14 papers · ranked by Valyu relevance
Arish Alreja, Ilya Nemenman, Christopher J. Rozell, Lyle J. Graham
The number of neurons in mammalian cortex varies by multiple orders of magnitude across different species. In contrast, the ratio of excitatory to inhibitory neurons (E:I ratio) varies in a much smaller range, from 3:1 to 9:1 and remains roughly constant for different sensory areas within a species. Despite this…
Yanbo Lian, Anthony N. Burkitt, Boris S. Gutkin
Sparse coding, predictive coding and divisive normalization have each been found to be principles that underlie the function of neural circuits in many parts of the brain, supported by substantial experimental evidence. However, the connections between these related principles are still poorly understood. Sparse coding…
Ziniu Wu, Harold Rockwell, Yimeng Zhang, Shiming Tang + 2 more
'Frédéric E. Theunissen'] System identification techniques-projection pursuit regression models (PPRs) and convolutional neural networks (CNNs)-provide state-of-the-art performance in predicting visual cortical neurons’ responses to arbitrary input stimuli. However, the constituent kernels recovered by these methods…
Joshua Bowren, Luis Sanchez-Giraldo, Odelia Schwartz
Sparse coding has been incorporated in models of the visual cortex for its computational advantages and connection to biology. But how the level of sparsity contributes to performance on visual tasks is not well understood. In this work, sparse coding has been integrated into an existing hierarchical V2 model ([21])…
Ilias Rentzeperis, Luca Calatroni, Laurent U. Perrinet, Dario Prandi + 1 more
'Xue-Xin Wei'] Growing evidence indicates that only a sparse subset from a pool of sensory neurons is active for the encoding of visual stimuli at any instant in time. Traditionally, to replicate such biological sparsity, generative models have been using the ℓ1 norm as a penalty due to its convexity, which makes it…
Hadi Vafaii, Dekel Galor, Jacob L. Yates
Variational autoencoders (VAEs) employ Bayesian inference to interpret sensory inputs, mirroring processes that occur in primate vision across both ventral [1] and dorsal [2] pathways. Despite their success, traditional VAEs rely on continuous latent variables, which deviates sharply from the discrete nature of…
Sahar Behpour, David J. Field, Mark V. Albert
Correlated, spontaneous neural activity is known to play a necessary role in visual development, but the higher-order statistical structure of these coherent, amorphous patterns has only begun to emerge in the past decade. Several computational studies have demonstrated how this endogenous activity can be used to train…
Yueran Qi, Yang Feng, Hai Wang, Chengcheng Wang + 7 more
'Jing Liu' 'Xuepeng Zhan' 'Jixuan Wu' 'Qianwen Wang' 'Jiezhi Chen' 'Aiqun Liu'] To address the concerns with power consumption and processing efficiency in big-size data processing, sparse coding in computing-in-memory (CIM) architectures is gaining much more attention. Here, a novel Flash-based CIM architecture is…
Catherine W. Tallman, Peter N. Steinmetz, John T. Wixted
Neurocomputational models hold that individual episodic memories are represented by a sparse, pattern-separated coding scheme in the hippocampus. Animal studies further suggest that the allocation of neurons to such codes is non-random and may be biased by their excitability at the time of encoding. Here, utilizing an…
Xin Li, Shuo Wang
This paper presents a theoretical perspective on modeling ventral stream processing by revisiting the computational abstraction of simple and complex cells. In parallel to David Marr's vision theory, we organize the new perspective into three levels. At the computational level, we abstract simple and complex cells into…
Wiktor Młynarski, Gašper Tkačik, Adam Kohn
Activity of sensory neurons is driven not only by external stimuli but also by feedback signals from higher brain areas. Attention is one particularly important internal signal whose presumed role is to modulate sensory representations such that they only encode information currently relevant to the organism at minimal…
Shyam Srinivasan, Simon Daste, Mehrab N. Modi, Glenn C. Turner + 3 more
Sparse coding can improve discrimination of sensory stimuli by reducing overlap between their representations. Two factors, however, can offset sparse coding’s benefits: similar sensory stimuli have significant overlap and responses vary across trials. To elucidate the effects of these 2 factors, we analyzed odor…
Naomi Auer, Lars Chen, Jakob Stubenrauch, Benjamin Lindner + 2 more
The brain can efficiently learn and form memories based on limited exposure to stimuli, often even in single trials. Two key factors are believed to support this ability: large synaptic plasticity to strongly encode new memories; and sparse coding, leading to low overlap between memory representations and to small…
Xiwei She, Bryan J. Moore, Brent M. Roeder, George Nune + 14 more
The hippocampus is crucial for forming new episodic memories. While its role in encoding spatial and temporal information (where and when) is well understood, how it encodes objects (what) remains unclear due to the high dimensionality of object space. Rather than encoding each object separately, the hippocampus may…