This report documents a proof-of-concept (POC) study carried out to assess the feasibility of an experimental procedure to be used in a full-fledged project that aims to improve the understanding of the neurocognitive characteristics of the processes of different domain-specific design for environmental sustainability (DfS) activities performed by designers with different levels of domain knowledge. The neural-imaging technique of electroencephalography (EEG) is used to carry out the data-collection. In brief, the full-fledged project aims to investigate and compare the neural characteristics specific to the processes of designing. The comparison can be between different tasks, for instance, 1) a product DfS task and 2) a product-service system (PSS) DfS task, and between different cohorts of designers, for instance, 1) designers with PSS design knowledge and 2) designers without PSS design knowledge.

Perceiving speech is not only dependent on the quality of speech sounds or the listening environment. Numerous studies in the last 10 years have demonstrated that cognitive factors and predictive mechanisms play a significant role on the perceived clarity of speech. In a series of behavioural and neuroimaging studies, I will present which cognitive factors can influence speech perception for both normal-hearing and hearing-impaired listeners, and how predictive mechanisms at phonological and semantic levels can independently and cumulatively enhance speech perception.

Objectives: The precision of stimulus-driven information is less critical for comprehension when accurate knowledge-based predictions of the upcoming stimulus can be generated. A recent study in listeners without hearing impairment (HI) has shown that form- and meaning-based predictability independently and cumulatively enhance perceived clarity of degraded speech. In the present study, we investigated whether form- and meaning-based predictability enhanced the perceptual clarity of degraded speech for individuals with moderate to severe sensorineural HI, a group for whom such enhancement may be particularly important.

Design: Spoken sentences with high or low semantic coherence were degraded by noise-vocoding and preceded by matching or nonmatching text primes. Matching text primes allowed generation of form-based predictions while semantic coherence allowed generation of meaning-based predictions.

Results: The results showed that both form- and meaning-based predictions make degraded speech seem clearer to individuals with HI. The benefit of form-based predictions was seen across levels of speech quality and was greater for individuals with HI in the present study than for individuals without HI in our previous study. However, for individuals with HI, the benefit of meaning-based predictions was only apparent when the speechwas slightly degraded. When it was more severely degraded, the benefit of meaning-based predictions was only seen when matching text primes preceded the degraded speech. The benefit in terms of perceptual clarity of meaning-based predictions was positively related to verbal fluency but not working memory performance.

Conclusions: Taken together, these results demonstrate that, for individuals with HI, form-based predictability has a robust effect on perceptual clarity that is greater than the effect previously shown for individuals without HI. However, when speech quality is moderately or severely degraded, meaning-based predictability is contingent on form-based predictability. Further, the ability to mobilize the lexicon seems to contribute to the strength of meaning-based predictions. Whereas individuals without HI may be able to devote explicit working memory capacity for storing meaning-based predictions, individuals with HI may already be using all available explicit capacity to process the degraded speech and thus become reliant on explicit skills such as their verbal fluency to generate useful meaning-based predictions.

Several studies have documented the importance of optimal work situation and the general well-being of early-career researchers (ECRs) for enhancing the academic performance of universities. Yet, most studies focused on specific categories of ECRs, or on specific academic disciplines as well as on specific outcomes. With this study, we recognize the need for a broader sample encompassing different categories of ECRs across academic disciplines. In a national survey of Swedish universities, the National Junior Faculty of Sweden (NJF) collected data from ECRs in order to study the influence of work situation and well-being on perceived scientific environment. We observed that work situation and well-being are interdependent and jointly influence each other in shaping the conditions for ideal scientific environment. Importantly, we employ structural equation model (SEM) analysis to account for the endogenous relationship between work situation and personal well-being in predicting perceived scientific environment. Results from SEM indicate that support from the university, work time management, job clarity, contract length and quality of life satisfaction were related to the perceived possibility of conducting the best science. Our research also highlighted individual differences across demographic factors and contract length in the perceived work situation and the possibility of conducting the best science. © 2018 International Association of Universities

Speech perception in noise is dependent on stimulus-driven and knowledge-driven processes. Here we investigate the neural correlates and time course of discrepancies between incoming auditory information (i.e. stimulus-driven processing) and linguistic expectations (knowledge-driven processing) by including 20 normal hearing adults in a MEG study. Participants read 48 rhyming sentence pairs beforehand. In the scanner, they listened to sentences that corresponded exactly to the read sentences except that the last word (presented after 1600 millisecond delay and with 50% intelligibility) was only correct in half of the cases. Otherwise, it was 1) phonologically but not semantically related, 2) semantically but not phonologically related, or 3) neither phonologically nor semantically related to the sentence. Participants indicated by button press whether the last word matched the sentence they had read outside the scanner. Behavioural results showed more errors in condition 1 than in conditions 2 or 3, suggesting that phonological compatibility overrides semantic discrepancy when intelligibility is poor. Event-related field analysis demonstrated larger activity on frontal sites for correct than unrelated words, suggesting that the former were more accurately expected than the latter. An early M170 component was also observed, possibly reflecting expectation violation in the auditory modality. Dipole analysis will reveal whether M170 could be modulated by type of linguistic discrepancy. Distributed-network analysis will further our understanding of the time course and neural correlates of discrepancies between incoming auditory information and linguistic expectations.

The perceptual clarity of speech is not entirely dependent on the acoustic quality of the sound. Other resources, such as linguistic representations, are involved during degraded speech perception. For example, presentation of the written version of a degraded sentence before hearing it will enable prior knowledge on the exact speech content, which will make the degraded sentence seems clearer. This phenomenon has been explained by top-down influence of phonological and lexical representations on acoustic processing. Another example is the influence of semantic representations on the intelligibility of degraded speech: degraded sentences are better reported if they are meaningful than meaningless. The question now is whether the semantic representations could further influence the perceptual clarity of degraded speech for both normal-hearing (NH) and hearing-impaired (HI) listeners. In the reported set of three experiments, grammatically correct Swedish spoken sentences were presented at different sound quality levels, from clear to unintelligible. The sound quality levels were manipulated by using noise vocoding (NV) method in which the number of bands reflects intelligibility: more bands for more intelligibility. HI listeners were provided with amplification according to the Cambridge formula. The sentences had either high (e.g. “His new clothes were from France.”) or low (e.g. “His red school was from the newspaper”) semantic coherence and were matched at the word level. The written version of each spoken word (matching text) or a string of consonants (non-matching text) was presented 200 ms beforehand in a rapid serial visual paradigm. The task of the listeners was to rate the clarity of each spoken sentence on a 7-point Likert scale. Results revealed significant interactions between coherence and text for both groups, showing a benefit of coherence with matching and non-matching text for NH listeners but only with matching text for HI listeners. Significant three-way interactions including sound quality level modified this finding to some extent. Indeed, NH listeners benefitted from semantic coherence with non-matching text at 6 and 12 band NV (but not 3 band) while HI listeners benefitted at 12 band (but not 3 and 6 band). Preliminary fMRI results obtained for NH listeners indicated that processing of semantic coherence with non-matching text is supported by right middle temporal gyrus. The overall pattern of results suggest that NH listeners successfully utilize semantic representations in spoken sentences that are moderately degraded and when no prior knowledge is available. What prevents HI listeners to do the same?

The purpose of this study is to examine whether the neural correlates of lexical expectations could be used to predict speech in noise perception. We analyse mag-netoencephalography (MEG) data from 20 normal hearing participants, who read a set of couplets (a pair of phrases with rhyming end words) prior to the experiment. During the experiment, the participants are asked to listen to the couplets, whose intelligibility is set to 80%. However, the last word is pronounced with a delay of 1600 ms (i.e. expectation gap) and is masked at 50% of intelligibility. At the end of each couplet, the participants are asked to indicate if the last word was cor-rect, i.e. corresponding to the expected word. Given the oscillatory characteristics of neural patterns of lexical expectations during the expectation gap, can we predict the participant’s actual perception of the last word? In order to approach this re-search question, we aim to identify the correlation patterns between the instances of neural pre-activation, occurring during the interval of the expectation gap and the type of the given answer. According to the sequential design of the experiment, the expectation gap is placed 4400 ms prior to the time interval dedicated to the participant’s answer. Machine Learning approach has been chosen as the main tool for the pattern recognition.