scholarly journals A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information Flow

2016 ◽  
Vol 63 (12) ◽  
pp. 2525-2539 ◽  
Author(s):  
Robyn L. Miller ◽  
Victor Manuel Vergara ◽  
David B. Keator ◽  
Vince D. Calhoun
2015 ◽  
Vol 13 (4) ◽  
pp. 501-509 ◽  
Author(s):  
Edward H. Herskovits ◽  
L. Elliot Hong ◽  
Peter Kochunov ◽  
Hemalatha Sampath ◽  
Rong Chen

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gert Pfurtscheller ◽  
Katarzyna J. Blinowska ◽  
Maciej Kaminski ◽  
Andreas R. Schwerdtfeger ◽  
Beate Rassler ◽  
...  

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.


2019 ◽  
Vol 116 (15) ◽  
pp. 7513-7522 ◽  
Author(s):  
Adrià Tauste Campo ◽  
Yuriria Vázquez ◽  
Manuel Álvarez ◽  
Antonio Zainos ◽  
Román Rossi-Pool ◽  
...  

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.


2021 ◽  
Vol 5 (1) ◽  
pp. 33
Author(s):  
Petr Jizba ◽  
Hynek Lavička ◽  
Zlata Tabachová

In this paper, we discuss the statistical coherence between financial time series in terms of Rényi’s information measure or entropy. In particular, we tackle the issue of the directional information flow between bivariate time series in terms of Rényi’s transfer entropy. The latter represents a measure of information that is transferred only between certain parts of underlying distributions. This fact is particularly relevant in financial time series, where the knowledge of “black swan” events such as spikes or sudden jumps is of key importance. To put some flesh on the bare bones, we illustrate the essential features of Rényi’s information flow on two coupled GARCH(1,1) processes.


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