Publications

Andre Longon, David Klindt, Meenakshi Khosla (2025). Superposition disentanglement of neural representations reveals hidden alignment. NeurIPS, UniReps.

Zoe He, Sean Trott, Meenakshi Khosla (2025). Seeing Through Words, Speaking Through Pixels: Deep Representational Alignment Between Vision and Language Models. EMNLP.

Shaan Shah, Meenakshi Khosla (2025). Representational Alignment Across Model Layers and Brain Regions with Hierarchical Optimal Transport.

Shreya Saha, Shurui Li, Greta Tuckute, Yuanning Li, Ru-Yuan Zhang, Leila Wehbe, Evelina Fedorenko, Meenakshi Khosla (2025). Modeling the language cortex with form-independent and enriched representations of sentence meaning reveals remarkable semantic abstractness.

Jialin Wu, Shreya Saha, Yiqing Bo, Meenakshi Khosla (2025). Measuring the Measures: Discriminative Capacity of Representational Similarity Metrics Across Model Families.

Jialin Wu, Shreya Saha, Yiqing Bo, Meenakshi Khosla (2025). Integrated representational signatures strengthen specificity in brains and models.

Yiqing Bo, Ansh Soni, Sudhanshu Srivastava, Meenakshi Khosla (2025). Evaluating representational similarity measures from the lens of functional correspondence. CCN.

Chaitanya Kapoor, Sudhanshu Srivastava, Meenakshi Khosla (2025). Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts. NeurIPS.

Jenelle Feather, Meenakshi Khosla, N Apurva Ratan Murty, Aran Nayebi (2025). Brain-model evaluations need the neuroai turing test.

Jialin Wu, Shreya Saha, Yiqing Bo, Meenakshi Khosla (2025). A Data-driven Typology of Vision Models from Integrated Representational Metrics.

Shreya Saha, Ishan Chadha, Meenakshi Khosla (2025). Modeling the Human Visual System: Comparative Insights from Response‑Optimized and Task‑Optimized Vision Models, Language Models, and Different Readout Mechanisms. CCN.

Meenakshi Khosla, Alex Williams (2023). Soft Matching Distance: A metric on neural representations that captures single-neuron tuning. NeurIPS UniReps.

Meenakshi Khosla, Alex Williams, Josh McDermott, Nancy Kanwisher (2023). Privileged representational axes in biological and artificial neural networks.

Meenakshi Khosla, Leila Wehbe (2023). Higher visual areas act like domain-general filters with strong selectivity and functional specialization.

Nancy Kanwisher, Meenakshi Khosla, Katharina Dobs (2023). Using artificial neural networks to ask ‘why’questions of minds and brains. Trends in Neurosciences.

Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (2022). Characterizing the ventral visual stream with response-optimized neural encoding models. In NeurIPS (Oral).

Meenakshi Khosla, N Apurva Ratan Murty, Nancy Kanwisher (2022). A highly selective response to food in human visual cortex revealed by hypothesis-free voxel decomposition. Current Biology.

Gia H Ngo, Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (2022). Predicting individual task contrasts from resting‐state functional connectivity using a surface‐based convolutional network. NeuroImage.

Zijin Gu, Keith Jamison, Meenakshi Khosla, Emily J. Allen, Yihan Wu, Ghislain St-Yves, Thomas Naselaris, Kendrick Kay, Mert Sabuncu, Amy Kuceyeski (2022). NeuroGen: Activation optimized image synthesis for discovery neuroscience. NeuroImage.

Meenakshi Khosla, Gia H Ngo, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (2021). Cortical response to naturalistic stimuli is largely predictable with deep neural networks. Science Advances.

Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (2020). Neural encoding with visual attention. In NeurIPS (Oral).

Gia H. Ngo, Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (2020). From connectomic to task-evoked fingerprints: Individualized prediction of task contrasts from resting-state functional connectivity. In MICCAI (Oral).

Meenakshi Khosla, Gia H. Ngo, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (2020). A shared neural encoding model for the prediction of subject-specific fMRI response. In MICCAI (Oral).

Meenakshi Khosla, Keith Jamison, Gia H Ngo, Amy Kuceyeski, Mert Sabuncu (2019). Machine learning in resting-state fMRI analysis. Magnetic resonance imaging.

Meenakshi Khosla, Keith Jamison, Gia H Ngo, Amy Kuceyeski, Mert Sabuncu (2019). Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction. NeuroImage.

Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (2018). 3D convolutional neural networks for classification of functional connectomes. In MICCAI DLMIA workshop.

Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu (0001). Detecting abnormalities in resting-state dynamics: An unsupervised learning approach. In MICCAI MLMI workshop.