Rhythmic behaviour and pattern-generating circuits in the locust: Key concepts and recent updates

There is growing recognition that rhythmic activity patterns are widespread in our brain and play an important role in all aspects of the functioning of our nervous system, from sensory integration to central processing and motor control. The study of the unique properties that enable central circuits to generate their rhythmic output in the absence of any patterned, sensory or descending, inputs, has been very rewarding in the relatively simple invertebrate preparations. The locust, specifically, is a remarkable example of an organism in which central pattern generator (CPG) networks have been suggested and studied in practically all aspects of their behaviour. Here we present an updated overview of the various rhythmic behaviours in the locust and aspects of their neural control. We focus on the fundamental concepts of multifunctional neuronal circuits, neural centre interactions and neuromodulation of CPG networks. We are certain that the very broad and solid knowledge base of locust rhythmic behaviour and pattern-generating circuits will continue to expand and further contribute to our understanding of the principles behind the functioning of the nervous system and, indeed, the brain.     

Understanding the brain by controlling neural activity

Causal methods to interrogate brain function have been employed since the advent of modern neuroscience in the nineteenth century. Initially, randomly placed electrodes and stimulation of parts of the living brain were used to localize specific functions to these areas. Recent technical developments have rejuvenated this approach by providing more precise tools to dissect the neural circuits underlying behaviour, perception and cognition. Carefully controlled behavioural experiments have been combined with electrical devices, targeted genetically encoded tools and neurochemical approaches to manipulate information processing in the brain. The ability to control brain activity in these ways not only deepens our understanding of brain function but also provides new avenues for clinical intervention, particularly in conditions where brain processing has gone awry.     

Single-chip microelectronic system to interface with living cells

A high degree of connectivity and the coordinated electrical activity of neural cells or networks are believed to be the reason that the brain is capable of highly sophisticated information processing. Likewise, the effectiveness of an animal heart largely depends on such coordinated cell activity. To advance our understanding of these complex biological systems, high spatiotemporal-resolution techniques to monitor the cell electrical activity and an ideally seamless interaction between cells and recording devices are desired. Here we present a monolithic microsystem in complementary metal oxide semiconductor (CMOS) technology that provides bidirectional communication (stimulation and recording) between standard electronics technology and cultured electrogenic cells. The microchip can be directly used as a substrate for cell culturing, it features circuitry units per electrode for stimulation and immediate cell signal treatment, and it provides on-chip signal transformation as well as a digital interface so that a very fast, almost real-time interaction (2 ms loop time from event recognition to, e.g., a defined stimulation) is possible at remarkable signal quality. The corresponding spontaneous and stimulated electrical activity recordings with neuronal and cardiac cell cultures will be presented. The system can be used to, e.g., study the development of neural networks, reveal the effects of neuronal plasticity and study cellular or network activity in response to pharmacological treatments.     

Bursting dynamics remarkably improve the performance of neural networks on liquid computing

Burst firings are functionally important behaviors displayed by neural circuits, which plays a primary role in reliable transmission of electrical signals for neuronal communication. However, with respect to the computational capability of neural networks, most of relevant studies are based on the spiking dynamics of individual neurons, while burst firing is seldom considered. In this paper, we carry out a comprehensive study to compare the performance of spiking and bursting dynamics on the capability of liquid computing, which is an effective approach for intelligent computation of neural networks. The results show that neural networks with bursting dynamic have much better computational performance than those with spiking dynamics, especially for complex computational tasks. Further analysis demonstrate that the fast firing pattern of bursting dynamics can obviously enhance the efficiency of synaptic integration from pre-neurons both temporally and spatially. This indicates that bursting dynamic can significantly enhance the complexity of network activity, implying its high efficiency in information processing.     

Transcranial alternating current stimulation enhances individual alpha activity in human EEG

Non-invasive electrical stimulation of the human cortex by means of transcranial direct current stimulation (tDCS) has been instrumental in a number of important discoveries in the field of human cortical function and has become a well-established method for evaluating brain function in healthy human participants. Recently, transcranial alternating current stimulation (tACS) has been introduced to directly modulate the ongoing rhythmic brain activity by the application of oscillatory currents on the human scalp. Until now the efficiency of tACS in modulating rhythmic brain activity has been indicated only by inference from perceptual and behavioural consequences of electrical stimulation. No direct electrophysiological evidence of tACS has been reported. We delivered tACS over the occipital cortex of 10 healthy participants to entrain the neuronal oscillatory activity in their individual alpha frequency range and compared results with those from a separate group of participants receiving sham stimulation. The tACS but not the sham stimulation elevated the endogenous alpha power in parieto-central electrodes of the electroencephalogram. Additionally, in a network of spiking neurons, we simulated how tACS can be affected even after the end of stimulation. The results show that spike-timing-dependent plasticity (STDP) selectively modulates synapses depending on the resonance frequencies of the neural circuits that they belong to. Thus, tACS influences STDP which in turn results in aftereffects upon neural activity.The present findings are the first direct electrophysiological evidence of an interaction of tACS and ongoing oscillatory activity in the human cortex. The data demonstrate the ability of tACS to specifically modulate oscillatory brain activity and show its potential both at fostering knowledge on the functional significance of brain oscillations and for therapeutic application.     

Gap junctions

Electrical coupling through gap junctions constitutes a mode of signal transmission between neurons (electrical synaptic transmission). Originally discovered in invertebrates and in lower vertebrates, electrical synapses have recently been reported in immature and adult mammalian nervous systems. This has renewed the interest in understanding the role of electrical synapses in neural circuit function and signal processing. The present review focuses on the role of gap junctions in shaping the dynamics of neural networks by forming electrical synapses between neurons. Electrical synapses have been shown to be important elements in coincidence detection mechanisms and they can produce complex input-output functions when arranged in combination with chemical synapses. We postulate that these synapses may also be important in redefining neuronal compartments, associating anatomically distinct cellular structures into functional units. The original view of electrical synapses as static connecting elements in neural circuits has been revised and a considerable amount of evidence suggests that electrical synapses substantially affect the dynamics of neural circuits.     

节律性听觉刺激下的神经振荡同步化及其应用

大脑的感觉、情绪、认知等功能与其神经振荡模式有密切的联系。通过施加节律性刺激可以调控大脑的神经振荡模式,进而影响个体感受、情绪状态和认知功能等。与近年来常见的非侵入性电刺激和磁刺激相比,同样依赖于外部刺激输入的节律性感觉刺激具有成本低、易操作等优点,被认为是一种极具潜力的神经调控手段。本文以节律性听觉刺激为例,系统综述了不同类型的节律性听觉刺激如何影响大脑的神经振荡模式,进而影响相关状态和功能;并通过总结外部节律性听觉刺激对个体感知觉、情绪与认知功能的影响,讨论其生理机制和应用前景。     

Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks

A large body of experimental and theoretical work on neural coding suggests that the information stored in brain circuits is represented by time-varying patterns of neural activity. Reservoir computing, where the activity of a recurrently connected pool of neurons is read by one or more units that provide an output response, successfully exploits this type of neural activity. However, the question of system robustness to small structural perturbations, such as failing neurons and synapses, has been largely overlooked. This contrasts with well-studied dynamical perturbations that lead to divergent network activity in the presence of chaos, as is the case for many reservoir networks. Here, we distinguish between two types of structural network perturbations, namely local (e.g., individual synaptic or neuronal failure) and global (e.g., network-wide fluctuations). Surprisingly, we show that while global perturbations have a limited impact on the ability of reservoir models to perform various tasks, local perturbations can produce drastic effects. To address this limitation, we introduce a new architecture where the reservoir is driven by a layer of oscillators that generate stable and repeatable trajectories. This model outperforms previous implementations while being resistant to relatively large local and global perturbations. This finding has implications for the design of reservoir models that capture the capacity of brain circuits to perform cognitively and behaviorally relevant tasks while remaining robust to various forms of perturbations. Further, our work proposes a novel role for neuronal oscillations found in cortical circuits, where they may serve as a collection of inputs from which a network can robustly generate complex dynamics and implement rich computations.     

A shift in sensory processing that enables the developing human brain to discriminate touch from pain

When and how infants begin to discriminate noxious from innocuous stimuli is a fundamental question in neuroscience [1]. However, little is known about the development of the necessary cortical somatosensory functional prerequisites in the intact human brain. Recent studies of developing brain networks have emphasized the importance of transient spontaneous and evoked neuronal bursting activity in the formation of functional circuits [2, 3]. These neuronal bursts are present during development and precede the onset of sensory functions [4, 5]. Their disappearance and the emergence of more adult-like activity are therefore thought to signal the maturation of functional brain circuitry [2, 4]. Here we show the changing patterns of neuronal activity that underlie the onset of nociception and touch discrimination in the preterm infant. We have conducted noninvasive electroencephalogram (EEG) recording of the brain neuronal activity in response to time-locked touches and clinically essential noxious lances of the heel in infants aged 28-45?weeks gestation. We show a transition in brain response following tactile and noxious stimulation from nonspecific, evenly dispersed neuronal bursts to modality-specific, localized, evoked potentials. The results suggest that specific neural circuits necessary for discrimination between touch and nociception emerge from 35-37?weeks gestation in the human brain.     

Low-frequency stimulation induces stable transitions in stereotypical activity in cortical networks

Reverberating spontaneous synchronized brain activity is believed to play an important role in neural information processing. Whether and how external stimuli can influence this spontaneous activity is poorly understood. Because periodic synchronized network activity is also prominent in in vitro neuronal cultures, we used cortical cultures grown on multielectrode arrays to examine how spontaneous activity is affected by external stimuli. Spontaneous network activity before and after low-frequency electrical stimulation was quantified in several ways. Our results show that the initially stable pattern of stereotypical spontaneous activity was transformed into another activity pattern that remained stable for at least 1 h. The transformations consisted of changes in single site and culture-wide network activity as well as in the spatiotemporal dynamics of network bursting. We show for the first time that low-frequency electrical stimulation can induce long-lasting alterations in spontaneous activity of cortical neuronal networks. We discuss whether the observed transformations in network activity could represent a switch in attractor state.     

Electrical synapses in mammalian CNS: Past eras,present focus and future directions

Gap junctions provide the basis for electrical synapses between neurons. Early studies in well-defined circuits in lower vertebrates laid the foundation for understanding various properties conferred by electrical synaptic transmission. Knowledge surrounding electrical synapses in mammalian systems unfolded first with evidence indicating the presence of gap junctions between neurons in various brain regions, but with little appreciation of their functional roles. Beginning at about the turn of this century, new approaches were applied to scrutinize electrical synapses, revealing the prevalence of neuronal gap junctions, the connexin protein composition of many of those junctions, and the myriad diverse neural systems in which they occur in the mammalian CNS. Subsequent progress indicated that electrical synapses constitute key elements in synaptic circuitry, govern the collective activity of ensembles of electrically coupled neurons, and in part orchestrate the synchronized neuronal network activity and rhythmic oscillations that underlie fundamental integrative processes. This article is part of a Special Issue entitled: Gap Junction Proteins edited by Jean Claude Herve.     

New insights from small rhythmic circuits

Small rhythmic circuits, such as those found in invertebrates, have provided fundamental insights into how circuit dynamics depend on individual neuronal and synaptic properties. Degenerate circuits are those with different network parameters and similar behavior. New work on degenerate circuits and their modulation illustrates some of the rules that help maintain stable and robust circuit function despite environmental perturbations. Advances in neuropeptide isolation and identification provide enhanced understanding of the neuromodulation of circuits for behavior. The advent of molecular studies of mRNA expression provides new insight into animal-to-animal variability and the homeostatic regulation of excitability in neurons and networks.     

An identified serotonergic neuron regulates adult neurogenesis in the crustacean brain

New neurons are born and integrated into functional circuits in the brains of many adult organisms. In virtually all of these systems, serotonin is a potent regulator of neuronal proliferation. Specific neural pathways underlying these serotonergic influences have not, however, been identified and manipulated. The goal of this study was to test whether adult neurogenesis in the crustacean brain is influenced by electrical activity in the serotonergic dorsal giant neurons (DGNs) innervating the primary olfactory processing areas, the olfactory lobes, and higher order centers, the accessory lobes. Adult‐born neurons occur in two interneuronal cell clusters that are part of the olfactory pathway. This study demonstrates that neurogenesis also continues in these areas in a dissected, perfused brain preparation, although the rate of neuronal production is lower than in brains from intact same‐sized animals. Inclusion of 10^?9 M serotonin in the perfusate delivered to the dissected brain preparation restores the rate of neurogenesis to in vivo levels. Although subthreshold stimulation of the DGN does not significantly alter the rate of neurogenesis, electrical activation of a single DGN results in significant increases in neurogenesis in Cluster 10 on the same side of the brain, when compared with levels on the contralateral, unstimulated side. Measurements of serotonin levels in the perfusate using high‐performance liquid chromatography established that serotonin levels are elevated about 10‐fold during DGN stimulation, confirming that serotonin is released during DGN activity. This is the first identified neural pathway through which adult neurogenesis has been directly manipulated. © 2009 Wiley Periodicals, Inc. Develop Neurobiol 2009     

Dynamics control of semantic processes in a hierarchical associative memory

A neural mechanism for control of dynamics and function of associative processes in a hierarchical memory system is demonstrated. For the representation and processing of abstract knowledge, the semantic declarative memory system of the human brain is considered. The dynamics control mechanism is based on the influence of neuronal adaptation on the complexity of neural network dynamics. Different dynamical modes correspond to different levels of the ultrametric structure of the hierarchical memory being invoked during an associative process. The mechanism is deterministic but may also underlie free associative thought processes. The formulation of an abstract neural network model of hierarchical associative memory utilizes a recent approach to incorporate neuronal adaptation. It includes a generalized neuronal activation function recently derived by a Hodgkin-Huxley-type model. It is shown that the extent to which a hierarchically organized memory structure is searched is controlled by the neuronal adaptability, i.e. the strength of coupling between neuronal activity and excitability. In the brain, the concentration of various neuromodulators in turn can regulate the adaptability. An autonomously controlled sequence of bifurcations, from an initial exploratory to a final retrieval phase, of an associative process is shown to result from an activity-dependent release of neuromodulators. The dynamics control mechanism may be important in the context of various disorders of the brain and may also extend the range of applications of artificial neural networks.     

Neuronal encoding of sound, gravity, and wind in the fruit fly

The fruit fly Drosophila melanogaster responds behaviorally to sound, gravity, and wind. Exposure to male courtship songs results in reduced locomotion in females, whereas males begin to chase each other. When agitated, fruit flies tend to move against gravity. When faced with air currents, they ‘freeze’ in place. Based on recent studies, Johnston’s hearing organ, the antennal ear of the fruit fly, serves as a sensor for all of these mechanosensory stimuli. Compartmentalization of sense cells in Johnston’s organ into vibration-sensitive and deflection-sensitive neural groups allows this single organ to mediate such varied functions. Sound and gravity/wind signals sensed by these two neuronal groups travel in parallel from the fly ear to the brain, feeding into neural pathways reminiscent of the auditory and vestibular pathways in the human brain. Studies of the similarities between mammals and flies will lead to a better understanding of the principles of how sound and gravity information is encoded in the brain. Here, we review recent advances in our understanding of these principles and discuss the advantages of the fruit fly as a model system to explore the fundamental principles of how neural circuits and their ensembles process and integrate sensory information in the brain.     

Remote excitation of neuronal circuits using low-intensity, low-frequency ultrasound

Possessing the ability to noninvasively elicit brain circuit activity yields immense experimental and therapeutic power. Most currently employed neurostimulation methods rely on the somewhat invasive use of stimulating electrodes or photon-emitting devices. Due to its ability to noninvasively propagate through bone and other tissues in a focused manner, the implementation of ultrasound (US) represents a compelling alternative approach to current neuromodulation strategies. Here, we investigated the influence of low-intensity, low-frequency ultrasound (LILFU) on neuronal activity. By transmitting US waveforms through hippocampal slice cultures and ex vivo mouse brains, we determined LILFU is capable of remotely and noninvasively exciting neurons and network activity. Our results illustrate that LILFU can stimulate electrical activity in neurons by activating voltage-gated sodium channels, as well as voltage-gated calcium channels. The LILFU-induced changes in neuronal activity were sufficient to trigger SNARE-mediated exocytosis and synaptic transmission in hippocampal circuits. Because LILFU can stimulate electrical activity and calcium signaling in neurons as well as central synaptic transmission we conclude US provides a powerful tool for remotely modulating brain circuit activity.     

Dynamics control of semantic processes in a hierarchical associative memory

 A neural mechanism for control of dynamics and function of associative processes in a hierarchical memory system is demonstrated. For the representation and processing of abstract knowledge, the semantic declarative memory system of the human brain is considered. The dynamics control mechanism is based on the influence of neuronal adaptation on the complexity of neural network dynamics. Different dynamical modes correspond to different levels of the ultrametric structure of the hierarchical memory being invoked during an associative process. The mechanism is deterministic but may also underlie free associative thought processes. The formulation of an abstract neural network model of hierarchical associative memory utilizes a recent approach to incorporate neuronal adaptation. It includes a generalized neuronal activation function recently derived by a Hodgkin-Huxley-type model. It is shown that the extent to which a hierarchically organized memory structure is searched is controlled by the neuronal adaptability, i.e. the strength of coupling between neuronal activity and excitability. In the brain, the concentration of various neuromodulators in turn can regulate the adaptability. An autonomously controlled sequence of bifurcations, from an initial exploratory to a final retrieval phase, of an associative process is shown to result from an activity-dependent release of neuromodulators. The dynamics control mechanism may be important in the context of various disorders of the brain and may also extend the range of applications of artificial neural networks. Received: 19 April 1995/Accepted in revised form: 8 August 1995     

Transcranial magnetic stimulation, causal structure-function mapping and networks of functional relevance

Transcranial magnetic stimulation is now a well-established tool for inducing transient changes in brain activity non-invasively in conscious human volunteers. During the past couple of years, the ability to actively interfere with neural processing during behavioral performance has been used increasingly for the investigation of causal brain-behavior relationships in higher cognitive functions. The simultaneous combination of transcranial magnetic stimulation with methods of functional brain imaging, however, promises to be of especially great value for our understanding of the human brain, as it provides the opportunity to stimulate brain circuits while simultaneously monitoring changes in brain activity and behavior. Such an approach could help us to identify brain networks of functional relevance, and might enable causal brain-behavior inferences across the entire brain.     

A cultured human neural network operates a robotic actuator

The development of bio-electronic prostheses, hybrid human-electronics devices and bionic robots has been the aim of many researchers. Although neurophysiologic processes have been widely investigated and bio-electronics has developed rapidly, the dynamics of a biological neuronal network that receive sensory inputs, store and control information is not yet understood. Toward this end, we have taken an interdisciplinary approach to study the learning and response of biological neural networks to complex stimulation patterns. This paper describes the design, execution, and results of several experiments performed in order to investigate the behavior of complex interconnected structures found in biological neural networks. The experimental design consisted of biological human neurons stimulated by parallel signal patterns intended to simulate complex perceptions. The response patterns were analyzed with an innovative artificial neural network (ANN), called ITSOM (Inductive Tracing Self Organizing Map). This system allowed us to decode the complex neural responses from a mixture of different stimulations and learned memory patterns inherent in the cell colonies. In the experiment described in this work, neurons derived from human neural stem cells were connected to a robotic actuator through the ANN analyzer to demonstrate our ability to produce useful control from simulated perceptions stimulating the cells. Preliminary results showed that in vitro human neuron colonies can learn to reply selectively to different stimulation patterns and that response signals can effectively be decoded to operate a minirobot. Lastly the fascinating performance of the hybrid system is evaluated quantitatively and potential future work is discussed.