A5039027821- Neural dynamics and brain function
- Neural Networks and Applications
- EEG and Brain-Computer Interfaces
- Advanced Memory and Neural Computing
- Olfactory and Sensory Function Studies
- Memory and Neural Mechanisms
- Advanced Chemical Sensor Technologies
- Neural and Behavioral Psychology Studies
- Neuroscience and Neural Engineering
- Blind Source Separation Techniques
- stochastic dynamics and bifurcation
- Neuroscience and Neuropharmacology Research
- Domain Adaptation and Few-Shot Learning
- Functional Brain Connectivity Studies
- Neurobiology and Insect Physiology Research
- Nonlinear Dynamics and Pattern Formation
- Solar and Space Plasma Dynamics
- Biochemical Analysis and Sensing Techniques
- Fault Detection and Control Systems
- Magnetic confinement fusion research
- Magnetic properties of thin films
- Insect Pheromone Research and Control
- Fuzzy Logic and Control Systems
- Generative Adversarial Networks and Image Synthesis
- Neural Networks and Reservoir Computing
KTH Royal Institute of Technology
2016-2025
Swedish e-Science Research Centre
2022-2024
AlbaNova
2023
Futures Group (United States)
2022-2023
Stockholm University
2013-2022
University of Ulster
2005-2010
Netherlands Institute for Neuroscience
2009
There is now sufficient evidence that using a rehabilitation protocol involving motor imagery (MI) practice in conjunction with physical (PP) of goal-directed tasks leads to enhanced functional recovery paralyzed limbs among stroke sufferers. It however difficult confirm patient engagement during an MI the absence any on-line measure. Fortunately EEG-based brain-computer interface (BCI) can provide measure activity as neurofeedback for BCI user help him/her focus better on task. However...
The quantification of the spectral content electroencephalogram (EEG) recordings has a substantial role in clinical and scientific applications. It is particular relevance analysis event-related brain oscillatory responses. This work focused on identification relevant frequency patterns motor imagery (MI) related EEGs utilized for brain-computer interface (BCI) purposes. main objective paper to perform comparative different approaches signal representation such as power density (PSD)...
Persistent spiking has been thought to underlie working memory (WM). However, virtually all of the evidence for this comes from studies that averaged across time and trials, which masks details. On single activity often occurs in sparse transient bursts. This important computational functional advantages. In addition, examination more complex tasks reveals neural coding WM is dynamic over course a trial. All suggests WM, but its role than simply persistent spiking.Dual Perspectives Companion...
Abstract Working memory (WM) activity is not as stationary or sustained previously thought. There are brief bursts of gamma (~50–120 Hz) and beta (~20–35 oscillations, the former linked to stimulus information in spiking. We examined these dynamics relation readout control mechanisms WM. Monkeys held sequences two objects WM match subsequent sequences. Changes bursting suggested their distinct roles. In anticipation having use an object for decision, there was increase spiking about that...
Changes in oscillatory brain activity are strongly correlated with performance cognitive tasks and modulations specific frequency bands associated working memory tasks. Mesoscale network models allow the study of oscillations as an emergent feature neuronal activity. Here we extend a previously developed attractor model, shown to faithfully reproduce single-cell during retention recall, synaptic augmentation. This enables function multi-item by cyclic reactivation up six items. The happens...
Working memory (WM) allows us to remember and selectively control a limited set of items. Neural evidence suggests it is achieved by interactions between bursts beta gamma oscillations. However, not clear how oscillations, reflecting coherent activity millions neurons, can individual WM Here we propose the novel concept spatial computing where cause item-specific flow spatially across network during task. This way, control-related information such as item order stored in independent detailed...
Odor naming is considered a particularly challenging cognitive test, but the underlying cause of this difficulty unknown. People often fail to report any source label identify common odors, resulting in omissions (i.e., lack response). Here, with support computational model, we offer hypothesis about neural network mechanisms odor omissions. Based on an evaluation behavioral data from almost 40,000 attempts, suggest that high omission rates are driven by odors referred multiple linguistic...
Abstract Working memory (WM) is a key component of human and cognition. Computational models have been used to study the underlying neural mechanisms, but neglected important role short-term (STM) long-term (LTM) interactions for WM. Here, we investigate these using novel multiarea spiking network model prefrontal cortex (PFC) two parietotemporal cortical areas based on macaque data. We propose WM indexing theory that explains how PFC could associate, maintain, update multimodal LTM...
Nested oscillations, where the phase of underlying slow rhythm modulates power faster have recently attracted considerable research attention as increased phase-coupling cross-frequency oscillations has been shown to relate memory processes. Here we investigate hypothesis that reactivations patterns, induced by either external stimuli or internal dynamics, are manifested distributed cell assemblies oscillating at gamma-like frequencies with life-times on a theta scale. For this purpose,...
One of the urgent challenges in automated analysis and interpretation electrical brain activity is effective handling uncertainties associated with complexity variability dynamics, reflected nonstationary nature signals such as electroencephalogram (EEG). This poses a severe problem for existing approaches to classification task within brain-computer interface (BCI) systems. Recently emerged type-2 fuzzy logic (T2FL) methodology has shown remarkable potential dealing uncertain information...
Abstract Digitalisation is an increasingly important driver of urban development. The ‘New Urban Science’ one particular approach to digitalisation that promises new ways knowing and managing cities more effectively. Proponents the New Science emphasise data analytics modelling as a means develop novel insights on how function. However, there are multiple opportunities broaden deepen these practices through collaborations between natural social sciences well with public authorities, private...
The performance of Deep-Learning (DL) computing frameworks rely on the data ingestion and checkpointing. In fact, during training, a considerable high number relatively small files are first loaded pre-processed CPUs then moved to accelerator for computation. addition, checkpointing restart operations carried out allow DL quickly from checkpoint. Because this, I/O affects applications. this work, we characterize scaling TensorFlow, an open-source programming framework developed by Google...
Time Series Representation Learning (TSRL) focuses on generating informative representations for various (TS) modeling tasks. Traditional Self-Supervised (SSL) methods in TSRL fall into four main categories: reconstructive, adversarial, contrastive, and predictive, each with a common challenge of sensitivity to noise intricate data nuances. Recently, diffusion-based have shown advanced generative capabilities. However, they primarily target specific application scenarios like imputation...
There is now sufficient evidence that using a rehabilitation protocol involving motor imagery (MI) practice (or mental (MP)) in conjunction with physical (PP) of goal-directed tasks leads to enhanced functional recovery paralyzed limbs among stroke sufferers. It however difficult ensure patient engagement during MP the absence any on-line measure MP. Fortunately an EEG-based brain-computer interface (BCI), MI activity used devise neurofeedback for BCI user help him/her focus better on task....
Spontaneous oscillations measured by local field potentials, electroencephalograms and magnetoencephalograms exhibit a pronounced peak in the alpha band (8–12 Hz) humans primates. Both instantaneous power phase of these ongoing have commonly been observed to correlate with psychophysical performance stimulus detection tasks. We use novel model-based approach study effect prestimulus on rate. A previously developed biophysically detailed attractor network exhibits spontaneous range before is...
Abstract Naming common odors is a surprisingly difficult task: Odors are frequently misnamed. Little known about the linguistic properties of odor misnamings. We test whether misnamings old adults carry information olfactory perception and its connection to lexical‐semantic processing. analyze olfactory–semantic content source naming failures in large sample older Sweden ( n = 2479; age 58–100 years). investigate factors semantic proximity target name predict how misnamed, these relate...