Detrended fluctuation analysis of amygdala-hippocampal beta synchrony reveals network rigidity in depression associated with temporal lobe epilepsy

Abstract Objective . Depressive symptoms are common in individuals with temporal lobe epilepsy (TLE), yet the network dynamics linking limbic circuitry to mood disturbance in TLE remain poorly understood. Here, we investigated whether the temporal organization of amygdala-hippocampal beta synchrony reflects depressive symptom burden in individuals with TLE undergoing intracranial EEG (iEEG) monitoring. Approach . We analyzed iEEG recordings from 14 adults with TLE who underwent intracranial monitoring as part of routine pre-surgical evaluation. Dynamic functional connectivity (dFC) in the beta band was calculated between the amygdala and the hippocampus, and the temporal structure of the dFC was quantified using detrended fluctuation analysis. Random permutation of epochs was performed to assess the influence of interictal epileptiform discharges (IEDs) on the network dynamics. We additionally extracted the ultra-slow fluctuations in dFC and assessed whether the timing of the IEDs was phase-locked to these ultra-slow rhythms. Main results . TLE patients with depression exhibited higher α than non-depressed TLE subjects ( P = 0.007), indicating greater temporal persistence of limbic beta synchrony. Across individuals, α was positively associated with depressive symptom severity ( r = 0.73, P = 0.003). Disrupting the temporal alignment of IED-containing epochs reduced α , whereas permuting IED-containing epochs among themselves preserved α , suggesting that the timing of IEDs contributes to the observed long-range temporal structure. In depressed TLE subjects, IEDs preferentially occurred during the rising phase of ultra-slow dFC fluctuations ( P = 0.004). Significance . Depressive symptoms in TLE are associated with more temporally persistent, less flexible beta band limbic network dynamics. These findings highlight the temporal organization of amygdala-hippocampal synchrony as a potential network-level signature of affective dysfunction within epilepsy and may inform future approaches to monitoring and modulating mood-related circuit activity in this population.