Search results for " intelligence"
showing 10 items of 6677 documents
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…
Distinct neural-behavioral correspondence within face processing and attention networks for the composite face effect
2022
The composite face effect (CFE) is recognized as a hallmark for holistic face processing, but our knowledge remains sparse about its cognitive and neural loci. Using functional magnetic resonance imaging with independent localizer and complete composite face task, we here investigated its neural-behavioral correspondence within face processing and attention networks. Complementing classical comparisons, we adopted a dimensional reduction approach to explore the core cognitive constructs of the behavioral CFE measurement. Our univariate analyses found an alignment effect in regions associated with both the extended face processing network and attention networks. Further representational simi…
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…
Holistic face processing is induced by shape and texture.
2013
There is increasing evidence that shape and texture are integral parts of face identity. However, it is less clear whether face-specific processing mechanisms are triggered by face shape alone, or if texture might play an important role. We address this question by studying mechanisms involved in holistic face processing. Face stimuli were either full-color pictures of real faces (shape and texture) or line drawings of the same faces (shape without texture). In a change detection task subjects judged whether eyes and eyebrows in two otherwise identical, sequentially presented faces were different in size or not. Afterwards, subjects had to identify the just presented face among two distrac…
Path Following in Non-Visual Conditions.
2018
Path-following tasks have been investigated mostly under visual conditions, that is when subjects are able to see both the path and the tool, or limb, used for navigation. Moreover, only basic path shapes are usually adopted. In the present experiment, participants must rely exclusively on continuous, non-speech, and ecological auditory and vibrotactile cues to follow a path on a flat surface. Two different, asymmetric path shapes were tested. Participants navigated by moving their index finger over a surface sensing position and force. Results show that the different non-visual feedback modes did not affect the task's accuracy, yet they affected its speed, with vibrotactile feedback causin…
Pointing to a target from an upright position in human: tuning of postural responses when there is target uncertainty
2000
International audience; Human subjects performed, from a standing position, rapid hand pointings to visual targets located within or beyond the prehension space. To examine the interaction between posture and the goal-directed movement we introduced a visual double-step perturbation requiring a reprogramming of the hand movement. Trials directed towards the same spatial goal but differentiated only by the likeliness of a visual double-step were compared. The hand kinematics was not affected by the uncertainty of the visual perturbation; an increased trunk bending, however, was observed. This suggests that uncertainty constraints are integrated in a predictive manner for the optimal coordina…
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 …
Reliability of Magnetoencephalography and High-Density Electroencephalography Resting-State Functional Connectivity Metrics
2019
Resting-state connectivity, for example, based on magnetoencephalography (MEG) or electroencephalography (EEG), is a widely used method for characterizing brain networks and a promising imaging biomarker. However, there is no established standard as to which method, modality, and analysis variant is preferable and there is only limited knowledge on the reproducibility, an important prerequisite for clinical application. We conducted an MEG-/ high-density (hd)-EEG-study on 22 young healthy adults, who were measured twice in a scan/rescan design after 7 – 2 days. Reliability of resting-state (15 min, eyes-closed) connectivity in source space was calculated via intraclass correlation coefficie…
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 …
Surrogate data analysis of sleep electroencephalograms reveals evidence for nonlinearity
1996
We tested the hypothesis of whether sleep electroencephalographic (EEG) signals of different time windows (164 s, 82 s, 41 s and 20.5 s) are in accordance with linear stochastic models. For this purpose we analyzed the all-night sleep electroencephalogram of a healthy subject and corresponding Gaussian-rescaled phase randomized surrogates with a battery of five non-linear measures. The following nonlinear measures were implemented: largest Lyapunov exponent L1, correlation dimension D2, and the Green-Savit measures delta 2, delta 4 and delta 6. The hypothesis of linear stochastic data was rejected with high statistical significance. L1 and D2 yielded the most pronounced effects, while the G…