Models of Tau pathology related to frontotemporal dementia (FTD) are essential to determine underlying neurodegenerative pathologies and resulting Tauopathy relevant behavioural changes. However, existing models are often limited in their translational value due to Tau overexpression, and the frequent occurrence of motor deficits which prevent comprehensive behavioural assessments. In order to address these limitations, a forebrain-specific (CaMKIIα promoter), human mutated Tau (hTauP301L+R406W) knock-in mouse was generated out of the previously characterised PLB1Triple mouse, and named PLB2Tau. After confirmation of an additional hTau species (~60 kDa) in forebrain samples, we identified age-dependent progressive Tau phosphorylation which coincided with the emergence of FTD relevant behavioural traits. In line with the noncognitive symptomatology of FTD, PLB2Tau mice demonstrated early emerging (~ 6 months) phenotypes of heightened anxiety in the elevated plus maze, depressive/apathetic behaviour in a sucrose preference test and generally reduced exploratory activity in the absence of motor impairments. Investigations of cognitive performance indicated prominent dysfunctions in semantic memory, as assessed by social transmission of food preference, and in behavioural flexibility during spatial reversal learning in a homecage corner-learning task. Spatial learning was only mildly affected and task-specific, with impairments at 12-month of age in the corner learning but not in the water maze task. Electroencephalographic (EEG) investigations indicated a vigilance-stage specific loss of alpha power during wakefulness at both parietal and prefrontal recording sites, and site-specific EEG changes during nonrapid eye movement sleep (prefrontal) and rapid eye movement sleep (parietal). Further investigation of hippocampal electrophysiology conducted in slice preparations indicated a modest reduction in efficacy of synaptic transmission in the absence of altered synaptic plasticity. Together, our data demonstrate that the transgenic PLB2Tau mouse model presents with striking behavioural and physiological face validity relevant for FTD, driven by the low level expression of mutant FTD hTau. AbstractModels of Tau pathology related to frontotemporal dementia (FTD) are essential to determine underlying neurodegenerative pathologies and resulting Tauopathy relevant behavioural changes. However, existing models are often limited in their translational value due to Tau overexpression, and the frequent occurrence of motor deficits which prevent comprehensive behavioural assessments. In order to address these limitations, a forebrain-specific (CaMKIIα promoter), human mutated Tau (hTau P301L+R406W ) knock-in mouse was generated out of the previously characterised PLB1 Triple mouse, and named PLB2 Tau . After confirmation of an additional hTau species (~60 kDa) in forebrain samples, we identified age-dependent progressive Tau phosphorylation which was coincided with the emergence of FTD relevant behavioural traits. In...

Electroencephalography (EEG) records fast-changing neuronal signalling and communication and thus can offer a deep understanding of cognitive processes. However, traditional data analyses which employ the Fast-Fourier Transform (FFT) have been of limited use as they do not allow time- and frequency-resolved tracking of brain activity and detection of directional connectivity. Here, we applied advanced qEEG tools using autoregressive (AR) modelling, alongside traditional approaches, to murine data sets from common research scenarios: (a) the effect of age on resting EEG; (b) drug actions on non-rapid eye movement (NREM) sleep EEG (pharmaco-EEG); and (c) dynamic EEG profiles during correct vs incorrect spontaneous alternation responses in the Y-maze. AR analyses of short data strips reliably detected age- and drug-induced spectral EEG changes, while renormalized partial directed coherence (rPDC) reported direction- and time-resolved connectivity dynamics in mice. Our approach allows for the first time inference of behaviour- and stage-dependent data in a time- and frequency-resolved manner, and offers insights into brain networks that underlie working memory processing beyond what can be achieved with traditional methods.

No abstract