No abstract

Human decisions are based on finite information, which makes them inherently imprecise. But what determines the degree of such imprecision? Here, we develop an efficient coding framework for higher-level cognitive processes in which information is represented by a finite number of discrete samples. We characterize the sampling process that maximizes perceptual accuracy or fitness under the often-adopted assumption that full adaptation to an environmental distribution is possible, and show how the optimal process differs when detailed information about the current contextual distribution is costly. We tested this theory on a numerosity discrimination task, and found that humans efficiently adapt to contextual distributions, but in the way predicted by the model in which people must economize on environmental information. Thus, understanding decision behavior requires that we account for biological restrictions on information coding, challenging the often-adopted assumption of precise prior knowledge in higher-level decision systems.

Here we demonstrate the suitability of a local mutual information measure for estimating the temporal dynamics of cross-frequency coupling (CFC) in brain electrophysiological signals. In CFC, concurrent activity streams in different frequency ranges interact and transiently couple. A particular form of CFC, phase-amplitude coupling (PAC), has raised interest given the growing amount of evidence of its possible role in healthy and pathological brain information processing. Although several methods have been proposed for PAC estimation, only a few have addressed the estimation of the temporal evolution of PAC, and these typically require a large number of experimental trials to return a reliable estimate. Here we explore the use of mutual information to estimate a PAC measure (MIPAC) in both continuous and event-related multi-trial data. To validate these two applications of the proposed method, we first apply it to a set of simulated phaseamplitude modulated signals and show that MIPAC can successfully recover the temporal dynamics of the simulated coupling in either continuous or multi-trial data. Finally, to explore the use of MIPAC to analyze data from human event-related paradigms, we apply it to an actual eventrelated human electrocorticographic (ECoG) data set that exhibits strong PAC, demonstrating that the MIPAC estimator can be used to successfully characterize amplitude-modulation dynamics in electrophysiological data.

PURPOSE: Immune checkpoint inhibitors (ICIs) cause immune-related adverse events (irAEs). The proportion of patients who are hospitalized for irAEs and their spectrum, management, and outcomes are not well described. METHODS: We report the proportion of hospitalized patients in an academic center who were treated with ICIs from May to December 2017. Patient characteristics, toxicities, management, and outcomes for confirmed irAE admissions are reported. Associations between patient features and irAE hospitalizations are examined. RESULTS: Twenty-three percent (n = 100) of 443 patients who were admitted to an academic oncology center over 6 months had ever received ICIs. Of these patients, 41% were admitted for suspected irAEs and 23% were confirmed irAEs. IrAEs accounted for 5% of all oncology hospitalizations (n = 23). Ninety-one percent of patients with confirmed irAEs prompted a medicine subspecialist consultation, most commonly gastroenterology (22%). Fifteen patients (65%) had their irAEs improve/resolve, seven (30%) had worsening irAEs, and three (13%) died of their irAEs. The majority of patients (n = 20; 87%) discontinued ICIs after discharge. Among ICI-treated patients who required admission, an increased likelihood of irAE-related hospitalization was associated with patient age older than 65 years (odds ratio, 5.4; 95% CI, 1.6 to 17.8) and receipt of combination immunotherapy (OR, 6.8; 95% CI, 2.0 to 23.2). CONCLUSION: A notable proportion of ICI-treated patients are hospitalized for irAEs, and these patients have a high demand for multidisciplinary management. Older age and combination ICI treatment were associated with an increased risk of irAE-related hospitalization. Whereas these data are from an academic center and include patients in clinical trials, with expanding use of ICIs, these data have important implications for inpatient service planning and risk stratification.