Microscopic Origin of the Entropy of Astrophysical Black Holes.

We construct an infinite family of microstates for black holes in Minkowski spacetime which have effective semiclassical descriptions in terms of collapsing dust shells in the black hole interior. Quantum mechanical wormholes cause these states to have exponentially small, but universal, overlaps. We show that these overlaps imply that the microstates span a Hilbert space of log dimension equal to the event horizon area divided by four times the Newton constant, explaining the statistical origin of the Bekenstein-Hawking entropy.

Connectivity and dynamics in the olfactory bulb.

Dendrodendritic interactions between excitatory mitral cells and inhibitory granule cells in the olfactory bulb create a dense interaction network, reorganizing sensory representations of odors and, consequently, perception. Large-scale computational models are needed for revealing how the collective behavior of this network emerges from its global architecture. We propose an approach where we summarize anatomical information through dendritic geometry and density distributions which we use to calculate the connection probability between mitral and granule cells, while capturing activity patterns of each cell type in the neural dynamical systems theory of Izhikevich. In this way, we generate an efficient, anatomically and physiologically realistic large-scale model of the olfactory bulb network. Our model reproduces known connectivity between sister vs. non-sister mitral cells; measured patterns of lateral inhibition; and theta, beta, and gamma oscillations. The model in turn predicts testable relationships between network structure and several functional properties, including lateral inhibition, odor pattern decorrelation, and LFP oscillation frequency. We use the model to explore the influence of cortex on the olfactory bulb, demonstrating possible mechanisms by which cortical feedback to mitral cells or granule cells can influence bulbar activity, as well as how neurogenesis can improve bulbar decorrelation without requiring cell death. Our methodology provides a tractable tool for other researchers.

Aggressive Afterload Lowering to Improve the Right Ventricle: A New Target for Medical Therapy in Pulmonary Arterial Hypertension?

Despite numerous therapeutic advances in pulmonary arterial hypertension, patients continue to suffer high morbidity and mortality, particularly considering a median age of 50 years. This article explores whether early, robust reduction of right ventricular afterload would facilitate substantial improvement in right ventricular function and thus whether afterload reduction should be a treatment goal for pulmonary arterial hypertension. The earliest clinical studies of prostanoid treatment in pulmonary arterial hypertension demonstrated an important link between lowering mean pulmonary arterial pressure (or pulmonary vascular resistance) and improved survival. Subsequent studies of oral monotherapy or sequential combination therapy demonstrated smaller reductions in mean pulmonary arterial pressure and pulmonary vascular resistance. More recently, retrospective reports of initial aggressive prostanoid treatment or initial combination oral and parenteral therapy have shown marked afterload reduction along with significant improvements in right ventricular function. Some data suggest that reaching threshold levels for pressure or resistance (components of right ventricular afterload) may be key to interrupting the self-perpetuating injury of pulmonary vascular disease in pulmonary arterial hypertension and could translate into improved long-term clinical outcomes. Based on these clues, the authors postulate that improved clinical outcomes might be achieved by targeting significant afterload reduction with initial oral combination therapy and early parenteral prostanoids.

The size of the immune repertoire of bacteria.

Some bacteria and archaea possess an immune system, based on the CRISPR-Cas mechanism, that confers adaptive immunity against viruses. In such species, individual prokaryotes maintain cassettes of viral DNA elements called spacers as a memory of past infections. Typically, the cassettes contain several dozen expressed spacers. Given that bacteria can have very large genomes and since having more spacers should confer a better memory, it is puzzling that so little genetic space would be devoted by prokaryotes to their adaptive immune systems. Here, assuming that CRISPR functions as a long-term memory-based defense against a diverse landscape of viral species, we identify a fundamental tradeoff between the amount of immune memory and effectiveness of response to a given threat. This tradeoff implies an optimal size for the prokaryotic immune repertoire in the observational range.

Cortical feedback and gating in odor discrimination and generalization.

A central question in neuroscience is how context changes perception. In the olfactory system, for example, experiments show that task demands can drive divergence and convergence of cortical odor responses, likely underpinning olfactory discrimination and generalization. Here, we propose a simple statistical mechanism for this effect based on unstructured feedback from the central brain to the olfactory bulb, which represents the context associated with an odor, and sufficiently selective cortical gating of sensory inputs. Strikingly, the model predicts that both convergence and divergence of cortical odor patterns should increase when odors are initially more similar, an effect reported in recent experiments. The theory in turn predicts reversals of these trends following experimental manipulations and in neurological conditions that increase cortical excitability.

How a well-adapting immune system remembers.

An adaptive agent predicting the future state of an environment must weigh trust in new observations against prior experiences. In this light, we propose a view of the adaptive immune system as a dynamic Bayesian machinery that updates its memory repertoire by balancing evidence from new pathogen encounters against past experience of infection to predict and prepare for future threats. This framework links the observed initial rapid increase of the memory pool early in life followed by a midlife plateau to the ease of learning salient features of sparse environments. We also derive a modulated memory pool update rule in agreement with current vaccine-response experiments. Our results suggest that pathogenic environments are sparse and that memory repertoires significantly decrease infection costs, even with moderate sampling. The predicted optimal update scheme maps onto commonly considered competitive dynamics for antigen receptors.

Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures.

In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding (CB): Only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to 12 monomolecular odorants to within 15% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive-binding model.

Environmental deformations dynamically shift human spatial memory.

Place and grid cells in the hippocampal formation are commonly thought to support a unified and coherent cognitive map of space. This mapping mechanism faces a challenge when a navigator is placed in a familiar environment that has been deformed from its original shape. Under such circumstances, many transformations could plausibly serve to map a navigator's familiar cognitive map to the deformed space. Previous empirical results indicate that the firing fields of rodent place and grid cells stretch or compress in a manner that approximately matches the environmental deformation, and human spatial memory exhibits similar distortions. These effects have been interpreted as evidence that reshaping a familiar environment elicits an analogously reshaped cognitive map. However, recent work has suggested an alternative explanation, whereby deformation-induced distortions of the grid code are attributable to a mechanism that dynamically anchors grid fields to the most recently experienced boundary, thus causing history-dependent shifts in grid phase. This interpretation raises the possibility that human spatial memory will exhibit similar history-dependent dynamics. To test this prediction, we taught participants the locations of objects in a virtual environment and then probed their memory for these locations in deformed versions of this environment. Across three experiments with variable access to visual and vestibular cues, we observed the predicted pattern, whereby the remembered locations of objects were shifted from trial to trial depending on the boundary of origin of the participant's movement trajectory. These results provide evidence for a dynamic anchoring mechanism that governs both neuronal firing and spatial memory.

An expert panel delphi consensus statement on patient selection and management for transitioning between oral and inhaled treprostinil.

Treprostinil, a prostacyclin analogue used in the treatment of pulmonary arterial hypertension (PAH), is available for administration by parenteral, oral, or inhaled routes. Transitioning between routes may be beneficial for appropriate patients; however, there is little published data on transitions between oral and inhaled treprostinil. We used a modified Delphi process to develop expert consensus recommendations on transitions between these formulations. Three questionnaires were used to develop statements about relevant aspects of transition management, which the panelists rated, using a Likert scale, from -5 (strongly disagree) to +5 (strongly agree). Eleven physicians with expertise in PAH treatment modalities, participated in the panel. Of the 492 statements evaluated, consensus was reached on 215 (43.7%). Key consensus recommendations included (1) accurately defining successful transition, as stable or improved PAH with good tolerability and adherence, and (2) patients with stable, low-risk PAH showing insufficient response or tolerability to their existing treprostinil therapy (and due to restrictions in up titration of dosing), as appropriate candidates for transitions between treprostinil formulations. Panelists did not reach consensus for an overall strategy for performing these transitions, mainly because of variability in their practice parameters. Consensus was also achieved on recommendations for adverse event management, including reassurance, administration of oral treprostinil 3 times daily with food, and dosing inhaled treprostinil at intervals ≥3 hours apart. The Delphi process aided in developing expert consensus recommendations that may provide clinically useful guidance for transitioning between treprostinil formulations. However, additional data from centers with high volumes of PAH patients undergoing treprostinil transitions would be optimal for defining more complete and robust strategies to facilitate successful transition.

Cortical Neural Activity Predicts Sensory Acuity Under Optogenetic Manipulation.

Excitatory and inhibitory neurons in the mammalian sensory cortex form interconnected circuits that control cortical stimulus selectivity and sensory acuity. Theoretical studies have predicted that suppression of inhibition in such excitatory-inhibitory networks can lead to either an increase or, paradoxically, a decrease in excitatory neuronal firing, with consequent effects on stimulus selectivity. We tested whether modulation of inhibition or excitation in the auditory cortex of male mice could evoke such a variety of effects in tone-evoked responses and in behavioral frequency discrimination acuity. We found that, indeed, the effects of optogenetic manipulation on stimulus selectivity and behavior varied in both magnitude and sign across subjects, possibly reflecting differences in circuitry or expression of optogenetic factors. Changes in neural population responses consistently predicted behavioral changes for individuals separately, including improvement and impairment in acuity. This correlation between cortical and behavioral change demonstrates that, despite the complex and varied effects that these manipulations can have on neuronal dynamics, the resulting changes in cortical activity account for accompanying changes in behavioral acuity.SIGNIFICANCE STATEMENT Excitatory and inhibitory interactions determine stimulus specificity and tuning in sensory cortex, thereby controlling perceptual discrimination acuity. Modeling has predicted that suppressing the activity of inhibitory neurons can lead to increased or, paradoxically, decreased excitatory activity depending on the architecture of the network. Here, we capitalized on differences between subjects to test whether suppressing/activating inhibition and excitation can in fact exhibit such paradoxical effects for both stimulus sensitivity and behavioral discriminability. Indeed, the same optogenetic manipulation in the auditory cortex of different mice could improve or impair frequency discrimination acuity, predictable from the effects on cortical responses to tones. The same manipulations sometimes produced opposite changes in the behavior of different individuals, supporting theoretical predictions for inhibition-stabilized networks.

Dynamics of adaptive immunity against phage in bacterial populations.

The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where bacterial and phage populations can co-exist, others where the populations exhibit damped oscillations, and still others where one population is driven to extinction. Our model considers two key parameters: (1) ease of acquisition and (2) spacer effectiveness in conferring immunity. Analytical calculations and numerical simulations show that if spacers differ mainly in ease of acquisition, or if the probability of acquiring them is sufficiently high, bacteria develop a diverse population of spacers. On the other hand, if spacers differ mainly in their effectiveness, their final distribution will be highly peaked, akin to a "winner-take-all" scenario, leading to a specialized spacer distribution. Bacteria can interpolate between these limiting behaviors by actively tuning their overall acquisition probability.

How a well-adapted immune system is organized.

The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from diverse pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. We develop a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters; individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens; and the optimal repertoires can be reached via the dynamics of competitive binding of antigens by receptors and selective amplification of stimulated receptors. Our results follow from a tension between the statistics of pathogen detection, which favor a broader receptor distribution, and the effects of cross-reactivity, which tend to concentrate the optimal repertoire onto a few highly abundant clones. Our predictions can be tested in high-throughput surveys of receptor and pathogen diversity.

Comparison of treadmill exercise stress cardiac MRI to stress echocardiography in healthy volunteers for adequacy of left ventricular endocardial wall visualization: A pilot study.

PURPOSE: To compare exercise stress cardiac magnetic resonance (cardiac MR) to echocardiography in healthy volunteers with respect to adequacy of endocardial visualization and confidence of stress study interpretation. MATERIALS AND METHODS: Twenty-eight healthy volunteers (age 28 ± 11 years, 15 males) underwent exercise stress echo and cardiac MR one week apart assigned randomly to one test first. Stress cardiac MR was performed using an MRI-compatible treadmill; stress echo was performed as per routine protocol. Cardiac MR and echo images were independently reviewed and scored for adequacy of endocardial visualization and confidence in interpretation of the stress study. RESULTS: Heart rate at the time of imaging was similar between the studies. Average time from cessation of exercise to start of imaging (21 vs. 31 s, P < 0.001) and time to acquire stress images (20 vs. 51 s, P < 0.001) was shorter for cardiac MR. The number of myocardial segments adequately visualized was significantly higher by cardiac MR at rest (99.8% vs. 96.4%, P = 0.002) and stress (99.8% vs. 94.1%, P = 0.001). The proportion of subjects in whom there was high confidence in the interpretation was higher for cardiac MR than echo (96% vs. 60%, P = 0.005). CONCLUSION: Exercise stress cardiac MR to assess peak exercise wall motion is feasible and can be performed at least as rapidly as stress echo.

Transformation of stimulus correlations by the retina.

Redundancies and correlations in the responses of sensory neurons may seem to waste neural resources, but they can also carry cues about structured stimuli and may help the brain to correct for response errors. To investigate the effect of stimulus structure on redundancy in retina, we measured simultaneous responses from populations of retinal ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure; these stimuli and recordings are publicly available online. Responding to spatio-temporally structured stimuli such as natural movies, pairs of ganglion cells were modestly more correlated than in response to white noise checkerboards, but they were much less correlated than predicted by a non-adapting functional model of retinal response. Meanwhile, responding to stimuli with purely spatial correlations, pairs of ganglion cells showed increased correlations consistent with a static, non-adapting receptive field and nonlinearity. We found that in response to spatio-temporally correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the pattern of pairwise correlations across stimuli where receptive field measurements were possible.

Physical effects of learning.

Interacting many-body physical systems ranging from neural networks in the brain to folding proteins to self-modifying electrical circuits can learn to perform diverse tasks. This learning, both in nature and in engineered systems, can occur through evolutionary selection or through dynamical rules that drive active learning from experience. Here, we show that learning in linear physical networks with weak input signals leaves architectural imprints on the Hessian of a physical system. Compared to a generic organization of the system components, (a) the effective physical dimension of the response to inputs decreases, (b) the response of physical degrees of freedom to random perturbations (or system "susceptibility") increases, and (c) the low-eigenvalue eigenvectors of the Hessian align with the task. Overall, these effects embody the typical scenario for learning processes in physical systems in the weak input regime, suggesting ways of discovering whether a physical network may have been trained.

Slow and steady: auditory features for discriminating animal vocalizations.

We propose that listeners can use temporal regularities - spectro-temporal correlations that change smoothly over time - to discriminate animal vocalizations within and between species. To test this idea, we used Slow Feature Analysis (SFA) to find the most temporally regular components of vocalizations from birds (blue jay, house finch, American yellow warbler, and great blue heron), humans (English speakers), and rhesus macaques. We projected vocalizations into the learned feature space and tested intra-class (same speaker/species) and inter-class (different speakers/species) auditory discrimination by a trained classifier. We found that: 1) Vocalization discrimination was excellent ( > 95%) in all cases; 2) Performance depended primarily on the ∼10 most temporally regular features; 3) Most vocalizations are dominated by ∼10 features with high temporal regularity; and 4) These regular features are highly correlated with the most predictable components of animal sounds.

Oral Treprostinil is Associated with Improved Survival in FREEDOM-EV and its Open-Label Extension.

INTRODUCTION: In the event-driven FREEDOM-EV trial, oral treprostinil delayed clinical worsening in patients with pulmonary arterial hypertension (PAH). Open-label extension studies offer additional data about tolerability, efficacy, and survival, especially for those initially assigned placebo. The aim of the current study was to determine if oral treprostinil changed survival when considering the parent and extension study, if treprostinil provides functional benefits for participants initially assigned to placebo, and if the benefits observed for those treated with treprostinil were durable. METHODS: Both active and placebo participants from FREEDOM-EV could enroll in the FREEDOM-EV open-label extension (OLE) study after experiencing an investigator-assessed clinical worsening event or after parent study closure. All participants in the OLE were offered open-label oral treprostinil. Previously assigned placebo participants titrated to maximally tolerated doses; previously assigned treprostinil participants continued dose titration. We repeated assessments including functional class and 6-min walk distance (6MWD) at 12-week intervals and measured N-terminal pro-brain natriuretic peptide (NT-proBNP) at week 48. Survival was estimated by Kaplan-Meier analysis, and we estimated hazard ratio (HR) using Cox proportional hazards. RESULTS: Of 690 FREEDOM-EV participants, 470 enrolled in the OLE; vital status was available for 89% of initial Freedom-EV participants. When considering the combined parent and open-label data, initial assignment to oral treprostinil reduced mortality (HR 0.64, 95% confidence interval 0.46-0.91, p = 0.013); absolute risk reduction was 9%. Participants randomized to placebo who initiated oral treprostinil after clinical worsening and tolerated treatment through week 48 demonstrated favorable shifts in functional class (p < 0.0001), 6MWD improvements of + 84 m (p < 0.0001), and a reduction in NT-proBNP of - 778 pg/mL (p = 0.02), compared to OLE baseline. Modest trends toward benefit were measured for those initially assigned placebo who did not have clinical worsening, and 132/144 (92%) of treprostinil assigned participants without clinical worsening remained on drug at week 48 in the OLE study. Adverse events were consistent with FREEDOM-EV. CONCLUSION: Initial treprostinil assignment improved survival in the entire data set; those who began treprostinil after a clinical worsening in the placebo arm and tolerated drug to week 48 enjoyed substantial functional gains. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01560637.

Why do axons differ in caliber?

CNS axons differ in diameter (d) by nearly 100-fold (∼0.1-10 µm); therefore, they differ in cross-sectional area (d(2)) and volume by nearly 10,000-fold. If, as found for optic nerve, mitochondrial volume fraction is constant with axon diameter, energy capacity would rise with axon volume, also as d(2). We asked, given constraints on space and energy, what functional requirements set an axon's diameter? Surveying 16 fiber groups spanning nearly the full range of diameters in five species (guinea pig, rat, monkey, locust, octopus), we found the following: (1) thin axons are most numerous; (2) mean firing frequencies, estimated for nine of the identified axon classes, are low for thin fibers and high for thick ones, ranging from ∼1 to >100 Hz; (3) a tract's distribution of fiber diameters, whether narrow or broad, and whether symmetric or skewed, reflects heterogeneity of information rates conveyed by its individual fibers; and (4) mitochondrial volume/axon length rises ≥d(2). To explain the pressure toward thin diameters, we note an established law of diminishing returns: an axon, to double its information rate, must more than double its firing rate. Since diameter is apparently linear with firing rate, doubling information rate would more than quadruple an axon's volume and energy use. Thicker axons may be needed to encode features that cannot be efficiently decoded if their information is spread over several low-rate channels. Thus, information rate may be the main variable that sets axon caliber, with axons constrained to deliver information at the lowest acceptable rate.

Optimal population coding by noisy spiking neurons.

In retina and in cortical slice the collective response of spiking neural populations is well described by "maximum-entropy" models in which only pairs of neurons interact. We asked, how should such interactions be organized to maximize the amount of information represented in population responses? To this end, we extended the linear-nonlinear-Poisson model of single neural response to include pairwise interactions, yielding a stimulus-dependent, pairwise maximum-entropy model. We found that as we varied the noise level in single neurons and the distribution of network inputs, the optimal pairwise interactions smoothly interpolated to achieve network functions that are usually regarded as discrete--stimulus decorrelation, error correction, and independent encoding. These functions reflected a trade-off between efficient consumption of finite neural bandwidth and the use of redundancy to mitigate noise. Spontaneous activity in the optimal network reflected stimulus-induced activity patterns, and single-neuron response variability overestimated network noise. Our analysis suggests that rather than having a single coding principle hardwired in their architecture, networks in the brain should adapt their function to changing noise and stimulus correlations.