A5030069824- Advanced Memory and Neural Computing
- Neural dynamics and brain function
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
- Neuroscience and Neuropharmacology Research
- Neurobiology and Insect Physiology Research
- Neuroscience and Neural Engineering
- Memory and Neural Mechanisms
- Ferroelectric and Negative Capacitance Devices
- Zebrafish Biomedical Research Applications
- Pulmonary Hypertension Research and Treatments
- Insect and Arachnid Ecology and Behavior
- Plant and animal studies
- Advanced Clustering Algorithms Research
- Photoreceptor and optogenetics research
- Animal Behavior and Reproduction
- EEG and Brain-Computer Interfaces
- Neural and Behavioral Psychology Studies
- Visual perception and processing mechanisms
- Genetic Neurodegenerative Diseases
- Reinforcement Learning in Robotics
- Face and Expression Recognition
- Data Management and Algorithms
- Nosocomial Infections in ICU
- stochastic dynamics and bifurcation
Crete University Press
2023-2025
University of Crete
2008-2025
University of Sheffield
2015-2024
Imperial College London
2021-2024
University of Zurich
2022-2023
ETH Zurich
2021-2023
Indian Institute of Technology Roorkee
2023
SIB Swiss Institute of Bioinformatics
2021-2023
Hammersmith Hospital
2023
Lung Institute
2023
Machine learning, particularly in the form of deep learning (DL), has driven most recent fundamental developments artificial intelligence (AI). DL is based on computational models that are, to a certain extent, bio‐inspired, as they rely networks connected simple computing units operating parallel. The success supported by three factors: availability vast amounts data, continuous growth power, and algorithmic innovations. approaching demise Moore's law, consequent expected modest...
Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field industry. However, this success comes at a great price; energy requirements for training advanced models are unsustainable. One promising way address pressing issue is by developing low-energy neuromorphic hardware that directly supports algorithm's requirements. The intrinsic non-volatility, non-linearity, memory spintronic devices make them...
Changes in synaptic efficacies need to be long-lasting order serve as a substrate for memory. Experimentally, plasticity exhibits phases covering the induction of long-term potentiation and depression (LTP/LTD) during early phase plasticity, setting tags, trigger process protein synthesis, slow transition leading consolidation late plasticity. We present mathematical model that describes these different The explains large body experimental data on tagging capture, cross-tagging, LTP LTD....
The urothelium is a specialized epithelium that lines the urinary tract. It consists of three different cell types, namely, basal, intermediate and superficial cells arranged in relatively distinct layers. Normally, quiescent, it regenerates fast upon injury, but regeneration process not fully understood. Although several reports have indicated existence progenitors, their identity exact topology, as well role key processes such tissue carcinogenesis been clarified. Here we show minor...
Abstract Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate single solid-state TiO 2 memristors can exhibit non-associative plasticity phenomena observed in synapses, supported by their metastable memory state transition properties. We show that, contrary to uses of memory, the...
Changes of synaptic connections between neurons are thought to be the physiological basis learning. These changes can gated by neuromodulators that encode presence reward. We study a family reward-modulated learning rules for spiking on task in continuous space inspired Morris Water maze. The update rule modifies release probability transmission and depends timing presynaptic spike arrival, postsynaptic action potentials, as well membrane potential neuron. includes an optimal derived from...
The Morris Water Maze is a widely used task in studies of spatial learning with rodents. Classical performance measures animals the include escape latency, and cumulative distance to platform. Other methods focus on classifying trajectory patterns stereotypical classes representing different animal strategies. However, these approaches typically consider trajectories as whole, consequence they assign one full class, whereas often switch between strategies, their corresponding classes, within...
The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought be dependent on top-down neocortical processing. It therefore surprising that honey bees apparantly have this capacity. Here we report model of the structures bee brain can sameness difference, well range complex simple associative learning tasks. Our constrained by known connections properties mushroom body, including protocerebral tract, provides...
Abstract Emergent behaviors occur when simple interactions between a system's constituent elements produce properties that the individual do not exhibit in isolation. This article reports tunable emergent observed domain wall (DW) populations of arrays interconnected magnetic ring‐shaped nanowires under an applied rotating field. DWs interact stochastically at ring junctions to create mechanisms DW population loss and gain. These combine give dynamic, field‐dependent equilibrium is robust...
Background: Pulmonary arterial hypertension (PAH) is a rare disease characterized by remodeling of the pulmonary arteries, increased vascular resistance, and right-sided heart failure. Genome-wide association studies idiopathic/heritable PAH established novel genetic risk variants, including conserved enhancers upstream transcription factor (TF) SOX17 containing 2 independent signals. an important TF in embryonic development homeostasis artery endothelial cells (hPAEC) adult. Rare pathogenic...
The insect central complex (CX) is an enigmatic structure whose computational function has evaded inquiry, but been implicated in a wide range of behaviours. Recent experimental evidence from the fruit fly (Drosophila melanogaster) and cockroach (Blaberus discoidalis) demonstrated existence neural activity corresponding to animal's orientation within virtual arena (a 'compass'), this provides insight into one component CX structure. There are two key features compass activity: offset between...
Machine learning techniques are commonly used to model complex relationships but implementations on digital hardware relatively inefficient due poor matching between conventional computer architectures and the structures of algorithms they required simulate. Neuromorphic devices, in particular reservoir computing architectures, utilize inherent properties physical systems implement machine so have potential be much more efficient. In this work, we demonstrate that dynamics individual domain...
We examined how bees solve a visual discrimination task with stimuli commonly used in numerical cognition studies. Bees performed well on the task, but additional tests showed that they had learned continuous (non-numerical) cues. A network model using biologically plausible feature filtering and simple associative rule was capable of learning only cues inherent training stimuli, no processing. This also able to reproduce behaviours have been considered other studies indicative cognition....
Abstract K-Means is one of the most used algorithms for data clustering and usual method benchmarking. Despite its wide application it well-known that suffers from a series disadvantages; only able to find local minima positions initial centres (centroids) can greatly affect solution. Over years many variations initialisation techniques have been proposed with different degrees complexity. In this study we focus on common along range deterministic stochastic techniques. We show that,...
Pulmonary arterial hypertension (PAH) is characterised by pulmonary vascular remodelling causing premature death from right heart failure. Established DNA variants influence PAH risk, but susceptibility epigenetic changes unknown. We addressed this through epigenome-wide association study (EWAS), testing 865,848 CpG sites for with in 429 individuals and 1226 controls. Three loci, at Cathepsin Z (CTSZ, cg04917472), Conserved oligomeric Golgi complex 6 (COG6, cg27396197), Zinc Finger Protein...
Background: Interactive learning environments have emerged as transformative tools in education, enhancing engagement, academic performance, and addressing challenges like anxiety. This study examines the influence of multiple variables, including anxiety, internet usage for problem-solving, attitude towards a history course, metacognitive awareness, interactive environments, on seventh-grade students’ performance. Methods: Using Exploration Attitudes Towards History Scale (EDIS) scale to...
Micro-Electrode Arrays (MEAs) have emerged as a mature technique to investigate brain (dys)functions in vivo and vitro animal models. Often referred "smart" Petri dishes, MEAs demonstrated great potential particularly for medium-throughput studies vitro, both academic pharmaceutical industrial contexts. Enabling rapid comparison of ionic/pharmacological/genetic manipulations with control conditions, are employed screen compounds by monitoring non-invasively the spontaneous evoked neuronal...
The Morris Water Maze is commonly used in behavioural neuroscience for the study of spatial learning with rodents. Over years, various methods analysing rodent data collected this task have been proposed. These span from classical performance measurements (e.g. escape latency, speed, quadrant preference) to more sophisticated categorisation which classify animal swimming path into classes known as strategies. Classification techniques provide additional insight relation actual behaviours but...
Although the basal ganglia have been widely studied and implicated in signal processing action selection, little information is known about active role striatal microcircuit plays selection ganglia-thalamo-cortical loops. To address this knowledge gap we use a large scale three dimensional spiking model of striatum, combined with rate coded loop, to asses computational striatum selection. We identify robust transient phenomena generated by microcircuit, which temporarily enhances difference...
"Sparse" neural networks, in which relatively few neurons or connections are active, common both machine learning and neuroscience. Whereas learning, "sparsity" is related to a penalty term that leads some connecting weights becoming small zero, biological brains, sparsity often created when high spiking thresholds prevent neuronal activity. Here we introduce into reservoir computing network via neuron-specific learnable of activity, allowing with low contribute decision-making but...
The present study performed a detailed analysis of behavior in rat model epilepsy using both established and novel methodologies to identify behavioral impairments that may differentiate between animals with short versus long latency spontaneous seizures low high number seizures. Temporal lobe was induced by electrical stimulation the amygdala. Rats were stimulated for 25 min 100-ms trains 1-ms biphasic square-wave pluses delivered every 0.5 s. Electroencephalographic recordings classify...