Results for “Variation (Genetics)/physiology”

NASA NTRS2001

Analysis and visualization of single-trial event-related potentials

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Copyright 2001 Wiley-Liss, Inc.

Non-NASA Center↗

NASA NTRS2001

Elevated breast cancer risk in irradiated BALB/c mice associates with unique functional polymorphism of the Prkdc (DNA-dependent protein kinase catalytic subunit) gene

Female BALB/c mice are unusually radiosensitive and more susceptible than C57BL/6 and other tested inbred mice to ionizing radiation (IR)-induced mammary tumors. This breast cancer susceptibility is correlated with elevated susceptibility for mammary cell transformation and genomic instability following irradiation. In this study, we report the identification of two BALB/c strain-specific polymorphisms in the coding region of Prkdc, the gene encoding the DNA-dependent protein kinase catalytic subunit, which is known to be involved in DNA double-stranded break repair and post-IR signal transduction. First, we identified an A --> G transition at base 11530 resulting in a Met --> Val conversion at codon 3844 (M3844V) in the phosphatidylinositol 3-kinase domain upstream of the scid mutation (Y4046X). Second, we identified a C --> T transition at base 6418 resulting in an Arg --> Cys conversion at codon 2140 (R2140C) downstream of the putative leucine zipper domain. This unique PrkdcBALB variant gene is shown to be associated with decreased DNA-dependent protein kinase catalytic subunit activity and with increased susceptibility to IR-induced genomic instability in primary mammary epithelial cells. The data provide the first evidence that naturally arising allelic variation in a mouse DNA damage response gene may associate with IR response and breast cancer risk.

Non-NASA Center↗