The Camouflage Machine: Optimizing protective coloration using deep learning with genetic algorithms.

Evolutionary biologists frequently wish to measure the fitness of alternative phenotypes using behavioral experiments. However, many phenotypes are complex. One example is coloration: camouflage aims to make detection harder, while conspicuous signals (e.g., for warning or mate attraction) require the opposite. Identifying the hardest and easiest to find patterns is essential for understanding the evolutionary forces that shape protective coloration, but the parameter space of potential patterns (colored visual textures) is vast, limiting previous empirical studies to a narrow range of phenotypes. Here, we demonstrate how deep learning combined with genetic algorithms can be used to augment behavioral experiments, identifying both the best camouflage and the most conspicuous signal(s) from an arbitrarily vast array of patterns. To show the generality of our approach, we do so for both trichromatic (e.g., human) and dichromatic (e.g., typical mammalian) visual systems, in two different habitats. The patterns identified were validated using human participants; those identified as the best for camouflage were significantly harder to find than a tried-and-tested military design, while those identified as most conspicuous were significantly easier to find than other patterns. More generally, our method, dubbed the "Camouflage Machine," will be a useful tool for identifying the optimal phenotype in high dimensional state spaces.

The Bayesian superorganism: externalized memories facilitate distributed sampling.

A key challenge for any animal (or sampling technique) is to avoid wasting time by searching for resources (information) in places already found to be unprofitable. In biology, this challenge is particularly strong when the organism is a central place forager-returning to a nest between foraging bouts-because it is destined repeatedly to cover much the same ground. This problem will be particularly acute if many individuals forage from the same central place, as in social insects such as the ants. Foraging (sampling) performance may be greatly enhanced by coordinating movement trajectories such that each ant (walker) visits separate parts of the surrounding (unknown) space. We find experimental evidence for an externalized spatial memory in Temnothorax albipennis ants: chemical markers (either pheromones or cues such as cuticular hydrocarbon footprints) that are used by nest-mates to mark explored space. We show these markers could be used by the ants to scout the space surrounding their nest more efficiently through indirect coordination. We also develop a simple model of this marking behaviour that can be applied in the context of Markov chain Monte Carlo methods (Baddeley et al. 2019 J. R. Soc. Interface16, 20190162 (doi:10.1098/rsif.2019.0162)). This substantially enhances the performance of standard methods like the Metropolis-Hastings algorithm in sampling from sparse probability distributions (such as those confronted by the ants) with only a little additional computational cost. Our Bayesian framework for superorganismal behaviour motivates the evolution of exploratory mechanisms such as trail marking in terms of enhanced collective information processing.

Author Correction: Fornix white matter glia damage causes hippocampal gray matter damage during age-dependent limbic decline.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Optimal foraging and the information theory of gambling.

At a macroscopic level, part of the ant colony life cycle is simple: a colony collects resources; these resources are converted into more ants, and these ants in turn collect more resources. Because more ants collect more resources, this is a multiplicative process, and the expected logarithm of the amount of resources determines how successful the colony will be in the long run. Over 60 years ago, Kelly showed, using information theoretic techniques, that the rate of growth of resources for such a situation is optimized by a strategy of betting in proportion to the probability of pay-off. Thus, in the case of ants, the fraction of the colony foraging at a given location should be proportional to the probability that resources will be found there, a result widely applied in the mathematics of gambling. This theoretical optimum leads to predictions as to which collective ant movement strategies might have evolved. Here, we show how colony-level optimal foraging behaviour can be achieved by mapping movement to Markov chain Monte Carlo (MCMC) methods, specifically Hamiltonian Monte Carlo (HMC). This can be done by the ants following a (noisy) local measurement of the (logarithm of) resource probability gradient (possibly supplemented with momentum, i.e. a propensity to move in the same direction). This maps the problem of foraging (via the information theory of gambling, stochastic dynamics and techniques employed within Bayesian statistics to efficiently sample from probability distributions) to simple models of ant foraging behaviour. This identification has broad applicability, facilitates the application of information theory approaches to understand movement ecology and unifies insights from existing biomechanical, cognitive, random and optimality movement paradigms. At the cost of requiring ants to obtain (noisy) resource gradient information, we show that this model is both efficient and matches a number of characteristics of real ant exploration.

Fornix white matter glia damage causes hippocampal gray matter damage during age-dependent limbic decline.

Aging leads to gray and white matter decline but their causation remains unclear. We explored two classes of models of age and dementia risk related brain changes. The first class of models emphasises the importance of gray matter: age and risk-related processes cause neurodegeneration and this causes damage in associated white matter tracts. The second class of models reverses the direction of causation: aging and risk factors cause white matter damage and this leads to gray matter damage. We compared these models with linear mediation analysis and quantitative MRI indices (from diffusion, quantitative magnetization transfer and relaxometry imaging) of tissue properties in two limbic structures implicated in age-related memory decline: the hippocampus and the fornix in 166 asymptomatic individuals (aged 38-71 years). Aging was associated with apparent glia but not neurite density damage in the fornix and the hippocampus. Mediation analysis supported white matter damage causing gray matter decline; controlling for fornix glia damage, the correlations between age and hippocampal damage disappear, but not vice versa. Fornix and hippocampal differences were both associated with reductions in episodic memory performance. These results suggest that fornix white matter glia damage may cause hippocampal gray matter damage during age-dependent limbic decline.

Sex-specific effects of central adiposity and inflammatory markers on limbic microstructure.

Midlife obesity is a risk factor of late onset Alzheimer's disease (LOAD) but why this is the case remains unknown. As systemic inflammation is involved in both conditions, obesity-related neuroinflammation may contribute to damage in limbic structures important in LOAD. Here, we investigated the hypothesis that systemic inflammation would mediate central obesity related effects on limbic tissue microstructure in 166 asymptomatic individuals (38-71 years old). We employed MRI indices sensitive to myelin and neuroinflammation [macromolecular proton fraction (MPF) and kf] from quantitative magnetization transfer (qMT) together with indices from neurite orientation dispersion and density imaging (NODDI) to investigate the effects of central adiposity on the fornix, parahippocampal cingulum, uncinate fasciculus (compared with whole brain white matter and corticospinal tract) and the hippocampus. Central obesity was assessed with the Waist Hip Ratio (WHR) and abdominal visceral and subcutaneous fat area fractions (VFF, SFF), and systemic inflammation with blood plasma concentrations of leptin, adiponectin, C-reactive protein and interleukin 8. Men were significantly more centrally obese and had higher VFF than women. Individual differences in WHR and in VFF were negatively correlated with differences in fornix MPF and kf, but not with any differences in neurite microstructure. In women, age mediated the effects of VFF on fornix MPF and kf, whilst in men differences in the leptin and adiponectin ratio fully mediated the effect of WHR on fornix MPF. These results suggest that visceral fat related systemic inflammation may damage myelin-related properties of the fornix, a key limbic structure known to be involved in LOAD.

Cultural evolution of military camouflage.

While one has evolved and the other been consciously created, animal and military camouflage are expected to show many similar design principles. Using a unique database of calibrated photographs of camouflage uniform patterns, processed using texture and colour analysis methods from computer vision, we show that the parallels with biology are deeper than design for effective concealment. Using two case studies we show that, like many animal colour patterns, military camouflage can serve multiple functions. Following the dissolution of the Warsaw Pact, countries that became more Western-facing in political terms converged on NATO patterns in camouflage texture and colour. Following the break-up of the former Yugoslavia, the resulting states diverged in design, becoming more similar to neighbouring countries than the ancestral design. None of these insights would have been obtained using extant military approaches to camouflage design, which focus solely on concealment. Moreover, our computational techniques for quantifying pattern offer new tools for comparative biologists studying animal coloration.This article is part of the themed issue 'Animal coloration: production, perception, function and application'.

Color generalization across hue and saturation in chicks described by a simple (Bayesian) model.

Color conveys important information for birds in tasks such as foraging and mate choice, but in the natural world color signals can vary substantially, so birds may benefit from generalizing responses to perceptually discriminable colors. Studying color generalization is therefore a way to understand how birds take account of suprathreshold stimulus variations in decision making. Former studies on color generalization have focused on hue variation, but natural colors often vary in saturation, which could be an additional, independent source of information. We combine behavioral experiments and statistical modeling to investigate whether color generalization by poultry chicks depends on the chromatic dimension in which colors vary. Chicks were trained to discriminate colors separated by equal distances on a hue or a saturation dimension, in a receptor-based color space. Generalization tests then compared the birds' responses to familiar and novel colors lying on the same chromatic dimension. To characterize generalization we introduce a Bayesian model that extracts a threshold color distance beyond which chicks treat novel colors as significantly different from the rewarded training color. These thresholds were the same for generalization along the hue and saturation dimensions, demonstrating that responses to novel colors depend on similarity and expected variation of color signals but are independent of the chromatic dimension.

Ants determine their next move at rest: motor planning and causality in complex systems.

To find useful work to do for their colony, individual eusocial animals have to move, somehow staying attentive to relevant social information. Recent research on individual Temnothorax albipennis ants moving inside their colony's nest found a power-law relationship between a movement's duration and its average speed; and a universal speed profile for movements showing that they mostly fluctuate around a constant average speed. From this predictability it was inferred that movement durations are somehow determined before the movement itself. Here, we find similar results in lone T. albipennis ants exploring a large arena outside the nest, both when the arena is clean and when it contains chemical information left by previous nest-mates. This implies that these movement characteristics originate from the same individual neural and/or physiological mechanism(s), operating without immediate regard to social influences. However, the presence of pheromones and/or other cues was found to affect the inter-event speed correlations. Hence we suggest that ants' motor planning results in intermittent response to the social environment: movement duration is adjusted in response to social information only between movements, not during them. This environmentally flexible, intermittently responsive movement behaviour points towards a spatially allocated division of labour in this species. It also prompts more general questions on collective animal movement and the role of intermittent causation from higher to lower organizational levels in the stability of complex systems.

Improved Executive Function and Callosal White Matter Microstructure after Rhythm Exercise in Huntington's Disease.

BACKGROUND: Huntington's disease (HD) is an autosominal dominant neurodegenerative condition that leads to progressive loss of motor and cognitive functions. Early symptoms in HD include subtle executive dysfunction related to white and grey matter loss in cortico-striatal-thalamic loops. There is no cure for HD and hence a significant need for early intervention with the potential to delay the clinical onset of the disease. OBJECTIVE: The objective of the present pilot study was to devise a novel behavioural intervention involving drumming and rhythm exercises that targets early dysexecutive problems, such as difficulties in sequence and reversal learning, response speed, timing, and dual tasking. METHOD: One preclinical person and nine people with early to advanced stages of HD were recruited of whom five completed the two months intervention. The effects of rhythm exercise on executive function, basal ganglia volume, and white matter microstructure in the anterior corpus callosum, the anterior thalamic radiation, and the cortico-spinal tract were assessed post- relative to pre-training. RESULTS: After two months training, improvements in executive function and changes in white matter microstructure, notably in the genu of the corpus callosum that connects prefrontal cortices of both hemispheres, were observed. No changes in basal ganglia volume were present. CONCLUSION: This pilot study provides novel preliminary evidence that carefully targeted behavioural stimulation in HD can result in cognitive enhancement and improvements in callosal white matter microstructure.

Individual differences in fornix microstructure and body mass index.

The prevalence of obesity and associated health conditions is increasing in the developed world. Obesity is related to atrophy and dysfunction of the hippocampus and hippocampal lesions may lead to increased appetite and weight gain. The hippocampus is connected via the fornix tract to the hypothalamus, orbitofrontal cortex, and the nucleus accumbens, all key structures for homeostatic and reward related control of food intake. The present study employed diffusion MRI tractography to investigate the relationship between microstructural properties of the fornix and variation in Body Mass Index (BMI), within normal and overweight ranges, in a group of community-dwelling older adults (53-93 years old). Larger BMI was associated with larger axial and mean diffusivity in the fornix (r = 0.64 and r = 0.55 respectively), relationships that were most pronounced in overweight individuals. Moreover, controlling for age, education, cognitive performance, blood pressure and global brain volume increased these correlations. Similar associations were not found in the parahippocampal cingulum, a comparison temporal association pathway. Thus, microstructural changes in fornix white matter were observed in older adults with increasing BMI levels from within normal to overweight ranges, so are not exclusively related to obesity. We propose that hippocampal-hypothalamic-prefrontal interactions, mediated by the fornix, contribute to the healthy functioning of networks involved in food intake control. The fornix, in turn, may display alterations in microstructure that reflect weight gain.

Reward is assessed in three dimensions that correspond to the semantic differential.

If choices are to be made between alternatives like should I go for a walk or grab a coffee, a 'common currency' is needed to compare them. This quantity, often known as reward in psychology and utility in economics, is usually conceptualised as a single dimension. Here we propose that to make a comparison between different options it is important to know not only the average reward, but also both the risk and level of certainty (or control) associated with an option. Almost all objects can be the subject of choice, so if these dimensions are required in order to make a decision, they should be part of the meaning of those objects. We propose that this ubiquity is unique, so if we take an average over many concepts and domains these three dimensions (reward, risk, and uncertainty) should emerge as the three most important dimensions in the "meaning" of objects. We investigated this possibility by relating the three dimensions of reward to an old, robust and extensively studied factor analytic instrument known as the semantic differential. Across a very wide range of situations, concepts and cultures, factor analysis shows that 50% of the variance in rating scales is accounted for by just three dimensions, with these dimensions being Evaluation, Potency, and Activity [1]. Using a statistical analysis of internet blog entries and a betting experiment, we show that these three factors of the semantic differential are strongly correlated with the reward history associated with a given concept: Evaluation measures relative reward; Potency measures absolute risk; and Activity measures the uncertainty or lack of control associated with a concept. We argue that the 50% of meaning captured by the semantic differential is simply a summary of the reward history that allows decisions to be made between widely different options.

Rapidly measuring the speed of unconscious learning: amnesics learn quickly and happy people slowly.

BACKGROUND: We introduce a method for quickly determining the rate of implicit learning. METHODOLOGY/PRINCIPAL FINDINGS: The task involves making a binary prediction for a probabilistic sequence over 10 minutes; from this it is possible to determine the influence of events of a different number of trials in the past on the current decision. This profile directly reflects the learning rate parameter of a large class of learning algorithms including the delta and Rescorla-Wagner rules. To illustrate the use of the method, we compare a person with amnesia with normal controls and we compare people with induced happy and sad moods. CONCLUSIONS/SIGNIFICANCE: Learning on the task is likely both associative and implicit. We argue theoretically and demonstrate empirically that both amnesia and also transient negative moods can be associated with an especially large learning rate: People with amnesia can learn quickly and happy people slowly.

Visual impairments in dementia with Lewy bodies and posterior cortical atrophy.

Dementia with Lewy bodies (DLB) and Posterior Cortical Atrophy (PCA), the visual variant of Alzheimer's disease, are neurodegenerative diseases that present with progressive deterioration in visual perception. However, little is known about the precise nature underlying the complex visual deficits associated with both conditions. The present study compared DLB, PCA, and healthy control participants, in four visual tasks designed to measure the efficiency of the visual system at different levels of processing. In ascending order of complexity there were tasks of visual acuity, line orientation, contour integration, and rotated object comparison. DLB patients did not differ from controls in low level visual functions of visual acuity and line orientation, suggesting that early visual processing areas including V1 were relatively preserved, consistent with pathology evidence (Yamamoto et al., 2006). However, higher level visual functions of contour integration, mediated by extrastriatal areas, and the most complex task of object rotation, relying on processing within inferior temporal (IT), parietal, and frontal cortices, were impaired in DLB. In contrast, PCA patients were impaired in all tasks, consistent with evidence of widespread pathology within occipital and parietal areas in PCA. The latter suggests that both lower and higher level visual impairments contribute to the complex visual symptoms associated with PCA.

Optimal feature integration in visual search.

Despite embodying fundamentally different assumptions about attentional allocation, a wide range of popular models of attention include a max-of-outputs mechanism for selection. Within these models, attention is directed to the items with the most extreme-value along a perceptual dimension via, for example, a winner-take-all mechanism. From the detection theoretic approach, this MAX-observer can be optimal under specific situations, however in distracter heterogeneity manipulations or in natural visual scenes this is not always the case. We derive a Bayesian maximum a posteriori (MAP)-observer, which is optimal in both these situations. While it retains a form of the max-of-outputs mechanism, it is based on the maximum a posterior probability dimension, instead of a perceptual dimension. To test this model we investigated human visual search performance using a yes/no procedure while adding external orientation uncertainty to distracter elements. The results are much better fitted by the predictions of a MAP observer than a MAX observer. We conclude a max-like mechanism may well underlie the allocation of visual attention, but this is based upon a probability dimension, not a perceptual dimension.

A review of cuttlefish camouflage and object recognition and evidence for depth perception.

Cuttlefishes of the genus Sepia produce adaptive camouflage by regulating the expression of visual features such as spots and lines, and textures including stipples and stripes. They produce the appropriate pattern for a given environment by co-ordinated expression of about 40 of these 'chromatic components'. This behaviour has great flexibility, allowing the animals to produce a very large number of patterns, and hence gives unique access to cuttlefish visual perception. We have, for instance, tested their sensitivity to image parameters including spatial frequency, orientation and spatial phase. One can also ask what features in the visual environment elicit a given coloration pattern; here most work has been on the disruptive body pattern, which includes well-defined light and dark features. On 2-D backgrounds, isolated pale objects of a specific size, that have well-defined edges, elicit the disruptive pattern. Here we show that visual depth is also relevant. Naturally, cuttlefish probably use the disruptive pattern amongst discrete objects, such as pebbles. We suggest that they use several visual cues to 'identify' this type of background (including: edges, contrast, size, and real and pictorial depth). To conclude we argue that the visual strategy cuttlefish use to select camouflage is fundamentally similar to human object recognition.

The distribution of reflectances within the visual environment.

The statistics of natural images have often been used to account for various properties of animal visual systems. However, for most visual tasks, the images themselves are not important; it is the physical properties of the surfaces which generated them that guide behaviour. Here, we present statistical characterisations of the surface reflectances encountered within four different visual environments (woodland, beach, urban and interior), sampled using a systematic, survey-based method. Of the distributions fitted to the data, the beta distribution provides the best description per number of free parameters. Such distributions may be used as priors in Bayesian models of lightness constancy, or to generate ecologically valid reflectance distributions for simulated environments. The implications of this for models of reflectance extraction within visual systems are discussed.

High frequency edges (but not contrast) predict where we fixate: A Bayesian system identification analysis.

A Bayesian system identification technique was used to determine which image characteristics predict where people fixate when viewing natural images. More specifically an estimate was derived for the mapping between image characteristics at a given location and the probability that this location was fixated. Using a large database of eye fixations to natural images, we determined the most probable (a posteriori) model of this mapping. From a set of candidate feature maps consisting of edge, contrast and luminance maps (at two different spatial scales), fixation probability was dominated by high spatial frequency edge information. The best model applied compressive non-linearity to the high frequency edge detecting filters (approximately a square root). Both low spatial frequency edges and contrast had weaker, but inhibitory, effects. The contributions of the other maps were so small as to be behaviourally irrelevant. This Bayesian method identifies not only the relevant weighting of the different maps, but how this weighting varies as a function of distance from the point of fixation. It was found that rather than centre surround inhibition, the weightings simply averaged over an area of about 2 degrees.

The long and the short of it: spatial statistics at fixation vary with saccade amplitude and task.

We recorded over 90,000 saccades while observers viewed a diverse collection of natural images and measured low level visual features at fixation. The features that discriminated between where observers fixated and where they did not varied considerably with task, and the length of the preceding saccade. Short saccades (<8 degrees) are image feature dependent, long are less so. For free viewing, short saccades target high frequency information, long saccades are scale-invariant. When searching for luminance targets, saccades of all lengths are scale-invariant. We argue that models of saccade behaviour must account not only for task but also for saccade length and that long and short saccades are targeted differently.

The temporal impulse response underlying saccadic decisions.

Models of perceptual decision making often assume that sensory evidence is accumulated over time in favor of the various possible decisions, until the evidence in favor of one of them outweighs the evidence for the others. Saccadic eye movements are among the most frequent perceptual decisions that the human brain performs. We used stochastic visual stimuli to identify the temporal impulse response underlying saccadic eye movement decisions. Observers performed a contrast search task, with temporal variability in the visual signals. In experiment 1, we derived the temporal filter observers used to integrate the visual information. The integration window was restricted to the first approximately 100 ms after display onset. In experiment 2, we showed that observers cannot perform the task if there is no useful information to distinguish the target from the distractor within this time epoch. We conclude that (1) observers did not integrate sensory evidence up to a criterion level, (2) observers did not integrate visual information up to the start of the saccadic dead time, and (3) variability in saccade latency does not correspond to variability in the visual integration period. Instead, our results support a temporal filter model of saccadic decision making. The temporal impulse response identified by our methods corresponds well with estimates of integration times of V1 output neurons.