Search results for "processi"
showing 10 items of 9638 documents
Early access to abstract representations in developing readers: evidence from masked priming
2013
A commonly shared assumption in the field of visual-word recognition is that retinotopic representations are rapidly converted into abstract representations. Here we examine the role of visual form vs. abstract representations during the early stages of word processing - as measured by masked priming - in young children (3rd and 6th Graders) and adult readers. To maximize the chances of detecting an effect of visual form, we employed a language with a very intricate orthography, Arabic. If visual form plays a role in the early stages of processing, greater benefit would be expected from related primes that have the same visual form (in terms of the ligation pattern between a word's letters)…
Chronometry of parietal and prefrontal activations in verbal working memory revealed by transcranial magnetic stimulation.
2003
We explored the temporal dynamics of parietal and prefrontal cortex involvement in verbal working memory employing single-pulse transcranial magnetic stimulation (TMS). In six healthy volunteers the left or right inferior parietal and prefrontal cortex was stimulated with the aid of a frameless stereotactic system. TMS was applied at 10 different time points 140-500 ms into the delay period of a two-back verbal working memory task. A choice reaction task was used as a control task. Interference with task accuracy was induced by TMS earlier in the parietal cortex than in the prefrontal cortex and earlier over the right than the left hemisphere. This suggests a propagation of information flow…
New perspectives on the manipulation of opiate urges and the assessment of cognitive effort associated with opiate urges
2000
Behavioral models of drug urges assume that conditioned urges are strongly associated with drug consumption. An alternative, cognitive model assumes that urges represent the operation of cognitively demanding processes devoted to either supporting or blocking the automatized drug-use behavior. In Study 1, the effect of verbal drug cues and mood induction on self-reported opiate urges were examined. Twenty-four opiate addicts were either instructed to listen to verbal drug cures or neutral cues. Negative mood induction was applied on 12 addicts. Study 2 examined the cognitive processes underlying these urges. In a dual task paradigm, participants responded to a probe stimulus and listened si…
From Vivaldi to Beatles and back: predicting lateralized brain responses to music.
2013
We aimed at predicting the temporal evolution of brain activity in naturalistic music listening conditions using a combination of neuroimaging and acoustic feature extraction. Participants were scanned using functional Magnetic Resonance Imaging (fMRI) while listening to two musical medleys, including pieces from various genres with and without lyrics. Regression models were built to predict voxel-wise brain activations which were then tested in a cross-validation setting in order to evaluate the robustness of the hence created models across stimuli. To further assess the generalizability of the models we extended the cross-validation procedure by including another dataset, which comprised …
LOW-RANK APPROXIMATION BASED NON-NEGATIVE MULTI-WAY ARRAY DECOMPOSITION ON EVENT-RELATED POTENTIALS
2014
Non-negative tensor factorization (NTF) has been successfully applied to analyze event-related potentials (ERPs), and shown superiority in terms of capturing multi-domain features. However, the time-frequency representation of ERPs by higher-order tensors are usually large-scale, which prevents the popularity of most tensor factorization algorithms. To overcome this issue, we introduce a non-negative canonical polyadic decomposition (NCPD) based on low-rank approximation (LRA) and hierarchical alternating least square (HALS) techniques. We applied NCPD (LRAHALS and benchmark HALS) and CPD to extract multi-domain features of a visual ERP. The features and components extracted by LRAHALS NCP…
Multi-domain feature extraction for small event-related potentials through nonnegative multi-way array decomposition from low dense array EEG
2013
Non-negative Canonical Polyadic decomposition (NCPD) and non-negative Tucker decomposition (NTD) were compared for extracting the multi-domain feature of visual mismatch negativity (vMMN), a small event-related potential (ERP), for the cognitive research. Since signal-to-noise ratio in vMMN is low, NTD outperformed NCPD. Moreover, we proposed an approach to select the multi-domain feature of an ERP among all extracted features and discussed determination of numbers of extracted components in NCPD and NTD regarding the ERP context.
Intra-individual gait patterns across different time-scales as revealed by means of a supervised learning model using kernel-based discriminant regre…
2017
Objective Traditionally, gait analysis has been centered on the idea of average behavior and normality. On one hand, clinical diagnoses and therapeutic interventions typically assume that average gait patterns remain constant over time. On the other hand, it is well known that all our movements are accompanied by a certain amount of variability, which does not allow us to make two identical steps. The purpose of this study was to examine changes in the intra-individual gait patterns across different time-scales (i.e., tens-of-mins, tens-of-hours). Methods Nine healthy subjects performed 15 gait trials at a self-selected speed on 6 sessions within one day (duration between two subsequent ses…
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…
Reproducibility of multiphase pseudo-continuous arterial spin labeling and the effect of post-processing analysis methods
2015
Arterial spin labeling (ASL) is an emerging MRI technique for non-invasive measurement of cerebral blood flow (CBF). Compared to invasive perfusion imaging modalities, ASL suffers from low sensitivity due to poor signal-to-noise ratio (SNR), susceptibility to motion artifacts and low spatial resolution, all of which limit its reliability. In this work, the effects of various state of the art image processing techniques for addressing these ASL limitations are investigated. A processing pipeline consisting of motion correction, ASL motion correction imprecision removal, temporal and spatial filtering, partial volume effect correction, and CBF quantification was developed and assessed. To fur…
k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation
2011
The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15. Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or …