Biology subjects

Cohen, J. D.

Publications and source records attributed to Cohen, J. D..

At least 37 records · Page 2Linked to original sources

bioRxiv2021

Biphasic Control of Cell Expansion by Auxin Coordinates Etiolated Seedling Development

Seedling emergence is critical for food security. It requires rapid hypocotyl elongation and apical hook formation, both of which are mediated by regulated cell expansion. How these events are coordinated in etiolated seedlings is unclear. Here, we show that biphasic control of cell expansion by the phytohormone auxin underlies this process. Shortly after germination, high auxin levels restrain elongation. This provides a temporal window for apical hook formation, involving a gravity-induced auxin maximum on the eventual concave side of the hook, triggering PP2C.D1controlled asymmetrical H+-ATPase activity, resulting in differential cell elongation. Subsequently, auxin concentrations decline acropetally and switch from restraining to promoting elongation, driving hypocotyl elongation. Our findings elucidate how differential auxin concentrations throughout the hypocotyl coordinate etiolated development, leading to successful soil emergence. One-Sentence SummaryAuxin concentration-dependent cell expansion coordinates hypocotyl elongation and apical hook development for soil emergence.

plant biology↗

bioRxiv2021

The C. elegans PTCHD homolog PTR-4 is required for proper organization of the pre-cuticular apical extracellular matrix

The Patched-related (PTR) superfamily of transmembrane proteins can transport lipids or other hydrophobic molecules across cell membranes. While the hedgehog receptor Patched has been intensively studied, much less is known about the biological roles of other PTR or Patched domain (PTCHD) family members. C. elegans has a large number of PTR/PTCHD proteins, despite lacking a canonical hedgehog pathway. Here, we show that PTR-4 promotes the assembly of the pre-cuticle apical extracellular matrix (aECM), a transient and molecularly distinct aECM that precedes and patterns the later collagenous cuticle or exoskeleton. ptr-4 mutants share many phenotypes with pre-cuticle mutants, including defects in eggshell dissolution, tube shaping, alae (cuticle ridge) structure, and cuticle barrier function. PTR-4 localizes to the apical side of a subset of outward-facing epithelia, in a cyclical manner that peaks when pre-cuticle matrix is present. Finally, PTR-4 acts in a cell non-autonomous manner to properly localize the secreted ZP domain protein LET-653 to the pre-cuticle aECM. We propose that PTR-4 exports lipids or other hydrophobic components of the pre-cuticle aECM.

cell biology↗

bioRxiv2021

Exonic Disruption Facilitates Antiviral CRISPR-Cas9 Activity for Multistrain HIV-1 Elimination

A barrier to HIV-1 cure rests in the persistence of proviral DNA in infected CD4+ leukocytes. The high mutation rate of HIV-1 gives rise to numerous circulating strains with increased capacity for immune evasion and antiretroviral drug resistance. To facilitate viral elimination while accounting for this diversity, we propose genetic inactivation of proviral DNA with CRISPR-spCas9. We designed a library of "mosaic gRNAs" against a HIV-1 consensus sequence constructed from 4004 clinical strains, targeting the viral transcriptional regulator tat. Testing in 7 HIV-1 transmitted founder strains led, on average, to viral reductions of 82% with tandem TatD and TatE (TatDE) treatment. No off-target cleavages were recorded. Lentiviral transduction of TatDE attenuated latency reversal by 94% in HIV-infected, transcriptionally silent ACH2 T cells. In all, TatDE guide RNAs successfully disrupted 5 separate HIV-1 exons (tat1-2/rev1-2/gp41) providing a pathway for CRISPR-directed HIV-1 cure therapies. Significance StatementOver 38 million individuals worldwide are infected with HIV-1, which necessitates lifelong dependence on antiretroviral therapy (ART) to prevent viral replication that leads to AIDS. Efforts to rid hosts of HIV-1 are limited by the virus abilities to integrate proviral DNA in nuclei, mutate their genomes, and lay dormant for decades during ART treatment. We developed mosaic guide RNAs, TatD and TatE, for CRISPR-Cas9 that recognize the majority of known HIV-1 strains and inactivate 94% of proviral DNA in latently infected cells. Tandem TatDE-CRISPR inactivation of 5 viral exons (tat1-2, rev1-2, and gp41), which blocked HIV-1 replication for 28 days in CD4+ T cells without unwanted editing to the host genome, may serve as a viable strategy for HIV cure.

microbiology↗

bioRxiv2020

Sculpting New Visual Concepts into the Human Brain

Learning requires changing the brain. This typically occurs through experience, study, or instruction. We report a proof-of-concept for a new way for humans to acquire visual knowledge by directly sculpting activity patterns in the human brain that mirror those expected to arise through learning. We used a non-invasive technique (closed-loop real-time functional magnetic resonance imaging neurofeedback) to create new categories of visual objects in the brain, without the participants explicit awareness. After neural sculpting, participants exhibited behavioral and neural biases for the sculpted, but not for the control categories. The ability to sculpt new perceptual distinctions in the human brain offers a new paradigm for human fMRI research that allows for non-invasive, causal testing of the link between neural representations and behavior. As such, beyond its current application to perception, our work potentially has broad relevance to other domains of cognition such as decision-making, memory, and motor control. Significance StatementObjects that belong to the same category tend to elicit similar patterns of brain activity. Here we reverse this mapping and ask whether neural similarity is sufficient to induce increased perceptual discrimination and categorical perception. We do this by using real-time fMRI to modify neural representations of objects in high-level visual cortex. Participants viewed an object and received closed-loop neurofeedback that pushed them to represent the object more similarly to a brain activity pattern we chose for that category. After successfully self-modulating their brain activity, participants began to perceive objects assigned to the same brain pattern as more categorically distinct from those assigned to a different brain pattern. These findings open a new avenue for understanding and accelerating human learning.

neuroscience↗

bioRxiv2020

The Temporal Dynamics of Opportunity Costs: A Normative Account of Cognitive Fatigue and Boredom

Cognitive fatigue and boredom are two phenomenological states that reflect overt task disengagement. In this paper, we present a rational analysis of the temporal structure of controlled behavior, which provides a formal account of these phenomena. We suggest that in controlling behavior, the brain faces competing behavioral and computational imperatives, and must balance them by tracking their opportunity costs over time. We use this analysis to flesh out previous suggestions that feelings associated with subjective effort, like cognitive fatigue and boredom, are the phenomenological counterparts of these opportunity cost measures, instead of reflecting the depletion of resources as has often been assumed. Specifically, we propose that both fatigue and boredom reflect the competing value of particular options that require foregoing immediate reward but can improve future performance: Fatigue reflects the value of offline computation (internal to the organism) to improve future decisions, while boredom signals the value of exploration (external in the world). We demonstrate that these accounts provide a mechanistically explicit and parsimonious account for a wide array of findings related to cognitive control, integrating and reimagining them under a single, formally rigorous framework.

neuroscience↗

bioRxiv2020

Closed-loop fMRI neurofeedback to reduce negative attentional bias in depression

Depressed individuals show an attentional bias toward negatively valenced stimuli and thoughts. Here we present a novel closed-loop neurofeedback procedure that seeks to remediate this bias. Internal attentional states were detected by applying machine learning techniques to fMRI data in real-time, and externalized using a visually presented stimulus that the participant could learn to control. We trained 15 depressed and 12 healthy control participants over three fMRI sessions, preceded and followed by behavioral and clinical assessments. Initially, depressed participants were more likely than non-depressed participants to get "stuck" in negative attentional states, but this diminished with neurofeedback training relative to controls. Depression severity also decreased from pre- to post-training. These results demonstrate that our method is sensitive to the negative attentional bias in depressed individuals, and its reduction after training showcases the potential of this method as a treatment in the future.

neuroscience↗

bioRxiv2020

A C. elegans Zona Pellucida domain protein functions via its ZPc domain

Zona Pellucida domain (ZP) proteins are critical components of the bodys external-most protective layers, apical extracellular matrices (aECMs). Although their loss or dysfunction is associated with many diseases, it remains unclear how ZP proteins assemble in aECMs. Current models suggest that ZP proteins polymerize via their ZPn subdomains, while ZPc subdomains modulate ZPn behavior. Using the model organism C. elegans, we investigated the aECM assembly of one ZP protein, LET-653, which shapes several tubes. Contrary to prevailing models, we find that LET-653 localizes and functions via its ZPc domain. Furthermore, the ZPc domain is inhibited by the ZPn domain and cleavage of the LET-653 C-terminus relieves this inhibition. In vitro, the ZPc, but not ZPn, domain formed crystalline aggregates. These data offer a new model for ZP function whereby the ZPc domain is primarily responsible for matrix incorporation and tissue shaping.

genetics↗

bioRxiv2020

A multi-layered and dynamic apical extracellular matrix shapes the vulva lumen in Caenorhabditis elegans

Biological tubes must develop and maintain their proper diameter in order to transport materials efficiently. These tubes are molded and protected in part by apical extracellular matrices (aECMs) that line their lumens. Despite their importance, aECMs are difficult to image in vivo and therefore poorly understood. The C. elegans vulva has been a paradigm for understanding many aspects of organogenesis. Here we describe the vulva luminal matrix, which contains chondroitin proteoglycans, Zona Pellucida (ZP) domain proteins, and other glycoproteins and lipid transporters related to those in mammals. Confocal and transmission electron microscopy revealed, with unprecedented detail, a complex and dynamic aECM. Different matrix factors assemble on the apical surfaces of each vulva cell type, with clear distinctions seen between Ras-dependent (1{degrees}) and Notch-dependent (2{degrees}) cell types. Genetic perturbations suggest that chondroitin and other aECM factors together generate a structured scaffold that both expands and constricts lumen shape.

developmental biology↗

bioRxiv2019

Human inference in changing environments

To make informed decisions in natural environments that change over time, humans must update their beliefs as new observations are gathered. Studies exploring human inference as a dynamical process that unfolds in time have focused on situations in which the statistics of observations are history-independent. Yet temporal structure is everywhere in nature, and yields history-dependent observations. Do humans modify their inference processes depending on the latent temporal statistics of their observations? We investigate this question experimentally and theoretically using a change-point inference task. We show that humans adapt their inference process to fine aspects of the temporal structure in the statistics of stimuli. As such, humans behave qualitatively in a Bayesian fashion, but, quantitatively, deviate away from optimality. Perhaps more importantly, humans behave suboptimally in that their responses are not deterministic, but variable. We show that this variability itself is modulated by the temporal statistics of stimuli. To elucidate the cognitive algorithm that yields this behavior, we investigate a broad array of existing and new models that characterize different sources of suboptimal deviations away from Bayesian inference. While models with output noise that corrupts the response-selection process are natural candidates, human behavior is best described by sampling-based inference models, in which the main ingredient is a compressed approximation of the posterior, represented through a modest set of random samples and updated over time. This result comes to complement a growing literature on sample-based representation and learning in humans.

neuroscience↗

bioRxiv2019

Assessing aneuploidy with repetitive element sequencing.

We report a sensitive PCR-based assay that can detect aneuploidy in samples containing as little as 3 picograms of DNA. Using a single primer pair, we amplified [~]750,000 amplicons distributed throughout the genome Aneuploidy was detected in 49% of liquid biopsies from a total of 883 non-metastatic cancers of eight different types. Combining aneuploidy with somatic mutation detection and eight standard protein biomarkers yielded a median sensitivity of 80% at 99% specificity.

cancer biology↗

bioRxiv2019

Rational use of Episodic and Working Memory: A Normative Account of Prospective Memory

AO_SCPLOWBSTRACTC_SCPLOWHumans often simultaneously pursue multiple plans at different time scales. The successful realization of non-immediate plans (e.g., post package after work) requires keeping track of a future plan while accomplishing other intermediate tasks (e.g., write a paper), a capacity known as prospective memory. This capacity requires the integration of noisy evidence from perceptual input with evidence from short-term working memory (WM) and longer-term or episodic memory (LTM/EM). Here we formulate a set of dual-task problems in empirical studies of prospective memory as problems of computational rationality, and ask how a rational model should exploit noisy perception and memory to maximize payoffs. The model combines reinforcement learning (optimal action selection) with evidence accumulation (optimal inference) in order to derive good decision parameters for optimal task performance (i.e., performing an ongoing task while monitoring for a cue that triggers executing a second prospective task). We compare model behavior to key accuracy and reaction time phenomena in human performance. Thus, we offer a normative approach to theorizing and modeling these phenomena without assumptions about mechanisms of attention or retrieval. This approach can be extended to study meta-parameters governing the boundedly rational use of memory in planned action in health, as well as compensatory mnemonic strategies that may be rational responses to disturbances of these mechanisms in neuropsychiatric disorders.

animal behavior and cognition↗

bioRxiv2019

A Comparison of Non-human Primate and Deep Reinforcement Learning Agent Performance in a Virtual Pursuit-Avoidance Task

We compare the performance of non-human primates and deep reinforcement learning agents in a virtual pursuit-avoidance task, as part of an effort to understand the role that cognitive control plays in the deeply evolved skill of chase and escape behavior. Here we train two agents, a deep Q network and an actor-critic model, on a video game in which the player must capture a prey while avoiding a predator. A previously trained rhesus macaque performed well on this task, and in a manner that obeyed basic principles of Newtonian physics. We sought to compare the principles learned by artificial agents with those followed by the animal, as determined by the ability of one to predict the other. Our findings suggest that the agents learn primarily 1st order physics of motion, while the animal exhibited abilities consistent with the 2nd order physics of motion. We identify scenarios in which the actions taken by the animal and agents were consistent as well as ones in which they differed, including some surprising strategies exhibited by the agents. Finally, we remark on how the differences between how the agents and the macaque learn the task may affect their peak performance as well as their ability to generalize to other tasks.

neuroscience↗

bioRxiv2018

Rats exhibit similar biases in foraging and intertemporal choice tasks

Animals, including humans, consistently exhibit myopia in two different contexts: foraging, in which they harvest locally beyond what is predicted by optimal foraging theory, and intertemporal choice, in which they exhibit a preference for immediate vs. delayed rewards beyond what is predicted by rational (exponential) discounting. Despite the similarity in behavior between these two contexts, previous efforts to reconcile these observations in terms of a consistent pattern of time preferences have failed. Here, via extensive behavioral testing and quantitative modeling, we show that rats exhibit similar time preferences in both contexts: they prefer immediate vs. delayed rewards and they are sensitive to opportunity costs -- delays to future decisions. Further, a quasi-hyperbolic discounting model, a form of hyperbolic discounting with separate components for short-and long-term rewards, explains individual rats time preferences across both contexts, providing evidence for a common mechanism for myopic behavior in foraging and intertemporal choice.

animal behavior and cognition↗

bioRxiv2018

On the adaptive behavior of head-fixed flies navigating in two-dimensional, visual virtual reality

A navigating animals sensory experience is shaped not just by its surroundings, but by its movements within them, which in turn are influenced by its past experiences. Studying the intertwined roles of sensation, experience and directed action in navigation has been made easier by the development of virtual reality (VR) environments for head-fixed animals, which allow for quantitative measurements of behavior in well-controlled sensory conditions. VR has long featured in studies of Drosophila melanogaster, but these experiments have typically relied on one-dimensional (1D) VR, effectively allowing the fly to change only its heading in a visual scene, and not its position. Here we explore how flies navigate in a two-dimensional (2D) visual VR environment that more closely resembles their experience during free behavior. We show that flies interaction with landmarks in 2D environments cannot be automatically derived from their behavior in simpler 1D environments. Using a novel paradigm, we then demonstrate that flies in 2D VR adapt their behavior in a visual environment in response to optogenetically delivered appetitive and aversive stimuli. Much like free-walking flies after encounters with food, head-fixed flies respond to optogenetic activation of sugar-sensing neurons by initiating a local search behavior. Finally, by pairing optogenetic activation of heat-sensing cells to the flies presence near visual landmarks of specific shapes, we elicit selective learned avoidance of landmarks associated with aversive \"virtual heat\". These head-fixed paradigms set the stage for an interrogation of fly brain circuitry underlying flexible navigation in complex visual environments.

animal behavior and cognition↗

bioRxiv2018

Limitations of Topological Data Analysis for event-related fMRI

Recent fMRI research shows that perceptual and cognitive representations are instantiated in high-dimensional multi-voxel patterns in the brain. However, the methods for detecting these representations are limited. Topological Data Analysis (TDA) is a new approach, based on the mathematical field of topology, that can detect unique types of geometric features in patterns of data. Several recent studies have successfully applied TDA to study various forms of neural data; however, to our knowledge, TDA has not been successfully applied to data from event-related fMRI designs. Event-related fMRI is very common but limited in terms of the number of events that can be run within a practical time frame and the effect size that can be expected. Here, we investigate whether persistent homology -- a popular TDA tool that identifies topological features in data and quantifies their robustness -- can identify known signals given these constraints. We use fmrisim, a Python-based simulator of realistic fMRI data, to assess the plausibility of recovering a simple topological representation under a variety of conditions. Our results suggest that persistent homology can be used under certain circumstances to recover topological structure embedded in realistic fMRI data simulations.

neuroscience↗

bioRxiv2018

The Eighty Five Percent Rule for Optimal Learning

Researchers and educators have long wrestled with the question of how best to teach their clients be they human, animal or machine. Here we focus on the role of a single variable, the difficulty of training, and examine its effect on the rate of learning. In many situations we find that there is a sweet spot in which training is neither too easy nor too hard, and where learning progresses most quickly. We derive conditions for this sweet spot for a broad class of learning algorithms in the context of binary classification tasks, in which ambiguous stimuli must be sorted into one of two classes. For all of these gradient-descent based learning algorithms we find that the optimal error rate for training is around 15.87% or, conversely, that the optimal training accuracy is about 85%. We demonstrate the efficacy of this Eighty Five Percent Rule for artificial neural networks used in AI and biologically plausible neural networks thought to describe human and animal learning.

animal behavior and cognition↗

bioRxiv2018

A pupillary index of susceptibility to decision biases

Under what conditions do humans systematically deviate from rational decision making? Here we show that pupillary indices of low neural gain are associated with strong and consistent biases across six different extensively-studied decision making tasks, whereas indices of high gain are associated with weak or absent biases. Lower susceptibility to biases, however, comes at the cost of indecisiveness, or alternatively, prolonged deliberation time. We explain the association between low gain and strong biases as reflecting a broader information integration process that gives greater weight to weak biasing influences. The findings underscore the role of pupil-linked brain states in the generation of decision making biases.\n\nSignificance\"Framing effects\" are demonstrations that peoples decisions can be biased by the way a decision problem is presented, and consequently, people can make decisions that violate the principles of rationality. Using a set of classic decision-making tasks, we show that pupil dilation, previously linked to levels of the neuromodulator norepinephrine and to a tradeoff between narrowly focused and broadly integrative modes of information processing, distinguishes between people who are consistently biased and people who are relatively immune to these effects. Our findings suggest that norepinephrine may drive these individual differences, and that a narrowly focused mode of information processing confers relative immunity to these decision making biases, whereas the integration of a wider range of information results in greater susceptibility.

neuroscience↗

bioRxiv2017

Anomalous Diffusion as a Descriptive Model of Cell Migration

Appropriately chosen descriptive models of cell migration in biomaterials will allow researchers to characterize and ultimately predict the movement of cells in engineered systems for a variety of applications in tissue engineering. The persistent random walk (PRW) model accurately describes cell migration on two-dimensional (2D) substrates. However, this model inherently cannot describe subdiffusive cell movement, i.e. migration paths in which the root mean square displacement increases more slowly than the square root of the time interval. Subdiffusivity is a common characteristic of cells moving in confined environments, such as three-dimensional (3D) porous scaffolds, hydrogel networks, and in vivo tissues. We demonstrate that a generalized anomalous diffusion (AD) model, which uses a simple power law to relate the mean square displacement (MSD) to time, more accurately captures individual cell migration paths across a range of engineered 2D and 3D environments than does the more commonly used PRW model. We used the AD model parameters to distinguish cell movement profiles on substrates with different chemokinetic factors, geometries (2D vs 3D), substrate adhesivities, and compliances. Although the two models performed with equal precision for superdiffusive cells, we suggest a simple AD model, in lieu of PRW, to describe cell trajectories in populations with a significant subdiffusive fraction, such as cells in confined, 3D environments.

bioengineering↗