Energy limitation as a selective pressure on the evolution of sensory systems

JE Niven, SB Laughlin - Journal of Experimental Biology, 2008 - journals.biologists.com
Evolution of animal morphology, physiology and behaviour is shaped by the selective
pressures to which they are subject. Some selective pressures act to increase the benefits …

Communication in neuronal networks

SB Laughlin, TJ Sejnowski - Science, 2003 - science.org
Brains perform with remarkable efficiency, are capable of prodigious computation, and are
marvels of communication. We are beginning to understand some of the geometric …

[KNIHA][B] Principles of neural design

P Sterling, S Laughlin - 2015 - books.google.com
Neuroscience research has exploded, with more than fifty thousand neuroscientists applying
increasingly advanced methods. A mountain of new facts and mechanisms has emerged …

Single Ih channels in pyramidal neuron dendrites: properties, distribution, and impact on action potential output

MHP Kole, S Hallermann, GJ Stuart - Journal of Neuroscience, 2006 - Soc Neuroscience
The hyperpolarization-activated cation current (I h) plays an important role in regulating
neuronal excitability, yet its native single-channel properties in the brain are essentially …

Fly photoreceptors demonstrate energy-information trade-offs in neural coding

JE Niven, JC Anderson, SB Laughlin - PLoS biology, 2007 - journals.plos.org
Trade-offs between energy consumption and neuronal performance must shape the design
and evolution of nervous systems, but we lack empirical data showing how neuronal energy …

Neuronal energy consumption: biophysics, efficiency and evolution

JE Niven - Current opinion in neurobiology, 2016 - Elsevier
Highlights•Electrical signaling consumes substantial amounts of energy influencing
physiology and anatomy.•Action potential energy consumption depends on the voltage …

Energy-efficient neuronal computation via quantal synaptic failures

WB Levy, RA Baxter - Journal of Neuroscience, 2002 - Soc Neuroscience
Organisms evolve as compromises, and many of these compromises can be expressed in
terms of energy efficiency. For example, a compromise between rate of information …

Design of silicon brains in the nano-CMOS era: Spiking neurons, learning synapses and neural architecture optimization

AS Cassidy, J Georgiou, AG Andreou - Neural Networks, 2013 - Elsevier
We present a design framework for neuromorphic architectures in the nano-CMOS era. Our
approach to the design of spiking neurons and STDP learning circuits relies on parallel …

Energy‐efficient neural information processing in individual neurons and neuronal networks

L Yu, Y Yu - Journal of Neuroscience Research, 2017 - Wiley Online Library
Brains are composed of networks of an enormous number of neurons interconnected with
synapses. Neural information is carried by the electrical signals within neurons and the …

Efficient sampling and noisy decisions

JA Heng, M Woodford, R Polania - Elife, 2020 - elifesciences.org
Human decisions are based on finite information, which makes them inherently imprecise.
But what determines the degree of such imprecision? Here, we develop an efficient coding …