poldrack_rodriguez_neuron_2003

poldrack_rodriguez_neuron_2003 - Previews 891 at various...

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Previews 891 at various positions in the apical dendritic tree of CA1 blocks of the nervous system—could process informa- tion. It also leaves open several questions. As noted by pyramids (Cash and Yuste, 1999). In addition to such pairs of inputs, high-frequency synaptic stimulation the authors themselves, it will be interesting to know if their results generalize beyond mean firing rate aver- trains were also investigated. The results suggest that linear summation of excitatory postsynaptic potentials aged over 250 ms, the neuronal output variable pre- dicted in their simulations. It is likely that in many cases at the soma—as reported by Cash and Yuste—could be compatible with strong nonlinear summation when processing of sensory information occurs on a faster timescale. An extension of their results would allow us several inputs are activated simultaneously in a single dendritic branch in the presence of active membrane to address such situations as well. Another challenge is to investigate whether such reductions can be obtained conductances. In the authors’ simulations and data analysis, nonlinear summation was most evident in the directly from experimental data. Pyramidal cells might not be the neuron type most easily amenable to testing, dendritic membrane potential recorded at the site of stimulation but could also be detected in the somatic since it is currently difficult to selectively stimulate single synaptic inputs at different positions in their dendritic membrane potential. An experimental verification of these predictions using similar methods as in Cash and tree and to simultaneously monitor dendritic integration. The method should however be applicable to other neu- Yuste (1999) should therefore be possible. An alternative but technically more difficult approach would be to di- rons where computational dendritic subunits are thought to exist and where integration of synaptic inputs rectly stimulate two distinct presynaptic inputs and re- cord from the postsynaptic target neuron as in Tamas across the cell could be nonlinear (Egelhaaf et al., 2002). In this context, the authors’ method should provide a et al. (2002). Poirazi et al. go on to show that summation of inputs distributed across more distant branches in useful complement to traditional compartmental model- ing methods in understanding dendritic integration and their model follows a much more linear characteristic. These results set the stage for the reductionist ap- the relative role played by various dendritic branches and conductances in this process. Finally, one would proach exposed in the second article (Poirazi et al., 2003b). The authors postulate that individual inputs sum like to relate the properties of the synaptic weights, a i , to aspects of computing performed by single neurons linearly within a dendritic branch before being trans- formed by a sigmoidal transfer function s ( ) similar in and, ideally, compare their values among neurons per- forming different computations on identical inputs. shape to nonlinear branch summation described above.
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poldrack_rodriguez_neuron_2003 - Previews 891 at various...

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