Biology subjects

Woestmann, M.

Publications and source records attributed to Woestmann, M..

6 recordsLinked to original sources

bioRxiv2018

Prestimulus neural alpha power predicts confidence in discriminating identical tones

There is growing evidence that the power of prestimulus neural alpha oscillations ([~]10 Hz) holds information on a perceivers bias or confidence in an ensuing perceptual decision, rather than perceptual sensitivity per se. Obviously, however, confidence also depends on the physical evidence available in the stimulus as well as on task performance. If prestimulus alpha power has a direct impact on decision confidence, this link should hold independent of variations in stimulus evidence and performance. We tested this assertion in a paradigm where human listeners (n = 17) rated their confidence in the discrimination of the pitch of two identical tones. Lower prestimulus alpha power in the electroencephalogram (EEG) was predictive of higher confidence ratings, but not of the decision outcome (i.e., judging the first or the second tone as being higher in pitch). Importantly, the link between prestimulus alpha power and decision confidence was not mediated by auditory evoked activity. Our findings demonstrate that the link between prestimulus alpha power and decision confidence does not hinge on physical evidence in the stimulus or task performance. Instead, these results speak to a model wherein low prestimulus alpha power increases neural baseline excitability, which is reflected in enhanced stimulus-evoked neural responses and higher confidence.\n\nSignificance statementIn order to understand the mechanistic relevance of neural oscillations for perception, we here relate these directly to changes in human auditory decision confidence. Human subjects rated their confidence in the discrimination of the pitch of two tones, which were, unbeknownst to the listener, physically identical. In the absence of changing evidence in the physical stimulus or changes in task performance, we demonstrate that prestimulus alpha power negatively relates to decision confidence. Our results support a model of cortical alpha oscillations as a proxy for neural baseline excitability in which lower prestimulus alpha power does not lead to more precise but rather to overall amplified neural representations.

neuroscience↗

bioRxiv2018

Probing the limits of alpha power lateralization as a neural marker of selective attention in middle-aged and older listeners

In recent years, hemispheric lateralization of alpha power has emerged as a neural mechanism thought to underpin spatial attention across sensory modalities. Yet, how healthy aging, beginning in middle adulthood, impacts the modulation of lateralized alpha power supporting auditory attention remains poorly understood. In the current electroencephalography (EEG) study, middle-aged and older adults (N = 29; ~40-70 years) performed a dichotic listening task that simulates a challenging, multi-talker scenario. We examined the extent to which the modulation of 8-12 Hz alpha power would serve as neural marker of listening success across age. With respect to the increase in inter-individual variability with age, we examined an extensive battery of behavioral, perceptual, and neural measures. Similar to findings on younger adults, middle-aged and older listeners' auditory spatial attention induced robust lateralization of alpha power, which synchronized with the speech rate. Notably, the observed relationship between this alpha lateralization and task performance did not co-vary with age. Instead, task performance was strongly related to an individuals attentional and working memory capacity. Multivariate analyses revealed a separation of neural and behavioral variables independent of age. Our results suggest that in age-varying samples as the present one, the lateralization of alpha power is neither a sufficient nor necessary neural strategy for an individuals auditory spatial attention, as higher age might come with increased use of alternative, compensatory mechanisms. Our findings emphasize that explaining inter-individual variability will be key to understanding the role of alpha oscillations in auditory attention in the aging listener.

neuroscience↗

bioRxiv2017

Unfolding of a noise-invariant neural representation of attended speech

Listening requires selective neural processing of the incoming sound mixture, which in humans is borne out by a surprisingly clean representation of attended-only speech in auditory cortex. How this neural selectivity is achieved even at negative signal-to-noise ratios (SNR) remains unclear. We show that, under such conditions, a late cortical representation (i.e., neural tracking) of the ignored acoustic signal is key to successful separation of attended and distracting talkers (i.e., neural selectivity). We recorded and modelled the electroencephalographic response of 18 participants who attended to one of two simultaneously presented stories, while the SNR between the two talkers varied dynamically. The neural tracking showed an increasing early-to-late attention-biased selectivity. Importantly, acoustically dominant ignored talkers were tracked neurally by late involvement of fronto-parietal regions, which contributed to enhanced neural selectivity. This neural selectivity by way of representing the ignored talker poses a mechanistic neural account of attention under real-life acoustic conditions.

neuroscience↗

bioRxiv2017

Neural noise in the age-varying human brain predicts perceptual decisions

Sensory representations of the physical world and thus human percepts are susceptible to fluctuations in brain state or \"neural irregularity\". Furthermore, aging brains display altered levels of irregularity. We here show that a single, within-trial information-theoretic measure (weighted permutation entropy) captures neural irregularity in the human electroencephalogram as a proxy for both, trait-like differences between individuals of varying age, and state-like fluctuations that bias perceptual decisions. First, the overall level of neural irregularity increased with participants age, paralleled by a decrease in variability over time, likely indexing age-related disintegration on structural and functional levels of brain activity. Second, states of higher neural irregularity were associated with optimized sensory encoding and a subsequently increased probability of choosing the first of two physically identical stimuli. In sum, neural irregularity not only characterizes behaviorally relevant brain states, but also can identify trait-like changes that come with age.

neuroscience↗

bioRxiv2016

Large-scale network dynamics of beta-band oscillations underlie auditory perceptual decision making

Perceptual decisions vary in the speed at which we make them. Evidence suggests that translating sensory information into behavioral decisions relies on distributed interacting neural populations, with decision speed hinging on power modulations of neural oscillations. Yet, the dependence of perceptual decisions on the large-scale network organization of coupled neural oscillations has remained elusive. We measured magnetoencephalography signals in human listeners who judged acoustic stimuli made of carefully titrated clouds of tone sweeps. These stimuli were used under two task contexts where the participants judged the overall pitch or direction of the tone sweeps. We traced the large-scale network dynamics of source-projected neural oscillations on a trial-by-trial basis using power envelope correlations and graph-theoretical network discovery. Under both tasks, faster decisions were predicted by higher segregation and lower integration of coupled beta-band (~16-28 Hz) oscillations. We also uncovered brain network states that promoted faster decisions and emerged from lower-order auditory and higher-order control brain areas. Specifically, decision speed in judging tone-sweep direction critically relied on nodal network configurations of anterior temporal, cingulate and middle frontal cortices. Our findings suggest that global network communication during perceptual decision-making is implemented in the human brain by large-scale couplings between beta-band neural oscillations.\n\nAuthor SummaryThe speed at which we make perceptual decisions varies. This translation of sensory information into behavioral decisions hinges on dynamic changes in neural oscillatory activity. However, the large-scale neural network embodiment supporting perceptual decision-making is unclear. Alavash et al. address this question by experimenting two auditory perceptual decision-making situations. Using graph-theoretical network discovery, they trace the large-scale network dynamics of coupled neural oscillations to uncover brain network states supporting the speed of auditory perceptual decisions. They find that higher network segregation of coupled beta-band oscillations supports faster auditory perceptual decisions over trials. Moreover, when auditory perceptual decisions are relatively difficult, the decision speed benefits from higher segregation of frontal cortical areas, but lower segregation and integration of auditory cortical areas.

neuroscience↗

bioRxiv2016

Single-channel in-Ear-EEG predicts the focus of auditory attention to concurrent tone streams and mixed speech

Conventional, multi-channel scalp electroencephalography (EEG) allows the identification of the attended speaker in concurrent-listening (\"cocktail party\") scenarios. This implies that EEG might provide valuable information to complement hearing aids with some form of EEG and to install a level of neuro-feedback. To investigate whether a listeners attentional focus can be predicted from single-channel hearing-aid-compatible EEG configurations, we recorded EEG from three electrodes inside the ear canal (\"in-Ear-EEG\") and additionally from 64 electrodes on the scalp. In two different, concurrent listening tasks, participants (n = 7) were fitted with individualized in-Ear-EEG pieces and were either asked to attend to one of two dichotically-presented, concurrent tone streams or to one of two diotically-presented, concurrent audiobooks. A forward encoding model was trained to predict the EEG response at single EEG channels. We found that all individual participants attentional focus could be predicted from single-channel EEG response recorded from short-distance configurations consisting only of a single in-Ear-EEG electrode and an adjacent scalp-EEG electrode. The responses to attended and ignored stimuli reveal differences consistent across subjects. In sum, our findings show that the EEG response from a single-channel, hearing-aid-compatible configuration provides valuable information to identify a listeners focus of attention.

bioengineering↗