In vivo neuropil density from anatomical MRI and machine learning.

Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from a person's individualized neuropil density would be ideal. We hypothesize that in vivo neuropil density can be derived from magnetic resonance imaging (MRI) data, consisting of longitudinal relaxation (T1) MRI for gray/white matter distinction and diffusion MRI for tissue cellularity (apparent diffusion coefficient, ADC) and axon directionality (fractional anisotropy, FA). We present a machine learning algorithm that predicts neuropil density from in vivo MRI scans, where ex vivo Merker staining and in vivo synaptic vesicle glycoprotein 2A Positron Emission Tomography (SV2A-PET) images were reference standards for cellular and synaptic density, respectively. We used Gaussian-smoothed T1/ADC/FA data from 10 healthy subjects to train an artificial neural network, subsequently used to predict cellular and synaptic density for 54 test subjects. While excellent histogram overlaps were observed both for synaptic density (0.93) and cellular density (0.85) maps across all subjects, the lower spatial correlations both for synaptic density (0.89) and cellular density (0.58) maps are suggestive of individualized predictions. This proof-of-concept artificial neural network may pave the way for individualized energy atlas prediction, enabling microscopic interpretations of functional neuroimaging data.

Switching of brain networks across different cerebral perfusion states: insights from EEG dynamic microstate analyses.

The alteration of neural interactions across different cerebral perfusion states remains unclear. This study aimed to fulfill this gap by examining the longitudinal brain dynamic information interactions before and after cerebral reperfusion. Electroencephalogram in eyes-closed state at baseline and postoperative 7-d and 3-month follow-ups (moyamoya disease: 20, health controls: 23) were recorded. Dynamic network analyses were focused on the features and networks of electroencephalogram microstates across different microstates and perfusion states. Considering the microstate features, the parameters were disturbed of microstate B, C, and D but preserved of microstate A. The transition probabilities of microstates A-B and B-D were increased to play a complementary role across different perfusion states. Moreover, the microstate variability was decreased, but was significantly improved after cerebral reperfusion. Regarding microstate networks, the functional connectivity strengths were declined, mainly within frontal, parietal, and occipital lobes and between parietal and occipital lobes in different perfusion states, but were ameliorated after cerebral reperfusion. This study elucidates how dynamic interaction patterns of brain neurons change after cerebral reperfusion, which allows for the observation of brain network transitions across various perfusion states in a live clinical setting through direct intervention.

A 3D atlas of functional human brain energetic connectome based on neuropil distribution.

The human brain is energetically expensive, yet the key factors governing its heterogeneous energy distributions across cortical regions to support its diversity of functions remain unexplored. Here, we built up a 3D digital cortical energy atlas based on the energetic costs of all neuropil activities into a high-resolution stereological map of the human cortex with cellular and synaptic densities derived, respectively, from ex vivo histological staining and in vivo PET imaging. The atlas was validated with PET-measured glucose oxidation at the voxel level. A 3D cortical activity map was calculated to predict the heterogeneous activity rates across all cortical regions, which revealed that resting brain is indeed active with heterogeneous neuronal activity rates averaging around 1.2 Hz, comprising around 70% of the glucose oxidation of the cortex. Additionally, synaptic density dominates spatial patterns of energetics, suggesting that the cortical energetics rely heavily on the distribution of synaptic connections. Recent evidence from functional imaging studies suggests that some cortical areas act as hubs (i.e., interconnecting distinct and functionally active regions). An inverse allometric relationship was observed between hub metabolic rates versus hub volumes. Hubs with smaller volumes have higher synapse density, metabolic rate, and activity rates compared to nonhubs. The open-source BrainEnergyAtlas provides a granular framework for exploring revealing design principles in energy-constrained human cortical circuits across multiple spatial scales.

Metabolic tuning of inhibition regulates hippocampal neurogenesis in the adult brain.

Hippocampus-engaged behaviors stimulate neurogenesis in the adult dentate gyrus by largely unknown means. To explore the underlying mechanisms, we used tetrode recording to analyze neuronal activity in the dentate gyrus of freely moving adult mice during hippocampus-engaged contextual exploration. We found that exploration induced an overall sustained increase in inhibitory neuron activity that was concomitant with decreased excitatory neuron activity. A mathematical model based on energy homeostasis in the dentate gyrus showed that enhanced inhibition and decreased excitation resulted in a similar increase in neurogenesis to that observed experimentally. To mechanistically investigate this sustained inhibitory regulation, we performed metabolomic and lipidomic profiling of the hippocampus during exploration. We found sustainably increased signaling of sphingosine-1-phosphate, a bioactive metabolite, during exploration. Furthermore, we found that sphingosine-1-phosphate signaling through its receptor 2 increased interneuron activity and thus mediated exploration-induced neurogenesis. Taken together, our findings point to a behavior-metabolism circuit pathway through which experience regulates adult hippocampal neurogenesis.

Loss of homeoprotein Msx1 and Msx2 leading to athletic and kinematic impairment related to the increasing neural excitability of neurons in aberrant neocortex in mice.

Although homeoproteins Msx1 and Msx2, the cell-specific transcription regulators, have been proven to play multiple roles in the embryogenesis of bone, muscle and tooth, the functions and mechanisms of Msx1 and Msx2 in the development of the central nervous system of mice after birth are not clear because of the death of Msx1 and Msx1/2 germline-deleted embryo at late gestation of mouse. In current research, Nestin-Cre mice was introduced to generate the central nervous system-specific knockout mice (Nestin-Cre;Msx1,Msx2fl/fl). We found that besides the falling of the body mass and the brain volume, the cortical tissue sections and staining showed the decreasing thickness of layer II-IV and declining number of vertebral cells in layer V resulting from Msx1/2 deletion. In addition, electrophysiological tests revealed the aberrant action potential parameters of deep pyramidal neurons in Nestin-Cre;Msx1,2 fl/fl mice, which may be related with the ethology impairment displayed in further experiments. We discovered Nestin-Cre;Msx1,2 fl/fl mice had severe impairment in their athletic ability and kinematic learning ability in rotate test, and exhibited hyperactivity in open-field test. Above all, our results revealed that deletion of homeoproteins Msx1 and Msx2 could lead to behavioral disorders and suggested that Msx1 and Msx2 played a crucial role in regulating the development and function of the neocortex. In addition, our current research provided a new mouse model for understanding the pathogenesis of human central nervous system disease.

Astrocytic Kir4.1 channels and gap junctions account for spontaneous epileptic seizure.

Experimental recordings in hippocampal slices indicate that astrocytic dysfunction may cause neuronal hyper-excitation or seizures. Considering that astrocytes play important roles in mediating local uptake and spatial buffering of K+ in the extracellular space of the cortical circuit, we constructed a novel model of an astrocyte-neuron network module consisting of a single compartment neuron and 4 surrounding connected astrocytes and including extracellular potassium dynamics. Next, we developed a new model function for the astrocyte gap junctions, connecting two astrocyte-neuron network modules. The function form and parameters of the gap junction were based on nonlinear regression fitting of a set of experimental data published in previous studies. Moreover, we have created numerical simulations using the above single astrocyte-neuron network module and the coupled astrocyte-neuron network modules. Our model validates previous experimental observations that both Kir4.1 channels and gap junctions play important roles in regulating the concentration of extracellular potassium. In addition, we also observe that changes in Kir4.1 channel conductance and gap junction strength induce spontaneous epileptic activity in the absence of external stimuli.

Effects of channel blocking on information transmission and energy efficiency in squid giant axons.

Action potentials are the information carriers of neural systems. The generation of action potentials involves the cooperative opening and closing of sodium and potassium channels. This process is metabolically expensive because the ions flowing through open channels need to be restored to maintain concentration gradients of these ions. Toxins like tetraethylammonium can block working ion channels, thus affecting the function and energy cost of neurons. In this paper, by computer simulation of the Hodgkin-Huxley neuron model, we studied the effects of channel blocking with toxins on the information transmission and energy efficiency in squid giant axons. We found that gradually blocking sodium channels will sequentially maximize the information transmission and energy efficiency of the axons, whereas moderate blocking of potassium channels will have little impact on the information transmission and will decrease the energy efficiency. Heavy blocking of potassium channels will cause self-sustained oscillation of membrane potentials. Simultaneously blocking sodium and potassium channels with the same ratio increases both information transmission and energy efficiency. Our results are in line with previous studies suggesting that information processing capacity and energy efficiency can be maximized by regulating the number of active ion channels, and this indicates a viable avenue for future experimentation.

Therapeutic effects of targeted nursing interventions combined with auricular-plaster therapy on anxiety level and life quality of Hepatitis B patients.

Mood disorders are common problems in patients with chronic hepatitis B virus (HBV) infection, most clinical treatment focus on anti-viral and anti-fibrosis rather than taking care of mood disorders. In the past decades, we have developed a Chinese medicine treatment method together with nursing intervention, which shows a positive treatment effect on patients. 158 cases of hepatitis B patients were randomly divided into one control group (78 cases), and one observation group (80 cases). The patients in control group received hepatology nursing, liver protecting and transaminase lowering medicine, and ear acupoint bean pressing treatment. In addition to the nursing and treatment as the control group, the patients in observation group were given targeted nursing interventions, including psychological intervention, emotional intervention, cognitive intervention, and systematic family and community support intervention. The anxiety level and sleep quality of patients in both groups were compared. The improvement of hepatic indexes was checked and life qualities in both groups were also compared. Compared to the control group, the patients in the observation group provided have statistically significant mprovement on anxiety control, sleep quality, and hepatic indexes changes (P<0.05). The observation group also showed remarkably better life quality scores (GQLI-64) than the control group (P<0.01). This research confirmed that targeted nursing intervention coupled with ear acupoint bean pressing showed effective improvement on the anxiety control and sleep quality of chronic hepatic B patients, and demonstrated better hepatic index recovery. Patients in the observation group also have higher life quality scores than the control group.

Energy-efficient neural information processing in individual neurons and neuronal networks.

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 chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc.

Sparse coding and lateral inhibition arising from balanced and unbalanced dendrodendritic excitation and inhibition.

The precise mechanism by which synaptic excitation and inhibition interact with each other in odor coding through the unique dendrodendritic synaptic microcircuits present in olfactory bulb is unknown. Here a scaled-up model of the mitral-granule cell network in the rodent olfactory bulb is used to analyze dendrodendritic processing of experimentally determined odor patterns. We found that the interaction between excitation and inhibition is responsible for two fundamental computational mechanisms: (1) a balanced excitation/inhibition in strongly activated mitral cells, leading to a sparse representation of odorant input, and (2) an unbalanced excitation/inhibition (inhibition dominated) in surrounding weakly activated mitral cells, leading to lateral inhibition. These results suggest how both mechanisms can carry information about the input patterns, with optimal level of synaptic excitation and inhibition producing the highest level of sparseness and decorrelation in the network response. The results suggest how the learning process, through the emergent development of these mechanisms, can enhance odor representation of olfactory bulb.

Effect of temperature and glia in brain size enlargement and origin of allometric body-brain size scaling in vertebrates.

BACKGROUND: Brain signaling requires energy. The cost of maintaining and supporting energetically demanding neurons is the key constraint on brain size. The dramatic increase in brain size among mammals and birds cannot be understood without solving this conundrum: larger brains, with more neurons, consume more energy. RESULTS: Here we examined the intrinsic relationships between metabolism, body-brain size ratios and neuronal densities of both endothermic and ectothermic animals. We formulated a general model to elucidate the key factors that correlate with brain enlargement, and the origin of allometric body-brain size scaling. This framework identified temperature as a critical factor in brain enlargement via temperature-regulated changes in metabolism. Our framework predicts that ectothermic animals living in tropical climates should have brain sizes that are several times larger than those of ectothermic animals living in cold climates. This prediction was confirmed by data from experiments in fish brains. Our framework also suggests that a rapid increase in the number of less energy-demanding glial cells may be another important factor contributing to the ten-fold increase in the brain sizes of endotherms compared with ectotherms. CONCLUSIONS: This study thus provides a quantitative theory that predicts the brain sizes of all the major types of animals and quantifies the contributions of temperature-dependent metabolism, body size and neuronal density.

Sparse distributed representation of odors in a large-scale olfactory bulb circuit.

In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and generation of testable hypotheses of the functional mechanisms underlying odor representation in the olfactory bulb circuit. Specifically, we demonstrate that lateral inhibition emerges within the olfactory bulb network through recurrent dendrodendritic synapses when constrained by a range of balanced excitatory and inhibitory conductances. We find that the spatio-temporal dynamics of lateral inhibition plays a critical role in building the glomerular-related cell clusters observed in experiments, through the modulation of synaptic weights during odor training. Lateral inhibition also mediates the development of sparse and synchronized spiking patterns of mitral cells related to odor inputs within the network, with the frequency of these synchronized spiking patterns also modulated by the sniff cycle.

Revealing neural dynamical structure of C. elegans with deep learning.

Caenorhabditis elegans serves as a common model for investigating neural dynamics and functions of biological neural networks. Data-driven approaches have been employed in reconstructing neural dynamics. However, challenges remain regarding the curse of high-dimensionality and stochasticity in realistic systems. In this study, we develop a deep neural network (DNN) approach to reconstruct the neural dynamics of C. elegans and study neural mechanisms for locomotion. Our model identifies two limit cycles in the neural activity space: one underpins basic pirouette behavior, essential for navigation, and the other introduces extra Ω turns. The combination of two limit cycles elucidates predominant locomotion patterns in neural imaging data. The corresponding energy landscape explains the switching strategies between two limit cycles, quantitatively, and provides testable predictions on neural functions and circuit roles. Our work provides a general approach to study neural dynamics by combining imaging data and stochastic modeling.

Warm body temperature facilitates energy efficient cortical action potentials.

The energy efficiency of neural signal transmission is important not only as a limiting factor in brain architecture, but it also influences the interpretation of functional brain imaging signals. Action potential generation in mammalian, versus invertebrate, axons is remarkably energy efficient. Here we demonstrate that this increase in energy efficiency is due largely to a warmer body temperature. Increases in temperature result in an exponential increase in energy efficiency for single action potentials by increasing the rate of Na(+) channel inactivation, resulting in a marked reduction in overlap of the inward Na(+), and outward K(+), currents and a shortening of action potential duration. This increase in single spike efficiency is, however, counterbalanced by a temperature-dependent decrease in the amplitude and duration of the spike afterhyperpolarization, resulting in a nonlinear increase in the spike firing rate, particularly at temperatures above approximately 35°C. Interestingly, the total energy cost, as measured by the multiplication of total Na(+) entry per spike and average firing rate in response to a constant input, reaches a global minimum between 37-42°C. Our results indicate that increases in temperature result in an unexpected increase in energy efficiency, especially near normal body temperature, thus allowing the brain to utilize an energy efficient neural code.

Neurophysiology: Hodgkin and Huxley model--still standing?

Action potentials in cortical neurons show a variable threshold and a sudden rise in membrane potential at initiation. Naundorf et al. fail to explain these features using single- or double-compartment Hodgkin-Huxley-style models, suggesting instead that they could arise from cooperative opening of Na+ channels, although there is no direct biological evidence to support this. Here we show that these so-called unique features are to be expected from Hodgkin-Huxley models if the spatial geometry and spike initiation properties of cortical neurons are taken into account--it is therefore unnecessary to invoke exotic channel-gating properties as an explanation.

Somatic membrane potential and Kv1 channels control spike repolarization in cortical axon collaterals and presynaptic boutons.

The shape of action potentials invading presynaptic terminals, which can vary significantly from spike waveforms recorded at the soma, may critically influence the probability of synaptic neurotransmitter release. Revealing the conductances that determine spike shape in presynaptic boutons is important for understanding how changes in the electrochemical context in which a spike is generated, such as subthreshold depolarization spreading from the soma, can modulate synaptic strength. Utilizing recent improvements in the signal-to-noise ratio of voltage-sensitive dye imaging in mouse brain slices, we demonstrate that intracortical axon collaterals and en passant presynaptic terminals of layer 5 pyramidal cells exhibit a high density of Kv1 subunit-containing ion channels, which generate a slowly inactivating K(+) current critically important for spike repolarization in these compartments. Blockade of the current by low doses of 4-aminopyridine or α-dendrotoxin dramatically slows the falling phase of action potentials in axon collaterals and presynaptic boutons. Furthermore, subthreshold depolarization of the soma broadened action potentials in collaterals bearing presynaptic boutons, an effect abolished by blocking Kv1 channels with α-dendrotoxin. These results indicate that action potential-induced synaptic transmission may operate through a mix of analog-digital transmission owing to the properties of Kv1 channels in axon collaterals and presynaptic boutons.

Modulation of intracortical synaptic potentials by presynaptic somatic membrane potential.

Traditionally, neuronal operations in the cerebral cortex have been viewed as occurring through the interaction of synaptic potentials in the dendrite and soma, followed by the initiation of an action potential, typically in the axon. Propagation of this action potential to the synaptic terminals is widely believed to be the only form of rapid communication of information between the soma and axonal synapses, and hence to postsynaptic neurons. Here we show that the voltage fluctuations associated with dendrosomatic synaptic activity propagate significant distances along the axon, and that modest changes in the somatic membrane potential of the presynaptic neuron modulate the amplitude and duration of axonal action potentials and, through a Ca2+-dependent mechanism, the average amplitude of the postsynaptic potential evoked by these spikes. These results indicate that synaptic activity in the dendrite and soma controls not only the pattern of action potentials generated, but also the amplitude of the synaptic potentials that these action potentials initiate in local cortical circuits, resulting in synaptic transmission that is a mixture of triggered and graded (analogue) signals.

A dynamics model of neuron-astrocyte network accounting for febrile seizures.

Febrile seizure (FS) is a full-body convulsion caused by a high body temperature that affect young kids, however, how these most common of human seizures are generated by fever has not been known. One common observation is that cortical neurons become overexcited with abnormal running of sodium and potassium ions cross membrane in raised body temperature condition, Considering that astrocyte Kir4.1 channel play a critical role in maintaining extracellular homeostasis of ionic concentrations and electrochemical potentials of neurons by fast depletion of extracellular potassium ions, we examined here the potential role of temperature-dependent Kir4.1 channel in astrocytes in causing FS. We first built up a temperature-dependent computational model of the Kir4.1 channel in astrocytes and validated with experiments. We have then built up a neuron-astrocyte network and examine the role of the Kir4.1 channel in modulating neuronal firing dynamics as temperature increase. The numerical experiment demonstrated that the Kir4.1 channel function optimally in the body temperature around 37 °C in cleaning 'excessive' extracellular potassium ions during neuronal firing process, however, higher temperature deteriorates its cleaning function, while lower temperature slows down its cleaning efficiency. With the increase of temperature, neurons go through different stages of spiking dynamics from spontaneous slow oscillations, to tonic spiking, fast bursting oscillations, and eventually epileptic bursting. Thus, our study may provide a potential new mechanism that febrile seizures may be happened due to temperature-dependent functional disorders of Kir4.1 channel in astrocytes. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-021-09706-w.

Unveiling Dynamic System Strategies for Multisensory Processing: From Neuronal Fixed-Criterion Integration to Population Bayesian Inference.

Multisensory processing is of vital importance for survival in the external world. Brain circuits can both integrate and separate visual and vestibular senses to infer self-motion and the motion of other objects. However, it is largely debated how multisensory brain regions process such multisensory information and whether they follow the Bayesian strategy in this process. Here, we combined macaque physiological recordings in the dorsal medial superior temporal area (MST-d) with modeling of synaptically coupled multilayer continuous attractor neural networks (CANNs) to study the underlying neuronal circuit mechanisms. In contrast to previous theoretical studies that focused on unisensory direction preference, our analysis showed that synaptic coupling induced cooperation and competition in the multisensory circuit and caused single MST-d neurons to switch between sensory integration or separation modes based on the fixed-criterion causal strategy, which is determined by the synaptic coupling strength. Furthermore, the prior of sensory reliability was represented by pooling diversified criteria at the MST-d population level, and the Bayesian strategy was achieved in downstream neurons whose causal inference flexibly changed with the prior. The CANN model also showed that synaptic input balance is the dynamic origin of neuronal direction preference formation and further explained the misalignment between direction preference and inference observed in previous studies. This work provides a computational framework for a new brain-inspired algorithm underlying multisensory computation.

Visual-Based Spatial Coordinate Dominates Probabilistic Multisensory Inference in Macaque MST-d Disparity Encoding.

Numerous studies have demonstrated that animal brains accurately infer whether multisensory stimuli are from a common source or separate sources. Previous work proposed that the multisensory neurons in the dorsal medial superior temporal area (MST-d) serve as integration or separation encoders determined by the tuning-response ratio. However, it remains unclear whether MST-d neurons mainly take a sense input as a spatial coordinate reference for carrying out multisensory integration or separation. Our experimental analysis shows that the preferred tuning response to visual input is generally larger than vestibular according to the Macaque MST-d neuronal recordings. This may be crucial to serving as the base of coordinate reference when the subject perceives moving direction information from two senses. By constructing a flexible Monte-Carlo probabilistic sampling (fMCS) model, we validate this hypothesis that the visual and vestibular cues are more likely to be integrated into a visual-based coordinate rather than vestibular. Furthermore, the property of the tuning gradient also affects decision-making regarding whether the cues should be integrated or not. To a dominant modality, an effective decision is produced by a steep response-tuning gradient of the corresponding neurons, while to a subordinate modality a steep tuning gradient produces a rigid decision with a significant bias to either integration or separation. This work proposes that the tuning response amplitude and tuning gradient jointly modulate which modality serves as the base coordinate for the reference frame and the direction change with which modality is decoded effectively.