Expectations boost the reconstruction of auditory features from electrophysiological responses to noisy speech.

Online speech processing imposes significant computational demands on the listening brain, the underlying mechanisms of which remain poorly understood. Here, we exploit the perceptual "pop-out" phenomenon (i.e. the dramatic improvement of speech intelligibility after receiving information about speech content) to investigate the neurophysiological effects of prior expectations on degraded speech comprehension. We recorded electroencephalography (EEG) and pupillometry from 21 adults while they rated the clarity of noise-vocoded and sine-wave synthesized sentences. Pop-out was reliably elicited following visual presentation of the corresponding written sentence, but not following incongruent or neutral text. Pop-out was associated with improved reconstruction of the acoustic stimulus envelope from low-frequency EEG activity, implying that improvements in perceptual clarity were mediated via top-down signals that enhanced the quality of cortical speech representations. Spectral analysis further revealed that pop-out was accompanied by a reduction in theta-band power, consistent with predictive coding accounts of acoustic filling-in and incremental sentence processing. Moreover, delta-band power, alpha-band power, and pupil diameter were all increased following the provision of any written sentence information, irrespective of content. Together, these findings reveal distinctive profiles of neurophysiological activity that differentiate the content-specific processes associated with degraded speech comprehension from the context-specific processes invoked under adverse listening conditions.

Action imagery as active inference: a commentary on Rieger et al. (2023).

Rieger et al. (Psychol Res 2023:1-10, 2023) describe action imagery as motor simulation. Inverse models encode predicted action effects and compute muscle commands, which are inhibited to prevent overt action. We welcome this conceptualization of action imagery as inherently generative and predictive. In the spirit of stimulating further theoretical discourse on action imagery, and more broadly, action control, our commentary provides a brief introduction to Active Inference to establish a contrasting perspective from which to consider what, how, and why action imagery contributes to motor learning.

Oscillatory and Aperiodic Neural Activity Jointly Predict Language Learning.

Memory formation involves the synchronous firing of neurons in task-relevant networks, with recent models postulating that a decrease in low-frequency oscillatory activity underlies successful memory encoding and retrieval. However, to date, this relationship has been investigated primarily with face and image stimuli; considerably less is known about the oscillatory correlates of complex rule learning, as in language. Furthermore, recent work has shown that nonoscillatory (1/ƒ) activity is functionally relevant to cognition, yet its interaction with oscillatory activity during complex rule learning remains unknown. Using spectral decomposition and power-law exponent estimation of human EEG data (17 women, 18 men), we show for the first time that 1/ƒ and oscillatory activity jointly influence the learning of word order rules of a miniature artificial language system. Flexible word-order rules were associated with a steeper 1/ƒ slope, whereas fixed word-order rules were associated with a shallower slope. We also show that increased theta and alpha power predicts fixed relative to flexible word-order rule learning and behavioral performance. Together, these results suggest that 1/ƒ activity plays an important role in higher-order cognition, including language processing, and that grammar learning is modulated by different word-order permutations, which manifest in distinct oscillatory profiles.

Automated design of probes for rRNA-targeted fluorescence in situ hybridization reveals the advantages of using dual probes for accurate identification.

Fluorescence in situ hybridization (FISH) is a common technique for identifying cells in their natural environment and is often used to complement next-generation sequencing approaches as an integral part of the full-cycle rRNA approach. A major challenge in FISH is the design of oligonucleotide probes with high sensitivity and specificity to their target group. The rapidly expanding number of rRNA sequences has increased awareness of the number of potential nontargets for every FISH probe, making the design of new FISH probes challenging using traditional methods. In this study, we conducted a systematic analysis of published probes that revealed that many have insufficient coverage or specificity for their intended target group. Therefore, we developed an improved thermodynamic model of FISH that can be applied at any taxonomic level, used the model to systematically design probes for all recognized genera of bacteria and archaea, and identified potential cross-hybridizations for the selected probes. This analysis resulted in high-specificity probes for 35.6% of the genera when a single probe was used in the absence of competitor probes and for 60.9% when up to two competitor probes were used. Requiring the hybridization of two independent probes for positive identification further increased specificity. In this case, we could design highly specific probe sets for up to 68.5% of the genera without the use of competitor probes and 87.7% when up to two competitor probes were used. The probes designed in this study, as well as tools for designing new probes, are available online (http://DECIPHER.cee.wisc.edu).

Accelerating scientific progress through Bayesian adversarial collaboration.

Adversarial collaboration has been championed as the gold standard for resolving scientific disputes but has gained relatively limited traction in neuroscience and allied fields. In this perspective, we argue that adversarial collaborative research has been stymied by an overly restrictive concern with the falsification of scientific theories. We advocate instead for a more expansive view that frames adversarial collaboration in terms of Bayesian belief updating, model comparison, and evidence accumulation. This framework broadens the scope of adversarial collaboration to accommodate a wide range of informative (but not necessarily definitive) studies while affording the requisite formal tools to guide experimental design and data analysis in the adversarial setting. We provide worked examples that demonstrate how these tools can be deployed to score theoretical models in terms of a common metric of evidence, thereby furnishing a means of tracking the amount of empirical support garnered by competing theories over time.

Body as First Teacher: The Role of Rhythmic Visceral Dynamics in Early Cognitive Development.

Embodied cognition-the idea that mental states and processes should be understood in relation to one's bodily constitution and interactions with the world-remains a controversial topic within cognitive science. Recently, however, increasing interest in predictive processing theories among proponents and critics of embodiment alike has raised hopes of a reconciliation. This article sets out to appraise the unificatory potential of predictive processing, focusing in particular on embodied formulations of active inference. Our analysis suggests that most active-inference accounts invoke weak, potentially trivial conceptions of embodiment; those making stronger claims do so independently of the theoretical commitments of the active-inference framework. We argue that a more compelling version of embodied active inference can be motivated by adopting a diachronic perspective on the way rhythmic physiological activity shapes neural development in utero. According to this visceral afferent training hypothesis, early-emerging physiological processes are essential not only for supporting the biophysical development of neural structures but also for configuring the cognitive architecture those structures entail. Focusing in particular on the cardiovascular system, we propose three candidate mechanisms through which visceral afferent training might operate: (a) activity-dependent neuronal development, (b) periodic signal modeling, and (c) oscillatory network coordination.

Stress and its sequelae: An active inference account of the etiological pathway from allostatic overload to depression.

Survival requires the implementation of adaptive changes that demand energy resources. The efficient regulation of energetic resources thus plays a critical role in enabling systems to adapt to the demands of their internal and external environments. The framework of active inference explains how living organisms can build probabilistic models that enable them to predict, track, and regulate energy expenditure in the short and long run. The aim of the paper is to characterize the physiological changes that accompany stress, and the relationship between these changes and the loss of confidence in a system's predictions about its internal and external milieu-ultimately manifesting as depressive symptomatology. We identify the systems that underwrite goal-directed behavior, and the neuroendocrine and immunological systems, as the hierarchical controller that regulates energy resources. In doing so, we establish an etiological pathway from allostatic overload to depression via active inference.

Waiting longer, feeling fatter: Effects of response delay on tactile distance estimation and confidence in females with anorexia nervosa.

BACKGROUND: Research suggests that patients with anorexia nervosa (AN) exhibit differences in the perceptual processing of their own bodies. However, some researchers suggest that these differences are better explained with reference to non-perceptual factors, such as demand characteristics or emotional responses to the task. In this study, we investigated whether overestimation of tactile distances in participants with AN results from differences in tactile processing or non-perceptual factors, by measuring the role of allowed response time in an adapted version of the tactile distance estimation task (TDE-D). We further investigated the relationship between allowed response time and participants' confidence in their tactile judgments. METHOD: Our sample consisted of females: participants with AN (n = 30), recovered (REC) participants (n = 29) and healthy controls (HC) (n = 31). Participants were asked to estimate tactile distances presented on the skin of either a salient (abdomen) or non-salient (arm) body part, either directly after stimulus presentation (direct condition) or after a 5 s delay (delayed condition). Confidence of estimation accuracy was measured after each response. RESULTS: Results showed that allowing AN and REC more time to respond caused them to estimate tactile distances as larger. Additionally, participants with AN became less confident when given more time to respond. CONCLUSIONS: These results suggest that non-perceptual influences cause participants with AN to increase their estimates of tactile distances and become less certain of these estimates. We speculate that previous findings-where participants with AN estimate tactile distances as larger than HC-may be due to non-perceptual differences.

Rapid adaptation of predictive models during language comprehension: Aperiodic EEG slope, individual alpha frequency and idea density modulate individual differences in real-time model updating.

Predictive coding provides a compelling, unified theory of neural information processing, including for language. However, there is insufficient understanding of how predictive models adapt to changing contextual and environmental demands and the extent to which such adaptive processes differ between individuals. Here, we used electroencephalography (EEG) to track prediction error responses during a naturalistic language processing paradigm. In Experiment 1, 45 native speakers of English listened to a series of short passages. Via a speaker manipulation, we introduced changing intra-experimental adjective order probabilities for two-adjective noun phrases embedded within the passages and investigated whether prediction error responses adapt to reflect these intra-experimental predictive contingencies. To this end, we calculated a novel measure of speaker-based, intra-experimental surprisal ("speaker-based surprisal") as defined on a trial-by-trial basis and by clustering together adjectives with a similar meaning. N400 amplitude at the position of the critical second adjective was used as an outcome measure of prediction error. Results showed that N400 responses attuned to speaker-based surprisal over the course of the experiment, thus indicating that listeners rapidly adapt their predictive models to reflect local environmental contingencies (here: the probability of one type of adjective following another when uttered by a particular speaker). Strikingly, this occurs in spite of the wealth of prior linguistic experience that participants bring to the laboratory. Model adaptation effects were strongest for participants with a steep aperiodic (1/f) slope in resting EEG and low individual alpha frequency (IAF), with idea density (ID) showing a more complex pattern. These results were replicated in a separate sample of 40 participants in Experiment 2, which employed a highly similar design to Experiment 1. Overall, our results suggest that individuals with a steep aperiodic slope adapt their predictive models most strongly to context-specific probabilistic information. Steep aperiodic slope is thought to reflect low neural noise, which in turn may be associated with higher neural gain control and better cognitive control. Individuals with a steep aperiodic slope may thus be able to more effectively and dynamically reconfigure their prediction-related neural networks to meet current task demands. We conclude that predictive mechanisms in language are highly malleable and dynamic, reflecting both the affordances of the present environment as well as intrinsic information processing capabilities of the individual.

Design and implementation of an institutional case report form library.

BACKGROUND: Case report forms (CRFs) are used to collect data in clinical research. Case report form development represents a significant part of the clinical trial process and can affect study success. Libraries of CRFs can preserve the organizational knowledge and expertise invested in CRF development and expedite the sharing of such knowledge. Although CRF libraries have been advocated, there have been no published accounts reporting institutional experiences with creating and using them. PURPOSE: We sought to enhance an existing institutional CRF library by improving information indexing and accessibility. We describe this CRF library and discuss challenges encountered in its development and implementation, as well as future directions for continued work in this area. METHODS: We transformed an existing but underused and poorly accessible CRF library into a resource capable of supporting and expediting clinical and translational investigation at our institution by (1) expanding access to the entire institution; (2) adding more form attributes for improved information retrieval; and (3) creating a formal information curation and maintenance process. An open-source content management system, Plone (Plone.org), served as the platform for our CRF library. RESULTS: We report results from these three processes. Over the course of this project, the size of the CRF library increased from 160 CRFs comprising an estimated total of 17,000 pages, to 177 CRFs totaling 1.5 gigabytes. Eighty-two of these CRFs are now available to researchers across our institution; 95 CRFs remain within a contractual confidentiality window (usually 5 years from database lock) and are not available to users outside of the Duke Clinical Research Institute (DCRI). Conservative estimates suggest that the library supports an average of 37 investigators per month. The resources needed to curate and maintain the CRF library require less than 10% of the effort of one full-time equivalent employee. LIMITATIONS: Although we succeeded in expanding use of the CRF library, creating awareness of such institutional resources among investigators and research teams remains challenging and requires additional efforts to overcome. Institutions that have not achieved a critical mass of attractive research resources or effective dissemination mechanisms may encounter persistent difficulty attracting researchers to use institutional resources. Further, a useful CRF library requires both an initial investment of resources for development, as well as ongoing maintenance once it is established. CONCLUSIONS: CRF libraries can be established and made broadly available to institutional researchers. Curation - that is, indexing newly added forms - is required. Such a resource provides knowledge management capacity for institutions until standards and software are available to support widespread exchange of data and form definitions.

Be still my heart: Cardiac regulation as a mode of uncertainty reduction.

Decreased heart rate (HR) and variability (HRV) are well-established correlates of attention; however, the functional significance of these dynamics remains unclear. Here, we investigate whether attention-related cardiac modulation is sensitive to different varieties of uncertainty. Thirty-nine adults performed a binocular rivalry-replay task in which changes in visual perception were driven either internally (in response to constant, conflicting stimuli; rivalry) or externally (in response to physically alternating stimuli; replay). Tonic HR and high-frequency HRV linearly decreased as participants progressed from resting-state baseline (minimal visual uncertainty) through replay (temporal uncertainty) to rivalry (temporal uncertainty and ambiguity). Time-resolved frequency estimates revealed that cardiac deceleration was sustained throughout the trial period and modulated by ambiguity, novelty, and switch rate. These findings suggest cardiac regulation during active attention may play an instrumental role in uncertainty reduction.

EEG and behavioral correlates of attentional processing while walking and navigating naturalistic environments.

The capacity to regulate one's attention in accordance with fluctuating task demands and environmental contexts is an essential feature of adaptive behavior. Although the electrophysiological correlates of attentional processing have been extensively studied in the laboratory, relatively little is known about the way they unfold under more variable, ecologically-valid conditions. Accordingly, this study employed a 'real-world' EEG design to investigate how attentional processing varies under increasing cognitive, motor, and environmental demands. Forty-four participants were exposed to an auditory oddball task while (1) sitting in a quiet room inside the lab, (2) walking around a sports field, and (3) wayfinding across a university campus. In each condition, participants were instructed to either count or ignore oddball stimuli. While behavioral performance was similar across the lab and field conditions, oddball count accuracy was significantly reduced in the campus condition. Moreover, event-related potential components (mismatch negativity and P3) elicited in both 'real-world' settings differed significantly from those obtained under laboratory conditions. These findings demonstrate the impact of environmental factors on attentional processing during simultaneously-performed motor and cognitive tasks, highlighting the value of incorporating dynamic and unpredictable contexts within naturalistic designs.

Anorexia nervosa and the size-weight illusion: No evidence of impaired visual-haptic object integration.

Body image disorders in anorexia nervosa (AN) patients and recovered AN (RAN) patients have been suggested to stem from aberrant integration of sensory information. Previous research by Case et al. (2012) used the size-weight illusion (SWI) to study multisensory integration in AN. Their results showed a diminished SWI in AN patients, which they interpreted as evidence of decreased integration of visual and proprioceptive information. However, their method did not distinguish between visual and haptic size information, which was presented concurrently while making weight judgements. Therefore, the reported effect might be attributed to integrating visual, haptic size cues, or a combination of both processes with proprioceptive input. Here, we use the SWI to investigate the integration of visual and haptic object-related sensory information in a sample of AN patients (n = 30), RAN patients (n = 29) and healthy controls (HC) (n = 29). We aimed to distinguish the contribution of visual and haptic object size by including separate visual and haptic SWI conditions. In addition to explicit measures, we included grip force measurements to assess implicit expectations about object weight. We further analysed the correlation between the SWI and a visual body size estimation (VSE) task. In contrast to Case et al. (2012), we found no evidence of differential SWI experience between groups. All participants reported a stronger visual SWI compared to haptic SWI. Grip force rate (but not peak) showed evidence of motor adaptation for the larger object in the visual condition. Furthermore, there was no correlation between the VSE and SWI, indicating no relation between perceived object weight and body size estimation. These results do not support the hypothesised impairment of visual-haptic object related integration in AN.

Individual alpha frequency modulates sleep-related emotional memory consolidation.

Alpha-band oscillatory activity is involved in modulating memory and attention. However, few studies have investigated individual differences in oscillatory activity during the encoding of emotional memory, particularly in sleep paradigms where sleep is thought to play an active role in memory consolidation. The current study aimed to address the question of whether individual alpha frequency (IAF) modulates the consolidation of declarative memory across periods of sleep and wake. 22 participants aged 18-41 years (mean age = 25.77) viewed 120 emotionally valenced images (positive, negative, neutral) and completed a baseline memory task before a 2hr afternoon sleep opportunity and an equivalent period of wake. Following the sleep and wake conditions, participants were required to distinguish between 120 learned (target) images and 120 new (distractor) images. This method allowed us to delineate the role of different oscillatory components of sleep and wake states in the emotional modulation of memory. Linear mixed-effects models revealed interactions between IAF, rapid eye movement sleep theta power, and slow-wave sleep slow oscillatory density on memory outcomes. These results highlight the importance of individual factors in the EEG in modulating oscillatory-related memory consolidation and subsequent behavioural outcomes and test predictions proposed by models of sleep-based memory consolidation.

Operationalizing needs-focused palliative care for older adults in intensive care units: Design of and rationale for the PCplanner randomized clinical trial.

INTRODUCTION: The number of older adults who receive life support in an intensive care unit (ICU), now 2 million per year, is increasing while survival remains unchanged. Because the quality of ICU-based palliative care is highly variable, we developed a mobile app intervention that integrates into the electronic health records (EHR) system called PCplanner (Palliative Care planner) with the goal of improving collaborative primary and specialist palliative care delivery in ICU settings. OBJECTIVE: To describe the methods of a randomized clinical trial (RCT) being conducted to compare PCplanner vs. usual care. METHODS AND ANALYSIS: The goal of this two-arm, parallel group mixed methods RCT is to determine the clinical impact of the PCplanner intervention on outcomes of interest to patients, family members, clinicians, and policymakers over a 3-month follow up period. The primary outcome is change in unmet palliative care needs measured by the NEST instrument between baseline and 1 week post-randomization. Secondary outcomes include goal concordance of care, patient-centeredness of care, and quality of communication at 1 week post-randomization; length of stay; as well as symptoms of depression, anxiety, and post-traumatic stress disorder at 3 months post-randomization. We will use general linear models for repeated measures to compare outcomes across the main effects and interactions of the factors. We hypothesize that compared to usual care, PCplanner will have a greater impact on the quality of ICU-based palliative care delivery across domains of core palliative care needs, psychological distress, patient-centeredness, and healthcare resource utilization.

Perceptual awareness and active inference.

Perceptual awareness depends upon the way in which we engage with our sensorium. This notion is central to active inference, a theoretical framework that treats perception and action as inferential processes. This variational perspective on cognition formalizes the notion of perception as hypothesis testing and treats actions as experiments that are designed (in part) to gather evidence for or against alternative hypotheses. The common treatment of perception and action affords a useful interpretation of certain perceptual phenomena whose active component is often not acknowledged. In this article, we start by considering Troxler fading - the dissipation of a peripheral percept during maintenance of fixation, and its recovery during free (saccadic) exploration. This offers an important example of the failure to maintain a percept without actively interrogating a visual scene. We argue that this may be understood in terms of the accumulation of uncertainty about a hypothesized stimulus when free exploration is disrupted by experimental instructions or pathology. Once we take this view, we can generalize the idea of using bodily (oculomotor) action to resolve uncertainty to include the use of mental (attentional) actions for the same purpose. This affords a useful way to think about binocular rivalry paradigms, in which perceptual changes need not be associated with an overt movement.

Individual differences in first- and second-order temporal judgment.

The ability of subjects to identify and reproduce brief temporal intervals is influenced by many factors whether they be stimulus-based, task-based or subject-based. The current study examines the role individual differences play in subsecond and suprasecond timing judgments, using the schizoptypy personality scale as a test-case approach for quantifying a broad range of individual differences. In two experiments, 129 (Experiment 1) and 141 (Experiment 2) subjects completed the O-LIFE personality questionnaire prior to performing a modified temporal-bisection task. In the bisection task, subjects responded to two identical instantiations of a luminance grating presented in a 4deg window, 4deg above fixation for 1.5 s (Experiment 1) or 3 s (Experiment 2). Subjects initiated presentation with a button-press, and released the button when they considered the stimulus to be half-way through (750/1500 ms). Subjects were then asked to indicate their 'most accurate estimate' of the two intervals. In this way we measure both performance on the task (a first-order measure) and the subjects' knowledge of their performance (a second-order measure). In Experiment 1 the effect of grating-drift and feedback on performance was also examined. Experiment 2 focused on the static/no-feedback condition. For the group data, Experiment 1 showed a significant effect of presentation order in the baseline condition (no feedback), which disappeared when feedback was provided. Moving the stimulus had no effect on perceived duration. Experiment 2 showed no effect of stimulus presentation order. This elimination of the subsecond order-effect was at the expense of accuracy, as the mid-point of the suprasecond interval was generally underestimated. Response precision increased as a proportion of total duration, reducing the variance below that predicted by Weber's law. This result is consistent with a breakdown of the scalar properties of time perception in the early suprasecond range. All subjects showed good insight into their own performance, though that insight did not necessarily correlate with the veridical bisection point. In terms of personality, we found evidence of significant differences in performance along the Unusual Experiences subscale, of most theoretical interest here, in the subsecond condition only. There was also significant correlation with Impulsive Nonconformity and Cognitive Disorganisation in the sub- and suprasecond conditions, respectively. Overall, these data support a partial dissociation of timing mechanisms at very short and slightly longer intervals. Further, these results suggest that perception is not the only critical mitigator of confidence in temporal experience, since individuals can effectively compensate for differences in perception at the level of metacognition in early suprasecond time. Though there are individual differences in performance, these are perhaps less than expected from previous reports and indicate an effective timing mechanism dealing with brief durations independent of the influence of significant personality trait differences.

Toward a reliable, automated method of individual alpha frequency (IAF) quantification.

Individual alpha frequency (IAF) is a promising electrophysiological marker of interindividual differences in cognitive function. IAF has been linked with trait-like differences in information processing and general intelligence, and provides an empirical basis for the definition of individualized frequency bands. Despite its widespread application, however, there is little consensus on the optimal method for estimating IAF, and many common approaches are prone to bias and inconsistency. Here, we describe an automated strategy for deriving two of the most prevalent IAF estimators in the literature: peak alpha frequency (PAF) and center of gravity (CoG). These indices are calculated from resting-state power spectra that have been smoothed using a Savitzky-Golay filter (SGF). We evaluate the performance characteristics of this analysis procedure in both empirical and simulated EEG data sets. Applying the SGF technique to resting-state data from n = 63 healthy adults furnished 61 PAF and 62 CoG estimates. The statistical properties of these estimates were consistent with previous reports. Simulation analyses revealed that the SGF routine was able to reliably extract target alpha components, even under relatively noisy spectral conditions. The routine consistently outperformed a simpler method of automated peak detection that did not involve spectral smoothing. The SGF technique is fast, open source, and available in two popular programming languages (MATLAB, Python), and thus can easily be integrated within the most popular M/EEG toolsets (EEGLAB, FieldTrip, MNE-Python). As such, it affords a convenient tool for improving the reliability and replicability of future IAF-related research.