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Search results for: DEEP BRAIN STIMULATION
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Deep brain stimulation: new possibilities for the treatment of mental disorders
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Deep brain stimulation in obsessive-compulsive disorder – case report of two patients
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Brain Stimulation
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Sleep assessment in obsessive-compulsive disorder treated with deep brain stimulation - double case report of morning and evening chronotype patients
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Various neuromodulation methods including Deep Brain Stimulation of the medial forebrain bundle combined with psychopharmacotherapy of treatment-resistant depression—Case report
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Direct brain stimulation modulates encoding states and memory performance in humans
PublicationPeople often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting,...
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Direct electrical brain stimulation of human memory: lessons learnt and future perspectives
PublicationModulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental...
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Direct electrical stimulation of the human brain has inverse effects on the theta and gamma neural activities
PublicationObjective: Our goal was to analyze the electrophysiological response to direct electrical stimulation (DES) systematically applied at a wide range of parameters and anatomical sites, with particular focus on neural activities associated with memory and cognition. Methods: We used a large set of intracranial EEG (iEEG) recordings with DES from 45 subjects with electrodes...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Brain-Inspired Deep Networks for Facial Expression Recognition. Frontiers in Biomedical Technologies
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Michał Lech dr inż.
PeopleMichał Lech was born in Gdynia in 1983. In 2007 he graduated from the faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. In June 2013, he received his Ph.D. degree. The subject of the dissertation was: “A Method and Algorithms for Controlling the Sound Mixing Processes by Hand Gestures Recognized Using Computer Vision”. The main focus of the thesis was the bias of audio perception caused...
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Joanna Rymaszewska prof. dr hab. n. med.
PeopleCV Joanna Rymaszewska Wroclaw University of Science and Technology, Wroclaw, Poland +48 601 98 26 24, joanna.rymaszewska@pwr.edu.pl orcid.org/0000-0001-8985-3592 2023 → Professor of Wroclaw University of Science and Technology (WUST), Poland 2011 → 2023 Professor of Wroclaw Medical University (WMU), PL 2016 → 2022 Head of the Department of Psychiatry, Wroclaw Medical University 2016 → 2022 Head of the Clinic of Psychiatry,...
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Human memory enhancement through electrical stimulation in the temporal cortex
PublicationDirect electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement...
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Michał Tomasz Kucewicz dr
PeopleMichal Kucewicz was born in 1986 in Gdansk. In 2005 he completed International Baccalaureate programme in Topolowka (III High School in Gdańsk). Thanks to the G. D. Fahrenheit scholarship, he moved to the United Kingdom to study neuroscience. He received his Bachelor’s and Master’s degree from the Cambridge University, and his doctoral degree from the University of Bristol specializing in electrophysiology of memory and cognitive...
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Electrical Stimulation Modulates High Gamma Activity and Human Memory Performance
PublicationDirect electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation...
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Closed-loop stimulation of temporal cortex rescues functional networks and improves memory
PublicationMemory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct...
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A Study in Experimental Methods of Human-Computer Communication for Patients After Severe Brain Injuries
PublicationExperimental research in the domain of multimedia technology applied to medical practice is discussed, employing a prototype of integrated multimodal system to assist diagnosis and polysensory stimulation of patients after severe brain injury. The system being developed includes among others: eye gaze tracker, and EEG monitoring of non-communicating patients after severe brain injuries. The proposed solutions are used for collecting...
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Interictal high-frequency oscillations in focal human epilepsy
PublicationPURPOSE OF REVIEW: Localization of focal epileptic brain is critical for successful epilepsy surgery and focal brain stimulation. Despite significant progress, roughly half of all patients undergoing focal surgical resection, and most patients receiving focal electrical stimulation, are not seizure free. There is intense interest in high-frequency oscillations (HFOs) recorded with intracranial electroencephalography as potential...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Nitric Oxide-Dependent Pathways as Critical Factors in the Consequences and Recovery after Brain Ischemic Hypoxia
PublicationBrain ischemia is one of the leading causes of disability and mortality worldwide. Nitric oxide (NO), a molecule that is involved in the regulation of proper blood flow, vasodilation, neuronal and glial activity constitutes the crucial factor that contributes to the development of pathological changes after stroke. One of the early consequences of a sudden interruption in the cerebral blood flow is the massive production of reactive...
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Wykłady neuronaukowe
EventsCentrum BioTechMed zaprasza na dwa wykłady neuronaukowe prowadzone przez profesorów wizytujących Politechnikę Gdańską.
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublicationElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Image
PublicationThis study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Hotspot of human verbal memory encoding in the left anterior prefrontal cortex
PublicationBackground: Treating memory and cognitive deficits requires knowledge about anatomical sites and neural activities to be targeted with particular therapies. Emerging technologies for local brain stimulation offer attractive therapeutic options but need to be applied to target specific neural activities, at distinct times, and in specific brain regions that are critical for memory formation. Methods: The areas that are critical...
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Natural fish oil improves the differentiation and maturation of oligodendrocyte precursor cells to oligodendrocytes in vitro after interaction with the blood–brain barrier
PublicationThe blood–brain barrier (BBB) tightly controls the microenvironment of the central nervous system (CNS) to allow neurons to function properly. Additionally, emerging studies point to the beneficial effect of natural oils affecting a wide variety of physiological and pathological processes in the human body. In this study, using an in vitro model of the BBB, we tested the influence of natural fish oil mixture (FOM) vs. borage oil...
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Pupil size reflects successful encoding and recall of memory in humans
PublicationPupil responses are known to indicate brain processes involved in perception, attention and decision-making. They can provide an accessible biomarker of human memory performance and cognitive states in general. Here we investigated changes in the pupil size during encoding and recall of word lists. Consistent patterns in the pupil response were found across and within distinct phases of the free recall task. The pupil was most...
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Problems in estimation of hand grip force based on EMG signal
PublicationThere has recently been a significant increase in the number of publications on and applications of bioelectric signals for diagnostic purposes. While the use of ECG (electrocardiography) is not surprising, the use of signals from registration of brain activity (EEG) and muscles activity (EMG) still finds new applications in various fields. The authors focus on the use of EMG signals for estimating hand grip force. Currently,...
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Sathwik Prathapagiri
PeopleSathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Deep Learning Basics 2023/24
e-Learning CoursesA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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The Brain of the city
PublicationIn order to highlight the characteristics of the West End of Wrocław, we conducted a site analysis. Using the strengths of the site, we were able to create a unique concept of the district while minimizing the impacts of weaknesses by design. The purpose of redesigning the West End of Wrocław is to attract new people to the district through the transformation of an identity. Initially, we conducted a SWOT analysis to identify the...
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Olgun Aydin dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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Deep neural networks for data analysis
e-Learning CoursesThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Pathological brain network activity: memory impairment in epilepsy
PublicationOur thinking, memory and cognition in general, relies upon precisely timed interactions among neurons forming brain networks that support cognitive processes. The surgical evaluation of drug-resistant epilepsy using intracranial electrodes provides a unique opportunity to record directly from human brain and to investigate the coordinated activity of cognitive networks. In this issue of Neurology®, Kleen and colleagues1 implicate...
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Investigation on accelerated impedance spectrum measurement method with multisine signal stimulation
PublicationThe paper presents an investigation on the accelerated impedance spectrum measurement method, oriented at parameter identification of technical objects modelled by a linear equivalent circuit, e.g. anticorrosion coatings.The method is based on multisine signal stimulation of an object and response analysis by triangle window filterbanks.It has several advantages, as compared with conventional point-by-point spectrum measurement....
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Deep Learning w Keras
e-Learning CoursesKurs przeznaczony dla słuchaczy studiów podyplomowych Sztuczna inteligencja i automatyzacja procesów biznesowych w ujęciu praktycznym - edycja biznesowa.
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Multimodal system for diagnosis and polysensory stimulation of subjects with communication disorders
PublicationAn experimental multimodal system, designed for polysensory diagnosis and stimulation of persons with impaired communication skills or even non-communicative subjects is presented. The user interface includes an eye tracking device and the EEG monitoring of the subject. Furthermore, the system consists of a device for objective hearing testing and an autostereoscopic projection system designed to stimulate subjects through their...
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Image Segmentation of MRI image for Brain Tumor Detection
Publicationthis research work presents a new technique for brain tumor detection by the combination of Watershed algorithm with Fuzzy K-means and Fuzzy C-means (KIFCM) clustering. The MATLAB based proposed simulation model is used to improve the computational simplicity, noise sensitivities, and accuracy rate of segmentation, detection and extraction from MR...
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublicationThe aim of this paper is to present a system for automatic assigning electroencephalographic (EEG) signals to appropriate classes associated with brain activity. The EEG signals are acquired from a headset consisting of 14 electrodes placed on skull. Data gathered are first processed by the Independent Component Analysis algorithm to obtain estimates of signals generated by primary sources reflecting the activity of the brain....
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Neural networks and deep learning
PublicationIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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CyberEye: New Eye-Tracking Interfaces for Assessment and Modulation of Cognitive Functions beyond the Brain
PublicationThe emergence of innovative neurotechnologies in global brain projects has accelerated research and clinical applications of BCIs beyond sensory and motor functions. Both invasive and noninvasive sensors are developed to interface with cognitive functions engaged in thinking, communication, or remembering. The detection of eye movements by a camera offers a particularly attractive external sensor for computer interfaces to monitor,...
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Intellectual brain drain and economic growth in developing countries: A theoretical solution of strategic compensation
PublicationBrain drain is a real problem for the developing countries like Pakistan. It not only impacts theworkforce, but its effect eventually translates to economic growth as well. The most severe form of braindrain is intellectual as top tier skilled employees’ move out of the country. This study explores the issue ofintellectual brain drain in Pakistan moreover analyzes its severity to the economic growth. Finally,...
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The Unfolded Protein Response: A Double-Edged Sword for Brain Health
PublicationEfficient brain function requires as much as 20% of the total oxygen intake to support normal neuronal cell function. This level of oxygen usage, however, leads to the generation of free radicals, and thus can lead to oxidative stress and potentially to age-related cognitive decay and even neurodegenerative diseases. The regulation of this system requires a complex monitoring network to maintain proper oxygen homeostasis. Furthermore,...
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Experimental tests of reinforced concrete deep-beams
PublicationThe paper presents results of experimental research of the reinforced concrete deep beam with a spatial arrangement. Tested structural elements consist of the cantilever deep beam loaded on the height and transverse deep beam with hanging on it another one. The analysis includes crack morphology, effort of steel and load distribution. The article verified effectiveness of two different kind of reinforcement in both tested deep...
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STEADY STATE VISUALLY EVOKED POTENTIALS FOR BRAIN COMPUTER INTERFACE
PublicationAn experiment conducted to validate a possibility of use a single active electrode EEG device for detecting Steady State Visually Evoked Potentials (SSVEP) is shown. A LED stimulator was applied to stimulate patients with two different frequencies - 13 Hz and 17 Hz. First, EEG signals were recorded and pre-processed using MATLAB software. In the next step recordings were analysed and classified employing the WEKA software. As indicated...
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Sweet grass protection against oxidative stress formation in the rat brain
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...