Temporal dynamics from fMRI in genetic frontotemporal dementias --------------------------------------------------------------- The brain balances integration and segregation of neural assemblies, with dynamic information processing, connectivity and regional specialisation. The dynamic nature of network connectivity has been shown to be important in health, with changes observed in diverse neurological and neuropsychiatric disorders. In this study, we consider the cognitive and behavioural syndrome of Frontotemporal Dementia (FTD). The behavioural variant of frontotemporal dementia impairs executive function, with disinhibition, cognitive inflexibility and poor set-shifting that together suggest altered temporal dynamics and stability. Static connectivity is severely impaired in symptomatic FTD (Seeley et al., 2009), but in presymptomatic familial FTD, there is preservation of static connectivity graph properties despite significant neurodegeneration 10 or more years before expected symptom onset (Rittman et al., 2019). Hidden Markov models can identify dynamic brain activity, as a finite number of mutually exclusive states between which the brain switches over time (Vidaurre et al., 2017). While these states are inferred at a group level, information about the sequence and timing in which an individual moves between states can be estimated. This approach allows quantification of network dynamics even for large data sets in a computationally efficient manner. This study has two parts. First an exploratory analysis undertaken pre-registration. Second, a confirmatory study in an independent dataset that will be conducted after registration. We have assessed dynamic connectivity using task-free functional magnetic resonance imaging (fMRI) of people with behavioural variant Frontotemporal Dementia (bvFTD n=38) and healthy controls (n=34) at the Cambridge Centre for Frontotemporal Dementia. Using hidden Markov models we found the following: • The rate of switching between states is reduced in bvFTD, compared to controls • People with bvFTD spend more time than healthy controls in high frequency states (particularly components of the salience and default mode networks) and less time in less-accessed states, including executive and attentional networks. • The pattern of state occupancy seen in bvFTD, as identified by a principal component analysis of all states over all participants, correlated with clinical severity (Frontal Assessment Battery and revised Addenbrooke's Cognitive Examination) Using these results to frame our hypotheses, we will next analyse data from the Genetic Frontotemporal Dementia Initiative (GENFI). GENFI is a longitudinal international study following people in families affected by FTD as a result of known mutations (C9ORF72, MAPT, GRN) (Rohrer et al., 2015). This dataset (GENFI data freeze 5) provides an opportunity to investigate how dynamic connectivity varies throughout during the course of the disease, including the long presymptomatic phase. We make the following hypotheses: **In symptomatic participants** • Switching rates are reduced in people with familial FTD • People with familial FTD spend more time in high frequency states (components of the salience and default mode network) and less time in states that represent a smaller proportion of state occupancy (including executive and attentional networks) compared to than non-mutation carriers • Changes in fractional occupancy correlate with 1) neuropsychological deficits and 2) carer assessed measures of impairment • Patterns of fractional occupancy differ by mutation type **In presymptomatic mutation carriers** • Presymptomatic mutation carriers (versus non-mutation carriers) will have abnormal switching rates, fractional occupancy and dwell time as a function of proximity to onset as denoted by 1) Expected Years until Onset (in MAPT carriers) and 2) age (in other mutations).