STUDYING SINGLE-TRIALS OF PHASE SYNCHRONOUS ACTIVITY IN THE BRAIN

2000 ◽  
Vol 10 (10) ◽  
pp. 2429-2439 ◽  
Author(s):  
JEAN-PHILIPPE LACHAUX ◽  
EUGENIO RODRIGUEZ ◽  
MICHEL LE VAN QUYEN ◽  
ANTOINE LUTZ ◽  
JACQUES MARTINERIE ◽  
...  
Keyword(s):  
Face Recognition ◽  
Long Range ◽  
Phase Locking ◽  
Previous Method ◽  
New Method ◽  
Single Trial ◽  
Brain Signals ◽  
The Brain ◽  
Trial Phase ◽  
Pls Method

This paper introduces a new method, single-trial phase locking statistics (S-PLS) to estimate phase locking in single trials of brain signals between two electrodes. The possibility of studying single trials removes an important limitation in the study of long-range synchrony in brain signals. S-PLS is closely related to our previous method, phase locking statistics (PLS) that estimates phase locking over a set of trials. The S-PLS method is described in detail and applied to human surface recordings during the task of face-recognition. We compare these results with those provided by PLS and show that they are qualitatively very similar, although S-PLS provides better discrimination of synchronic episodes.

Low Frequency Phase-locking of Brain Signals Contribute to Efficient Face Recognition

Neuroscience ◽  
2019 ◽  
Vol 422 ◽  
pp. 172-183 ◽  
Author(s):  
Yifeng Wang ◽  
Xinju Huang ◽  
Xuezhi Yang ◽  
Qi Yang ◽  
Xinqi Wang ◽  
...  
Keyword(s):  
Face Recognition ◽  
Phase Locking ◽  
Low Frequency ◽  
Brain Signals ◽  
Frequency Phase

NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

2019 ◽  
pp. 139-145
Author(s):  
Selma Büyükgöze
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Electrode Placement ◽  
Eeg Signals ◽  
Non Invasive ◽  
Brain Signals ◽  
Brain States ◽  
The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

Phase-Locked Responses to Pure Tones in the Inferior Colliculus

2006 ◽  
Vol 95 (3) ◽  
pp. 1926-1935 ◽  
Author(s):  
Liang-Fa Liu ◽  
Alan R. Palmer ◽  
Mark N. Wallace
Keyword(s):  
Guinea Pig ◽  
Inferior Colliculus ◽  
Phase Locking ◽  
Single Units ◽  
Central Nucleus ◽  
Dorsal Cortex ◽  
Upper Limits ◽  
Ascending Pathways ◽  
Pure Tones ◽  
The Brain

In the auditory system, some ascending pathways preserve the precise timing information present in a temporal code of frequency. This can be measured by studying responses that are phase-locked to the stimulus waveform. At each stage along a pathway, there is a reduction in the upper frequency limit of the phase-locking and an increase in the steady-state latency. In the guinea pig, phase-locked responses to pure tones have been described at various levels from auditory nerve to neocortex but not in the inferior colliculus (IC). Therefore we made recordings from 161 single units in guinea pig IC. Of these single units, 68% (110/161) showed phase-locked responses. Cells that phase-locked were mainly located in the central nucleus but also occurred in the dorsal cortex and external nucleus. The upper limiting frequency of phase-locking varied greatly between units (80−1,034 Hz) and between anatomical divisions. The upper limits in the three divisions were central nucleus, >1,000 Hz; dorsal cortex, 700 Hz; external nucleus, 320 Hz. The mean latencies also varied and were central nucleus, 8.2 ± 2.8 (SD) ms; dorsal cortex, 17.2 ms; external nucleus, 13.3 ms. We conclude that many cells in the central nucleus receive direct inputs from the brain stem, whereas cells in the external and dorsal divisions receive input from other structures that may include the forebrain.

A new method of NIR face recognition using kernel projection DCV and neural networks

2013 ◽  
Author(s):  
Ya Qiao ◽  
Yuan Lu ◽  
Yun-song Feng ◽  
Feng Li ◽  
Yongshun Ling
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
New Method

Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition

NeuroImage ◽  
2014 ◽  
Vol 100 ◽  
pp. 325-336 ◽  
Author(s):  
Jonathan Wirsich ◽  
Christian Bénar ◽  
Jean-Philippe Ranjeva ◽  
Médéric Descoins ◽  
Elisabeth Soulier ◽  
...  
Keyword(s):  
Face Recognition ◽  
Bold Signal ◽  
Spatial Dependency ◽  
Single Trial

Differentiation of Healthy Individuals from Those with Autism Spectrum Disorders using Information Graph of Complementary Opposites

2020 ◽  
Keyword(s):  
Children With Autism ◽  
Autism Spectrum ◽  
Brain Signals ◽  
Three Stages ◽  
The Mean ◽  
Spectrum Disorders ◽  
Pediatric Psychiatry ◽  
The Brain ◽  
Optimal Feature ◽  
Information Graph

This study aimed to examine the brain signals of children with Autism Spectrum Disorder (ASD) and use a method according to the concept of complementary opposites to obtain the prominent features or a pattern of EEG signal that represents the biological characteristic of such children. In this study, 20 children with the mean±SD age of 8±5 years were divided into two groups of normal control (NC) and ASD. The diagnosis and approval of individuals in both groups were conducted by two experts in the field of pediatric psychiatry and neurology. The recording protocol was designed with the most accuracy; therefore, the brain signals were recorded with the least noise in the awake state of the individuals in both groups. Moreover, the recording was conducted in three stages from two channels (C3-C4) of EEG ( referred to as the central part of the brain) which were symmetrical in function. In this study, the Mandala method was adopted based on the concept of complementary opposites to investigate the features extracted from Mandala pattern topology and obtain new features and pseudo-patterns for the screening and early diagnosis of ASD. The optimal feature here was based on different stages of processing and statistical analysis of Pattern Detection Capability (PDC). The PDC is a biomarker derived from the Mandala pattern for differentiating the NC from ASD groups.

Rutеnbeck. New in the treatment of essential hypertension. (KI. Wschr. V. 15.26 / XII 1936)

1937 ◽  
Vol 33 (9) ◽  
pp. 1142-1143
Keyword(s):  
Essential Hypertension ◽  
New Method ◽  
The Brain

As a new method of treatment of essential hypertension, the author describes craniocerebral electrophoresis, which results in reflex hyperemia of the brain.

scholarly journals Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

2007 ◽  
Vol 2007 ◽  
pp. 1-12 ◽  
Author(s):  
Gerolf Vanacker ◽  
José del R. Millán ◽  
Eileen Lew ◽  
Pierre W. Ferrez ◽  
Ferran Galán Moles ◽  
...  
Keyword(s):  
Control System ◽  
Shared Control ◽  
Eeg Signals ◽  
Intelligent Processing ◽  
Intelligent Wheelchair ◽  
Brain Signals ◽  
Brain Interface ◽  
The Subject ◽  
Electroencephalogram Eeg ◽  
The Brain

Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the nonstationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand, however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a noninvasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair.

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