Estimating Respiratory Rate From Breath Audio Obtained Through Wearable Microphones.

Respiratory rate (RR) is a clinical metric used to assess overall health and physical fitness. An individual's RR can change from their baseline due to chronic illness symptoms (e.g., asthma, congestive heart failure), acute illness (e.g., breathlessness due to infection), and over the course of the day due to physical exhaustion during heightened exertion. Remote estimation of RR can offer a cost-effective method to track disease progression and cardio-respiratory fitness over time. This work investigates a model-driven approach to estimate RR from short audio segments obtained after physical exertion in healthy adults. Data was collected from 21 individuals using microphone-enabled, near-field headphones before, during, and after strenuous exercise. RR was manually annotated by counting perceived inhalations and exhalations. A multi-task Long-Short Term Memory (LSTM) network with convolutional layers was implemented to process mel-filterbank energies, estimate RR in varying background noise conditions, and predict heavy breathing, indicated by an RR of more than 25 breaths per minute. The multi-task model performs both classification and regression tasks and leverages a mixture of loss functions. It was observed that RR can be estimated with a concordance correlation coefficient (CCC) of 0.76 and a mean squared error (MSE) of 0.2, demonstrating that audio can be a viable signal for approximating RR.Clinical relevance-The subject technology facilitates the use of accessible, aesthetically acceptable wearable headphones to provide a technologically efficient and cost-effective method to estimate respiratory rate and track cardio-respiratory fitness over time.

Smartwatch inertial sensors continuously monitor real-world motor fluctuations in Parkinson's disease.

Longitudinal, remote monitoring of motor symptoms in Parkinson's disease (PD) could enable more precise treatment decisions. We developed the Motor fluctuations Monitor for Parkinson's Disease (MM4PD), an ambulatory monitoring system that used smartwatch inertial sensors to continuously track fluctuations in resting tremor and dyskinesia. We designed and validated MM4PD in 343 participants with PD, including a longitudinal study of up to 6 months in a 225-subject cohort. MM4PD measurements correlated to clinical evaluations of tremor severity (ρ = 0.80) and mapped to expert ratings of dyskinesia presence (P < 0.001) during in-clinic tasks. MM4PD captured symptom changes in response to treatment that matched the clinician's expectations in 94% of evaluated subjects. In the remaining 6% of cases, symptom data from MM4PD identified opportunities to make improvements in pharmacologic strategy. These results demonstrate the promise of MM4PD as a tool to support patient-clinician communication, medication titration, and clinical trial design.

Distinguishing cognitive effort and working memory load using scale-invariance and alpha suppression in EEG.

Despite being intuitive, cognitive effort has proven difficult to define quantitatively. Here, we proposed to study cognitive effort by investigating the degree to which the brain deviates from its default state, where brain activity is scale-invariant. Specifically, we measured such deviations by examining changes in scale-invariance of brain activity as a function of task difficulty and posited suppression of scale-invariance as a proxy for exertion of cognitive effort. While there is some fMRI evidence supporting this proposition, EEG investigations on the matter are scant, despite the EEG signal being more suitable for analysis of scale invariance (i.e., having a much broader frequency range). In the current study we validated the correspondence between scale-invariance (H) of cortical activity recorded by EEG and task load during two working memory (WM) experiments with varying set sizes. Then, we used this neural signature to disentangle cognitive effort from the number of items stored in WM within participants. Our results showed monotonic decreases in H with increased set size, even after set size exceeded WM capacity. This behavior of H contrasted with behavioral performance and an oscillatory indicator of WM load (i.e., alpha-band desynchronization), both of which showed a plateau at difficulty levels surpassing WM capacity. This is the first reported evidence for the suppression of scale-invariance in EEG due to task difficulty, and our work suggests that H suppression may be used to quantify changes in cognitive effort even when working memory load is at maximum capacity.

Sleepless Night and Day, the Plight of Progressive Supranuclear Palsy.

Objectives: To elucidate the unique sleep and waking characteristics in progressive supranuclear palsy (PSP), a neurodegenerative disease associated with motor deficits and dementia that largely affects the brainstem and thalamic regions. Methods: A total of 20 PSP and 16 healthy older adult controls participated in this study. The participants underwent an overnight polysomnography and multiple sleep latency test (MSLT) the following day. Prior to the MSLT last trial, they were asked to complete the Stanford Sleepiness Scale. Data were assessed for measures of latency to sleep onset, sleep duration, waking, and sleep staging during the night. Mean sleep latency, a measure of daytime sleepiness, sleep onset rapid eye movement (REM) periods, and microsleeps were studied with the MSLT. Spectral analysis of wake electroencephalogram (EEG) was performed for 30-second periods at the start of each MSLT trial. Results: PSP took significantly longer time to fall asleep (p < .001), slept less during the night (p ≤ .001), and had more wake after sleep onset than controls (p ≤ .001). PSP had less N2 sleep (p < .05) and N3 sleep (p < .05), and REM sleep (p < .001) than controls. During the MSLT, PSP took significantly longer to fall asleep (p < .001), did not have microsleeps when they remained awake throughout the assessment periods, but were subjectively sleepier than controls (p < .05). Gamma power was increased during wake EEG in PSP (p < .01). Conclusions: Sleep/waking regulation and REM sleep regulation are disrupted in PSP, leading to profound sleep deprivation without recuperation. Our findings suggest a diminished homeostatic sleep drive in PSP. This hyperaroused state is unique and is a severely disabling feature of PSP.

α Power Modulation and Event-Related Slow Wave Provide Dissociable Correlates of Visual Working Memory.

Traditionally, electrophysiological correlates of visual working memory (VWM) capacity have been characterized using a lateralized VWM task in which participants had to remember items presented on the cued hemifield while ignoring the distractors presented on the other hemifield. Though this approach revealed a lateralized parieto-occipital negative slow wave (i.e., the contralateral delay activity) and lateralized α power modulation as neural correlates of VWM capacity that may be mechanistically related, recent evidence suggested that these measures might be reflecting individuals' ability to ignore distractors rather than their ability to maintain VWM representations. To better characterize the neural correlates of VWM capacity, we had human participants perform a whole-field VWM task in which they remembered all the items on the display. Here, we found that both the parieto-occipital negative slow wave and the α power suppression showed the characteristics of VWM capacity in the absence of distractors, suggesting that they reflect the maintenance of VWM representations rather than filtering of distractors. Furthermore, the two signals explained unique portions of variance in individual differences of VWM capacity and showed differential temporal characteristics. This pattern of results clearly suggests that individual differences in VWM capacity are determined by dissociable neural mechanisms reflected in the ERP and the oscillatory measures of VWM capacity. SIGNIFICANCE STATEMENT: Our work demonstrates that there exist event-related potential and oscillatory correlates of visual working memory (VWM) capacity even in the absence of task-irrelevant distractors. This clearly shows that the two neural correlates are directly linked to maintenance of task-relevant information rather than filtering of task-irrelevant information. Furthermore, we found that these two correlates show differential temporal characteristics. These results are inconsistent with proposals that the two neural correlates are byproducts of asymmetric α power suppression and indicate that they reflect dissociable neural mechanisms subserving VWM.

The contribution of attentional lapses to individual differences in visual working memory capacity.

Attentional control and working memory capacity are important cognitive abilities that substantially vary between individuals. Although much is known about how attentional control and working memory capacity relate to each other and to constructs like fluid intelligence, little is known about how trial-by-trial fluctuations in attentional engagement impact trial-by-trial working memory performance. Here, we employ a novel whole-report memory task that allowed us to distinguish between varying levels of attentional engagement in humans performing a working memory task. By characterizing low-performance trials, we can distinguish between models in which working memory performance failures are caused by either (1) complete lapses of attention or (2) variations in attentional control. We found that performance failures increase with set-size and strongly predict working memory capacity. Performance variability was best modeled by an attentional control model of attention, not a lapse model. We examined neural signatures of performance failures by measuring EEG activity while participants performed the whole-report task. The number of items correctly recalled in the memory task was predicted by frontal theta power, with decreased frontal theta power associated with poor performance on the task. In addition, we found that poor performance was not explained by failures of sensory encoding; the P1/N1 response and ocular artifact rates were equivalent for high- and low-performance trials. In all, we propose that attentional lapses alone cannot explain individual differences in working memory performance. Instead, we find that graded fluctuations in attentional control better explain the trial-by-trial differences in working memory that we observe.

A soft handoff of attention between cerebral hemispheres.

Each cerebral hemisphere initially processes one half of the visual world. How are moving objects seamlessly tracked when they traverse visual hemifields? Covert tracking of lateralized objects evokes a difference between slow-wave electrophysiological activity observed from contralateral and ipsilateral electrodes in occipitoparietal regions. This event-related potentials (ERP) waveform, known as contralateral delay activity (CDA) [1, 2], is sensitive to the number of objects tracked [1, 2] and responds dynamically to changes in this quantity [3]. When a tracked object crosses the midline, an inversion in CDA polarity revealed the dropping of the object's representation by one hemisphere and its acquisition by the other. Importantly, our data suggest that the initially tracking hemisphere continues to represent the object for a period after that object crosses the midline. Meanwhile, the receiving hemisphere begins to represent the object before the object crosses the midline, leading to a period in which the object is represented by both hemispheres. Further, this overlap in representation is reduced if the midline crossing is unpredictable. Thus, this process is sensitive to observer expectations and does not simply reflect overlapping receptive fields near the midline.

Visual working memory.

Visual working memory (VWM), the system of storing, manipulating, and utilizing, visual information is fundamental to many cognitive acts. Exploring the limitations of this system is essential to understand the characteristics of higher-order cognition, since at a basic level, VWM is the interface through which we interact with our environment. Given its important function, this system has become a very active area of research in the recent years. Here, we examine current models of VWM, along with the proposed reasons for what limits its capacity. This is followed by a short description of recent neural findings that have helped constrain models of VWM. In closing, we focus on work exploring individual differences in working memory capacity, and what these findings reveal about the intimate relationship between VWM and attention. WIREs Cogn Sci 2013, 4:179-190. doi: 10.1002/wcs.1219 For further resources related to this article, please visit the WIREs website.

Parallel consolidation of simple features into visual short-term memory.

Although considerable research has examined the storage limits of visual short-term memory (VSTM), little is known about the initial formation (i.e., the consolidation) of VSTM representations. A few previous studies have estimated the capacity of consolidation to be one item at a time. Here we used a sequential-simultaneous manipulation to reexamine the limits of consolidating items into VSTM. Participants viewed briefly presented and masked color patches (targets), which were shown either sequentially or simultaneously. A probe color followed the targets and participants decided whether it matched one of the targets or was a novel color. In four experiments, we consistently found equal performance for sequential and simultaneous presentations for two targets. Worse performance in the simultaneous than the sequential condition was observed for larger set sizes (three and four). Contrary to previous results, suggesting a severe capacity limit of one item, our results indicate that consolidation into VSTM can occur in parallel and without capacity limits for at least two items.

Constant spread of feature-based attention across the visual field.

Attending to a feature in one location can produce feature-specific modulation in a different location. This global feature-based attention effect has been demonstrated using two stimulus locations. Although the spread of feature-based attention is presumed to be constant across spatial locations, it has not been tested empirically. We examined the spread of feature-based attention by measuring attentional modulation of the motion aftereffect (MAE) at remote locations. Observers attended to one of two directions in a compound motion stimulus (adapter) and performed a speed-increment task. MAE was measured via a speed nulling procedure for a test stimulus at different distances from the adapter. In Experiment 1, the adapter was at fixation, while the test stimulus was located at different eccentricities. We also measured the magnitude of baseline MAE for each location in two control conditions that did not require feature-based selection necessitated by a compound stimulus. In Experiment 2, the adapter and test stimuli were all located in the periphery at the same eccentricity. Our results showed that attention induced MAE spread completely across the visual field, indicating a genuine global effect. These results add to our understanding of the deployment of feature-based attention and provide empirical constraints on theories of visual attention.