首页|Energy-information trade-off induces continuous and discontinuous phase transitions in lateral predictive coding
Energy-information trade-off induces continuous and discontinuous phase transitions in lateral predictive coding
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Lateral predictive coding is a recurrent neural network that.creates energy-efficient internal representations by exploiting statis-tical regularity in sensory inputs.Here,we analytically investigate the trade-off between information robustness and energy in a linear model of lateral predictive coding and numerically minimize a free energy quantity.We observed several phase transi-tions in the synaptic weight matrix,particularly a continuous transition that breaks reciprocity and permutation symmetry and builds cyclic dominance and a discontinuous transition with the associated sudden emergence of tight balance between excitatory and inhibitory interactions.The optimal network follows an ideal gas law over an extended temperature range and saturates the efficiency upper bound of energy use.These results provide theoretical insights into the emergence and evolution of complex internal models in predictive processing systems.
predictive codingrecurrent neural networkphase transitioninternal modelfree energy
Zhen-Ye Huang、Ruyi Zhou、Miao Huang、Hai-Jun Zhou
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Key Laboratory for Theoretical Physics,Institute of Theoretical Physics,Chinese Academy of Sciences,Beijing 100190,China
School of Physical Sciences,University of Chinese Academy of Sciences,Beijing 100049,China
School of Optics and Photonics,Beijing Institute of Technology,Beijing 100081,China
Minjiang Collaborative Center for Theoretical Physics,Minjiang University,Fuzhou 350108,China
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National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Innovation Institute of Defense Technology
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