RESUMO
BACKGROUND: Psychosis spectrum disorders are characterized by significant alterations in social functioning, which is a major factor for patient recovery. Despite its importance, objectively quantifying the complex day-to-day social behavior in real-life settings has rarely been attempted. Here, we conducted a pilot study with wearable sensors that passively and continuously register interactions with other participants. We hypothesized that the amount and pattern of social interaction was associated with the severity of psychotic symptoms. STUDY DESIGN: We recruited 7 patients with psychosis spectrum disorders and 18 team members from a Soteria-style ward. Each participant wore a radio frequency identification badge, sending and receiving signals from nearby badges, allowing passive quantification of social interactions. In addition, symptom severity was assessed weekly by the Positive and Negative Syndrome Scale (PANSS). STUDY RESULTS: During an 11-week period, we identified 17 970 interactions among patients and staff. On average, patients spent 2.6 h per day interacting, capturing relevant aspects of daily social life. Relative daily interaction time, average interaction duration, and clustering coefficient, a measure of local network integration, were significantly associated with lower PANSS scores. Self-reported interaction time did not correlate with measured interaction time or with PANSS, indicating the importance of objective markers. CONCLUSIONS: This pilot study demonstrates the feasibility of passively recording social interaction of patients and staff at high resolution and for a long observation period in a real-life setting in a psychiatric department. We show links between quantified social interaction and psychopathology that may facilitate development and personalization of targeted treatments.
RESUMO
Neurons are highly vulnerable to conditions of hypoxia-ischemia (HI) such as stroke or transient ischemic attacks. Recovery of cognitive and behavioral functions requires re-emergence of coordinated network activity, which, in turn, relies on the well-orchestrated interaction of pyramidal cells (PYRs) and interneurons. We therefore modelled HI in the mouse hippocampus, a particularly vulnerable region showing marked loss of PYR and fast-spiking interneurons (FSIs) after hypoxic-ischemic insults. Transient oxygen-glucose deprivation (OGD) in ex vivo hippocampal slices led to a rapid loss of neuronal activity and spontaneous network oscillations (sharp wave-ripple complexes; SPW-Rs), and to the occurrence of a spreading depolarization. Following reperfusion, both SPW-R and neuronal spiking resumed, but FSI activity remained strongly reduced compared with PYR. Whole-cell recordings in CA1 PYR revealed, however, a similar reduction of both EPSCs and IPSCs, leaving inhibition-excitation (I/E) balance unaltered. At the network level, SPW-R incidence was strongly reduced and the remaining network events showed region-specific changes including reduced ripple energy in CA3 and increased ripple frequency in CA1. Together, our data show that transient hippocampal energy depletion results in severe functional alterations at the cellular and network level. While I/E balance is maintained, synaptic activity, interneuron spiking and coordinated network patterns remain reduced. Such alterations may be network-level correlates of cognitive and functional deficits after cerebral HI.
Assuntos
Glucose , Oxigênio , Animais , Hipocampo , Interneurônios , Camundongos , Células PiramidaisRESUMO
The rodent hippocampus expresses a variety of neuronal network oscillations depending on the behavioral state of the animal. Locomotion and active exploration are accompanied by theta-nested gamma oscillations while resting states and slow-wave sleep are dominated by intermittent sharp wave-ripple complexes. It is believed that gamma rhythms create a framework for efficient acquisition of information whereas sharp wave-ripples are thought to be involved in consolidation and retrieval of memory. While not strictly mutually exclusive, one of the two patterns usually dominates in a given behavioral state. Here we explore how different input patterns induce either of the two network states, using an optogenetic stimulation approach in hippocampal brain slices of mice. We report that the pattern of the evoked oscillation depends strongly on the initial synchrony of activation of excitatory cells within CA3. Short, synchronous activation favors the emergence of sharp wave-ripple complexes while persistent but less synchronous activity-as typical for sensory input during exploratory behavior-supports the generation of gamma oscillations. This dichotomy is reflected by different degrees of synchrony of excitatory and inhibitory synaptic currents within these two states. Importantly, the induction of these two fundamental network patterns does not depend on the presence of any neuromodulatory transmitter like acetylcholine, but is merely based on a different synchrony in the initial activation pattern.