Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

10.3791/62927 ◽  
2021 ◽  
Author(s):  
Siyuan Zhou ◽  
Yuhang Long ◽  
Chunming Lu
Keyword(s):  
Wavelet Transform ◽  
Information Flow ◽  
Directional Information ◽  
Wavelet Transform Coherence

scholarly journals Application of the continuous wavelet transform in the extraction of directional data on RTM imaging condition wavefields

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Juan Guillermo Paniagua Castrillón ◽  
Olga Lucía Quintero- Montoya
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Low Frequency ◽  
Continuous Wavelet ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Model Quality ◽  
Directional Information ◽  
Imaging Condition ◽  
Time Migration

Low-frequency artifacts in reverse time migration result from unwanted cross-correlation of the source and receiver wavefields at non-reflecting points along ray-paths. These artifacts can hide important details in migrated models and increase poor interpretation risk. Some methods have been proposed to avoid or reduce the number of these artifacts, preserving reflections, and improving model quality, implementing other strategies such as modification of the wave equation, proposing other imaging conditions, and using image filtering techniques. One of these methods uses wavefield decomposition, correlating components of the wavefields that propagate in opposite directions. We propose a method for extracting directional information from the RTM imaging condition wavefields to obtain characteristics allowing for better, more refined imaging. The method works by separating directional information about the wavefields based on the continuous wavelet transform (CWT), and the analysis of the main changes on the frequency content revealed within the scalogram obtained by a Gaussian wavelet family. Through numerical applications, we demonstrate that this method can effectively remove undesired artifacts in migrated images. In addition, we use the Laguerre-Gauss filtering to improve the results obtained with the proposed method.

scholarly journals Processing of fMRI-related anxiety and bi-directional information flow between prefrontal cortex and brain stem

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gert Pfurtscheller ◽  
Katarzyna J. Blinowska ◽  
Maciej Kaminski ◽  
Andreas R. Schwerdtfeger ◽  
Beate Rassler ◽  
...  
Keyword(s):  
Brain Stem ◽  
Information Flow ◽  
Well Being ◽  
Causality Principle ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Directed Transfer Function ◽  
Directional Information ◽  
Central Gyrus ◽  
Young Subjects

AbstractBrain–heart synchronization is fundamental for emotional-well-being and brain–heart desynchronization is characteristic for anxiety disorders including specific phobias. Recording BOLD signals with functional magnetic resonance imaging (fMRI) is an important noninvasive diagnostic tool; however, 1–2% of fMRI examinations have to be aborted due to claustrophobia. In the present study, we investigated the information flow between regions of interest (ROI’s) in the cortex and brain stem by using a frequency band close to 0.1 Hz. Causal coupling between signals important in brain–heart interaction (cardiac intervals, respiration, and BOLD signals) was studied by means of Directed Transfer Function based on the Granger causality principle. Compared were initial resting states with elevated anxiety and final resting states with low or no anxiety in a group of fMRI-naïve young subjects. During initial high anxiety the results showed an increased information flow from the middle frontal gyrus (MFG) to the pre-central gyrus (PCG) and to the brainstem. There also was an increased flow from the brainstem to the PCG. While the top-down flow during increased anxiety was predominant, the weaker ascending flow from brainstem structures may characterize a rhythmic pacemaker-like activity that (at least in part) drives respiration. We assume that these changes in information flow reflect successful anxiety processing.

scholarly journals Feed-forward information and zero-lag synchronization in the sensory thalamocortical circuit are modulated during stimulus perception

2019 ◽  
Vol 116 (15) ◽  
pp. 7513-7522 ◽  
Author(s):  
Adrià Tauste Campo ◽  
Yuriria Vázquez ◽  
Manuel Álvarez ◽  
Antonio Zainos ◽  
Román Rossi-Pool ◽  
...  
Keyword(s):  
Information Flow ◽  
Tactile Stimulus ◽  
Functional Information ◽  
Stimulus Amplitude ◽  
Lag Synchronization ◽  
Directional Information ◽  
Feed Forward ◽  
Somatosensory Thalamus ◽  
Stimulus Perception ◽  
Ventral Posterolateral Nucleus

The direction of functional information flow in the sensory thalamocortical circuit may play a role in stimulus perception, but, surprisingly, this process is poorly understood. We addressed this problem by evaluating a directional information measure between simultaneously recorded neurons from somatosensory thalamus (ventral posterolateral nucleus, VPL) and somatosensory cortex (S1) sharing the same cutaneous receptive field while monkeys judged the presence or absence of a tactile stimulus. During stimulus presence, feed-forward information (VPL → S1) increased as a function of the stimulus amplitude, while pure feed-back information (S1 → VPL) was unaffected. In parallel, zero-lag interaction emerged with increasing stimulus amplitude, reflecting externally driven thalamocortical synchronization during stimulus processing. Furthermore, VPL → S1 information decreased during error trials. Also, VPL → S1 and zero-lag interaction decreased when monkeys were not required to report the stimulus presence. These findings provide evidence that both the direction of information flow and the instant synchronization in the sensory thalamocortical circuit play a role in stimulus perception.

scholarly journals Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence

2013 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Ana Catarino ◽  
Alexandre Andrade ◽  
Owen Churches ◽  
Adam P Wagner ◽  
Simon Baron-Cohen ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Functional Connectivity ◽  
Autism Spectrum ◽  
Autism Spectrum Conditions ◽  
Wavelet Transform Coherence
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