Gamma oscillations are thought to play a key role in neuronal network function and neuronal communication, yet the underlying generating mechanisms have not been fully elucidated to date. At least partly, this may be due to the fact that even in simple network models of interconnected inhibitory (I) and excitatory (E) neurons, many parameters remain unknown and are set based on practical considerations or by convention. Here, we mitigate this problem by requiring PING (Pyramidal Interneuron Network Gamma) models to simultaneously satisfy a broad set of criteria for realistic behaviour based on empirical data spanning both the single unit (spikes) and local population (LFP) levels while unknown parameters are varied. By doing so, we were able to constrain the parameter ranges and select empirically valid models. The derived model constraints implied weak rather than strong PING as the generating mechanism for gamma, connectivity between E and I neurons within specific bounds, and variations of the external input to E but not I neurons. Constrained models showed valid behaviours, including gamma frequency increases with contrast and power saturation or decay at high contrasts. Using an empirically-validated model we studied the route to gamma instability at high contrasts. This involved increased heterogeneity of E neurons with increasing input triggering a breakdown of I neuron pacemaker function. Further, we illustrate the model's capacity to resolve disputes in the literature concerning gamma oscillation properties and GABA conductance proxies. We propose that the models derived in our study will be useful for other modelling studies, and that our approach to the empirical constraining of PING models can be expanded when richer empirical datasets become available. As local gamma networks are the building blocks of larger networks that aim to understand complex cognition through their interactions, there is considerable value in improving our models of these building blocks.

Alzheimer's disease (AD) involves not only progressive memory and cognition deficits but also motor impairments, including disturbed balance and activity levels and gait dysfunction. We examined age-related changes in fine motor skills of an Alzheimer's mouse model, the transgenic 5xFAD, from 3 to 9 months of age (3 M, 9 M), using a battery of behavioral tests including the rotarod for motor coordination and balance, balance beam test for fine motor precision and coordination, and single-pellet reaching test for forelimb dexterity. Rotarod test showed that 9 M 5xFAD mice displayed mild motor coordination deficits, spending less time on the rod and falling at lower speeds than 9 M WT mice. In the balance beam test, 9 M 5xFAD mice exhibited significantly slower traversal times compared to other groups and demonstrated frequent foot slips and dragging behavior with more pronounced effects on the narrower beam. The single-pellet reaching test revealed impaired fine limb movements in 9 M 5xFAD mice, with reduced success rates and slower speed than the other groups. This study showed that 9 M 5xFAD mice exhibited the most impaired performance at each assay in an age-dependent manner, suggesting that the accumulation of the underlying AD-related pathology affects motor function, extending even to fine motor skills.