Search results for "hermoverkot"
showing 7 items of 17 documents
Aberrant brain functional networks in type 2 diabetes mellitus: A graph theoretical and support-vector machine approach
2022
ObjectiveType 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.MethodsA total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were ana…
Koneoppimisen hyödyntäminen konenäössä
2016
Konenäön hyödyntäminen yleistyy ja sitä mukaa myös konenäön ongelmat monimutkaistuvat. Yksi suosittu tapa ratkaista näitä ongelmia on hyödyntää koneoppimista. Tässä tutkielmassa tarkastellaan miten koneoppimista hyödynnetään konenäössä ja vertaillaan eri koneoppimisalgoritmeja konenäön näkökulmasta. omputer Vision faces increasing challenges as its used more. Common way to solve these complex problems is to use Machine Learning. In this thesis workings of different Machine Learing algorithms are looked on and their advantages and disadvantages are compared.
Identifying Oscillatory Hyperconnectivity and Hypoconnectivity Networks in Major Depression Using Coupled Tensor Decomposition
2021
AbstractPrevious researches demonstrate that major depression disorder (MDD) is associated with widespread network dysconnectivity, and the dynamics of functional connectivity networks are important to delineate the neural mechanisms of MDD. Cortical electroencephalography (EEG) oscillations act as coordinators to connect different brain regions, and various assemblies of oscillations can form different networks to support different cognitive tasks. Studies have demonstrated that the dysconnectivity of EEG oscillatory networks is related with MDD. In this study, we investigated the oscillatory hyperconnectivity and hypoconnectivity networks in MDD under a naturalistic and continuous stimuli…
Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression
2021
To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscil…
Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics
2012
In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESCs), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing …
Spatio-temporal Dynamical Analysis of Brain Activity during Mental Fatigue Process
2021
Mental fatigue is a common phenomenon with implicit and multidimensional properties. It brings dynamic changes of functional brain networks. However, the challenging problem of false positives appears when the connectivity is estimated by Electroencephalography (EEG). In this paper, we propose a novel framework based on spatial clustering to explore the sources of mental fatigue and functional activity changes caused by them. To suppress the false positive observations, spatial clustering is implemented in brain networks. The nodes extracted by spatial clustering are registered back to functional magnetic resonance imaging (fMRI) source space to determined the sources of mental fatigue. The…
Rhythmic Memory Consolidation in the Hippocampus
2022
Functions of the brain and body are oscillatory in nature and organized according to a logarithmic scale. Brain oscillations and bodily functions such as respiration and heartbeat appear nested within each other and coupled together either based on phase or based on phase and amplitude. This facilitates communication in wide-spread neuronal networks and probably also between the body and the brain. It is a widely accepted view, that nested electrophysiological brain oscillations involving the neocortex, thalamus, and the hippocampus form the basis of memory consolidation. This applies especially to declarative memories, that is, memories of life events, for example. Here, we present our vie…