Search results for " Neural Network"
showing 10 items of 1232 documents
Spatiotemporal Neurodynamics Underlying Internally and Externally Driven Temporal Prediction: A High Spatial Resolution ERP Study
2015
Abstract Temporal prediction (TP) is a flexible and dynamic cognitive ability. Depending on the internal or external nature of information exploited to generate TP, distinct cognitive and brain mechanisms are engaged with the same final goal of reducing uncertainty about the future. In this study, we investigated the specific brain mechanisms involved in internally and externally driven TP. To this end, we employed an experimental paradigm purposely designed to elicit and compare externally and internally driven TP and a combined approach based on the application of a distributed source reconstruction modeling on a high spatial resolution electrophysiological data array. Specific spatiotemp…
A deep learning framework for automatic diagnosis of unipolar depression.
2019
Abstract Background and purpose In recent years, the development of machine learning (ML) frameworks for automatic diagnosis of unipolar depression has escalated to a next level of deep learning frameworks. However, this idea needs further validation. Therefore, this paper has proposed an electroencephalographic (EEG)-based deep learning framework that automatically discriminated depressed and healthy controls and provided the diagnosis. Basic procedures In this paper, two different deep learning architectures were proposed that utilized one dimensional convolutional neural network (1DCNN) and 1DCNN with long short-term memory (LSTM) architecture. The proposed deep learning architectures au…
Prediction of the hemoglobin level in hemodialysis patients using machine learning techniques
2013
HighlightsDifferent prediction algorithms were used to predict Hb levels in CRF patients.Prediction errors in the validation cohorts of patients were around 0.6g/dl.Difficulty to obtain lower errors due to the measuring machine precision (0.2g/dl).Relevance analysis of features have been applied for each predictor. Patients who suffer from chronic renal failure (CRF) tend to suffer from an associated anemia as well. Therefore, it is essential to know the hemoglobin (Hb) levels in these patients. The aim of this paper is to predict the hemoglobin (Hb) value using a database of European hemodialysis patients provided by Fresenius Medical Care (FMC) for improving the treatment of this kind of …
Disentangling common and specific neural subprocesses of response inhibition.
2012
article i nfo Response inhibition is disturbed in several disorders sharing impulse control deficits as a core symptom. Since response inhibition is a cognitively and neurally multifaceted function which has been shown to rely on differing neural subprocesses and neurotransmitter systems, further differentiation to define neurophys- iological endophenotypes is essential. Response inhibition may involve at least three separable cognitive sub- components, i.e. interference inhibition, action withholding, and action cancelation. Here, we introduce a novel paradigm - the Hybrid Response Inhibition task - to disentangle interference inhibition, action withholding and action cancelation and their…
The what and how of observational learning
2007
Abstract Neuroimaging evidence increasingly supports the hypothesis that the same neural structures subserve the execution, imagination, and observation of actions. We used repetitive transcranial magnetic stimulation (rTMS) to investigate the specific roles of cerebellum and dorsolateral prefrontal cortex (DLPFC) in observational learning of a visuomotor task. Subjects observed an actor detecting a hidden sequence in a matrix and then performed the task detecting either the previously observed sequence or a new one. rTMS applied over the cerebellum before the observational training interfered with performance of the new sequence, whereas rTMS applied over the DLPFC interfered with performa…
pBrain: A novel pipeline for Parkinson related brain structure segmentation
2020
[EN] Parkinson is a very prevalent neurodegenerative disease impacting the life of millions of people worldwide. Although its cause remains unknown, its functional and structural analysis is fundamental to advance in the search of a cure or symptomatic treatment. The automatic segmentation of deep brain structures related to Parkinson's disease could be beneficial for the follow up and treatment planning. Unfortunately, there is not broadly available segmentation software to automatically measure Parkinson related structures. In this paper, we present a novel pipeline to segment three deep brain structures related to Parkinson's disease (substantia nigra, subthalamic nucleus and red nucleus…
Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures
2001
In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of …
Neural correlates of interference inhibition, action withholding and action cancelation in adult ADHD
2011
Attention-Deficit/Hyperactivity Disorder (ADHD) is marked by inhibitory and attentional deficits which can persist into adulthood. Those deficits have been associated with dysfunctional fronto-striatal and fronto-parietal circuits. The present study sought to delineate neural correlates of component specific inhibitory deficits in adult ADHD using functional magnetic resonance imaging (fMRI). 20 adult ADHD patients and 24 matched healthy controls were included. Brain activation was assessed during three stages of behavioral inhibition, i.e. interference inhibition (Simon task), action withholding (Go/no-go task) and action cancelation (Stop-signal task). Behaviorally, ADHD patients were aff…
Diagnosing fatigue in gait patterns by support vector machines and self-organizing maps
2009
The aim of the study was to train and test support vector machines (SVM) and self-organizing maps (SOM) to correctly classify gait patterns before, during and after complete leg exhaustion by isokinetic leg exercises. Ground reaction forces were derived for 18 gait cycles on 9 adult participants. Immediately before the trials 7-12, participants were required to completely exhaust their calves with the aid of additional weights (44.4±8.8kg). Data were analyzed using: (a) the time courses directly and (b) only the deviations from each individual's calculated average gait pattern. On an inter-individual level the person recognition of the gait patterns was 100% realizable. Fatigue recognition …
Online detection of rem sleep based on the comprehensive evaluation of short adjacent eeg segments by artificial neural networks
1997
Abstract 1. 1. For scientific and clinical requirements the present objective is a robust automatic online algorithm to detect rapid eye movement (REM) steep from single channel sleep EEG data without using EMG or EOG information. 2. 2. For data preprocessing 20 seconds time periods of the continuous EEG activity are digitally filtered in 7 frequency bands. Then the RMS values of these filtered signals are calculated along segments of 2.5 seconds. The resulting matrix of RMS values is representing information on the power of the signal localized in time and frequency and serves as input to an artificial neural network. A pooled set of EEG data together with the corresponding manual evaluati…