An Integrative Account of Neural Network Interaction: Neuro-Messenger Theory

Neural interaction is realized by information exchange. It seemed that the information amount does not keep constant and may be reduced during the travel between neural nodes. In addition, recent research of neural coding has suggested that neural information could be represented by parsimonious spiking pattern, named sparse coding. Based on the above observation, neuro-messenger theory (NMT) is proposed to explicate the communicative process between the source and the target neural nodes. Neuro-messenger is a sparse code which does not have to carry every detail of the dynamics in source node. Other formats of neural coding (e.g., temporal and rate coding) could be the precursors of neuro-messengers, and the repeated spatiotemporal patterns buried in the ongoing brain activities may be the circulated neuro-messengers from diverse origins. Referred to chaos/complexity theory, information can be recovered at target node where neuro-messenger serves as a facilitator to locate the trajectory at proper attractor, and hence the associated psychological entity. In contrast to conventional concepts of encoding and decoding, the processes of encoding in source node, issuing neuro-messengers, and recovering information at target node are summarized as “three-facet coding scheme”. The design of neuro-messenger enables the brain to utilize energy in an efficient and economical way. NMT may have substantial implication in several major psychiatric disorders. Some psychiatric conditions could be mediated by abnormal neuro-messengers that coerce the regional neuro-dynamics to delve into maladaptive attractors and hence the characteristic symptoms.

Different coding characteristics between flight and freezing in dorsal periaqueductal gray of mice during exposure to innate threats

Background:Flight and freezing are two vital defensive behaviors that mice display to avoid natural enemies.When they are exposed to innate threats,visual cues are processed and transmitted by the visual system into the emotional nuclei and finally transmitted to the periaqueductal gray(PAG)to induce defensive behaviors.However,how the dorsal PAG(dPAG)encodes the two defensive behaviors is unclear.Methods:Multi-array electrodes were implanted in the dPAG nuclei of C57BL/6 mice.Two kinds of visual stimuli(looming and sweeping)were used to induce defensive behaviors in mice.Neural signals under different defense behaviors were recorded,and the encoding characteristics of the two behaviors were extracted and analyzed from spike firing and frequency oscillations.Finally,synchronization of neural activity during the defense process was analyzed.Results:The neural activity between flight and freezing behaviors showed different firing patterns,and the differences in the inter-spike interval distribution were mainly reflected in the 2–10 ms period.The frequency band activities under both defensive behaviors were concentrated in the theta band;the active frequency of flight was~8to 10 Hz,whereas that of freezing behavior was~6 to 8 Hz.The network connection density under both defense behaviors was significantly higher than the period before and after defensive behavior occurred,indicating that there was a high synchronization of neural activity during the defense process.Conclusions:The dPAG nuclei of mice have different coding features between flight and freezing behaviors;during strong looming stimulation,fast neuro-i nstinctive decision making is required while encountering weak sweeping stimulation,and computable planning late behavior is predicted in the early stage.The frequency band activities under both defensive behaviors were concentrated in the theta band.There was a high synchronization of neural activity during the defense process,which may be a key factor triggering different defensive behaviors.

Integrating Various Neural Features Based on Mechanism of Intricate Balance and Ongoing Activity: Unified Neural Account Underlying and Correspondent to Mental Phenomena

In recent decades, brain science has been enriched from both empirical and computational approaches. Interesting emerging neural features include power-law distribution, chaotic behavior, self-organized criticality, variance approach, neuronal avalanches, difference-based and sparse coding, optimized information transfer, maximized dynamic range for information processing, and reproducibility of evoked spatio-temporal motifs in spontaneous activities, and so on. These intriguing findings can be largely categorized into two classes: complexity and regularity. This article would like to highlight that the above-mentioned properties although look diverse and unrelated, but actually may be rooted in a common foundation—excitatory and inhibitory balance (EIB) and ongoing activities (OA). To be clear, description and observation of neural features are phenomena or epiphenomena, while EIB-OA is the underlying mechanism. The EIB is maintained in a dynamic manner and may possess regional specificity, and importantly, EIB is organized along the boundary of phase transition which has been called criticality, bifurcation or edge of chaos. OA is composed of spontaneous organized activity, physiological noise, non-physiological noise and the interacting effect between OA and evoked activities. Based on EIB-OA, the brain may accommodate the property of chaos and regularity. We propose “virtual brain space” to bridge brain dynamics and mental space, and “code driving complexity hypothesis” to integrate regularity and complexity. The functional implication of oscillation and energy consumption of the brain are discussed.

Influence of sympathetic stumulating time series on activity of chronically compressed dorsal root ganglion neurons in rat

Objective: To study responses of injured DRG neurons to sympathetic stimulation with different temporal stimulating pattern. Methods: In chronically compressed DRG model, the spontaneous activity of single fiber from the injured DRG neuron was recorded, lumbar sympathetic trunk was electrical stimulated, and the responses of DRG neurons caused by chaotic and periodic sympathetic stimulation were compared. Results: It was found that the response of DRG increased gradually as the sympathetic stimulating frequency increased from 5 Hz to 20 Hz(P<0.01). The chaotic stimulation evoked much greater response than periodic stimulation did, even though the stimulating frequence was similar(P<0.01). Conclusion: Besides the stimulating frequency, the temporal stimulating pattern is one of important factor that effect response of DRG neuron to sympathetic stimulation. The chaotic activity of neurons might be one of effective way to transmit neural information.

Study of TSP based on self-organizing map

Self-organizing map(SOM) proposed by Kohonen has obtained certain achievements in solving the traveling salesman problem(TSP).To improve Kohonen SOM,an effective initialization and parameter modification method is discussed to obtain a faster convergence rate and better solution.Therefore,a new improved self-organizing map(ISOM)algorithm is introduced and applied to four traveling salesman problem instances for experimental simulation,and then the result of ISOM is compared with those of four SOM algorithms:AVL,KL,KG and MSTSP.Using ISOM,the average error of four travelingsalesman problem instances is only 2.895 0%,which is greatly better than the other four algorithms:8.51%(AVL),6.147 5%(KL),6.555%(KG) and 3.420 9%(MSTSP).Finally,ISOM is applied to two practical problems:the Chinese 100 cities-TSP and102 counties-TSP in Shanxi Province,and the two optimal touring routes are provided to the tourists.

Ventral Hippocampal CA1 Pyramidal Neurons Encode Nociceptive Information

As a main structure of the limbic system,the hippocampus plays a critical role in pain perception and chronicity.The ventral hippocampal CA1(vCA1)is closely associated with negative emotions such as anxiety,stress,and fear,yet how vCA1 neurons encode nociceptive information remains unclear.Using in vivo electrophysiological recording,we characterized vCA1 pyramidal neuron subpopulations that exhibited inhibitory or excitatory responses to plantar stimuli and were implicated in encoding stimuli modalities in naïve rats.Functional heterogeneity of the vCA1 pyramidal neurons was further identified in neuropathic pain conditions:the proportion and magnitude of the inhibitory response neurons paralleled mechanical allodynia and contributed to the confounded encoding of innocuous and noxious stimuli,whereas the excitatory response neurons were still instrumental in the discrimination of stimulus properties.Increased theta power and theta-spike coupling in vCA1 correlated with nociceptive behaviors.Optogenetic inhibition of vCA1 pyramidal neurons induced mechanical allodynia in naïve rats,whereas chemogenetic reversal of the overall suppressed vCA1 activity had analgesic effects in rats with neuropathic pain.These results provide direct evidence for the representations of nociceptive information in vCA1.

On brain activity mapping: Insights and lessons from Brain Decoding Project to map memory patterns in the hippocampus

The BRAIN project recently announced by the president Obama is the reflection of unrelenting human quest for cracking the brain code, the patterns of neuronal activity that define who we are and what we are. While the Brain Activity Mapping proposal has rightly emphasized on the need to develop new technologies for measuring every spike from every neuron, it might be helpful to consider both the theoretical and experimental aspects that would accelerate our search for the organizing principles of the brain code. Here we share several insights and lessons from the similar proposal, namely, Brain Decoding Project that we initiated since 2007. We provide a specific example in our initial mapping of real-time memory traces from one part of the memory circuit, namely, the CA1 region of the mouse hippocampus. We show how innovative behavioral tasks and appropriate mathematical analyses of large datasets can play equally, if not more, important roles in uncovering the specific-to-general feature-coding cell assembly mechanism by which episodic memory, semantic knowledge, and imagination are generated and organized. Our own experiences suggest that the bottleneck of the Brain Project is not only at merely developing additional new technologies, but also the lack of efficient avenues to disseminate cutting edge platforms and decoding expertise to neuroscience community. Therefore, we propose that in order to harness unique insights and extensive knowledge from various investigators working in diverse neuroscience subfields, ranging from perception and emotion to memory and social behaviors, the BRAIN project should create a set of International and National Brain Decoding Centers at which cutting-edge recording technologies and expertise on analyzing large datasets analyses can be made readily available to the entire community of neuroscientists who can apply and schedule to perform cutting-edge research.

A neural network model on self-organizing emergence of simple-cell receptive field with orientation selectivity in visual cortex

In order to probe into the self-organizing emergence of simple cell orientation selectivity,we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells.However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.

nanoscale communication networks： utilizing an active network architecture

A safe and reliable nication network will be of in vivo nanoscale commu- great benefit for medical diagnosis and monitoring as well as medical implant communication. This review article provides a brief introduction to nanoscale and molecular networking in general and provides opinions on the role of active networking for in vivo nanoscale information transport. While there are many in vivo communication mechanisms that can be leveraged, for example, forms of cell signaling, gap junctions, calcium and ion signaling, and circulatory borne communication, this review examines two in particular： molecular motor transport and neuronal information communication. Molecular motors transport molecules representing information and neural coding operates by means of the action potential; these mechan- isms are reviewed within the theoretical framework of an active network. This review suggests that an active networking paradigm is necessary at the nanoscale along with a new communication constraint, namely, minimiz- ing the communication impact upon the living environment. The goal is to assemble efficient nanoscale and molecular communication channels while minimizing disruption to the host organism.