On Performance and Perceived Effort in Trail Runners Using Sensor Control to Generate Biosynchronous Music.

Music has been shown to be capable of improving runners' performance in treadmill and laboratory-based experiments. This paper evaluates a generative music system, namely HEARTBEATS, designed to create biosignal synchronous music in real-time according to an individual athlete's heartrate or cadence (steps per minute). The tempo, melody, and timbral features of the generated music are modulated according to biosensor input from each runner using a combination of PPG (Photoplethysmography) and GPS (Global Positioning System) from a wearable sensor, synchronized via Bluetooth. We compare the relative performance of athletes listening to music with heartrate and cadence synchronous tempos, across a randomized trial (N = 54) on a trail course with 76 ft of elevation. Participants were instructed to continue until their self-reported perceived effort went beyond an 18 using the Borg rating of perceived exertion. We found that cadence-synchronous music improved performance and decreased perceived effort in male runners. For female runners, cadence synchronous music improved performance but it was heartrate synchronous music which significantly reduced perceived effort and allowed them to run the longest of all groups tested. This work has implications for the future design and implementation of novel portable music systems and in music-assisted coaching.

Music-induced emotions can be predicted from a combination of brain activity and acoustic features.

It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music. We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to r=0.234,p<0.001. This regression fit suggests that over 20% of the variance of the participant's music induced emotions can be predicted by their neural activity and the properties of the music. Given the large amount of noise, non-stationarity, and non-linearity in both EEG and music, this is an encouraging result. Additionally, the combination of measures of brain activity and acoustic features describing the music played to our participants allows us to predict music-induced emotions with significantly higher accuracies than either feature type alone (p<0.01).

Laser-Assisted In Situ Keratomileusis Surgery on a Patient with Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease or Neuromyelitis Optica Spectrum Disorder.

Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) and neuromyelitis optica spectrum disorder (NMOSD) are rare central demyelinating diseases that may affect refractive surgery outcomes. Optic neuritis and brainstem syndromes affecting cranial nerves are particularly relevant to corneal refractive surgery (CRS), such as laser-assisted in situ keratomileusis (LASIK), photorefractive keratectomy, or small incision lenticule extraction. There is currently no existing literature concerning the outcomes of CRS in patients with MOGAD or NMOSD. This article reports the clinical outcome of a MOGAD patient who underwent LASIK.

Successful management of a large air embolus during an extended right hepatectomy with an emergency cardiopulmonary bypass.

BACKGROUND: An air embolus is a recognized but rare complication of a partial hepatectomy. The aim of this report was to describe the diagnosis and management of a large paradoxical air embolus during hepatic resection. METHODS: Case report. RESULTS: A single patient report of a massive paradoxical air embolus during an extended right hepatectomy is described. The diagnosis was confirmed by trans-oesophageal echo (video provided). After failed conservative management an emergency cardiopulmonary bypass was instituted with a successful outcome. CONCLUSION: Surgeons and anaesthetists involved in hepatic surgery should be aware of signs, investigations and management of this life-threatening intra-operative complication.

Potential Risks of Corneal Refractive Surgery in Patients with Ectodermal Dysplasia.

Ectodermal dysplasia (ED) involves the aberrant development of at least two ectodermal derivatives, such as skin, teeth, hair, sweat glands, and ocular tissue. The group of over 200 conditions is commonly classified into two major types: hypohidrotic/anhidrotic ED, in which sweat glands are either absent or significantly reduced, and hidrotic ED, in which sweat glands are normal. Ocular manifestations pertinent to patients undergoing corneal vision correction surgery include multifaceted dry eye syndrome, corneal pathology, such as recurrent erosions, scars, neovascularization, and limbal stem cell deficiency, and early-onset cataracts and glaucoma. In this article we discuss the current understanding of ED and offer factors to consider when these patients are seeking corneal refractive surgery.

Sonic enhancement of virtual exhibits.

Museums have widely embraced virtual exhibits. However, relatively little attention is paid to how sound may create a more engaging experience for audiences. To begin addressing this lacuna, we conducted an online experiment to explore how sound influences the interest level, emotional response, and engagement of individuals who view objects within a virtual exhibit. As part of this experiment, we designed a set of different soundscapes, which we presented to participants who viewed museum objects virtually. We then asked participants to report their felt affect and level of engagement with the exhibits. Our results show that soundscapes customized to exhibited objects significantly enhance audience engagement. We also found that more engaged audience members were more likely to want to learn additional information about the object(s) they viewed and to continue viewing these objects for longer periods of time. Taken together, our findings suggest that virtual museum exhibits can improve visitor engagement through forms of customized soundscape design.

Human-centred mechanism design with Democratic AI.

Building artificial intelligence (AI) that aligns with human values is an unsolved problem. Here we developed a human-in-the-loop research pipeline called Democratic AI, in which reinforcement learning is used to design a social mechanism that humans prefer by majority. A large group of humans played an online investment game that involved deciding whether to keep a monetary endowment or to share it with others for collective benefit. Shared revenue was returned to players under two different redistribution mechanisms, one designed by the AI and the other by humans. The AI discovered a mechanism that redressed initial wealth imbalance, sanctioned free riders and successfully won the majority vote. By optimizing for human preferences, Democratic AI offers a proof of concept for value-aligned policy innovation.

On the use of AI for Generation of Functional Music to Improve Mental Health.

Increasingly music has been shown to have both physical and mental health benefits including improvements in cardiovascular health, a link to reduction of cases of dementia in elderly populations, and improvements in markers of general mental well-being such as stress reduction. Here, we describe short case studies addressing general mental well-being (anxiety, stress-reduction) through AI-driven music generation. Engaging in active listening and music-making activities (especially for at risk age groups) can be particularly beneficial, and the practice of music therapy has been shown to be helpful in a range of use cases across a wide age range. However, access to music-making can be prohibitive in terms of access to expertize, materials, and cost. Furthermore the use of existing music for functional outcomes (such as targeted improvement in physical and mental health markers suggested above) can be hindered by issues of repetition and subsequent over-familiarity with existing material. In this paper, we describe machine learning approaches which create functional music informed by biophysiological measurement across two case studies, with target emotional states at opposing ends of a Cartesian affective space (a dimensional emotion space with points ranging from descriptors from relaxation, to fear). Galvanic skin response is used as a marker of psychological arousal and as an estimate of emotional state to be used as a control signal in the training of the machine learning algorithm. This algorithm creates a non-linear time series of musical features for sound synthesis "on-the-fly", using a perceptually informed musical feature similarity model. We find an interaction between familiarity and perceived emotional response. We also report on subsequent psychometric evaluation of the generated material, and consider how these - and similar techniques - might be useful for a range of functional music generation tasks, for example, in nonlinear sound-tracking such as that found in interactive media or video games.

Neural and physiological data from participants listening to affective music.

Music provides a means of communicating affective meaning. However, the neurological mechanisms by which music induces affect are not fully understood. Our project sought to investigate this through a series of experiments into how humans react to affective musical stimuli and how physiological and neurological signals recorded from those participants change in accordance with self-reported changes in affect. In this paper, the datasets recorded over the course of this project are presented, including details of the musical stimuli, participant reports of their felt changes in affective states as they listened to the music, and concomitant recordings of physiological and neurological activity. We also include non-identifying meta data on our participant populations for purposes of further exploratory analysis. This data provides a large and valuable novel resource for researchers investigating emotion, music, and how they affect our neural and physiological activity.

Electroencephalography reflects the activity of sub-cortical brain regions during approach-withdrawal behaviour while listening to music.

The ability of music to evoke activity changes in the core brain structures that underlie the experience of emotion suggests that it has the potential to be used in therapies for emotion disorders. A large volume of research has identified a network of sub-cortical brain regions underlying music-induced emotions. Additionally, separate evidence from electroencephalography (EEG) studies suggests that prefrontal asymmetry in the EEG reflects the approach-withdrawal response to music-induced emotion. However, fMRI and EEG measure quite different brain processes and we do not have a detailed understanding of the functional relationships between them in relation to music-induced emotion. We employ a joint EEG - fMRI paradigm to explore how EEG-based neural correlates of the approach-withdrawal response to music reflect activity changes in the sub-cortical emotional response network. The neural correlates examined are asymmetry in the prefrontal EEG, and the degree of disorder in that asymmetry over time, as measured by entropy. Participants' EEG and fMRI were recorded simultaneously while the participants listened to music that had been specifically generated to target the elicitation of a wide range of affective states. While listening to this music, participants also continuously reported their felt affective states. Here we report on co-variations in the dynamics of these self-reports, the EEG, and the sub-cortical brain activity. We find that a set of sub-cortical brain regions in the emotional response network exhibits activity that significantly relates to prefrontal EEG asymmetry. Specifically, EEG in the pre-frontal cortex reflects not only cortical activity, but also changes in activity in the amygdala, posterior temporal cortex, and cerebellum. We also find that, while the magnitude of the asymmetry reflects activity in parts of the limbic and paralimbic systems, the entropy of that asymmetry reflects activity in parts of the autonomic response network such as the auditory cortex. This suggests that asymmetry magnitude reflects affective responses to music, while asymmetry entropy reflects autonomic responses to music. Thus, we demonstrate that it is possible to infer activity in the limbic and paralimbic systems from pre-frontal EEG asymmetry. These results show how EEG can be used to measure and monitor changes in the limbic and paralimbic systems. Specifically, they suggest that EEG asymmetry acts as an indicator of sub-cortical changes in activity induced by music. This shows that EEG may be used as a measure of the effectiveness of music therapy to evoke changes in activity in the sub-cortical emotion response network. This is also the first time that the activity of sub-cortical regions, normally considered "invisible" to EEG, has been shown to be characterisable directly from EEG dynamics measured during music listening.

Differential detection of tuberculous and non-tuberculous mycobacteria by qPCR in lavage fluids of tuberculosis-suspicious white rhinoceros.

Tuberculosis (TB) occurs in a wide range of mammalian species and thus poses a health risk to humans living or working in close proximity with TB infected animals. Despite a high incidence of M. bovis infections in domestic or wildlife species tuberculosis infections in rhinoceros have so far been very limited. Over the past 53 years, tuberculosis of the respiratory tract has been confirmed in just 22 rhinoceros, most of those infected not by M. bovis but M. tuberculosis. However, because of the zoonotic risk TB testing is recommended or becomes even mandatory in endangered species. The dilemma in rhinoceros and many other wildlife species; non-validated tests are highly inconsistent in their ability to identify TB infection. Current lack of TB diagnostics may result in TB positive rhinoceros living with the infection, transmitting it to those around them or in euthanasia of animals found unconfirmed at necropsy. This is an unacceptable diagnostic status considering that some species are critically endangered and therefore should not be euthanized in order to confirm suspicion of disease. To overcome this shortcoming we used bronchoscopy to detect mycobacteria in respiratory fluids of TB suspicious rhinoceros. Fluids from seven, TB suspicious white rhinoceros were harvested during 21 bronchoscopies. Our new approach: In addition to bacterial culture a dual quantitative PCR system tested for the general presence of DNA from NTM and more specifically for DNA from MTC. Both, bacterial culture and qPCR were negative for MTC in respiratory fluids of all rhinoceros (7/7). At the same time, respiratory fluids from six rhinoceros tested positive for the presence of NTM or other closely related bacteria (6/7). M. tuberculosis was found only once in an oesophageal aspirate. The high incidence of mycobacterial DNA in the respiratory tract suggests that white rhinoceros, as strict grazers, are immensely exposed to environmental bacteria of this genus. Presence of NTM in the respiratory or intestinal system could possibly cause false positive results in intradermal tests. A wider use of bronchoalveolar lavage is warranted to further elucidate immunologic response to NTM and exposure to, incidence and prevalence of MTC infections in rhinoceros.

Directed Motor-Auditory EEG Connectivity Is Modulated by Music Tempo.

Beat perception is fundamental to how we experience music, and yet the mechanism behind this spontaneous building of the internal beat representation is largely unknown. Existing findings support links between the tempo (speed) of the beat and enhancement of electroencephalogram (EEG) activity at tempo-related frequencies, but there are no studies looking at how tempo may affect the underlying long-range interactions between EEG activity at different electrodes. The present study investigates these long-range interactions using EEG activity recorded from 21 volunteers listening to music stimuli played at 4 different tempi (50, 100, 150 and 200 beats per minute). The music stimuli consisted of piano excerpts designed to convey the emotion of "peacefulness". Noise stimuli with an identical acoustic content to the music excerpts were also presented for comparison purposes. The brain activity interactions were characterized with the imaginary part of coherence (iCOH) in the frequency range 1.5-18 Hz (δ, θ, α and lower ß) between all pairs of EEG electrodes for the four tempi and the music/noise conditions, as well as a baseline resting state (RS) condition obtained at the start of the experimental task. Our findings can be summarized as follows: (a) there was an ongoing long-range interaction in the RS engaging fronto-posterior areas; (b) this interaction was maintained in both music and noise, but its strength and directionality were modulated as a result of acoustic stimulation; (c) the topological patterns of iCOH were similar for music, noise and RS, however statistically significant differences in strength and direction of iCOH were identified; and (d) tempo had an effect on the direction and strength of motor-auditory interactions. Our findings are in line with existing literature and illustrate a part of the mechanism by which musical stimuli with different tempi can entrain changes in cortical activity.

Affective brain-computer music interfacing.

OBJECTIVE: We aim to develop and evaluate an affective brain-computer music interface (aBCMI) for modulating the affective states of its users. APPROACH: An aBCMI is constructed to detect a user's current affective state and attempt to modulate it in order to achieve specific objectives (for example, making the user calmer or happier) by playing music which is generated according to a specific affective target by an algorithmic music composition system and a case-based reasoning system. The system is trained and tested in a longitudinal study on a population of eight healthy participants, with each participant returning for multiple sessions. MAIN RESULTS: The final online aBCMI is able to detect its users current affective states with classification accuracies of up to 65% (3 class, [Formula: see text]) and modulate its user's affective states significantly above chance level [Formula: see text]. SIGNIFICANCE: Our system represents one of the first demonstrations of an online aBCMI that is able to accurately detect and respond to user's affective states. Possible applications include use in music therapy and entertainment.

Automated identification of neural correlates of continuous variables.

BACKGROUND: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. NEW METHOD: A method is presented for the automated identification of features that differentiate two or more groups in neurological datasets based upon a spectral decomposition of the feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. RESULTS: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally, the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. COMPARISON WITH EXISTING METHODS: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. CONCLUSIONS: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.

Changes in music tempo entrain movement related brain activity.

The neural mechanisms of music listening and appreciation are not yet completely understood. Based on the apparent relationship between the beats per minute (tempo) of music and the desire to move (for example feet tapping) induced while listening to that music it is hypothesised that musical tempo may evoke movement related activity in the brain. Participants are instructed to listen, without moving, to a large range of musical pieces spanning a range of styles and tempos during an electroencephalogram (EEG) experiment. Event-related desynchronisation (ERD) in the EEG is observed to correlate significantly with the variance of the tempo of the musical stimuli. This suggests that the dynamics of the beat of the music may induce movement related brain activity in the motor cortex. Furthermore, significant correlations are observed between EEG activity in the alpha band over the motor cortex and the bandpower of the music in the same frequency band over time. This relationship is observed to correlate with the strength of the ERD, suggesting entrainment of motor cortical activity relates to increased ERD strength.

Neural correlates of emotional responses to music: an EEG study.

This paper presents an EEG study into the neural correlates of music-induced emotions. We presented participants with a large dataset containing musical pieces in different styles, and asked them to report on their induced emotional responses. We found neural correlates of music-induced emotion in a number of frequencies over the pre-frontal cortex. Additionally, we found a set of patterns of functional connectivity, defined by inter-channel coherence measures, to be significantly different between groups of music-induced emotional responses.