Improved biological plausibility
- In cortical neural networks, connections from a given neuron are either inhibitory
or excitatory, but not both. This observation is called Dale's Principle. This constraint is often ignored by theoreticians
who build models of these systems. Using the NEF, we have developed a general
solution to the problem of converting such unrealistic network models into
biologically plausible models that respect this constraint. The work is described in this paper.
Generalized neural dynamics
- We extended the NEF to allow us to show that the precise pattern of irregularity in neural spike patterns
contains information beyond that contained in mean firing rates.
We used the NEF to show that an ensemble
of neurons firing at a constant mean rate can induce arbitrarily
chosen temporal current patterns in postsynaptic cells.
These results describe an unrestrictive set
of conditions in which postsynaptic cells might exploit virtually any
information contained in spike timing. In short we show how this
capability may underlie an extension of the NEF to a more dynamic temporal domain than originally assumed. The details of this work are in this paper.