Behavioral experiments: Compressed timeline of past and future
Behavioral experiments test whether people search the recent past and the near future along an ordered, compressed timeline.
Temporal coding in neural populations
Single-unit recordings reveal compressed sequential activity and slowly varying temporal context signals that can support a mental timeline.
Reinforcement learning with cognitive maps
Agents learn latent variables directly from pixels and represent those learned dimensions as compressed, map-like internal codes.
Using compressed maps for long-range time-series prediction and time-scale invariance
DeepSITH and related models use logarithmically compressed memory to support long-range prediction and robust generalization across temporal rescaling.
Modeling path integration to identify early markers of Alzheimer's disease
A mechanistic model of path integration decomposes navigation errors and helps identify early changes associated with subjective cognitive decline.
Learning from infant perspective: slow changes for development of a visual system in humans and machines
Head-mounted infant videos reveal a natural slow-to-fast developmental curriculum, and training in that order improves later visual recognition.
ModelVsBaby: Object recognition in infants and machines
ModelVsBaby compares toddlers and models on realistic, silhouette, geon, blurred, and feature-only views of common objects.
Aligning foundation models with human perception
Vision-language models and humans show closely aligned perceptual structure in both individual feature ratings and representational geometry.
LLMs and Episodic memory
Language models retrieve temporal sequences in a way that looks more like serial recall than human episodic retrieval, and induction heads help explain why.
Group coordination in humans and LLMs
Human groups coordinate more stably than large-language-model groups, which tend to show high volatility and action bias in common-interest games.