  Directional detection is the only strategy for the unambiguous identification
of galactic Dark Matter (DM) even in the presence of an irreducible background
such as beyond the neutrino floor. This approach requires measuring the
direction of a DM-induced nuclear recoil in the keV-range. To probe such low
energies, directional detectors must operate at high gain where 3D track
reconstruction can be distorted by the influence of the numerous ions produced
in the avalanches. The article describes the interplay between electrons and
ions during signal formation in a Micromegas. It introduces SimuMimac, a
simulation tool dedicated to high gain detection that agrees with MIMAC
measurements. This work proposes an analytical formula to deconvolve the ionic
signal induced on the grid from any measurements, with no need for prior nor ad
hoc parameter. This deconvolution is experimentally tested and validated,
revealing the fine structure of the primary electrons cloud and consequently
leading to head-tail recognition in the keV-range. Finally, the article
presents how this deconvolution can be used for directionality by
reconstructing the spectra of mono-energetic $27~\mathrm{keV}$ and
$8~\mathrm{keV}$ neutrons with an angular resolution better than $15^\circ$.
This novel approach for directionality appears as complementary to the standard
one from 3D tracks reconstruction and offers redundancy for improving
directional performances at high gain in the keV region.
