work using linear models has shown that subthreshold resonance can be communicated to the supra-threshold regime [2,3]; i.e., the firing frequency (or signal gain) response to oscillatory input currents peaks at the subthreshold resonant frequency. Whether this property is maintained under more general conditions and for different types of inputs is still an open question. In this work, we investigate the firing frequency patterns generated in response to both current and conductance sinusoidal inputs in a biophysical (conductance-based) neuron model that includes two ionic currents: h- (Ih) and persistent sodium (INap). This model is based on measurements for stellate cells (SCs) in layer II of the medial entorhinal cortex [4] and captures various phenomena observed in SCs such as membrane potential oscillations and membrane potential (subthreshold) resonance at theta frequencies (4 - 10 Hz)[2]. The Ih/INap model describes the cell's subthreshold dynamics and the onset of spikes [5]. Spikes were generated artificially as in integrate/resonate-and-fire models (see [5]). We computed the firing rate and signal gain responses of the Ih/INap model to both current and conductance sinusoidal inputs for a wide range of frequencies and input amplitudes (Ain). The resulting patterns for current and conductance input are qualitatively different. For current inputs, the firing frequency (and signal gain) patterns show up to three prominent peaks with heights that differ only slightly. The number of peaks increases with increasing values of Ain. For small values of Ain, the peak input frequency coincides with the subthreshold resonant frequency. The voltage traces (voltage vs. time) corresponding different peaks for the same value of Ain have roughly the same number of spikes (and inter-spike intervals of similar size), and differ in the number of subthreshold oscillations interspersed in between two consecutive spikes. For conductance (excitatory) inputs, the firing rate patterns show multiple peaks with different heights. As Ain increases, the highest peak moves to the right. For input frequencies above 60 Hz, the firing rate and gain of the highest peak significantly increases relative to other peaks for the same value of Ain. This prominent peak reflects the fast time scale present in the model that has been shown to underlie hyper-excitable firing in SCs [6] observed in animal models of temporal lobe epilepsy. We use dynamical systems tools to explain the mechanism that govern the generation of the firing frequency patterns described above. We show that the nonlinearities present in the model and the time scale separation between voltage and the h-current gating variables play an important role in determining these patterns.

A dynamical model of perceptual categorization

In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. We consider the case of temporally streamed input: sequentially presented or sampled objects, disregarding (in the case of vision) spatial arrangement. The process of grouping by similarity is easy, fast, and does not require attention or training when the stimuli are sufficiently simple. What neural mechanisms govern such a grouping process remains an open question. We propose a high-level, neuro-mechanistic model of perceptual grouping based on the framework of continuous attractor networks [1,2]. The network model is able to dynamically cluster the features of the sensory objects present in the input stream, thereby performing an elementary categorization of the sensory scene. The resulting categories are represented by self-sustained selective patterns of neuronal activity, or “bumps”, in which only a fraction of neurons with similar selectivity properties are active. Such activity patterns can be thought of as localized in feature space, and persist in the absence of inputs due to recurrent excitation. The connectivity of the network is sufficiently structured for these non-homogeneous patterns to be stable, while is mild enough to maintain the stability of a homogeneous, low-activity state, associated with spontaneous activity. The bistability between the homogeneous and the localized states allows for the formation of categories conditioned on the statistics of the external inputs, idealized as temporal sequences of single feature values. We suppose that the presentation of a single item in the sequence elicits a subthreshold response that, compared to the stimulus presentation rate, decays slowly after the stimulus is removed. Because of the slow decay, the network responds to the sequence of stimuli by effectively summing temporally the responses triggered separately by each item. Only when the input stream consists of an adequate number of similar feature values, will there be successive hits within a critical time window in one or more localized regions of feature space that will be sufficient to trigger the emergence of one or more bump states. Each such bump state encodes approximately the mean feature value of the items belonging to a particular category, and hence can be regarded as the neural representation of a category prototype. Using a combination of analytical and numerical methods, we study the conditions for the network to be capable of forming categories. More specifically, we investigate the necessary conditions that the connectivity has to satisfy so that multiple localized states can coexist, while preserving the bistability with a homogeneous state. These conditions can be fulfilled when the connectivity has a narrow Mexican-hat profile, and there is an approximate balance between excitation and inhibition. A generalization of the model for multi-dimensional features is also analyzed and leads to similar results. We characterize the ability of the network to extract clusters of features as a function of the statistics of the input stream, and show that results are consistent with the psychophysics of perceptual categorization and ensemble statistics [3].

Cell-type–specific sub- and suprathreshold receptive fields of layer 4 and layer 2/3 pyramids in rat primary visual cortex

Connectivity of cortical pyramidal neurons is layer-specific in the primary visual cortex (V1) and this is thought to be reflected in different receptive field (RF) properties of layer 4 and layer 2/3 pyramidal neurons (L4Ps and L2/3Ps, respectively). However, it remains unclear how the two cell populations convert incoming visually driven synaptic inputs into action potential (AP) outputs. Here I compared postsynaptic potentials (PSPs) and AP responses of L4Ps and L2/3Ps in the binocular portion of rat V1 by intrinsic optical imaging (IOI)-targeted whole-cell recordings followed by anatomical identification and dendritic reconstructions. L2/3Ps had about 2-fold longer dendritic branches and a higher number of branch points and endings in their apical portions. Functionally, L2/3Ps had more hyperpolarized resting potentials and lower rates of spontaneous APs (medians: 0.07 vs. 0.60 AP/s). PSP responses to optimally oriented moving bars were comparable in terms of amplitude (16.0±0.9 vs. 17.3±1.1 mV for L2/3Ps and L4Ps, respectively), reliability and size of the RF. The modulated component of subthreshold responses of L4Ps to optimal sinusoidal drifting gratings was larger and their PSP onset latency in response to bars flashed in the cell's RF center were shorter (60 vs. 86 ms). In contrast to the similarities of PSP responses to moving bars, AP responses of L2/3Ps were more sparse (medians: 0.7 vs. 2.9 APs/stimulus passage), less reliable, but sharper in terms of angular size. Based on the differences of subthreshold inputs, I conclude that L4Ps may receive mostly thalamic inputs, whereas L2/3Ps may receive both thalamic and cortical inputs from layer 4. The comparable subthreshold responses to moving bars are converted by L2/3Ps into sparser but sharper AP outputs possibly by cell-type-specific AP-generating mechanisms or differences in visually driven inhibitory inputs.

Neuronal Responses Below Firing Threshold for Subthreshold Cross-Modal Enhancement

Multisensory integration (such as somatosensation-vision, gustation-olfaction) could occur even between subthreshold stimuli that in isolation do not reach perceptual awareness. For example, when a somatosensory (subthreshold) stimulus is delivered within a close spatiotemporal congruency, a visual (subthreshold) stimulus evokes a visual percept. Cross-modal enhancement of visual perception is maximal when the somatosensory stimulation precedes the visual one by tens of milliseconds. This rapid modulatory response would not be consistent with a top-down mechanism acting through higher-order multimodal cortical areas, but rather a direct interaction between lower-order unimodal areas. To elucidate the neuronal mechanisms of subthreshold cross-modal enhancement, we simulated a neural network model. In the model, lower unimodal (X, Y) and higher multimodal (M) networks are reciprocally connected by bottom-up and top-down axonal projections. The lower networks are laterally connected with each other. A pair of stimuli was presented to the lower networks, whose respective intensities were too weak to induce salient neuronal activity (population response) when presented alone. Neurons of the Y network were slightly depolarized below firing threshold when a cross-modal stimulus was presented alone to the X network. This allowed the Y network to make a rapid (within tens of milliseconds) population response when presented with a subsequent congruent stimulus. The reaction speed of the Y network was accelerated, provided that the top-down projections were strengthened. We suggest that a subthreshold (nonpopulation) response to a cross-modal stimulus, acting through interaction between lower (primary unisensory) areas, may be essential for a rapid suprathreshold (population) response to a congruent stimulus that follows. Top-down influences on cross-modal enhancement may be faster than expected, accelerating reaction speed to input, in which ongoing-spontaneous subthreshold excitation of lower-order unimodal cells by higher-order multimodal cells may play an active role.

The spike initiation in neurons with low input resistance

Event Abstract Back to Event The spike initiation in neurons with low input resistance Simon Lehnert1* and Christian Leibold1, 2 1 Ludwig-Maximilians-Universität München, Department of Biology II, Germany 2 Bernstein Center for Computational Neuroscience Munich, Germany Spike initiation is generally assumed to occur in the axon's initial segment (AIS). In neurons with very low input resistance, however, this may no longer hold true, because the soma constitutes a huge current sink. As an example, we consider the principal cells of the medial superior olive (MSO). These neurons are very fast coincidence detectors in the auditory brainstem that encode low frequency azimuthal sound localization by interaural time differences. Their enormously low time constant of only a few hundred microseconds yields from a very low input resistance of about 5MΩ at rest [1], which arises from the expression of low-voltage-activated potassium channels and hyperpolarization-activated unspecific cation channels. Since these cells receive a huge amount of slowly-decaying inhibition [1], it is likely that their input resistance in vivo is even much smaller than at rest. Hence the question arises: how are these cells able to elicit action potentials (AP) at all? By using a multi-compartemental model of an MSO cell, we found that the spike initiation segment (SIS) in the model is still the AIS. The reason for this is the electrotonic independence of the AIS from the leaky soma. The input resistance of the axonal segments is considerably higher than that of the soma and hence an input current is able to evoke an AP in the AIS, while an AP in the soma is hardly distinguishable from a subthreshold response. We conclude, that the excitability of the axon enables the cell to convey information downstream, although the soma itself is not excitable. Thus, neurons with low input resistance cannot be realistically modeled using only a single compartment.

3D reverse engineering and simulation of signal flow in anatomically realistic neuronal networks

Event Abstract Back to Event 3D reverse engineering and simulation of signal flow in anatomically realistic neuronal networks Marcel Oberlaender1*, Christiaan DeKock2, Randy Bruno3, Stefan Lang4 and Bert Sakmann1 1 Max Planck Florida Institute, United States 2 VU University Amsterdam, Netherlands 3 Columbia University, United States 4 Heidelberg University, IWR, Germany Soma location, dendrite morphology and presynaptic innervation represent key determinants of functional responses of individual neurons, such a sensory-evoked spiking. Here, we reverse engineer the three-dimensional networks formed by thalamocortical afferents from the lemniscal pathway and excitatory neurons of an anatomically defined cortical column in rat vibrissal cortex. We objectively classify nine cell types and quantify the number and distribution of their somata, dendrites and thalamocortical synapses. Somata and dendrites of most cell types intermingle, while thalamocortical connectivity depends strongly upon the cell type and the three-dimensional soma location of the postsynaptic neuron. Our dataset provides the first three-dimensional anatomical description of the cell type-specific lemniscal synaptic wiring diagram and elucidates structure-function relationships of this physiologically relevant pathway at single-cell resolution. Simulation of signal flow, evoked by passive whisker touch, revealed that the three-dimensional structure of thalamocortical networks in a cortical column can account for cell type- and location-specific subthreshold and spiking responses. Thus, the present approach may allow investigating the cellular and subcellular mechanisms that underlie whisker-mediated behaviors. Figure 1 Keywords: computational neuroscience Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: Computational neuroscience Citation: Oberlaender M, DeKock C, Bruno R, Lang S and Sakmann B (2011). 3D reverse engineering and simulation of signal flow in anatomically realistic neuronal networks. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00005 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Marcel Oberlaender, Max Planck Florida Institute, Jupiter, United States, marcel.oberlaender@maxplanckflorida.org Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann Google Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann Google Scholar Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann PubMed Marcel Oberlaender Christiaan DeKock Randy Bruno Stefan Lang Bert Sakmann Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

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.

Central gating of fly optomotor response

We study the integration of multisensory and central input at the level of an identified fly motoneuron, the ventral cervical nerve motoneuron (VCNM) cell, which controls head movements of the animal. We show that this neuron receives input from a central neuron signaling flight activity, from two identified wide-field motion-sensitive neurons, from the wind-sensitive Johnston organ on the antennae, and from the campaniform sensillae of the halteres. We find that visual motion alone leads to only subthreshold responses. Only when it is combined with flight activity or wind stimuli does the VCNM respond to visual motion by modulating its spike activity in a directionally selective way. This nonlinear enhancement of visual responsiveness in the VCNM by central activity is reflected at the behavioral level, when compensatory head movements are measured in response to visual motion. While head movements of flies have only a small amplitude when flies are at rest, the response amplitude is increased by a factor of 30-40 during flight.

Effect of interface states on sub-threshold response of III–V MOSFETs, MOS HEMTs and tunnel FETs

The effect of interface states on the current–voltage characteristics in the sub-threshold region of three different types of III–V based transistor architectures has been studied using a drift–diffusion based numerical simulator. Experimentally extracted interface state density profile is included in the simulation to analyze their effect on the sub-threshold response of InGaAs based MOSFETs, MOS HEMTs and tunnel FETs. Based on the Fermi-level position at the oxide/semiconductor interface and the corresponding interface state density ( D it), the sub-threshold response for the three devices can vary, with tunnel FETs having the least sub-threshold degradation due to D it.

Insulin facilitates repetitive spike firing in rat insular cortex via phosphoinositide 3-kinase but not mitogen activated protein kinase cascade

The insular cortex (IC) processes gustatory and visceral information, which functionally correlate to feeding behavior. Insulin, a well-known hormone controlling glucose metabolism, is released by elevation of blood glucose concentration following feeding behavior. The IC expresses dense insulin receptors and receives projection from the hypothalamus, which monitors changes in glucose concentration. Therefore, it is likely that insulin modulates neural properties in the IC. However, little is known about the effects of insulin on electrophysiological properties of the neocortex including the IC. To explore the effects of insulin on subthreshold responses and action potential properties in the IC, intracellular recording with sharp glass electrodes was performed from IC pyramidal cells using slice preparations. Although application of insulin (100 nM) had little effect on the resting membrane potential, input resistance and rheobase, insulin significantly increased the frequency of repetitive spike firing in response to a long depolarizing current pulse injection: the slope of the frequency-current curve was increased from 23.7±2.3 Hz/nA to 29.5±3.4 Hz/nA. Insulin slightly decreased the action potential threshold without affecting the amplitude of medium-duration and slow afterhyperpolarization (sAHP) s. The insulin-induced facilitation of repetitive spike firing was dose-dependent and blocked by pre-application of 200 nM lavendustin A, a tyrosine kinase inhibitor. Moreover, when combined with 200 nM wortmannin, a phosphoinositide 3-kinase (PI3-K) inhibitor, or 500 nM deguelin, an inhibitor of protein kinase B (PKB/Akt) downstream of PI3-K, insulin failed to increase the frequency of repetitive spike firing. In contrast, co-application of insulin and (10 μM) PD 98059, an inhibitor of mitogen activated protein kinase (MAPK), exerted facilitation of repetitive spike firing. These results suggest that acute insulin-induced facilitation of firing frequency is at least partially induced by hyperpolarizing effects on the action potential threshold, and that this facilitation is induced by activation of PI3-K but not MAPK cascade.

Cervix Stimulation Evokes Predominantly Subthreshold Synaptic Responses in Mouse Thoracolumbar and Lumbosacral Superficial Dorsal Horn Neurons

Sensory input from the female reproductive tract (FRT) plays a pivotal role in coordinating reproductive reflexes. Additionally, a number of disorders, especially chronic pelvic pain, may be due to disturbances in sensory processing of signals from the FRT. Our aim was to record synaptic responses in neurons from lumbar and sacral spinal cord segments during mechanical stimulation of the cervix. We developed an in vivo preparation of the mouse spinal cord to record synaptic potentials from superficial dorsal horn (SDH) neurons under whole-cell patch clamp recording conditions. We analyzed the strength and distribution of excitatory postsynaptic potentials in SDH neurons evoked during mechanical stimulation of the cervix and cutaneous sites. Resting membrane potential and neuronal input resistance was similar in thoracolumbar (TL, T13-L3) and lumbosacral (LS, L6-S2) segments. We elicited activity in 6/21 TL neurons and 15/39 LS neurons using mechanical stimulation of the cervix with a blunt probe. The majority of these neurons responded to cervix stimulation with bursts of subthreshold excitatory postsynaptic potentials (4/6 and 12/15 TL and LS neurons, respectively). The remainder responded with sufficient magnitude to generate action potentials (2/6 and 3/15 TL and LS neurons). Cutaneous synaptic inputs were also elicited in 11/21 TL neurons following stimulation of the flank/leg, 19/39 LS neurons by stimulation of the tail, and three LS neurons by perineal stimulation. Some neurons received convergent synaptic inputs from the cervix and cutaneous sites (4/6 TL and 4/15 LS). These data demonstrate that spinal projections of cervix afferents are widely dispersed in the SDH and considerable convergence exists between neurons innervating the cervix and cutaneous structures. Our results indicate that much of the synaptic activity evoked in SDH neurons following cervix stimulation is subthreshold.

Morphologically accurate reduced order modeling of spiking neurons

Accurately simulating neurons with realistic morphological structure and synaptic inputs requires the solution of large systems of nonlinear ordinary differential equations. We apply model reduction techniques to recover the complete nonlinear voltage dynamics of a neuron using a system of much lower dimension. Using a proper orthogonal decomposition, we build a reduced-order system from salient snapshots of the full system output, thus reducing the number of state variables. A discrete empirical interpolation method is then used to reduce the complexity of the nonlinear term to be proportional to the number of reduced variables. Together these two techniques allow for up to two orders of magnitude dimension reduction without sacrificing the spatially-distributed input structure, with an associated order of magnitude speed-up in simulation time. We demonstrate that both nonlinear spiking behavior and subthreshold response of realistic cells are accurately captured by these low-dimensional models.

Preceding Inhibition Silences Layer 6 Neurons in Auditory Cortex

A canonical feedforward circuit is proposed to underlie sensory cortical responses with balanced excitation and inhibition in layer 4 (L4). However, in another input layer, L6, sensory responses and the underlying synaptic circuits remain largely unclear. Here, cell-attached recordings in rat primary auditory cortex revealed that for the majority of L6 excitatory neurons, tonal stimuli did not drive spike responses, but suppressed spontaneous firings. Whole-cell recordings further revealed that the silencing resulted from tone-evoked strong inhibition arriving earlier than excitation. This pattern of inputs can be attributed to a parallel feedforward circuit with both excitatory and inhibitory inputs disynaptically relayed. In contrast, in the other neurons directly driven by thalamic input, stimuli evoked excitation preceding relatively weak inhibition, resulting in robust spike responses. Thus, the dichotomy of L6 response properties arises from two distinct patterns of excitatory-inhibitory interplay. The parallel circuit module generating preceding inhibition may provide a gating mechanism for conditional corticothalamic feedback.

Dichotomy of functional organization in the mouse auditory cortex

The sensory areas of the cerebral cortex possess multiple topographic representations of sensory dimensions. Gradient of frequency selectivity (tonotopy) is the dominant organizational feature in the primary auditory cortex, while other feature-based organizations are less well established. We probed the topographic organization of the mouse auditory cortex at the single cell level using in vivo two-photon Ca2+ imaging. Tonotopy was present on a large scale but was fractured on a fine scale. Intensity tuning, important in level-invariant representation, was observed in individual cells but was not topographically organized. The presence or near-absence of putative sub-threshold responses revealed a dichotomy in topographic organization. Inclusion of sub-threshold responses revealed a topographic clustering of neurons with similar response properties, while such clustering was absent in supra-threshold responses. This dichotomy indicates that groups of nearby neurons with locally shared inputs can perform independent parallel computations in ACX.

Simulation of innervation and activation scenarios of morphologically detailed, large-scale neuron networks in a column of the primary somatosensory cortex with NeuroDUNE

Event Abstract Back to Event Simulation of innervation and activation scenarios of morphologically detailed, large-scale neuron networks in a column of the primary somatosensory cortex with NeuroDUNE Stefan Lang1*, Marcel Oberlaender2, Peter Bastian1 and Bert Sakmann2 1 University of Heidelberg, Parallel Computing Group, Interdisciplinary Center for Scientific Computing, Germany 2 Max Planck Florida Institute, Department of Digital Neuroanatomy, United States To understand and describe how the cortex processes sensory information about its environment within functional explanatory models and to understand how the model structure can be related to behavior is of special interest in neuroscience. The information related to the deflection of a single facial whisker on the snout of rodents (e.g. mice and rats) is processed by a network of about 17500 neurons (in rat), substructured by 9 distinct cell types in a cortical column. We present numerical simulations of morphological detailed, large-scale neuron networks. Network generation is based on experimentally determined 3D neuron distributions. Furthermore, individual network cells are derived from anatomically reconstructed and then quantitatively classified neuronal cell-types. Synapse densities are statistically distributed on each cell according to measured anatomical and functional data. As example of a quantitatively determined microcircuit we simulate the thalamocortical pathway (VPM) providing excitatory input to the networks in barrel cortex. Since no definitive information about the innervation is present we investigate several innervation scenarios in relation to the network response. Network activation is analyzed with regard to biophysically relevant quantities such as subthreshold response, number of activated synapses as well as spike output of the VPM-activated network. The previously described statistical approach to build networks necessitates Monte-Carlo simulation to determine quantities of interest by ensemble averaging. An ensemble individual consists hereby of a single large-scale network realisation consisting of morphologically detailed neurons activated by the driving VPM cells with multivariate statistical wiring. To perform simulations and analyse responses of distinct ensemble series we use the numerical framework, NeuroDUNE, that has been developed to enable modeling and simulation of signal processing in such large-scale, full-compartmental neuron networks on sub cellular basis. Figure !: Left: Morphological detailed L5B cell with statistically constrained synapse distribution (red dots). Middle Left: Subthreshold activation of a small network of 60 L5B cells. Middle Right: Column response to VPM activation, spiking cell somata in green. Right: Relationship between cell specific quantities and cell activation: number of synapses (blue), number of activated synapses (green). Spike times as red marks indicate cell response (ms from whisker deflection). Figure 1 Keywords: computational neuroscience Conference: Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010. Presentation Type: Poster Abstract Topic: Bernstein Conference on Computational Neuroscience Citation: Lang S, Oberlaender M, Bastian P and Sakmann B (2010). Simulation of innervation and activation scenarios of morphologically detailed, large-scale neuron networks in a column of the primary somatosensory cortex with NeuroDUNE. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.fncom.2010.51.00014 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 22 Sep 2010; Published Online: 23 Sep 2010. * Correspondence: Dr. Stefan Lang, University of Heidelberg, Parallel Computing Group, Interdisciplinary Center for Scientific Computing, Heidelberg, Germany, Stefan.Lang@iwr.uni-heidelberg.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Stefan Lang Marcel Oberlaender Peter Bastian Bert Sakmann Google Stefan Lang Marcel Oberlaender Peter Bastian Bert Sakmann Google Scholar Stefan Lang Marcel Oberlaender Peter Bastian Bert Sakmann PubMed Stefan Lang Marcel Oberlaender Peter Bastian Bert Sakmann Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

When Right Feels Left: Referral of Touch and Ownership between the Hands

Feeling touch on a body part is paradigmatically considered to require stimulation of tactile afferents from the body part in question, at least in healthy non-synaesthetic individuals. In contrast to this view, we report a perceptual illusion where people experience “phantom touches” on a right rubber hand when they see it brushed simultaneously with brushes applied to their left hand. Such illusory duplication and transfer of touch from the left to the right hand was only elicited when a homologous (i.e., left and right) pair of hands was brushed in synchrony for an extended period of time. This stimulation caused the majority of our participants to perceive the right rubber hand as their own and to sense two distinct touches – one located on the right rubber hand and the other on their left (stimulated) hand. This effect was supported by quantitative subjective reports in the form of questionnaires, behavioral data from a task in which participants pointed to the felt location of their right hand, and physiological evidence obtained by skin conductance responses when threatening the model hand. Our findings suggest that visual information augments subthreshold somatosensory responses in the ipsilateral hemisphere, thus producing a tactile experience from the non-stimulated body part. This finding is important because it reveals a new bilateral multisensory mechanism for tactile perception and limb ownership.

A precise form of divisive suppression supports population coding in the primary visual cortex

The responses of neurons in the primary visual cortex (V1) to an optimally-oriented grating are suppressed when a non-optimal grating is superimposed. Although cross-orientation suppression is thought to reflect mechanisms that maintain a distributed code for orientation, the impact of superimposed gratings upon V1 populations is unknown. Using intrinsic signal optical imaging, we find that patterns of tree shrew V1 activity evoked by superimposed equal-contrast gratings were predicted by the mean of patterns evoked by individual component gratings. This prediction held across contrasts, for summed sinusoidal gratings or non-summing square-wave gratings, and was reflected in single-unit extracellular recordings. Intracellular recordings revealed consistent levels of suppression throughout the evolution of subthreshold responses. These results indicate that divisive suppression powerfully governs population responses to multiple orientations. Moreover, the specific form of suppression we observe appears to support independent population codes for stimulus orientation and strength, and calls for a reassessment of mechanisms that underlie cross-orientation suppression.

Subthreshold Receptive Field Properties Distinguish Different Classes of Corticothalamic Neurons in the Somatosensory System

Most corticothalamic (CT) neurons in somatosensory cortex are silent in lightly anesthetized and even awake animals, making it difficult to investigate CT function and the underlying circuitry. Here we use juxtasomal recording and stimulation techniques to probe subthreshold response properties of antidromically identified CT neurons in the rat whisker/barrel system. When neuronal firing is facilitated by depolarizing juxtasomal currents, silent neurons become responsive to whisker stimuli, permitting identification of three functional classes of CT cells: those having a short-latency excitatory response to whisker deflection, those having a long-latency response, and neurons whose firing is suppressed by whisker deflection. During sensorimotor behaviors when the CT system may be active, cells having excitatory vs inhibitory receptive fields may participate in push-pull corticothalamic circuits that, acting together, selectively enhance sensory signaling in the thalamocortical system.

Cellular contribution to vestibular signal processing - a modeling approach

Event Abstract Back to Event Cellular contribution to vestibular signal processing - a modeling approach Christian Rossert1, 2*, Hans Straka3 and Stefan Glasauer1 1 Bernstein Center for Computational Neuroscience, Germany 2 Ludwig-Maximilians-Universitaet, Institute for Clinical Neurosciences, Germany 3 Universite Paris Descartes, Laboratoire de Neurobiologie des Réseaux Sensorimoteurs, Centre National de la Recherche Scientifique, France Computational modeling of the vestibulo-ocular circuitry is essential for understanding the sensory-motor transformation that generates spatially and dynamically appropriate compensatory eye movements during self-motion. Central vestibular neurons in the brainstem are responsible for the major computational step that transforms head acceleration-related sensory vestibular signals into extraocular motor commands that cause compensatory eye motion for gaze stabilization. In frog, second-order vestibular neurons (2°VN) separate into two functional subgroups (tonic - phasic neurons) that distinctly differ in their intrinsic membrane properties and discharge characteristics. While tonic 2°VN exhibit a continuous discharge in response to positive current steps, phasic 2°VN display a brief, high-frequency burst of spikes but no continuous discharge, corresponding to class 1 and class 3 excitability, respectively. Based on the dynamics of sinusoidally modulated changes of the membrane potential, tonic 2°VN show low-pass filter-like response properties, whereas phasic 2°VN have band-pass filter-like characteristics. Correlated with these cellular properties, tonic and phasic 2°VN exhibit pronounced differences in subthreshold response dynamics and discharge kinetics during synaptic activation of individual labyrinthine nerve branches with sinusoidally modulated trains of single electrical pulses. Physio-pharmacological analyses indicated that the two types of 2°VN are differentially embedded into local inhibitory circuits that reinforce the cellular properties of these neurons, respectively, thus indicating a co-adaptation of intrinsic membrane and emerging network properties in the two neuronal subtypes. The channel mechanisms responsible for the different discharge characteristics of the two neuronal subtypes were revealed by a frequency-domain analysis in the subthreshold domain: tonic 2°VN exhibit an increasing impedance with membrane depolarization which likely results from an activation of persistent sodium currents, while phasic 2°VN show a decreasing impedance and increasing resonance with membrane depolarization due to the activation of low-threshold, voltage-dependent ID-type potassium channels. These results also revealed the necessary channel mechanisms to generate spiking multi-compartment models. By extending these models with conductance-based synapses that simulate the corresponding activation and inhibition it was possible to reproduce the distinct firing behavior of the two neuronal subtypes during intracellular and synaptic activation, respectively. By modifying different components of the intrinsic cellular or the synaptic circuit properties it is now possible to determine the relative contributions of membrane and network properties for vestibular signal processing. Selective modifications of different neuronal circuit components or particular properties of ion channel conductances in the model allow making predictions of how eco-physiological or patho-physiological changes affect vestibular signal processing and how cellular and network mechanisms might compensate for induced alterations. Acknowledgements:Supported by Bayerische Forschungsstiftung (C.R.) and Bundesministerium für Bildung und Forschung (BCCN 01GQ0440). Conference: Bernstein Conference on Computational Neuroscience, Frankfurt am Main, Germany, 30 Sep - 2 Oct, 2009. Presentation Type: Poster Presentation Topic: Sensory processing Citation: Rossert C, Straka H and Glasauer S (2009). Cellular contribution to vestibular signal processing - a modeling approach. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.neuro.10.2009.14.157 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 28 Aug 2009; Published Online: 28 Aug 2009. * Correspondence: Christian Rossert, Bernstein Center for Computational Neuroscience, Munich, Germany, christian.a@roessert.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Christian Rossert Hans Straka Stefan Glasauer Google Christian Rossert Hans Straka Stefan Glasauer Google Scholar Christian Rossert Hans Straka Stefan Glasauer PubMed Christian Rossert Hans Straka Stefan Glasauer Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Visual Avoidance inXenopusTadpoles Is Correlated With the Maturation of Visual Responses in the Optic Tectum

The optic tectum is central for transforming incoming visual input into orienting behavior. Yet it is not well understood how this behavior is organized early in development and how it relates to the response properties of the developing visual system. We designed a novel behavioral assay to study the development of visually guided behavior in Xenopus laevis tadpoles. We found that, during early development, visual avoidance-an innate, tectally mediated behavior-is tuned to a specific stimulus size and is sensitive to changes in contrast. Using in vivo recordings we found that developmental changes in the spatial tuning of visual avoidance are mirrored by changes in tectal receptive field sharpness and the temporal properties of subthreshold visual responses, whereas contrast sensitivity is affected by the gain of the visual response. We also show that long- and short-term perturbations of visual response properties predictably alter behavioral output. We conclude that our assay for visual avoidance is a useful functional measure of the developmental state of the tectal circuitry. We use this assay to show that the developing visual system is tuned to facilitate behavioral output and that the system can be modulated by neural activity, allowing it to adapt to environmental changes it encounters during development.