Global rhythmic activities in hippocampal neural fields and neural coding

Global oscillations of the neural field represent some of the most interesting expressions of the hippocampal activity, being related also to learning and memory. To study oscillatory activities of the CA3 field in theta range, a model of this sub-field of Hippocampus has been formulated. The model describes the firing activity of CA3 neuronal populations within the frame of a kinetic theory of neural systems and it has been used for computer simulations. The results show that the propagation of activities induced in the neural field by hippocampal afferents occurs only in narrow time windows confined by inhibitory barrages, whose time-course follows the theta rhythm. Moreover, during each period of a theta wave, the entire CA3 field bears a firing activity with peculiar space-time patterns, a sort of specific imprint, which can induce effects with similar patterns on brain regions driven by the hippocampal formation. The simulation has also demonstrated the ability of medial septum to influence the global activity of the CA3 pyramidal population through the control of the population of inhibitory interneurons. At last, the possible involvement of global population oscillations in neural coding has been discussed.     

Computational experiments support a competitive function in the the CA3 region of the hippocampus

The comprehension of activities and functions of complex brain structures requires, among other things, information on simultaneous activities in several regions. Results reported in the literature using multi(micro/macro)electrode recordings or imaging techniques provide incomplete information due either to the small size and/or small number of investigated regions or to the poor spatiotemporal resolution, respectively. This is particularly true for the hippocampus and its subfields, and mathematical modeling and computer simulation have been used with the aim of obtaining information when this is lacking. Global activities in the CA3 field of the hippocampus, and in particular the genesis of theta rhythm and sharp waves, have been investigated here by a mathematical model formulated within the frame of a kinetic theory of neural systems. The model has taken into account data of experimental results both on different PSPs recorded in hippocampal neurons and on recurrent pyramidal collateral geometries. The computational ‘experiments’ to which the model was subjected suggest that the sharp waves arise through a selective and short block of the fast inhibitory neurons of CA3, produced by a medial septum inhibitory input, whereas the theta activity is produced by a durable, continuous inhibition of the slow inhibitory neurons. Information obtained also suggests that the recurrent pyramidal collaterals subserve a competitive, rather than a cooperative, organization. Based on these results a hypothesis on the possible functional organization of the CA3 field and of the entire hippocampus has been formulated. According to this hypothesis, the CA3 imposes a serial order on the flow of activity arriving at the hippocampus from the entorhinal cortex and from its connected polymodal cortical regions. This ordering permits cortical activities, arriving at CA3 on appropriate time intervals, to produce effects in regions of brain to which the CA3 projects. The competing cortical activities are lost.     

Establishing a Statistical Link between Network Oscillations and Neural Synchrony

Pairs of active neurons frequently fire action potentials or “spikes” nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons’ fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron’s firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony.     

Extremely low-frequency electromagnetic fields affect lipid-linked Carbonic anhydrase

In the last years, the effect of extremely low-frequency electromagnetic fields (ELF-EMF) on the activity of different enzymes were investigated. Only the membrane-anchored enzymes did decrease their activity, up to 50%. In this work, the effect of ELF-EMF on bovine lung membrane carbonic anhydrase (CA) were studied. Carbonic anhydrases are a family of 14 zinc-containing isozymes catalyzing the reversible reaction: CO₂+H₂O = HCO₃^? +H⁺. CA differ in catalytic activity and subcellular localization. CA IV, IX, XII, XIV, and XV are membrane bound. In particular, CA IV, which is expressed in the lung, is glycosyl phosphatidyl inositol-linked to the membrane, therefore it was a candidate to inhibition by ELF-EMF. Exposure to the membranes to a field of 75 Hz frequency and different amplitudes caused CA activity to a reproducible decrease in enzymatic activity by 17% with a threshold of about 0.74 mT. The decrease in enzymatic activity was independent of the time of permanence in the field and was completely reversible. When the source of enzyme was solubilized with Triton, the field lost its effect on CA enzymatic activity, suggesting a crucial role of the membrane, as well as of the particular linkage of the enzyme to it, in determining the conditions for CA inactivation. Results are discussed in terms of the possible physiologic effects of CA inhibition in target organs.     

Small-molecule probes elucidate global enzyme activity in a proteomic context

The recent dramatic improvements in high-resolution mass spectrometry (MS) have revolutionized the speed and scope of proteomic studies. Conventional MS-based proteomics methodologies allow global protein profiling based on expression levels. Although these techniques are promising, there are numerous biological activities yet to be unveiled, such as the dynamic regulation of enzyme activity. Chemical proteomics is an emerging field that extends these types proteomic profiling. In particular, activity-based protein profiling (ABPP) utilizes small-molecule probes to monitor enzyme activity directly in living intact subjects. In this mini-review, we summarize the unique roles of smallmolecule probes in proteomics studies and highlight some recent examples in which this principle has been applied. [BMB Reports 2014; 47(3): 149-157]     

动态神经网络中的同步振荡

目前有一种假设认为同一视觉对象是由一群神经元的同步振荡活动来表征的。这一神经元发放活动的时间特性,是解决视觉信息处理中“结合问题（Ｂｉｎｄｉｎｇｐｒｏｂｌｅｍ）”的可能机制。本文用我们所提出的一种简化现实性神经网络模型［１］所构造的时滞非线性振子网络［２］,模拟生物神经网络的同步振荡活动。并考虑了振子各参数的设置与振荡活动的关系,以及网络振子间耦联对同步活动的影响．     

Temporal dynamics of distinct CA1 cell populations during unconscious state induced by ketamine

Ketamine is a widely used dissociative anesthetic which can induce some psychotic-like symptoms and memory deficits in some patients during the post-operative period. To understand its effects on neural population dynamics in the brain, we employed large-scale in vivo ensemble recording techniques to monitor the activity patterns of simultaneously recorded hippocampal CA1 pyramidal cells and various interneurons during several conscious and unconscious states such as awake rest, running, slow wave sleep, and ketamine-induced anesthesia. Our analyses reveal that ketamine induces distinct oscillatory dynamics not only in pyramidal cells but also in at least seven different types of CA1 interneurons including putative basket cells, chandelier cells, bistratified cells, and O-LM cells. These emergent unique oscillatory dynamics may very well reflect the intrinsic temporal relationships within the CA1 circuit. It is conceivable that systematic characterization of network dynamics may eventually lead to better understanding of how ketamine induces unconsciousness and consequently alters the conscious mind.     

Magnetic field perturbations as a tool for controlling enzyme-regulated and oscillatory biochemical reactions

The feasibility of magnetic field perturbations as a tool for controlling enzyme-regulated and oscillatory biochemical reactions is studied. Our approach is based on recent experimental results that revealed magnetic field effects on the in vitro activity of enzyme systems in accordance with the radical pair mechanism. A minimum model consisting of two coupled enzyme-regulated reactions is discussed that combines, in a self-consistent manner, magnetic field-sensitive enzyme kinetics with non-linear dynamical principles. Furthermore, a simple detector mechanism is described that is capable of responding to an oscillatory input. Results reveal that moderate-strength magnetic fields (B=1-100 mT) may effectively alter the dynamics of the system. In particular, a response behavior is observed that depends on: (1) the combination of static and time-varying magnetic fields; (2) the field amplitude; and (3) the field frequency in a non-linear fashion. The specific response behavior is critically determined by the biochemical boundary conditions as defined by the kinetic properties of the system. We propose an experimental implementation of the results based on the oscillatory peroxidase-oxidase reaction controlled by the enzyme horseradish peroxidase.     

Dynamics of pattern formation in lateral-inhibition type neural fields

The dynamics of pattern formation is studied for lateral-inhibition type homogeneous neural fields with general connections. Neural fields consisting of single layer are first treated, and it is proved that there are five types of pattern dynamics. The type of the dynamics of a field depends not only on the mutual connections within the field but on the level of homogeneous stimulus given to the field. An example of the dynamics is as follows: A fixed size of localized excitation, once evoked by stimulation, can be retained in the field persistently even after the stimulation vanishes. It moves until it finds the position of the maximum of the input stimulus. Fields consisting of an excitatory and an inhibitory layer are next analyzed. In addition to stationary localized excitation, fields have such pattern dynamics as production of oscillatory waves, travelling waves, active and dual active transients, etc.This research was supported in part by a Sloan Foundation grant to the Center for Systems Neuroscience, University of Massachusetts at AmherstOn sabbatical leave from the University of Tokyo     

Sparse Coding Models Can Exhibit Decreasing Sparseness while Learning Sparse Codes for Natural Images

The sparse coding hypothesis has enjoyed much success in predicting response properties of simple cells in primary visual cortex (V1) based solely on the statistics of natural scenes. In typical sparse coding models, model neuron activities and receptive fields are optimized to accurately represent input stimuli using the least amount of neural activity. As these networks develop to represent a given class of stimulus, the receptive fields are refined so that they capture the most important stimulus features. Intuitively, this is expected to result in sparser network activity over time. Recent experiments, however, show that stimulus-evoked activity in ferret V1 becomes less sparse during development, presenting an apparent challenge to the sparse coding hypothesis. Here we demonstrate that some sparse coding models, such as those employing homeostatic mechanisms on neural firing rates, can exhibit decreasing sparseness during learning, while still achieving good agreement with mature V1 receptive field shapes and a reasonably sparse mature network state. We conclude that observed developmental trends do not rule out sparseness as a principle of neural coding per se: a mature network can perform sparse coding even if sparseness decreases somewhat during development. To make comparisons between model and physiological receptive fields, we introduce a new nonparametric method for comparing receptive field shapes using image registration techniques.     

The remote consequences of hypoxia influence in perinatal development period on structurally functional characteristics of the rat brain

The study has shown that influence of acute hypoxia in perinatal period leads to structural changes in motor and visual of the neocortex for 20 postnatal days in the form of disturbance of the structural organisation of the neocortex layers. Different fields of hippocampus in perinatal period differently react to hypoxia, and evidence of existence of a long-term perinatal hypoxia was obtained. It is established that after action of acute hypoxia in all the fields there is a cellular destruction, and thinning of pyramidal neurones layers. The most expressed cellular destruction takes place in fields CA4 and CA3. In process of augmentation, the destruction of cells remains appreciable in the field CA4, reduced in the field CA3 and not found in the field CA1; however, in fascia dentate, the destruction of granular neurones with age augmentation increases. Along with in reduction of the dimensions of cellular bodies pyramidal neurones in all fields of hippocampus takes place. Also in all fields of hippocampus, activation of astrocytic reaction occurs, more expressed in the field CA4. The hypoxia influence in the early postnatal period can affect synaptogenes, particularly the formation of giant synapses in a dentate fascia. Study of functional features of the excitatory system of such animals has shown that hypoxia can induce appreciable disturbances of behavioural responses. In rats, disturbances of inhibiting functions of the cerebral cortex, raised anxiety, and spatial learning and working memory disturbances have been noted.     

Extremely low-frequency electromagnetic fields affect lipid-linked carbonic anhydrase

In the last years, the effect of extremely low-frequency electromagnetic fields (ELF-EMF) on the activity of different enzymes were investigated. Only the membrane-anchored enzymes did decrease their activity, up to 50%. In this work, the effect of ELF-EMF on bovine lung membrane carbonic anhydrase (CA) were studied. Carbonic anhydrases are a family of 14 zinc-containing isozymes catalyzing the reversible reaction: CO(2)+H(2)O = HCO(3)(- )+H(+). CA differ in catalytic activity and subcellular localization. CA IV, IX, XII, XIV, and XV are membrane bound. In particular, CA IV, which is expressed in the lung, is glycosyl phosphatidyl inositol-linked to the membrane, therefore it was a candidate to inhibition by ELF-EMF. Exposure to the membranes to a field of 75 Hz frequency and different amplitudes caused CA activity to a reproducible decrease in enzymatic activity by 17% with a threshold of about 0.74 mT. The decrease in enzymatic activity was independent of the time of permanence in the field and was completely reversible. When the source of enzyme was solubilized with Triton, the field lost its effect on CA enzymatic activity, suggesting a crucial role of the membrane, as well as of the particular linkage of the enzyme to it, in determining the conditions for CA inactivation. Results are discussed in terms of the possible physiologic effects of CA inhibition in target organs.     

A model cortical circuit for the storage of temporal sequences

Despite the fact that temporal information processing is of particular significance in biological memory systems, not much has yet been explored about how these systems manage to store temporal information involved in sequences of stimuli. A neural network model capable of learning and recalling temporal sequences is proposed, based on a neural mechanism in which the sequences are expanded into a series of periodic rectangular oscillations. Thus, the mathematical framework underlying the model, to some extent, is concerned with the Walsh function series. The oscillatory activities generated by the interplay between excitatory and inhibitory neuron pools are transmitted to another neuron pool whose role in learning and retrieval is to modify the rhythms and phases of the rectangular oscillations. Thus, a basic functional neural circuit involves three different neuron pools. The modifiability of rhythms and phases is incorporated into the model with the aim of improving the quality of the retrieval. Numerical simulations were conducted to show the characteristic features of the learning as well as the performance of the model in memory recall.     

A Dendritic Mechanism for Decoding Traveling Waves: Principles and Applications to Motor Cortex

Traveling waves of neuronal oscillations have been observed in many cortical regions, including the motor and sensory cortex. Such waves are often modulated in a task-dependent fashion although their precise functional role remains a matter of debate. Here we conjecture that the cortex can utilize the direction and wavelength of traveling waves to encode information. We present a novel neural mechanism by which such information may be decoded by the spatial arrangement of receptors within the dendritic receptor field. In particular, we show how the density distributions of excitatory and inhibitory receptors can combine to act as a spatial filter of wave patterns. The proposed dendritic mechanism ensures that the neuron selectively responds to specific wave patterns, thus constituting a neural basis of pattern decoding. We validate this proposal in the descending motor system, where we model the large receptor fields of the pyramidal tract neurons — the principle outputs of the motor cortex — decoding motor commands encoded in the direction of traveling wave patterns in motor cortex. We use an existing model of field oscillations in motor cortex to investigate how the topology of the pyramidal cell receptor field acts to tune the cells responses to specific oscillatory wave patterns, even when those patterns are highly degraded. The model replicates key findings of the descending motor system during simple motor tasks, including variable interspike intervals and weak corticospinal coherence. By additionally showing how the nature of the wave patterns can be controlled by modulating the topology of local intra-cortical connections, we hence propose a novel integrated neuronal model of encoding and decoding motor commands.     

Modelled biophysical impacts of conservation agriculture on local climates

Including the parameterization of land management practices into Earth System Models has been shown to influence the simulation of regional climates, particularly for temperature extremes. However, recent model development has focused on implementing irrigation where other land management practices such as conservation agriculture (CA) has been limited due to the lack of global spatially explicit datasets describing where this form of management is practiced. Here, we implement a representation of CA into the Community Earth System Model and show that the quality of simulated surface energy fluxes improves when including more information on how agricultural land is managed. We also compare the climate response at the subgrid scale where CA is applied. We find that CA generally contributes to local cooling (~1°C) of hot temperature extremes in mid‐latitude regions where it is practiced, while over tropical locations CA contributes to local warming (~1°C) due to changes in evapotranspiration dominating the effects of enhanced surface albedo. In particular, changes in the partitioning of evapotranspiration between soil evaporation and transpiration are critical for the sign of the temperature change: a cooling occurs only when the soil moisture retention and associated enhanced transpiration is sufficient to offset the warming from reduced soil evaporation. Finally, we examine the climate change mitigation potential of CA by comparing a simulation with present‐day CA extent to a simulation where CA is expanded to all suitable crop areas. Here, our results indicate that while the local temperature response to CA is considerable cooling (>2°C), the grid‐scale changes in climate are counteractive due to negative atmospheric feedbacks. Overall, our results underline that CA has a nonnegligible impact on the local climate and that it should therefore be considered in future climate projections.     

Alternating current electric field effects on neural stem cell viability and differentiation

Methods utilizing stem cells hold tremendous promise for tissue engineering applications; however, many issues must be worked out before these therapies can be routinely applied. Utilization of external cues for preimplantation expansion and differentiation offers a potentially viable approach to the use of stem cells in tissue engineering. The studies reported here focus on the response of murine neural stem cells encapsulated in alginate hydrogel beads to alternating current electric fields. Cell viability and differentiation was studied as a function of electric field magnitude and frequency. We applied fields of frequency (0.1–10) Hz, and found a marked peak in neural stem cell viability under oscillatory electric fields with a frequency of 1 Hz. We also found an enhanced propensity for astrocyte differentiation over neuronal differentiation in the 1 Hz cultures, as compared to the other field frequencies we studied. Published 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Sensitivity of basic oscillatory mechanisms for pattern generation and detection

 Intrinsic oscillators are the basic building blocks of central pattern generators, which model the neural circuits underlying pattern generation. Coupled intrinsic oscillators have been shown to synchronize their oscillatory frequencies and to maintain a characteristic pattern of phase relationships. Recently, oscillatory neurons have also been identified in sensory systems that are involved in decoding phase information. It has been hypothesized that the neural oscillators are part of neural circuits that implement phase-locked loops (PLLs), which are well-known electrical circuits for temporal decoding. Thus, there is evidence that intrinsic neural oscillators participate in both temporal pattern generation and temporal pattern decoding. The present paper investigates the dynamics underlying forced oscillators and forced PLLs, using a single framework, and compares both their stability and sensitivity characteristics. In particular, a method for assessing whether an oscillatory neuron is forced directly or indirectly, as part of a PLL, is developed and applied to published data. Received: 17 July 2000 / Accepted in revised form: 14 March 2001     

The International Joint Experiment ISTTOK

The 3rd International Joint Experiment has been carried out on ISTTOK following the last RUSFD (technical meeting on Research Using Small Fusion Devices) conference, held at Lisbon, in the scope of the IAEA Coordinated Research Project. This program has allowed a great knowledge interchange among the “small” fusion devices community and, in particular, in the development of common work-programs. This communication gives an overview of the impact of such activities. The JE have proved to be a very useful applied forum to share knowledge and to initiate young scientists in some fields of tokamak operation and diagnostics. Many of the ISTTOK 2008 relevant results were obtained under this scope.     

A review of cell assemblies

Since the cell assembly (CA) was hypothesised, it has gained substantial support and is believed to be the neural basis of psychological concepts. A CA is a relatively small set of connected neurons, that through neural firing can sustain activation without stimulus from outside the CA, and is formed by learning. Extensive evidence from multiple single unit recording and other techniques provides support for the existence of CAs that have these properties, and that their neurons also spike with some degree of synchrony. Since the evidence is so broad and deep, the review concludes that CAs are all but certain. A model of CAs is introduced that is informal, but is broad enough to include, e.g. synfire chains, without including, e.g. holographic reduced representation. CAs are found in most cortical areas and in some sub-cortical areas, they are involved in psychological tasks including categorisation, short-term memory and long-term memory, and are central to other tasks including working memory. There is currently insufficient evidence to conclude that CAs are the neural basis of all concepts. A range of models have been used to simulate CA behaviour including associative memory and more process- oriented tasks such as natural language parsing. Questions involving CAs, e.g. memory persistence, CAs’ complex interactions with brain waves and learning, remain unanswered. CA research involves a wide range of disciplines including biology and psychology, and this paper reviews literature directly related to the CA, providing a basis of discussion for this interdisciplinary community on this important topic. Hopefully, this discussion will lead to more formal and accurate models of CAs that are better linked to neuropsychological data.     

Characteristics of the background fields in multichannel-recorded magnetic field responses

We have studied the background fields in the auditory evoked magnetic field responses recorded with a 37-channel SQUID magnetometer. The background fields were found to have a main contribution from the spontaneous fields, which originate in the neural activities of the brain. The spontaneous fields had strong spatial correlation across the recording sites even after averaging over 100 epochs. The spatial distribution of the spontaneous field consisted of 3 main components of single extremum pattern, dipolar pattern, and a dipolar pattern with some distortion. Computer simulations of the localization of a single dipole source of the evoked field response showed that the spontaneous background field could bring about large location errors in an unpredictable manner, as compared with the location errors caused by a spatially random Gaussian noise field.