Neural Functional Alignment Space: Brain-Referenced Representation of Artificial Neural Networks
Authors: Ruiyu Yan, Hanqi Jiang, Yi Pan, Xiaobo Li, Tianming Liu, Xi Jiang, Lin Zhao
Organizations: Tandon School of Engineering, New York University, Brooklyn, NY 11201, USA · School of Computing, University of Georgia, Athens, GA 30602, USA · Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA · The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroInformation,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China
We propose the Neural Functional Alignment Space (NFAS), a brain-referenced representational framework for characterizing artificial neural networks on equal functional grounds. NFAS departs from conventional alignment approaches that rely on layer-wise features or task-specific activations by modeling the intrinsic dynamical evolution of stimulus representations across network depth. Specifically, we model layer-wise embeddings as a depth-wise dynamical trajectory and apply Dynamic Mode Decomposition (DMD) to extract the stable mode. This representation is then projected into a biologically anchored coordinate system defined by distributed neural responses. We also introduce the Signal-to-Noise Consistency Index (SNCI) to quantify cross-model consistency at the modality level. Across 45 pretrained models spanning vision, audio, and language, NFAS reveals structured organization within this brain-referenced space, including modality-specific clustering and cross-modal convergence in integrative cortical systems. Our findings suggest that representation dynamics provide a principled basis for
Figures & tables
Figure 1: Overview of the Neural Functional Alignment Space Framework
Figure 2: Structured Geometry of the Neural Functional Alignment Space.
Figure 3: Modality-Specific Cortical Distribution of SNCI.
Figure 4: Comparison of brain SNCI across functional networks.
Department of Experimental Psychology, University of Oxford, Oxford, UK · Gatsby Unit & Sainsbury Wellcome Centre, University College London, London, UK