- Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections (Konkle & Alvarez, NeurIPS 2023)
- Decision-margin consistency: A principled metric for human and machine performance alignment (Alvarez & Konkle, UniReps workshop, NeurIPS 2024)
- A large-scale examination of inductive biases shaping high-level visual representation in brains and machines (Conwell et al, Nature Communications, 2024)
- Contrastive learning explains the emergence and function of visual category-selective regions (Prince et al, Science Advances, 2024)
- Full-field fMRI: a novel approach to study immersive vision (Park, et al., Nature Comms, 2024)
- Emergent dimensions underlying the reachable world (Josephs, et al., Cognition, 2023)
- Systematic transition from boundary extension to contraction along an object-to-scene continuum (Park, et al., Cognition, 2024)
- Cortical topographic motifs emerge in a self-organized map of object space (Doshi & Konkle, Science Advances, 2023)
Several preprints and talks delivered.
Research Experience
Current researcher at Harvard University, research projects include deep neural network model development and human-model comparisons, application of contrastive learning in biological visual representation, etc.
Background
Research Interests: organization of the visual system, interface between vision and action demands, conceptual representation; Professional Field: Neuroscience, Cognitive Science.
Miscellany
Contact: talia_konkle@harvard.edu | CV | Google Scholar | @talia_konkle
Office Address: William James Hall 780, 33 Kirkland St, Cambridge, MA