Going Beyond Rote Auditory Learning: Neural Patterns of Generalized Auditory Learning.

The ability to generalize across specific experiences is vital for the recognition of new patterns, especially in speech perception considering acoustic-phonetic pattern variability. Indeed, behavioral research has demonstrated that listeners are able via a process of generalized learning to leverage their experiences of past words said by difficult-to-understand talker to improve their understanding for new words said by that talker. Here, we examine differences in neural responses to generalized versus rote learning in auditory cortical processing by training listeners to understand a novel synthetic talker. Using a pretest-posttest design with EEG, participants were trained using either (1) a large inventory of words where no words were repeated across the experiment (generalized learning) or (2) a small inventory of words where words were repeated (rote learning). Analysis of long-latency auditory evoked potentials at pretest and posttest revealed that rote and generalized learning both produced rapid changes in auditory processing, yet the nature of these changes differed. Generalized learning was marked by an amplitude reduction in the N1-P2 complex and by the presence of a late negativity wave in the auditory evoked potential following training; rote learning was marked only by temporally later scalp topography differences. The early N1-P2 change, found only for generalized learning, is consistent with an active processing account of speech perception, which proposes that the ability to rapidly adjust to the specific vocal characteristics of a new talker (for which rote learning is rare) relies on attentional mechanisms to selectively modify early auditory processing sensitivity.

Single-trial visually evoked potentials predict both individual choice and market outcomes.

A central assumption in the behavioral sciences is that choice behavior generalizes enough across individuals that measurements from a sampled group can predict the behavior of the population. Following from this assumption, the unit of behavioral sampling or measurement for most neuroimaging studies is the individual; however, cognitive neuroscience is increasingly acknowledging a dissociation between neural activity that predicts individual behavior and that which predicts the average or aggregate behavior of the population suggesting a greater importance of individual differences than is typically acknowledged. For instance, past work has demonstrated that some, but not all, of the neural activity observed during value-based decision-making is able to predict not just individual subjects' choices but also the success of products on large, online marketplaces-even when those two behavioral outcomes deviate from one another-suggesting that some neural component processes of decision-making generalize to aggregate market responses more readily across individuals than others do. While the bulk of such research has highlighted affect-related neural responses (i.e. in the nucleus accumbens) as a better predictor of group-level behavior than frontal cortical activity associated with the integration of more idiosyncratic choice components, more recent evidence has implicated responses in visual cortical regions as strong predictors of group preference. Taken together, these findings suggest a role of neural responses during early perception in reinforcing choice consistency across individuals and raise fundamental scientific questions about the role sensory systems in value-based decision-making processes. We use a multivariate pattern analysis approach to show that single-trial visually evoked electroencephalographic (EEG) activity can predict individual choice throughout the post-stimulus epoch; however, a nominally sparser set of activity predicts the aggregate behavior of the population. These findings support an account in which a subset of the neural activity underlying individual choice processes can scale to predict behavioral consistency across people, even when the choice behavior of the sample does not match the aggregate behavior of the population.

Individual differences in human frequency-following response predict pitch labeling ability.

The frequency-following response (FFR) provides a measure of phase-locked auditory encoding in humans and has been used to study subcortical processing in the auditory system. While effects of experience on the FFR have been reported, few studies have examined whether individual differences in early sensory encoding have measurable effects on human performance. Absolute pitch (AP), the rare ability to label musical notes without reference notes, provides an excellent model system for testing how early neural encoding supports specialized auditory skills. Results show that the FFR predicts pitch labelling performance better than traditional measures related to AP (age of music onset, tonal language experience, pitch adjustment and just-noticeable-difference scores). Moreover, the stimulus type used to elicit the FFR (tones or speech) impacts predictive performance in a manner that is consistent with prior research. Additionally, the FFR predicts labelling performance for piano tones better than unfamiliar sine tones. Taken together, the FFR reliably distinguishes individuals based on their explicit pitch labeling abilities, which highlights the complex dynamics between sensory processing and cognition.

Expertise Modulates Neural Stimulus-Tracking.

How does the brain anticipate information in language? When people perceive speech, low-frequency (<10 Hz) activity in the brain synchronizes with bursts of sound and visual motion. This phenomenon, called cortical stimulus-tracking, is thought to be one way that the brain predicts the timing of upcoming words, phrases, and syllables. In this study, we test whether stimulus-tracking depends on domain-general expertise or on language-specific prediction mechanisms. We go on to examine how the effects of expertise differ between frontal and sensory cortex. We recorded electroencephalography (EEG) from human participants who were experts in either sign language or ballet, and we compared stimulus-tracking between groups while participants watched videos of sign language or ballet. We measured stimulus-tracking by computing coherence between EEG recordings and visual motion in the videos. Results showed that stimulus-tracking depends on domain-general expertise, and not on language-specific prediction mechanisms. At frontal channels, fluent signers showed stronger coherence to sign language than to dance, whereas expert dancers showed stronger coherence to dance than to sign language. At occipital channels, however, the two groups of participants did not show different patterns of coherence. These results are difficult to explain by entrainment of endogenous oscillations, because neither sign language nor dance show any periodicity at the frequencies of significant expertise-dependent stimulus-tracking. These results suggest that the brain may rely on domain-general predictive mechanisms to optimize perception of temporally-predictable stimuli such as speech, sign language, and dance.

Chest Compression Duration May Be Improved When Rescuers Breathe Supplemental Oxygen.

BACKGROUND: At sea level, performing chest compressions is a demanding physical exercise. On a commercial flight at cruise altitude, the barometric pressure in the cabin is approximately equal to an altitude of 2438 m. This results in a Po2 equivalent to breathing an FIo2 of 15% at sea level, a condition under which both the duration and quality of cardiopulmonary resuscitation (CPR) may deteriorate. We hypothesized that rescuers will be able to perform fewer rounds of high-quality CPR at an FIo2 of 15%.METHODS: In this crossover simulation trial, 16 healthy volunteers participated in 2 separate sessions and performed up to 14 2-min rounds of chest compressions at an FIo2 of either 0.15 or 0.21 in randomized order. Subjects were stopped if their Spo2 was below 80%, if chest compression rate or depth was not achieved for 2/3 of compressions, or if they felt fatigued or dyspneic.RESULTS: Fewer rounds of chest compressions were successfully completed in the hypoxic than in the normoxic condition, (median [IQR] 4.5 [3,8.5]) vs. 5 [4,14]). The decline in arterial Spo2 while performing chest compressions was greater in the hypoxic condition than in the normoxic condition [mean (SD), 6.19% (4.1) vs. 2% (1.66)].DISCUSSION: Our findings suggest that the ability of rescuers to perform chest compressions in a commercial airline cabin at cruising altitude may be limited due to hypoxia. One possible solution is supplemental oxygen for rescuers who perform chest compressions for in-flight cardiac arrest.Clebone A, Reis K, Tung A, OConnor M, Ruskin KJ. Chest compression duration may be improved when rescuers breathe supplemental oxygen. Aerosp Med Hum Perform. 2020; 91(12):918922.

Cortical mechanisms of talker normalization in fluent sentences.

Adjusting to the vocal characteristics of a new talker is important for speech recognition. Previous research has indicated that adjusting to talker differences is an active cognitive process that depends on attention and working memory (WM). These studies have not examined how talker variability affects perception and neural responses in fluent speech. Here we use source analysis from high-density EEG to show that perceiving fluent speech in which the talker changes recruits early involvement of parietal and temporal cortical areas, suggesting functional involvement of WM and attention in talker normalization. We extend these findings to acoustic source change in general by examining understanding environmental sounds in spoken sentence context. Though there may be differences in cortical recruitment to processing demands for non-speech sounds versus a changing talker, the underlying mechanisms are similar, supporting the view that shared cognitive-general mechanisms assist both talker normalization and speech-to-nonspeech transitions.

NRXN1 is associated with enlargement of the temporal horns of the lateral ventricles in psychosis.

Schizophrenia, Schizoaffective, and Bipolar disorders share behavioral and phenomenological traits, intermediate phenotypes, and some associated genetic loci with pleiotropic effects. Volumetric abnormalities in brain structures are among the intermediate phenotypes consistently reported associated with these disorders. In order to examine the genetic underpinnings of these structural brain modifications, we performed genome-wide association analyses (GWAS) on 60 quantitative structural brain MRI phenotypes in a sample of 777 subjects (483 cases and 294 controls pooled together). Genotyping was performed with the Illumina PsychChip microarray, followed by imputation to the 1000 genomes multiethnic reference panel. Enlargement of the Temporal Horns of Lateral Ventricles (THLV) is associated with an intronic SNP of the gene NRXN1 (rs12467877, P = 6.76E-10), which accounts for 4.5% of the variance in size. Enlarged THLV is associated with psychosis in this sample, and with reduction of the hippocampus and enlargement of the choroid plexus and caudate. Eight other suggestively significant associations (P < 5.5E-8) were identified with THLV and 5 other brain structures. Although rare deletions of NRXN1 have been previously associated with psychosis, this is the first report of a common SNP variant of NRXN1 associated with enlargement of the THLV in psychosis.