Faculty Bibliography

Vocalizations are ancient behaviours that require the complex coordination of breath and display. Understanding how laryngeal anatomy shapes vocalization provides insights into this diversity, its mechanisms and their evolution. Rodents are ideal for exploring this variation because of their diverse mechanisms and vocal structures. Here, we describe the laryngeal morphology and sound production mechanisms underlying the vocalizations of Alston's singing mouse (Scotinomys teguina) and compare these results to those of other vocalizing mammals. We reconstructed the three-dimensional laryngeal morphology with micro-computed tomography, recorded laryngeal sound production using high-speed video and investigated frequency control using surgical ablations. We found that singing mice use a whistle mechanism that uniquely relies on the inflation of an enlarged air sac called the ventral pouch. Song frequency can be controlled by pouch volume, airflow and cricothyroid muscle action. Singing mouse laryngeal morphology and vocal mechanism are distinct from those of other Neotomids; singing mice appear to use inflation-mediated whistles for both distant and close exchanges. Inflatable air sacs have evolved repeatedly for sound modulation and filtering. Our results indicate a novel role for these structures in being required to generate sound. Together, our results expand on an emerging story of how biomechanic and morphological variation contributes to vocal diversity.

The relation between the vocal capacities of animals and those of humans is a long-standing topic of interest for scientists, philosophers, and lay people alike. While similar neural and physiological substrates underlie the production of vocal signals in humans and animals, the most celebrated and prototypical aspects of language are cognitive phenomena that go far beyond speech sensorimotor processes. These include a subset of features that have begun to be systematically investigated in nonhuman animals, namely: (i) the presence of statistical laws, (ii) hierarchical syntactic rules, and (iii) the capacity for meaning and reference. Here we review recent progress describing and quantifying language-like structure in animal vocalizations. We highlight agreement and disagreement about the similarities that may exist between human language and animal vocal repertoires, with an eye toward what these phenomena may reveal about the evolution of language and its neural control.

Intercompartmental water exchange in brain and other biological tissue can be probed in vivo with diffusion MRI (dMRI). We assess the accuracy of a recently proposed method for estimating a mean exchange rate by performing Monte Carlo simulations of random walkers through a packing of permeable, randomly placed, parallel cylinders to model water exchange within axonal fiber bundles. The diffusivity and kurtosis of the full system are calculated for a broad range of diffusion times and model parameters. The mean exchange rate is estimated from the logarithmic derivative of the kurtosis with respect to the diffusion time and compared with the exchange rate predicted by the Kärger model (KM), which is exact in certain limits. The mean exchange rate is also compared with the reciprocal exchange time obtained by conventional fitting of the kurtosis time dependence to a two-compartment KM, with a high correlation being found between the two quantities. The estimates from the logarithmic derivative are in good agreement with the KM predictions when the exchange time is long in comparison to the compartment traversal times, which corresponds to barrier-limited exchange. Compared to the standard procedure of fitting the kurtosis to the KM over a broad range of diffusion times, using the logarithmic derivative reduces the data acquisition burden by only requiring a narrow range of times and increases generality in that number of compartments need not be specified. This method may be useful for estimating the mean exchange rate from the kurtosis time dependence measured with dMRI.

The autonomic nervous system (ANS) plays a vital role in health care for both acute care and chronic diseases. The traditional view of the ANS is to divide it into individual organ systems and study the separate components with a reductionist approach, which has been proven insufficient. Here, we argue that a holistic network-level view of the ANS is critical for generating new insights and deepening our understanding of its complex and dynamic functions. In this review, we treat the ANS as such a coordinated and dynamic network. We advocate for studying its interactions with major organ systems and the central nervous system using continuous and longitudinal monitoring in ambulatory and at-home settings rather than clinic-based snapshots. We first briefly review ANS physiology, then outline our network perspective, and finally highlight cutting-edge research directions and emerging engineering innovations in ANS monitoring, modeling, and modulation that benefit from this network-level view.

The cardiac conduction system (CCS) has a vital role in initiating and coordinating nearly 3 billion heartbeats throughout a person's lifetime. The CCS comprises two primary tissue types: the impulse-generating, slow-conducting nodes and the fast-conducting components of the ventricular conduction system. Dysfunction in this system can give rise to a spectrum of clinical symptoms, including palpitations, syncope, heart failure and even sudden cardiac death. Owing to the limited therapeutic options other than electronic pacemakers, substantial research efforts have been aimed at uncovering the root causes of conduction system disorders. A comprehensive investigative approach integrating genetics, transcriptomics and proteomics has been used to unravel the complex biology of these diseases. Advances in single-cell genomic and transcriptomic technologies, together with spatial transcriptomics, are offering new insights into the cellular microenvironments that govern conduction system function. In this Review, we examine the latest progress in understanding the biology of the CCS, situating new findings within both established and emerging scientific paradigms. Additionally, we discuss how these insights can be leveraged to improve clinical risk assessment, expand drug discovery efforts, accelerate technology aimed at promoting CCS regeneration and foster the development of innovative therapies, including biological pacemakers.

MR imaging is increasingly used in evaluation of patients with known or suspected hypertrophic cardiomyopathy (HCM), as it provides useful information on cardiac structure, function, and tissue characterization that is complementary to echocardiography. While the adverse effect of left ventricle (LV) outflow tract obstruction on blood flow patterns is well characterized by the midsystolic drop in LV ejection velocities and flow, flow patterns in HCM with mid-LV obstruction, with or without apical aneurysm, are less well characterized. MR imaging can provide additional information on alterations of blood flow patterns in these HCM phenotypes and "paradoxic" flows associated with apical aneurysms.

INTRODUCTION/BACKGROUND:Measuring plasma biomarkers effectively assesses early-stage Alzheimer's disease. METHODS:Subjects were categorized as cognitively unimpaired (CU) (n = 66), CU with subjective cognitive decline (SCD) (n = 100), and mild cognitive impairment (MCI) (n = 25). Plasma biomarkers measured were amyloid beta (Aβ) 40, Aβ42, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), tau phosphorylated at threonine 181 (pTau181), neuroinflammatory biomarkers, and blood-brain barrier biomarkers. Amyloid and tau positron emission tomography (PET) imaging was performed in 186 and 144 subjects, respectively. RESULTS:Comparing those having MCI, both CU and SCD participants had significantly lower amyloid PET standardized uptake value ratio (SUVR) (p < 0.001; p = 0.005). Higher amyloid PET SUVR was significantly associated with higher pTau181 (p = 0.001) and a higher pTau181/Aβ42 ratio (p < 0.001). Higher tau PET SUVR was associated with lower plasma Aβ42 (p = 0.020), older age (p = 0.005), higher GFAP (p = 0.020), and lower interleukin-8 levels (p < 0.001). DISCUSSION/CONCLUSIONS:Our study supports plasma biomarker monitoring of at-risk patients at various stages of pre-dementia.

In a dynamic environment, sensory systems must filter out irrelevant information to construct a stable percept. Animals who rely on smell need to identify and discriminate odors despite fluctuations in concentration, yet odor receptor activation is strongly concentration dependent. Here we explored how odor signals are transformed within the mouse olfactory bulb (OB) by developing an all-optical approach to identify the connectivity between odor receptor channels (glomeruli) and the mitral and tufted cells (MTCs), while monitoring their odor responses. We found that the glomeruli and MTCs activated earliest in a sniff robustly represented odor identity across concentrations, whereas MTCs connected to later activated glomeruli were concentration dependent. Furthermore, probing the responsiveness of MTCs to glomerular input found a short temporal window of excitability at a sniff's onset, followed by prolonged odor-evoked inhibition. Our findings demonstrate, in awake animals, that the OB implements a rapid temporal filter, which is responsible for stabilizing identity across concentrations while decorrelating responses between odors.

BACKGROUND/UNASSIGNED:As life expectancy rises, identifying causes and risk factors for incident acute ischemic stroke (AIS) among the oldest-old (≥80 years) is increasingly important. We examined whether the effect of age at stroke on AIS subtype is mediated by embolic risk factors and whether these factors improve AIS prediction. METHODS/UNASSIGNED:-VASc) and compared preinclusion and postinclusion of embolic risk factors. RESULTS/UNASSIGNED:-VASc: C statistics, 0.63 [95% CI, 0.59-0.67]). CONCLUSIONS/UNASSIGNED:These findings suggest that identification and control of embolic risk factors are critical to reduce stroke risk as people age, and better stroke-specific prediction tools are needed.