Quantum Brain States

If conscious observers are to be included in the quantum mechanical universe, we need to find the rules that engage observers with quantum mechanical systems. The author has proposed five rules that are discovered by insisting on empirical completeness; that is, by requiring the rules to draw empirical information from Schrödinger's solutions that is more complete than is currently possible with the (Born) probability interpretation. I discard Born's interpretation, introducing probability solely through probability current. These rules tell us something about brains. They require the existence of observer brain states that are neither conscious nor unconscious. I call them ready brain states because they are on stand-by, ready to become conscious the moment they are stochastically chosen. Two of the rules are selection rules involving ready brain states. The place of these rules in a wider theoretical context is discussed.     

脑科学与量子理论

简要回顾了生物学与物理学之间的紧密关系,其中包括人工神经网络的经典物理模型和脑的某些量子理论;概要综述了细胞骨架微管的结构和生物功能及有关近期理论研究。注意到微声是细胞和神经元中重要的组成和功能单元,进而以较大篇幅介绍了近期关于微管的理论研究工作,特别是基于量子场论中两能级系统的赝自旋模型,对微管管壁上电子的动力学行为作了较深入的探讨;此外,基于量子场论,对微管中的水分子系统可能存在微波受激辐射也作了阐述。The present paper briefly reviews the relationship between biology and physics, especially including the classical physics models for the artificial neuron networks, some quantum theories for brains, and simply describes the structures and functions of cytoskeletal microtubules （MTs） in cells and some recent theoretical studies on MTs.Noting MTs are the important components and function units in cells and neurons, furthermore, the paper lays emphasis on our recent theoretical work on MTs. Particularly, based on the pseudo-spin quantum theory, the dynamic behavior of electrons on the MT wall has been discussed in some detail. Based on the quantum field theory, it has been described that the maser radiation might exist in the water molecular system within the MT.     

Self-organized Criticality in Hierarchical Brain Network

It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.     

Self-organized Criticality in Hierarchical Brain Network

It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.     

Brain maps of Iowa gambling task

Background  

Somatic Marker Hypothesis (SMH), based on clinical observations, delineates neuronal networks for interpreting consciousness generation and decision-making. The Iowa gambling task (IGT) was designed to verify the SMH. However, more and more behavioral and brain imaging studies had reported incongruent results that pinpointed a need to re-evaluate the central representations of SMH. The current study used event-related fMRI (functional Magnetic Resonance Imaging) to examine neural correlates of anticipation vs. outcome, wins vs. losses, and differential decks' contingencies of IGT.     

Analysis of Brain Tissue by FT-IR Microspectroscopy

Biological specimens contain a vast array of cell types, cell layers, extracellular materials, and other components that are structurally and functionally interrelated. Although the histological relationship of each of these constituents has been documented for most mammalian tissues, the chemical relationships between constituents has largely gone unexplored. Fourier transform infrared (FT-IR) spectroscopy can be a powerful tool for analyzing the chemical composition and molecular interactions of biological materials. Analyses of biological materials, however, have been conducted primarily on homogenized and/or purified samples. As a consequence of these limitations, the distribution and concentration of functional groups within different regions of biological tissues have not been appreciated. Several recent technological developments have enabled an FT-IR spectrometer to be combined with microscope optics. This integrated instrument, called an FT-IR microspectrometer, is capable of collecting good quality spectra from small regions of tissues down to a 10 μm × 10 μm square. Spectra collected along a grid pattern can be combined to generate contour or three-dimensional maps that represent the concentration and distribution of functional groups across a tissue. This is important because it permits a correlation of the spatial concentration of chemical functional groups with tissue histology. Analyses can be performed on normal tissue or tissues with unique properties, i.e., developmental or pathological tissues. This review will focus on FT-IR microspectroscopic investigations of normal biological tissue. Particular attention will be given to one example of FT-IR microspectroscopic analysis: white matter of brain tissue. This region was chosen because its infrared profile is very different from other brain regions, and thus it provides a clear illustration of the information that can be obtained by FT-IR microspectroscopy. This review is intended for the spectroscopist who is interested in applying his or her expertise to biological questions as well as to the biologist who is looking for new ways to obtain chemical information about his or her area of study.     

Modelling Human Cortical Network in Real Brain Space

Highly specific structural organization is of great significance in the topology of cortical networks. We introduce a human cortical network model, taking the specific cortical structure into account, in which nodes are brain sites placed in the actual positions of cerebral cortex and the establishment of edges depends on the spatial path length rather than the linear distance. The resulting network exhibits the essential features of cortical connectivity, properties of small-world networks and multiple clusters structure. Additionally, assortative mixing is also found in this model. All of these findings may be attributed to the specific cortical architecture.     

Brain mechanisms involved in the control of vocalization

This article reviews recent experimental and clinical literature on the central neural mechanisms involved in vocalization. Various parts of the cerebral cortex, limbic system, basal ganglia, and extrapyramidal system have been shown in human and animal studies to be important in vocalization, but the exact function of these areas with regard to vocal control is unclear. The limbic system and diencephalon project to the midbrain periaqueductal gray (PAG), which may be important for coordination of various muscle groups involved in vocalization. The PAG neurons project to the reticular formation, nucleus retroambiguus, and nucleus ambiguus. Neurons in the nucleus retroambiguus seem to be involved in control of neurons related to the respiratory or laryngeal systems. Different types of motoneurons of the laryngeal muscles in the nucleus ambiguus are related to various functions such as vocalization, swallowing, and respiration.     

基于高斯平均的DTI脑模板构建方法

在获取被试的张量数据后通常对其进行多通道线性平均以得到张量模板．但线性平均不仅会忽略张量中的向量信息,还会使灰质和白质的交界处过于平滑,降低模板的分辨率．为了解决以上问题,本文引入了四元数及高斯加权平均来构建高斯扩散张量成像（Diffusion Tensor Imaging,DTI）脑模板．本文首先对55个健康被试的DTI数据进行预处理,使得数据伪影最小化;再通过扩散张量成像工具包（Diffusion Tensor Imaging ToolKit,DTI-TK）将预处理后的数据进行初步空间标准化;然后将张量通过特征分解得到特征向量和特征值;最后,将由特征向量转化的四元数标量和特征值分别进行高斯加权平均得到平均后的特征向量和特征值,并对其进行重建得到张量模板．实验结果表明相比于线性DTI模板,高斯DTI模板在DTED、COH、DVED、OVL、corr FA评估指标上表现更优,而IA指标较差,说明本文提出的高斯DTI模板在整体信息保留方面有所优化,但方向信息有所丢失．     

脑科学研究中的质子磁共振波谱方法

核磁共振（NMR）波谱作为一种操作简单、高效且重复性良好的技术手段,在脑科学领域的应用日益广泛,尤其是离体核磁共振氢谱（¹H NMR）和活体核磁共振氢谱（¹H MRS）.¹H NMR和¹H MRS在实验设计、样品预处理、数据处理等方面各有优劣、各擅胜场.本综述主要从适用范围、样品预处理、数据处理分析等方面,对二者在方法学层面的研究现状进行总结和讨论,以期为脑科学领域的研究者进行大脑代谢相关研究时提供一定的参考和帮助.     

EEG Fractal Analysis Reflects Brain Impairment after Stroke

Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.     

Brain weight differences associated with induced focal microgyria

Background  

Disrupting neural migration with bilateral focal freezing necrosis on postnatal day 1 (P1) results in the formation of 4-layered microgyria. This developmental injury triggers a pervasive neural reorganization, which is evident at the electrophysiological, behavioral, and anatomical levels. In this experiment, we investigated changes in brain weight as an index of global disruption of neural systems caused by focal damage to the developing cortical plate.     

Multidisciplinary Role of Mesoporous Silica Nanoparticles in Brain Regeneration and Cancers: From Crossing the Blood–Brain Barrier to Treatment

Mesoporous silica nanoparticles (MSNs) have gained wide attention for their role in biomedicine and as drug delivery vehicles. Their structural tunability, high surface area, and easy functionalization impart significant advantages over conventional materials. In this Review, recent advances in the synthesis, drug delivery, and therapeutic roles of MSNs in the treatment of various neurodegenerative and neuroinflammatory diseases are presented. The intention is to understand how MSN formulations that are capable of encapsulating drug molecules can enhance drug delivery by overcoming the blood–brain barrier (BBB) mediated by specific transport processes. The composition and characteristics of the BBB, and how alterations are observed in neurodegenerative diseases including Alzheimer's, epilepsy, and intracerebral hemorrhage are reviewed. Finally, the factors affecting efficient delivery of MSNs into the brain are summarized, and their most promising functional outcomes are discussed.     

高级脑活动的功能性核磁共振成像

功能性核磁共振成像技术可以显示大脑各个区域内静脉毛细血管中血液氧合状态所起的磁共振信号的小变化。使用ｆＭＲＩ的方法，可以在正常的活体上无损伤地实现大脑活动的功能定位，时空分辨率可分别达到秒和毫米数量级，尽管目前还面临一系列技术的困难，ｆＭＲＩ已经日益成为观察大脑活动，研究有脑的拓扑结构，进而揭示脑和思维关系的一种重要方法。     

Brain stem neuronal noise and neocortical “resonance”

We present a qualitative model and data in evidence for the selection and stabilization of neocortical brain-wave power spectral modes by slow periodic and fast noise driving by brain stem neurons. Unlike noise effects in a bistable potential, increasing noise amplitude via more brain stem neurons increases the measure on unstable manifolds trapped in the saddle-sinks of the neural membrane attractor andincreases dwell times. We suggest that the effect of noise in expanding dynamical systems such as the generalized neuronal membrane equations studied here may be analogous to that of many-frequency quasiperiodic driving which leads to the stabilization of the EEG as a strange, nonchaotic attractor.     

Brain networks responsive to aversive visual stimuli in humans

The neural mechanisms subserving recognition of noxious stimuli and empathy for pain appear to involve at least in part the cortical regions associated with the processing of pain affect. An important issue concerns the specificity of brain networks associated with observing and representing painful conditions, in comparison with other unpleasant stimuli. Recently, we found both similarities and differences between the brain patterns of activity related to the observation of noxious or disgusting stimuli delivered to one hand or foot. Overlap regions included the perigenual anterior cingulate (pACC), whose activity was related to the perceived unpleasantness. We aimed here at revealing how pACC functional connectivity changes in relationship to the different experimental conditions, using a psychophysiological interaction model. Activity in pACC during the observation of painful stimuli was specifically and positively related to regions in the right hemisphere, including portions of the prefrontal, midcingulate and insular cortex. On the other hand, positive changes in pACC connectivity during the vision of disgusting stimuli were present in the right basal ganglia. These data suggest that pACC activity is part of different networks involved in the recognition of painful or disgusting stimuli.