Electroencephalographic Activity in Response to Procedural Pain in Preterm Infants Born at 28 and 33 Weeks Gestational Age

OBJECTIVES:: Preterm infants undergo frequent painful procedures in the neonatal intensive care unit. Electroencephalography (EEG) changes in reaction to invasive procedures have been reported in preterm and full-term neonates. Frontal EEG asymmetry as an index of emotion during tactile stimulation shows inconsistent findings in full-term infants, and has not been examined in the context of pain in preterm infants. Our aim was to examine whether heel lance for blood collection induces changes in right-left frontal asymmetry, suggesting negative emotional response, in preterm neonates at different gestational age (GA) at birth and different duration of stay in the neonatal intensive care unit. MATERIALS AND METHODS:: Three groups of preterm infants were compared: set 1: group 1 (n=24), born and tested at 28 weeks GA; group 2 (n=22), born at 28 weeks GA and tested at 33 weeks; set 2: group 3 (n=25), born and tested at 33 weeks GA. EEG power was calculated for 30-second artifact-free periods, in standard frequency bandwidths, in 3 phases (baseline, up to 5 min after heel lance, 10 min after heel lance). RESULTS:: No significant differences were found in right-left frontal asymmetry, or in ipsilateral or contralateral somatosensory response, across phases. In contrast, the Behavioral Indicators of Infant Pain scores changed across phase (P

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.

Attention-based modulation of tactile stimuli: A comparison between prefrontal lesion patients and healthy age-matched controls

Objectives: To investigate the role of the prefrontal cortex in attention-based modulation of cortical somatosensory processing.

Methods: Six prefrontal stroke patients were compared with eleven neurologically intact older adults during a vibrotactile discrimination task. All subjects attended to stimuli on one digit while ignoring distracter stimuli on a separate digit of the same hand. Subjects were required to report infrequent targets on the attended digit only. Throughout testing electroencephalography was used to measure event-related potentials for both task-relevant and irrelevant stimuli.

Results: Prefrontal patients demonstrated significant changes in cortical somatosensory processing based on attention compared to age-matched controls. This was evident both in early unimodal somatosensory processing (i.e. P100) and in later cortical processing stages (i.e. long-latency positivity). Moreover, there was a tendency towards a tonic loss of inhibition over early somatosensory cortical processing (i.e. P50).

Conclusions: The attention-based modulation noted for neurologically intact older adults was absent in prefrontal lesion patients.

Significance: The present study highlights the important role of prefrontal regions in sustaining inhibition over early sensory cortical processing stages and in modifying somatosensory transmission based on task-relevance. Notably these deficits extend beyond those previously shown to occur as a function of age.

Using Brain Data for Sentiment Analysis

We present the results of exploratory experiments using lexical valence extracted from brain using electroencephalography (EEG) for sentiment analysis. We selected 78 English words (36 for training and 42 for testing), presented as stimuli to 3 English native speakers. EEG signals were recorded from the subjects while they performed a mental imaging task for each word stimulus. Wavelet decomposition was employed to extract EEG features from the time-frequency domain. The extracted features were used as inputs to a sparse multinomial logistic regression (SMLR) classifier for valence classification, after univariate ANOVA feature selection. After mapping EEG signals to sentiment valences, we exploited the lexical polarity extracted from brain data for the prediction of the valence of 12 sentences taken from the SemEval-2007 shared task, and compared it against existing lexical resources.

Perceptual learning of acoustic noise generates memory-evoked potentials

Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.