Know thy neighbour: A normative theory of synaptic depression

Synapses exhibit an extraordinary degree of short-term malleability, with release probabilities and effective synaptic strengths changing markedly over multiple timescales. From the perspective of a fixed computational operation in a network, this seems like a most unacceptable degree of added variability. We suggest an alternative theory according to which short-term synaptic plasticity plays a normatively-justifiable role. This theory starts from the commonplace observation that the spiking of a neuron is an incomplete, digital, report of the analog quantity that contains all the critical information, namely its membrane potential. We suggest that a synapse solves the inverse problem of estimating the pre-synaptic membrane potential from the spikes it receives, acting as a recursive filter. We show that the dynamics of short-term synaptic depression closely resemble those required for optimal filtering, and that they indeed support high quality estimation. Under this account, the local postsynaptic potential and the level of synaptic resources track the (scaled) mean and variance of the estimated presynaptic membrane potential. We make experimentally testable predictions for how the statistics of subthreshold membrane potential fluctuations and the form of spiking non-linearity should be related to the properties of short-term plasticity in any particular cell type.

SynGAP isoforms exert opposing effects on synaptic strength.

Alternative promoter usage and alternative splicing enable diversification of the transcriptome. Here we demonstrate that the function of Synaptic GTPase-Activating Protein (SynGAP), a key synaptic protein, is determined by the combination of its amino-terminal sequence with its carboxy-terminal sequence. 5' rapid amplification of cDNA ends and primer extension show that different N-terminal protein sequences arise through alternative promoter usage that are regulated by synaptic activity and postnatal age. Heterogeneity in C-terminal protein sequence arises through alternative splicing. Overexpression of SynGAP α1 versus α2 C-termini-containing proteins in hippocampal neurons has opposing effects on synaptic strength, decreasing and increasing miniature excitatory synaptic currents amplitude/frequency, respectively. The magnitude of this C-terminal-dependent effect is modulated by the N-terminal peptide sequence. This is the first demonstration that activity-dependent alternative promoter usage can change the function of a synaptic protein at excitatory synapses. Furthermore, the direction and degree of synaptic modulation exerted by different protein isoforms from a single gene locus is dependent on the combination of differential promoter usage and alternative splicing.

Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks

Cortical neurons receive balanced excitatory and inhibitory synaptic currents. Such a balance could be established and maintained in an experience-dependent manner by synaptic plasticity at inhibitory synapses. We show that this mechanism provides an explanation for the sparse firing patterns observed in response to natural stimuli and fits well with a recently observed interaction of excitatory and inhibitory receptive field plasticity. The introduction of inhibitory plasticity in suitable recurrent networks provides a homeostatic mechanism that leads to asynchronous irregular network states. Further, it can accommodate synaptic memories with activity patterns that become indiscernible from the background state but can be reactivated by external stimuli. Our results suggest an essential role of inhibitory plasticity in the formation and maintenance of functional cortical circuitry.

Single-electron tunneling depressing synapse for cellular neural networks

In this paper, a cellular neural network with depressing synapses for contrast-invariant pattern classification and synchrony detection is presented, starting from the impulse model of the single-electron tunneling junction. The results of the impulse model and the network are simulated using simulation program with integrated circuit emphasis (SPICE). It is demonstrated that depressing synapses should be an important candidate of robust systems since they exhibit a rapid depression of excitatory postsynaptic potentials for successive presynaptic spikes.

Nanoelectronic Circuit Architectures Based on Single-Electron Turnstiles

Single-electron devices (SEDs) have ultra-low power dissipation and high integration density, which make them promising candidates as basic circuit elements of the next generation VLSI circuits. In this paper, we propose two novel circuit single-electron architectures: the single-electron simulated annealing algorithm (SAA) circuit and the single-electron cellular neural network (CNN). We used the MOSFET-based single-electron turnstile [1] as the basic circuit element. The SAA circuit consists of the voltage-controlled single-electron random number generator [2] and the single-electron multiple-valued memories (SEMVs) [3]. The random-number generation and variable variations in SAA are easily achieved by transferring electrons using the single-electron turnstile. The CNN circuit used the floating-gate single-electron turnstile as the neural synapses, and the number of electrons is used to represent the cells states. These novel circuits are promising in future nanoscale integrated circuits.

PLCß介导的钙调腺苷酸环化酶在突触可塑性相关基因转录中的作用和FE65对海马依赖学习及LTP的调节

Gene regulation is required for activity-dependent changes in synaptic plasticity and remodeling. The metabotropic glutamate receptors (mGluRs) contribute to different brain functions, including learning/memory, mental disorders, drug addiction, and persistent pain in the CNS. We found that Gp I mGluRs activate PLCß through Gq and then lead to activation of several calcium-dependent signaling pathways, including ERK, which play an important role in gene transcription. These findings support a calcium-dependent role for Gq in release of Calcium and activation of calcium-stimulated adenylyl cyclases I in activity-dependent transcription in response to application of group I metabotropic glutamate receptors agonist and may provide insights into group I mGluRs-dependent synaptic plasticity through MAP kinases signaling. Moreover, the present study investigated the transcription-dependent changes of Arc in response to the activation of group I mGluRs and suggested the central role of ERK1/2 in group I mGluR-mediated Arc transcription. Further, we selected APP-interaction protein FE65 to investigate the mechanism of transcription-related process in synaptic plasticity. FE65 is expressed predominantly in the brain, and interacts with the C-terminal domain of β-amyloid precursor protein (APP). We examined hippocampus-dependent memory and in vivo long-term potentiation (LTP) at the CA1 synapses with the isoform-specific FE65 knock-out (p97FE65-/-) mice. p97FE65 knock-out mice showed impaired short-term memory for both TDPA and CFC when tested 10min after training, which is transcription-independent. Consistently, at the Schaffer collateral-CA1 synapses, p97FE65 knock-out mice showed defective early phase LTP. These results demonstrate novel roles of FE65 in synaptic plasticity, acquisition, and retention for certain forms of memory formation.

Doença de Alzheimer e Periodontite

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

A Dopamine-Acetylcholine Cascade: Simulating Learned and Lesion-Induced Behavior ff Striatal Cholinergic Interneurons

The "teaching signal" that modulates reinforcement learning at cortico-striatal synapses may be a sequence composed of an adaptively scaled DA burst, a brief ACh burst, and a scaled ACh pause. Such an interpretation is consistent with recent data on cholinergic interneurons of the striatum are tonically active neurons (TANs) that respond with characteristic pauses to novel events and to appetitive and aversive conditioned stimuli. Fluctuations in acetylcholine release by TANs modulate performance- and learning- related dynamics in the striatum. Whereas tonic activity emerges from intrinsic properties of these neurons, glutamatergic inputs from thalamic centromedian-parafascicular nuclei, and dopaminergic inputs from midbrain are required for the generation of pause responses. No prior computational models encompass both intrinsic and synaptically-gated dynamics. We present a mathematical model that robustly accounts for behavior-related electrophysiological properties of TANs in terms of their intrinsic physiological properties and known afferents. In the model balanced intrinsic hyperpolarizing and depolarizing currents engender tonic firing, and glutamatergic inputs from thalamus (and cortex) both directly excite and indirectly inhibit TANs. If the latter inhibition, probably mediated by GABAergic NOS interneurons, exceeds a threshold, its effect is amplified by a KIR current to generate a prolongued pause. In the model, the intrinsic mechanisms and external inputs are both modulated by learning-dependent dopamine (DA) signals and our simulations revealed that many learning-dependent behaviors of TANs are explicable without recourse to learning-dependent changes in synapses onto TANs.

KInNeSS: A Modular Framework for Computational Neuroscience

Making use of very detailed neurophysiological, anatomical, and behavioral data to build biological-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalabiltiy, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multu-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions of ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further developement of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effecitively collaborate using a modern neural simulation platform.

A Local Circuit Model of Learned Straitial and Dopamine Cell Responses under Probabilistic Schedules of Reward

Before choosing, it helps to know both the expected value signaled by a predictive cue and the associated uncertainty that the reward will be forthcoming. Recently, Fiorillo et al. (2003) found the dopamine (DA) neurons of the SNc exhibit sustained responses related to the uncertainty that a cure will be followed by reward, in addition to phasic responses related to reward prediction errors (RPEs). This suggests that cue-dependent anticipations of the timing, magnitude, and uncertainty of rewards are learned and reflected in components of the DA signals broadcast by SNc neurons. What is the minimal local circuit model that can explain such multifaceted reward-related learning? A new computational model shows how learned uncertainty responses emerge robustly on single trial along with phasic RPE responses, such that both types of DA responses exhibit the empirically observed dependence on conditional probability, expected value of reward, and time since onset of the reward-predicting cue. The model includes three major pathways for computing: immediate expected values of cures, timed predictions of reward magnitudes (and RPEs), and the uncertainty associated with these predictions. The first two model pathways refine those previously modeled by Brown et al. (1999). A third, newly modeled, pathway is formed by medium spiny projection neurons (MSPNs) of the matrix compartment of the striatum, whose axons co-release GABA and a neuropeptide, substance P, both at synapses with GABAergic neurons in the SNr and with the dendrites (in SNr) of DA neurons whose somas are in ventral SNc. Co-release enables efficient computation of sustained DA uncertainty responses that are a non-monotonic function of the conditonal probability that a reward will follow the cue. The new model's incorporation of a striatal microcircuit allowed it to reveals that variability in striatal cholinergic transmission can explain observed difference, between monkeys, in the amplitutude of the non-monotonic uncertainty function. Involvement of matriceal MSPNs and striatal cholinergic transmission implpies a relation between uncertainty in the cue-reward contigency and action-selection functions of the basal ganglia. The model synthesizes anatomical, electrophysiological and behavioral data regarding the midbrain DA system in a novel way, by relating the ability to compute uncertainty, in parallel with other aspects of reward contingencies, to the unique distribution of SP inputs in ventral SN.

KInNeSS: A Modular Framework for Computational Neuroscience

Making use of very detailed neurophysiological, anatomical, and behavioral data to build biologically-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalability, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multi-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions or ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further development of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effectively collaborate using a modern neural simulation platform.

Simulating Effects of Learning and Lesions with a Model of Intrinsic and Synaptically Gated Responses of Striatal Cholinergic Interneurons

The giant cholinergic interneurons of the striatum are tonically active neurons (TANs) that respond with characteristic pauses to novel events and to appetitive and aversive conditioned stimuli. Fluctuations in acetylcholine release by TANs modulate performance- and learning-related dynamics in the striatum. Whereas tonic activity emerges from intrinsic properties of these neurons, glutamatergic inputs from thalamic centromedian-parafascicular nuclei, and dopaminergic inputs from midbrain, are required for the generation of pause responses. No prior computational models encompass both intrinsic and synaptically-gated dynamics. We present a mathematical model that robustly accounts for behavior-related electrophysiological properties of TANs in terms of their intrinsic physiological properties and known afferents. In the model, balanced intrinsic hyperpolarizing and depolarizing currents engender tonic firing, and glutamatergic inputs from thalamus (and cortex) both directly excite and indirectly inhibit TANs. If the latter inhibition, presumably mediated by GABAergic interneurons, exceeds a threshold, its effect is amplified by a KIR current to generate a prolonged pause. In the model, the intrinsic mechanisms and external inputs are both modulated by learning-dependent dopamine (DA) signals and our simulations revealed that many learning-dependent behaviors of TANs are explicable without recourse to learning-dependent changes in synapses onto TANs. The "teaching signal" that modulates reinforcement learning at cortico-striatal synapses may be a sequence composed of an adaptively scaled DA burst, a brief ACh burst, and a scaled ACh pause. Such an interpretation is consistent with recent data on cholinergic control of LTD of cortical synapses onto striatal spiny projection neurons.

Investigations into the cellular and molecular changes in the amygdala in models of temporal lobe epilepsy and maternal immune activation

The amygdala is a limbic structure that is involved in many of our emotions and processing of these emotions such as fear, anger and pleasure. Conditions such as anxiety, autism, and also epilepsy, have been linked to abnormal functioning of the amygdala, owing to improper neurodevelopment or damage. This thesis investigated the cellular and molecular changes in the amygdala in models of temporal lobe epilepsy (TLE) and maternal immune activation (MIA). The kainic acid (KA) model of temporal lobe epilepsy (TLE) was used to induce Ammon’s-horn sclerosis (AHS) and to investigate behavioural and cytoarchitectural changes that occur in the amygdala related to Neuropeptide Y1 receptor expression. Results showed that KA-injected animals showed increased anxiety-like behaviours and displayed histopathological hallmarks of AHS including CA1 ablation, granule cell dispersion, volume reduction and astrogliosis. Amygdalar volume and neuronal loss was observed in the ipsilateral nuclei which was accompanied by astrogliosis. In addition, a decrease in Y1 receptor expressing cells in the ipsilateral CA1 and CA3 sectors of the hippocampus, ipsi- and contralateral granule cell layer of the dentate gyrus and ipsilateral central nucleus of the amygdala was found, consistent with a reduction in Y1 receptor protein levels. The results suggest that plastic changes in hippocampal and/or amygdalar Y1 receptor expression may negatively impact anxiety levels. Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the brain and tight regulation and appropriate control of GABA is vital for neurochemical homeostasis. GABA transporter-1 (GAT-1) is abundantly expressed by neurones and astrocytes and plays a key role in GABA reuptake and regulation. Imbalance in GABA homeostasis has been implicated in epilepsy with GAT-1 being an attractive pharmacological target. Electron microscopy was used to examine the distribution, expression and morphology of GAT-1 expressing structures in the amygdala of the TLE model. Results suggest that GAT-1 was preferentially expressed on putative axon terminals over astrocytic processes in this TLE model. Myelin integrity was examined and results suggested that in the TLE model myelinated fibres were damaged in comparison to controls. Synaptic morphology was studied and results suggested that asymmetric (excitatory) synapses occurred more frequently than symmetric (inhibitory) synapses in the TLE model in comparison to controls. This study illustrated that the amygdala undergoes ultrastructural alterations in this TLE model. Maternal immune activation (MIA) is a risk factor for neurodevelopmental disorders such as autism, schizophrenia and also epilepsy. MIA was induced at a critical window of amygdalar development at E12 using bacterial mimetic lipopolysaccharide (LPS). Results showed that MIA activates cytokine, toll-like receptor and chemokine expression in the fetal brain that is prolonged in the postnatal amygdala. Inflammation elicited by MIA may prime the fetal brain for alterations seen in the glial environment and this in turn have deleterious effects on neuronal populations as seen in the amygdala at P14. These findings may suggest that MIA induced during amygdalar development may predispose offspring to amygdalar related disorders such as heightened anxiety, fear impairment and also neurodevelopmental disorders.

Astrocytes refine cortical connectivity at dendritic spines.

During cortical synaptic development, thalamic axons must establish synaptic connections despite the presence of the more abundant intracortical projections. How thalamocortical synapses are formed and maintained in this competitive environment is unknown. Here, we show that astrocyte-secreted protein hevin is required for normal thalamocortical synaptic connectivity in the mouse cortex. Absence of hevin results in a profound, long-lasting reduction in thalamocortical synapses accompanied by a transient increase in intracortical excitatory connections. Three-dimensional reconstructions of cortical neurons from serial section electron microscopy (ssEM) revealed that, during early postnatal development, dendritic spines often receive multiple excitatory inputs. Immuno-EM and confocal analyses revealed that majority of the spines with multiple excitatory contacts (SMECs) receive simultaneous thalamic and cortical inputs. Proportion of SMECs diminishes as the brain develops, but SMECs remain abundant in Hevin-null mice. These findings reveal that, through secretion of hevin, astrocytes control an important developmental synaptic refinement process at dendritic spines.

Huntingtin is required for normal excitatory synapse development in cortical and striatal circuits.

Huntington's disease (HD) is a neurodegenerative disease caused by the expansion of a poly-glutamine (poly-Q) stretch in the huntingtin (Htt) protein. Gain-of-function effects of mutant Htt have been extensively investigated as the major driver of neurodegeneration in HD. However, loss-of-function effects of poly-Q mutations recently emerged as potential drivers of disease pathophysiology. Early synaptic problems in the excitatory cortical and striatal connections have been reported in HD, but the role of Htt protein in synaptic connectivity was unknown. Therefore, we investigated the role of Htt in synaptic connectivity in vivo by conditionally silencing Htt in the developing mouse cortex. When cortical Htt function was silenced, cortical and striatal excitatory synapses formed and matured at an accelerated pace through postnatal day 21 (P21). This exuberant synaptic connectivity was lost over time in the cortex, resulting in the deterioration of synapses by 5 weeks. Synaptic decline in the cortex was accompanied with layer- and region-specific reactive gliosis without cell loss. To determine whether the disease-causing poly-Q mutation in Htt affects synapse development, we next investigated the synaptic connectivity in a full-length knock-in mouse model of HD, the zQ175 mouse. Similar to the cortical conditional knock-outs, we found excessive excitatory synapse formation and maturation in the cortices of P21 zQ175, which was lost by 5 weeks. Together, our findings reveal that cortical Htt is required for the correct establishment of cortical and striatal excitatory circuits, and this function of Htt is lost when the mutant Htt is present.