Assessment of the excitation-inhibition ratio in the Fmr1 KO2 mouse using neuronal oscillation dynamics.

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fragile X Messenger Ribonucleoprotein 1 (Fmr1) knockout mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional excitation-inhibition ratio from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic excitation-inhibition disturbances translate to disturbances in network physiology in the Fragile X Messenger Ribonucleoprotein 1 (Fmr1) gene knockout model. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioral condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the functional excitation-inhibition biomarker, long-range temporal correlations, and spectral power. We corroborated earlier studies showing increased high-frequency power in Fragile X Messenger Ribonucleoprotein 1 (Fmr1) knockout mice. Long-range temporal correlations were higher in the gamma frequency ranges. Contrary to expectations, functional excitation-inhibition was lower in the knockout mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the Gamma-aminobutyric acid (GABA)-agonist clonazepam decreased the functional excitation-inhibition in both genotypes, confirming that increasing inhibitory tone results in a reduction of functional excitation-inhibition. In addition, clonazepam decreased electroencephalogram power and increased long-range temporal correlations in both genotypes. These findings show applicability of these new resting-state electroencephalogram biomarkers to animal for translational studies and allow investigation of the effects of lower-level disturbances in excitation-inhibition balance.

The effects of social environment on AD-related pathology in hAPP-J20 mice and tau-P301L mice.

In humans, social factors (e.g., loneliness) have been linked to the risk of developing Alzheimer's Disease (AD). To date, AD pathology is primarily characterized by amyloid-ß plaques and tau tangles. We aimed to assess the effect of single- and group-housing on AD-related pathology in a mouse model for amyloid pathology (J20, and WT controls) and a mouse model for tau pathology (P301L) with and without seeding of synthetic human tau fragments (K18). Female mice were either single housed (SH) or group housed (GH) from the age of 6-7 weeks onwards. In 12-week-old P301L mice, tau pathology was induced through seeding by injecting K18 into the dorsal hippocampus (P301LK18), while control mice received a PBS injection (P301LPBS). P301L mice were sacrificed at 4 months of age and J20 mice at 10 months of age. In all mice brain pathology was histologically assessed by examining microglia, the CA1 pyramidal cell layer and specific AD pathology: analysis of plaques in J20 mice and tau hyperphosphorylation in P301L mice. Contrary to our expectation, SH-J20 mice interestingly displayed fewer plaques in the hippocampus compared to GH-J20 mice. However, housing did not affect tau hyperphosphorylation at Ser202/Thr205 of P301L mice, nor neuronal cell death in the CA1 region in any of the mice. The number of microglia was increased by the J20 genotype, and their activation (based on cell body to cell size ratio) in the CA1 was affected by genotype and housing condition (interaction effect). Single housing of P301L mice was linked to the development of stereotypic behavior (i.e. somersaulting and circling behavior). In P301LK18 mice, an increased number of microglia were observed, among which were rod microglia. Taken together, our findings point to a significant effect of social housing conditions on amyloid plaques and microglia in J20 mice and on the development of stereotypic behavior in P301L mice, indicating that the social environment can modulate AD-related pathology.

Assessment of Social Behavior Using a Passive Monitoring App in Cognitively Normal and Cognitively Impaired Older Adults: Observational Study.

BACKGROUND: In people with cognitive impairment, loss of social interactions has a major impact on well-being. Therefore, patients would benefit from early detection of symptoms of social withdrawal. Current measurement techniques such as questionnaires are subjective and rely on recall, in contradiction to smartphone apps, which measure social behavior passively and objectively. OBJECTIVE: This study uses the remote monitoring smartphone app Behapp to assess social behavior, and aims to investigate (1) the association between social behavior, demographic characteristics, and neuropsychiatric symptoms in cognitively normal (CN) older adults, and (2) if social behavior is altered in cognitively impaired (CI) participants. In addition, we explored in a subset of individuals the association between Behapp outcomes and neuropsychiatric symptoms. METHODS: CN, subjective cognitive decline (SCD), and CI older adults installed the Behapp app on their own Android smartphone for 7 to 42 days. CI participants had a clinical diagnosis of mild cognitive impairment (MCI) or Alzheimer-type dementia. The app continuously measured communication events, app use and location. Neuropsychiatric Inventory (NPI) total scores were available for 20 SCD and 22 CI participants. Linear models were used to assess group differences on Behapp outcomes and to assess the association of Behapp outcomes with the NPI. RESULTS: We included CN (n=209), SCD (n=55) and CI (n=22) participants. Older cognitively normal participants called less frequently and made less use of apps (P<.05). No sex effects were found. Compared to the CN and SCD groups, CI individuals called less unique contacts (ß=-0.7 [SE 0.29], P=.049) and contacted the same contacts relatively more often (ß=0.8 [SE 0.25], P=.004). They also made less use of apps (ß=-0.83 [SE 0.25], P=.004). Higher total NPI scores were associated with further traveling (ß=0.042 [SE 0.015], P=.03). CONCLUSIONS: CI individuals show reduced social activity, especially those activities that are related to repeated and unique behavior, as measured by the smartphone app Behapp. Neuropsychiatric symptoms seemed only marginally associated with social behavior as measured with Behapp. This research shows that the Behapp app is able to objectively and passively measure altered social behavior in a cognitively impaired population.