EEG decoding of spoken words in bilingual listeners: from words to language invariant semantic-conceptual representations

Impaired Cortical Tracking of Speech in Children with Developmental Language Disorder

In developmental language disorder (DLD), learning to comprehend and express oneself with spoken language is impaired, but the reason for this remains unknown. Using millisecond-scale magnetoencephalography recordings combined with machine learning models, we investigated whether the possible neural basis of this disruption lies in poor cortical tracking of speech. The stimuli were common spoken Finnish words (e.g., dog, car, hammer) and sounds with corresponding meanings (e.g., dog bark, car engine, hammering). In both children with DLD (10 boys and 7 girls) and typically developing (TD) control children (14 boys and 3 girls), aged 10-15 years, the cortical activation to spoken words was best modeled as time-locked to the unfolding speech input at ∼100 ms latency between sound and cortical activation. Amplitude envelope (amplitude changes) and spectrogram (detailed time-varying spectral content) of the spoken words, but not other sounds, were very successfully decoded based on time-locked brain responses in bilateral temporal areas; based on the cortical responses, the models could tell at ∼75-85% accuracy which of the two sounds had been presented to the participant. However, the cortical representation of the amplitude envelope information was poorer in children with DLD compared with TD children at longer latencies (at ∼200-300 ms lag). We interpret this effect as reflecting poorer retention of acoustic-phonetic information in short-term memory. This impaired tracking could potentially affect the processing and learning of words as well as continuous speech. The present results offer an explanation for the problems in language comprehension and acquisition in DLD.

Decoding speech sounds from neurophysiological data: Practical considerations and theoretical implications

Machine learning techniques have proven to be a useful tool in cognitive neuroscience. However, their implementation in scalp-recorded electroencephalography (EEG) is relatively limited. To address this, we present three analyses using data from a previous study that examined event-related potential (ERP) responses to a wide range of naturally-produced speech sounds. First, we explore which features of the EEG signal best maximize machine learning accuracy for a voicing distinction, using a support vector machine (SVM). We manipulate three dimensions of the EEG signal as input to the SVM: number of trials averaged, number of time points averaged, and polynomial fit. We discuss the trade-offs in using different feature sets and offer some recommendations for researchers using machine learning. Next, we use SVMs to classify specific pairs of phonemes, finding that we can detect differences in the EEG signal that are not otherwise detectable using conventional ERP analyses. Finally, we characterize the timecourse of phonetic feature decoding across three phonological dimensions (voicing, manner of articulation, and place of articulation), and find that voicing and manner are decodable from neural activity, whereas place of articulation is not. This set of analyses addresses both practical considerations in the application of machine learning to EEG, particularly for speech studies, and also sheds light on current issues regarding the nature of perceptual representations of speech.

Proactive and reactive language control in bilingual language production revealed by decoding sustained potentials and electroencephalography oscillations

Adopting highly sensitive multivariate electroencephalography (EEG) and alpha-band decoding analyses, the present study investigated proactive and reactive language control during bilingual language production. In a language-switching task, Chinese-English bilinguals were asked to name pictures based on visually presented cues. EEG and alpha-band decoding accuracy associated with switch and non-switch trials were used as indicators for inhibition over the non-target language. Multivariate EEG decoding analyses showed that the decoding accuracy in L1 but not in L2, was above chance level shortly after cue onset. In addition, alpha-band decoding results showed that the decoding accuracy in L1 rose above chance level in an early time window and a late time window locked to the stimulus. Together, these asymmetric patterns of decoding accuracy indicate that both proactive and reactive attentional control over the dominant L1 are exerted during bilingual word production, with a possibility of overlap between two control mechanisms. We addressed theoretical implications based on these findings for bilingual language control models.

Artificial intelligence based multimodal language decoding from brain activity: A review

Decoding brain activity is conducive to the breakthrough of brain-computer interface (BCI) technology. The development of artificial intelligence (AI) continually promotes the progress of brain language decoding technology. Existent research has mainly focused on a single modality and paid insufficient attention to AI methods. Therefore, our objective is to provide an overview of relevant decoding research from the perspective of different modalities and methodologies. The modalities involve text, speech, image, and video, whereas the core method is using AI-built decoders to translate brain signals induced by multimodal stimuli into text or vocal language. The semantic information of brain activity can be successfully decoded into a language at various levels, ranging from words through sentences to discourses. However, the decoding effect is affected by various factors, such as the decoding model, vector representation model, and brain regions. Challenges and future directions are also discussed. The advances in brain language decoding and BCI technology will potentially assist patients with clinical aphasia in regaining the ability to communicate.

Examination of gaze behaviour in social anxiety disorder using a virtual reality eye-tracking paradigm: protocol for a casecontrol study

INTRODUCTION

Social anxiety disorder (SAD) has an early onset, a high lifetime prevalence, and may be a risk factor for developing other mental disorders. Gaze behaviour is considered an aberrant feature of SAD. Eye-tracking, a novel technology device, enables recording eye movements in real time, making it a direct and objective measure of gaze behaviour. Virtual reality (VR) is a promising tool for assessment and diagnostic purposes. Developing an objective screening tool based on examination of gaze behaviour in SAD may potentially aid early detection. The objective of this current study is, therefore to examine gaze behaviour in SAD utilising VR.

METHODS AND ANALYSIS

A case-control study design is employed in which a clinical sample of 29 individuals with SAD will be compared with a matched healthy control group of 29 individuals. In the VR-based eye-tracking paradigm, participants will be presented to stimuli consisting of high-res 360° 3D stereoscopic videos of three social-evaluative tasks designed to elicit social anxiety. The study will investigate between-group gaze behaviour differences during stimuli presentation.

ETHICS AND DISSEMINATION

The study has been approved by the National Committee on Health Research Ethics for the Capital Region of Denmark (H-22041443). The study has been preregistered on OSF registries: https://doi.org/10.17605/OSF.IO/XCTAKAll participants will be provided with written and oral information. Informed consent is required for all the participants. Participation is voluntarily, and the participants can at any time terminate their participation without any consequences. Study results; positive, negative or inconclusive will be published in relevant scientific journals.

The depth of semantic processing modulates cross-language pattern similarity in Chinese-English bilinguals

Previous studies have investigated factors related to the degree of cross-language overlap in brain activations in bilinguals/multilinguals. However, it is still unclear whether and how the depth of semantic processing (a critical task-related factor) affects the neural pattern similarity between native and second languages. To address this question, 26 Chinese-English bilinguals were scanned with fMRI while performing a word naming task (i.e., a task with shallow semantic processing) and a semantic judgment task (i.e., a task with deep semantic processing) in both native and second languages. Based on three sets of representational similarity analysis (whole brain, ROI-based, and within-language vs. cross-language semantic representation), we found that select regions in the reading brain network showed higher cross-language pattern similarity and higher cross-language semantic representations during deep semantic processing than during shallow semantic processing. These results suggest that compared to shallow semantic processing, deep semantic processing may lead to greater language-independent processing (i.e., cross-language semantic representation) and cross-language pattern similarity, and provide direct quantitative neuroimaging evidence for cognitive models of bilingual lexical memory.

Vulnerabilities in clinician-parent exchanges and the cascade of communication traps: a review

This review considers parent-clinician interactions that are associated with vulnerabilities in communication and what we refer to as 'communication traps'. Communication traps are defined by high-stress situations with affect-laden subject matter that can lead to progressively dysfunctional communications/exchanges that are avoidable. While this framework was developed in neonatology, it can be applied to other clinical practices.Communication competencies in paediatrics require the rapid development of a therapeutic alliance between parents and clinicians to ensure the provision of best care to their infants. In order to facilitate parent-clinician communication, our framework focuses clinicians' attention on the affective, behavioural and cognitive (ABC) cues that are indicative of real, apparent or potential communication traps. Strategies are provided to slow down clinicians' responses to more effectively consider ABC cues that suggest if patients/parents have failed to engage or disengage from a situation. This framework is illustrated by presenting a narrative synthesised from a number of experiences that clinicians have encountered. This review identifies key decision points in the communication process that, if left unaddressed, can cascade into communication traps which may be difficult to escape.Using results from communication studies and psychological research, our framework was developed to identify key decision points for ABC cues that can be used to prevent falling into communication traps.

Experiences and perception of character strengths among patients with breast cancer in China: a qualitative study

OBJECTIVE

To explore the patients' experiences on character strengths that Chinese patients experience after the diagnosis of breast cancer.

DESIGN

A qualitative, exploratory study using semistructured interviews based on the patients' lived experience after being diagnosed with breast cancer. Ethics approval was granted. Interviews were audiorecorded and transcribed verbatim. Values in Action Classification of Strengths provided conceptual framework for analysing strengths. Directed content analysis based on the classification of strengths and framework analysis were used to analyse transcribed data. The Standards for Reporting Qualitative Research guideline was followed.

SETTING

The Second Affiliated Hospital of Zhengzhou University and Henan Provincial Cancer Hospital in China.

PARTICIPANTS

Adult patients over 18 years, diagnosed with breast cancer between October 2019 and December 2020 were recruited. We used purposive sample method to collected data from 24 participants diagnosed with breast cancer.

RESULTS

Six themes (virtues) emerged from our analysis. In addition, two new subthemes (character strengths) emerged in this study, selflessness and pragmatism, respectively. Patients with breast cancer described a large repertoire of character strengths they used or wished for during survivorship, including gratitude, hope, humility, kindness, humour, honesty and forgiveness. Cultural values (eg, collectivism, familyism, Confucianism and Buddhist beliefs) helped structure the experiences of Chinese patients' character strengths. Patients wanted their character strengths to be more noticed, appreciated and encouraged by others and reported their psychological trajectory of using personal strengths.

CONCLUSION

The findings indicated that patients with breast cancer believing character strengths are important to them. Medical staff should pay more attention to motivating and cultivating character strengths of patients with breast cancer. Attention to make strength-based practices workable in clinical health promotion programmes is necessary. The healthcare system should develop tailored individualised psychological services that specifically address patients' needs for the application of personalised character strengths.

TRIAL REGISTRATION NUMBER

NCT04219267, Pre-results.

Association of objective and subjective socioeconomic markers with cognitive impairment among older adults: cross-sectional evidence from a developing country

OBJECTIVE

This study explored how various markers of objective and subjective socioeconomic status (SES) are associated with cognitive impairment among older Indian adults.

DESIGN

A cross-sectional study was conducted using large nationally representative survey data.

SETTING AND PARTICIPANT

This study used data from the Longitudinal Ageing Study in India (2017-2018). The sample included 31 464 older adults aged 60 years and above.

PRIMARY AND SECONDARY OUTCOME MEASURES

Outcome variable was cognitive impairment, measured through broad domains of memory, orientation, arithmetic function, and visuo-spatial and constructive skills. We estimated descriptive statistics and presented cross-tabulations of the outcome. Χ2 test was used to evaluate the significance level of differences in cognitive impairment by subjective (ladder) and objective SES measures (monthly per-capita consumption expenditure (MPCE) quintile, education and caste status). Multivariable linear and logistic regression analyses were conducted to fulfil the objectives.

RESULTS

A proportion of 41.7% and 43.4% of older adults belonged to low subjective (ladder) and objective (MPCE) SES, respectively. Older adults with low subjective (adjusted OR (aOR): 2.04; p<0.05) and objective SES (aOR: 1.32; p<0.05) had higher odds of having cognitive impairment in comparison with their counterparts, with a stronger subjective SES-cognitive impairment association. Older adults with lower education or belonged to lower caste had higher odds of cognitive impairment than their counterparts. Interaction analyses revealed that older adults who belonged to lower subjective and objective (poorest MPCE quintile, Scheduled Castes and lowest education) SES had 2.45 (CI: 1.77 to 3.39), 4.56 (CI: 2.97 to 6.98) and 54.41 (CI: 7.61 to 388.93) higher odds of cognitive impairment than those from higher subjective and objective SES, respectively.

CONCLUSION

Subjective measures of SES were linked to cognitive outcomes, even more strongly than objective measures of SES; considering the relative ease of obtaining such measures, subjective SES measures are a promising target for future study on socioeconomic indicators of cognitive impairment.

Neural decoding of semantic concepts: A systematic literature review

Objective Semantic concepts are coherent entities within our minds. They underpin our thought processes and are a part of the basis for our understanding of the world. Modern neuroscience research is increasingly exploring how individual semantic concepts are encoded within our brains and a number of studies are beginning to reveal key patterns of neural activity that underpin specific concepts. Building upon this basic understanding of the process of semantic neural encoding, neural engineers are beginning to explore tools and methods for semantic decoding: identifying which semantic concepts an individual is focused on at a given moment in time from recordings of their neural activity. In this paper we review the current literature on semantic neural decoding. Approach We conducted this review according to the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. Specifically, we assess the eligibility of published peer-reviewed reports via a search of PubMed and Google Scholar. We identify a total of 74 studies in which semantic neural decoding is used to attempt to identify individual semantic concepts from neural activity. Results Our review reveals how modern neuroscientific tools have been developed to allow decoding of individual concepts from a range of neuroimaging modalities. We discuss specific neuroimaging methods, experimental designs, and machine learning pipelines that are employed to aid the decoding of semantic concepts. We quantify the efficacy of semantic decoders by measuring information transfer rates. We also discuss current challenges presented by this research area and present some possible solutions. Finally, we discuss some possible emerging and speculative future directions for this research area. Significance Semantic decoding is a rapidly growing area of research. However, despite its increasingly widespread popularity and use in neuroscientific research this is the first literature review focusing on this topic across neuroimaging modalities and with a focus on quantifying the efficacy of semantic decoders.

A practical guide to applying machine learning to infant EEG data

Electroencephalography (EEG) has been widely adopted by the developmental cognitive neuroscience community, but the application of machine learning (ML) in this domain lags behind adult EEG studies. Applying ML to infant data is particularly challenging due to the low number of trials, low signal-to-noise ratio, high inter-subject variability, and high inter-trial variability. Here, we provide a step-by-step tutorial on how to apply ML to classify cognitive states in infants. We describe the type of brain attributes that are widely used for EEG classification and also introduce a Riemannian geometry based approach for deriving connectivity estimates that account for inter-trial and inter-subject variability. We present pipelines for learning classifiers using trials from a single infant and from multiple infants, and demonstrate the application of these pipelines on a standard infant EEG dataset of forty 12-month-old infants collected under an auditory oddball paradigm. While we classify perceptual states induced by frequent versus rare stimuli, the presented pipelines can be easily adapted for other experimental designs and stimuli using the associated code that we have made publicly available.

Group cognitive behavioural therapy with virtual reality exposure versus group cognitive behavioural therapy with in vivo exposure for social anxiety disorder and agoraphobia: a protocol for a randomised clinical trial

INTRODUCTION

Anxiety disorders have a high lifetime prevalence, early-onset and long duration or chronicity. Exposure therapy is considered one of the most effective elements in cognitive behavioural therapy (CBT) for anxiety, but in vivo exposure can be challenging to access and control, and is sometimes rejected by patients because they consider it too aversive. Virtual reality allows flexible and controlled exposure to challenging situations in an immersive and protected environment.

AIM

The SoREAL-trial aims to investigate the effect of group cognitive behavioural therapy (CBT-in vivo) versus group CBT with virtual reality exposure (CBT-in virtuo) for patients diagnosed with social anxiety disorder and/or agoraphobia, in mixed groups.

METHODS AND ANALYSIS

The design is an investigator-initiated randomised, assessor-blinded, parallel-group and superiority-designed clinical trial. Three hundred two patients diagnosed with social anxiety disorder and/or agoraphobia will be included from the regional mental health centres of Copenhagen and North Sealand and the Northern Region of Denmark. All patients will be offered a manual-based 14-week cognitive behavioural group treatment programme, including eight sessions with exposure therapy. Therapy groups will be centrally randomised with concealed allocation sequence to either CBT-in virtuo or CBT-in vivo. Patients will be assessed at baseline, post-treatment and 1-year follow-up by treatment blinded researchers and research assistants. The primary outcome will be diagnosis-specific symptoms measured with the Liebowitz Social Anxiety Scale for patients with social anxiety disorder and the Mobility Inventory for Agoraphobia for patients with agoraphobia. Secondary outcome measures will include depression symptoms, social functioning and patient satisfaction. Exploratory outcomes will be substance and alcohol use, working alliance and quality of life.

ETHICS AND DISSEMINATION

The trial has been approved by the research ethics committee in the Capital Region of Denmark. All results, positive, negative as well as inconclusive, will be published as quickly as possible and still in concordance with Danish law on the protection of confidentially and personal information. Results will be presented at national and international scientific conferences. The trial has obtained approval by the Regional Ethics Committee of Zealand (H-6-2013-015) and the Danish Data Protection Agency (RHP-2014-009-02670). The trial is registered at ClinicalTrial.gov as NCT03845101. The patients will receive information on the trial both verbally and in written form. Written informed consent will be obtained from each patient before inclusion in the trial. The consent form will be scanned and stored in the database system and the physical copy will be destroyed. It is emphasised that participation in the trial is voluntary and that the patient can withdraw his or her consent at any time without consequences for further and continued treatment.

TRIAL REGISTRATION NUMBER

NCT03845101.

Complex auditory musical hallucinations with ambivalent feelings

A 78-year-old woman with hypertension, diabetes mellitus type 2 and bilateral sensorineural hearing loss was referenced to geriatric psychiatry consultation. She presented cognitive dysfunction, erotomanic delusion and complex musical hallucinations (MH), described as hearing her neighbour singing a familiar church song along with bells in the background, making comments and talking to her. A computed tomography (CT) of the brain detected small right nucleocapsular and bilateral external capsules hypodensities of presumed vascular aetiology during hospitalisation. MH are a rare phenomenon with heterogeneous aetiology. Most frequently, the cause is hearing impairment; other causes include social isolation, cognitive dysfunction, vascular risk factors and medication. Studies suggest that some brain areas related to musical memory circuitry might be related and not fully mapped. Auditory verbal hallucinations with a voice that either comments, talks or sings to the patient have never been described in the literature, making this clinical case attractive.

Brain decoding in multiple languages: Can cross-language brain decoding work?

The approach of cross-language brain decoding is to use models of brain decoding from one language to decode stimuli of another language. It has the potential to provide new insights into how our brain represents multiple languages. While it is possible to decode semantic information across different languages from neuroimaging data, the approach's overall success remains to be tested and depends on a number of factors such as cross-language similarity, age of acquisition/proficiency levels, and depth of language processing. We expect to see continued progress in this domain, from a traditional focus on words and concrete concepts toward the use of naturalistic experimental tasks involving higher-level language processing (e.g., discourse processing). The approach can also be applied to understand how cross-modal, cross-cultural, and other nonlinguistic factors may influence neural representations of different languages. This article provides an overview of cross-language brain decoding with suggestions for future research directions.

Repetitive transcranial magnetic stimulation alone and in combination with motor control exercise for the treatment of individuals with chronic non-specific low back pain (ExTraStim trial): study protocol for a randomised controlled trial

INTRODUCTION

While multiple pharmacological and non-pharmacological interventions treating chronic non-specific low back pain (CLBP) are available, they have been shown to produce at best modest effects. Interventions such as repetitive transcranial magnetic stimulation (rTMS), a form of non-invasive brain stimulation, have exhibited promising results to alleviate chronic pain. However, evidence on the effectiveness of rTMS for CLBP is scarce due to limited rigorous clinical trials. Combining rTMS with motor control exercises (MCE) may help to address both central and nociceptive factors contributing to the persistence of LBP. The primary aim of this randomised controlled trial is to compare the effectiveness of a combination of rTMS and MCE to repeated rTMS sessions alone, sham rTMS and a combination of sham rTMS and MCE on pain intensity.

METHODS AND ANALYSIS

One hundred and forty participants (35/group) with CLBP will be randomised into four groups (active rTMS+MCE, sham rTMS+MCE, active rTMS and sham rTMS) to receive 10 sessions of their allocated intervention. The primary outcome will be the pain intensity, assessed at baseline, 4, 8, 12 and 24 weeks. Secondary outcomes will include disability, fear of movement, quality of life and patient global rating of change.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Comité d'éthique de la recherche sectoriel en réadaptation et intégration sociale, CIUSS de la Capitale Nationale in June 2019 (#2020-1844 - CER CIUSSS-CN). The results of the study will be submitted to a peer-reviewed journal and scientific meetings.

TRIAL REGISTRATION NUMBER

NCT04555278.

High-pass filtering artifacts in multivariate classification of neural time series data

BACKGROUND

Traditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown.

NEW METHOD

To prevent potential displacement effects, we extend an alternative method of removing slow drift noise - robust detrending - with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending.

RESULTS

In both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements.

COMPARISON WITH EXISTING METHOD(S)

Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial.

CONCLUSIONS

Decoding analyses benefit from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

Dynamic Time-Locking Mechanism in the Cortical Representation of Spoken Words

Human speech has a unique capacity to carry and communicate rich meanings. However, it is not known how the highly dynamic and variable perceptual signal is mapped to existing linguistic and semantic representations. In this novel approach, we used the natural acoustic variability of sounds and mapped them to magnetoencephalography (MEG) data using physiologically-inspired machine-learning models. We aimed at determining how well the models, differing in their representation of temporal information, serve to decode and reconstruct spoken words from MEG recordings in 16 healthy volunteers. We discovered that dynamic time-locking of the cortical activation to the unfolding speech input is crucial for the encoding of the acoustic-phonetic features of speech. In contrast, time-locking was not highlighted in cortical processing of non-speech environmental sounds that conveyed the same meanings as the spoken words, including human-made sounds with temporal modulation content similar to speech. The amplitude envelope of the spoken words was particularly well reconstructed based on cortical evoked responses. Our results indicate that speech is encoded cortically with especially high temporal fidelity. This speech tracking by evoked responses may partly reflect the same underlying neural mechanism as the frequently reported entrainment of the cortical oscillations to the amplitude envelope of speech. Furthermore, the phoneme content was reflected in cortical evoked responses simultaneously with the spectrotemporal features, pointing to an instantaneous transformation of the unfolding acoustic features into linguistic representations during speech processing.

Shared and modality-specific brain regions that mediate auditory and visual word comprehension

Visual speech carried by lip movements is an integral part of communication. Yet, it remains unclear in how far visual and acoustic speech comprehension are mediated by the same brain regions. Using multivariate classification of full-brain MEG data, we first probed where the brain represents acoustically and visually conveyed word identities. We then tested where these sensory-driven representations are predictive of participants' trial-wise comprehension. The comprehension-relevant representations of auditory and visual speech converged only in anterior angular and inferior frontal regions and were spatially dissociated from those representations that best reflected the sensory-driven word identity. These results provide a neural explanation for the behavioural dissociation of acoustic and visual speech comprehension and suggest that cerebral representations encoding word identities may be more modality-specific than often upheld.

Multivariate Pattern Analysis Techniques for Electroencephalography Data to Study Flanker Interference Effects

A central challenge in cognitive neuroscience is to understand the neural mechanisms that underlie the capacity to control our behavior according to internal goals. Flanker tasks, which require responding to stimuli surrounded by distracters that trigger incompatible action tendencies, are frequently used to measure this conflict. Even though the interference generated in these situations has been broadly studied, multivariate analysis techniques can shed new light into the underlying neural mechanisms. The current study is an initial approximation to adapt an interference Flanker paradigm embedded in a Demand-Selection Task (DST) to a format that allows measuring concurrent high-density electroencephalography (EEG). We used multivariate pattern analysis (MVPA) to decode conflict-related electrophysiological markers associated with congruent or incongruent target events in a time-frequency resolved way. Our results replicate findings obtained with other analysis approaches and offer new information regarding the dynamics of the underlying mechanisms, which show signs of reinstantiation. Our findings, some of which could not have been obtained with classic analytical strategies, open novel avenues of research.

False memory in nonhuman animals

This paper examines recent evidence from behavioral and neuroscience research with nonhuman animals that suggests the intriguing possibility that they, like their human counterparts, are vulnerable to creating false memories. Once considered a uniquely human memory phenomenon, the creation of false memories in lower animals can be seen especially readily in studies involving memory for source, or contextual attributes. Furthermore, evidence of "implanted" misinformation has also been obtained. Here, we review that research and consider its relevance to our empirical understanding of false memories, as well as speculate about its potential clinical implications for trauma memory.

Bipolar and psychotic disorders in elite athletes: a narrative review

Bipolar and psychotic disorders are relatively common and likely to have a significant impact on quality of life and functioning which, in the context of elite sport, includes a potential negative impact on sporting performance. For this narrative review article, the literature on bipolar and psychotic disorders in elite athletes was comprehensively searched, and little empirical research was found. A diagnosis of bipolar or psychotic disorders may be challenging in elite athletes because of complicating factors related to the modifying role of exercise and potential precipitating impact of substance use. Medications used to treat bipolar and psychotic disorders may have side effects particularly problematic for elite athletes. Future research should be tailored to the specific characteristics and needs of elite athletes and to the sporting context in which the disorders may arise. Specifically, further research is needed on the prevalence and incidence of these conditions in elite athletes and the impact of both the disorders and their treatments on sporting performance.

Electroencephalogram-Based Single-Trial Detection of Language Expectation Violations in Listening to Speech

We propose an approach for the detection of language expectation violations that occur in communication. We examined semantic and syntactic violations from electroencephalogram (EEG) when participants listened to spoken sentences. Previous studies have shown that such event-related potential (ERP) components as N400 and the late positivity (P600) are evoked in the auditory where semantic and syntactic anomalies occur. We used this knowledge to detect language expectation violation from single-trial EEGs by machine learning techniques. We recorded the brain activity of 18 participants while they listened to sentences that contained semantic and syntactic anomalies and identified the significant main effects of these anomalies in the ERP components. We also found that a multilayer perceptron achieved 59.5% (semantic) and 57.7% (syntactic) accuracies.

Physical separation from the mate diminishes male's attentiveness towards other females: a study in monogamous prairie voles Microtus ochrogaster

We tested whether continuous cohabitation in monogamous voles affects the mated male's attentiveness to his breeding partner versus another female. Each male was housed in a 3-chamber apparatus with a Focal female (FF) and a Control female (CF) for 13 days then placed in a T-maze to assess his attentiveness to and memory of those females. The Distal male remained physically separated from both females, but received their distal cues. The Separate male cohabited with the FF for 3 days then remained physically separated from both females. The Disrupt male's continuous cohabitation with the FF was disrupted by having him physically separated from her after 10 days and placed with the CF for the last 3 days. The Continuous male cohabited continuously with the FF for 13 days. With females in the T-maze, the Separate and Disrupt males spent more time near the FF's box and the Disrupt males spent more time manipulating the FF's box than the CF's box. The Separate males groomed themselves more when near the FF's box than the CF's box. The Distal and Continuous males' attentiveness to the two females did not differ. Results suggest that physical distance from the partner may reduce male's attentiveness toward other potential mates. Prairie voles might be similar to socially monogamous primates in using tactile cues as a signal for maintaining their social bonds.

Does exposure to simulated patient cases improve accuracy of clinicians' predictive value estimates of diagnostic test results? A within-subjects experiment at St Michael's Hospital, Toronto, Canada

OBJECTIVE

Clinicians often overestimate the probability of a disease given a positive test result (positive predictive value; PPV) and the probability of no disease given a negative test result (negative predictive value; NPV). The purpose of this study was to investigate whether experiencing simulated patient cases (ie, an 'experience format') would promote more accurate PPV and NPV estimates compared with a numerical format.

DESIGN

Participants were presented with information about three diagnostic tests for the same fictitious disease and were asked to estimate the PPV and NPV of each test. Tests varied with respect to sensitivity and specificity. Information about each test was presented once in the numerical format and once in the experience format. The study used a 2 (format: numerical vs experience) × 3 (diagnostic test: gold standard vs low sensitivity vs low specificity) within-subjects design.

SETTING

The study was completed online, via Qualtrics (Provo, Utah, USA).

PARTICIPANTS

50 physicians (12 clinicians and 38 residents) from the Department of Family and Community Medicine at St Michael's Hospital in Toronto, Canada, completed the study. All participants had completed at least 1 year of residency.

RESULTS

Estimation accuracy was quantified by the mean absolute error (MAE; absolute difference between estimate and true predictive value). PPV estimation errors were larger in the numerical format (MAE=32.6%, 95% CI 26.8% to 38.4%) compared with the experience format (MAE=15.9%, 95% CI 11.8% to 20.0%, d=0.697, P<0.001). Likewise, NPV estimation errors were larger in the numerical format (MAE=24.4%, 95% CI 14.5% to 34.3%) than in the experience format (MAE=11.0%, 95% CI 6.5% to 15.5%, d=0.303, P=0.015).

CONCLUSIONS

Exposure to simulated patient cases promotes accurate estimation of predictive values in clinicians. This finding carries implications for diagnostic training and practice.

Decoding semantic representations from functional near-infrared spectroscopy signals

This study uses representational similarity-based neural decoding to test whether semantic information elicited by words and pictures is encoded in functional near-infrared spectroscopy (fNIRS) data. In experiment 1, subjects passively viewed eight audiovisual word and picture stimuli for 15 min. Blood oxygen levels were measured using the Hitachi ETG-4000 fNIRS system with a posterior array over the occipital lobe and a left lateral array over the temporal lobe. Each participant's response patterns were abstracted to representational similarity space and compared to the group average (excluding that subject, i.e., leave-one-out cross-validation) and to a distributional model of semantic representation. Mean accuracy for both decoding tasks significantly exceeded chance. In experiment 2, we compared three group-level models by averaging the similarity structures from sets of eight participants in each group. In these models, the posterior array was accurately decoded by the semantic model, while the lateral array was accurately decoded in the between-groups comparison. Our findings indicate that semantic representations are encoded in the fNIRS data, preserved across subjects, and decodable by an extrinsic representational model. These results are the first attempt to link the functional response pattern measured by fNIRS to higher-level representations of how words are related to each other.

Decoding the neural representation of story meanings across languages

Drawing from a common lexicon of semantic units, humans fashion narratives whose meaning transcends that of their individual utterances. However, while brain regions that represent lower-level semantic units, such as words and sentences, have been identified, questions remain about the neural representation of narrative comprehension, which involves inferring cumulative meaning. To address these questions, we exposed English, Mandarin, and Farsi native speakers to native language translations of the same stories during fMRI scanning. Using a new technique in natural language processing, we calculated the distributed representations of these stories (capturing the meaning of the stories in high-dimensional semantic space), and demonstrate that using these representations we can identify the specific story a participant was reading from the neural data. Notably, this was possible even when the distributed representations were calculated using stories in a different language than the participant was reading. Our results reveal that identification relied on a collection of brain regions most prominently located in the default mode network. These results demonstrate that neuro-semantic encoding of narratives happens at levels higher than individual semantic units and that this encoding is systematic across both individuals and languages. Hum Brain Mapp 38:6096-6106, 2017. © 2017 Wiley Periodicals, Inc.

The neuro-cognitive representations of symbols: the case of concrete words

We live our lives surrounded by symbols (e.g., road signs, logos, but especially words and numbers), and throughout our life we use them to evoke, communicate and reflect upon ideas and things that are not currently present to our senses. Symbols are represented in our brains at different levels of complexity: at the first and most simple level, as physical entities, in the corresponding primary and secondary sensory cortices. The crucial property of symbols, however, is that, despite the simplicity of their surface forms, they have the power of evoking higher order multifaceted representations that are implemented in distributed neural networks spanning a large portion of the cortex. The rich internal states that reflect our knowledge of the meaning of symbols are what we call semantic representations. In this review paper, we summarize our current knowledge of both the cognitive and neural substrates of semantic representations, focusing on concrete words (i.e., nouns or verbs referring to concrete objects and actions), which, together with numbers, are the most-studied and well defined classes of symbols. Following a systematic descriptive approach, we will organize this literature review around two key questions: what is the content of semantic representations? And, how are semantic representations implemented in the brain, in terms of localization and dynamics? While highlighting the main current opposing perspectives on these topics, we propose that a fruitful way to make substantial progress in this domain would be to adopt a geometrical view of semantic representations as points in high dimensional space, and to operationally partition the space of concrete word meaning into motor-perceptual and conceptual dimensions. By giving concrete examples of the kinds of research that can be done within this perspective, we illustrate how we believe this framework will foster theoretical speculations as well as empirical research.

Unique and Overlapping Symptoms in Schizophrenia Spectrum and Dissociative Disorders in Relation to Models of Psychopathology: A Systematic Review

Schizophrenia spectrum disorders (SSDs) and dissociative disorders (DDs) are described in the fifth edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) and tenth edition of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) as 2 categorically distinct diagnostic categories. However, several studies indicate high levels of co-occurrence between these diagnostic groups, which might be explained by overlapping symptoms. The aim of this systematic review is to provide a comprehensive overview of the research concerning overlap and differences in symptoms between schizophrenia spectrum and DDs. For this purpose the PubMed, PsycINFO, and Web of Science databases were searched for relevant literature. The literature contained a large body of evidence showing the presence of symptoms of dissociation in SSDs. Although there are quantitative differences between diagnoses, overlapping symptoms are not limited to certain domains of dissociation, nor to nonpathological forms of dissociation. In addition, dissociation seems to be related to a history of trauma in SSDs, as is also seen in DDs. There is also evidence showing that positive and negative symptoms typically associated with schizophrenia may be present in DD. Implications of these results are discussed with regard to different models of psychopathology and clinical practice.

Semantic Structural Alignment of Neural Representational Spaces Enables Translation between English and Chinese Words

Two sets of items can share the same underlying conceptual structure, while appearing unrelated at a surface level. Humans excel at recognizing and using alignments between such underlying structures in many domains of cognition, most notably in analogical reasoning. Here we show that structural alignment reveals how different people's neural representations of word meaning are preserved across different languages, such that patterns of brain activation can be used to translate words from one language to another. Groups of Chinese and English speakers underwent fMRI scanning while reading words in their respective native languages. Simply by aligning structures representing the two groups' neural semantic spaces, we successfully infer all seven Chinese–English word translations. Beyond language translation, conceptual structural alignment underlies many aspects of high-level cognition, and this work opens the door to deriving many such alignments directly from neural representational content.

A multivariate method for estimating cross-frequency neuronal interactions and correcting linear mixing in MEG data, using canonical correlations

BACKGROUND

Cross-frequency interactions between distinct brain areas have been observed in connection with a variety of cognitive tasks. With electro- and magnetoencephalography (EEG/MEG) data, typical connectivity measures between two brain regions analyze a single quantity from each region within a specific frequency band; given the wideband nature of EEG/MEG signals, many statistical tests may be required to identify true coupling. Furthermore, because of the poor spatial resolution of activity reconstructed from EEG/MEG, some interactions may actually be due to the linear mixing of brain sources.

NEW METHOD

In the present work, a method for the detection of cross-frequency functional connectivity in MEG data using canonical correlation analysis (CCA) is described. We demonstrate that CCA identifies correlated signals and also the frequencies that cause the correlation. We also implement a procedure to deal with linear mixing based on symmetry properties of cross-covariance matrices.

RESULTS

Our tests with both simulated and real MEG data demonstrate that CCA is able to detect interacting locations and the frequencies that cause them, while accurately discarding spurious coupling.

COMPARISON WITH EXISTING METHODS

Recent techniques look at time delays in the activity between two locations to discard spurious interactions, while we propose a linear mixing model and demonstrate its relationship with symmetry aspects of cross-covariance matrices.

CONCLUSIONS

Our tests indicate the benefits of the CCA approach in connectivity studies, as it allows the simultaneous evaluation of several possible combinations of cross-frequency interactions in a single statistical test.

Decoding Articulatory Features from fMRI Responses in Dorsal Speech Regions

The brain's circuitry for perceiving and producing speech may show a notable level of overlap that is crucial for normal development and behavior. The extent to which sensorimotor integration plays a role in speech perception remains highly controversial, however. Methodological constraints related to experimental designs and analysis methods have so far prevented the disentanglement of neural responses to acoustic versus articulatory speech features. Using a passive listening paradigm and multivariate decoding of single-trial fMRI responses to spoken syllables, we investigated brain-based generalization of articulatory features (place and manner of articulation, and voicing) beyond their acoustic (surface) form in adult human listeners. For example, we trained a classifier to discriminate place of articulation within stop syllables (e.g., /pa/ vs /ta/) and tested whether this training generalizes to fricatives (e.g., /fa/ vs /sa/). This novel approach revealed generalization of place and manner of articulation at multiple cortical levels within the dorsal auditory pathway, including auditory, sensorimotor, motor, and somatosensory regions, suggesting the representation of sensorimotor information. Additionally, generalization of voicing included the right anterior superior temporal sulcus associated with the perception of human voices as well as somatosensory regions bilaterally. Our findings highlight the close connection between brain systems for speech perception and production, and in particular, indicate the availability of articulatory codes during passive speech perception.

SIGNIFICANCE STATEMENT

Sensorimotor integration is central to verbal communication and provides a link between auditory signals of speech perception and motor programs of speech production. It remains highly controversial, however, to what extent the brain's speech perception system actively uses articulatory (motor), in addition to acoustic/phonetic, representations. In this study, we examine the role of articulatory representations during passive listening using carefully controlled stimuli (spoken syllables) in combination with multivariate fMRI decoding. Our approach enabled us to disentangle brain responses to acoustic and articulatory speech properties. In particular, it revealed articulatory-specific brain responses of speech at multiple cortical levels, including auditory, sensorimotor, and motor regions, suggesting the representation of sensorimotor information during passive speech perception.

Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS

Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits.