6 papers
Integrated representational signatures strengthen specificity in brains and models
Jialin Wu, Shreya Saha, Yiqing Bo +1
The extent to which different neural or artificial neural networks (models) rely on equivalent representations to support similar tasks remains a central question in neuroscience a…
Comparing and Integrating Different Notions of Representational Correspondence in Neural Systems
Jialin Wu, Shreya Saha, Yiqing Bo +1
The extent to which different biological and artificial neural systems rely on equivalent internal representations to support similar tasks remains a central question in neuroscien…
Barycentric alignment for instance-level comparison of neural representations
Shreya Saha, Zoe Wanying He, Meenakshi Khosla
Comparing representations across neural networks is challenging because representations admit symmetries, such as arbitrary reordering of units or rotations of activation space, th…
Measuring the Measures: Discriminative Capacity of Representational Similarity Metrics Across Model Families
Jialin Wu, Shreya Saha, Yiqing Bo +1
Representational similarity metrics are fundamental tools in neuroscience and AI, yet we lack systematic comparisons of their discriminative power across model families. We introdu…
Modeling the language cortex with form-independent and enriched representations of sentence meaning reveals remarkable semantic abstractness
Shreya Saha, Shurui Li, Greta Tuckute +5
The human language system represents both linguistic forms and meanings, but the abstractness of the meaning representations remains debated. Here, we searched for abstract represe…
Modeling the Human Visual System: Comparative Insights from Response-Optimized and Task-Optimized Vision Models, Language Models, and different Readout Mechanisms
Shreya Saha, Ishaan Chadha, Meenakshi Khosla
Over the past decade, predictive modeling of neural responses in the primate visual system has advanced significantly, largely driven by various DNN approaches. These include model…