Donor Ability of Bisphosphinemonoxide Ligands Relevant to Late-Metal Olefin Polymerization Catalysis.

Late-transition-metal catalysts for polymerization of olefins have drawn a significant amount of attention owing to their ability to tolerate and incorporate polar comonomers. However, a systematic way to experimentally quantify the electronic properties of the ligands used in these systems has not been developed. Quantified ligand parameters will allow for the rational design of tailored polymerization catalysts, which would target specific polymer properties. We report a series of platinum complexes bearing bisphosphinemonoxide ligands, which resemble those used in the polymerization catalysts of Nozaki and Chen. Their electronic properties are investigated experimentally, and trends are rationalized by using computed spectral properties. Benchmarking computational data with known experimental parameters further enhances the utility of both methods for determining optimal ligands for catalytic application.

Neurophysiological Evidence for Semantic Processing of Irrelevant Speech and Own-Name Detection in a Virtual Café.

The well-known "cocktail party effect" refers to incidental detection of salient words, such as one's own-name, in supposedly unattended speech. However, empirical investigation of the prevalence of this phenomenon and the underlying mechanisms has been limited to extremely artificial contexts and has yielded conflicting results. We introduce a novel empirical approach for revisiting this effect under highly ecological conditions, by immersing participants in a multisensory Virtual Café and using realistic stimuli and tasks. Participants (32 female, 18 male) listened to conversational speech from a character at their table, while a barista in the back of the café called out food orders. Unbeknownst to them, the barista sometimes called orders containing either their own-name or words that created semantic violations. We assessed the neurophysiological response-profile to these two probes in the task-irrelevant barista stream by measuring participants' brain activity (EEG), galvanic skin response and overt gaze-shifts.SIGNIFICANCE STATEMENT We found distinct neural and physiological responses to participants' own-name and semantic violations, indicating their incidental semantic processing despite being task-irrelevant. Interestingly, these responses were covert in nature and gaze-patterns were not associated with word-detection responses. This study emphasizes the nonexclusive nature of attention in multimodal ecological environments and demonstrates the brain's capacity to extract linguistic information from additional sources outside the primary focus of attention.

An ecological investigation of the capacity to follow simultaneous speech and preferential detection of ones' own name.

Many situations require focusing attention on one speaker, while monitoring the environment for potentially important information. Some have proposed that dividing attention among 2 speakers involves behavioral trade-offs, due to limited cognitive resources. However the severity of these trade-offs, particularly under ecologically-valid circumstances, is not well understood. We investigated the capacity to process simultaneous speech using a dual-task paradigm simulating task-demands and stimuli encountered in real-life. Participants listened to conversational narratives (Narrative Stream) and monitored a stream of announcements (Barista Stream), to detect when their order was called. We measured participants' performance, neural activity, and skin conductance as they engaged in this dual-task. Participants achieved extremely high dual-task accuracy, with no apparent behavioral trade-offs. Moreover, robust neural and physiological responses were observed for target-stimuli in the Barista Stream, alongside significant neural speech-tracking of the Narrative Stream. These results suggest that humans have substantial capacity to process simultaneous speech and do not suffer from insufficient processing resources, at least for this highly ecological task-combination and level of perceptual load. Results also confirmed the ecological validity of the advantage for detecting ones' own name at the behavioral, neural, and physiological level, highlighting the contribution of personal relevance when processing simultaneous speech.

"Unattended, distracting or irrelevant": Theoretical implications of terminological choices in auditory selective attention research.

For seventy years, auditory selective attention research has focused on studying the cognitive mechanisms of prioritizing the processing a 'main' task-relevant stimulus, in the presence of 'other' stimuli. However, a closer look at this body of literature reveals deep empirical inconsistencies and theoretical confusion regarding the extent to which this 'other' stimulus is processed. We argue that many key debates regarding attention arise, at least in part, from inappropriate terminological choices for experimental variables that may not accurately map onto the cognitive constructs they are meant to describe. Here we critically review the more common or disruptive terminological ambiguities, differentiate between methodology-based and theory-derived terms, and unpack the theoretical assumptions underlying different terminological choices. Particularly, we offer an in-depth analysis of the terms 'unattended' and 'distractor' and demonstrate how their use can lead to conflicting theoretical inferences. We also offer a framework for thinking about terminology in a more productive and precise way, in hope of fostering more productive debates and promoting more nuanced and accurate cognitive models of selective attention.

Assessing the Sensitivity of EEG-Based Frequency-Tagging as a Metric for Statistical Learning.

Statistical learning (SL) is hypothesized to play an important role in language development. However, the measures typically used to assess SL, particularly at the level of individual participants, are largely indirect and have low sensitivity. Recently, a neural metric based on frequency-tagging has been proposed as an alternative measure for studying SL. We tested the sensitivity of frequency-tagging measures for studying SL in individual participants in an artificial language paradigm, using non-invasive electroencephalograph (EEG) recordings of neural activity in humans. Importantly, we used carefully constructed controls to address potential acoustic confounds of the frequency-tagging approach, and compared the sensitivity of EEG-based metrics to both explicit and implicit behavioral tests of SL. Group-level results confirm that frequency-tagging can provide a robust indication of SL for an artificial language, above and beyond potential acoustic confounds. However, this metric had very low sensitivity at the level of individual participants, with significant effects found only in 30% of participants. Comparison of the neural metric to previously established behavioral measures for assessing SL showed a significant yet weak correspondence with performance on an implicit task, which was above-chance in 70% of participants, but no correspondence with the more common explicit 2-alternative forced-choice task, where performance did not exceed chance-level. Given the proposed ubiquitous nature of SL, our results highlight some of the operational and methodological challenges of obtaining robust metrics for assessing SL, as well as the potential confounds that should be taken into account when using the frequency-tagging approach in EEG studies.