Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory
  and Inhibitory Neurons   Excitation-inhibition (E-I) balance is ubiquitously observed in the cortex.
Recent studies suggest an intriguing link between balance on fast timescales,
tight balance, and efficient information coding with spikes. We further this
connection by taking a principled approach to optimal balanced networks of
excitatory (E) and inhibitory (I) neurons. By deriving E-I spiking neural
networks from greedy spike-based optimizations of constrained minimax
objectives, we show that tight balance arises from correcting for deviations
from the minimax optima. We predict specific neuron firing rates in the network
by solving the minimax problem, going beyond statistical theories of balanced
networks. Finally, we design minimax objectives for reconstruction of an input
signal, associative memory, and storage of manifold attractors, and derive from
them E-I networks that perform the computation. Overall, we present a novel
normative modeling approach for spiking E-I networks, going beyond the
widely-used energy minimizing networks that violate Dale's law. Our networks
can be used to model cortical circuits and computations.

35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
1
The categories of this paper are: cs
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat