Investigating Penetration and Antimicrobial Activity of Vector-Bicycle Conjugates.

Growing antibiotic resistance is rapidly threatening the efficacy of treatments for Gram-negative infections. Bicycle molecules, constrained bicyclic peptides from diverse libraries generated by bacteriophage display that bind with high affinity to a chosen target are a potential new class of antibiotics. The generally impermeable bacterial outer membrane currently limits the access of peptides to bacteria. The conjugation of membrane active peptides offers an avenue for outer membrane penetration. Here, we investigate which physicochemical properties of a specific membrane active peptide (MAP), derived from ixosin-B, could be tweaked to enhance the penetration of conjugates by generating multiple MAP-Bicycle conjugate variants. We demonstrate that charge and hydrophobicity are important factors, which enhance penetration and, therefore, antimicrobial potency. Interestingly, we show that induction of secondary structure, but not a change in amphipathicity, is vital for effective penetration of the Gram-negative outer membrane. These results offer insights into the ways vectors could be designed to deliver Bicycle molecules (and other cargos) through biological membranes.

A reference genome for ecological restoration of the sunflower sea star, Pycnopodia helianthoides.

Wildlife diseases, such as the sea star wasting (SSW) epizootic that outbroke in the mid-2010s, appear to be associated with acute and/or chronic abiotic environmental change; dissociating the effects of different drivers can be difficult. The sunflower sea star, Pycnopodia helianthoides, was the species most severely impacted during the SSW outbreak, which overlapped with periods of anomalous atmospheric and oceanographic conditions, and there is not yet a consensus on the cause(s). Genomic data may reveal underlying molecular signatures that implicate a subset of factors and, thus, clarify past events while also setting the scene for effective restoration efforts. To advance this goal, we used Pacific Biosciences HiFi long sequencing reads and Dovetail Omni-C proximity reads to generate a highly contiguous genome assembly that was then annotated using RNA-seq-informed gene prediction. The genome assembly is 484 Mb long, with contig N50 of 1.9 Mb, scaffold N50 of 21.8 Mb, BUSCO completeness score of 96.1%, and 22 major scaffolds consistent with prior evidence that sea star genomes comprise 22 autosomes. These statistics generally fall between those of other recently assembled chromosome-scale assemblies for two species in the distantly related asteroid genus Pisaster. These novel genomic resources for P. helianthoides will underwrite population genomic, comparative genomic, and phylogenomic analyses-as well as their integration across scales-of SSW and environmental stressors.

Embodying cognitive ethology.

Cognitive psychology considers the environment as providing information, not affecting fundamental information processes. Thus, cognitive psychology's traditional paradigms study responses to precisely timed stimuli in controlled environments. However, new research demonstrates the environment does influence cognitive processes and offers cognitive psychology new methods. The authors examine one such proposal: cognitive ethology. Cognitive ethology improves cognitive psychology's ecological validity through first drawing inspiration from robust phenomena in the real world, then moving into the lab to test those phenomena. To support such methods, cognitive ethologists appeal to embodied cognition, or 4E cognition, for its rich relationships between agents and environments. However, the authors note while cognitive ethology focuses on new methods (epistemology) inspired by embodied cognition, it preserves most traditional assumptions about cognitive processes (ontology). But embodied cognition-particularly its radical variants-also provides strong ontological challenges to cognitive psychology, which work against cognitive ethology. The authors argue cognitive ethology should align with the ontology of less radical embodied cognition, which produces epistemological implications, offering alternative methodologies. For example, cognitive ethology can explore differences between real-world and lab studies to fully understand how cognition depends on environments.

How Do Artificial Neural Networks Classify Musical Triads? A Case Study in Eluding Bonini's Paradox.

How might artificial neural networks (ANNs) inform cognitive science? Often cognitive scientists use ANNs but do not examine their internal structures. In this paper, we use ANNs to explore how cognition might represent musical properties. We train ANNs to classify musical chords, and we interpret network structure to determine what representations ANNs discover and use. We find connection weights between input units and hidden units can be described using Fourier phase spaces, a representation studied in musical set theory. We find the total signal coming through these weighted connection weights is a measure of the similarity between two Fourier structures: the structure of the hidden unit's weights and the structure of the stimulus. This is surprising because neither of these Fourier structures is computed by the hidden unit. We then show how output units use such similarity measures to classify chords. However, we also find different types of units-units that use different activation functions-use this similarity measure very differently. This result, combined with other findings, indicates that while our networks are related to the Fourier analysis of musical sets, they do not perform Fourier analyses of the kind usually described in musical set theory. Our results show Fourier representations of music are not limited to musical set theory. Our results also suggest how cognitive psychologists might explore Fourier representations in musical cognition. Critically, such theoretical and empirical implications require researchers to understand how network structure converts stimuli into responses.

A Decade of Death and Other Dynamics: Deepening Perspectives on the Diversity and Distribution of Sea Stars and Wasting.

AbstractMass mortality events provide valuable insight into biological extremes and also ecological interactions more generally. The sea star wasting epidemic that began in 2013 catalyzed study of the microbiome, genetics, population dynamics, and community ecology of several high-profile species inhabiting the northeastern Pacific but exposed a dearth of information on the diversity, distributions, and impacts of sea star wasting for many lesser-known sea stars and a need for integration across scales. Here, we combine datasets from single-site to coast-wide studies, across time lines from weeks to decades, for 65 species. We evaluated the impacts of abiotic characteristics hypothetically associated with sea star wasting (sea surface temperature, pelagic primary productivity, upwelling wind forcing, wave exposure, freshwater runoff) and species characteristics (depth distribution, developmental mode, diet, habitat, reproductive period). We find that the 2010s sea star wasting outbreak clearly affected a little over a dozen species, primarily intertidal and shallow subtidal taxa, causing instantaneous wasting prevalence rates of 5%-80%. Despite the collapse of some populations within weeks, environmental and species variation protracted the outbreak, which lasted 2-3 years from onset until declining to chronic background rates of ∼2% sea star wasting prevalence. Recruitment began immediately in many species, and in general, sea star assemblages trended toward recovery; however, recovery was heterogeneous, and a marine heatwave in 2019 raised concerns of a second decline. The abiotic stressors most associated with the 2010s sea star wasting outbreak were elevated sea surface temperature and low wave exposure, as well as freshwater discharge in the north. However, detailed data speaking directly to the biological, ecological, and environmental cause(s) and consequences of the sea star wasting outbreak remain limited in scope, unavoidably retrospective, and perhaps always indeterminate. Redressing this shortfall for the future will require a broad spectrum of monitoring studies not less than the taxonomically broad cross-scale framework we have modeled in this synthesis.

Species' attributes predict the relative magnitude of ecological and genetic recovery following mass mortality.

Theoretically, species' characteristics should allow estimation of dispersal potential and, in turn, explain levels of population genetic differentiation. However, a mismatch between traits and genetic patterns is often reported for marine species, and interpreted as evidence that life-history traits do not influence dispersal. Here, we couple ecological and genomic methods to test the hypothesis that species with attributes favouring greater dispersal potential-e.g., longer pelagic duration, higher fecundity and larger population size-have greater realized dispersal overall. We used a natural experiment created by a large-scale and multispecies mortality event which created a "clean slate" on which to study recruitment dynamics, thus simplifying a usually complex problem. We surveyed four species of differing dispersal potential to quantify the abundance and distribution of recruits and to genetically assign these recruits to probable parental sources. Species with higher dispersal potential recolonized a broader extent of the impacted range, did so more quickly and recovered more genetic diversity than species with lower dispersal potential. Moreover, populations of taxa with higher dispersal potential exhibited more immigration (71%-92% of recruits) than taxa with lower dispersal potential (17%-44% of recruits). By linking ecological with genomic perspectives, we demonstrate that a suite of interacting life-history and demographic attributes do influence species' realized dispersal and genetic neighbourhoods. To better understand species' resilience and recovery in this time of global change, integrative eco-evolutionary approaches are needed to more rigorously evaluate the effect of dispersal-linked attributes on realized dispersal and population genetic differentiation.

A chromosome-level reference genome for the giant pink sea star, Pisaster brevispinus, a species severely impacted by wasting.

Efforts to protect the ecologically and economically significant California Current Ecosystem from global change will greatly benefit from data about patterns of local adaptation and population connectivity. To facilitate that work, we present a reference-quality genome for the giant pink sea star, Pisaster brevispinus, a species of ecological importance along the Pacific west coast of North America that has been heavily impacted by environmental change and disease. We used Pacific Biosciences HiFi long sequencing reads and Dovetail Omni-C proximity reads to generate a highly contiguous genome assembly of 550 Mb in length. The assembly contains 127 scaffolds with a contig N50 of 4.6 Mb and a scaffold N50 of 21.4 Mb; the BUSCO completeness score is 98.70%. The P. brevispinus genome assembly is comparable to the genome of the congener species P. ochraceus in size and completeness. Both Pisaster assemblies are consistent with previously published karyotyping results showing sea star genomes are organized into 22 autosomes. The reference genome for P. brevispinus is an important first step toward the goal of producing a comprehensive, population genomics view of ecological and evolutionary processes along the California coast. This resource will help scientists, managers, and policy makers in their task of understanding and protecting critical coastal regions from the impacts of global change.

Reference genome for the California ribbed mussel, Mytilus californianus, an ecosystem engineer.

The California ribbed mussel, Mytilus californianus, is an ecosystem engineer crucial for the survival of many marine species inhabiting the intertidal zone of California. Here, we describe the first reference genome for M. californianus and compare it to previously published genomes from three other Mytilus species: M. edulis, M. coruscus, and M. galloprovincialis. The M. californianus reference genome is 1.65 Gb in length, with N50 sequence length of 118 Mb, and an estimated 86.0% complete single copy genes. Compared with the other three Mytilus species, the M. californianus genome assembly is the longest, has the highest N50 value, and the highest percentage complete single copy genes. This high-quality genome assembly provides a foundation for population genetic analyses that will give insight into future conservation work along the coast of California.

Preliminary Evaluation of the Effect of Mechanotactile Feedback Location on Myoelectric Prosthesis Performance Using a Sensorized Prosthetic Hand.

A commonly cited reason for the high abandonment rate of myoelectric prostheses is a lack of grip force sensory feedback. Researchers have attempted to restore grip force sensory feedback by stimulating the residual limb's skin surface in response to the prosthetic hand's measured grip force. Recent work has focused on restoring natural feedback to the missing digits directly through invasive surgical procedures. However, the functional benefit of utilizing somatotopically matching feedback has not been evaluated. In this paper, we propose an experimental protocol centered on a fragile object grasp and lift task using a sensorized myoelectric prosthesis to evaluate sensory feedback techniques. We formalized a suite of outcome measures related to task success, timing, and strategy. A pilot study (n = 3) evaluating the effect of utilizing a somatotopically accurate feedback stimulation location in able-bodied participants was conducted to evaluate the feasibility of the standardized platform, and to inform future studies on the role of feedback stimulation location in prosthesis use. Large between-participant effect sizes were observed in all outcome measures, indicating that the feedback location likely plays a role in myoelectric prosthesis performance. The success rate decreased, and task timing and task focus metrics increased, when using somatotopically-matched feedback compared to non-somatotopically-matched feedback. These results were used to conduct a power analysis, revealing that a sample size of n = 8 would be sufficient to achieve significance in all outcome measures.

Recurrent Convolutional Neural Networks as an Approach to Position-Aware Myoelectric Prosthesis Control.

OBJECTIVE: Persons with normal arm function can perform complex wrist and hand movements over a wide range of limb positions. However, for those with transradial amputation who use myoelectric prostheses, control across multiple limb positions can be challenging, frustrating, and can increase the likelihood of device abandonment. In response, the goal of this research was to investigate convolutional neural network (RCNN)-based position-aware myoelectric prosthesis control strategies. METHODS: Surface electromyographic (EMG) and inertial measurement unit (IMU) signals, obtained from 16 non-disabled participants wearing two Myo armbands, served as inputs to RCNN classification and regression models. Such models predicted movements (wrist flexion/extension and forearm pronation/supination), based on a multi-limb-position training routine. RCNN classifiers and RCNN regressors were compared to linear discriminant analysis (LDA) classifiers and support vector regression (SVR) regressors, respectively. Outcomes were examined to determine whether RCNN-based control strategies could yield accurate movement predictions, while using the fewest number of available Myo armband data streams. RESULTS: An RCNN classifier (trained with forearm EMG data, and forearm and upper arm IMU data) predicted movements with 99.00% accuracy (versus the LDA's 97.67%). An RCNN regressor (trained with forearm EMG and IMU data) predicted movements with R2 values of 84.93% for wrist flexion/extension and 84.97% for forearm pronation/supination (versus the SVR's 77.26% and 60.73%, respectively). The control strategies that employed these models required fewer than all available data streams. CONCLUSION: RCNN-based control strategies offer novel means of mitigating limb position challenges. SIGNIFICANCE: This research furthers the development of improved position-aware myoelectric prosthesis control.

Minor Genetic Consequences of a Major Mass Mortality: Short-Term Effects in Pisaster ochraceus.

AbstractMass mortality events are increasing globally in frequency and magnitude, largely as a result of human-induced change. The effects of these mass mortality events, in both the long and short term, are of imminent concern because of their ecosystem impacts. Genomic data can be used to reveal some of the population-level changes associated with mass mortality events. Here, we use reduced-representation sequencing to identify potential short-term genetic impacts of a mass mortality event associated with a sea star wasting outbreak. We tested for changes in the population for genetic differentiation, diversity, and effective population size between pre-sea star wasting and post-sea star wasting populations of Pisaster ochraceus-a species that suffered high sea star wasting-associated mortality (75%-100% at 80% of sites). We detected no significant population-based genetic differentiation over the spatial scale sampled; however, the post-sea star wasting population tended toward more differentiation across sites than the pre-sea star wasting population. Genetic estimates of effective population size did not detectably change, consistent with theoretical expectations; however, rare alleles were lost. While we were unable to detect significant population-based genetic differentiation or changes in effective population size over this short time period, the genetic burden of this mass mortality event may be borne by future generations, unless widespread recruitment mitigates the population decline. Prior results from P. ochraceus indicated that natural selection played a role in altering allele frequencies following this mass mortality event. In addition to the role of selection found in a previous study on the genomic impacts of sea star wasting on P. ochraceus, our current study highlights the potential role the stochastic loss of many individuals plays in altering how genetic variation is structured across the landscape. Future genetic monitoring is needed to determine long-term genetic impacts in this long-lived species. Given the increased frequency of mass mortality events, it is important to implement demographic and genetic monitoring strategies that capture baselines and background dynamics to better contextualize species' responses to large perturbations.

Is It in the Stars? Exploring the Relationships between Species' Traits and Sea Star Wasting Disease.

AbstractAn explanation for variation in impacts of sea star wasting disease across asteroid species remains elusive. Although various traits have been suggested to play a potential role in sea star wasting susceptibility, currently we lack a thorough comparison that explores how life-history and natural history traits shape responses to mass mortality across diverse asteroid taxa. To explore how asteroid traits may relate to sea star wasting, using available data and recognizing the potential for biological correlations to be driven by phylogeny, we generated a supertree, tested traits for phylogenetic association, and evaluated associations between traits and sea star wasting impact. Our analyses show no evidence for a phylogenetic association with sea star wasting impact, but there does appear to be phylogenetic association for a subset of asteroid life-history traits, including diet, substrate, and reproductive season. We found no relationship between sea star wasting and developmental mode, diet, pelagic larval duration, or substrate but did find a relationship with minimum depth, reproductive season, and rugosity (or surface complexity). Species with the greatest sea star wasting impacts tend to have shallower minimum depth distributions, they tend to have their median reproductive period 1.5 months earlier, and they tend to have higher rugosities relative to species less affected by sea star wasting. Fully understanding sea star wasting remains challenging, in part because dramatic gaps still exist in our understanding of the basic biology and phylogeny of asteroids. Future studies would benefit from a more robust phylogenetic understanding of sea stars, as well as leveraging intra- and interspecific comparative transcriptomics and genomics to elucidate the molecular pathways responding to sea star wasting.

Landscape analyses using eDNA metabarcoding and Earth observation predict community biodiversity in California.

Ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level patterns and that can be applied rapidly across space and time. Using modern ecological models and community science, we integrate environmental DNA and Earth observations to produce a time snapshot of regional biodiversity patterns and provide multi-scalar community-level characterization. We collected 278 samples in spring 2017 from coastal, shrub, and lowland forest sites in California, a complex ecosystem and biodiversity hotspot. We recovered 16,118 taxonomic entries from eDNA analyses and compiled associated traditional observations and environmental data to assess how well they predicted alpha, beta, and zeta diversity. We found that local habitat classification was diagnostic of community composition and distinct communities and organisms in different kingdoms are predicted by different environmental variables. Nonetheless, gradient forest models of 915 families recovered by eDNA analysis and using BIOCLIM variables, Sentinel-2 satellite data, human impact, and topographical features as predictors, explained 35% of the variance in community turnover. Elevation, sand percentage, and photosynthetic activities (NDVI32) were the top predictors. In addition to this signal of environmental filtering, we found a positive relationship between environmentally predicted families and their numbers of biotic interactions, suggesting environmental change could have a disproportionate effect on community networks. Together, these analyses show that coupling eDNA with environmental predictors including remote sensing data has capacity to test proposed Essential Biodiversity Variables and create new landscape biodiversity baselines that span the tree of life.

Influence of Lipophilicity on the Antibacterial Activity of Polymyxin Derivatives and on Their Ability to Act as Potentiators of Rifampicin.

Novel polymyxin derivatives are often classified either as having direct activity against Gram-negative pathogens or as compounds inactive in their own right, which through permeabilization of the outer membrane act as potentiators of other antibiotics. Here, we report the systematic investigation of the influence of lipophilicity on microbiological activity (including against strains with reduced susceptibility to polymyxins), potentiation of rifampicin, and in vitro toxicity within a series of next-generation polymyxin nonapeptides. We demonstrate that the lipophilicity at the N-terminus and amino acids 6 and 7 in the cyclic peptide core is interchangeable and that the activity, ability to potentiate, and cytotoxicity all appear to be primarily driven by overall lipophilicity. Our work also suggests that the characterization of a polymyxin molecule as either a direct acting compound or a potentiator is more of a continuum that is strongly influenced by lipophilicity rather than as a result of fundamentally different modes-of-action.

Using a lake sediment record to infer the long-term history of cyanobacteria and the recent rise of an anatoxin producing Dolichospermum sp.

Lakes that experience recurrent toxic cyanobacterial harmful algae blooms (cyanoHABS) are often subject to cultural eutrophication, where landscape development and upland activities increase the nutrient inputs to the water column and fuel cyanoHABS. Few studies have focused on the response of a lake to nutrient inputs for which the natural geomorphic setting predisposes a nutrient-rich water column to already support abundant cyanobacteria. Here, we present a sediment core record from a lake surrounded by parkland that experiences recurrent cyanoHABs which produce dangerous levels of the neurotoxin, anatoxin-a, impacting the recreational use of the lake and park. Using photoautotrophic pigments in the sediment record, we establish cyanobacteria have long been part of the diverse and abundant phytoplankton community within the lake. Despite this long record, shotgun metagenome and other DNA analyses of the sediment record suggest that the current anatoxin-a producer Dolichospermum sp. WA102 only emerged to dominate the cyanobacterial community in the mid-1990s. A period of lakeshore farming that finished in the 1950s-1960s and possibly the stocking of rainbow trout fry (1970-2016) coincide with a progressive shift in primary production, together with a change in bacterial communities. Based on the history of the lake and contemporary ecology of Dolichospermum, we propose that the legacy of nutrient inputs and changes in nutrient cycling within the lake has encouraged the development of an ecosystem where the toxin producing Dolichospermum sp WA102 is highly competitive. Understanding the historical presence of cyanobacteria in the lake provides a context for current-day management strategies of cyanoHABs.

Lassa Virus Circulation in Small Mammal Populations in Bo District, Sierra Leone.

Lassa fever is a viral hemorrhagic fever caused by the Lassa virus LASV, which was first isolated in the rodent Mastomys natalensis in 1974 in Kenema, Sierra Leone. As little is known about the abundance and the presence of LASV in rodents living in the Bo area, we carried out a small mammal longitudinal population survey. A standardized trapping session was performed in various habitats and seasons in six villages over two years (2014-2016) and samples collected were tested for arenavirus IgG and LASV. A Bayesian phylogenetic analysis was performed on sequences identified by PCR. A total of 1490 small mammals were collected, and 16 rodent species were identified, with M. natalensis (355, 24%) found to be the most prevalent species. Forty-one (2.8%) samples were IgG positive, and 31 of these were trapped in homes and 10 in surrounding vegetation. Twenty-nine of 41 seropositive rodents were M. natalensis. We detected four LASV by PCR in two villages, all found in M. natalensis. Phylogenetic analysis showed that the sequences were distributed within the Sierra Leonean clade within lineage IV, distinguishing a Bo sub-clade older than a Kenema sub-clade. Compared to other settings, we found a low abundance of M. natalensis and a low circulation of LASV in rodents in villages around Bo district.

Defining the design requirements for an assistive powered hand exoskeleton: A pilot explorative interview study and case series.

BACKGROUND: Powered hand exoskeletons are an emerging technology that have shown promise in assisting individuals with impaired hand function. A number of hand exoskeleton designs have been described in the literature; however, the majority have not been supported by patient-oriented criteria. OBJECTIVE: The aim of this study was to define preliminary end-user needs and expectations for an assistive hand exoskeleton. STUDY DESIGN: Explorative interview and case series. METHODS: Six clinicians and eight individuals with impaired hand function were interviewed in small groups or individually. A standardized list of questions was used to elicit feedback on specific design criteria or promote the discovery of new criteria. In addition, three participants with impaired hand function returned for a second session where hand characteristics, such as range of motion and force required to flex/extend fingers, were recorded to further quantify design requirements. RESULTS: Interview responses indicated that there was general consensus among participants on criteria relating to important grasp patterns, grip strength, wear time, and acceptable bulk/weight. However, interview responses and hand characteristics also revealed important differences between individuals with impaired hand function. CONCLUSION: Qualitative and quantitative data were collected to develop an understanding of end-user design requirements for assistive hand exoskeletons. Although the data collected were helpful in identifying some preliminary criteria, differences between participants exist and identifying a universal set of criteria applicable across individuals with impaired hand function is challenging. This work reinforces the importance of involving users of rehabilitation technology in the device development process.

Demographic, Environmental, and Phenotypic Change but Genetic Consistency in the Jellyfish Mastigias papua.

AbstractSpatiotemporal environmental change can produce phenotypic differences within and between populations. For scyphozoans, the effect of environmental variation on phenotype has been unclear because of multiple challenges, including difficulties delimiting populations. Marine lakes, bodies of seawater entirely surrounded by land, provide an opportunity to study discrete populations and capture responses to perturbations. We use this opportunity to compare Mastigias papua (Lesson, 1830) medusae before and after a demographic and environmental perturbation. We reconstructed mitochondrial DNA haplotype networks, measured morphological variation, and assessed swimming behavior of pre- and post-perturbation samples to evaluate two hypotheses about the source of variation: recolonization from an alternate location or endemic phenotypic variation. We found significant differences between samples in morphology (F > 9.5, P < 0.001) and in two of three behaviors (F > 8.45, P < 0.005) but no substantial genetic differentiation (ΦST = 0.03, P = 0.09). We reject the hypothesis of recolonization because pre- and post-perturbation lake medusae were genetically similar to each other and also significantly different from any potential source locations (ΦST > 0.48, P > 0.001). We could not distinguish the source of endemic variation; this will require genomic or experimental analyses. Increasing climatic variability emphasizes the need for understanding population-level responses to environmental change and how responses may be modified by sources of intraspecific variation.

An Assay for Periplasm Entry Advances the Development of Chimeric Peptide Antibiotics.

The treatment of infection by Gram-negative bacteria is increasingly challenging as resistance to existing antibiotics spreads. Constrained peptides, selected for high target specificity and affinity via library display technologies, are an emerging therapeutic modality in many disease areas and may be a fertile source of new antibiotics. Currently, the utility of constrained peptides and other large molecules as antibiotics is limited by the outer membrane (OM) barrier of Gram-negative bacteria. However, the addition of certain moieties to large molecules can confer the ability to cross the OM; these moieties function as intramolecular trans-OM "vectors". Here, we present a method to systematically assess the carrying capacity of candidate trans-OM vectors using a real-time luminescence assay ("SLALOM", Split Luciferase Assay for Live monitoring of Outer Membrane transit), reporting on periplasmic entry. We demonstrate the usefulness of our tools by constructing a 3800 Da chimeric compound composed of a constrained bicyclic peptide (Bicycle) with a periplasmic target, linked to an intramolecular peptide vector; the resulting chimera is a broad-spectrum inhibitor of pathogenic Gram-negative bacterial growth.

Artificial Neural Networks Solve Musical Problems With Fourier Phase Spaces.

How does the brain represent musical properties? Even with our growing understanding of the cognitive neuroscience of music, the answer to this question remains unclear. One method for conceiving possible representations is to use artificial neural networks, which can provide biologically plausible models of cognition. One could train networks to solve musical problems, and then study how these networks encode musical properties. However, researchers rarely examine network structure in detail because networks are difficult to interpret, and because many assume that networks capture informal or subsymbolic properties. Here we report very high correlations between network connection weights and discrete Fourier phase spaces used to represent musical sets. This is remarkable because there is no clear mathematical relationship between network learning rules and discrete Fourier analysis. That networks discover Fourier phase spaces indicates that these spaces have an important role to play outside of formal music theory. Finding phase spaces in networks raises the strong possibility that Fourier components are possible codes for musical cognition.