In this work, we propose a novel method to transform a time series into a weighted and directed network. For a given time series, we first generate a set of segments via a sliding window, and then use a doubly symbolic scheme to characterize every windowed segment by combining absolute amplitude information with an ordinal pattern characterization. Based on this construction, a network can be directly constructed from the given time series: segments corresponding to different symbol-pairs are mapped to network nodes and the temporal succession between nodes is represented by directed links. With this conversion, dynamics underlying the time series has been encoded into the network structure. We illustrate the potential of our networks with a well-studied dynamical model as a benchmark example. Results show that network measures for characterizing global properties can detect the dynamical transitions in the underlying system. Moreover, we employ a random walk algorithm to sample loops in our networks, and find that time series with different dynamics exhibits distinct cycle structure. That is, the relative prevalence of loops with different lengths can be used to identify the underlying dynamics.

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Objective: This research was aimed to evaluate the behaviors of short-or long-term antidepressant effects of ketamine in rats exposed to chronic unpredictable stress (CUS).Background: Ketamine, a glutamate noncompetitive NMDA receptor antagonist, reg-

Associations between depressive symptoms and relationship distress are well-established, but little is known about these linkages among Black couples, or about the role of sociocultural factors in these processes. In this study, we applied a dyadic analytic approach, Actor-Partner Interdependence Modeling (APIM), to address 2 goals: to assess the prospective, bidirectional associations between depressive symptoms and marital satisfaction over a 1-year period in a racially homogenous sample of 168 heterosexual Black couples, and to explore whether these associations were moderated by husbands’ and wives’ experiences of racial discrimination and/or the centrality of race in their personal identities. Findings revealed that depressive symptoms predicted relative declines in marital satisfaction reported by both self and partner for both husbands and wives. Moderation analyses indicated that, when wives reported greater racial centrality, their depressive symptoms predicted relative declines in husbands’ marital satisfaction. In contrast, when wives reported lower racial centrality, their depressive symptoms were not associated with husbands’ satisfaction. Together, the findings highlight the interdependence between spouses’ mental health and relationship satisfaction and the role of sociocultural factors in these linkages.