Feedback-related EEG dynamics separately reflect decision parameters, biases, and future choices

Optimal decision making in complex environments requires dynamic learning from unexpected events. To speed up learning, we should heavily weight information that indicates state-action-outcome contingency changes and ignore uninformative fluctuations in the environment. Often, however, unrelated information is hard to ignore and can potentially bias our learning. Here we used computational modelling and EEG to investigate learning behaviour in a modified probabilistic choice task that introduced two task-irrelevant factors that were uninformative for optimal task performance, but nevertheless could potentially bias learning: pay-out magnitudes were varied randomly and, occasionally, feedback presentation was enhanced by visual surprise. We found that participants’ overall good learning performance was biased by distinct effects of these non-normative factors. On the neural level, these parameters are represented in a dynamic and spatiotemporally dissociable sequence of EEG activity. Later in feedback processing the different streams converged on a central to centroparietal positivity reflecting a signal that is interpreted by downstream learning processes that adjust future behaviour

Unraveling the influence of trial-based motivational changes on performance monitoring stages in a flanker task

Performance monitoring (PM) is a vital component of adaptive behavior and known to be influenced by motivation. We examined effects of potential gain (PG) and loss avoidance (LA) on neural correlates of PM at different processing stages, using a task with trial-based changes in these motivational contexts. Findings suggest more attention is allocated to the PG context, with higher amplitudes for respective correlates of stimulus and feedback processing. The PG context favored rapid responses, while the LA context emphasized accurate responses. Lower response thresholds in the PG context after correct responses derived from a drift–diffusion model also indicate a more approach-oriented response style in the PG context. This cognitive shift is mirrored in neural correlates: negative feedback in the PG context elicited a higher feedback-related negativity (FRN) and higher theta power, whereas positive feedback in the LA context elicited higher P3a and P3b amplitudes, as well as higher theta power. There was no effect of motivational context on response-locked brain activity. Given the similar frequency of negative feedback in both contexts, the elevated FRN and theta power in PG trials cannot be attributed to variations in reward prediction error. The observed variations in the FRN indicate that the effect of outcome valence is modulated by motivational salience

Gender influences on brain responses to errors and post-error adjustments

Sexual dimorphisms have been observed in many species, including humans, and extend to the prevalence and presentation of important mental disorders associated with performance monitoring malfunctions. However, precisely which underlying differences between genders contribute to the alterations observed in psychiatric diseases is unknown. Here, we compare behavioural and neural correlates of cognitive control functions in 438 female and 436 male participants performing a flanker task while EEG was recorded. We found that males showed stronger performance-monitoring-related EEG amplitude modulations which were employed to predict subjects’ genders with ~72% accuracy. Females showed more post-error slowing, but both samples did not differ in regard to response-conflict processing and coupling between the error-related negativity (ERN) and consecutive behavioural slowing. Furthermore, we found that the ERN predicted consecutive behavioural slowing within subjects, whereas its overall amplitude did not correlate with post-error slowing across participants. These findings elucidate specific gender differences in essential neurocognitive functions with implications for clinical studies. They highlight that within- and between-subject associations for brain potentials cannot be interpreted in the same way. Specifically, despite higher general amplitudes in males, it appears that the dynamics of coupling between ERN and post-error slowing between men and women is comparable

Transdiagnostic inflexible learning dynamics explain deficits in depression and schizophrenia

Deficits in reward learning are core symptoms across many mental disorders. Recent work suggests that such learning impairments arise by a diminished ability to use reward history to guide behaviour, but the neuro-computational mechanisms through which these impairments emerge remain unclear. Moreover, limited work has taken a transdiagnostic approach to investigate whether the psychological and neural mechanisms that give rise to learning deficits are shared across forms of psychopathology. To provide insight into this issue, we explored probabilistic reward learning in patients diagnosed with major depressive disorder (n = 33) or schizophrenia (n = 24) and 33 matched healthy controls by combining computational modelling and single-trial EEG regression. In our task, participants had to integrate the reward history of a stimulus to decide whether it is worthwhile to gamble on it. Adaptive learning in this task is achieved through dynamic learning rates that are maximal on the first encounters with a given stimulus and decay with increasing stimulus repetitions. Hence, over the course of learning, choice preferences would ideally stabilize and be less susceptible to misleading information. We show evidence of reduced learning dynamics, whereby both patient groups demonstrated hypersensitive learning (i.e. less decaying learning rates), rendering their choices more susceptible to misleading feedback. Moreover, there was a schizophrenia-specific approach bias and a depression-specific heightened sensitivity to disconfirmational feedback (factual losses and counterfactual wins). The inflexible learning in both patient groups was accompanied by altered neural processing, including no tracking of expected values in either patient group. Taken together, our results thus provide evidence that reduced trial-by-trial learning dynamics reflect a convergent deficit across depression and schizophrenia. Moreover, we identified disorder distinct learning deficits

Abyssal fauna of the UK-1 polymetallic nodule exploration area, Clarion-Clipperton Zone, central Pacific Ocean: Mollusca

The file attached is the Published/publisher’s pdf version of the article. This is an OpenAccess article.Copyright Helena Wiklund et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Efficient Passive ICS Device Discovery and Identification by MAC Address Correlation

Owing to a growing number of attacks, the assessment of Industrial Control Systems (ICSs) has gained in importance. An integral part of an assessment is the creation of a detailed inventory of all connected devices, enabling vulnerability evaluations. For this purpose, scans of networks are crucial. Active scanning, which generates irregular traffic, is a method to get an overview of connected and active devices. Since such additional traffic may lead to an unexpected behavior of devices, active scanning methods should be avoided in critical infrastructure networks. In such cases, passive network monitoring offers an alternative, which is often used in conjunction with complex deep-packet inspection techniques. There are very few publications on lightweight passive scanning methodologies for industrial networks. In this paper, we propose a lightweight passive network monitoring technique using an efficient Media Access Control (MAC) address-based identification of industrial devices. Based on an incomplete set of known MAC address to device associations, the presented method can guess correct device and vendor information. Proving the feasibility of the method, an implementation is also introduced and evaluated regarding its efficiency. The feasibility of predicting a specific device/vendor combination is demonstrated by having similar devices in the database. In our ICS testbed, we reached a host discovery rate of 100% at an identification rate of more than 66%, outperforming the results of existing tools.Comment: http://dx.doi.org/10.14236/ewic/ICS2018.

Considering the Case for Biodiversity Cycles: Reexamining the Evidence for Periodicity in the Fossil Record

Medvedev and Melott (2007) have suggested that periodicity in fossil biodiversity may be induced by cosmic rays which vary as the Solar System oscillates normal to the galactic disk. We re-examine the evidence for a 62 million year (Myr) periodicity in biodiversity throughout the Phanerozoic history of animal life reported by Rohde & Mueller (2005), as well as related questions of periodicity in origination and extinction. We find that the signal is robust against variations in methods of analysis, and is based on fluctuations in the Paleozoic and a substantial part of the Mesozoic. Examination of origination and extinction is somewhat ambiguous, with results depending upon procedure. Origination and extinction intensity as defined by RM may be affected by an artifact at 27 Myr in the duration of stratigraphic intervals. Nevertheless, when a procedure free of this artifact is implemented, the 27 Myr periodicity appears in origination, suggesting that the artifact may ultimately be based on a signal in the data. A 62 Myr feature appears in extinction, when this same procedure is used. We conclude that evidence for a periodicity at 62 Myr is robust, and evidence for periodicity at approximately 27 Myr is also present, albeit more ambiguous.Comment: Minor modifications to reflect final published versio

Which leukocyte subsets predict cardiovascular mortality? From the LUdwigshafen RIsk and Cardiovascular Health (LURIC) Study

AbstractObjectiveWhite blood cells are known to predict cardiovascular mortality, but form a highly heterogeneous population. It is therefore possible that specific subtypes disproportionally contribute to the prediction of cardiovascular outcomes. Therefore, we compared leukocyte subsets alone and in conjunction with an established inflammatory marker, C-reactive protein, for predicting death due to cardiovascular disease in a high-risk population.MethodsPatients, 3316, (mean [SD] age, 62 [10] years) scheduled for coronary angiography were prospectively followed up. Neutrophil, monocyte and lymphocyte counts were determined. Neutrophil and monocyte subsets were further analysed on the basis of surface expression of CD11b, CD18, CD31, CD40 and CD58. Lymphocytes were further subdivided into CD3, CD4, CD8, and CD19 subsets. The association between each marker and subsequent cardiovascular mortality was assessed using multivariable Cox regression models.ResultsDuring a median follow-up period of 7.8 years, 745 (22.5%) patients died, of which 484 were due to cardiovascular events. After entering conventional risk factors and removing patients with a current infection, neutrophil count (HR [95% CI]=1.90 [1.39, 2.60], P<0.001) and the neutrophil/lymphocyte ratio (HR [95% CI]=1.68 [1.24, 2.27], P=0.003) emerged as independent predictors of cardiovascular mortality. After mutual adjustment, neutrophil count (HR [95% CI]=1.87 [1.35, 2.50], P<0.001) out-performed C-reactive protein (HR [95% CI] 1.32 [0.99, 1.78], P=0.06) as a predictor of cardiovascular mortality.ConclusionsDue to its predictive potential and inexpensive determination, assessment of high neutrophil counts may represent an important marker, possibly improving cardiovascular mortality risk prediction

Analysis of bi-atrial function using CMR feature tracking and long-axis shortening approaches in patients with diastolic dysfunction and atrial fibrillation.

OBJECTIVES Atrial function can be assessed using advancing cardiovascular magnetic resonance (CMR) post-processing methods: atrial feature tracking (FT) strain analysis or a long-axis shortening (LAS) technique. This study aimed to first compare the two FT and LAS techniques in healthy individuals and cardiovascular patients and then investigated how left (LA) and right atrial (RA) measurements are related to the severity of diastolic dysfunction or atrial fibrillation. METHODS Sixty healthy controls and 90 cardiovascular disease patients with coronary artery disease, heart failure, or atrial fibrillation, underwent CMR. LA and RA were analyzed for standard volumetry as well as for myocardial deformation using FT and LAS for the different functional phases (reservoir, conduit, booster). Additionally, ventricular shortening and valve excursion measurements were assessed with the LAS module. RESULTS The measurements for each of the LA and RA phases were correlated (p < 0.05) between the two approaches, with the highest correlation coefficients occurring in the reservoir phase (LA: r = 0.83, p < 0.01, RA: r = 0.66, p < 0.01). Both methods demonstrated reduced LA (FT: 26 ± 13% vs 48 ± 12%, LAS: 25 ± 11% vs 42 ± 8%, p < 0.01) and RA reservoir function (FT: 28 ± 15% vs 42 ± 15%, LAS: 27 ± 12% vs 42 ± 10%, p < 0.01) in patients compared to controls. Atrial LAS and FT decreased with diastolic dysfunction and atrial fibrillation. This mirrored ventricular dysfunction measurements. CONCLUSION Similar results were generated for bi-atrial function measurements between two CMR post-processing approaches of FT and LAS. Moreover, these methods allowed for the assessment of incremental deterioration of LA and RA function with increasing left ventricular diastolic dysfunction and atrial fibrillation. A CMR-based analysis of bi-atrial strain or shortening discriminates patients with early-stage diastolic dysfunction prior to the presence of compromised atrial and ventricular ejection fractions that occur with late-stage diastolic dysfunction and atrial fibrillation. KEY POINTS • Assessing right and left atrial function with CMR feature tracking or long-axis shortening techniques yields similar measurements and could potentially be used interchangeably based on the software capabilities of individual sites. • Atrial deformation and/or long-axis shortening allow for early detection of subtle atrial myopathy in diastolic dysfunction, even when atrial enlargement is not yet apparent. • Using a CMR-based analysis to understand the individual atrial-ventricular interaction in addition to tissue characteristics allows for a comprehensive interrogation of all four heart chambers. In patients, this could add clinically meaningful information and potentially allow for optimal therapies to be chosen to better target the dysfunction

Quantum Imaging with Incoherently Scattered Light from a Free-Electron Laser

The advent of accelerator-driven free-electron lasers (FEL) has opened new avenues for high-resolution structure determination via diffraction methods that go far beyond conventional x-ray crystallography methods. These techniques rely on coherent scattering processes that require the maintenance of first-order coherence of the radiation field throughout the imaging procedure. Here we show that higher-order degrees of coherence, displayed in the intensity correlations of incoherently scattered x-rays from an FEL, can be used to image two-dimensional objects with a spatial resolution close to or even below the Abbe limit. This constitutes a new approach towards structure determination based on incoherent processes, including Compton scattering, fluorescence emission or wavefront distortions, generally considered detrimental for imaging applications. Our method is an extension of the landmark intensity correlation measurements of Hanbury Brown and Twiss to higher than second-order paving the way towards determination of structure and dynamics of matter in regimes where coherent imaging methods have intrinsic limitations