关于耦合神经元活动时的能量原理

最近美国耶鲁大学的神经科学家们用实验数据表明,哺乳动物大脑皮层中神经信号的传递是一个代价昂贵的能量支出过程,而神经信号的编码是与能量代谢紧密地耦合在一起的,但是到目前为止还无法定量给出神经元活动时的能量函数。在这篇文章中,能量原理被用于神经活动和神经信息处理机制的研究,在电生理实验数据的基础上,建立神经元活动的用能量函数表示的运动方程。结果表明用能量函数表达耦合神经元的阈下电活动和动作电位,数值计算结果与用Hodgkin-Huxley方程所描述的动作电位一致。从而有可能依据能量原理从脑信息处理的角度揭示和理解大脑神经网络系统的信息表现规律。     

Asymmetric neural coding revealed by in vivo calcium imaging in the honey bee brain

Left–right asymmetries are common properties of nervous systems. Although lateralized sensory processing has been well studied, information is lacking about how asymmetries are represented at the level of neural coding. Using in vivo functional imaging, we identified a population-level left–right asymmetry in the honey bee''s primary olfactory centre, the antennal lobe (AL). When both antennae were stimulated via a frontal odour source, the inter-odour distances between neural response patterns were higher in the right than in the left AL. Behavioural data correlated with the brain imaging results: bees with only their right antenna were better in discriminating a target odour in a cross-adaptation paradigm. We hypothesize that the differences in neural odour representations in the two brain sides serve to increase coding capacity by parallel processing.     

Information coding by ensembles of resonant neurons

In the present paper, we propose a novel neural procedure for signal processing and coding based on the subthreshold oscillations and resonance of the neural membrane potential that could be used by real neurons to perform frequency spectra analysis and information coding of incoming signals. Taking into account the biophysical properties of the neural membranes, we note that the subthreshold resonant behaviour they exhibit can be used to analyse incoming signals and represent them in the frequency domain. We study the reliability of the representation of signals depending on the biophysical parameters of the neurons, the fault-tolerance of this coding scheme and its robustness against noise and in the presence of spikes. The principal characteristics of our system are the use of the physical phenomenon of neural resonance (rarely considered in the literature for signal coding); it fits well with the biophysical parameters of most neurons that exhibit subthreshold oscillations; it is compatible with experimental data; and it can be easily integrated in a more general model of information processing and coding that includes communication between neurons based on spikes.     

Quantifying the information transmitted in a single stimulus

Information theory - in particular mutual information- has been widely used to investigate neural processing in various brain areas. Shannon mutual information quantifies how much information is, on average, contained in a set of neural activities about a set of stimuli. To extend a similar approach to single stimulus encoding, we need to introduce a quantity specific for a single stimulus. This quantity has been defined in literature by four different measures, but none of them satisfies the same intuitive properties (non-negativity, additivity), that characterize mutual information. We present here a detailed analysis of the different meanings and properties of these four definitions. We show that all these measures satisfy, at least, a weaker additivity condition, i.e. limited to the response set. This allows us to use them for analysing correlated coding, as we illustrate in a toy-example from hippocampal place cells.     

神经元信息编码的代谢消耗：动作电位与能量效率

人脑是一个高效、可靠的信息处理系统,它主导着个体的认知、情感、意识与行为,这些功能的实现需要不断地消耗代谢能量.大脑的能量需求主要被神经元信息编码所消耗,相应的亚细胞过程包括产生和传导动作电位、维持静息电位以及突触传递.神经元编码信息的主要载体是动作电位序列,它的产生与传导贡献了大脑的大部分代谢消耗.动作电位的能量消耗受离子通道的生物物理特性控制.生物物理特性的细胞特异性和空间异质性使得动作电位对代谢能量的利用效率呈现高度可变性,它为理解神经元代谢消耗的规律、起因与结果带来了挑战.本文首先介绍参与神经元编码的亚细胞过程及它们在大脑和小脑皮层中的代谢消耗,然后详细梳理近年来关于动作电位代谢消耗的研究成果,重点讨论影响其能量效率的生物物理因素和放电形状特性,并归纳总结放电消耗的特点,最后对未来神经元编码的代谢消耗研究进行展望.     

An information theoretic characterisation of auditory encoding

The entropy metric derived from information theory provides a means to quantify the amount of information transmitted in acoustic streams like speech or music. By systematically varying the entropy of pitch sequences, we sought brain areas where neural activity and energetic demands increase as a function of entropy. Such a relationship is predicted to occur in an efficient encoding mechanism that uses less computational resource when less information is present in the signal: we specifically tested the hypothesis that such a relationship is present in the planum temporale (PT). In two convergent functional MRI studies, we demonstrated this relationship in PT for encoding, while furthermore showing that a distributed fronto-parietal network for retrieval of acoustic information is independent of entropy. The results establish PT as an efficient neural engine that demands less computational resource to encode redundant signals than those with high information content.     

神经信息学的原理与展望

神经信息学是研究神经系统信息的载体形式,神经信息的产生、传输、加工、编码、存储与提取机理,以及建立神经数据库系统的科学。它是脑科学,信息科学和计算机科学相互交叉的边缘学科。神经信息学可分为分子神经信息学和系统神经信息学两个层次。神经信息编码可分为神经元脉冲序列的数字编码和突触联结权重编码两种编码方式。对21世纪神经信息学可能取得的新进展进行分析和预测,并论证开展人类神经组计划（HuNP）和建立神经数据库系统的必要性与可行性。对人类神经计划与人类脑计划的异同步,进行比较和讨论。     

Cracking the code of oscillatory activity

Neural oscillations are ubiquitous measurements of cognitive processes and dynamic routing and gating of information. The fundamental and so far unresolved problem for neuroscience remains to understand how oscillatory activity in the brain codes information for human cognition. In a biologically relevant cognitive task, we instructed six human observers to categorize facial expressions of emotion while we measured the observers' EEG. We combined state-of-the-art stimulus control with statistical information theory analysis to quantify how the three parameters of oscillations (i.e., power, phase, and frequency) code the visual information relevant for behavior in a cognitive task. We make three points: First, we demonstrate that phase codes considerably more information (2.4 times) relating to the cognitive task than power. Second, we show that the conjunction of power and phase coding reflects detailed visual features relevant for behavioral response--that is, features of facial expressions predicted by behavior. Third, we demonstrate, in analogy to communication technology, that oscillatory frequencies in the brain multiplex the coding of visual features, increasing coding capacity. Together, our findings about the fundamental coding properties of neural oscillations will redirect the research agenda in neuroscience by establishing the differential role of frequency, phase, and amplitude in coding behaviorally relevant information in the brain.     

Graded,Dynamically Routable Information Processing with Synfire-Gated Synfire Chains

Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Recently experimental evidence has been presented suggesting that neural information is encoded and transferred in packets, i.e., in stereotypical, correlated spiking patterns of neural activity. Due to their relevance to coherent spiking, synfire chains are one of the main theoretical constructs that have been appealed to in order to describe coherent spiking and information transfer phenomena. However, for some time, it has been known that synchronous activity in feedforward networks asymptotically either approaches an attractor with fixed waveform and amplitude, or fails to propagate. This has limited the classical synfire chain’s ability to explain graded neuronal responses. Recently, we have shown that pulse-gated synfire chains are capable of propagating graded information coded in mean population current or firing rate amplitudes. In particular, we showed that it is possible to use one synfire chain to provide gating pulses and a second, pulse-gated synfire chain to propagate graded information. We called these circuits synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded information can rapidly cascade through a neural circuit, and show a correspondence between this type of transfer and a mean-field model in which gating pulses overlap in time. We show that SGSCs are robust in the presence of variability in population size, pulse timing and synaptic strength. Finally, we demonstrate the computational capabilities of SGSC-based information coding by implementing a self-contained, spike-based, modular neural circuit that is triggered by streaming input, processes the input, then makes a decision based on the processed information and shuts itself down.     

Neural coding and contextual influences in the whisker system

A fundamental problem in neuroscience, to which Prof. Segundo has made seminal contributions, is to understand how action potentials represent events in the external world. The aim of this paper is to review the issue of neural coding in the context of the rodent whiskers, an increasingly popular model system. Key issues we consider are: the role of spike timing; mechanisms of spike timing; decoding and context-dependence. Significant insight has come from the development of rigorous, information theoretic frameworks for tackling these questions, in conjunction with suitably designed experiments. We review both the theory and experimental studies. In contrast to the classical view that neurons are noisy and unreliable, it is becoming clear that many neurons in the subcortical whisker pathway are remarkably reliable and, by virtue of spike timing with millisecond-precision, have high bandwidth for conveying sensory information. In this way, even small (~200 neuron) subcortical modules are able to support the sensory processing underlying sophisticated whisker-dependent behaviours. Future work on neural coding in cortex will need to consider new findings that responses are highly dependent on context, including behavioural and internal states. This article is part of a special issue on Neuronal Dynamics of Sensory Coding.     

Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex

Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial frequency (SF) signals and had different neural origins. The low gamma (LG; 25 to 40 Hz) rhythm was generated at the V1 superficial layer and preferred a higher SF compared with spike activity, whereas both the medium gamma (MG; 40 to 65 Hz), generated at the cortical level, and the high gamma HG; (65 to 85 Hz), originated precortically, preferred lower SF information. Furthermore, compared with the rates of spike activity, the powers of the 3 gammas had better performance in discriminating the edge and surface of simple objects. These findings suggest that gamma rhythms reflect the neural dynamics of neural circuitries that process different SF information in the visual system, which may be crucial for multiplexing SF information and synchronizing different features of an object.

Gamma rhythms in many brain regions are thought to play a role in information processing. This study reports the surprising coexistence of three narrow-band gamma rhythms in visual cortex with distinct coding properties for visual features and distinct neural origins.     

Gill surface area provides a clue for the respiratory basis of brain size in the blacktip shark (Carcharhinus limbatus)

Brain size varies dramatically, both within and across species, and this variation is often believed to be the result of trade-offs between the cognitive benefits of having a large brain for a given body size and the energetic cost of sustaining neural tissue. One potential consequence of having a large brain is that organisms must also meet the associated high energetic demands. Thus, a key question is whether metabolic rate correlates with brain size. However, using metabolic rate to measure energetic demand yields a relatively instantaneous and dynamic measure of energy turnover, which is incompatible with the longer evolutionary timescale of changes in brain size within and across species. Morphological traits associated with oxygen consumption, specifically gill surface area, have been shown to be correlates of oxygen demand and energy use, and thus may serve as integrated correlates of these processes, allowing us to assess whether evolutionary changes in brain size correlate with changes in longer-term oxygen demand and energy use. We tested how brain size relates to gill surface area in the blacktip shark Carcharhinus limbatus. First, we examined whether the allometric slope of brain mass (i.e., the rate that brain mass changes with body mass) is lower than the allometric slope of gill surface area across ontogeny. Second, we tested whether gill surface area explains variation in brain mass, after accounting for the effects of body mass on brain mass. We found that brain mass and gill surface area both had positive allometric slopes, with larger individuals having both larger brains and larger gill surface areas compared to smaller individuals. However, the allometric slope of brain mass was lower than the allometric slope of gill surface area, consistent with our prediction that the allometric slope of gill surface area could pose an upper limit to the allometric slope of brain mass. Finally, after accounting for body mass, individuals with larger brains tended to have larger gill surface areas. Together, our results provide clues as to how fishes may evolve and maintain large brains despite their high energetic cost, suggesting that C. limbatus individuals with a large gill surface area for their body mass may be able to support a higher energetic turnover, and, in turn, a larger brain for their body mass.     

Spatiotemporal Imaging of Glutamate-Induced Biophotonic Activities and Transmission in Neural Circuits

The processing of neural information in neural circuits plays key roles in neural functions. Biophotons, also called ultra-weak photon emissions (UPE), may play potential roles in neural signal transmission, contributing to the understanding of the high functions of nervous system such as vision, learning and memory, cognition and consciousness. However, the experimental analysis of biophotonic activities (emissions) in neural circuits has been hampered due to technical limitations. Here by developing and optimizing an in vitro biophoton imaging method, we characterize the spatiotemporal biophotonic activities and transmission in mouse brain slices. We show that the long-lasting application of glutamate to coronal brain slices produces a gradual and significant increase of biophotonic activities and achieves the maximal effect within approximately 90 min, which then lasts for a relatively long time (>200 min). The initiation and/or maintenance of biophotonic activities by glutamate can be significantly blocked by oxygen and glucose deprivation, together with the application of a cytochrome c oxidase inhibitor (sodium azide), but only partly by an action potential inhibitor (TTX), an anesthetic (procaine), or the removal of intracellular and extracellular Ca²⁺. We also show that the detected biophotonic activities in the corpus callosum and thalamus in sagittal brain slices mostly originate from axons or axonal terminals of cortical projection neurons, and that the hyperphosphorylation of microtubule-associated protein tau leads to a significant decrease of biophotonic activities in these two areas. Furthermore, the application of glutamate in the hippocampal dentate gyrus results in increased biophotonic activities in its intrahippocampal projection areas. These results suggest that the glutamate-induced biophotonic activities reflect biophotonic transmission along the axons and in neural circuits, which may be a new mechanism for the processing of neural information.     

Neural mechanism of visual information degradation from retina to V1 area

The information processing mechanism of the visual nervous system is an unresolved scientific problem that has long puzzled neuroscientists. The amount of visual information is significantly degraded when it reaches the V1 after entering the retina; nevertheless, this does not affect our visual perception of the outside world. Currently, the mechanisms of visual information degradation from retina to V1 are still unclear. For this purpose, the current study used the experimental data summarized by Marcus E. Raichle to investigate the neural mechanisms underlying the degradation of the large amount of data from topological mapping from retina to V1, drawing on the photoreceptor model first. The obtained results showed that the image edge features of visual information were extracted by the convolution algorithm with respect to the function of synaptic plasticity when visual signals were hierarchically processed from low-level to high-level. The visual processing was characterized by the visual information degradation, and this compensatory mechanism embodied the principles of energy minimization and transmission efficiency maximization of brain activity, which matched the experimental data summarized by Marcus E. Raichle. Our results further the understanding of the information processing mechanism of the visual nervous system.     

Insect–machine hybrid system for understanding and evaluating sensory-motor control by sex pheromone in Bombyx mori

To elucidate the dynamic information processing in a brain underlying adaptive behavior, it is necessary to understand the behavior and corresponding neural activities. This requires animals which have clear relationships between behavior and corresponding neural activities. Insects are precisely such animals and one of the adaptive behaviors of insects is high-accuracy odor source orientation. The most direct way to know the relationships between neural activity and behavior is by recording neural activities in a brain from freely behaving insects. There is also a method to give stimuli mimicking the natural environment to tethered insects allowing insects to walk or fly at the same position. In addition to these methods an ‘insect–machine hybrid system’ is proposed, which is another experimental system meeting the conditions necessary for approaching the dynamic processing in the brain of insects for generating adaptive behavior. This insect–machine hybrid system is an experimental system which has a mobile robot as its body. The robot is controlled by the insect through its behavior or the neural activities recorded from the brain. As we can arbitrarily control the motor output of the robot, we can intervene at the relationship between the insect and the environmental conditions.     

Neuron-astrocyte interactions in the regulation of brain energy metabolism: a focus on NMR spectroscopy

An adequate and timely production of ATP by brain cells is of cardinal importance to support the major energetic cost of the rapid processing of information via synaptic and action potentials. Recently, evidence has been accumulated to support the view that the regulation of brain energy metabolism is under the control of an intimate dialogue between astrocytes and neurons. In vitro studies on cultured astrocytes and in vivo studies on rodents have provided evidence that glutamate and Na(+) uptake in astrocytes is a key triggering signal regulating glucose use in the brain. With the advent of NMR spectroscopy, it has been possible to provide experimental evidence to show that energy consumption is mainly devoted to glutamatergic neurotransmission and that glutamate-glutamine cycling is coupled in a approximately 1 : 1 molar stoichiometry to glucose oxidation, at least in the cerebral cortex. This improved understanding of neuron-astrocyte metabolic interactions offers the potential for developing novel therapeutic strategies for many neurological disorders that include a metabolic deficit.     

Bone fracture characterization under mixed-mode I+II loading using the single leg bending test

Fracture under mixed-mode I+II was induced in bovine cortical bone tissue using a developed miniaturized version of the single leg bending test (SLB). Due to the difficulty in crack length monitoring in the course of the test, an equivalent crack method based on specimen compliance and beam theory was adopted as a data reduction scheme. The method was applied to the experimental results in order to obtain the Resistance curves in each loading mode. The determined fracture energy is well described by an energetic power law whose exponent is below one, which means that the linear energetic criterion is not applicable to this material. The proposed procedure was numerically validated by means of a cohesive mixed-mode I+II damage model with bilinear softening. It was concluded that the miniaturized version of the SLB test is adequate for mixed-mode I+II fracture characterization of bone for a constant mode ratio.     

Cytoskeletal involvement in neuronal learning: a review

This paper introduces the ideas of neural networks in the context of currently recognized cellular structures within neurons. Neural network models and paradigms require adaptation of synapses for learning to occur in the network. Some models of learning paradigms require information to move from axon to dendrite. This motivated us to examine the possibility of intracellular signaling to mediate such signals. The cytoskeleton forms a substrate for intracellular signaling via material transport and other putative mechanisms. Furthermore, many experimental results suggest a link between the cytoskeleton and cognitive processing. In this paper we review research on intracellular signaling in the context of neural network learning.Abbreviations MT microtubule - MTs microtubules - ART adaptive resonance theory - RCE restricted coulomb energy - MAP microtubule associated protein - NO nitric oxide Correspondence to: J. Dayhoff     

Two distinct channels of olfactory bulb output

Rhythmic neural activity is a hallmark of brain function, used ubiquitously to structure neural information. In mammalian olfaction, repetitive sniffing sets the principal rhythm but little is known about its role in sensory coding. Here, we show that mitral and tufted cells, the two main classes of olfactory bulb projection neurons, tightly lock to this rhythm, but to opposing phases of the sniff cycle. This phase shift is established by local inhibition that selectively delays mitral cell activity. Furthermore, while tufted cell phase is unperturbed in response to purely excitatory odorants, mitral cell phase is advanced in a graded, stimulus-dependent manner. Thus, phase separation by inhibition forms the basis for two distinct channels of olfactory processing.     

自然图像效率编码

效率编码理论认为经过漫长历史进化,大脑感知系统有效地适应了自然环境.自然图像统计规律计算建模对视觉信息处理机理的理解大有裨益.本文简要回顾近期视觉系统对自然图像效率编码的最新进展.