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PLoS One. 2012;7(8):e41806.
A novel phase portrait for neuronal excitability.
Drion G, Franci A, Seutin V, Sepulchre R.
Abstract
Fifty years ago, FitzHugh introduced a phase portrait that became famous for a twofold
reason: it captured in a physiological way the qualitative behavior of Hodgkin-Huxley model
and it revealed the power of simple dynamical models to unfold complex fring patterns. To
date, in spite of the enormous progresses in qualitative and quantitative neural modeling, this
phase portrait has remained a core picture of neuronal excitability. Yet, a major diference
between the neurophysiology of 1961 and of 2011 is the recognition of the prominent role
of calcium channels in fring mechanisms. We show that including this extra current in Hodgkin-
Huxley dynamics leads to a revision of FitzHugh-Nagumo phase portrait that afects in a fun-
damental way the reduced modeling of neural excitability. The revisited model considerably
enlarges the modeling power of the original one. In particular, it captures essential electro-
physiological signatures that otherwise require non-physiological alteration or considerable
complexifcation of the classical model. As a basic illustration, the new model is shown to
highlight a core dynamical mechanism by which calcium channels control the two distinct
fring modes of thalamocortical neurons.
PLoS One. 2012;7(1):e29594.
Lower-order efects adjustment in quantitative
traits model-based multifactor dimensionality
reduction.
Mahachie John JM, Cattaert T, Lishout FV, Gusareva ES, Steen KV.
Abstract
Identifying gene-gene interactions or gene-environment interactions in studies of human
complex diseases remains a big challenge in genetic epidemiology. An additional chal-
lenge, often forgotten, is to account for important lower-order genetic efects. These may
hamper the identifcation of genuine epistasis. If lower-order genetic efects contribute to
the genetic variance of a trait, identifed statistical interactions may simply be due to a signal
boost of these efects. In this study, we restrict attention to quantitative traits and bi-allelic
SNPs as genetic markers. Moreover, our interaction study focuses on 2-way SNP-SNP interac-
tions. Via simulations, we assess the performance of diferent corrective measures for lower-
order genetic efects in Model-Based Multifactor Dimensionality Reduction epistasis detec-
tion, using additive and co-dominant coding schemes. Performance is evaluated in terms of
power and familywise error rate. Our simulations indicate that empirical power estimates are
reduced with correction of lower-order efects, likewise familywise error rates. Easy-to-use
automatic SNP selection procedures, SNP selection based on «top» fndings, or SNP selec-
tion based on p-value criterion for interesting main efects result in reduced power but also
almost zero false positive rates. Always accounting for main efects in the SNP-SNP pair under
investigation during Model-Based Multifactor Dimensionality Reduction analysis adequately
controls false positive epistasis fndings. This is particularly true when adopting a co-domi-
nant corrective coding scheme. In conclusion, automatic search procedures to identify lower-
order efects to correct for during epistasis screening should be avoided. The same is true for
procedures that adjust for lower-order efects prior to Model-Based Multifactor Dimensio-
nality Reduction and involve using residuals as the new trait. We advocate using «on-the-fy»
lower-order efects adjusting when screening for SNP-SNP interactions using Model-Based
Multifactor Dimensionality Reduction analysis.