  We present a collated set of algorithms to obtain objective measures of
synchronisation in brain time-series data. The algorithms are implemented in
MATLAB; we refer to our collated set of 'tools' as SyncBox. Our motivation for
SyncBox is to understand the underlying dynamics in an existing population
neural network, commonly referred to as neural mass models, that mimic Local
Field Potentials of the visual thalamic tissue. Specifically, we aim to measure
the phase synchronisation objectively in the model response to periodic
stimuli; this is to mimic the condition of
Steady-state-visually-evoked-potentials (SSVEP), which are scalp
Electroencephalograph (EEG) corresponding to periodic stimuli. We showcase the
use of SyncBox on our existing neural mass model of the visual thalamus.
Following our successful testing of SyncBox, it is currently being used for
further research on understanding the underlying dynamics in enhanced neural
networks of the visual pathway
