Episodic memory formation entails the integration of diverse elements such as people, places, and objects. This process, known as binding, creates a unified memory trace that the brain maintains and retrieves as a coherent representation of the episode. Despite extensive research, the precise neural mechanisms underlying this binding process are still not fully understood. We hypothesized that the

Assessment of bilingual children in only one language fails to acknowledge their distributed linguistic competence and has been shown to overidentify language disorder in bilingual populations. However, other factors, sometimes associated with bilingualism, may also contribute to low results in language assessments. Our aim was to examine the impact of these factors on language abilities. We used

At the current time, social robots are poised to enter human society in an unprecedented way. However, robots currentlyare not adept at communicating emotional states, even if humans to a large extent rely on such communication to regulateinteraction. Although facial expressions are difficult for robots to make use of, colored lights are readily available. Currentlythough, there is no consensus on

The physical layer foundations of cell-free massive MIMO (CF-mMIMO) have been well-established. As a next step, researchers are investigating practical and energy-efficient network implementations. This paper focuses on multiple sets of access points (APs) where user equipments (UEs) are served in each set, termed a federation, without inter-federation interference. The combination of federations

System logs are crucial for understanding the state and health of systems, yet manual inspection becomes impractical due to the high volume of messages. Consequently, machine learning-based log anomaly detection has emerged to automatically identify irregularities. This study investigates the effectiveness of log message embeddings, a novel parsing method, for anomaly detection in complex systems.

The human brain performs tasks with an outstanding energy efficiency, i.e., with approximately 20 Watts. The state-of-the-art Artificial/Deep Neural Networks (ANN/DNN), on the other hand, have recently been shown to consume massive amounts of energy. The training of these ANNs/DNNs is done almost exclusively based on the back-propagation algorithm, which is known to be biologically implausible. Th

The dendritic arbour of striatal projection neurons (SPNs) is the primary anatomical site where dopamine and glutamate inputs to the basal ganglia functionally interact to control movement. These dendritic arbourisations undergo atrophic changes in Parkinson's disease. A reduction in the dendritic complexity of SPNs is found also in animal models with severe striatal dopamine denervation. Using 6-

In this paper, we propose a joint transmit and receive antenna selection scheme for frequency diverse array (FDA) radar that aims at finding an optimal selection of employed FDA antennas, formed by minimizing the Cramér–Rao lower bound (CRLB) of the target localization problem given the available a priori knowledge of potential target locations. The resulting problem is a non-convex Boolean proble

The insect central complex appears to encode and process spatial information through vector manipulation. Here, we draw on recent insights into circuit structure to fuse previous models of sensory-guided navigation, path integration and vector memory. Specifically, we propose that the allocentric encoding of location provided by path integration creates a spatially stable anchor for converging sen

This paper addresses the weak signal detection problem in a massive colocated multiple-input multiple-output (MIMO) radar. To cope with the sheer amount of data produced by the large-scale antennas, a low-bit quantizer is introduced in the sampling process to enable both for hardware limitations and a high detection performance. The generalized likelihood ratio test (GLRT) detector is proposed for

Planets with radii between that of the Earth and Neptune (hereafter referred to as ‘sub-Neptunes’) are found in close-in orbits around more than half of all Sun-like stars 1,2. However, their composition, formation and evolution remain poorly understood 3. The study of multiplanetary systems offers an opportunity to investigate the outcomes of planet formation and evolution while controlling for i

Motivated by empirical research on bias and opinion formation, we formulate a multidimensional nonlinear opinion-dynamical model where agents have individual biases, which are fixed, as well as opinions, which evolve. The dimensions represent competing options, of which each agent has a relative opinion, and are coupled through normalization of the opinion vector. This can capture, for example, an

In this work, we introduce a spatio-temporal kernel for Gaussian process (GP) regression-based sound field estimation. Notably, GPs have the attractive property that the sound field is a linear function of the measurements, allowing the field to be estimated efficiently from distributed microphone measurements. However, to ensure analytical tractability, most existing kernels for sound field estim

Interpretability has become a crucial component in the Machine Learning (ML) domain. This is particularly important in the context of medical and health applications, where the underlying reasons behind how an ML model makes a certain decision are as important as the decision itself for the experts. However, interpreting an ML model based on limited local data may potentially lead to inaccurate co

Intratelencephalic neurons are a crucial class of cortical principal neurons that heavily innervate the striatum and cortical areas bilaterally. Their extensive cortico-cortical and cortico-striatal connectivity enables sensorimotor integration within the telencephalon, but their role in motor control remains poorly understood. Here, we used a chemogenetic approach to explore the role of intratele

We investigated whether sign-naïve learners can infer and learn the meaning of signs after minimal exposure to continuous, naturalistic input in the form of a weather forecast in Swedish Sign Language. Participants were L1-English adults. Two experimental groups watched the forecast once (N=40) or twice (N=42); a control group did not (N=42). Participants were then asked to assign meaning to 22 ta