Chromatic Illumination Discrimination Ability Reveals that Human Colour Constancy Is Optimised for Blue Daylight Illuminations

The phenomenon of colour constancy in human visual perception keeps surface colours constant, despite changes in their reflected light due to changing illumination. Although colour constancy has evolved under a constrained subset of illuminations, it is unknown whether its underlying mechanisms, thought to involve multiple components from retina to cortex, are optimised for particular environmental variations. Here we demonstrate a new method for investigating colour constancy using illumination matching in real scenes which, unlike previous methods using surface matching and simulated scenes, allows testing of multiple, real illuminations. We use real scenes consisting of solid familiar or unfamiliar objects against uniform or variegated backgrounds and compare discrimination performance for typical illuminations from the daylight chromaticity locus (approximately blue-yellow) and atypical spectra from an orthogonal locus (approximately red-green, at correlated colour temperature 6700 K), all produced in real time by a 10-channel LED illuminator. We find that discrimination of illumination changes is poorer along the daylight locus than the atypical locus, and is poorest particularly for bluer illumination changes, demonstrating conversely that surface colour constancy is best for blue daylight illuminations. Illumination discrimination is also enhanced, and therefore colour constancy diminished, for uniform backgrounds, irrespective of the object type. These results are not explained by statistical properties of the scene signal changes at the retinal level. We conclude that high-level mechanisms of colour constancy are biased for the blue daylight illuminations and variegated backgrounds to which the human visual system has typically been exposed

Charting Evolution’s Trajectory: Using Molluscan Eye Diversity to Understand Parallel and Convergent Evolution

For over 100 years, molluscan eyes have been used as an example of convergent evolution and, more recently, as a textbook example of stepwise evolution of a complex lens eye via natural selection. Yet, little is known about the underlying mechanisms that create the eye and generate different morphologies. Assessing molluscan eye diversity and understanding how this diversity came about will be important to developing meaningful interpretations of evolutionary processes. This paper provides an introduction to the myriad of eye types found in molluscs, focusing on some of the more unusual structures. We discuss how molluscan eyes can be applied to the study of evolution by examining patterns of convergent and parallel evolution and provide several examples, including the putative convergence of the camera-type eyes of cephalopods and vertebrates

A Model for the Detection of Moving Targets in Visual Clutter Inspired by Insect Physiology

We present a computational model for target discrimination based on intracellular recordings from neurons in the fly visual system. Determining how insects detect and track small moving features, often against cluttered moving backgrounds, is an intriguing challenge, both from a physiological and a computational perspective. Previous research has characterized higher-order neurons within the fly brain, known as ‘small target motion detectors’ (STMD), that respond robustly to moving features, even when the velocity of the target is matched to the background (i.e. with no relative motion cues). We recorded from intermediate-order neurons in the fly visual system that are well suited as a component along the target detection pathway. This full-wave rectifying, transient cell (RTC) reveals independent adaptation to luminance changes of opposite signs (suggesting separate ON and OFF channels) and fast adaptive temporal mechanisms, similar to other cell types previously described. From this physiological data we have created a numerical model for target discrimination. This model includes nonlinear filtering based on the fly optics, the photoreceptors, the 1st order interneurons (Large Monopolar Cells), and the newly derived parameters for the RTC. We show that our RTC-based target detection model is well matched to properties described for the STMDs, such as contrast sensitivity, height tuning and velocity tuning. The model output shows that the spatiotemporal profile of small targets is sufficiently rare within natural scene imagery to allow our highly nonlinear ‘matched filter’ to successfully detect most targets from the background. Importantly, this model can explain this type of feature discrimination without the need for relative motion cues

Intrinsic activity in the fly brain gates visual information during behavioral choices

The small insect brain is often described as an input/output system that executes reflex-like behaviors. It can also initiate neural activity and behaviors intrinsically, seen as spontaneous behaviors, different arousal states and sleep. However, less is known about how intrinsic activity in neural circuits affects sensory information processing in the insect brain and variability in behavior. Here, by simultaneously monitoring Drosophila's behavioral choices and brain activity in a flight simulator system, we identify intrinsic activity that is associated with the act of selecting between visual stimuli. We recorded neural output (multiunit action potentials and local field potentials) in the left and right optic lobes of a tethered flying Drosophila, while its attempts to follow visual motion (yaw torque) were measured by a torque meter. We show that when facing competing motion stimuli on its left and right, Drosophila typically generate large torque responses that flip from side to side. The delayed onset (0.1-1 s) and spontaneous switch-like dynamics of these responses, and the fact that the flies sometimes oppose the stimuli by flying straight, make this behavior different from the classic steering reflexes. Drosophila, thus, seem to choose one stimulus at a time and attempt to rotate toward its direction. With this behavior, the neural output of the optic lobes alternates; being augmented on the side chosen for body rotation and suppressed on the opposite side, even though the visual input to the fly eyes stays the same. Thus, the flow of information from the fly eyes is gated intrinsically. Such modulation can be noise-induced or intentional; with one possibility being that the fly brain highlights chosen information while ignoring the irrelevant, similar to what we know to occur in higher animals

Very Bright Green Fluorescent Proteins from the Pontellid Copepod Pontella mimocerami

Marguerite E. Hunt is with UT Austin; Michael P. Scherrer is with UT Austin; Frank D. Ferrari is with the National Museum of Natural History at the Smithsonian Institution; Mikhail V. Matz is with UT Austin.Background -- Fluorescent proteins (FP) homologous to the green fluorescent protein (GFP) from the jellyfish Aequorea victoria have revolutionized biomedical research due to their usefulness as genetically encoded fluorescent labels. Fluorescent proteins from copepods are particularly promising due to their high brightness and rapid fluorescence development. Results -- Here we report two novel FPs from Pontella mimocerami (Copepoda, Calanoida, Pontellidae), which were identified via fluorescence screening of a bacterial cDNA expression library prepared from the whole-body total RNA of the animal. The proteins are very similar in sequence and spectroscopic properties. They possess high molar extinction coefficients (79,000 M−1 cm−) and quantum yields (0.92), which make them more than two-fold brighter than the most common FP marker, EGFP. Both proteins form oligomers, which we were able to counteract to some extent by mutagenesis of the N-terminal region; however, this particular modification resulted in substantial drop in brightness. Conclusions -- The spectroscopic characteristics of the two P. mimocerami proteins place them among the brightest green FPs ever described. These proteins may therefore become valuable additions to the in vivo imaging toolkit.This work was supported by the Ocean Exploration program of the National Oceanic and Atmospheric Administration (“Operation Deep Scope 2007”), and the National Institutes of Health grant R01 GM078247 to M. V. M. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o

Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors

Network adaptation improves temporal representation of naturalistic stimuli in drosophila eye: II Mechanisms

Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information

Estrogen and progesterone induce persistent increases in p53-dependent apoptosis and suppress mammary tumors in BALB/c-Trp53+/- mice

Introduction Treatment with estrogen and progesterone (E+P) mimics the protective effect of parity on mammary tumors in rodents and depends upon the activity of p53. The following experiments tested whether exogenous E+P primes p53 to be more responsive to DNA damage and whether these pathways confer resistance to mammary tumors in a mouse model of Li-Fraumeni syndrome. Methods Mice that differ in p53 status (Trp53+/+, Trp53+/-, Trp53-/-) were treated with E+P for 14 days and then were tested for p53-dependent responses to ionizing radiation. Responses were also examined in parous and age-matched virgins. The effects of hormonal exposures on tumor incidence were examined in BALB/c-Trp53+/- mammary tissues. Results Nuclear accumulation of p53 and apoptotic responses were increased similarly in the mammary epithelium from E+P-treated and parous mice compared with placebo and age-matched virgins. This effect was sustained for at least 7 weeks after E+P treatment and did not depend on the continued presence of ovarian hormones. Hormone stimulation also enhanced apoptotic responses to ionizing radiation in BALB/c-Trp53+/- mice but these responses were intermediate compared with Trp53+/+ and Trp-/- tissues, indicating haploinsufficiency. The appearance of spontaneous mammary tumors was delayed by parity in BALB/c-Trp53+/- mice. The majority of tumors lacked estrogen receptor (ER), but ER+ tumors were observed in both nulliparous and parous mice. However, apoptotic responses to ionizing radiation and tumor incidence did not differ among outgrowths of epithelial transplants from E+P-treated donors and nulliparous donors

Cytoarchitecture of mouse and human subventricular zone in developing cerebral neocortex

During cerebral neocortical development, excitatory neurons are generated from radial glial cells in the ventricular zone (VZ) or from secondary progenitor cells in the subventricular zone (SVZ); these neurons then migrate toward the pial surface. We have observed that post-mitotic neurons generated directly in the VZ accumulated just above the VZ with a multipolar morphology, while secondary progenitor cells having a long ascending process left the VZ faster than the post-mitotic neurons. Recent observations of human developing neocortex have revealed the existence of radial glia-like progenitors (oRG cells) in the SVZ. This type of progenitor was first thought to be human specific; however, similar cells have also been found in mouse neocortex, and the morphology of these cells resembled that of some of the secondary progenitor cells that we had previously observed, suggesting the existence of a common architecture for the developing neocortex among mammals. In this review, we discuss the nature of the SVZ and its similarities and differences between humans and mice

Participants in Citizen Science

The most important factor that defines citizen science is that non-professional scientists contribute to scientific research. Therefore, it is important to recognise the perspectives and experiences of these participants. Projects may provide ways for participants to contribute to scientific research at different stages of the scientific process according to different levels of engagement. Understanding what motivates citizen scientists to engage in a project, and subsequently matching the project to these motivations, will help project leaders to recruit and retain participants. In addition, it is important to understand what benefits participants gain from engagement in citizen science projects. For individual projects, this will help ensure that scientists as well as participants benefit. For the wider field of citizen science, this will provide evidence of the potential impact of citizen science on participants. However, participants may also encounter challenges during their engagement with citizen science projects. Project leaders and scientists should plan in advance to address these challenges and ensure that relevant expertise is present in the project team. Keywords Citizen engagement · Participant motiScience Communication and Societ