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  • 11
    Electronic Resource
    Electronic Resource
    The computational options (1988)
    [s.l.] : Nature Publishing Group
    Nature 335 (1988), S. 213-214 
    Details
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] IT HAS become very fashionable in the past few years to investigate various aspects of the nervous system from a theoretical point of view. Indeed 'experimental neuroscience' (until recently, quite simply 'neuroscience') has acquired a twin, 'computational neuroscience'. This new field is ...
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1038/335213a0
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  • 12
    Electronic Resource
    Electronic Resource
    Cable theory in neurons with active, linearized membranes (1984)
    Springer
    Biological cybernetics 50 (1984), S. 15-33 
    Details
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract This investigation aims at exploring some of the functional consequences of single neurons containing active, voltage dependent channels for information processing. Assuming that the voltage change in the dendritic tree of these neurons does not exceed a few millivolts, it is possible to linearize the non-linear channel conductance. The membrane can then be described in terms of resistances, capacitances and inductances, as for instance in the small-signal analysis of the squid giant axon. Depending on the channel kinetics and the associated ionic battery the linearization yields two basic types of membrane: a membrane modeled by a collection of resistances and capacitances and membranes containing in addition to these components inductances. Under certain specified conditions the latter type of membrane gives rise to a membrane impedance that displays a prominent maximum at some nonzero resonant frequency f max. We call this type of membrane quasi-active, setting it apart from the usual passive membrane. We study the linearized behaviour of active channels giving rise to quasi-active membranes in extended neuronal structures and consider several instances where such membranes may subserve neuronal function: 1. The resonant frequency of a quasi-active membrane increases with increasing density of active channels. This might be one of the biophysical mechanisms generating the large range over which hair cells in the vertebrate cochlea display frequency tuning. 2. The voltage recorded from a cable with a quasi-active membrane can be proportional to the temporal derivative of the injected current. 3. We modeled a highly branched dendritic tree (δ-ganglion cell of the cat retina) using a quasi-active membrane. The voltage attenuation from a given synaptic site to the soma decreases with increasing frequency up to the resonant frequency, in sharp contrast to the behaviour of passive membranes. This might be the underlying biophysical mechanism of receptive fields whose dimensions are large for rapid signals but contract to a smaller area for slow signals as suggested by Detwiler et al. (1978).
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00317936
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  • 13
    Electronic Resource
    Electronic Resource
    A Robust Analog VLSI Motion Sensor Based on the Visual System of the Fly (1999)
    Springer
    Autonomous robots 7 (1999), S. 211-224 
    Details
    ISSN: 1573-7527
    Keywords: optomotor system ; analog VLSI ; optic flow ; motion detector ; insect vision
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Sensing visual motion gives a creature valuable information about its interactions with the environment. Flies in particular use visual motion information to navigate through turbulent air, avoid obstacles, and land safely. Mobile robots are ideal candidates for using this sensory modality to enhance their performance, but so far have been limited by the computational expense of processing video. Also, the complex structure of natural visual scenes poses an algorithmic challenge for extracting useful information in a robust manner. We address both issues by creating a small, low-power visual sensor with integrated analog parallel processing to extract motion in real-time. Because our architecture is based on biological motion detectors, we gain the advantages of this highly evolved system: A design that robustly and continuously extracts relevant information from its visual environment. We show that this sensor is suitable for use in the real world, and demonstrate its ability to compensate for an imperfect motor system in the control of an autonomous robot. The sensor attenuates open-loop rotation by a factor of 31 with less than 1 mW power dissipation.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008916202887
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  • 14
    Electronic Resource
    Electronic Resource
    A Robust Analog VLSI Reichardt Motion Sensor (2000)
    Springer
    Analog integrated circuits and signal processing 24 (2000), S. 213-229 
    Details
    ISSN: 1573-1979
    Keywords: Reichardt motion detector ; analog VLSI ; insect vision ; motion sensor ; robust sensing ; biological model
    Source: Springer Online Journal Archives 1860-2000
    Topics: Electrical Engineering, Measurement and Control Technology
    Notes: Abstract Silicon imagers with integrated motion-detection circuitry have been developed and tested for the past 15 years. Many previous circuits estimate motion by identifying and tracking spatial or temporal features. These approaches are prone to failure at low SNR conditions, where feature detection becomes unreliable. An alternate approach to motion detection is an intensity-based spatiotemporal correlation algorithm, such as the one proposed by Hassenstein and Reichardt in 1956 to explain aspects of insect vision. We implemented a Reichardt motion sensor with integrated photodetectors in a standard CMOS process. Our circuit operates at sub-microwatt power levels, the lowest reported for any motion sensor. We measure the effects of device mismatch on these parallel, analog circuits to show they are suitable for constructing 2-D VLSI arrays. Traditional correlation-based sensors suffer from strong contrast dependence. We introduce a circuit architecture that lessens this dependence. We also demonstrate robust performance of our sensor to complex stimuli in the presence of spatial and temporal noise.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008361525235
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  • 15
    Electronic Resource
    Electronic Resource
    A model for the neuronal implementation of selective visual attention based on temporal correlation among neurons (1994)
    Springer
    Journal of computational neuroscience 1 (1994), S. 141-158 
    Details
    ISSN: 1573-6873
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract We propose a model for the neuronal implementation of selective visual attention based on temporal correlation among groups of neurons. Neurons in primary visual cortex respond to visual stimuli with a Poisson distributed spike train with an appropriate, stimulus-dependent mean firing rate. The spike trains of neurons whose receptive fields donot overlap with the “focus of attention” are distributed according to homogeneous (time-independent) Poisson process with no correlation between action potentials of different neurons. In contrast, spike trains of neurons with receptive fields within the focus of attention are distributed according to non-homogeneous (time-dependent) Poisson processes. Since the short-term average spike rates of all neurons with receptive fields in the focus of attention covary, correlations between these spike trains are introduced which are detected by inhibitory interneurons in V4. These cells, modeled as modified integrate-and-fire neurons, function as coincidence detectors and suppress the response of V4 cells associated with non-attended visual stimuli. The model reproduces quantitatively experimental data obtained in cortical area V4 of monkey by Moran and Desimone (1985).
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00962722
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  • 16
    Electronic Resource
    Electronic Resource
    Do neurons have a voltage or a current threshold for action potential initiation? (1995)
    Springer
    Journal of computational neuroscience 2 (1995), S. 63-82 
    Details
    ISSN: 1573-6873
    Keywords: voltage threshold ; current threshold ; action potential initiation ; integrate-and-fire models ; single cell models
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract The majority of neural network models consider the output of single neurons to be a continuous, positive, and saturating firing ratef(t), while a minority treat neuronal output as a series of delta pulses ∑δ (t — t i ). We here argue that the issue of the proper output representation relates to the biophysics of the cells in question and, in particular, to whether initiation of somatic action potentials occurs when a certain thresholdvoltage or a thresholdcurrent is exceeded. We approach this issue using numerical simulations of the electrical behavior of a layer 5 pyramidal cell from cat visual cortex. The dendritic tree is passive while the cell body includes eight voltage- and calcium-dependent membrane conductances. We compute both the steady-state (I ∞ static (V m )) and the instantaneous (I o (Vm)) I–V relationships and argue that the amplitude of the local maximum inI ∞ static (V m ) corresponds to the current thresholdI th for sustained inputs, while the location of the middle zero-crossing ofI o corresponds to a fixed voltage thresholdV th for rapid inputs. We confirm this using numerical simulations: for “rapid” synaptic inputs, spikes are initiated if the somatic potential exceedsV th, while for slowly varying inputI th must be exceeded. Due to the presence of the large dendritic tree, no charge thresholdQ th exists for physiological input. Introducing the temporal average of the somatic membrane potential 〈(V m)〉 while the cell is spiking repetitively, allows us to define a dynamic I-V relationship ∞ dynamic (〈(V m)〉). We find an exponential relationship between 〈(V m)〉 and the net current sunk by the somatic membrane during spiking (diode-like behavior). The slope ofI∞/dynamic(〈(V m))〉 allows us to define a dynamic input conductance and a time constant that characterizes how rapidly the cell changes its output firing frequency in response to a change in its input.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00962708
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  • 17
    Electronic Resource
    Electronic Resource
    Electrical Interactions via the Extracellular Potential Near Cell Bodies (1999)
    Springer
    Journal of computational neuroscience 6 (1999), S. 169-184 
    Details
    ISSN: 1573-6873
    Keywords: extracellular field potential ; volume conduction ; branch point failure ; axon hillock/initial segment
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract Ephaptic interactions between a neuron and axons or dendrites passing by its cell body can be, in principle, more significant than ephaptic interactions among axons in a fiber tract. Extracellular action potentials outside axons are small in amplitude and spatially spread out, while they are larger in amplitude and much more spatially confined near cell bodies. We estimated the extracellular potentials associated with an action potential in a cortical pyramidal cell using standard one-dimensional cable theory and volume conductor theory. Their spatial and temporal pattern reveal much about the location and timing of currents in the cell, especially in combination with a known morphology, and simple experiments could resolve questions about spike initiation. From the extracellular potential we compute the ephaptically induced polarization in a nearby passive cable. The magnitude of this induced voltage can be several mV, does not spread electrotonically, and depends only weakly on the passive properties of the cable. We discuss their possible functional relevance.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008832702585
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  • 18
    Electronic Resource
    Electronic Resource
    Subthreshold Voltage Noise Due to Channel Fluctuations in Active Neuronal Membranes (2000)
    Springer
    Journal of computational neuroscience 9 (2000), S. 133-148 
    Details
    ISSN: 1573-6873
    Keywords: membrane noise ; active ion channels ; Markov kinetic models ; stochastic ion channels
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract Voltage-gated ion channels in neuronal membranes fluctuate randomly between different conformational states due to thermal agitation. Fluctuations between conducting and nonconducting states give rise to noisy membrane currents and subthreshold voltage fluctuations and may contribute to variability in spike timing. Here we study subthreshold voltage fluctuations due to active voltage-gated Na+ and K+ channels as predicted by two commonly used kinetic schemes: the Mainen et al. (1995) (MJHS) kinetic scheme, which has been used to model dendritic channels in cortical neurons, and the classical Hodgkin-Huxley (1952) (HH) kinetic scheme for the squid giant axon. We compute the magnitudes, amplitude distributions, and power spectral densities of the voltage noise in isopotential membrane patches predicted by these kinetic schemes. For both schemes, noise magnitudes increase rapidly with depolarization from rest. Noise is larger for smaller patch areas but is smaller for increased model temperatures. We contrast the results from Monte Carlo simulations of the stochastic nonlinear kinetic schemes with analytical, closed-form expressions derived using passive and quasi-active linear approximations to the kinetic schemes. For all subthreshold voltage ranges, the quasi-active linearized approximation is accurate within 8% and may thus be used in large-scale simulations of realistic neuronal geometries.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008967807741
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  • 19
    Electronic Resource
    Electronic Resource
    Analog hardware for detecting discontinuities in early vision (1990)
    Springer
    International journal of computer vision 4 (1990), S. 211-223 
    Details
    ISSN: 1573-1405
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The detection of discontinuities in motion, intensity, color, and depth is a well-studied but difficult problem in computer vision [6]. We discuss the first hardware circuit that explicitly implements either analog or binary line processes in a deterministic fashion. Specifically, we show that the processes of smoothing (using a first-order or membrane type of stabilizer) and of segmentation can be implemented by a single, two-terminal nonlinear voltage-controlled resistor, the “resistive fuse”; and we derive its current-voltage relationship from a number of deterministic approximations to the underlying stochastic Markov random fields algorthms. The concept that the quadratic variation functionals of early vision can be solved via linear resistive networks minimizing power dissipation [37] can be extended to non-convex variational functionals with analog or binary line processes being solved by nonlinear resistive networks minimizing the electrical co-content. We have successfully designed, tested, and demonstrated an analog CMOS VLSI circuit that contains a 1D resistive network of fuses implementing piecewise smooth surface interpolation. We furthermore demonstrate the segmenting abilities of these analog and deterministic “line processes” by numerically simulating the nonlinear resistive network computing optical flow in the presence of motion discontinuities. Finally, we discuss various circuit implementations of the optical flow computation using these circuits.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00054996
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  • 20
    Electronic Resource
    Electronic Resource
    Computing optical flow across multiple scales: An adaptive coarse-to-fine strategy (1991)
    Springer
    International journal of computer vision 6 (1991), S. 133-145 
    Details
    ISSN: 1573-1405
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Single-scale approaches to the determination of the optical flow field from the time-varying brightness pattern assume that spatio-temporal discretization is adequate for representing the patterns and motions in a scene. However, the choice of an appropriate spatial resolution is subject to conflicting, scene-dependent, constraints. In intensity-base methods for recovering optical flow, derivative estimation is more accurate for long wavelengths and slow velocities (with respect to the spatial and temporal discretization steps). On the contrary, short wavelengths and fast motions are required in order to reduce the errors caused by noise in the image acquisition and quantization process. Estimating motion across different spatial scales should ameliorate this problem. However, homogeneous multiscale approaches, such as the standard multigrid algorithm, do not improve this situation, because an optimal velocity estimate at a given spatial scale is likely to be corrupted at a finer scale. We propose an adaptive multiscale method, where the discretization scale is chosen locally according to an estimate of the relative error in the velocity estimation, based on image properties. Results for synthetic and video-acquired images show that our coarse-to-fine method, fully parallel at each scale, provides substantially better estimates of optical flow than do conventional algorithms, while adding little computational cost.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00128153
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