Search results for "EEG"

showing 10 items of 313 documents

Haptic Perception in Extreme Obesity: qEEG Study Focused on Predictive Coding and Body Schema

2020

Haptic perception (HP) is a perceptual modality requiring manual exploration to elaborate the physical characteristics of external stimuli through multisensory integrative cortical pathways. Cortical areas exploit processes of predictive coding that collect sensorial inputs to build and update internal perceptual models. Modifications to the internal representation of the body have been associated with eating disorders. In the light of this, obese subjects were selected as a valid experimental model to explore predictive coding in haptic perception. To this purpose, we performed electroencephalographic (EEG) continuous recordings during a haptic task in normally weighted versus obese subjec…

power spectrum analysihaptic perceptionmedicine.medical_specialtyobesitytemporal cortexmedia_common.quotation_subjectElectroencephalographyAudiologyhaptic perception; obesity; EEG; multisensory integration; parietal cortex; temporal cortex; power spectrum analysis; body schemaSettore BIO/09 - Fisiologiabehavioral disciplines and activitiesArticlelcsh:RC321-571PerceptionmedicineEEGbody schemapower spectrum analysislcsh:Neurosciences. Biological psychiatry. Neuropsychiatrymedia_commonHaptic technologyTemporal cortexmedicine.diagnostic_testGeneral Neurosciencemultisensory integrationMultisensory integrationBody schemaparietal cortexHaptic perceptionPsychologypsychological phenomena and processesCoding (social sciences)Brain Sciences; Volume 10; Issue 12; Pages: 908
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Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends

2023

Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural acti…

pre-processingsource localizationfunctional connectivitySettore ING-INF/06 - Bioingegneria Elettronica E Informaticadata-drivenEEG; functional connectivity; data-driven; signal acquisition; pre-processing; source localizationBioengineeringEEGsignal acquisitionBioengineering
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Prismatic adaptation modulates oscillatory EEG correlates of motor preparation but not visual attention in healthy participants

2018

Prismatic adaption (PA) has been proposed as a tool to induce neural plasticity and is used to help neglect rehabilitation. It leads to a recalibration of visuo-motor coordination during pointing as well as to after-effects on a number of sensorimotor and attention tasks, but whether these effects originate at a motor or attentional level remains a matter of debate. Our aim was to further characterise PA after-effects by using an approach that allows distinguishing between effects on attentional and motor processes. We recorded electroencephalography (EEG) in healthy human participants (9 females and 7 males) while performing a new double step, anticipatory attention/motor preparation parad…

prismatic adaptationSettore M-PSI/02 - Psicobiologia E Psicologia Fisiologicamotor cortexeeg
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Does predictability matter? Effects of cue predictability on neurocognitive mechanisms underlying prospective memory

2015

Prospective memory (PM) represents the ability to successfully realize intentions when the appropriate moment or cue occurs. In this study, we used event-related potentials (ERPs) to explore the impact of cue predictability on the cognitive and neural mechanisms supporting PM. Participants performed an ongoing task and, simultaneously, had to remember to execute a pre-specified action when they encountered the PM cues. The occurrence of the PM cues was predictable (being signalled by a warning cue) for some participants and was completely unpredictable for others. In the predictable cue condition, the behavioural and ERP correlates of strategic monitoring were observed mainly in the ongoing…

prospective memoryContext (language use)ElectroencephalographyTask (project management)lcsh:RC321-571Behavioral NeuroscienceEvent-related potentialpredictabilityProspective memorymedicineEEGneuralPredictabilitylcsh:Neurosciences. Biological psychiatry. NeuropsychiatryBiological PsychiatryOriginal ResearchAtoDI modelSettore M-PSI/02 - Psicobiologia E Psicologia Fisiologicamedicine.diagnostic_testAtoDI model; ERPs; dynamic multiprocess framework; intention; neural; predictability; prospective memory; strategic monitoringCognitiondynamic multiprocess frameworkERPsPsychiatry and Mental healthNeuropsychology and Physiological PsychologyNeurologyintentionstrategic monitoringPsychologySocial psychologyNeurocognitiveERPCognitive psychologyEvent-related potentialsNeuroscienceFrontiers in Human Neuroscience
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Distinct Patterns of Functional Connectivity During the Comprehension of Natural, Narrative Speech

2020

Recent continuous task studies, such as narrative speech comprehension, show that fluctuations in brain functional connectivity (FC) are altered and enhanced compared to the resting state. Here, we characterized the fluctuations in FC during comprehension of speech and time-reversed speech conditions. The correlations of Hilbert envelope of source-level EEG data were used to quantify FC between spatially separate brain regions. A symmetric multivariate leakage correction was applied to address the signal leakage issue before calculating FC. The dynamic FC was estimated based on a sliding time window. Then, principal component analysis (PCA) was performed on individually concatenated and tem…

puhe (puhuminen)reorganizationspeech comprehensionfunctional connectivitynatural paradigmsnaturalistic speechkuullun ymmärtäminenEEG
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Puuttuvan tiedon käsittely aivosähkökäyrämittauksissa

2016

Aivosähkökäyrämittaukset ovat tyypillisesti hyvin työläitä ja pitkäkestoisia. Näiden seikkojen johdosta otoskoot ovat usein pieniä. Lisäksi osa koehenkilöistä päätyy lopettamaan mittaukset kesken, tai ei jaksa keskittyä annetun ohjeistuksen mukaisesti. Näin ollen valmiiksi hyvin rajalliseen aineistoon syntyy puuttuvuutta siten, että tietyt osakokeet jäävät kokonaan mittaamatta joidenkin henkilöiden osalta. Aineistossa ilmenevä puuttuvuus on käsitelty aivojenkuvantamismittauksissa tavanomaisesti siten, että analyysiin otetaan mukaan vain niitä koehenkilöitä koskevat mittaukset, joilta ei puutu lainkaan tietoa. Tätä menetelmää kutsutaan täydellisten havaintorivien analyysiksi. Tällainen analy…

puuttuva tietobayesilainen menetelmäBaeys-bootstraphot decktilastomenetelmätEEGimputointiERPjackknife
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Quantitative EEG differentiates multiple sclerosis with and without cognitive impairment from healthy controls at the beginning of the disease: preli…

2018

Background and aims: The present study aims to assess possible qEEG differences between newly diagnosed multiple sclerosis (MS) patients with or without cognitive impairment (CI). Methods: We enrolled 22 patients (18-55-years-old) treated with first-line drugs for <6 months, and 11 healthy controls. All subjects underwent neuropsychological assessment including BICAMS and BDI. EEG recordings were performed during a cognitive task (computerised “SDMT” subtest of BICAMS) and at rest. Based on neuropsychological assessment, patients were considered as affected (MSCI group) or not (MS group) by cognitive impairment. We analysed data comparing MSCI patients matched by sex, age (±5years) and e…

qEEG MS power spectrum analysis Cognitive impairmentmultiple sclerosis quantitative EEG cognitive impairmentSettore MED/26 - NeurologiaSettore BIO/09 - Fisiologia
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Māsas un vecāku sadarbība bērna sagatavošanā elektroencefalogrāfijas izmeklēšanai

2017

Bakalaura darba tēma - māsas un vecāku sadarbība bērna sagatavošanā elektroencefalogrāfijas izmeklēšanai. Tēmas aktualitāti nosaka tas, ka elktroencefalogrāfijas izemeklēšana ir viena no biežāk izmantotajām metodēm epilepsijas un citu lēkmjveidīgu stāvokļu diganostikai. EEG izmeklējums ir svarīgs arī uzvedības traucējumu, galvassāpju, valodas attīstības aiztures gadījumos un mācīšanās traucējumu noteikšanai. Darba mērķis ir izzināt un novērtēt vecāku, bērnu un māsas sadarbību bērna sagatavošanā elektroencefalogrāfijas izmeklējumam. Pētniecības uzdevumi ir veikt M.Levaines “Enerģijas saglabāšanas modelis” teorētisko analīzi, apkopot literatūru par elektroencefalogrāfijas izmeklējumu, veikt l…

sadarbībasaskarsmeEEGmāsaMedicīna
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Analysis of event related potentials in a word recognition experiment with fluent and dysfluent readers

2014

Tutkimuksessa on analysoitu EEG-mittauksia, jotka on tehty sanantunnistuskokeen aikana sekä dyslektisille että sujuville lukijoille. Vertaamalla herätevastepotentiaaleja (Event-Related Potential, ERP) sanoille, pseudosanoille ja muille visuaalisille herätteille on työssä saatu tuloksia, jotka näyt- tävät sanantunnistusprosessin sisältävän sekä sarjallisia että rinnakkaisia piirteitä ja hahmottelevat näiden ajallista esiintymistä. Aineiston perusteella sekä kirjaimet että muut symbolit aktivoivat vi- suaalisen sananmuotoalueen (Visual Word Form Area, VWFA). Voidaan havaita, että kirjainjono tunnistetaan sanaksi prosessissa, jossa yleiset sanat tunnistetaan nopeammin kuin harvinaiset. Täl- la…

sanantunnistusdysleksiaEEG
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SingleChannelNet : A model for automatic sleep stage classification with raw single-channel EEG

2022

In diagnosing sleep disorders, sleep stage classification is a very essential yet time-consuming process. Various existing state-of-the-art approaches rely on hand-crafted features and multi-modality polysomnography (PSG) data, where prior knowledge is compulsory and high computation cost can be expected. Besides, it is a big challenge to handle the task with raw single-channel electroencephalogram (EEG). To overcome these shortcomings, this paper proposes an end-to-end framework with a deep neural network, namely SingleChannelNet, for automatic sleep stage classification based on raw single-channel EEG. The proposed model utilizes a 90s epoch as the textual input and employs two multi-conv…

signaalinkäsittelyBiomedical EngineeringsignaalianalyysiHealth InformaticsSleep stage classificationConvolutional neural networkRaw single-channel EEGneuroverkotuni (lepotila)koneoppiminenSignal ProcessingContextual inputEEGunihäiriöt
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