Fully optimized discrimination of physiological responses to auditory stimuli

The use of multivariate measurements to characterize brain activity (electrical, magnetic, optical) is widespread. The most common approaches to reduce the complexity of such observations include principal and independent component analyses (PCA and ICA), which are not well suited for discrimination tasks. We addressed two questions: first, how do the neurophysiological responses to elongated phonemes relate to tone and phoneme responses in normal children, and, second, how discriminable are these responses. We employed fully optimized linear discrimination analysis to maximally separate the multi-electrode responses to tones and phonemes, and classified the response to elongated phonemes. We find that discrimination between tones and phonemes is dependent upon responses from associative regions of the brain apparently distinct from the primary sensory cortices typically emphasized by PCA or ICA, and that the neuronal correlates corresponding to elongated phonemes are highly variable in normal children (about half respond with neural correlates of tones and half as phonemes). Our approach is made feasible by the increase in computational power of ordinary personal computers and has significant advantages for a wide range of neuronal imaging modalities.

Interplay of electroencephalogram phase and auditory-evoked neural activity

Auditory-evoked potentials (AEPs) were triggered in real time as a function of ongoing electroencephalogram (EEG) phase. Phase triggering on-line or retrospective phase-selective averaging introduces phase artifacts such as spurious troughs or peaks, which mask mid-latency and affect the amplitude of late AEPs. We developed a method to control for phase artifacts by phase-selective averaging of trials, recorded without stimulation, and used this to uncover a previously unknown phase dependency of AEPs. Not only are such findings inconsistent with the standard additive evoked potential model, but we identified clear neural correlates at fixed latencies, which are inconsistent with the recently proposed phase-resetting model. Our findings suggest that a new conceptualization is required to account for the interplay between the correlates of neural-evoked activity and modulation of ongoing EEG that together constitute evoked potentials.