scholarly journals Investigating neural primacy in Major Depressive Disorder: multivariate Granger causality analysis of resting-state fMRI time-series data

2010 ◽  
Vol 16 (7) ◽  
pp. 763-772 ◽  
Author(s):  
J P Hamilton ◽  
G Chen ◽  
M E Thomason ◽  
M E Schwartz ◽  
I H Gotlib
Keyword(s):  
Time Series ◽  
Major Depressive Disorder ◽  
Resting State ◽  
Time Series Data ◽  
Resting State Fmri ◽  
Series Data ◽  
Causality Analysis ◽  
Major Depressive ◽  
Granger Causality Analysis ◽  
Fmri Time Series

HUBUNGAN KAUSALITAS HARGA JUAL DAN HARGA SEWA APARTEMEN DI JABODETABEK

2021 ◽  
Vol 1 (1) ◽  
pp. 93-105
Author(s):  
Zainal Zawir Simon ◽  
Effendy Zain ◽  
Zulihar Zulihar
Keyword(s):  
Time Series ◽  
Granger Causality ◽  
Time Series Data ◽  
Investment Analysis ◽  
Series Data ◽  
Analysis Tool ◽  
Selling Price ◽  
Causality Analysis ◽  
Granger Causality Analysis ◽  
Causality Relationship

Abstrak Penelitian ini bertujuan untuk mengetahui hubungan kausalitas antara harga jual apartemen dan harga sewa apartemen di wilayah Jabodetabek. Data yang dipergunakan adalah data  time series dalam bentuk kuartalan untuk periode 2007:1-2018:3 dan alat analisis yang dipergunakan adalah analisa kausalitas Granger. Hasil penelitian menunjukkan bahwa tidak terdapat hubungan kausalitas antara harga jual apartemen dan harga sewa apartemen di wilayah Jabodetabek. Dengan kata lain perubahan harga jual  tidak mempengaruhi harga sewa. Sebaliknya harga sewa juga tidak mempengaruhi harga jual apartemen. Dengan demikian Investor diharapkan dalam melakukan analisis investasinya memasukkan faktor-faktor lain yang dapat mempengaruhi harga jual dan harga sewa untuk apartemen, agar terlepas dari pandangan bahwa harga jual mempengaruhi harga sewa dan sebaliknya.Kata Kunci : Harga Jual apartemen, Harga Sewa Apartemen, Data Runtut Waktu, Analisa Kausalitas GrangerABSTRACTThis study aims to determine the causality relationship between the selling price of apartments and apartment rental prices in the Greater Jakarta area. The data used are time series data in quarterly form for the period 2007: 1-2018: 3 and the analysis tool used is the Granger causality analysis. The results showed that there was no causality relationship between apartment selling prices and apartment rental prices in the Greater Jakarta area. In other words, changes in selling prices do not affect rental prices. Conversely the rental price also does not affect the selling price of the apartment. Thus Investors are expected to carry out investment analysis to include other factors that can affect the selling price and rental price for an apartment, so that regardless of the view that the selling price affects the rental price and vice versa.Keywords : Selling Price of apartments, rental prices apartments, time series data, Granger Causality Analysis

scholarly journals The Ubiquitous Vigilance Signal in fMRI Time Series Data

2021 ◽  
Author(s):  
Javier Gonzalez-Castillo ◽  
Isabel Fernandez ◽  
Daniel A Handwerker ◽  
Peter A Bandettini
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Time Series Data ◽  
Resting State Fmri ◽  
Series Data ◽  
Similar Frequency ◽  
Global Signal ◽  
Human Connectome Project ◽  
Fmri Time Series ◽  
Eye Closure

Vigilance and wakefulness modulate estimates of functional connectivity, and, if unaccounted for, they can become a substantial confound in resting-state fMRI. Unfortunately, wakefulness is rarely monitored due to the need for additional concurrent recordings (e.g., eye tracking, EEG). Recent work has shown that strong fluctuations around 0.05Hz, hypothesized to be CSF inflow, appear in the fourth ventricle (FV) when subjects fall asleep. The analysis of these fluctuations could provide an easy way to evaluate wakefulness in fMRI-only data. Here we evaluate this possibility using the 7T resting-state sample from the Human Connectome Project. Our results confirm the presence of those fluctuations in the HCP sample despite this data having relatively small inflow weighting. Moreover, we show that fluctuations of a similar frequency appear in large portions of grey matter with different temporal delays, and that they can substantially influence estimates of functional connectivity. Finally, we demonstrate that the temporal evolution of this signal cannot only help us reproduce previously reported overall sleep patterns in resting-state data, but also predict individual periods of eye closure with 70% accuracy, matching predictions attainable using the amplitude of the global signal (a common fMRI marker of arousal). In summary, our results demonstrate the ubiquitous presence of this signal in a large, publicly available, fMRI sample, its value as a marker of arousal in absence of a better metric, its relationship to the global signal, and its potential nuisance effects on functional connectivity estimates when ignored.

Examining the Long Run Effects of Export, Import and FDI Inflows on the FDI Outflows from India: A Causality Analysis

2009 ◽  
Vol 10 (1) ◽  
pp. 65-88
Author(s):  
Nandita Dasgupta
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Driving Force ◽  
Time Series Data ◽  
Series Data ◽  
Causality Analysis ◽  
Fdi Inflows ◽  
Long Run ◽  
Time Series Data Analysis ◽  
Trade And Investment

The objective of this paper is to examine the effects of international trade and investment related macro economic variables, namely, exports, imports and FDI inflows on the outflows of FDI from India over 1970 through 2005. Using time series data analysis, the empirical part of the paper finds unidirectional Granger Causality from export and import to FDI outflows but no such causality exists from FDI inflows to the corresponding outflows from India. Results confirm the assumption that lagged imports and exports are a driving force of ing front.

Altered brain function and clinical features in patients with first-episode, drug naïve major depressive disorder: A resting-state fMRI study

2020 ◽  
Vol 303 ◽  
pp. 111134
Author(s):  
Sixiang Liang ◽  
Kaizhong Xue ◽  
Wenchen Wang ◽  
Wenwen Yu ◽  
Xiaojuan Ma ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Clinical Features ◽  
Resting State ◽  
Brain Function ◽  
Resting State Fmri ◽  
First Episode ◽  
Major Depressive ◽  
Fmri Study ◽  
Drug Naïve

Dimensionality reduction of fMRI time series data using locally linear embedding

2010 ◽  
Vol 23 (5-6) ◽  
pp. 327-338 ◽  
Author(s):  
Peter Mannfolk ◽  
Ronnie Wirestam ◽  
Markus Nilsson ◽  
Freddy Ståhlberg ◽  
Johan Olsrud
Keyword(s):  
Time Series ◽  
Dimensionality Reduction ◽  
Time Series Data ◽  
Series Data ◽  
Locally Linear Embedding ◽  
Fmri Time Series ◽  
Linear Embedding ◽  
Locally Linear

scholarly journals A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

NeuroImage ◽  
2014 ◽  
Vol 95 ◽  
pp. 287-304 ◽  
Author(s):  
Ameera X. Patel ◽  
Prantik Kundu ◽  
Mikail Rubinov ◽  
P. Simon Jones ◽  
Petra E. Vértes ◽  
...  
Keyword(s):  
Time Series ◽  
Resting State ◽  
Resting State Fmri ◽  
Motion Artifacts ◽  
Wavelet Method ◽  
Fmri Time Series

scholarly journals Reduced Default Mode Network Functional Connectivity in Patients with Recurrent Major Depressive Disorder

2018 ◽  
Author(s):  
Chao-Gan Yan ◽  
Xiao Chen ◽  
Le Li ◽  
Francisco Xavier Castellanos ◽  
Tong-Jian Bai ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Research Groups ◽  
Major Depressive ◽  
Default Mode ◽  
Normal Controls

ABSTRACTMajor Depressive Disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol prior to aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. Finally, all resting-state fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.SIGNIFICANCE STATEMENTFunctional connectivity within the default mode network in major depressive disorder patients has been frequently reported abnormal but with contradicting directions in previous small sample size studies. In creating the REST-meta-MDD consortium containing neuroimaging data of 1,300 depressed patients and 1,128 normal controls from 25 research groups in China, we found decreased default mode network functional connectivity in depressed patients, driven by patients with recurrent depression, and associated with current medication treatment but not with disease duration. These findings suggest that default mode network functional connectivity remains a prime target for understanding the pathophysiology of depression, with particular relevance to revealing mechanisms of effective treatments.

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