Experimental Paradigm Research Articles

Examining the Effects of Cognitive Behavioral Therapy With a Virtual Agent on User Motivation and Improvement in Psychological Distress and Anxiety: Two-Session Experimental Study.

Cognitive behavioral therapy (CBT) is a valuable treatment for mood disorders and anxiety. CBT methods, such as cognitive restructuring, are employed to change automatic negative thoughts to more realistic ones. This study extends on previous research conducted by the authors, focused on the process of correcting automatic negative thoughts to realistic ones and reducing distress and anxiety via CBT with a virtual agent. It was aimed to investigate whether the previously applied virtual agent would achieve changes in automatic negative thoughts when modifications to the previous experimental paradigm are applied and when user motivation is taken into consideration. Furthermore, thepotential effects of existing participant knowledge concerning CBT or automatic thoughts were explored. A single-group, 2-session experiment was conducted using a within-group design. The study recruited 35 participants from May 15, 2023, to June 2, 2023, via Inter Group Corporation, with data collection following from June 5 to June 20, 2023, at Nara Institute of Science and Technology, Japan. There were 19 male and 16 female participants (age range: 18-50 years; mean 33.66, SD 10.77 years). Participants answered multiple questionnaires covering depressive symptomatology and other cognitive variables before and after a CBT session. CBT was carried out using a virtual agent, who participants conversed with using a CBT dialogue scenario on the topic of automatic negative thoughts. Session 2 of the experiment took place 1 week after session 1. Changes in distress and state anxiety were analyzed using a Wilcoxon signed-rank test and t-test for paired samples. The relationships of motivation with cognitive changes and distress or anxiety changes were investigated via correlation analysis. Multiple linear regression was used to analyze the potential predictive qualities of previous knowledge of CBT and automatic negative thoughts regarding outcome measures. Significant reductions in distress (all P<.001) and state anxiety (all P<.003) emerged throughout the first and second experimental sessions. The CBT intervention increased participants' recognition of their negative thinking and their intention to change it, namely their motivation to change it. However, no clear correlations of motivation with changes in distress or anxiety were found (all P>.04). Participants reported moderate subjective changes in their cognition, which were in part positively correlated with their motivation (all P<.007). Lastly, existing knowledge of CBT did not predict reductions in distress during the first session of the experiment (P=.02). CBT using a virtual agent and a CBT dialogue scenario was successful in reducing distress and anxiety when talking about automatic negative thoughts. The promotion of client motivation needs to be critically considered when designing interventions using CBT with a virtual agent, and further experimental investigations on the causal influences between motivation and outcome measures need to be conducted.

On aggregation invariance of multinomial processing tree models

Multinomial processing tree (MPT) models are prominent and frequently used tools to model and measure cognitive processes underlying responses in many experimental paradigms. Although MPT models typically refer to cognitive processes within single individuals, they have often been applied to group data aggregated across individuals. We investigate the conditions under which MPT analyses of aggregate data make sense. After introducing the notions of structural and empirical aggregation invariance of MPT models, we show that any MPT model that holds at the level of single individuals must also hold at the aggregate level when it is both structurally and empirically aggregation invariant. Moreover, group-level parameters of aggregation-invariant MPT models are equivalent to the expected values (i.e., means) of the corresponding individual parameters. To investigate the robustness of MPT results for aggregate data when one or both invariance conditions are violated, we additionally performed a series of simulation studies, systematically manipulating (1) the sample sizes in different trees of the model, (2) model parameterization, (3) means and variances of crucial model parameters, and (4) their correlations with other parameters of the respective MPT model. Overall, our results show that MPT parameter estimates based on aggregate data are trustworthy under rather general conditions, provided that a few preconditions are met.

Gateway to the study of the amygdala and emotion.

The study of the amygdala and its role in the processing of emotions has become a common focus in neuroscience. The modern expansion of research in this area is partly due to the discovery of a subcortical pathway for the transmission of emotional information and the experimental paradigm that was developed to study it. Groundbreaking experiments during the 90s utilized anatomical, neurophysiological, and behavioral lesion studies in a rodent animal model to uncover the neural circuitry of a simple emotional memory. These studies demonstrated the essential role of a specific monosynaptic pathway in emotional memory, using traditional tools and behavioral methods. The development of an animal model with a simple and appropriate classical conditioning paradigm made experimental investigations into the neural basis of emotion tenable and available to a generation of neuroscientists. These tools and a focus on the amygdala's neural connections and their essential role in emotional memory were a driving force in the explosion of research regarding the amygdala and emotion.

Chronic treatment with the antipsychotic lurasidone modulates the neuroinflammatory changes associated with the vulnerability to chronic mild stress exposure in female rats

Stress exposure is a key risk factor for the developmentof depressive-like conditions. However, despite the higher incidence of Major Depressive Disorder in the female population, classical stress-based experimental paradigms have primarily focused on males. In the present study, we used the well-established chronic mild stress (CMS) paradigm to investigate the development of anhedonia, a cardinal symptom of affective disorders, in the female animals and we also studied the potential effect of the antipsychotic drug lurasidone in normalizing the alterations brought about by stress exposure. We found that three weeks of CMS exposure produced a significant reduction of sucrose intake in 50% of the animals (vulnerable, CMS-V), whereas the others were resilient (CMS-R). The development of an anhedonic phenotype in CMS-V was associated with a significant elevation of different immune markers, such as Complement C3 and C4, and inflammatory cytokines, including INFß and Il1ß in dorsal and ventral hippocampus. Interestingly, sub-chronic treatment with the antipsychotic drug lurasidone was able to revert the anhedonic phenotype while normalizing most of the molecular alterations found in rats vulnerable to CMS exposure. This study extends the ability of lurasidone to normalize the anhedonic phenotype in CMS rats also to females. Moreover, we provide novel evidence on lurasidone’s potential effectiveness in treating mental disorders characterized by immune-inflammatory dysfunction.

Concerted modulation of spontaneous behavior and time-integrated whole-brain neuronal activity by serotonin receptors.

Serotonin neurons from the raphe nuclei project across the entire brain and modulate diverse physiology and behavior by acting on over a dozen receptors. Here, we took a step towards dissecting this complex process by examining the effects of agonists and antagonists of four widely expressed serotonin receptors (2A, 2C, 1A, and 1B) on spontaneous mouse behavior, which we related to time-integrated whole-brain neuronal activity as assessed by the expression of Fos, a canonical immediate-early gene product. Low-dimensional representations of behavioral and Fos map data revealed the dominant factors of variation in each domain, captured predictable differences across drug groups, and enabled predictions of behavioral changes following perturbations in Fos maps and vice versa. Our study provides a rich resource describing the effects of manipulating serotonin receptors on animal behavior and whole-brain integrated neuronal activity. It also establishes an experimental and analysis paradigm for interrogating the relationship between behavior and neuronal activity across different time scales.

Research on Pattern Classification Based on Double Pseudo-Inverse Extreme Learning Machine

This research aims to address the limitations inherent in the traditional Extreme Learning Machine (ELM) algorithm, particularly the stochastic determination of input-layer weights and hidden-layer biases, which frequently leads to an excessive number of hidden-layer neurons and inconsistent performance. To augment the neural network’s efficacy in pattern classification, Principal Component Analysis (PCA) is employed to reduce the dimensionality of the input matrix and alleviate multicollinearity issues during the computation of the input weight matrix. This paper introduces an enhanced ELM methodology, designated the PCA-DP-ELM algorithm, which integrates PCA with Double Pseudo-Inverse Weight Determination (DP). The PCA-DP-ELM algorithm proposed in this study consistently achieves superior average classification accuracy across various datasets, irrespective of whether assessed through longitudinal or cross-sectional experiments. The results from both experimental paradigms indicate that the optimized algorithm not only enhances accuracy but also improves stability. These findings substantiate that the proposed methodology exerts a positive influence on pattern classification.

Oscillatory features of German–English sentence processing: Evidence from an EEG study

Aims and objectives: In this study, we investigated the neural oscillatory patterns occurring during sentence-level overt bilingual processing tasks on 46 German–English bilinguals with the intention of finding out if there were task-specific oscillations for this language pair. Methodology: Four tasks, including Language 2 (L2) listening, Language 1 (L1) speaking, L2 shadowing (i.e., repeating a segment of an utterance), and backward interpreting (i.e., orally translating L2 sentences to L1), were implemented with the technique of electroencephalography (EEG). Data and analysis: Data included demographic indices, neural oscillation metrics, and oral production scores from participants. Static spectral analysis, time–frequency analysis, principal components analysis, cross-frequency coupling, and inferential statistics were applied to the data. Findings: The sensory task and articulatory tasks differed greatly in the delta–theta band and the beta–gamma band in terms of time–frequency dynamics. Analyses also revealed variations in a frontal/prefrontal theta component and a distinct gamma component across the four tasks. Moreover, we found a right fronto-temporal theta–gamma coupling unique to backward interpreting. Originality: The task-wise comparison experiment paradigm has rarely been implemented in neuroimaging research on language, especially so in EEG research on bilingualism. Significance: The findings provide novel insights for the understanding of language conversion mechanism and may benefit the training of professional interpreters.

Self-other voice discrimination task: A potential neuropsychological tool for clinical assessment of self-related deficits

BackgroundDeficits in self are commonly described through different neuro-pathologies, based on clinical evaluations and experimental paradigms. However, currently available approaches lack appropriate clinical validation, making objective evaluation and discrimination of self-related deficits challenging. MethodsWe applied a statistical standardized method to assess the clinical discriminatory capacity of a Self-Other Voice Discrimination (SOVD) task. This task, validated experimentally as a marker for self-related deficits, was administered to 17 patients eligible for neurosurgery due to focal hemispheric brain tumors or epileptic lesions. ResultsThe clinical discriminatory capacity of the SOVD task was evident in three patients who exhibited impairments for self-voice perception that could not be predicted by other neuropsychological deficits. Impairments in other-voice perception were linked to inhibitory neuropsychological deficits, suggesting a potential association with executive deficits in voice recognition. ConclusionsThis exploratory study highlights the clinical discriminatory potential of the SOVD task and suggests that it could complement the standard neuropsychological assessment, paving the way for enhanced diagnoses and tailored treatments for self-related deficits.

A large corpus for the recognition of Greek Sign Language gestures

Sign language recognition (SLR) from videos constitutes a captivating problem in gesture recognition, requiring the interpretation of hand movements, facial expressions, and body postures. The complexity of sign formation, signing variability among signers, and the technical hurdles of visual detection and tracking render SLR a challenging task. At the same time, the scarcity of large-scale SLR datasets, which are critical for developing robust data-intensive deep-learning SLR models, exacerbates these issues. In this article, we introduce a multi-signer video corpus of Greek Sign Language (GSL), which is the largest GSL database to date, serving as a valuable resource for SLR research. This corpus comprises an extensive RGB+D video collection that conveys rich lexical content in a multi-modal fashion, encompassing three subsets: (i) isolated signs; (ii) continuous signing; and (iii) continuous alphabet fingerspelling of words. Moreover, we introduce a comprehensive experimental setup that paves the way for more accurate and robust SLR solutions. In particular, except for the multi-signer (MS) and signer-independent (SI) settings, we employ a signer-adapted (SA) experimental paradigm, facilitating a comprehensive evaluation of system performance across various scenarios. Further, we provide three baseline SLR systems for isolated signs, continuous signing, and continuous fingerspelling. These systems leverage cutting-edge methods in deep learning and sequence modeling to capture the intricate temporal dynamics inherent in sign gestures. The models are evaluated on the three corpus subsets, setting their state-of-the-art recognition benchmark. The SL-ReDu GSL corpus, including its recommended experimental frameworks, is publicly available at https://sl-redu.e-ce.uth.gr/corpus.

Reliability and validity of facial expression recognition in the screening of generalized anxiety disorder

IntroductionAnxiety disorder is one of the most prevalent mental disorders in China. However, there are obvious subjective factors in the current assessment of anxiety disorders, which may lead to certain diagnostic errors. The identification and diagnosis of anxiety disorders can be further improved if objective biological indicators are added in the assessment process. The current research validates facial expression recognition as a screening tool to assist in detecting generalized anxiety disorder. MethodsBased on the International Affective Picture System, we constructed an aided diagnostic experimental paradigm and recorded their facial expression. The split-half reliability was displayed by the Pearson correlation heatmap. The paradigm, GAD-7 and HAMA scales were administered to 60 generalized anxiety disorder patients and 60 matched healthy controls to evaluate the criterion-related validity. Additionally, we conducted a diagnostic study by using MINI as a gold standard and calculated ROC analysis to examine the screening performance of the facial expressions. ResultsThe heatmap showed very high correlations (r > 0.60, PS < 0.05) along the diagonal of the square heatmap (from the bottom left corner to the top right). The Pearson correlation coefficients between the GAD-7, HAMA and seven facial expressions ranged from −0.35(neutral, P < 0.01) to 0.34(angry, P < 0.01). The intergroup effects of neutral, anger and fear emotions were statistically significant (F = 18.893, P < 0.001; F = 20.535, P < 0.001; F = 9.091, P = 0.003). ROC analysis showed AUC for neutral, angry and scared facial expressions were 0.723, 0.792 and 0.727 respectively. ConclusionThis study constructed a tool for auxiliary screening of GAD patients and provided an objective automatic facial expression recognition method to assist psychological diagnosis.

Portfolio framing and diversification in a disposition effect experiment

We experimentally test an intervention designed to reduce investors’ disposition effect by prompting them to identify their worst asset, from the standpoint of its impact on future portfolio performance. We find that this intervention is mildly effective, and significantly more so for participants who correctly identify their worst asset, and/or sell the asset they identify. We also find that participants who correctly understand diversification in a financial literacy questionnaire exhibit larger disposition effects in the experiment. The latter finding raises concerns over the external validity of standard experimental paradigms used to study the disposition effect.

The effects of experimental pain on episodic memory and its top-down modulation: a preregistered pooled analysis.

Pain can automatically interfere with ongoing cognitive processes such as attention and memory. The extent of pain's negative effects on cognitive functioning seems to depend on a balance between top-down and bottom-up factors. In this large, preregistered, pooled reanalysis of 8 studies, we investigated the robustness of the detrimental effect of acute pain on recognition memory and whether top-down mechanisms such as pain-related expectations or cognitions (pain-related fear, pain catastrophizing) modulate this effect. Two hundred forty-seven healthy participants underwent similar experimental paradigms, including a visual categorization task with images randomly paired with (or without) concomitant painful stimulation and a subsequent unannounced recognition task. Recognition memory (ie, d', recollection, and familiarity) and categorization performance (ie, reaction time, accuracy) served as proxies for the effect of pain on cognitive performance. Acute painful stimulation significantly impaired recognition performance (d', familiarity). However, recognition performance was not significantly modulated by participants' expectations regarding the effect of pain on task performance or pain-related cognitions in this sample of healthy participants. Our results corroborate the negative effects of pain on (visual) memory encoding reported in previous studies and reports of "memory problems" from patients with chronic pain. To characterize the role of bottom-up and top-down factors for the detrimental effects of pain, large-scale studies with more nuanced study designs are necessary. Future studies in patient cohorts must unravel the interaction of maladaptive pain-related cognitions and the often-reported impaired cognitive performance in chronic pain patients.

Pre-existing visual responses in a projection-defined dopamine population explain individual learning trajectories

A key challenge of learning a new task is that the environment is high dimensional-there are many different sensory features and possible actions, with typically only a small reward-relevant subset. Although animals can learn to perform complex tasks that involve arbitrary associations between stimuli, actions, and rewards,1,2,3,4,5,6 a consistent and striking result across varied experimental paradigms is that in initially acquiring such tasks, large differences between individuals are apparent in the learning process.7,8,9,10,11,12 What neural mechanisms contribute to initial task acquisition, and why do some individuals learn a new task much more quickly than others? To address these questions, we recorded longitudinally from dopaminergic (DA) axon terminals in mice learning a visual decision-making task.7 Across striatum, DA responses tracked idiosyncratic and side-specific learning trajectories, consistent with widespread reward prediction error coding across DA terminals. However, even before any rewards were delivered, contralateral-side-specific visual responses were present in DA terminals, primarily in the dorsomedial striatum (DMS). These pre-existing responses predicted the extent of learning for contralateral stimuli. Moreover, activation of these terminals improved contralateral performance. Thus, the initial conditions of a projection-specific and feature-specific DA signal help explain individual learning trajectories. More broadly, this work suggests that functional heterogeneity across DA projections may serve to bias target regions toward learning about different subsets of task features, providing a potential mechanism to address the dimensionality of the initial task learning problem.

Interference inhibition of multimodal information in digital interfaces and its rule of cognitive processing

AbstractIn the digital interface of multimodal audio–visual presentation, the appearance of irrelevant information often brings cognitive interference or even confusion, leading to decision‐making errors when users focus on or manipulate the interface target. However, few studies have explored the brain's inhibition effect and cognitive law evoked by audio–visual interference from the perspective of interface information design. On the basis of Stroop's classic interference task, an experimental paradigm of multimodal audio–visual stimuli to induce event‐related potential (ERP) components was designed for digital interfaces in this study. Combining behavioral measurement and ERP technology, this study discussed the differences in the induced inhibition effects between the two carriers under various audio–visual interferences. The findings demonstrated that all five interference stimuli, based on functional icons and Chinese characters, elicited significant N250 and N400, with a similar time course. Compared with the Chinese character group, the functional icon group elicited more negative activity in the frontal and some parietal‐occipital regions, indicating that the functional icon required more cognitive inhibitory resources to resist interference stimuli. Moreover, the inhibition effect induced by audio–visual interference with the same semantics was significantly lower than that of opposite semantics and even lower than that of single‐sensory interference. The findings offered physiological evidence for the inhibition effect induced by audio–visual semantic interference in digital interfaces and proposed design principles for the interface information of human–machine systems.

Online functional connectivity analysis of large all-to-all networks in MNE Scan

Abstract The analysis of electroencephalography (EEG)/magnetoencephalography (MEG) functional connectivity has become an important tool in neuroscience. Especially the high time resolution of EEG/MEG enables important insight into the functioning of the human brain. To date, functional connectivity is commonly estimated offline, that is, after the conclusion of the experiment. However, online computation of functional connectivity has the potential to enable unique experimental paradigms. For example, changes of functional connectivity due to learning processes could be tracked in real time and the experiment be adjusted based on these observations. Furthermore, the connectivity estimates can be used for neurofeedback applications or the instantaneous inspection of measurement results. In this study, we present the implementation and evaluation of online sensor and source space functional connectivity estimation in the open-source software MNE Scan. Online capable implementations of several functional connectivity metrics were established in the Connectivity library within MNE-CPP and made available as a plugin in MNE Scan. Online capability was achieved by enforcing multithreading and high efficiency for all computations, so that repeated computations were avoided wherever possible, which allows for a major speed-up in the case of overlapping intervals. We present comprehensive performance evaluations of these implementations proving the online capability for the computation of large all-to-all functional connectivity networks. As a proof of principle, we demonstrate the feasibility of online functional connectivity estimation in the evaluation of somatosensory evoked brain activity

Distractor effects in decision making are related to the individual’s style of integrating choice attributes

Humans make irrational decisions in the presence of irrelevant distractor options. There is little consensus on whether decision making is facilitated or impaired by the presence of a highly rewarding distractor, or whether the distractor effect operates at the level of options’ component attributes rather than at the level of their overall value. To reconcile different claims, we argue that it is important to consider the diversity of people’s styles of decision making and whether choice attributes are combined in an additive or multiplicative way. Employing a multi-laboratory dataset investigating the same experimental paradigm, we demonstrated that people used a mix of both approaches and the extent to which approach was used varied across individuals. Critically, we identified that this variability was correlated with the distractor effect during decision making. Individuals who tended to use a multiplicative approach to compute value, showed a positive distractor effect. In contrast, a negative distractor effect (divisive normalisation) was prominent in individuals tending towards an additive approach. Findings suggest that the distractor effect is related to how value is constructed, which in turn may be influenced by task and subject specificities. This concurs with recent behavioural and neuroscience findings that multiple distractor effects co-exist.

Abnormal resting-state functional connectivity of hippocampal subregions in type 2 diabetes mellitus-associated cognitive decline.

Type 2 diabetes mellitus (T2DM) over time predisposes to inflammatory responses and abnormalities in functional brain networks that damage learning, memory, or executive function. The hippocampus is a key region often reporting connectivity abnormalities in memory disorders. Here, we investigated peripheral inflammatory responses and resting-state functional connectivity (RSFC) changes characterized of hippocampal subregions in type 2 diabetes-associated cognitive decline (T2DACD). The study included 16 patients with T2DM, 16 patients with T2DACD and 25 healthy controls (HCs). Subjects were assessed for cognitive performance, tested for the expression of inflammatory factors IL-6, IL-10 and TNF-α in peripheral serum, underwent resting-state functional magnetic resonance imaging scans, and analyzed for RSFC using the hippocampal subregions as seeds. We also calculated the correlation between cognitive performance and RSFC of hippocampal subregion, and analyzed the significantly altered RSFC values of T2DACD for Receiver Operating Characteristic (ROC) analysis. T2DACD patients showed a decline in their ability to complete cognitive assessment scales and experimental paradigms, and T2DM did not show abnormal cognitive performance. IL-6 expression was increased in peripheral serum in both T2DACD and T2DM. Compared with HCs, T2DACD showed abnormalities RSFC of the left anterior hippocampus with left precentral gyrus and left angular gyrus. T2DM showed abnormalities RSFC of the left middle hippocampus with right medial frontal gyrus, right anterior and middle hippocampus with left precuneus, left anterior hippocampus with right precuneus and right posterior middle temporal gyrus. Compared with T2DM, T2DACD showed abnormalities RSFC of the left posterior hippocampus and right middle hippocampus with left precuneus. In addition, RSFC in the left posterior hippocampus with left precuneus of T2DACD was positively correlated with Flanker conflict response time (r=0.766, P=0.001). In the ROC analysis, the significantly altered RSFC values of T2DACD achieved significant performance. T2DACD showed a significant decrease in attentional inhibition and working memory, peripheral pro-inflammatory response increased, and abnormalities RSFC of the hippocampal subregions with default mode network and sensory-motor network. T2DM did not show a significant cognitive decline, but peripheral pro-inflammatory response increased and abnormalities RSFC of the hippocampus subregions occurred in the brain. In addition, the left precuneus may be a key brain region in the conversion of T2DM to T2DACD. The results of this study may provide a basis for the preliminary diagnosis of T2DACD.

The strategic allocation theory of vigilance.

Despite its importance in different occupational and everyday contexts, vigilance, typically defined as the capacity to sustain attention over time, is remarkably limited. What explains these limits? Two theories have been proposed. The Overload Theory states that being vigilant consumes limited information-processing resources; when depleted, task performance degrades. The Underload Theory states that motivation to perform vigilance tasks declines over time, thereby prompting attentional shifts and hindering performance. We highlight some conceptual and empirical problems for both theories and propose an alternative: the Strategic Allocation Theory. For the Strategic Allocation Theory, performance on vigilance tasks optimizes as a function of intrinsic and extrinsic motivations, including metacognitive factors such as the expected value of effort and the expected value of planning. Limited capacities must be deployed across task sets to maximize expected reward. The observed limits of vigilance reflect changes in the perceived value of, among other things, sustaining attention to a task rather than attending to something else. Drawing from recent computational theories of cognitive control and meta-reasoning, we argue that the Strategic Allocation Theory explains more phenomena related to vigilance behavior than other theories, including self-report data. Finally, we outline some of the testable predictions the theory makes across several experimental paradigms. This article is categorized under: Philosophy > Foundations of Cognitive Science Psychology > Attention.

Did H.M. exhibit accelerated long-term forgetting? Measuring forgetting in amnesia

The early investigations of patient H.M. inaugurated the modern era of memory research. During the 1970s and 1980s, a key debate over whether H.M. with bilateral medial temporal lobe lesions exhibited accelerated long-term forgetting attracted an increasing interest in forgetting research among amnestic patients. Huppert and Piercy (1979) examined H.M.’s performance in visual recognition at 10-minute, 1-day, and 7-day intervals and suggested that H.M. was subjected to rapid forgetting compared with Korsakoff patients and healthy participants reported in Huppert and Piercy (1978). In contrast, Freed et al. (1987) employed the same experimental paradigm and concluded that forgetting rates in H.M. did not differ from those in healthy controls. These incompatible findings highlighted a methodological challenge in measuring forgetting in the cross-group comparison design, where closely equalising the initial performance between patient and control groups is usually suggested. The re-analysis in this viewpoint, using both linear- and nonlinear-based modelling, reconciled the discrepancy between the aforementioned studies. Our results indicated that the rate of forgetting in H.M. did not differ from that in healthy controls, regardless of whether the initial performance was closely matched. Here, we suggest that the cross-group comparisons in forgetting studies do not necessarily seek a perfect match in initial performance unless the risks of confounding encoding and retrieval processes can be effectively controlled.

Head-orienting behaviors during simultaneous speech detection and localization.

Head movement plays a vital role in auditory processing by contributing to spatial awareness and the ability to identify and locate sound sources. Here we investigate head-orienting behaviors using a dual-task experimental paradigm to measure: (a) localization of a speech source; and (b) detection of meaningful speech (numbers), within a complex acoustic background. Ten younger adults with normal hearing and 20 older adults with mild-to-severe sensorineural hearing loss were evaluated in the free field on two head-movement conditions: (1) head fixed to the front and (2) head moving to a source location; and two context conditions: (1) with audio only or (2) with audio plus visual cues. Head-tracking analyses quantified the target location relative to head location, as well as the peak velocity during head movements. Evaluation of head-orienting behaviors revealed that both groups tended to undershoot the auditory target for targets beyond 60° in azimuth. Listeners with hearing loss had higher head-turn errors than the normal-hearing listeners, even when a visual location cue was provided. Digit detection accuracy was better for the normal-hearing than hearing-loss groups, with a main effect of signal-to-noise ratio (SNR). When performing the dual-task paradigm in the most difficult listening environments, participants consistently demonstrated a wait-and-listen head-movement strategy, characterized by a short pause during which they maintained their head orientation and gathered information before orienting to the target location.