TY - JOUR
T1 - Revealing drug effects utilizing brain network activation (BNA)
T2 - A working memory study
AU - Shani-Hershkovitch, R
AU - Reches, A
AU - Pinchuk, N
AU - Ben Bashat, G
AU - Levy-Cooperman, N
AU - Milovan, D
AU - Romach, MK
AU - Sellers, EM
AU - Geva, AB
PY - 2011/11
Y1 - 2011/11
N2 - Finding tools to evaluate drug effects on brain processes is a true necessity in drug development targeting neurodegenerative and psychiatric disorders. Drug testing may be done on healthy volunteers treated with substances associated with reversible cognitive effects such as scopolamine, an acetylcholine antagonist, and ketamine, a NMDA antagonist. Both drugs have previously been used as models of Alzheimer and schizophrenia respectively, and showed electrophysiological abnormalities associated with these disorders. We have recently developed a novel algorithm to extract brain network activation (BNA) patterns that reveal in an unsupervised manner spatio-temporal networks from EEG data. In this study BNA analysis was used in order to assess changes in brain networks in 15 healthy volunteers following administration of scopolamine (0.4 mg) and ketamine (100 mg) in a double-blinded, placebo-controlled, crossover study. Subjects (18-45 y) performed a working memory task in which they determined whether two consecutive face stimuli were identical, while EEG was recorded from 64 channels. The networks showing the activation differences between placebo and scopolamine revealed a delay in posterior face processing activity and a fronto-central, widely distributed activity around 250 ms following scopolamine administration. The later activity was restricted to pre-frontal areas under placebo. The placebo-ketamine differentiating networks showed that the frontal negativity at 250 ms peaked earlier, and was lateralized to the right under placebo, while ketamine administration disrupted this hemispheric asymmetry - a known phenomenon in schizophrenia. To conclude, this study shows that BNA analysis can automatically detect significant changes in brain states between different conditions, validating its use for investigating effects of pharmacological treatments on CNS diseases.
AB - Finding tools to evaluate drug effects on brain processes is a true necessity in drug development targeting neurodegenerative and psychiatric disorders. Drug testing may be done on healthy volunteers treated with substances associated with reversible cognitive effects such as scopolamine, an acetylcholine antagonist, and ketamine, a NMDA antagonist. Both drugs have previously been used as models of Alzheimer and schizophrenia respectively, and showed electrophysiological abnormalities associated with these disorders. We have recently developed a novel algorithm to extract brain network activation (BNA) patterns that reveal in an unsupervised manner spatio-temporal networks from EEG data. In this study BNA analysis was used in order to assess changes in brain networks in 15 healthy volunteers following administration of scopolamine (0.4 mg) and ketamine (100 mg) in a double-blinded, placebo-controlled, crossover study. Subjects (18-45 y) performed a working memory task in which they determined whether two consecutive face stimuli were identical, while EEG was recorded from 64 channels. The networks showing the activation differences between placebo and scopolamine revealed a delay in posterior face processing activity and a fronto-central, widely distributed activity around 250 ms following scopolamine administration. The later activity was restricted to pre-frontal areas under placebo. The placebo-ketamine differentiating networks showed that the frontal negativity at 250 ms peaked earlier, and was lateralized to the right under placebo, while ketamine administration disrupted this hemispheric asymmetry - a known phenomenon in schizophrenia. To conclude, this study shows that BNA analysis can automatically detect significant changes in brain states between different conditions, validating its use for investigating effects of pharmacological treatments on CNS diseases.
U2 - 10.1007/s12031-011-9491-9
DO - 10.1007/s12031-011-9491-9
M3 - Meeting Abstract
SN - 0895-8696
VL - 45
SP - S107-S107
JO - Journal of Molecular Neuroscience
JF - Journal of Molecular Neuroscience
IS - Supplement 1
ER -