Biomarker reconstruction of phytoplankton productivity and community structure changes in the middle Okinawa Trough during the last 15 ka

2008 ◽  
Vol 53 (16) ◽  
pp. 2552-2559 ◽  
Author(s):  
Lei Xing ◽  
MeiXun Zhao ◽  
HaiLong Zhang ◽  
YanGuang Liu ◽  
XueFa Shi
Keyword(s):  
Community Structure ◽  
Okinawa Trough ◽  
Phytoplankton Productivity ◽  
Structure Changes

Biomarker records of phytoplankton productivity and community structure changes in the Japan Sea over the last 166 kyr

2011 ◽  
Vol 30 (19-20) ◽  
pp. 2666-2675 ◽  
Author(s):  
Lei Xing ◽  
Rongping Zhang ◽  
Yanguang Liu ◽  
Xiaochen Zhao ◽  
Sumei Liu ◽  
...  
Keyword(s):  
Community Structure ◽  
Japan Sea ◽  
Phytoplankton Productivity ◽  
Structure Changes ◽  
The Japan Sea

Biomarker records of phytoplankton productivity and community structure changes in the Central Yellow Sea mud area during the Mid-late Holocene

2013 ◽  
Vol 12 (4) ◽  
pp. 639-646 ◽  
Author(s):  
Xiaochen Zhao ◽  
Shuqin Tao ◽  
Rongping Zhang ◽  
Hailong Zhang ◽  
Zuosheng Yang ◽  
...  
Keyword(s):  
Community Structure ◽  
Yellow Sea ◽  
Late Holocene ◽  
Phytoplankton Productivity ◽  
Structure Changes ◽  
Sea Mud ◽  
Mud Area

scholarly journals Effect of antipsychotics on community structure in functional brain networks

2019 ◽  
Vol 7 (6) ◽  
pp. 932-960 ◽  
Author(s):  
Ryan Flanagan ◽  
Lucas Lacasa ◽  
Emma K Towlson ◽  
Sang Hoon Lee ◽  
Mason A Porter
Keyword(s):  
Community Structure ◽  
Network Effects ◽  
Brain Networks ◽  
Relevant Information ◽  
Control Group ◽  
Functional Brain ◽  
Structure Changes ◽  
Structural Abnormalities ◽  
Functional Brain Networks ◽  
Network Properties

AbstractSchizophrenia, a mental disorder that is characterized by abnormal social behaviour and failure to distinguish one’s own thoughts and ideas from reality, has been associated with structural abnormalities in the architecture of functional brain networks. In this article, we (1) investigate whether mesoscale network properties give relevant information to distinguish groups of patients from controls in different scenarios and (2) use this lens to examine network effects of different antipsychotic treatments. Using various methods of network analysis, we examine the effect of two classical therapeutic antipsychotics—Aripiprazole and Sulpiride—on the architecture of functional brain networks of both controls (i.e., a set of people who were deemed to be healthy) and patients (who were diagnosed with schizophrenia). We compare community structures of functional brain networks of different individuals using mesoscopic response functions, which measure how community structure changes across different scales of a network. Our approach does a reasonably good job of distinguishing patients from controls, and the distinction is sharper for patients and controls who have been treated with Aripiprazole. Unexpectedly, we find that this increased separation between patients and controls is associated with a change in the control group, as the functional brain networks of the patient group appear to be predominantly unaffected by this drug. This suggests that Aripiprazole has a significant and measurable effect on community structure in healthy individuals but not in individuals who are diagnosed with schizophrenia, something that conflicts with the naive assumption that the drug alters the mesoscale network properties of the patients (rather than the controls). By contrast, we are less successful at separating the networks of patients from those of controls when the subjects have been given the drug Sulpiride. Taken together, in our results, we observe differences in the effects of the drugs (and a placebo) on community structure in patients and controls and also that this effect differs across groups. From a network-science perspective, we thereby demonstrate that different types of antipsychotic drugs selectively affect mesoscale properties of brain networks, providing support that structures such as communities are meaningful functional units in the brain.

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