13 papers · ranked by Valyu relevance
William B Levy, Victoria G. Calvert
Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. After establishing an energy-efficient viewpoint, we define computation and construct an energy-constrained, computational function that can be optimized.…
William Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington
The efficient coding hypothesis presents a compelling success story for theoretical and systems neuroscience. It marshals a unifying idea, that neural codes can be understood as efficient encodings of natural stimuli, to explain phenomena from across sensory systems, sometimes with exquisite precision. However, similar…
Raja Appuswamy, Jacques Fellay, Nimisha Chaturvedi
Rapid advances in sequencing technologies are producing genomic data on an unprecedented scale. The first, and often one of the most time consuming, step of genomic data analysis is sequence alignment, where sequenced reads must be aligned to a reference genome. Several years of research on alignment algorithms has led…
Hongwei Cai, Zheng Ao, Chunhui Tian, Zhuhao Wu + 5 more
Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we…
Eugene Christo V R, Christoph Robert Meinecke, Bert Nitzsche, Roman Lyttleton + 5 more
Network-based biocomputing (NBC) presents an energy-efficient, parallel computing approach for solving nondeterministic polynomial time (NP) complete problems by leveraging motor-driven cytoskeletal filaments that explore all possible solutions through nanofabricated networks in a massively parallel fashion. However…
Dale Zhou, Christopher W. Lynn, Zaixu Cui, Rastko Ciric + 8 more
In systems neuroscience, most models posit that brain regions communicate information under constraints of efficiency. Yet, metabolic and information transfer efficiency across structural networks are not understood. In a large cohort of youth, we find metabolic costs associated with structural path strengths…
Juan Pablo Franco, Nitin Yadav, Peter Bossaerts, Carsten Murawski
Life presents us with decisions of varying degrees of difficulty. Many of them are NP-hard, that is, they are computationally intractable. Two important questions arise: which properties of decisions drive extreme computational hardness and what are the effects of these properties on human-decision making? Here, we…
Juan P. Franco, Karlo Doroc, Nitin Yadav, Peter Bossaerts + 1 more
The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of…
Tianxiang Gao, Omri Finkel, Jeff Dangl, Vladimir Jojic
Identifying significant causal agents among a large number of candidates is challenging. When experimental resources are limited, exhaustively screening a large number of agents for the desired effect could incur a large cost and take a substantial amount of time. However, in many large scale experiments, such as…
Lewis Grozinger, Jesús Miró-Bueno, Ángel Goñi-Moreño
The programming of computations in living cells can be done by manipulating information flows within genetic networks. Typically, a single bit of information is encoded by a single gene’s steady state expression. Expression is discretized into high and low levels that correspond to 0 and 1 logic values, analogous to…
Thomas D. Schneider
Unlike the Carnot heat engine efficiency published in 1824, an isothermal efficiency derived from thermodynamics and information theory can be applied to biological systems. The original approach by Pierce and Cutler in 1959 to derive the isothermal efficiency equation came from Shannon’s channel capacity of 1949 and…
Veronika Koren, Simone Blanco Malerba, Tilo Schwalger, Stefano Panzeri
The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuroscience, it has remained unclear whether fundamental empirical properties of neural network activity can be…
Michał J. Wójcik, Amy Li, Dante Wasmuht, Jake P. Stroud + 3 more
Working memory has been traditionally studied as a passive storage for information. However, recent advances have suggested that working memory is prospective rather than retrospective, meaning that its content undergoes transformations that will support future behaviour. One perspective that underscores this notion…