Visual representations

Visual representations become progressively more abstract along the cortical hierarchy. These abstract representations define notions like objects and shapes but at the cost of spatial specificity. By contrast, low-level regions represent spatially local but simple input features. How do spatially non-specific representations of abstract concepts in high-level areas flexibly modulate the low-level sensory representations in appropriate ways to guide context-driven and goal-directed behaviors across various tasks? We present a biologically motivated and trainable neural network model of dyna

Practicing a visual task leads to long-lasting perceptual improvements in humans and other animals. However, the generalization of Visual Learning (VL) to unseen conditions varies across different tasks. Particularly, it has been shown that learning ‘easy’ visual tasks leads to better generalization than learning ‘hard’ ones. Moreover, experimental evidence suggests that greater generalizability in VL can be achieved through sequential curriculum training, specifically by training on ‘easier’ versions of a task before progressing to ‘harder’ versions. Yet, a neurocomputational explanation for

…models of the joint learning of visual representations, eye movements, and accommodation control in the perception-action cycle. The simulated lens properties are kept simple for efficiency reasons but are detailed enough to capture essential depth-of-field effects. The model can simulate different accommodation states depending on focal point and pupil aperture. The longitudinal chromatic aberration is used to produce c

Spatial reasoning is the capacity to manipulate visual representations. Performance on spatial reasoning tasks has been related to testosterone, which increases in males during pubertal development. Nevertheless, it is not clear if children of different pubertal development have indeed differences in pubertal development, since the studies have not controlled the age and education of participants.Participants were 36 girls and 28 boys (10.28±0.98 years; 5.13±1.0 completed school years). The score on the Pubertal Development Scale was used to create high and low pubertal development groups, whi

Recent experiments demonstrate that the brain transforms visual inputs into representations that follow straighter temporal trajectories than their initial photoreceptor encoding, facilitating prediction by linear extrapolation (Hénaff et al 2019; 2021). Can the brain use this principle to learn visual representations? Here, we develop an objective that quantifies straightening, augment it with a regularizer to prevent collapse to trivial solutions, and use it to train deep feedforward neural networks on video sequences. Decoding of the learned representation with a separately trained readout

…involving a comparison between a visual input and a mental representation of faces, built from previous experience. Whilst emotional state was found to affect the way humans attend to faces, little research has explored the effects of emotions on the mental representation of faces. Here, we examined the specific perceptual modulation of geometric properties of the mental representations associated with state anxiety and state depression on face detection, and to compare their emotional expression. To this end, we used an adaptation

…I will explore how and why visual representations and analogies are related, and why. I will also explore how considering the relation between analogy and spatial reasoning can shed light on why and how spatial thinking is correlated with learning in STEM fields. For example, I will consider children’s numbers sense and learning of the number line from the perspective of analogical reasoning.