The computational power of astrocyte mediated synaptic plasticity

Tactile discrimination as a diagnostic indicator of cognitive decline in patients with mild cognitive impairment: A narrative review

Background

Tactile discrimination, a cognitive task reliant on fingertip touch for stimulus discrimination, encompasses the somatosensory system and working memory, with its acuity diminishing with advancing age. Presently, the evaluation of cognitive capacity to differentiate between individuals with early Alzheimer's disease (AD) and typical older adults predominantly relies on visual or auditory tasks, yet the efficacy of discrimination remains constrained.

Aims

To review the existing tactile cognitive tasks and explore the interaction between tactile perception and the pathological process of Alzheimer's disease. The tactile discrimination task may be used as a reference index of cognitive decline in patients with mild cognitive impairment and provide a new method for clinical evaluation.

Methods

We searched four databases (Embase, PubMed, Web of Science and Google scholar). The reference coverage was from 1936 to 2023. The search terms included "Alzheimer disease" "mild cognitive impairment" "tactile" "tactile discrimination" "tactile test" and so on. Reviews and experimental reports in the field were examined and the effectiveness of different types of tactile tasks was compared.

Main results

Individuals in the initial phases of Alzheimer's spectrum disease, specifically those in the stage of mild cognitive impairment (MCI), exhibit notable impairments in tasks involving tactile discrimination. These tasks possess certain merits, such as their quick and straightforward comparability, independence from educational background, and ability to circumvent the limitations associated with conventional cognitive assessment scales. Furthermore, tactile discrimination tasks offer enhanced accuracy compared to cognitive tasks that employ visual or auditory stimuli.

Conclusions

Tactile discrimination has the potential to serve as an innovative reference indicator for the swift diagnosis of clinical MCI patients, thereby assisting in the screening process on a clinical scale.

The computational power of the human brain

At the end of the 20th century, analog systems in computer science have been widely replaced by digital systems due to their higher computing power. Nevertheless, the question keeps being intriguing until now: is the brain analog or digital? Initially, the latter has been favored, considering it as a Turing machine that works like a digital computer. However, more recently, digital and analog processes have been combined to implant human behavior in robots, endowing them with artificial intelligence (AI). Therefore, we think it is timely to compare mathematical models with the biology of computation in the brain. To this end, digital and analog processes clearly identified in cellular and molecular interactions in the Central Nervous System are highlighted. But above that, we try to pinpoint reasons distinguishing in silico computation from salient features of biological computation. First, genuinely analog information processing has been observed in electrical synapses and through gap junctions, the latter both in neurons and astrocytes. Apparently opposed to that, neuronal action potentials (APs) or spikes represent clearly digital events, like the yes/no or 1/0 of a Turing machine. However, spikes are rarely uniform, but can vary in amplitude and widths, which has significant, differential effects on transmitter release at the presynaptic terminal, where notwithstanding the quantal (vesicular) release itself is digital. Conversely, at the dendritic site of the postsynaptic neuron, there are numerous analog events of computation. Moreover, synaptic transmission of information is not only neuronal, but heavily influenced by astrocytes tightly ensheathing the majority of synapses in brain (tripartite synapse). At least at this point, LTP and LTD modifying synaptic plasticity and believed to induce short and long-term memory processes including consolidation (equivalent to RAM and ROM in electronic devices) have to be discussed. The present knowledge of how the brain stores and retrieves memories includes a variety of options (e.g., neuronal network oscillations, engram cells, astrocytic syncytium). Also epigenetic features play crucial roles in memory formation and its consolidation, which necessarily guides to molecular events like gene transcription and translation. In conclusion, brain computation is not only digital or analog, or a combination of both, but encompasses features in parallel, and of higher orders of complexity.

A novel role for MLC1 in regulating astrocyte-synapse interactions

Loss of function of the astrocyte membrane protein MLC1 is the primary genetic cause of the rare white matter disease Megalencephalic Leukoencephalopathy with subcortical Cysts (MLC), which is characterized by disrupted brain ion and water homeostasis. MLC1 is prominently present around fluid barriers in the brain, such as in astrocyte endfeet contacting blood vessels and in processes contacting the meninges. Whether the protein plays a role in other astrocyte domains is unknown. Here, we show that MLC1 is present in distal astrocyte processes, also known as perisynaptic astrocyte processes (PAPs) or astrocyte leaflets, which closely interact with excitatory synapses in the CA1 region of the hippocampus. We find that the PAP tip extending toward excitatory synapses is shortened in Mlc1-null mice. This affects glutamatergic synaptic transmission, resulting in a reduced rate of spontaneous release events and slower glutamate re-uptake under challenging conditions. Moreover, while PAPs in wildtype mice retract from the synapse upon fear conditioning, we reveal that this structural plasticity is disturbed in Mlc1-null mice, where PAPs are already shorter. Finally, Mlc1-null mice show reduced contextual fear memory. In conclusion, our study uncovers an unexpected role for the astrocyte protein MLC1 in regulating the structure of PAPs. Loss of MLC1 alters excitatory synaptic transmission, prevents normal PAP remodeling induced by fear conditioning and disrupts contextual fear memory expression. Thus, MLC1 is a new player in the regulation of astrocyte-synapse interactions.

Analysis of Network Models with Neuron-Astrocyte Interactions

Neural networks, composed of many neurons and governed by complex interactions between them, are a widely accepted formalism for modeling and exploring global dynamics and emergent properties in brain systems. In the past decades, experimental evidence of computationally relevant neuron-astrocyte interactions, as well as the astrocytic modulation of global neural dynamics, have accumulated. These findings motivated advances in computational glioscience and inspired several models integrating mechanisms of neuron-astrocyte interactions into the standard neural network formalism. These models were developed to study, for example, synchronization, information transfer, synaptic plasticity, and hyperexcitability, as well as classification tasks and hardware implementations. We here focus on network models of at least two neurons interacting bidirectionally with at least two astrocytes that include explicitly modeled astrocytic calcium dynamics. In this study, we analyze the evolution of these models and the biophysical, biochemical, cellular, and network mechanisms used to construct them. Based on our analysis, we propose how to systematically describe and categorize interaction schemes between cells in neuron-astrocyte networks. We additionally study the models in view of the existing experimental data and present future perspectives. Our analysis is an important first step towards understanding astrocytic contribution to brain functions. However, more advances are needed to collect comprehensive data about astrocyte morphology and physiology in vivo and to better integrate them in data-driven computational models. Broadening the discussion about theoretical approaches and expanding the computational tools is necessary to better understand astrocytes' roles in brain functions.

Far from home: the role of glial mRNA localization in synaptic plasticity

Neurons and glia are highly polarized cells, whose distal cytoplasmic functional subdomains require specific proteins. Neurons have axonal and dendritic cytoplasmic extensions containing synapses whose plasticity is regulated efficiently by mRNA transport and localized translation. The principles behind these mechanisms are equally attractive for explaining rapid local regulation of distal glial cytoplasmic projections, independent of their cell nucleus. However, in contrast to neurons, mRNA localization has received little experimental attention in glia. Nevertheless, there are many functionally diverse glial subtypes containing extensive networks of long cytoplasmic projections with likely localized regulation that influence neurons and their synapses. Moreover, glia have many other neuron-like properties, including electrical activity, secretion of gliotransmitters and calcium signaling, influencing, for example, synaptic transmission, plasticity and axon pruning. Here, we review previous studies concerning glial transcripts with important roles in influencing synaptic plasticity, focusing on a few cases involving localized translation. We discuss a variety of important questions about mRNA transport and localized translation in glia that remain to be addressed, using cutting-edge tools already available for neurons.

Presynaptic NMDA Receptors Influence Ca2+ Dynamics by Interacting with Voltage-Dependent Calcium Channels during the Induction of Long-Term Depression

Spike-timing-dependent long-term depression (t-LTD) of glutamatergic layer (L)4-L2/3 synapses in developing neocortex requires activation of astrocytes by endocannabinoids (eCBs), which release glutamate onto presynaptic NMDA receptors (preNMDARs). The exact function of preNMDARs in this context is still elusive and strongly debated. To elucidate their function, we show that bath application of the eCB 2-arachidonylglycerol (2-AG) induces a preNMDAR-dependent form of chemically induced LTD (eCB-LTD) in L2/3 pyramidal neurons in the juvenile somatosensory cortex of rats. Presynaptic Ca²⁺ imaging from L4 spiny stellate axons revealed that action potential (AP) evoked Ca²⁺ transients show a preNMDAR-dependent broadening during eCB-LTD induction. However, blockade of voltage-dependent Ca²⁺ channels (VDCCs) did not uncover direct preNMDAR-mediated Ca²⁺ transients in the axon. This suggests that astrocyte-mediated glutamate release onto preNMDARs does not result in a direct Ca²⁺ influx, but that it instead leads to an indirect interaction with presynaptic VDCCs, boosting axonal Ca²⁺ influx. These results reveal one of the main remaining missing pieces in the signaling cascade of t-LTD at developing cortical synapses.

Neuronal Glial Crosstalk: Specific and Shared Mechanisms in Alzheimer’s Disease

The human brain maintains billions of neurons functional across the lifespan of the individual. The glial, supportive cells of the brain are indispensable to neuron elasticity. They undergo various states (active, reactive, macrophage, primed, resting) and carefully impose either quick repair or the cleaning of injured neurons to avoid damage extension. Identifying the failure of these interactions involving the relation of the input of glial cells to the inception and/or progression of chronic neurodegenerative diseases (ND) is crucial in identifying therapeutic options, given the well-built neuro-immune module of these diseases. In the present review, we scrutinize different interactions and important factors including direct cell–cell contact, intervention by the CD200 system, various receptors present on their surfaces, CXC3RI and TREM2, and chemokines and cytokines with special reference to Alzheimer’s disease (AD). The present review of the available literature will elucidate the contribution of microglia and astrocytes to the pathophysiology of AD, thus evidencing glial cells as obligatory transducers of pathology and superlative targets for interference.

Dendritic Organic Electrochemical Transistors Grown by Electropolymerization for 3D Neuromorphic Engineering

One of the major limitations of standard top-down technologies used in today's neuromorphic engineering is their inability to map the 3D nature of biological brains. Here, it is shown how bipolar electropolymerization can be used to engineer 3D networks of PEDOT:PSS dendritic fibers. By controlling the growth conditions of the electropolymerized material, it is investigated how dendritic fibers can reproduce structural plasticity by creating structures of controllable shape. Gradual topologies evolution is demonstrated in a multielectrode configuration. A detailed electrical characterization of the PEDOT:PSS dendrites is conducted through DC and impedance spectroscopy measurements and it is shown how organic electrochemical transistors (OECT) can be realized with these structures. These measurements reveal that quasi-static and transient response of OECTs can be adjusted by controlling dendrites' morphologies. The unique properties of organic dendrites are used to demonstrate short-term, long-term, and structural plasticity, which are essential features required for future neuromorphic hardware development.

Chemokine-like Receptor 1 in Brain of Spontaneously Hypertensive Rats Mediates Systemic Hypertension

Adipocytokine chemerin is a biologically active molecule secreted from adipose tissue. Chemerin elicits a variety of functions via chemokine-like receptor 1 (CMKLR1). The cardiovascular center in brain that regulates blood pressure (BP) is involved in pathophysiology of systemic hypertension. Thus, we explored the roles of brain chemerin/CMKLR1 on regulation of BP in spontaneously hypertensive rats (SHR). For this aim, we examined effects of intracerebroventricular (i.c.v.) injection of CMKLR1 small interfering (si)RNA on both systemic BP as measured by tail cuff system and protein expression in paraventricular nucleus (PVN) of SHR as determined by Western blotting. We also examined both central and peripheral protein expression of chemerin by Western blotting. Systolic BP of SHR but not normotensive Wistar Kyoto rats (WKY) was decreased by CMKLR1 siRNA. The decrease of BP by CMKLR1 siRNA persisted for 3 days. Protein expression of CMKLR1 in PVN of SHR tended to be increased compared with WKY, which was suppressed by CMKLR1 siRNA. Protein expression of chemerin in brain, peripheral plasma, and adipose tissue was not different between WKY and SHR. In summary, we for the first time revealed that the increased protein expression of CMKLR1 in PVN is at least partly responsible for systemic hypertension in SHR.

Astrocytic IGF-IRs Induce Adenosine-Mediated Inhibitory Downregulation and Improve Sensory Discrimination

Insulin-like growth factor-I (IGF-I) signaling plays a key role in learning and memory processes. While the effects of IGF-I on neurons have been studied extensively, the involvement of astrocytes in IGF-I signaling and the consequences on synaptic plasticity and animal behavior remain unknown. We have found that IGF-I induces long-term potentiation (LTP_IGFI) of the postsynaptic potentials that is caused by a long-term depression of inhibitory synaptic transmission in mice. We have demonstrated that this long-lasting decrease in the inhibitory synaptic transmission is evoked by astrocytic activation through its IGF-I receptors (IGF-IRs). We show that LTP_IGFI not only increases the output of pyramidal neurons, but also favors the NMDAR-dependent LTP, resulting in the crucial information processing at the barrel cortex since specific deletion of IGF-IR in cortical astrocytes impairs the whisker discrimination task. Our work reveals a novel mechanism and functional consequences of IGF-I signaling on cortical inhibitory synaptic plasticity and animal behavior, revealing that astrocytes are key elements in these processes.SIGNIFICANCE STATEMENT Insulin-like growth factor-I (IGF-I) signaling plays key regulatory roles in multiple processes of brain physiology, such as learning and memory. Yet, the underlying mechanisms remain largely undefined. Here we demonstrate that astrocytes respond to IGF-I signaling, elevating their intracellular Ca²⁺ and stimulating the release of ATP/adenosine, which triggers the LTD of cortical inhibitory synapses, thus regulating the behavioral task performance related to cortical sensory information processing. Therefore, the present work represents a major conceptual advance in our knowledge of the cellular basis of IGF-I signaling in brain function, by including for the first time astrocytes as key mediators of IGF-I actions on synaptic plasticity, cortical sensory information discrimination and animal behavior.

Estimating integrated information in bidirectional neuron-astrocyte communication

There is growing evidence that suggests the importance of astrocytes as elements for neural information processing through the modulation of synaptic transmission. A key aspect of this problem is understanding the impact of astrocytes in the information carried by compound events in neurons across time. In this paper, we investigate how the astrocytes participate in the information integrated by individual neurons in an ensemble through the measurement of "integrated information." We propose a computational model that considers bidirectional communication between astrocytes and neurons through glutamate-induced calcium signaling. Our model highlights the role of astrocytes in information processing through dynamical coordination. Our findings suggest that the astrocytic feedback promotes synergetic influences in the neural communication, which is maximized when there is a balance between excess correlation and spontaneous spiking activity. The results were further linked with additional measures such as net synergy and mutual information. This result reinforces the idea that astrocytes have integrative properties in communication among neurons.

On the Self-Repair Role of Astrocytes in STDP Enabled Unsupervised SNNs

Neuromorphic computing is emerging to be a disruptive computational paradigm that attempts to emulate various facets of the underlying structure and functionalities of the brain in the algorithm and hardware design of next-generation machine learning platforms. This work goes beyond the focus of current neuromorphic computing architectures on computational models for neuron and synapse to examine other computational units of the biological brain that might contribute to cognition and especially self-repair. We draw inspiration and insights from computational neuroscience regarding functionalities of glial cells and explore their role in the fault-tolerant capacity of Spiking Neural Networks (SNNs) trained in an unsupervised fashion using Spike-Timing Dependent Plasticity (STDP). We characterize the degree of self-repair that can be enabled in such networks with varying degree of faults ranging from 50 to 90% and evaluate our proposal on the MNIST and Fashion-MNIST datasets.

Astrocyte-mediated spike-timing-dependent long-term depression modulates synaptic properties in the developing cortex

Astrocytes have been shown to modulate synaptic transmission and plasticity in specific cortical synapses, but our understanding of the underlying molecular and cellular mechanisms remains limited. Here we present a new biophysicochemical model of a somatosensory cortical layer 4 to layer 2/3 synapse to study the role of astrocytes in spike-timing-dependent long-term depression (t-LTD) in vivo. By applying the synapse model and electrophysiological data recorded from rodent somatosensory cortex, we show that a signal from a postsynaptic neuron, orchestrated by endocannabinoids, astrocytic calcium signaling, and presynaptic N-methyl-D-aspartate receptors coupled with calcineurin signaling, induces t-LTD which is sensitive to the temporal difference between post- and presynaptic firing. We predict for the first time the dynamics of astrocyte-mediated molecular mechanisms underlying t-LTD and link complex biochemical networks at presynaptic, postsynaptic, and astrocytic sites to the time window of t-LTD induction. During t-LTD a single astrocyte acts as a delay factor for fast neuronal activity and integrates fast neuronal sensory processing with slow non-neuronal processing to modulate synaptic properties in the brain. Our results suggest that astrocytes play a critical role in synaptic computation during postnatal development and are of paramount importance in guiding the development of brain circuit functions, learning and memory.

Unifying Long-Term Plasticity Rules for Excitatory Synapses by Modeling Dendrites of Cortical Pyramidal Neurons

A large number of experiments have indicated that precise spike times, firing rates, and synapse locations crucially determine the dynamics of long-term plasticity induction in excitatory synapses. However, it remains unknown how plasticity mechanisms of synapses distributed along dendritic trees cooperate to produce the wide spectrum of outcomes for various plasticity protocols. Here, we propose a four-pathway plasticity framework that is well grounded in experimental evidence and apply it to a biophysically realistic cortical pyramidal neuron model. We show in computer simulations that several seemingly contradictory experimental landmark studies are consistent with one unifying set of mechanisms when considering the effects of signal propagation in dendritic trees with respect to synapse location. Our model identifies specific spatiotemporal contributions of dendritic and axo-somatic spikes as well as of subthreshold activation of synaptic clusters, providing a unified parsimonious explanation not only for rate and timing dependence but also for location dependence of synaptic changes.

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A phenomenological synaptic plasticity rule is applied to a pyramidal neuron model

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Model reproduces rate-, timing-, and location-dependent plasticity results

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Active dendrites allow plasticity via dendritic spikes and subthreshold events

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Cooperative plasticity exists across the dendritic tree and within single branches

Cannabinoid Signaling Recruits Astrocytes to Modulate Presynaptic Function in the Suprachiasmatic Nucleus

Circadian rhythms are 24-h cycles in physiology regulated by the suprachiasmatic nucleus (SCN) in the brain, where daily cues act on SCN neurons to alter clock timing. Cannabinoid signaling modulates SCN neuronal activity, although the mechanism remains unclear. We propose that neuronal activity generates endocannabinoid release, activating astrocyte Ca²⁺ signaling, which releases adenosine and activates adenosine-1 receptors (A1Rs) on the presynaptic axon terminals, decreasing GABA release. We demonstrated, in mice, that activation of cannabinoid-1 receptors (CB1R) with the agonist WIN 55,212-2 (WIN) reduced the miniature GABA receptor-mediated postsynaptic current (mGPSC) frequency by a mechanism that requires astrocytes and A1R. WIN activated an intracellular Ca²⁺ signaling pathway in astrocytes. Activating this intracellular Ca²⁺ pathway with designer receptors exclusively activated by designer drugs (DREADDs) also decreased the mGPSC frequency and required A1R activation. The frequency of spontaneous Ca²⁺ events, including those induced by depolarization of a postsynaptic SCN neuron, was reduced by blocking CB1R activation with AM251, demonstrating neuronal endocannabinoid signaling modulates astrocytic Ca²⁺ signaling in the SCN. Finally, daytime application of WIN or adenosine phase advanced the molecular circadian clock, indicating that this cannabinoid signaling pathway is vital for the timing of circadian rhythms.

The endocannabinoid system regulates the moderate exercise-induced enhancement of learning and memory in mice

BACKGROUND

Exercise has been reported to enhance cognitive functions via mechanism(s) yet to be fully understood. The endogenous cannabinoid system (ECS) is involved in regulating cognitive function, including learning and memory. This system may also be involved in enhancing learning and memory after exercise. The objective of this study is to explore whether and how ECS participates in the enhancement of learning and memory after exercise.

METHODS

In this study, a treadmill exercise training model was established. Wild-type C57BL/6J mice and those deficient in the cannabinoid receptor 1 (CB1R) coding gene, Cnr1, specifically in the glutamatergic neurons, γ-aminobutyric acid (GABA) neurons or glial cells were randomly grouped for 4 weeks' moderate treadmill exercise. The Morris water maze was used to evaluate the spatial learning and memory abilities of mice in each group. The expression of brain-derived neurotrophic factor (BDNF) and CB1R in hippocampus was detected by western blot. The dendritic spine density of pyramidal cells in the hippocampal CA1 region was analyzed by quantitative Golgi staining. This study consisted of eight single-factor inter-subject designs, and each batch of experiments was divided into two groups. Corresponding experimental items and data analysis were carried out according to the experimental objectives.

RESULTS

CB1R antagonist administration or CB1R knockout in glutamatergic neurons eliminated the effect of exercise on learning and memory, and counteracted exercise-elicited upregulation of BDNF in the hippocampus; CB1R-specific knockout on GABAergic neurons and glial cells did not affect the moderate exercise-induced enhancement of learning and memory. In addition, the results of Golgi staining showed that exercise increased dendritic spine density in hippocampal neurons, which was abolished by specific CB1R depletion in glutamatergic neurons.

CONCLUSIONS

The ECS, particularly CB1R signaling in glutamatergic neurons, mediates the enhancement of learning and memory by exercise, which involves increased BDNF production and dendritic spine density.

A Computational Model of Interactions Between Neuronal and Astrocytic Networks: The Role of Astrocytes in the Stability of the Neuronal Firing Rate

Recent research in neuroscience indicates the importance of tripartite synapses and gliotransmission mediated by astrocytes in neuronal system modulation. Although the astrocyte and neuronal network functions are interrelated, they are fundamentally different in their signaling patterns and, possibly, the time scales at which they operate. However, the exact nature of gliotransmission and the effect of the tripartite synapse function at the network level are currently elusive. In this paper, we propose a computational model of interactions between an astrocyte network and a neuron network, starting from tripartite synapses and spanning to a joint network level. Our model focuses on a two-dimensional setup emulating a mixed in vitro neuron-astrocyte cell culture. The model depicts astrocyte-released gliotransmitters exerting opposing effects on the neurons: increasing the release probability of the presynaptic neuron while hyperpolarizing the post-synaptic one at a longer time scale. We simulated the joint networks with various levels of astrocyte contributions and neuronal activity levels. Our results indicate that astrocytes prolong the burst duration of neurons, while restricting hyperactivity. Thus, in our model, the effect of astrocytes is homeostatic; the firing rate of the network stabilizes to an intermediate level independently of neuronal base activity. Our computational model highlights the plausible roles of astrocytes in interconnected astrocytic and neuronal networks. Our simulations support recent findings in neurons and astrocytes in vivo and in vitro suggesting that astrocytic networks provide a modulatory role in the bursting of the neuronal network.

Dopamine-Evoked Synaptic Regulation in the Nucleus Accumbens Requires Astrocyte Activity

Dopamine is involved in physiological processes like learning and memory, motor control and reward, and pathological conditions such as Parkinson's disease and addiction. In contrast to the extensive studies on neurons, astrocyte involvement in dopaminergic signaling remains largely unknown. Using transgenic mice, optogenetics, and pharmacogenetics, we studied the role of astrocytes on the dopaminergic system. We show that in freely behaving mice, astrocytes in the nucleus accumbens (NAc), a key reward center in the brain, respond with Ca²⁺ elevations to synaptically released dopamine, a phenomenon enhanced by amphetamine. In brain slices, synaptically released dopamine increases astrocyte Ca²⁺, stimulates ATP/adenosine release, and depresses excitatory synaptic transmission through activation of presynaptic A₁ receptors. Amphetamine depresses neurotransmission through stimulation of astrocytes and the consequent A₁ receptor activation. Furthermore, astrocytes modulate the acute behavioral psychomotor effects of amphetamine. Therefore, astrocytes mediate the dopamine- and amphetamine-induced synaptic regulation, revealing a novel cellular pathway in the brain reward system.

Molecular Plasticity of the Nucleus Accumbens Revisited-Astrocytic Waves Shall Rise

Part of the ventral striatal division, the nucleus accumbens (NAc) drives the circuit activity of an entire macrosystem about reward like a "flagship," signaling and leading diverse conducts. Accordingly, NAc neurons feature complex inhibitory phenotypes that assemble to process circuit inputs and generate outputs by exploiting specific arrays of opposite and/or parallel neurotransmitters, neuromodulatory peptides. The resulting complex combinations enable versatile yet specific forms of accumbal circuit plasticity, including maladaptive behaviors. Although reward signaling and behavior are elaborately linked to neuronal circuit activities, it is plausible to propose whether these neuronal ensembles and synaptic islands can be directly controlled by astrocytes, a powerful modulator of neuronal activity. Pioneering studies showed that astrocytes in the NAc sense citrate cycle metabolites and/or ATP and may induce recurrent activation. We argue that the astrocytic calcium, GABA, and Glu signaling and altered sodium and chloride dynamics fundamentally shape metaplasticity by providing active regulatory roles in the synapse- and network-level flexibility of the NAc.

A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations

Neurophysiological observations are clarifying how astrocytes can actively participate in information processing and how they can encode information through frequency and amplitude modulation of intracellular Ca²⁺ signals. Consequently, hardware realization of astrocytes is important for developing the next generation of bio-inspired computing systems. In this paper, astrocytic calcium oscillations and neuronal firing dynamics are presented by De Pittà and IF (Integrated & Fire) models, respectively. Considering highly nonlinear equations of the astrocyte model, linear approximation and single constant multiplication (SCM) techniques are employed for efficient hardware execution while maintaining the dynamic of the original models. This low-cost hardware architecture for the astrocyte model is able to show the essential features of different types of Ca²⁺ modulation such as amplitude modulation (AM), frequency modulation (FM), or both modes (AFM). To show good agreement between the results of original models simulated in MATLAB and the proposed digital circuits executed on FPGA, quantitative, and qualitative analyses including phase plane are done. This new neuromorphic circuit of astrocyte is able to successfully demonstrate AM/FM/AFM calcium signaling in its real operation on FPGA and has applications in self-repairing systems. It also can be employed as a subsystem for linking biological cells to artificial neuronal networks using astrocytic calcium oscillations in future research.

Neurons and astrocytes interaction in neuronal network: A game-theoretic approach

A neuron is the fundamental unit of the nervous system and the brain, crucial for transducing information in form of trains of electrical pulses known as action potentials. The connection between neurons is through synapses, enabling communication between neurons. This communication link is one of the key elements in processing of information from a neuron to another neuron. The strength of the synapses may vary over time, a phenomenon known as synaptic plasticity. This is the process by which it is believed memory and learning is governed. Recent studies revealed environmental factors affect the strength of synapses, and the way neurons communicate to each other. This poses the question as to what extent the pre- and post- synaptic neurons sense the environmental changes, and in turn adjust their synaptic link. Here, we model the behavior of an interconnected neuronal network in various environmental conditions as a multi-agent system in a game theoretic framework. We focus on a CA1 lattice subfield as an example plastic neuronal network. Our analysis revealed the neuronal network converges to different equilibria depending on the environmental changes. The model well-predicts the behavior of the network compared to a well-known theoretical model of individual neurons.

Planarian regeneration as a model of anatomical homeostasis: Recent progress in biophysical and computational approaches

Planarian behavior, physiology, and pattern control offer profound lessons for regenerative medicine, evolutionary biology, morphogenetic engineering, robotics, and unconventional computation. Despite recent advances in the molecular genetics of stem cell differentiation, this model organism's remarkable anatomical homeostasis provokes us with truly fundamental puzzles about the origin of large-scale shape and its relationship to the genome. In this review article, we first highlight several deep mysteries about planarian regeneration in the context of the current paradigm in this field. We then review recent progress in understanding of the physiological control of an endogenous, bioelectric pattern memory that guides regeneration, and how modulating this memory can permanently alter the flatworm's target morphology. Finally, we focus on computational approaches that complement reductive pathway analysis with synthetic, systems-level understanding of morphological decision-making. We analyze existing models of planarian pattern control and highlight recent successes and remaining knowledge gaps in this interdisciplinary frontier field.

Astrocyte-Neuron Networks: A Multilane Highway of Signaling for Homeostatic Brain Function

Research on glial cells over the past 30 years has confirmed the critical role of astrocytes in pathophysiological brain states. However, most of our knowledge about astrocyte physiology and of the interactions between astrocytes and neurons is based on the premises that astrocytes constitute a homogeneous cell type, without considering the particular properties of the circuits or brain nuclei in which the astrocytes are located. Therefore, we argue that more-sophisticated experiments are required to elucidate the specific features of astrocytes in different brain regions, and even within different layers of a particular circuit. Thus, in addition to considering the diverse mechanisms used by astrocytes to communicate with neurons and synaptic partners, it is necessary to take into account the cellular heterogeneity that likely contributes to the outcomes of astrocyte-neuron signaling. In this review article, we briefly summarize the current data regarding the anatomical, molecular and functional properties of astrocyte-neuron communication, as well as the heterogeneity within this communication.

Diversity and Specificity of Astrocyte-neuron Communication

Astrocytes are emerging as important players in synaptic function, and, consequently, on brain function and animal behavior. According to the Tripartite Synapse concept, astrocytes are integral elements involved in synaptic function. They establish bidirectional communication with neurons, whereby they respond to synaptically released neurotransmitters and, in turn, release gliotransmitters that influence neuronal and synaptic activity. Accumulating evidence is revealing that the mechanisms and functional consequences of astrocyte-neuron signaling are more complex than originally thought. Furthermore, astrocyte-neuron signaling is not based on broad, unspecific interaction; rather, it is a synapse-, cell- and circuit-specific phenomenon that presents a high degree of complexity. This diversity and complexity of astrocyte-synapse interactions greatly enhance the degrees of freedom of the neural circuits and the consequent computational power of the neural systems.

Peeking into the sleeping brain: Using in vivo imaging in rodents to understand the relationship between sleep and cognition

Sleep is well known to benefit cognitive function. In particular, sleep has been shown to enhance learning and memory in both humans and animals. While the underlying mechanisms are not fully understood, it has been suggested that brain activity during sleep modulates neuronal communication through synaptic plasticity. These insights were mostly gained using electrophysiology to monitor ongoing large scale and single cell activity. While these efforts were instrumental in the characterisation of important network and cellular activity during sleep, several aspects underlying cognition are beyond the reach of this technology. Neuronal circuit activity is dynamically regulated via the precise interaction of different neuronal and non-neuronal cell types and relies on subtle modifications of individual synapses. In contrast to established electrophysiological approaches, recent advances in imaging techniques, mainly applied in rodents, provide unprecedented access to these aspects of neuronal function in vivo. In this review, we describe various techniques currently available for in vivo brain imaging, from single synapse to large scale network activity. We discuss the advantages and limitations of these approaches in the context of sleep research and describe which particular aspects related to cognition lend themselves to this kind of investigation. Finally, we review the few studies that used in vivo imaging in rodents to investigate the sleeping brain and discuss how the results have already significantly contributed to a better understanding on the complex relation between sleep and plasticity across development and adulthood.

Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures

The possibility to replicate and reproduce published research results is one of the biggest challenges in all areas of science. In computational neuroscience, there are thousands of models available. However, it is rarely possible to reimplement the models based on the information in the original publication, let alone rerun the models just because the model implementations have not been made publicly available. We evaluate and discuss the comparability of a versatile choice of simulation tools: tools for biochemical reactions and spiking neuronal networks, and relatively new tools for growth in cell cultures. The replicability and reproducibility issues are considered for computational models that are equally diverse, including the models for intracellular signal transduction of neurons and glial cells, in addition to single glial cells, neuron-glia interactions, and selected examples of spiking neuronal networks. We also address the comparability of the simulation results with one another to comprehend if the studied models can be used to answer similar research questions. In addition to presenting the challenges in reproducibility and replicability of published results in computational neuroscience, we highlight the need for developing recommendations and good practices for publishing simulation tools and computational models. Model validation and flexible model description must be an integral part of the tool used to simulate and develop computational models. Constant improvement on experimental techniques and recording protocols leads to increasing knowledge about the biophysical mechanisms in neural systems. This poses new challenges for computational neuroscience: extended or completely new computational methods and models may be required. Careful evaluation and categorization of the existing models and tools provide a foundation for these future needs, for constructing multiscale models or extending the models to incorporate additional or more detailed biophysical mechanisms. Improving the quality of publications in computational neuroscience, enabling progressive building of advanced computational models and tools, can be achieved only through adopting publishing standards which underline replicability and reproducibility of research results.

Long-Term Plasticity of Neurotransmitter Release: Emerging Mechanisms and Contributions to Brain Function and Disease

Long-lasting changes of brain function in response to experience rely on diverse forms of activity-dependent synaptic plasticity. Chief among them are long-term potentiation and long-term depression of neurotransmitter release, which are widely expressed by excitatory and inhibitory synapses throughout the central nervous system and can dynamically regulate information flow in neural circuits. This review article explores recent advances in presynaptic long-term plasticity mechanisms and contributions to circuit function. Growing evidence indicates that presynaptic plasticity may involve structural changes, presynaptic protein synthesis, and transsynaptic signaling. Presynaptic long-term plasticity can alter the short-term dynamics of neurotransmitter release, thereby contributing to circuit computations such as novelty detection, modifications of the excitatory/inhibitory balance, and sensory adaptation. In addition, presynaptic long-term plasticity underlies forms of learning and its dysregulation participates in several neuropsychiatric conditions, including schizophrenia, autism, intellectual disabilities, neurodegenerative diseases, and drug abuse.

Computational Models for Calcium-Mediated Astrocyte Functions

The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus, we would like to emphasize that only via reproducible research are we able to build better computational models for astrocytes, which truly advance science. Our study is the first to characterize in detail the biophysical and biochemical mechanisms that have been modeled for astrocytes.

Computational modeling of opioid-induced synaptic plasticity in hippocampus

According to a broad range of research, opioids consumption can lead to pathological memory formation. Experimental observations suggested that hippocampal glutamatergic synapses play an indispensable role in forming such a pathological memory. It has been suggested that memory formation at the synaptic level is developed through LTP induction. Here, we attempt to computationally indicate how morphine induces pathological LTP at hippocampal CA3-CA1 synapses. Then, based on simulations, we will suggest how one can prevent this type of pathological LTP. To this purpose, a detailed computational model is presented, which consists of one pyramidal neuron and one interneuron both from CA3, one CA1 pyramidal neuron, and one astrocyte. Based on experimental findings morphine affects the hippocampal neurons in three primary ways: 1) disinhibitory mechanism of interneurons in CA3, 2) enhancement of NMDARs current by μ Opioid Receptor (μOR) activation and 3) by attenuation of astrocytic glutamate reuptake ability. By utilizing these effects, simulations were implemented. Our results indicate that morphine can induce LTP by all aforementioned possible mechanisms. Based on our simulation results, attenuation of pathologic LTP achieved mainly by stimulation of astrocytic glutamate transporters, down-regulation of the astrocytic metabotropic glutamate receptors (mGlurs) or by applying NMDAR’s antagonist. Based on our observations, we suggest that astrocyte has a dominant role in forming addiction-related memories. This finding may help researchers in exploring drug actions for preventing relapse.

The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics

Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

Neuronal activity determines distinct gliotransmitter release from a single astrocyte

Accumulating evidence indicates that astrocytes are actively involved in brain function by regulating synaptic activity and plasticity. Different gliotransmitters, such as glutamate, ATP, GABA or D-serine, released form astrocytes have been shown to induce different forms of synaptic regulation. However, whether a single astrocyte may release different gliotransmitters is unknown. Here we show that mouse hippocampal astrocytes activated by endogenous (neuron-released endocannabinoids or GABA) or exogenous (single astrocyte Ca²⁺ uncaging) stimuli modulate putative single CA3-CA1 hippocampal synapses. The astrocyte-mediated synaptic modulation was biphasic and consisted of an initial glutamate-mediated potentiation followed by a purinergic-mediated depression of neurotransmitter release. The temporal dynamic properties of this biphasic synaptic regulation depended on the firing frequency and duration of the neuronal activity that stimulated astrocytes. Present results indicate that single astrocytes can decode neuronal activity and, in response, release distinct gliotransmitters to differentially regulate neurotransmission at putative single synapses.

The influence of astrocytes on the width of orientation hypercolumns in visual cortex: A computational perspective

Orientation preference maps (OPMs) are present in carnivores (such as cats and ferrets) and primates but are absent in rodents. In this study we investigate the possible link between astrocyte arbors and presence of OPMs. We simulate the development of orientation maps with varying hypercolumn widths using a variant of the Laterally Interconnected Synergetically Self-Organizing Map (LISSOM) model, the Gain Control Adaptive Laterally connected (GCAL) model, with an additional layer simulating astrocytic activation. The synaptic activity of V1 neurons is given as input to the astrocyte layer. The activity of this astrocyte layer is now used to modulate bidirectional plasticity of lateral excitatory connections in the V1 layer. By simply varying the radius of the astrocytes, the extent of lateral excitatory neuronal connections can be manipulated. An increase in the radius of lateral excitatory connections subsequently increases the size of a single hypercolumn in the OPM. When these lateral excitatory connections become small enough the OPM disappears and a salt-and-pepper organization emerges.

Columns of neurons in the primary visual cortex (V1) are known to be tuned to visual stimuli containing edges of a particular orientation. The arrangement of these cortical columns varies across species. In many species such as in ferrets, cats, and monkeys a topology preserving map is observed, wherein similarly tuned columns are observed in close proximity to each other, resulting in the formation of Orientation Preference Maps (OPMs). The width of the hypercolumns, the fundamental unit of an OPM, also varies across species. However, such an arrangement is not observed in rodents, wherein a more random arrangement of these cortical columns is reported. We explore the role of astrocytes in the arrangement of these cortical columns using a self-organizing computational model. Invoking evidence that astrocytes could influence bidirectional plasticity among effective lateral excitatory connections in V1, we introduce a mechanism by which astrocytic inputs can influence map formation in the neuronal network. In the resulting model-generated OPMs the radius of the hypercolumns is found to be correlated with that of astrocytic arbors, a feature that finds support in experimental studies.

Synaptic Plasticity Selectively Activated by Polarization-Dependent Energy-Efficient Ion Migration in an Ultrathin Ferroelectric Tunnel Junction

Selectively activated inorganic synaptic devices, showing a high on/off ratio, ultrasmall dimensions, low power consumption, and short programming time, are required to emulate the functions of high-capacity and energy-efficient reconfigurable human neural systems combining information storage and processing ( Li et al. Sci. Rep. 2014 , 4 , 4096 ). Here, we demonstrate that such a synaptic device is realized using a Ag/PbZr_0.52Ti_0.48O₃ (PZT)/La_0.8Sr_0.2MnO₃ (LSMO) ferroelectric tunnel junction (FTJ) with ultrathin PZT (thickness of ∼4 nm). Ag ion migration through the very thin FTJ enables a large on/off ratio (10⁷) and low energy consumption (potentiation energy consumption = ∼22 aJ and depression energy consumption = ∼2.5 pJ). In addition, the simple alignment of the downward polarization in PZT selectively activates the synaptic plasticity of the FTJ and the transition from short-term plasticity to long-term potentiation.

Reproducibility and Comparability of Computational Models for Astrocyte Calcium Excitability

The scientific community across all disciplines faces the same challenges of ensuring accessibility, reproducibility, and efficient comparability of scientific results. Computational neuroscience is a rapidly developing field, where reproducibility and comparability of research results have gained increasing interest over the past years. As the number of computational models of brain functions is increasing, we chose to address reproducibility using four previously published computational models of astrocyte excitability as an example. Although not conventionally taken into account when modeling neuronal systems, astrocytes have been shown to take part in a variety of in vitro and in vivo phenomena including synaptic transmission. Two of the selected astrocyte models describe spontaneous calcium excitability, and the other two neurotransmitter-evoked calcium excitability. We specifically addressed how well the original simulation results can be reproduced with a reimplementation of the models. Additionally, we studied how well the selected models can be reused and whether they are comparable in other stimulation conditions and research settings. Unexpectedly, we found out that three of the model publications did not give all the necessary information required to reimplement the models. In addition, we were able to reproduce the original results of only one of the models completely based on the information given in the original publications and in the errata. We actually found errors in the equations provided by two of the model publications; after modifying the equations accordingly, the original results were reproduced more accurately. Even though the selected models were developed to describe the same biological event, namely astrocyte calcium excitability, the models behaved quite differently compared to one another. Our findings on a specific set of published astrocyte models stress the importance of proper validation of the models against experimental wet-lab data from astrocytes as well as the careful review process of models. A variety of aspects of model development could be improved, including the presentation of models in publications and databases. Specifically, all necessary mathematical equations, as well as parameter values, initial values of variables, and stimuli used should be given precisely for successful reproduction of scientific results.

Feedback control stabilization of critical dynamics via resource transport on multilayer networks: How glia enable learning dynamics in the brain

Learning and memory are acquired through long-lasting changes in synapses. In the simplest models, such synaptic potentiation typically leads to runaway excitation, but in reality there must exist processes that robustly preserve overall stability of the neural system dynamics. How is this accomplished? Various approaches to this basic question have been considered. Here we propose a particularly compelling and natural mechanism for preserving stability of learning neural systems. This mechanism is based on the global processes by which metabolic resources are distributed to the neurons by glial cells. Specifically, we introduce and study a model composed of two interacting networks: a model neural network interconnected by synapses that undergo spike-timing-dependent plasticity; and a model glial network interconnected by gap junctions that diffusively transport metabolic resources among the glia and, ultimately, to neural synapses where they are consumed. Our main result is that the biophysical constraints imposed by diffusive transport of metabolic resources through the glial network can prevent runaway growth of synaptic strength, both during ongoing activity and during learning. Our findings suggest a previously unappreciated role for glial transport of metabolites in the feedback control stabilization of neural network dynamics during learning.

Astrocytes regulate heterogeneity of presynaptic strengths in hippocampal networks

Dendrites are neuronal structures specialized for receiving and processing information through their many synaptic inputs. How input strengths are modified across dendrites in ways that are crucial for synaptic integration and plasticity remains unclear. We examined in single hippocampal neurons the mechanism of heterosynaptic interactions and the heterogeneity of synaptic strengths of pyramidal cell inputs. Heterosynaptic presynaptic plasticity that counterbalances input strengths requires N-methyl-d-aspartate receptors (NMDARs) and astrocytes. Importantly, this mechanism is shared with the mechanism for maintaining highly heterogeneous basal presynaptic strengths, which requires astrocyte Ca(2+) signaling involving NMDAR activation, astrocyte membrane depolarization, and L-type Ca(2+) channels. Intracellular infusion of NMDARs or Ca(2+)-channel blockers into astrocytes, conditionally ablating the GluN1 NMDAR subunit, or optogenetically hyperpolarizing astrocytes with archaerhodopsin promotes homogenization of convergent presynaptic inputs. Our findings support the presence of an astrocyte-dependent cellular mechanism that enhances the heterogeneity of presynaptic strengths of convergent connections, which may help boost the computational power of dendrites.

Modulation of Synaptic Plasticity by Glutamatergic Gliotransmission: A Modeling Study

Glutamatergic gliotransmission, that is, the release of glutamate from perisynaptic astrocyte processes in an activity-dependent manner, has emerged as a potentially crucial signaling pathway for regulation of synaptic plasticity, yet its modes of expression and function in vivo remain unclear. Here, we focus on two experimentally well-identified gliotransmitter pathways, (i) modulations of synaptic release and (ii) postsynaptic slow inward currents mediated by glutamate released from astrocytes, and investigate their possible functional relevance on synaptic plasticity in a biophysical model of an astrocyte-regulated synapse. Our model predicts that both pathways could profoundly affect both short- and long-term plasticity. In particular, activity-dependent glutamate release from astrocytes could dramatically change spike-timing-dependent plasticity, turning potentiation into depression (and vice versa) for the same induction protocol.

Roles of Presynaptic NMDA Receptors in Neurotransmission and Plasticity

Presynaptic NMDA receptors (preNMDARs) play pivotal roles in excitatory neurotransmission and synaptic plasticity. They facilitate presynaptic neurotransmitter release and modulate mechanisms controlling synaptic maturation and plasticity during formative periods of brain development. There is an increasing understanding of the roles of preNMDARs in experience-dependent synaptic and circuit-specific computation. In this review we summarize the latest understanding of compartment-specific expression and function of preNMDARs, and how they contribute to synapse-specific and circuit-level information processing.

Astrocyte and Neuronal Plasticity in the Somatosensory System

Changing the whisker complement on a rodent's snout can lead to two forms of experience-dependent plasticity (EDP) in the neurons of the barrel cortex, where whiskers are somatotopically represented. One form, termed coding plasticity, concerns changes in synaptic transmission and connectivity between neurons. This is thought to underlie learning and memory processes and so adaptation to a changing environment. The second, called homeostatic plasticity, serves to maintain a restricted dynamic range of neuronal activity thus preventing its saturation or total downregulation. Current explanatory models of cortical EDP are almost exclusively neurocentric. However, in recent years, increasing evidence has emerged on the role of astrocytes in brain function, including plasticity. Indeed, astrocytes appear as necessary partners of neurons at the core of the mechanisms of coding and homeostatic plasticity recorded in neurons. In addition to neuronal plasticity, several different forms of astrocytic plasticity have recently been discovered. They extend from changes in receptor expression and dynamic changes in morphology to alteration in gliotransmitter release. It is however unclear how astrocytic plasticity contributes to the neuronal EDP. Here, we review the known and possible roles for astrocytes in the barrel cortex, including its plasticity.

Artificial Neuron–Glia Networks Learning Approach Based on Cooperative Coevolution

Artificial Neuron–Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

Conceptual Network Model From Sensory Neurons to Astrocytes of the Human Nervous System

From a single-cell animal like paramecium to vertebrates like ape, the nervous system plays an important role in responding to the variations of the environment. Compared to animals, the nervous system in the human body possesses more intricate organization and utility. The nervous system anatomy has been understood progressively, yet the explanation at the cell level regarding complete information transmission is still lacking. Along the signal pathway toward the brain, an external stimulus first activates action potentials in the sensing neuron and these electric pulses transmit along the spinal nerve or cranial nerve to the neurons in the brain. Second, calcium elevation is triggered in the branch of astrocyte at the tripartite synapse. Third, the local calcium wave expands to the entire territory of the astrocyte. Finally, the calcium wave propagates to the neighboring astrocyte via gap junction channel. In our study, we integrate the existing mathematical model and biological experiments in each step of the signal transduction to establish a conceptual network model for the human nervous system. The network is composed of four layers and the communication protocols of each layer could be adapted to entities with different characterizations. We verify our simulation results against the available biological experiments and mathematical models and provide a test case of the integrated network. As the production of conscious episode in the human nervous system is still under intense research, our model serves as a useful tool to facilitate, complement and verify current and future study in human cognition.

A framework for plasticity implementation on the SpiNNaker neural architecture

Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system.

Rising stars: modulation of brain functions by astroglial type-1 cannabinoid receptors

The type-1-cannabinoid (CB1 ) receptor is amongst the most widely expressed G protein-coupled receptors in the brain. In few decades, CB1 receptors have been shown to regulate a large array of functions from brain cell development and survival to complex cognitive processes. Understanding the cellular mechanisms underlying these functions of CB1 is complex due to the heterogeneity of the brain cell types on which the receptor is expressed. Although the large majority of CB1 receptors act on neurons, early studies pointed to a direct control of CB1 receptors over astroglial functions including brain energy supply and neuroprotection. In line with the growing concept of the tripartite synapse highlighting astrocytes as direct players in synaptic plasticity, astroglial CB1 receptor signaling recently emerged as the mediator of several forms of synaptic plasticity associated to important cognitive functions. Here, we shortly review the current knowledge on CB1 receptor-mediated astroglial functions. This functional spectrum is large and most of the mechanisms by which CB1 receptors control astrocytes, as well as their consequences in vivo, are still unknown, requiring innovative approaches to improve this new cannabinoid research field.

Mechanisms of hippocampal astrocytes mediation of spatial memory and theta rhythm by gliotransmitters and growth factors

Our knowledge about encoding and maintenance of spatial memory emphasizes the integrated functional role of the grid cells and the place cells of the hippocampus in the generation of theta rhythm in spatial memory formation. However, the role of astrocytes in these processes is often underestimated in their contribution to the required structural and functional characteristics of hippocampal neural network operative in spatial memory. We show that hippocampal astrocytes, by the secretion of gliotransmitters, such as glutamate, d-serine, and ATP and growth factors such as BDNF and by the expression of receptors and channels such as those of TNFα and aquaporin, have several diverse fuctions in spatial memory. We specifically focus on the role of astrocytes on five phases of spatial memory: (1) theta rhythm generation, (2) theta phase precession, (3) formation of spatial memory by mapping data of entorhinal grid cells into the place cells, (4) storage of spatial information, and (5) maintenance of spatial memory. Finally, by reviewing the literature, we propose specific mechanisms mentioned in the form of a hypothesis suggesting that astrocytes are important in spatial memory formation.

Astrocyte-neuron interactions: from experimental research-based models to translational medicine

In this chapter, we review the principal astrocyte functions and the interactions between neurons and astrocytes. We then address how the experimentally observed functions have been verified in computational models and review recent experimental literature on astrocyte-neuron interactions. Benefits of computational neuroscience work are highlighted through selected studies with neurons and astrocytes by analyzing the existing models qualitatively and assessing the relevance of these models to experimental data. Common strategies to mathematical modeling and computer simulation in neuroscience are summarized for the nontechnical reader. The astrocyte-neuron interactions are then further illustrated by examples of some neurological and neurodegenerative diseases, where the miscommunication between glia and neurons is found to be increasingly important.