Auditory Recognition Task Research Articles

Longstanding Auditory Sensory and Semantic Differences in Preterm Born Children

More than 10% of births are preterm, and the long-term consequences on sensory and semantic processing of non-linguistic information remain poorly understood. 17 very preterm-born children (born at < 33 weeks gestational age) and 15 full-term controls were tested at 10 years old with an auditory object recognition task, while 64-channel auditory evoked potentials (AEPs) were recorded. Sounds consisted of living (animal and human vocalizations) and manmade objects (e.g. household objects, instruments, and tools). Despite similar recognition behavior, AEPs strikingly differed between full-term and preterm children. Starting at 50ms post-stimulus onset, AEPs from preterm children differed topographically from their full-term counterparts. Over the 108-224ms post-stimulus period, full-term children showed stronger AEPs in response to living objects, whereas preterm born children showed the reverse pattern; i.e. stronger AEPs in response to manmade objects. Differential brain activity between semantic categories could reliably classify children according to their preterm status. Moreover, this opposing pattern of differential responses to semantic categories of sounds was also observed in source estimations within a network of occipital, temporal and frontal regions. This study highlights how early life experience in terms of preterm birth shapes sensory and object processing later on in life.

‘De-ethnicization’ in New Englishes: Perception and recognition of ethnicity in Namibian English

Do New Englishes develop ethnically neutral forms? This study showcases a combined perceptual and variationist approach to this question, using the case of Namibian English. It seeks to locate ‘de-ethnicized’ Namibian English varieties in mismatches between variety perception and auditory variety recognition, assessed via an experiment involving 244 young Namibian respondents. Namibian voices are used as playback material as part of an ethnic recognition task. These voices are selected from a sample of 94 ethnically diverse informants from both government and private schools in Namibia’s capital city following a phonetic characterization of all sampled individual varieties. While the respondents are sometimes unsure as to whether some specific Namibian ethnic groups speak a distinctive English variety, they generally endorse the notion that there is a ‘racial’ continuum of Namibian English varieties comprising ‘Black’, ‘White’, and ‘Coloured’ varieties. Meanwhile, vowel variation patterns among the informants, which I treat as a potential indicator of ethnoracial backgrounds, reveal an ethnoracially heterogenous variety cluster. This cluster is located in between a White cluster and a (mostly) Black cluster and displays combined Coloured, female, and private school associations. The auditory variety recognition task suggests that this cluster tends to be ethnically misrecognized by the respondents, as are women's voices in general, and non-White private school women's voices in particular. Still, the Black respondents largely recognize the Black informants’ voices as Black, irrespective of these voices’ ethnic background. The findings offer joint variationist and perceptual suggestions that Non-White women are gradually de-ethnicizing Namibian English across social classes. This trend possibly results in Black and Coloured varieties amalgamating into a local high-status English variety.

Demonstration of intrinsic STDP learning capability in all-2D multi-state MoS2 memory and its application in modelling neuromorphic speech recognition

The human brain can be characterized by its large number of adaptive synapses, connecting billions of neurons capable of both learning and perceiving the environment. Neuromorphic computing, based on brain-inspired principles, is a promising technology, to build low-power, distributed, fault-tolerant intelligent systems mainly for perception tasks. Here, we demonstrate the intrinsic capability of floating gate (FG) MoS2 device (MoS2 FG-FET) to model the spike time dependent plasticity (STDP) learning rule that is based on the transient response of the MoS2 channel to spikes applied to the source and gate leads. We implemented the STDP learning protocol in a neuromorphic speech recognition system (NSRS), inspired by the human auditory pathway, for various auditory recognition tasks. Our proposed NSRS consists of a cochlea model, an unsupervised feature learning stage, and a simple linear classifier. The unsupervised learning stage uses the biologically plausible STDP learning in novel two-dimensional MoS2 FG-FET memory which circumvents the requirement of any other learning circuitry. Demonstration of STDP modelling in two-dimensional (2D) MoS2 is an important step towards incorporating 2D architectures for reduced device footprints in neuromorphic learning circuits.

Is Oral Bilingualism an Advantage for Word Learning in Children With Hearing Loss?

Purpose The purpose of this study was to examine whether oral bilingualism could be an advantage for children with hearing loss when learning new words. Method Twenty monolingual and 13 bilingual children with hearing loss were compared with each other and with 20 monolingual and 20 bilingual children with normal hearing on receptive vocabulary and on three word-learning tasks containing nonsense words in familiar (English and Spanish) and unfamiliar (Arabic) languages. We measured word learning on the day of the training and retention the next day using an auditory recognition task. Analyses of covariance were used to compare performance on the word learning tasks by language group (monolingual vs. bilingual) and hearing status (normal hearing vs. hearing loss), controlling for age and maternal education. Results No significant differences were observed between monolingual and bilingual children with and without hearing loss in any of the word-learning task. Children with hearing loss performed more poorly than their hearing peers in Spanish word retention and Arabic word learning and retention. Conclusions Children with hearing loss who grew up being exposed to Spanish did not show higher or lower word-learning abilities than monolingual children with hearing loss exposed to English only. Therefore, oral bilingualism was neither an advantage nor a disadvantage for word learning. Hearing loss negatively affected performance in monolingual and bilingual children when learning words in languages other than English (the dominant language). Monolingual and bilingual children with hearing loss are equally at risk for word-learning difficulties and vocabulary size matters for word learning.

Word and Nonword Reading Efficiency in Postlingually Deafened Adult Cochlear Implant Users.

This study tested the hypotheses that 1) experienced adult cochlear implants (CI) users demonstrate poorer reading efficiency relative to normal-hearing controls, 2) reading efficiency reflects basic, underlying neurocognitive skills, and 3) reading efficiency relates to speech recognition outcomes in CI users. Weak phonological processing skills have been associated with poor speech recognition outcomes in postlingually deaf adult CI users. Phonological processing can be captured in nonauditory measures of reading efficiency, which may have wide use in patients with hearing loss. This study examined reading efficiency in adults CI users, and its relation to speech recognition outcomes. Forty-eight experienced, postlingually deaf adult CI users (ECIs) and 43 older age-matched peers with age-normal hearing (ONHs) completed the Test of Word Reading Efficiency (TOWRE-2), which measures word and nonword reading efficiency. Participants also completed a battery of nonauditory neurocognitive measures and auditory sentence recognition tasks. ECIs and ONHs did not differ in word (ECIs: M = 78.2, SD = 11.4; ONHs: M = 83.3, SD = 10.2) or nonword reading efficiency (ECIs: M = 42.0, SD = 11.2; ONHs: M = 43.7, SD = 10.3). For ECIs, both scores were related to untimed word reading with moderate to strong effect sizes (r = 0.43-0.69), but demonstrated differing relations with other nonauditory neurocognitive measures with weak to moderate effect sizes (word: r = 0.11-0.44; nonword: r = (-)0.15 to (-)0.42). Word reading efficiency was moderately related to sentence recognition outcomes in ECIs (r = 0.36-0.40). Findings suggest that postlingually deaf adult CI users demonstrate neither impaired word nor nonword reading efficiency, and these measures reflect different underlying mechanisms involved in language processing. The relation between sentence recognition and word reading efficiency, a measure of lexical access speed, suggests that this measure may be useful for explaining outcome variability in adult CI users.

Test–retest reliability of RC21X: a web-based cognitive and neuromotor performance measurement tool

As computerized cognitive testing becomes increasingly popular in clinical and research settings, conducting studies on efficacy and psychometric properties is essential. One such program is RC21X, a web-based brain performance measurement tool. Based on empirically supported neurocognitive and neuromotor tasks, the 12-min test consists of 15 modules measuring memory, motor coordination, processing speed, and executive functioning. Because individuals may use RC21X repeatedly to track changes in cognitive performance, establishing reliability of the program is imperative. The current study examined test-retest reliability of RC21X within a 2-week period. The sample consisted of 222 individuals: 192 (86.5%) were male, and 30 (13.5%) were female. Average age was 44.06years (SD=17.76), with ages ranging from 7 to 82years. We computed Pearson's correlation coefficients for module and composite scores to determine reliability between performance at times 1 and 2. All correlations were statistically significant (p<.001). The 2-week test-retest reliability for composite score was 0.72, with subtest coefficients ranging from 0.54 on an auditory memory recognition task to 0.89 on a finger tapping task. We replicated these analyses with participants' (n=43) test sessions 3 and 4; we found similar results to those from test 1 and test 2 analyses, suggesting stability of results over multiple administrations. Results for RC21X were comparable to existing literature that supports moderate to high reliability of other computer-based tests. Although future research needs to investigate validity of RC21X, our findings support potential applications in research, clinical use, and personal brain performance measurement.

Auditory hallucinations, top-down processing and language perception: a general population study.

Studies investigating the underlying mechanisms of hallucinations in patients with schizophrenia suggest that an imbalance in top-down expectations v. bottom-up processing underlies these errors in perception. This study evaluates this hypothesis by testing if individuals drawn from the general population who have had auditory hallucinations (AH) have more misperceptions in auditory language perception than those who have never hallucinated. We used an online survey to determine the presence of hallucinations. Participants filled out the Questionnaire for Psychotic Experiences and participated in an auditory verbal recognition task to assess both correct perceptions (hits) and misperceptions (false alarms). A hearing test was performed to screen for hearing problems. A total of 5115 individuals from the general Dutch population participated in this study. Participants who reported AH in the week preceding the test had a higher false alarm rate in their auditory perception compared with those without such (recent) experiences. The more recent the AH were experienced, the more mistakes participants made. While the presence of verbal AH (AVH) was predictive for false alarm rate in auditory language perception, the presence of non-verbal or visual hallucinations were not. The presence of AVH predicted false alarm rate in auditory language perception, whereas the presence of non-verbal auditory or visual hallucinations was not, suggesting that enhanced top-down processing does not transfer across modalities. More false alarms were observed in participants who reported more recent AVHs. This is in line with models of enhanced influence of top-down expectations in persons who hallucinate.

Multiple exemplar instruction and integration of listening and speaking behaviors with substantive-adjective syntactic units in children with ANSD and CI.

To verify the effect of the multiple exemplar instruction at the acquisition and integration of listening and speaking behaviors, with substantives and substantive-adjective combinations, in children with Auditory Neuropathy Spectrum Disorder (ANSD) and cochlear implant (CI). Participants were two children with ANSD that were users of CI. We adopted dictated stimulus and pictures that corresponded to words (substantive) and substantive-adjective syntactic units. The study was arranged in teaching steps that were intercalated with listening and speaking behaviors probes, with all stimuli. The multiple exemplar instruction presented oral imitation (echoic), auditory recognition (listening) and pictures naming (touch) tasks, on a rotating way; the substantives were taught first and, after that, the substantive-adjective combinations. In the pre-test, the participants showed variability and discrepancy in the correct responses percentages of listening and speaking. All achieved firstly 100% correct responses in the listening task and the speaking performances were close to listening after the teaching. All extended substantive learning to substantive-adjective syntactic units. Children with ANSD and CI can learn and integrate listening and speaking behaviors by multiple exemplar instruction, from words to syntactic units.

An emotion recognition subtyping approach to studying the heterogeneity and comorbidity of autism spectrum disorders and attention-deficit/hyperactivity disorder

BackgroundEmotion recognition dysfunction has been reported in both autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). This suggests that emotion recognition is a cross-disorder trait that may be utilised to understand the heterogeneous psychopathology of ASD and ADHD. We aimed to identify emotion recognition subtypes and to examine their relation with quantitative and diagnostic measures of ASD and ADHD to gain further insight into disorder comorbidity and heterogeneity.MethodsFactor mixture modelling was used on speed and accuracy measures of auditory and visual emotion recognition tasks. These were administered to children and adolescents with ASD (N = 89), comorbid ASD + ADHD (N = 64), their unaffected siblings (N = 122), ADHD (N = 111), their unaffected siblings (N = 69), and controls (N = 220). Identified classes were compared on diagnostic and quantitative symptom measures.ResultsA four-class solution was revealed, with the following emotion recognition abilities: (1) average visual, impulsive auditory; (2) average-strong visual and auditory; (3) impulsive/imprecise visual, average auditory; (4) weak visual and auditory. The weakest performing class (4) contained the highest percentage of patients (66.07%) and the lowest percentage controls (10.09%), scoring the highest on ASD/ADHD measures. The best performing class (2) demonstrated the opposite: 48.98% patients, 15.26% controls with relatively low scores on ASD/ADHD measures.ConclusionsSubgroups of youths can be identified that differ both in quantitative and qualitative aspects of emotion recognition abilities. Weak emotion recognition abilities across sensory domains are linked to an increased risk for ASD as well as ADHD, although emotion recognition impairments alone are neither necessary nor sufficient parts of these disorders.

Predictive modeling for odor character of a chemical using machine learning combined with natural language processing.

Recent studies on machine learning technology have reported successful performances in some visual and auditory recognition tasks, while little has been reported in the field of olfaction. In this paper we report computational methods to predict the odor impression of a chemical from its physicochemical properties. Our predictive model utilizes nonlinear dimensionality reduction on mass spectra data and performs the clustering of descriptors by natural language processing. Sensory evaluation is widely used to measure human impressions to smell or taste by using verbal descriptors, such as “spicy” and “sweet”. However, as it requires significant amounts of time and human resources, a large-scale sensory evaluation test is difficult to perform. Our model successfully predicts a group of descriptors for a target chemical through a series of computer simulations. Although the training text data used in the language modeling is not specialized for olfaction, the experimental results show that our method is useful for analyzing sensory datasets. This is the first report to combine machine olfaction with natural language processing for odor character prediction.

Locus coeruleus activation accelerates perceptual learning

Neural representations of the external world are constructed and updated in a manner that depends on behavioral context. For neocortical networks, this contextual information is relayed by a diverse range of neuromodulatory systems, which govern attention and signal the value of internal state variables such as arousal, motivation, and stress. Neuromodulators enable cortical circuits to differentially process specific stimuli and modify synaptic strengths in order to maintain short- or long-term memory traces of significant perceptual events and behavioral episodes. One of the most important subcortical neuromodulatory systems for attention and arousal is the noradrenergic locus coeruleus. Here we report that the noradrenergic system can enhance behavior in rats performing a self-initiated auditory recognition task, and optogenetic stimulation of noradrenergic locus coeruleus neurons accelerated the rate at which trained rats began correctly responding to a change in reward contingency. Animals successively progressed through distinct behavioral epochs, including periods of perseverance and exploration that occurred much more rapidly when animals received locus coeruleus stimulation. In parallel, we made recordings from primary auditory cortex and found that pairing tones with locus coeruleus stimulation led to a similar set of changes to cortical tuning profiles. Thus both behavioral and neural responses go through phases of adjustment for exploring and exploiting environmental reward contingencies. Furthermore, behavioral engagement does not necessarily recruit optimal locus coeruleus activity.

Does phonological overlap of cognate words modulate cognate acquisition and processing in developing and skilled readers?

ABSTRACTVery few studies exist on the role of cross-language similarities in cognate word acquisition. Here we sought to explore, for the first time, the interplay of orthography (O) and phonology (P) during the early stages of cognate word acquisition, looking at children and adults with the same level of foreign language proficiency and by using two variants of the word-association learning paradigm (auditory learning method vs. auditory + written method). Eighty participants (40 children and 40 adults, native speakers of European Portuguese [EP]), learned a set of EP-Catalan cognate words and noncognate words. Among the cognate words, the degree of orthographic and phonological similarity was manipulated. Half of the children and adult participants learned the new words via an L2 auditory and written-L1 word association method, while the other half learned the same words only through an L2 auditory-L1 word association method. Both groups were tested in an auditory recognition task and a go/no-go lexical decision task. Results revealed a disadvantage for children in comparison to adults, which was reduced in the auditory learning method. Furthermore, there was an advantage for cognates relative to noncognates regardless of the age of participants. Importantly, there were modulations in cognate word processing as a function of the degree of O and P overlap that were restricted to children. The findings are discussed in light of the most relevant bilingual models of word recognition.

Deep Learning in Medical Imaging: General Overview.

The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.

Limitations of episodic memory for highly similar auditory stimuli

ABSTRACTTwo experiments investigated participants’ recognition memory for word content, while varying vocal characteristics, and for vocal characteristics alone. In Experiment 1, participants performed an auditory recognition task in which they identified whether a spoken word was “new”, “old” (repeated word, repeated voice), or “similar” (repeated word, new voice). Results showed that word recognition accuracy was lower for similar trials than old trials. In Experiment 2, participants performed an auditory recognition task in which they identified whether or not a phrase was spoken in an old or new voice, with repetitions occurring after a variable number of intervening stimuli. Results showed that recognition accuracy was lower when old voices spoke an alternate message than a repeated message and accuracy decreased as a function of number of intervening items. Overall, the results suggest that speech recognition is better for lexical content than vocal characteristics alone.

ID 88 – Anterior thalamus in cognition: An intracerebral recording study

Objective To study the involvement of the anterior thalamic nuclei (ANT) in the cognitive processes. Methods We recorded the event-related potentials (ERPs) by visual and auditory memory encoding-recognition tasks by intracerebral recordings in patients with pharmacoresistent epilepsy who underwent the deep brain stimulation (DBS) surgery of the anterior thalamic nuclei with depth electrodes implanted bilaterally in the ANT. We compared the results with epilepsy-surgery candidates with depth electrodes implanted bilaterally in the hippocampus. Results In the ANT we recorded ERPs during the visual encoding and visual and auditory recognition tasks. No significant ERPs were recorded during the encoding phase by auditory stimuli in ANT. In hippocampus ERPs were recorded by visual and auditory memory encoding and recognition tasks. In the recognition tasks (visual and auditory) the ERPs in ANT preceded the ERPs in hippocampus. Conclusions ERPs are elicited by visual memory encoding and recognition, as well as by auditory recognition memory processes, but not by encoding auditory memory processing in the ANT. The ANT precedes the hippocampus in the memory recognition pathway. Key message ANT has a specific role in the memory processes, especially the memory recognition.

Auditory tasks for assessment of sensory function and affective prosody in schizophrenia

Schizophrenia patients exhibit impairments in auditory-based social cognition, indicated by deficits in detection of prosody, such as affective prosody and basic pitch perception. However, little is known about the psychometric properties of behavioral tests used to assess these functions. The goal of this paper is to characterize the properties of prosody and pitch perception tasks and to investigate whether they can be shortened. The pitch perception test evaluated is a tone-matching task developed by Javitt and colleagues (J-TMT). The prosody test evaluated is the auditory emotion recognition task developed by Juslin and Laukka (JL-AER). The sample includes 124 schizophrenia patients (SZ) and 131 healthy controls (HC). Properties, including facility and discrimination, of each item were assessed. Effects of item characteristics (e.g., emotion) were also evaluated. Shortened versions of the tests are proposed based on facility, discrimination, and/or ability of item characteristics to discriminate between patients and controls. Test–retest reliability is high for patients and controls for both the original and short forms of the J-TMT and JL-AER. Thus, the original as well as short forms of the J-TMT and JL-AER are suggested for inclusion in clinical trials of social cognitive and perceptual treatments. The development of short forms further increases the utility of these auditory tasks in clinical trials and clinical practice. The large SZ vs. HC differences reported here also highlight the profound nature of auditory deficits and a need for remediation.

A hierarchical model of vision (HMAX) can also recognize speech

HMAX is a well-known computational model of visual recognition in cortex consisting of just two computational operations – a “template match” and non-linear pooling – alternating in a feedforward hierarchy in which receptive fields exhibit increasing specificity and invariance [1]. Interestingly, auditory recognition problems (such as speech recognition) share similar computational requirements, and recent work in auditory neuroscience suggests that auditory and visual cortex share similar anatomical and functional organization. Based on these similarities, we tested whether HMAX could support an auditory recognition task (specifically, word spotting). To test HMAX on word spotting, recorded speech samples from the TIMIT corpus [2] were first converted into time-frequency spectrograms using a computational model of the auditory periphery [3]. These spectrograms were then split into 750 ms frames and input to a standard HMAX model [4]. Based on observed similarities between the receptive fields in primary auditory cortex (spectro-temporal receptive fields, or STRFs) and primary visual cortex (typically modeled as oriented Gabor filters), we used S1 filters identical to those used in vision [4]. Similarly, S2 “patches” were randomly selected from C1 representations of speech sounds drawn from an independent speech corpus. One vs. all linear support vector machines (SVMs) were then trained to discriminate frames that contain a target word from those that did not. These SVMs were then tested on a novel set of test sentences using a sliding frame approach (750 ms frame size, 20 ms step size). For each frame in a sentence, the SVM produced a distance from the hyperplane, and a threshold value was applied to produce a binary classification whether or not the target word was present in the sentence. When tested on target words that appeared in a fixed context (i.e. SA sentences in TIMIT), performance was highly robust, with ROC areas consistently above 0.9. When tested on target words that appeared in variable contexts (i.e., SI sentences in TIMIT), performance was somewhat decreased with ROC areas around 0.8. This decrease in performance is likely due to the inclusion of “clutter” (i.e., target irrelevant features) within the frame, also commonly observed when HMAX is applied to visual object recognition tasks [1]. These results are novel in that they provide support for the hypothesis that the simple computational framework implemented in HMAX – consisting of a feedforward hierarchy of only two alternating computational operations – may generalize beyond vision to support auditory recognition as well. It is possible that such a representation could give rise to stable neural encodings that are invariant to behaviorally irrelevant characteristics as seen in higher order visual and auditory cortices [5,6]. While it is likely that this auditory version of the HMAX model would benefit from the use of more auditory-specific filters based on STRF models [7], the Gabor features used here are largely compatible with previous computational models based on STRFs up to the level of primary auditory cortex [8]. Additional benefit may also be gained by learning sparse representations from natural sounds, at both the S1 and S2 levels [9].

Function determines structure in complex neural networks.

In the course of our daily lives, we rely on our ability to quickly recognize visual objects despite variations in the viewing angle or lighting conditions (1). Most of the time, this process occurs so naturally that it is easy to underestimate the computational challenge it poses. In fact, as much as one third of our cortex is involved in visual object recognition (2). Thus far, we have not been able to create artificial object recognition systems that can match the performance of the human visual system, especially when one takes into account the energetic constraints. However, understanding the principles of visual object recognition has major implications not only because of potential wide-ranging practical applications but also because these principles are likely to hold clues to how sensory systems work in general. After all, there is a growing body of experimental and computational evidence that similar principles (3) might be at work during visual, auditory, or olfactory object recognition tasks. In PNAS, Yamins et al. present an important advance in this research direction by demonstrating how to optimize artificial networks to match the discrimination ability of primates when it comes to categorizing objects (4). Importantly, optimized networks share many features with the corresponding networks in the brain. Thus, although the structure of neural networks in the brain could have been largely determined by the idiosyncrasies of the previous evolutionary trajectory, they seem to reflect instead a unique optimal solution. This in turn offers more support for theoretical and computational pursuits to find optimal circuit organization in the brain (5).

Active recognition enhances the representation of behaviorally relevant information in single auditory forebrain neurons

Sensory systems are dynamic. They must process a wide range of natural signals that facilitate adaptive behaviors in a manner that depends on an organism's constantly changing goals. A full understanding of the sensory physiology that underlies adaptive natural behaviors must therefore account for the activity of sensory systems in light of these behavioral goals. Here we present a novel technique that combines in vivo electrophysiological recording from awake, freely moving songbirds with operant conditioning techniques that allow control over birds' recognition of conspecific song, a widespread natural behavior in songbirds. We show that engaging in a vocal recognition task alters the response properties of neurons in the caudal mesopallium (CM), an avian analog of mammalian auditory cortex, in European starlings. Compared with awake, passive listening, active engagement of subjects in an auditory recognition task results in neurons responding to fewer song stimuli and a decrease in the trial-to-trial variability in their driven firing rates. Mean firing rates also change during active recognition, but not uniformly. Relative to nonengaged listening, active recognition causes increases in the driven firing rates in some neurons, decreases in other neurons, and stimulus-specific changes in other neurons. These changes lead to both an increase in stimulus selectivity and an increase in the information conveyed by the neurons about the animals' behavioral task. This study demonstrates the behavioral dependence of neural responses in the avian auditory forebrain and introduces the starling as a model for real-time monitoring of task-related neural processing of complex auditory objects.

Children's recognition of emotions from vocal cues

Emotional cues contain important information about the intentions and feelings of others. Despite a wealth of research into children's understanding of facial signals of emotions, little research has investigated the developmental trajectory of interpreting affective cues in the voice. In this study, 48 children ranging between 5 and 10 years were tested using forced-choice tasks with non-verbal vocalizations and emotionally inflected speech expressing different positive, neutral and negative states. Children as young as 5 years were proficient in interpreting a range of emotional cues from vocal signals. Consistent with previous work, performance was found to improve with age. Furthermore, the two tasks, examining recognition of non-verbal vocalizations and emotionally inflected speech, respectively, were sensitive to individual differences, with high correspondence of performance across the tasks. From this demonstration of children's ability to recognize emotions from vocal stimuli, we also conclude that this auditory emotion recognition task is suitable for a wide age range of children, providing a novel, empirical way to investigate children's affect recognition skills.