In vision science, cascades of Linear+Nonlinear transforms are very successful in modeling a number of perceptual experiences. However, the conventional literature is usually too focused on only describing the forward input-output transform. Instead, in this work we present the mathematics of such cascades beyond the forward transform, namely the Jacobian matrices and the inverse. The fundamental reason for this analytical treatment is that it offers useful analytical insight into the psychophysics, the physiology, and the function of the visual system. For instance, we show how the trends of the sensitivity (volume of the discrimination regions) and the adaptation of the receptive fields can be identified in the expression of the Jacobian w.r.t. the stimulus. This matrix also tells us which regions of the stimulus space are encoded more efficiently in multi-information terms. The Jacobian w.r.t. the parameters shows which aspects of the model have bigger impact in the response, and hence their relative relevance. The analytic inverse implies conditions for the response and model parameters to ensure appropriate decoding. From the experimental and applied perspective, (a) the Jacobian w.r.t. the stimulus is necessary in new experimental methods based on the synthesis of visual stimuli with interesting geometrical properties, (b) the Jacobian matrices w.r.t. the parameters are convenient to learn the model from classical experiments or alternative goal optimization, and (c) the inverse is a promising model-based alternative to blind machine-learning methods for neural decoding that do not include meaningful biological information. The theory is checked by building and testing a vision model that actually follows a modular Linear+Nonlinear program. Our illustrative derivable and invertible model consists of a cascade of modules that account for brightness, contrast, energy masking, and wavelet masking. To stress the generality of this modular setting we show examples where some of the canonical Divisive Normalization modules are substituted by equivalent modules such as the Wilson-Cowan interaction model (at the V1 cortex) or a tone-mapping model (at the retina).

Subjective image quality databases are a major source of raw data on how the visual system works in naturalistic environments. These databases describe the sensitivity of many observers to a wide range of distortions of different nature and intensity seen on top of a variety of natural images. Data of this kind seems to open a number of possibilities for the vision scientist to check the models in realistic scenarios. However, while these natural databases are great benchmarks for models developed in some other way (e.g., by using the well-controlled artificial stimuli of traditional psychophysics), they should be carefully used when trying to fit vision models. Given the high dimensionality of the image space, it is very likely that some basic phenomena are under-represented in the database. Therefore, a model fitted on these large-scale natural databases will not reproduce these under-represented basic phenomena that could otherwise be easily illustrated with well selected artificial stimuli. In this work we study a specific example of the above statement. A standard cortical model using wavelets and divisive normalization tuned to reproduce subjective opinion on a large image quality dataset fails to reproduce basic cross-masking. Here we outline a solution for this problem by using artificial stimuli and by proposing a modification that makes the model easier to tune. Then, we show that the modified model is still competitive in the large-scale database. Our simulations with these artificial stimuli show that when using steerable wavelets, the conventional unit norm Gaussian kernels in divisive normalization should be multiplied by high-pass filters to reproduce basic trends in masking. Basic visual phenomena may be misrepresented in large natural image datasets but this can be solved with model-interpretable stimuli. This is an additional argument in praise of artifice in line with Rust and Movshon (2005).

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Breast cancer susceptibility gene 1(BRCA1) and binding partner BRCA1-associated RING domain protein 1 (BARD1) form an essential E3 ubiquitin ligase important for DNA damage repair and homologous recombination. In Caenorhabditis elegans BRCA1/BRC-1 and BARD1/BRD-1 orthologs are not essential, but function in DNA damage repair and homologous recombination, as well as in meiosis. In proliferating germ cells and in early meiotic prophase, BRC-1 and BRD-1 are nucleoplasmic, with enrichment at foci that partially overlap with the recombinase RAD-51.In mid-pachytene, BRC-1 and BRD-1 are observed on tracks, before concentrating to the short arms of bivalents, co-localizing with a central region component of the synaptonemal complex.We found that BRD-1 is essential for BRC-1 to associate with chromatin and the synaptonemal complex, but BRC-1 is not required for BRD-1 localization; the complex fails to properly localize in the absence of either meiotic recombination or chromosome synapsis. Inactivation of BRC-1/BRD-1 enhances the embryonic lethality of mutants that perturb chromosome synapsis and crossover recombination, suggesting that BRC-1/BRD-1 plays an important role in monitoring recombination in the context of the synaptonemal complex. We discovered that BRC-1/BRD-1 stabilizes the RAD51 filament when the formation of a crossover-intermediate is disrupted.Further, in the absence of BRC-1/BRD-1 crossover distribution is altered, and under meiotic dysfunction, crossover numbers are perturbed. Together, our studies indicate that BRC-1/BRD-1 localizes to the synaptonemal complex where it serves a checkpoint function to monitor and modulate meiotic recombination.. CC-BY-NC 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/280909 doi: bioRxiv preprint first posted online Mar. 12, 2018; 3 Project SummaryOur genomes are passed down from one generation to the next through the specialized cell division program of meiosis. Meiosis is highly regulated to coordinate both the large scale chromosomal and fine scale DNA events to ensure fidelity. We analyzed the role of the tumor suppressor BRCA1/BARD1 complex in meiosis in the worm, Caenorhabditis elegans. We find that BRCA1/BARD1 localizes dynamically to the proteinaeous structure that aligns maternal and paternal chromosomes, where it regulates crossover recombination. Although BRCA1/BARD1 mutants have only subtle meiotic defects, we show that this complex plays a critical role in meiotic recombination when meiosis is perturbed. These results highlight the complexity of ensuring accurate transmission of the genome and uncover the requirement for this conserved complex in meiosis. As women carrying BRCA1 mutations with no indication of cancer have fertility defects, our results provide insight into why BRCA1 mutations impact reproductive success.

Population confinements have been one of the most widely adopted non-pharmaceutical interventions (NPIs) implemented by governments across the globe to help contain the spread of the SARS-CoV-2 virus. While confinement measures have been proven to be effective to reduce the number of infections, they entail significant economic and social costs. Thus, different policy makers and social groups have exhibited varying levels of acceptance of this type of measures. In this context, understanding the factors that determine the willingness of individuals to be confined during a pandemic is of paramount importance, particularly, to policy and decision-makers. In this paper, we study the factors that influence the unwillingness to be confined during the COVID-19 pandemic by the means of a large-scale, online population survey deployed in Spain. We perform two types of analyses (logistic regression and automatic pattern discovery) and consider socio-demographic, economic and psychological factors, together with the 14-day cumulative incidence per 100,000 inhabitants. Our analysis of 109,515 answers to the survey covers data spanning over a 5-month time period to shed light on the impact of the passage of time. We find evidence of pandemic fatigue as the percentage of those who report an unwillingness to be in confinement increases over time; we identify significant gender differences, with women being generally less likely than men to be able to sustain long-term confinement of at least 6 months; we uncover that the psychological impact was the most important factor to determine the willingness to be in confinement at the beginning of the pandemic, to be replaced by the economic impact as the most important variable towards the end of our period of study. Our results highlight the need to design gender and age specific public policies, to implement psychological and economic support programs and to address the evident pandemic fatigue as the success of potential future confinements will depend on the population’s willingness to comply with them.

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Neural correlations during a cognitive task are central to study brain information processing and computation. However, they have been poorly analyzed due to the difficulty of recording simultaneous single neurons during task performance. In the present work, we quantified neural directional correlations using spike trains that were simultaneously recorded in sensory, premotor, and motor cortical areas of two monkeys during a somatosensory discrimination task. Upon modeling spike trains as binary time series, we used a nonparametric Bayesian method to estimate pairwise directional correlations between many pairs of neurons throughout different stages of the task, namely, perception, working memory, decision making, and motor report. We find that solving the task involves feedforward and feedback correlation paths linking sensory and motor areas during certain task intervals. Specifically, information is communicated by task-driven neural correlations that are significantly delayed across secondary somatosensory cortex, premotor, and motor areas when decision making takes place. Crucially, when sensory comparison is no longer requested for task performance, a major proportion of directional correlations consistently vanish across all cortical areas.vibrotactile discrimination | large-scale cortical networks | spike-train analysis | information theory | decision making T he problem of neural communication in the brain has been little explored traditionally due to the need for simultaneous recordings (1). The arrival of new techniques to record both neural population activity and single-neuron action potentials offers new prospects to study this problem (2, 3). Recently, population recordings have motivated a large number of works on multiunit interactions, including the study of interactions between local field potentials (LFPs) (4-6), LFPs and multiunit activity (5), and LFPs and neuronal spikes (7), but less attention has been paid to interactions between single-unit recordings (8). However, the analysis of simultaneous spike trains becomes critical because it is generally assumed that neurons are key units in distributing information across brain areas (9).An ideal paradigm to study neural communication is the somatosensory discrimination task designed by Romo and coworkers (10). In this task, a trained monkey discriminates the difference in frequency between two mechanical vibrations delivered sequentially to one fingertip (Fig. 1A). Essentially, the monkey must hold the first stimulus frequency (f 1) in working memory, must compare the second stimulus frequency (f 2) with the memory trace of f1 to form a decision of whether f 2 > f 1 or f 2 < f 1, and must postpone the decision until a sensory cue triggers the motor report (11). At the end of every trial, the monkey is rewarded with a drop of liquid for correct discriminations. Previous work on this task has analyzed how single-neuron responses across sensory and motor areas linearly correlate with stimuli and the decision report during the key stages of the ...

We consider the mechanisms that enable decisions to be postponed for a period after the evidence has been provided. Using an information theoretic approach, we show that information about the forthcoming action becomes available from the activity of neurons in the medial premotor cortex in a sequential decisionmaking task after the second stimulus is applied, providing the information for a decision about whether the first or second stimulus is higher in vibrotactile frequency. The information then decays in a 3-s delay period in which the neuronal activity declines before the behavioral response can be made. The information then increases again when the behavioral response is required. We model this neuronal activity using an attractor decision-making network in which information reflecting the decision is maintained at a low level during the delay period, and is then selectively restored by a nonspecific input when the response is required. One mechanism for the short-term memory is synaptic facilitation, which can implement a mechanism for postponed decisions that can be correct even when there is little neuronal firing during the delay period before the postponed decision. Another mechanism is graded firing rates by different neurons in the delay period, with restoration by the nonspecific input of the low-rate activity from the higher-rate neurons still firing in the delay period. These mechanisms can account for the decision making and for the memory of the decision before a response can be made, which are evident in the activity of neurons in the medial premotor cortex.attractor network | delayed response | recall