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Wyniki wyszukiwania dla: INTRACRANIAL EEG (IEEG)
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0021)
Dane BadawczeData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0020)
Dane BadawczeData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0019)
Dane BadawczeData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0024)
Dane BadawczeData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_0023)
Dane BadawczeData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Direct electrical stimulation of the human brain has inverse effects on the theta and gamma neural activities
PublikacjaObjective: 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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Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding
PublikacjaBACKGROUND: We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding. METHODS: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the...
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Gamma oscillations precede interictal epileptiform spikes in the seizure onset zone
PublikacjaOBJECTIVE: To investigate the generation, spectral characteristics, and potential clinical significance of brain activity preceding interictal epileptiform spike discharges (IEDs) recorded with intracranial EEG. METHODS: Seventeen adult patients with drug-resistant temporal lobe epilepsy were implanted with intracranial electrodes as part of their evaluation for epilepsy surgery. IEDs detected on clinical macro- and research microelectrodes...
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Electrical Stimulation Modulates High Gamma Activity and Human Memory Performance
PublikacjaDirect 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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Reactivation of seizure‐related changes to interictal spike shape and synchrony during postseizure sleep in patients
PublikacjaOBJECTIVE: Local field potentials (LFPs) arise from synchronous activation of millions of neurons, producing seemingly consistent waveform shapes and relative synchrony across electrodes. Interictal spikes (IISs) are LFPs associated with epilepsy that are commonly used to guide surgical resection. Recently, changes in neuronal firing patterns observed in the minutes preceding seizure onset were found to be reactivated during postseizure...
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Balance recognition on the basis of EEG measurement.
PublikacjaAlthough electroencephalography (EEG) is not typically used for verifying the sense of balance, it can be used for analysing cortical signals responsible for this phenomenon. Simple balance tasks can be proposed as a good indicator of whether the sense of balance is acting more or less actively. This article presents preliminary results for the potential of using EEG to balance sensing....
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Metody redukcji artefaktów w zapisie EEG.
PublikacjaPrzegląd i opis metod badania EEG jego uwarunkowań technicznych oraz problemy z tym związane. Dokonano przeglądu metod pozwalających na zredukowanie bądź eliminacje artefaktów w zapisie EEG.
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Labeler-hot Detection of EEG Epileptic Transients
PublikacjaPreventing early progression of epilepsy and sothe severity of seizures requires effective diagnosis. Epileptictransients indicate the ability to develop seizures but humansoverlook such brief events in an electroencephalogram (EEG)what compromises patient treatment. Traditionally, trainingof the EEG event detection algorithms has relied on groundtruth labels, obtained from the consensus...
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublikacjaIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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Tensor Decomposition for Imagined Speech Discrimination in EEG
PublikacjaMost of the researches in Electroencephalogram(EEG)-based Brain-Computer Interfaces (BCI) are focused on the use of motor imagery. As an attempt to improve the control of these interfaces, the use of language instead of movement has been recently explored, in the form of imagined speech. This work aims for the discrimination of imagined words in electroencephalogram signals. For this purpose, the analysis of multiple variables...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-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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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublikacjaThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublikacjaThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Brain-computer interaction based on EEG signal and gaze-tracking information = Analiza interackji mózg-komputer wykorzystująca sygnał EEg i informacje z systemu śledzenia punktu fiksacji wzroku
PublikacjaThe article presents an attempt to integrate EEG signal analysis with information about human visual activities, i.e. gaze fixation point. The results from gaze-tracking-based measurement were combined with the standard EEG analysis. A search for correlation between the brain activity and the region of the screen observed by the user was performed. The preliminary stage of the study consists in electrooculography (EOG) signal processing....
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublikacjaThe 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....