Statistical independence and neural computation in the leech ganglion |
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Authors: | Giulietta Pinato Stefano Battiston Vincent Torre |
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Institution: | (1) INFM, Unita' di Trieste, c/o SISSA, Trieste, Italy, IT;(2) SISSA, Via Beirut 2, Trieste, Italy, IT |
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Abstract: | In this report, the input/output relations in an isolated ganglion of the leech Hirudo medicinalis were studied by simultaneously using six or eight suction pipettes and two intracellular electrodes. Sensory input was mimicked
by eliciting action potentials in mechanosensory neurons with intracellular electrodes. The integrated neural output was measured
by recording extracellular voltage signals with pipettes sucking the roots and the connectives. A single evoked action potential
activated electrical activity in at least a dozen different neurons, some of which were identified. This electrical activity
was characterized by a high degree of temporal and spatial variability. The action potentials of coactivated neurons, i.e.
activated by the same mechanosensory neuron, did not show any significant pairwise correlation. Indeed, the analysis of evoked
action potentials indicates clear statistical independence among coactivated neurons, presumably originating from the independence
of synaptic transmission at distinct synapses. This statistical independence may be used to increase reliability when neuronal
activity is averaged or pooled. It is suggested that statistical independence among coactivated neurons may be a usual property
of distributed processing of neuronal networks and a basic feature of neural computation.
Received: 20 September 1999 / Accepted in revised form: 3 March 2000 |
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