Biology subjects

Lourenco, S. F.

Publications and source records attributed to Lourenco, S. F..

5 recordsLinked to original sources

bioRxiv2024

Fast and robust visual object recognition in young children

By adulthood, humans rapidly identify objects from sparse visual displays and across significant disruptions to their appearance. What are the minimal conditions needed to achieve robust recognition abilities and when might these abilities develop? To test this question, we investigated the upper-limits of childrens object recognition abilities. We found that children as young as 3-years-of-age successfully identified objects at speeds of 100 ms (both forward and backward masked) under sparse and disrupted viewing conditions. By contrast, a range computational models implemented with biologically plausible properties or optimized for visual recognition did not reach child-level performance. Models only matched children if they were trained with more data than children are capable of experiencing. These findings highlight the robustness of the human visual system in the absence of extensive experience and identify important developmental constraints for building biologically plausible machines.

neuroscience↗

bioRxiv2023

Visual looming is a primitive for human emotion

Looming objects afford threat of collision across the animal kingdom. Defensive responses to looming and neural computations for looming detection are strikingly conserved across species. In mammals, information about rapidly approaching threats is conveyed from the retina to the midbrain superior colliculus, where variables that indicate the position and velocity of approach are computed to enable defensive behavior. Although neuroscientific theories posit that midbrain representations contribute to emotion through connectivity with distributed brain systems, it remains unknown whether a computational system for looming detection can predict both defensive behavior and phenomenal experience in humans. Here, we show that a shallow convolutional neural network based on the Drosophila visual system predicts defensive blinking to looming objects in infants and superior colliculus responses to optical expansion in adults. Further, the responses of the convolutional network to a broad array of naturalistic video clips predict self-reported emotion largely on the basis of subjective arousal. Our findings illustrate how motor and experiential components of human emotion relate to species-general systems for survival in unpredictable environments.

neuroscience↗

bioRxiv2019

A dual role for shape skeletons in human vision: perceptual organization and object recognition

Shape perception is crucial for object recognition. However, it remains unknown exactly how shape information is represented, and, consequently, used by the visual system. Here, we hypothesized that the visual system represents "shape skeletons" to both (1) perceptually organize contours and component parts into a shape percept, and (2) compare shapes to recognize objects. Using functional magnetic resonance imaging (fMRI) and representational similarity analysis (RSA), we found that a model of skeletal similarity explained significant unique variance in the response profiles of V3 and LO, regions known to be involved in perceptual organization and object recognition, respectively. Moreover, the skeletal model remained predictive in these regions even when controlling for other models of visual similarity that approximate low- to high-level visual features (i.e., Gabor-jet, GIST, HMAX, and AlexNet), and across different surface forms, a manipulation that altered object contours while preserving the underlying skeleton. Together, these findings shed light on the functional roles of shape skeletons in human vision, as well as the computational properties of V3 and LO.

neuroscience↗

bioRxiv2019

Canine sense of quantity: evidence for numerical ratio-dependent activation in parietotemporal cortex

The approximate number system, which supports the rapid estimation of quantity, emerges early in human development and is widespread across species. Neural evidence from both human and non-human primates suggests the parietal cortex as a primary locus of numerical estimation, but it is unclear whether the numerical competencies observed across non-primate species are subserved by similar neural mechanisms. Moreover, because studies with non-human animals typically involve extensive training, little is known about the spontaneous numerical capacities of non-human animals. To address these questions, we examined the neural underpinnings of number perception using awake canine functional magnetic resonance imaging. Dogs passively viewed dot arrays that varied in ratio and, critically, received no task-relevant training or exposure prior to testing. We found evidence of ratio-dependent activation, which is a key feature of the approximate number system, in canine parietotemporal cortex in the majority of dogs tested. This finding is suggestive of a neural mechanism for quantity perception that has been conserved across mammalian evolution.

neuroscience↗

bioRxiv2019

Skeletal descriptions of shape provide unique and privileged perceptual information for object recognition

With seemingly little effort, humans can both identify an object across large changes in orientation and extend category membership to novel exemplars. Although researchers argue that object shape is crucial in these cases, there are open questions as to how shape is represented for object recognition. Here we tested whether the human visual system incorporates a three-dimensional skeletal descriptor of shape to determine an objects identity. Skeletal models not only provide a compact description of an objects global shape structure, but also provide a quantitative metric by which to compare the visual similarity between shapes. Our results showed that a model of skeletal similarity explained the greatest amount of variance in participants object dissimilarity judgments when compared with other computational models of visual similarity (Experiment 1). Moreover, parametric changes to an objects skeleton led to proportional changes in perceived similarity, even when controlling for another model of structure (Experiment 2). Importantly, participants preferentially categorized objects by their skeletons across changes to local shape contours and non-accidental properties (Experiment 3). Our findings highlight the importance of skeletal structure in vision, not only as a shape descriptor, but also as a diagnostic cue of object identity.

neuroscience↗