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  • 1
    Electronic Resource
    Electronic Resource
    A neural network model for texture discrimination (1993)
    Springer
    Biological cybernetics 69 (1993), S. 97-108 
    Details
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract A model of texture discrimination in visual cortex was built using a feedforward network with lateral interactions among relatively realistic spiking neural elements. The elements have various membrane currents, equilibrium potentials and time constants, with action potentials and synapses. The model is derived from the modified programs of MacGregor (1987). Gabor-like filters are applied to overlapping regions in the original image; the neural network with lateral excitatory and inhibitory interactions then compares and adjusts the Gabor amplitudes in order to produce the actual texture discrimination. Finally, a combination layer selects and groups various representations in the output of the network to form the final transformed image material. We show that both texture segmentation and detection of texture boundaries can be represented in the firing activity of such a network for a wide variety of synthetic to natural images. Performance details depend most strongly on the global balance of strengths of the excitatory and inhibitory lateral interconnections. The spatial distribution of lateral connective strengths has relatively little effect. Detailed temporal firing activities of single elements in the lateral connected network were examined under various stimulus conditions. Results show (as in area 17 of cortex) that a single element's response to image features local to its receptive field can be altered by changes in the global context.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00226193
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  • 2
    Electronic Resource
    Electronic Resource
    Rectification of correlation by a sigmoid nonlinearity (1994)
    Springer
    Biological cybernetics 70 (1994), S. 219-225 
    Details
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract We investigated the normalized autocovariance (correlation coefficient) function of the output of an erf( ) function nonlinearity subject to non-zero mean Gaussian noise input. When the sigmoid is wide compared to the input, or the input mean is close to the midpoint of the sigmoid, the output correlation coefficient function is very close to the input correlation coefficient function. When the noise mean and variance are such that there is a significant probability of operating in the saturation region and the sigmoid is not too flat, the correlation coefficient of the output function is less than that of the input. This difference is much greater when the correlation coefficient is negative than when it is positive. The sigmoid partially rectifies the correlation coefficient function. The analysis does not depend on the spectral properties of the input noise. All that is required is that the input at times t and (t + τ) be jointly gaussian with the same mean and autocovariance. The analysis therefore applies equally well to the case of two identical sigmoids with jointly gaussian inputs. This correlational rectification could help explain the parameter sensitivity of “neural network” models. If biological neurons share this property it could explain why few negative correlations between spike trains-have been observed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00197602
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  • 3
    Electronic Resource
    Electronic Resource
    Rectification of correlation by a sigmoid nonlinearity (1994)
    Springer
    Biological cybernetics 70 (1994), S. 219-225 
    Details
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract. We investigated the normalized autocovariance (correlation coefficient) function of the output of an erf( ) function nonlinearity subject to non-zero mean Gaussian noise input. When the sigmoid is wide compared to the input, or the input mean is close to the midpoint of the sigmoid, the output correlation coefficient function is very close to the input correlation coefficient function. When the noise mean and variance are such that there is a significant probability of operating in the saturation region and the sigmoid is not too flat, the correlation coefficient output function is less than that of the input. This difference is much greater when the correlation coefficient is negative than when it is positive. The sigmoid partially rectifies the correlation coefficient function. The analysis does not depend on the spectral properties of the input noise. All that is required is that the input at times t and (t+τ) be jointly Gaussian with the same mean and autocovariance. The analysis therefore applies equally well to the case of two identical sigmoids with jointly Gaussian inputs. This correlational rectification could help explain the parameter sensitivity of "neural network" models. If biological neurons share this property it could explain why few negative correlations between spike trains have been observed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s004220050026
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  • 4
    Electronic Resource
    Electronic Resource
    A Feedback Model of Attention and Context Dependence in Visual Cortical Networks (1999)
    Springer
    Journal of computational neuroscience 7 (1999), S. 255-267 
    Details
    ISSN: 1573-6873
    Keywords: attention vision cortex model
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract We have modeled biologically realistic neural networks that may be involved in contextual modulation of stimulus responses, as reported in the neurophysiological experiments of Motter (1994a, 1994b) (Journal of Neuroscience, 14:2179–2189 and 2190–2199). The networks of our model are structured hierarchically with feedforward, feedback, and lateral connections, totaling several thousand cells and about 300,000 synapses. The contextual modulation, arising from attention cues, is explicitly modeled as a feedback signal coming from the highest-order cortical network. The feedback signal arises from mutually inhibitory neurons with different stimulus preferences. Although our model is probably the simplest one consistent with available anatomical and physiological evidence and ignores the complexities that may exist in high-level cortical networks such as the prefrontal cortex, it reproduces the experimental results quite well and offers some guidance for future experiments. We also report the unexpected observation of 40 Hz oscillations in the model.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008923203424
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  • 5
    Electronic Resource
    Electronic Resource
    Reflex pathways of the crayfish claw (1976)
    Springer
    Journal of comparative physiology 107 (1976), S. 309-326 
    Details
    ISSN: 1432-1351
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Summary Efferent and sensory axons were monitored near the carpopoditepropodite joint of the crayfish (Procambarus clarkii) cheliped using en passant suction electrodes. Controlled movements were imposed by an electric motor; tactile stimulation was delivered either manually or with electrically controlled mechanical probes. Statistical spike train analysis methods were used to study correlated firing among the observed neurons. We find that individual spikes in proprioceptive afferents have a strong excitatory effect on OI and CE, probably through a monosynaptic connection. These relationships are observed for proprioceptive axons that are active during claw opening or closing, or that are tonically active when the claw is motionless. Conversely, individual OE or OI spikes exert excitatory or inhibitory (respectively) effects on the firing of proprioceptive units sensitive to claw opening. This suggests that individual efferent spikes can produce enough change in claw position to modulate proprioceptive responses. Tactile afferents also excited OI and CE strongly and directly.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00656740
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  • 6
    Electronic Resource
    Electronic Resource
    Feature-linked synchronization of thalamic relay cell firing induced by feedback from the visual cortex (1994)
    [s.l.] : Nature Publishing Group
    Nature 369 (1994), S. 479-482 
    Details
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Figure 1 illustrates the essence of our approach and shows feedback connections from a cell in layer VI of the visual cortex to relay cells in the dorsal lateral geniculate nucleus (dLGN), the thalamic nucleus relaying the retinal input to the cortex. The key prediction is that when the ...
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1038/369479a0
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  • 7
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    A neural network model for texture discrimination (1993)
    Springer
    Details
    Publication Date: 1993-06-01
    Print ISSN: 0340-1200
    Electronic ISSN: 1432-0770
    Topics: Biology , Computer Science , Physics
    Published by Springer
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  • 8
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    Rectification of correlation by a sigmoid nonlinearity (1994)
    Springer
    Details
    Publication Date: 1994-01-01
    Print ISSN: 0340-1200
    Electronic ISSN: 1432-0770
    Topics: Biology , Computer Science , Physics
    Published by Springer
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  • 9
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    Rectification of correlation by a sigmoid nonlinearity (1994)
    Springer
    Details
    Publication Date: 1994-01-01
    Print ISSN: 0340-1200
    Electronic ISSN: 1432-0770
    Topics: Biology , Computer Science , Physics
    Published by Springer
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  • 10
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    Feature-linked synchronization of thalamic relay cell firing induced by feedback from the visual cortex (1994)
    Springer Nature
    Details
    Publication Date: 1994-06-01
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Published by Springer Nature
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