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The extent to which age-related differences in neural markers of visual processing are influenced by changes in visual acuity has not been systematically investigated. Studies often indicate that their subjects had normal or corrected-to-normal vision, but the assessment of visual acuity seems to most frequently be based only on self-report. Consistent with prior research, to be included in the current study, subjects had to report normal or corrected-to-normal vision. Additionally, visual acuity was formally tested using a Snellen eye chart. Event-related potentials (ERPs) were studied in young adults (18-32years old), young-old adults (65-79years old), and old-old adults (80+ years old) while they performed a visual processing task involving selective attention to color. Age-related differences in the latency and amplitude of ERP markers of early visual processing, the posterior P1 and N1 components, were examined. All results were then re-analyzed after controlling for visual acuity. We found that visual acuity declined as a function of age. Accounting for visual acuity had an impact on whether older and younger adults differed significantly in the size and latency of the posterior P1 and N1 components. After controlling for visual acuity, age-related increases in P1 and N1 latency did not remain significant, and older adults were found to have a larger P1 amplitude than young adults. Our results suggest that until the relationship between age-associated differences in visual acuity and early ERPs is clearly established, investigators should be cautious when interpreting the meaning of their findings. Self-reports about visual acuity may be inaccurate, necessitating formal measures. Additional investigation is needed to help establish guidelines for future research, especially of very old adults.
Pubmed ID: 23153966
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Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling
View all literature mentionsA set of open source, freely available Matlab routines for analyzing Event Related Potential (ERP) data. It is tightly integrated with the EEGLAB Toolbox. ERPLAB routines can be accessed from the Matlab command window and from Matlab scripts in addition to being accessed from the EEGLAB GUI. Consequently, ERPLAB provides the ease of learning of a GUI-based system but also provides the power and flexibility of a scripted system.The development of ERPLAB Toolbox is being coordinated by Steve Luck and Javier Lopez-Calderon at the UC-Davis Center for Mind & Brain, with financial support from NIMH.
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