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  • 1
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Group
    Nature 373 (1995), S. 563-564 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] OF the many secrets that each of us carries in our brains, the one that we would all dearly love to know is how we remember things. How is it that Music, when soft voices die,/ Vibrates in the memory? How do we instantly pick out the individual face of a friend in a crowd, identify the aroma ...
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Group
    Nature 377 (1995), S. 683-684 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] ANIMALS must learn a substantial part of their behavioural repertoire through trial and error interactions with a dynamic and uncertain environment. A simple neural substrate for such a learning process is described in a paper by Montague and colleagues that appears elsewhere in this issue ...
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Group
    Nature 379 (1996), S. 584-585 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] IT is a truth universally acknowledged that, to survive, living organisms are in need of accurate information about their world. This information is collected by a dazzling array of specialized receptors that transduce the stimulus energy, whether it be light, pressure, tension, heat, chemical or ...
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Journal of computational neuroscience 2 (1995), S. 63-82 
    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
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Journal of neurocytology 25 (1996), S. 893-911 
    ISSN: 1573-7381
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine
    Notes: Summary The synapse, first introduced as a physiological hypothesis by C. S. Sherrington at the close of the nineteenth century, has, 100 years on, become the nexus for anatomical and functional investigations of interneuronal communication. A number of hypotheses have been proposed that give local synaptic interactions specific roles in generating an algebra or logic for computations in the neocortex. Experimental work, however, has provided little support for such schemes. Instead, both structural and functional studies indicate that characteristically cortical functions, e. g., the identification of the motion or orientation of objects, involve computations that must be achieved with high accuracy through the collective action of hundreds or thousands of neurons connected in recurrent microcircuits. Some important principles that emerge from this collective action can effectively be captured by simple electronic models. More detailed models explain the nature of the complex computations performed by the cortical circuits and how the computations remain so remarkably robust in the face of a number of sources of noise, including variability in the anatomical connections, large variance in the synaptic responses and in the tria-to-trial output of single neurons, and weak or degraded input signals.
    Type of Medium: Electronic Resource
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