[HTML][HTML] Emergent human-like covert attention in feedforward convolutional neural networks

S Srivastava, WY Wang, MP Eckstein - Current Biology, 2024‏ - cell.com
Covert attention allows the selection of locations or features of the visual scene without
moving the eyes. Cues and contexts predictive of a target's location orient covert attention …

Efficient coding theory of dynamic attentional modulation

W Młynarski, G Tkačik - PLoS Biology, 2022‏ - journals.plos.org
Activity of sensory neurons is driven not only by external stimuli but also by feedback signals
from higher brain areas. Attention is one particularly important internal signal whose …

The geometry of efficient codes: how rate-distortion trade-offs distort the latent representations of generative models

L D'Amato, GL Lancia, G Pezzulo - arxiv preprint arxiv:2406.07269, 2024‏ - arxiv.org
Living organisms rely on internal models of the world to act adaptively. These models cannot
encode every detail and hence need to compress information. From a cognitive standpoint …

Modeling Adaptability Mechanisms of Speech Perception

N Jurov - 2024‏ - search.proquest.com
Speech is a complex, redundant and variable signal happening in a noisy and ever
changing world. How do listeners navigate these complex auditory scenes and continuously …

[HTML][HTML] Exploring the bounded rationality in human decision anomalies through an assemblable computational framework

YL Lu, YF Lu, X Ren, H Zhang - Cognitive Psychology, 2025‏ - Elsevier
Some seemingly irrational decision behaviors (anomalies), once seen as flaws in human
cognition, have recently received explanations from a rational perspective. The basic idea is …

A neural architecture for selective attention to speech features

N Jurov, W Idsardi, NH Feldman - Proceedings of Interspeech, 2023‏ - par.nsf.gov
Speech perception is complex and demands constant adaptations to the speaker and the
environment (ie noisy speech, accent, etc.). To adapt, the listener relies on one speech …

Implications of capacity-limited, generative models for human vision

JS German, RA Jacobs - Behavioral and Brain Sciences, 2023‏ - search.proquest.com
Although discriminative deep neural networks are currently dominant in cognitive modeling,
we suggest that capacity-limited, generative models are a promising avenue for future work …

Linking cognitive and neural models of audiovisual processing to explore speech perception in autism

G Brown, NH Feldman - Proceedings of the Annual Meeting of the …, 2023‏ - escholarship.org
Autistic and neurotypical children do not handle audiovisual speech in the same manner.
Current evidence suggests that this difference occurs at the level of cue combination. Here …

Coding strategies in memory for 3d objects: The influence of task uncertainty

C Bates, S Gershman - Proceedings of the Annual Meeting of the …, 2022‏ - escholarship.org
Memory is limited in capacity, which means that we must choose what information to
prioritize for storage. Part of knowing what to prioritize is predicting future needs. For …

Learning generalizable representations through compression

Z Fang - 2022‏ - search.proquest.com
The ability of humans and other animals to generalize from their past experiences to novel
situations is at the heart of intelligent behavior. Generalization is more likely to occur …