On the Evaluation of Information Flow in Multivariate Systems by the Directed Transfer Function

Background: A proper explanation for perceptual symptoms in neurodegenerative disorders including Alzheimer’s disease and Parkinson’s disease (PD) is still lacking. Objective: This study aimed at investigating the imbalance between ‘bottom-up’ and ‘top-down’ information flow (IF) and processing in PD in relation with visual hallucination symptoms. Methods: Here, we looked at bottom-up and top-down IF markers using resting state electroencephalographic (EEG) data from PD patients analyzed through three different IF measures (direct Directed Transfer Function (dDTF), full frequency Directed Transfer Function (ff-DTF), and renormalized Partial Directed Coherence (rPDC). Results: We observed an increased gamma band IF and a reduced beta band IF in PD patients compared to healthy controls. Additionally, we noticed a reduced theta band IF in PD patients using dDTF as a measure of IF. By source localizing the EEG activity of the PD patients and healthy controls, we looked at the alterations of IF in the prefrontal cortex of PD patients as well. Conclusion: In line with previous studies, our results suggest that the delicate balance between bottom-up and top-down IF is disrupted in Parkinson’s disease potentially contributing to the cognitive symptoms of PD patients.

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Multiresolution directed transfer function approach for segment-wise seizure classification of epileptic EEG signal

Cognitive Neurodynamics ◽

10.1007/s11571-021-09773-z ◽

2022 ◽

Author(s):

Dhanalekshmi P. Yedurkar ◽

Shilpa P. Metkar ◽

Thompson Stephan

Keyword(s):

Transfer Function ◽

Function Approach ◽

Eeg Signal ◽

Directed Transfer Function ◽

Seizure Classification

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Limitations of Employing Undirected Information Flow Graphs for the Maintenance of Rigid Vehicular Formations

ASME 2009 Dynamic Systems and Control Conference, Volume 2 ◽

10.1115/dscc2009-2767 ◽

2009 ◽

Cited By ~ 1

Author(s):

Swaroop Darbha ◽

Prabhakar R. Pagilla

Keyword(s):

Transfer Function ◽

Information Flow ◽

Control Input ◽

Safe Distance ◽

Mass Model ◽

Disturbance Propagation ◽

Rational Transfer ◽

Reference Vehicle ◽

Vehicle Information ◽

Flow Graphs

In this paper, we consider the problem of decentralized control of a collection of homogeneous vehicles trying to maintain a rigid formation. Each vehicle attempts to maintain a specified constant safe distance from its adjacent vehicles in the collection. We consider an identical structure for each decentralized controller so that it is simpler from an implementation viewpoint as it does not depend on collection size or vehicle indices. We call a vehicle B adjacent to vehicle A if the relative position of vehicle B is known to vehicle A either by communication or by sensing. In this paper, we only consider undirected information flow graphs, i.e., graphs where vehicle A is adjacent to vehicle B if and only if vehicle B is adjacent to vehicle A. We consider a point mass model for each vehicle and assume the actuation transfer function, which relates the control input to the force supplied to the vehicle, to be a strictly proper rational transfer function. It is known that spacing errors due to disturbances amplify if the reference vehicle information is not available to Ω(n) vehicles, n being the size of the collection [1]. In this paper, we generalize this result to show the following: If there are two or more vehicles in the collection that are adjacent to Ω(n) vehicles, then there is a critical size N* so that the motion of the collection will be unstable if the size of the collection exceeds N*. Practical issues of fault tolerance indicate that there be at least two vehicles that are adjacent to Ω(n) vehicles in the collection. We also further show that the use of a kinematic vehicle model for analysis of disturbance propagation yields results which may not agree with what is observed in practice and hence are inappropriate.

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Direction of Information Flow in Alzheimer's Disease and MCI Patients

International Journal of Alzheimer s Disease ◽

10.4061/2011/214580 ◽

2011 ◽

Vol 2011 ◽

pp. 1-7 ◽

Cited By ~ 8

Author(s):

Fabrizio Vecchio ◽

Claudio Babiloni

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Information Flow ◽

Additive Model ◽

Functional Coupling ◽

Directed Transfer Function ◽

Directional Flow ◽

Eeg Data ◽

Rest Condition ◽

Amnesic Mild Cognitive Impairment

Is directionality of electroencephalographic (EEG) synchronization abnormal in amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD)? And, do cerebrovascular and AD lesions represent additive factors in the development of MCI as a putative preclinical stage of AD? Here we reported two studies that tested these hypotheses. EEG data were recorded in normal elderly (Nold), amnesic MCI, and mild AD subjects at rest condition (closed eyes). Direction of information flow within EEG electrode pairs was performed by directed transfer function (DTF) atδ(2–4 Hz),θ(4–8 Hz),α1 (8–10 Hz),α2 (10–12 Hz),β1 (13–20 Hz),β2 (20–30 Hz), andγ(30–40 Hz). Parieto-to-frontal direction was stronger in Nold than in MCI and/or AD subjects forαandβrhythms. In contrast, the directional flow within interhemispheric EEG functional coupling did not discriminate among the groups. More interestingly, this coupling was higher atθ,α1,α2, andβ1 in MCI with higher than in MCI with lower vascular load. These results suggest that directionality of parieto-to-frontal EEG synchronization is abnormal not only in AD but also in amnesic MCI, supporting the additive model according to which MCI state would result from the combination of cerebrovascular and neurodegenerative lesions.

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