TY - GEN
T1 - A new computational tool for the post session analysis of the prepulse inhibition test in neural science
AU - Zhou, Hongbo
AU - Yang, Hong Ju
AU - Xu, Haiyun
AU - Cheng, Qiang
PY - 2009
Y1 - 2009
N2 - Prepulse inhibition (PPI) refers to the reduction in startle reaction towards a startle-eliciting "pulse" stimulus when it is shortly preceded by a sub-threshold "prepulse" stimulus. PPI deficits have been seen in various neuropsychiatric disorders, such as schizophrenia, Tourette's syndrome, and Huntington's disease. Recent animal studies have employed PPI test to address issues relevant to mental disorders. Measuring the acoustic startle reflex and calculating PPI in small animals produces myriads of numeral data. These raw data need to be justified and organized properly before being analyzed statistically. Therefore, organizing and analyzing these raw data without a computer software is time consuming and tedious. The software we created is useful and powerful in the post session data analysis of PPI test as it has the following three advantages: (1) grouping data under different chambers and trials; (2) eliminating questionable data; (3) batch processing data, which enable researchers to finish the post session data analysis for a number of PPI tests in a few seconds.
AB - Prepulse inhibition (PPI) refers to the reduction in startle reaction towards a startle-eliciting "pulse" stimulus when it is shortly preceded by a sub-threshold "prepulse" stimulus. PPI deficits have been seen in various neuropsychiatric disorders, such as schizophrenia, Tourette's syndrome, and Huntington's disease. Recent animal studies have employed PPI test to address issues relevant to mental disorders. Measuring the acoustic startle reflex and calculating PPI in small animals produces myriads of numeral data. These raw data need to be justified and organized properly before being analyzed statistically. Therefore, organizing and analyzing these raw data without a computer software is time consuming and tedious. The software we created is useful and powerful in the post session data analysis of PPI test as it has the following three advantages: (1) grouping data under different chambers and trials; (2) eliminating questionable data; (3) batch processing data, which enable researchers to finish the post session data analysis for a number of PPI tests in a few seconds.
UR - http://www.scopus.com/inward/record.url?scp=70749094794&partnerID=8YFLogxK
U2 - 10.1109/CSE.2009.61
DO - 10.1109/CSE.2009.61
M3 - Conference contribution
AN - SCOPUS:70749094794
SN - 9780769538235
T3 - Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009
SP - 1077
EP - 1080
BT - Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 - 7th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2009
T2 - 7th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2009
Y2 - 29 August 2009 through 31 August 2009
ER -