Physically stressed bees expect less reward in an active choice judgement bias test by Procenko O, Read JCA, Nityananda V, rspb.2024.0512.html (9 KiB) - Emotion-like states in animals are commonly assessed using judgment bias tests that measure judgements of ambiguous cues. Some studies have used these tests to argue for emotion-like states in insects. However, most of these results could have other explanations, including changes in motivation and attention. To control for these explanations, we developed a novel judgment bias test, requiring bumblebees to make an active choice indicating their interpretation of ambiguous stimuli. Bumblebees were trained to associate high or low rewards, in two different reward chambers, with distinct colours. We subsequently presented bees with ambiguous colours between the two learnt colours. In response, physically stressed bees were less likely than control bees to enter the reward chamber associated with high reward. Signal detection and drift diffusion models showed that stressed bees were more likely to choose low reward locations in response to ambiguous cues. The signal detection model further showed that the behaviour of stressed bees was explained by a reduction in the estimated probability of high rewards. We thus provide strong evidence for judgement biases in bees and suggest that their stress-induced behaviour is explained by reduced expectation of higher rewards, as expected for a pessimistic judgement bias.
Different memory systems in food-hoarding birds: A response to Pravosudov by Smulders TV, Read JCA, SmuldersRead2024.pdf (0.5 MiB) - We recently showed that food-hoarding birds use familiarity processes more than recollection processes when remembering the spatial location of their caches (Smulders et al., Animal Cognition 26:1929-1943, 2023). Pravosudov (Learning & Behavior, https://doi.org/ https://doi.org/10.3758/s13420-023-00616-x , 2023) called our findings into question, claiming that our method is unable to distinguish between recollection and familiarity, and that associative learning tasks are a better way to study the memory for cache sites. In this response, we argue that our methods would have been more likely to detect recollection than familiarity, if Pravosudov's assertions were correct. We also point out that associative learning mechanisms may be good for building semantic knowledge, but are incompatible with the needs of cache site memory, which requires the unique encoding of caching events.
Seeing the future: Predictive control in neural models of ocular accommodation by Read JCA, Kaspiris-Rousellis C, Wood TS, Wu B, Vlaskamp BNS, Schor CM, ReadKaspirisRousellisWoodWuVlaskampSchor2022.pdf (5.4 MiB) - Ocular accommodation is the process of adjusting the eye's crystalline lens so as to bring the retinal image into sharp focus. The major stimulus to accommodation is therefore retinal defocus, and in essence, the job of accommodative control is to send a signal to the ciliary muscle which will minimize the magnitude of defocus. In this article, we first provide a tutorial introduction to control theory to aid vision scientists without this background. We then present a unified model of accommodative control that explains properties of the accommodative response for a wide range of accommodative stimuli. Following previous work, we conclude that most aspects of accommodation are well explained by dual integral control, with a “fast” or “phasic” integrator enabling response to rapid changes in demand, which hands over control to a “slow” or “tonic” integrator which maintains the response to steady demand. Control is complicated by the sensorimotor latencies within the system, which delay both information about defocus and the accommodation changes made in response, and by the sluggish response of the motor plant. These can be overcome by incorporating a Smith predictor, whereby the system predicts the delayed sensory consequences of its own motor actions. For the first time, we show that critically-damped dual integral control with a Smith predictor accounts for adaptation effects as well as for the gain and phase for sinusoidal oscillations in demand. In addition, we propose a novel proportional-control signal to account for the power spectrum of accommodative microfluctuations during steady fixation, which may be important in hunting for optimal focus, and for the nonlinear resonance observed for low-amplitude, high-frequency input.
Stereopsis without correspondence by Read JCA, Read2022.pdf (1.9 MiB) - Stereopsis has traditionally been considered a complex visual ability, restricted
to large-brained animals. The discovery in the 1980s that insects, too, have
stereopsis, therefore, challenged theories of stereopsis. How can such simple
brains see in three dimensions? A likely answer is that insect stereopsis has
evolved to produce simple behaviour, such as orienting towards the closer
of two objects or triggering a strike when prey comes within range. Scientific
thinking about stereopsis has been unduly anthropomorphic, for example
assuming that stereopsis must require binocular fusion or a solution of the
stereo correspondence problem. In fact, useful behaviour can be produced
with very basic stereoscopic algorithms which make no attempt to achieve
fusion or correspondence, or to produce even a coarse map of depth across
the visual field. This may explain why some aspects of insect stereopsis
seem poorly designed from an engineering point of view: for example,
paying no attention to whether interocular contrast or velocities match. Such
algorithms demonstrably work well enough in practice for their species, and
may prove useful in particular autonomous applications.
This article is part of a discussion meeting issue ‘New approaches to 3D
vision’.
Synthetic OCT Data Generation to Enhance the Performance of Diagnostic Models for Neurodegenerative Diseases by Danesh H, Steel DH, Hogg J, Ashtari F, Innes WF, Bacardit, J, Hurlbert A, Read JCA, Kafieh R, DaneshMaghooliDehghaniKafieh2021.pdf (3.1 MiB) - Purpose: Optical coherence tomography (OCT) has recently emerged as a source for powerful biomarkers in neurodegenerative diseases such as multiple sclerosis (MS) and neuromyelitis optica (NMO). The application of machine learning techniques to the analysis of OCT data has enabled automatic extraction of information with potential to aid the timely diagnosis of neurodegenerative diseases. These algorithms require large amounts of labeled data, but few such OCT data sets are available now.
Methods: To address this challenge, here we propose a synthetic data generation method yielding a tailored augmentation of three-dimensional (3D) OCT data and preserving differences between control and disease data. A 3D active shape model is used to produce synthetic retinal layer boundaries, simulating data from healthy controls (HCs) as well as from patients with MS or NMO.
Results: To evaluate the generated data, retinal thickness maps are extracted and evaluated under a broad range of quality metrics. The results show that the proposed model can generate realistic-appearing synthetic maps. Quantitatively, the image histograms of the synthetic thickness maps agree with the real thickness maps, and the cross-correlations between synthetic and real maps are also high. Finally, we use the generated data as an augmentation technique to train stronger diagnostic models than those using only the real data.
Conclusions: This approach provides valuable data augmentation, which can help overcome key bottlenecks of limited data.
Translational Relevance: By addressing the challenge posed by limited data, the proposed method helps apply machine learning methods to diagnose neurodegenerative diseases from retinal imaging.
A computational model of stereoscopic prey capture in praying mantises by O’Keeffe J, Yap SH, Llamas-Cornejo I, Nityananda V, Read JCA, OKeeffeYapLlamasCornejoNityanandaRead2022.pdf (4.2 MiB) - We present a simple model which can account for the stereoscopic sensitivity of praying mantis predatory strikes. The model consists of a single “disparity sensor”: a binocular neuron sensitive to stereoscopic disparity and thus to distance from the animal. The model is based closely on the known behavioural and neurophysiological properties of mantis stereopsis. The monocular inputs to the neuron reflect temporal change and are insensitive to contrast sign, making the sensor insensitive to interocular correlation. The monocular receptive fields have a excitatory centre and inhibitory surround, making them tuned to size. The disparity sensor combines inputs from the two eyes linearly, applies a threshold and then an exponent output nonlinearity. The activity of the sensor represents the model mantis’s instantaneous probability of striking. We integrate this over the stimulus duration to obtain the expected number of strikes in response to moving targets with different stereoscopic disparity, size and vertical disparity. We optimised the parameters of the model so as to bring its predictions into agreement with our empirical data on mean strike rate as a function of stimulus size and disparity. The model proves capable of reproducing the relatively broad tuning to size and narrow tuning to stereoscopic disparity seen in mantis striking behaviour. Although the model has only a single centre-surround receptive field in each eye, it displays qualitatively the same interaction between size and disparity as we observed in real mantids: the preferred size increases as simulated prey distance increases beyond the preferred distance. We show that this occurs because of a stereoscopic “false match” between the leading edge of the stimulus in one eye and its trailing edge in the other; further work will be required to find whether such false matches occur in real mantises. Importantly, the model also displays realistic responses to stimuli with vertical disparity and to pairs of identical stimuli offering a “ghost match”, despite not being fitted to these data. This is the first image-computable model of insect stereopsis, and reproduces key features of both neurophysiology and striking behaviour.
Binocular responsiveness of projection neurons of the praying mantis optic lobe in the frontal visual field by Rosner R, Tarawneh G, Lukyanova V, Read JCA, Full-text-available-for-free-at-https.txt (94 B) - Praying mantids are the only insects proven to have stereoscopic vision (stereopsis): the ability to perceive depth from the slightly shifted images seen by the two eyes. Recently, the first neurons likely to be involved in mantis stereopsis were described and a speculative neuronal circuit suggested. Here we further investigate classes of neurons in the lobula complex of the praying mantis brain and their tuning to stereoscopically-defined depth. We used sharp electrode recordings with tracer injections to identify visual projection neurons with input in the optic lobe and output in the central brain. In order to measure binocular response fields of the cells the animals watched a vertical bar stimulus in a 3D insect cinema during recordings. We describe the binocular tuning of 19 neurons projecting from the lobula complex and the medulla to central brain areas. The majority of neurons (12/19) were binocular and had receptive fields for both eyes that overlapped in the frontal region. Thus, these neurons could be involved in mantis stereopsis. We also find that neurons preferring different contrast polarity (bright vs dark) tend to be segregated in the mantis lobula complex, reminiscent of the segregation for small targets and widefield motion in mantids and other insects.
A neuronal correlate of insect stereopsis by Rosner R, von Hadeln J, Tarawneh G, Read JCA, Rosner_et_al-2019-Nature_Communications.pdf (2.9 MiB) - A puzzle for neuroscience-and robotics-is how insects achieve surprisingly complex behaviours with such tiny brains. One example is depth perception via binocular stereopsis in the praying mantis, a predatory insect. Praying mantids use stereopsis, the computation of distances from disparities between the two retinal images, to trigger a raptorial strike of their forelegs when prey is within reach. The neuronal basis of this ability is entirely unknown. Here we show the first evidence that individual neurons in the praying mantis brain are tuned to specific disparities and eccentricities, and thus locations in 3D-space. Like disparity-tuned cortical cells in vertebrates, the responses of these mantis neurons are consistent with linear summation of binocular inputs followed by an output nonlinearity. Our study not only proves the existence of disparity sensitive neurons in an insect brain, it also reveals feedback connections hitherto undiscovered in any animal species.
The psychophysics of stereopsis can be explained without invoking independent ON and OFF channels by Read JCA, Cumming BG, ReadCumming2019.pdf (1.3 MiB) - Early vision proceeds through distinct ON and OFF channels, which encode luminance increments and decrements respectively. It has been argued that these channels also contribute separately to stereoscopic vision. This is based on the fact that observers perform better on a noisy disparity discrimination task when the stimulus is a random-dot pattern consisting of equal numbers of black and white dots (a “mixed-polarity stimulus”, argued to activate both ON and OFF stereo channels), than when it consists of all-white or all-black dots (“same-polarity”, argued to activate only one). However, it is not clear how this theory can be reconciled with our current understanding of disparity encoding. Recently, a binocular convolutional neural network was able to replicate the mixed-polarity advantage shown by human observers, even though it was based on linear filters and contained no mechanisms which would respond separately to black or white dots. Here, we show that a subtle feature of the way the stimuli were constructed in all these experiments can explain the results. The interocular correlation between left and right images is actually lower for the same-polarity stimuli than for mixed-polarity stimuli with the same amount of disparity noise applied to the dots. Since our current theories suggest stereopsis is based on a correlation-like computation in primary visual cortex, this can explain why performance was better for the mixed-polarity stimuli. We conclude that there is currently no evidence supporting separate ON and OFF channels in stereopsis.
Apparent Motion Perception in the Praying Mantis: Psychophysics and Modelling by Tarawneh G, Jones L, Nityananda V, Rosner R, Rind C, Read JCA, TarawnehNityanandaJonesNityanandaRosnerRindRead2018.pdf (0.9 MiB) - Apparent motion is the perception of motion created by rapidly presenting still frames in which objects are displaced in space. Observers can reliably discriminate the direction of apparent motion when inter-frame object displacement is below a certain limit, Dmax. Earlier studies of motion perception in humans found that Dmax is lower-bounded at around 15 arcmin, and thereafter scales with the size of the spatial elements in the images. Here, we run corresponding experiments in the praying mantis Sphodromantis lineola to investigate how Dmax scales with the element size. We use random moving chequerboard patterns of varying element and displacement step sizes to elicit the optomotor response, a postural stabilization mechanism that causes mantids to lean in the direction of large-field motion. Subsequently, we calculate Dmax as the displacement step size corresponding to a 50% probability of detecting an optomotor response in the same direction as the stimulus. Our main findings are that the mantis Dmax scales roughly as a square-root of element size and that, in contrast to humans, it is not lower-bounded. We present two models to explain these observations: a simple high-level model based on motion energy in the Fourier domain and a more-detailed one based on the Reichardt Detector. The models present complementary intuitive and physiologically-realistic accounts of how Dmax scales with the element size in insects. We conclude that insect motion perception is limited by only a single stage of spatial filtering, reflecting the optics of the compound eye. In contrast, human motion perception reflects a second stage of spatial filtering, at coarser scales than imposed by human optics, likely corresponding to the magnocellular pathway. After this spatial filtering, mantis and human motion perception and Dmax are qualitatively very similar.
