Abstract (may include machine translation)
The trajectory of the somatic membrane potential of a cortical neuron exactly reflects the computations performed on its afferent inputs. However, the spikes of such a neuron are a very low-dimensional and discrete projection of this continually evolving signal. We explored the possibility that the neuronĝ€2s efferent synapses perform the critical computational step of estimating the membrane potential trajectory from the spikes. We found that short-term changes in synaptic efficacy can be interpreted as implementing an optimal estimator of this trajectory. Short-term depression arose when presynaptic spiking was sufficiently intense as to reduce the uncertainty associated with the estimate; short-term facilitation reflected structural features of the statistics of the presynaptic neuron such as up and down states. Our analysis provides a unifying account of a powerful, but puzzling, form of plasticity.
Original language | English |
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Pages (from-to) | 1271-1275 |
Number of pages | 5 |
Journal | Nature Neuroscience |
Volume | 13 |
Issue number | 10 |
DOIs | |
State | Published - Oct 2010 |
Externally published | Yes |