Age trends in auditory oddball evoked potentials via component scoring and deconvolution

• Published in: Clinical neurophysiology 2010-06, Vol.121 (6), p.962-976
• Main Authors: Kerr, Cliff C, van Albada, Sacha J, Rennie, Christopher J, Robinson, Peter A
• Format: Article
• Language: English
• Subjects: Acoustic Stimulation; Adolescent; Adult; Age Factors; Aged; Aged, 80 and over; Aging; Aging - physiology; Auditory oddball; Auditory Pathways - physiology; Biological and medical sciences; Brain Mapping; Cerebral Cortex - physiology; Child; Component scoring; Deconvolution; Development; Electrodiagnosis. Electric activity recording; Electroencephalography; Evoked potential; Evoked Potentials, Auditory - physiology; Female; Fundamental and applied biological sciences. Psychology; Humans; Investigative techniques, diagnostic techniques (general aspects); Male; Medical sciences; Middle Aged; Models, Neurological; Nervous system; Neurology; Reaction Time - physiology; Reference Values; Somesthesis and somesthetic pathways (proprioception, exteroception, nociception); interoception; electrolocation. Sensory receptors; Vertebrates: nervous system and sense organs
• ISSN: 1388-2457; 1872-8952
• DOI: 10.1016/j.clinph.2009.11.077

Objective This study examines developmental and aging trends in auditory evoked potentials (AEPs) by applying two analysis methods to a large database of healthy subjects. Methods AEPs and reaction times were recorded from 1498 healthy subjects aged 6–86 years using an auditory oddball paradigm. AEPs were analyzed using a recently published deconvolution method and conventional component scoring. Age trends in the resultant data were determined using smooth median-based fits. Results Component latencies generally decreased during development and increased during aging. Deconvolution showed the emergence of a new feature during development, corresponding to improved differentiation between standard and target tones. The latency of this feature provides similar information as the target component latencies, while its amplitude provides a marker of cognitive development. Conclusions Age trends in component scores can be related to physiological changes in the brain. However, component scores show a high degree of redundancy, which limits their information content, and are often invalid when applied to young children. Deconvolution provides additional information on development not available through other methods. Significance This is the largest study of AEP age trends to date. It provides comprehensive statistics on conventional component scores and shows that deconvolution is a simple and informative alternative.