Varhaisten visuaalisten EEG vasteiden mallintaminen kuva-ärsykkeen ominaisuuksien mukaan

Introduction Experiment consisting of a visual search was conducted in order to investigate the effect of top-down and bottom-up processing with natural stimuli. Gray-scale photographs of nature scenes were used as stimuli. Stimuli had two conditions: natural and scrambled. Natural images were unaltered photographs and in scrambled images the global information was reduced. Aim Aim of the experiment was to form statistical models explaining the effect the amplitude of early visual potentials as functions of visual input, oculomotor variables and top-down factors. Methods Magnetoencephalography (MEG), electroencephalography (EEG) and eye tracking were recorded simultaneously during the experiment. In the scope of this thesis only EEG and eye tracking were analysed. Statistical models were generated using a method called linear mixed (effect) modeling. Results Data analysis produced two models describing the early visual potential as parameters of visual input and oculomotor variables. The effect of top-down processing was investigated as an additional statistical test. Conclusion Out of the two generated models the visual input model was deemed more accurate due to spatial focality and amplitude latency. Results of the study indicate that early visual responses in EEG correlate strongly with low-level visual inputs and to a lesser degree with oculomotor variables. No evidence of correlation between response amplitude and top-down factors were observed.Johdanto Visuaalista tarkkaavaisuutta tutkittiin koeasetelmassa, jossa koehenkilöt etsivät heille esitettyjä kuvan osia suuremmista luontovalokuvista. Kuvia oli kahta tyyppiä: muokkaamattomia, sekä kuvia joista globaali informaatio oli hävitetty. Tavoite Kokeen tavoitteena oli kehittää visuaalisia hermostovasteita kuvaava tilastollinen malli. Mallin avulla oli tarkoitus tutkia kuinka matalan ja korkean tason tarkkaavaisuusprosessit vaikuttavat mitattuun vasteeseen. Menetelmät Kokeen aikana koehenkilöiltä mitattiin aivosähkökäyrää (EEG), aivomagneettikäyrää (MEG) sekä silmänliikettä. Kerätty data analysoitiin mallintamalla katseeseen synkronisoituja EEG-vasteita tilastollisesti. Kokeessa kerättyä MEG dataa ei analysoitu tämän työn puitteissa. Mallintamiseen käytettiin lineaarisia sekamalleja, jotka muodostettiin ärsykekuvien, silmänliikkeiden ja tarkkaavaisuusprosessien avulla. Tulokset Mallintaminen tuotti kaksi erilaista mallia, jotka selittivät syntyneen vasteen visuaali-informaation ja silmänliikkeiden perusteella. Korkean tason tarkkaavaisuuden vaikutusta tutkittiin molemmissa malleissa ylimääräisellä tilastollisella testillä. Johtopäätökset Kahdesta tuotetusta mallista visuaalimalli vaikutti todenmukaisemmalta. Silmänliikemallin tulokset olivat puolestaan epävarmempia sijaintinsa ja esiintymislatenssinsa takia. Kummankaan mallin tapauksessa ei havaittu todisteita korkean tason tarkkaavaisuuden vaikutuksesta vasteisiin

Computational Testing for Automated Preprocessing : a Matlab toolbox to enable large scale electroencephalography data processing

Electroencephalography (EEG) is a rich source of information regarding brain function. However, the preprocessing of EEG data can be quite complicated, due to several factors. For example, the distinction between true neural sources and noise is indeterminate; EEG data can also be very large. The various factors create a large number of subjective decisions with consequent risk of compound error. Existing tools present the experimenter with a large choice of analysis methods. Yet it remains a challenge for the researcher to integrate methods for batch-processing of the average large datasets, and compare methods to choose an optimal approach across the many possible parameter configurations. Additionally, many tools still require a high degree of manual decision making for, e.g. the classification of artefacts in channels, epochs or segments. This introduces extra subjectivity, is slow and is not reproducible. Batching and well-designed automation can help to regularise EEG preprocessing, and thus reduce human effort, subjectivity and consequent error. We present the computational testing for automated preprocessing (CTAP) toolbox, to facilitate: (i) batch-processing that is easy for experts and novices alike; (ii) testing and manual comparison of preprocessing methods. CTAP extends the existing data structure and functions from the well-known EEGLAB toolbox, based on Matlab and produces extensive quality control outputs. CTAP is available under MIT licence from https://github.com/bwrc/ctap.Peer reviewe

Eye movement related brain responses to emotional scenes during free viewing

Emotional stimuli are preferentially processed over neutral stimuli. Previous studies, however, disagree on whether emotional stimuli capture attention preattentively or whether the processing advantage is dependent on allocation of attention. The present study investigated attention and emotion processes by measuring brain responses related to eye movement events while 11 participants viewed images selected from the International Affective Picture System (IAPS). Brain responses to emotional stimuli were compared between serial and parallel presentation. An “emotional” set included one image with high positive or negative valence among neutral images. A “neutral” set comprised four neutral images. The participants were asked to indicate which picture—if any—was emotional and to rate that picture on valence and arousal. In the serial condition, the event-related potentials (ERPs) were time-locked to the stimulus onset. In the parallel condition, the ERPs were time-locked to the first eye entry on an image. The eye movement results showed facilitated processing of emotional, especially unpleasant information. The EEG results in both presentation conditions showed that the LPP (“late positive potential”) amplitudes at 400–500 ms were enlarged for the unpleasant and pleasant pictures as compared to neutral pictures. Moreover, the unpleasant scenes elicited stronger responses than pleasant scenes. The ERP results did not support parafoveal emotional processing, although the eye movement results suggested faster attention capture by emotional stimuli. Our findings, thus, suggested that emotional processing depends on overt attentional resources engaged in the processing of emotional content. The results also indicate that brain responses to emotional images can be analyzed time-locked to eye movement events, although the response amplitudes were larger during serial presentation.Peer reviewe

Cognitive Collaboration Found in Cardiac Physiology : Study in Classroom Environment

It is known that periods of intense social interaction result in shared patterns in collaborators' physiological signals. However, applied quantitative research on collaboration is hindered due to scarcity of objective metrics of teamwork effectiveness. Indeed, especially in the domain of productive, ecologically-valid activity such as programming, there is a lack of evidence for the most effective, affordable and reliable measures of collaboration quality. In this study we investigate synchrony in physiological signals between collaborating computer science students performing pair-programming exercises in a class room environment. We recorded electrocardiography over the course of a 60 minute programming session, using lightweight physiological sensors. We employ correlation of heart-rate variability features to study social psychophysiological compliance of the collaborating students. We found evident physiological compliance in collaborating dyads' heart-rate variability signals. Furthermore, dyads' self-reported workload was associated with the physiological compliance. Our results show viability of a novel approach to field measurement using lightweight devices in an uncontrolled environment, and suggest that self-reported collaboration quality can be assessed via physiological signals.Peer reviewe

Using Galvanic Vestibular Stimulation to Sense Abstract Data

We propose using galvanic vestibular stimulation for presenting abstract data, for instance stock market trends. Using galvanic vestibular stimulation, data is felt directly as a perturbation in the sense of balance. This work is showcased as an art performance, where stock market fluctuations cause a person to maintain or lose balance. We present the artistic and technical principles underlying the performance and describe the technical implementation of a working system. The work shows how abstract data can be presented in a way that is not limited to visual, auditory, olfactory, or tactile sensing.Peer reviewe

Near-Infrared Spectroscopy Enables Arthroscopic Histologic Grading of Human Knee Articular Cartilage

Purpose: To develop the means to estimate cartilage histologic grades and proteoglycan content in ex vivo arthroscopy using near-infrared spectroscopy (NIRS). Methods: In this experimental study, arthroscopic NIR spectral measurements were performed on both knees of 9 human cadavers, followed by osteochondral block extraction and in vitro measurements: reacquisition of spectra and reference measurements (proteoglycan content, and three histologic scores). A hybrid model, combining principal component analysis and linear mixed-effects model (PCA-LME), was trained for each reference to investigate its relationship with in vitro NIR spectra. The performance of the PCA-LME model was validated with ex vivo spectra before and after the exclusion of outlying spectra. Model performance was evaluated based on Spearman rank correlation (ρ) and root-mean-square error (RMSE). Results: The PCA-LME models performed well (independent test: average ρ = 0.668, RMSE = 0.892, P < .001) in the prediction of the reference measurements based on in vitro data. The performance on ex vivo arthroscopic data was poorer but improved substantially after outlier exclusion (independent test: average ρ = 0.462 to 0.614, RMSE = 1.078 to 0.950, P = .019 to .008). Conclusions: NIRS is capable of nondestructive evaluation of cartilage integrity (i.e., histologic scores and proteoglycan content) under similar conditions as in clinical arthroscopy. Clinical Relevance: There are clear clinical benefits to the accurate assessment of cartilage lesions in arthroscopy. Visual grading is the current standard of care. However, optical techniques, such as NIRS, may provide a more objective assessment of cartilage damage.publishedVersionPeer reviewe

The NDE1 genomic locus can affect treatment of psychiatric illness through gene expression changes related to microRNA-484

Genetic studies of familial schizophrenia in Finland have observed significant associations with a group of biologically related genes, DISCI1, NDE1,NDEL1, PDE4B and PDE4D, the 'DISCI network'. Here, we use gene expression and psychoactive medication use data to study their biological consequences and potential treatment implications. Gene expression levels were determined in 64 individuals from 18 families, while prescription medication information has been collected over a 10 -year period for 931 affected individuals. We demonstrate that the NDE1 SNP rs2242549 associates with significant changes in gene expression for 2908 probes (2542 genes), of which 794 probes (719 genes) were replicable. A significant number of the genes altered were predicted targets of microRNA-484 (p = 3.0 x 10(-8)), located on a non -coding exon of NDE1. Variants within the NM. locus also displayed significant genotype by gender interaction to early cessation of psychoactive medications metabolized by CYP2C19. Furthermore, we demonstrate that miR-484 can affect the expression of CYP2C19 in a cell culture system. Thus, variation at the IVDET locus may alter risk of mental illness, in part through modification of miR-484, and such modification alters treatment response to specific psychoactive medications, leading to the potential for use of this locus in targeting treatment.Peer reviewe

Near infrared spectroscopic evaluation of biochemical and crimp properties of knee joint ligaments and patellar tendon

Knee ligaments and tendons play an important role in stabilizing and controlling the motions of the knee. Injuries to the ligaments can lead to abnormal mechanical loading of the other supporting tissues (e.g., cartilage and meniscus) and even osteoarthritis. While the condition of knee ligaments can be examined during arthroscopic repair procedures, the arthroscopic evaluation suffers from subjectivity and poor repeatability. Near infrared spectroscopy (NIRS) is capable of non-destructively quantifying the composition and structure of collagen-rich connective tissues, such as articular cartilage and meniscus. Despite the similarities, NIRS-based evaluation of ligament composition has not been previously attempted. In this study, ligaments and patellar tendon of ten bovine stifle joints were measured with NIRS, followed by chemical and histological reference analysis. The relationship between the reference properties of the tissue and NIR spectra was investigated using partial least squares regression. NIRS was found to be sensitive towards the water (R2CV = .65) and collagen (R2CV = .57) contents, while elastin, proteoglycans, and the internal crimp structure remained undetectable. As collagen largely determines the mechanical response of ligaments, we conclude that NIRS demonstrates potential for quantitative evaluation of knee ligaments.publishedVersionPeer reviewe

The psychophysiology primer : A guide to methods and a broad review with a focus on human-computer interaction

Publisher Copyright: © 2016 B. Cowley, M. Filetti, K. Lukander.Peer reviewe

Reaction Time and Visual Memory in Connection with Alcohol Use in Schizophrenia and Schizoaffective Disorder

The purpose of this study was to explore the association between cognition and hazardous drinking and alcohol use disorder in schizophrenia and schizoaffective disorder. Cognition is more or less compromised in schizophrenia, and schizoaffective disorder and alcohol use might aggravate this phenomenon. The study population included 3362 individuals from Finland with diagnoses of schizophrenia or schizoaffective disorder. Hazardous drinking was screened with the AUDIT-C (Alcohol Use Disorders Identification Test for Consumption) screening tool. Alcohol use disorder (AUD) diagnoses were obtained from national registrar data. Participants performed two computerized tasks from the Cambridge Automated Neuropsychological Test Battery (CANTAB) on a tablet computer: The Five-Choice Serial Reaction Time Task (5-CSRTT) or the reaction time (RT) test and the Paired Associative Learning (PAL) test. The association between alcohol use and the RT and PAL tests was analyzed with log-linear regression and logistic regression, respectively. After adjustment for age, education, housing status, and the age at which the respondents had their first psychotic episodes, hazardous drinking was associated with a lower median RT in females and less variable RT in males, while AUD was associated with a poorer PAL test performance in terms of the total errors adjusted scores (TEASs) in females. Our findings of positive associations between alcohol and cognition in schizophrenia and schizoaffective disorder are unique.Peer reviewe