Self-sustained firing activities of the cortical network with plastic rules in weak AC electrical fields

Both external and endogenous electrical fields widely exist in the environment of cortical neurons. The effects of a weak alternating current (AC) field on a neural network model with synaptic plasticity are studied. It is found that self-sustained rhythmic firing patterns, which are closely correlated with the cognitive functions, are significantly modified due to the self-organizing of the network in the weak AC field. The activities of the neural networks are affected by the synaptic connection strength, the external stimuli, and so on. In the presence of learning rules, the synaptic connections can be modulated by the external stimuli, which will further enhance the sensitivity of the network to the external signal. The properties of the external AC stimuli can serve as control parameters in modulating the evolution of the neural network.     

基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性动态平衡

大脑皮层的兴奋性与抑制性平衡是维持正常脑功能的前提, 而其失衡会诱发癫痫、帕金森、抑郁症等多种神经疾病, 因此兴奋性与抑制性平衡的研究是脑科学领域的核心科学问题. 反馈神经回路是脑皮层网络的典型连接模式, 抑制性突触可塑性在兴奋性与抑制性平衡中扮演关键角色. 本文首先构建具有抑制性突触可塑性的反馈神经回路模型; 然后通过计算模拟研究揭示在抑制性突触可塑性的调控下反馈神经回路的兴奋性与抑制性可取得较高程度的动态平衡, 并且二者的平衡对输入扰动具有较强的鲁棒性; 其次给出了基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性平衡机理的解释; 最后发现反馈回路神经元数目有利于提高兴奋性与抑制性平衡的程度, 这在一定程度上解释了为何神经元之间会存在较多的连接. 本文的研究对于理解脑皮层的兴奋性与抑制性动态平衡机理具有重要的参考价值.     

Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin--Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ_syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ_syn, suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks.     

Cognition coming about: Self-organisation and free-energy: Commentary on Wright,J.J. and Bourke,P.D. (2020) “The growth of cognition: Free energy minimization and the embryogenesis of cortical computation”

Wright and Bourke's compelling article rightly points out that existing models of embryogenesis fail to explain the mechanisms and functional significance of the dynamic connections among neurons. We pursue their account of Dynamic Logic by appealing to the Markov blanket formalism that underwrites the Free Energy Principle. We submit that this allows one to model embryogenesis as self-organisation in a dynamical system that minimises free-energy. The ensuing formalism may be extended to also explain the autonomous emergence of cognition, specifically in the brain, as a dynamic self-assembling process.     

Network dilution and asymmetry in an efficient brain

ABSTRACT

The ultimate goal of neuroscience is to ultimately understand how the brain functions. The advancement of brain imaging shows us how the brain continuously alternates complex activity patterns and experimentally reveals how these patterns are responsible for memory, association, reasoning, and countless other tasks. Two fundamental parameters, dilution (the number of connections per node), and symmetry (the number of bidirectional connections of the same weight) characterise two fundamental features underlying the networks that connect the single neurons in the brain and generate these patterns. Mammalian brains show large variations of dilution, and mostly asymmetric connectivity, unfortunately the advantages which drove evolution to these state of network dilution and asymmetry are still unknown. Here, we studied the effects of symmetry and dilution on a discrete-time recurrent neural network with McCulloch–Pitts neurons. We use an exhaustive approach, in which we probe all possible inputs for several randomly connected neuron networks with different degrees of dilution and symmetry. We find an optimum value for the synaptic dilution and symmetry, which turns out to be in striking quantitative agreement with what previous researchers have found in the brain cortex, neocortex and hippocampus. The diluted asymmetric brain shows high memory capacity and pattern recognition speed, but most of all it is the less energy-consumptive with respect to fully connected and symmetric network topologies.     

Topographic organization of Hebbian neural connections by synchronous wave activity

Experimental studies have revealed that the refinement of early, imprecise connections in the developing visual system involves activity in the retina before the onset of vision. We study the evolution of initially random unidirectional connections between two excitable layers of FitzHugh-Nagumo neurons with simulated spontaneous activity in the input layer. Lateral coupling within the layers yields synchronous neural wave activity that serves as a template for the Hebbian learning process, which establishes topographically precise interlayer connections. (c) 2001 American Institute of Physics.     

The auditory cortex of the bat <Emphasis Type="Italic">Phyllostomus discolor</Emphasis>: Localization and organization of basic response properties

Background  

The mammalian auditory cortex can be subdivided into various fields characterized by neurophysiological and neuroarchitectural properties and by connections with different nuclei of the thalamus. Besides the primary auditory cortex, echolocating bats have cortical fields for the processing of temporal and spectral features of the echolocation pulses. This paper reports on location, neuroarchitecture and basic functional organization of the auditory cortex of the microchiropteran bat Phyllostomus discolor (family: Phyllostomidae).     

Dopamine presynaptically and heterogeneously modulates nucleus accumbens medium-spiny neuron GABA synapses in vitro

Background  

The striatal complex is the major target of dopamine action in the CNS. There, medium-spiny GABAergic neurons, which constitute about 95% of the neurons in the area, form a mutually inhibitory synaptic network that is modulated by dopamine. When put in culture, the neurons reestablish this network. In particular, they make autaptic connections that provide access to single, identified medium-spiny to medium-spiny neuron synaptic connections.     

Dynamics of simple electronic neural networks

We examine systems of one and two nonlinear threshold switching elements (“neurons”), of the kind used in electronic neural networks. Characteristics of these systems which deviate from standard ideal models are found to induce complex dynamics. When the neurons possess a finite frequency response or a transfer characteristic with a time delay, underdamped transients and instability leading to oscillation can occur. Inertia in the neuron connections is found to cause ringing about fixed points, convoluted basin boundaries, instability and spontaneous oscillation, and chaotic behavior when driven. Furthermore, the collective behavior of a network of multiple neurons can be underdamped even when the individual connections are overdamped. These results imply that care should be exercised in implementing networks with electronic devices or when adding inertia to enhance the performance of optimizing networks.     

Auditory perception of objects by blind persons, using a bioacoustic high resolution air sonar

A high-resolution octave band air sonar for spatial sensing and object imaging by blind persons is described. The system has wide-angle overlapping peripheral fields of view with a narrow central field superposed. It is noninvasively coupled to the auditory system for neural processing and spatial imaging. Blind persons learn to comprehend the auditory cortical multiple-object image that is created. The real-time synchronous relationship between hearing a change in the sensor sounds and the sensed motor actions causing the change seems to aid the learning process. Computer based testing of the sensor system is described so as to relate the physical system performance with the time-varying human auditory perception. This is so that the basic psychometric experiments studying the sensor bio-acoustic spatial resolution, resulting from the superposition of two wide-angle peripheral fields with one central narrow field, may be better understood. These tests confirm that the auditory ability of subjects to resolve close objects using the combined fields is significantly improved relative to using the peripheral fields alone. These measurements are supported by blind children learning to use the sensor system.     

Pattern-specific neural network design

We present evidence that the performance of the traditional fully connected Hopfield model can be dramatically improved by carefully selecting an information-specific connectivity structure, while the synaptic weights of the selected connections are the same as in the Hopfield model. Starting from a completely disconnected network we let genuine Hebbian synaptic connections grow, one by one, until a desired degree of stability is achieved. Neural pathways are thus fixed notbefore, butduring the learning phase.     

Development of synaptic connectivity onto interneurons in stratum radiatum in the CA1 region of the rat hippocampus

Background  

The impact of a given presynaptic neuron on the firing probability of the postsynaptic neuron critically depends on the number of functional release sites that connect the two neurons. One way of determining the average functional synaptic connectivity onto a postsynaptic neuron is to compare the amplitudes of action potential dependent spontaneous synaptic currents with the amplitude of the synaptic currents that are independent of action potentials ("minis"). With this method it has been found that average synaptic connectivity between glutamatergic CA3 and CA1 pyramidal cells increases from single connections in the neonatal rat, to multiple connections in the young adult rat. On the other hand, γ-aminobutyric acid (GABA)ergic interneurons form multiple connections onto CA1 pyramidal cells already in the neonatal rat, and the degree of multiple GABAergic connectivity is preserved into adulthood. In the present study, we have examined the development of glutamate and GABA connectivity onto GABAergic CA1 stratum radiatum interneurons in the hippocampal slice, and compared this to the connectivity onto CA1 pyramidal neurons.     

Synaptic Plasticity and Spike Synchronisation in Neuronal Networks

Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic plasticity on neuronal networks composed by Hodgkin-Huxley neurons. We show that the final topology of the evolved network depends crucially on the ratio between the strengths of the inhibitory and excitatory synapses. Excitation of the same order of inhibition revels an evolved network that presents the rich-club phenomenon, well known to exist in the brain. For initial networks with considerably larger inhibitory strengths, we observe the emergence of a complex evolved topology, where neurons sparsely connected to other neurons, also a typical topology of the brain. The presence of noise enhances the strength of both types of synapses, but if the initial network has synapses of both natures with similar strengths. Finally, we show how the synchronous behaviour of the evolved network will reflect its evolved topology.     

Cortical representation of spatiotemporal pattern of firing evoked by echolocation signals: population encoding of target features in real time.

Target perception in echolocating bats entails the generation of an acoustic image of the target in the auditory cortex. By integrating information conveyed in the sequence of acoustic echoes, the population of cortical neurons in hypothesized to encode different target features based on its spatiotemporal pattern of neural-spike firing during the course of echolocation. A biologically plausible approach to the cortical representation of target features is employed by using electrophysiological data recorded from the auditory cortex of the FM bat, Myotis lucifugus. A single-neuron model of delay-sensitive neurons is first approximated by the formulation of a Gaussian function with different variables to represent the delay-tuning properties of individual cortical neurons. A cortical region consisting of delay-sensitive neurons organized topographically according to best frequency (i.e., tontopically organized) is then modeled with multiple layers of the single-neuron model. A mechanism is developed to represent and encode the responses of these neurons based on time-dependent, incoming echo signals. The time-varying responses of the population of neurons are mapped spatially on the auditory-cortical surface as a cortical response map (CORMAP). The model is tested using phantom targets with single and multiple glints. These simulation results provide further validation of the current auditory framework as a biomimetic mechanism for capturing time-varying, acoustic stimuli impinging in the bat's ears, and the neural representation of acoustic stimulus features by saptiotemporal-firing patterns in the cortical population.     

Hippocampal CA1/subiculum-prefrontal cortical pathways induce plastic changes of nociceptive responses in cingulate and prelimbic areas

Background  

Projections from hippocampal CA1-subiculum (CA1/SB) areas to the prefrontal cortex (PFC), which are involved in memory and learning processes, produce long term synaptic plasticity in PFC neurons. We examined modifying effects of these projections on nociceptive responses recorded in the prelimbic and cingulate areas of the PFC.     

Collective behaviors in coupled map lattices with local and nonlocal connections

After having recalled the basic properties of the nontrivial collective dynamics exhibited by lattices of maps with local coupling and synchronous updating, we present the behavior of the same models in which all the connections are random. The mean-field, synchronized limit is shown to be reached only for large enough connectivities and sufficiently strong local chaos. Intermediate models, in which only a few of the connections of each site are taken at random, are then considered. Preliminary results indicate that the nontrivial collective behaviors shown by the regularly connected models may be robust to a small proportion of nonlocal, random connections.     

Patterns and Symmetries in the Visual Cortex and in Natural Images

As borders between different entities, lines are an important element of natural images. Indeed, the neurons of the mammalian visual cortex are tuned to respond best to lines of a given orientation. This preferred orientation varies continuously across most of the cortex, but also has vortex-like singularities known as pinwheels. In attempting to describe such patterns of orientation preference, we are led to consider underlying rotation symmetries: Oriented segments in natural images tend to be collinear; neurons are more likely to be connected if their preferred orientations are aligned to their topographic separation. These are indications of a reduced symmetry requiring joint rotations of both orientation preference and the underlying topography. This is verified by direct statistical tests in both natural images and in cortical maps. Using the statistics of natural scenes we construct filters that are best suited to extracting information from such images, and find qualitative similarities to mammalian vision. PACS84.35+i 89.70.+c 87.57.Nk     

Synaptic plasticity modulates autonomous transitions between waking and sleep states: insights from a Morris-Lecar model

The transitions between waking and sleep states are characterized by considerable changes in neuronal firing. During waking, neurons fire tonically at irregular intervals and a desynchronized activity is observed at the electroencephalogram. This activity becomes synchronized with slow wave sleep onset when neurons start to oscillate between periods of firing (up-states) and periods of silence (down-states). Recently, it has been proposed that the connections between neurons undergo potentiation during waking, whereas they weaken during slow wave sleep. Here, we propose a dynamical model to describe basic features of the autonomous transitions between such states. We consider a network of coupled neurons in which the strength of the interactions is modulated by synaptic long term potentiation and depression, according to the spike time-dependent plasticity rule (STDP). The model shows that the enhancement of synaptic strength between neurons occurring in waking increases the propensity of the network to synchronize and, conversely, desynchronization appears when the strength of the connections become weaker. Both transitions appear spontaneously, but the transition from sleep to waking required a slight modification of the STDP rule with the introduction of a mechanism which becomes active during sleep and changes the proportion between potentiation and depression in accordance with biological data. At the neuron level, transitions from desynchronization to synchronization and vice versa can be described as a bifurcation between two different states, whose dynamical regime is modulated by synaptic strengths, thus suggesting that transition from a state to an another can be determined by quantitative differences between potentiation and depression.