Mechanisms generating the time course of dual component excitatory synaptic currents recorded in hippocampal slices

A fast model of voltage-dependent NMDA receptors

NMDA receptors are among the crucial elements of central nervous system models. Recent studies show that both conductance and kinetics of these receptors are changing voltage-dependently in some parts of the brain. Therefore, several models have been introduced to simulate their current. However, on the one hand, kinetic models-which are able to simulate these voltage-dependent phenomena-are computationally expensive for modeling of large neural networks. On the other hand, classic exponential models, which are computationally less expensive, are not able to simulate the voltage-dependency of these receptors, accurately. In this study, we have modified these classic models to endow them with the voltage-dependent conductance and time constants. Temperature sensitivity and desensitization of these receptors are also taken into account. We show that, it is possible to simulate the most important physiological aspects of NMDA receptor's behavior using only three to four differential equations, which is significantly smaller than the previous kinetic models. Consequently, it seems that our model is both fast and physiologically plausible and therefore is a suitable candidate for the modeling of large neural networks.

A large-scale model of the functioning brain

A central challenge for cognitive and systems neuroscience is to relate the incredibly complex behavior of animals to the equally complex activity of their brains. Recently described, large-scale neural models have not bridged this gap between neural activity and biological function. In this work, we present a 2.5-million-neuron model of the brain (called "Spaun") that bridges this gap by exhibiting many different behaviors. The model is presented only with visual image sequences, and it draws all of its responses with a physically modeled arm. Although simplified, the model captures many aspects of neuroanatomy, neurophysiology, and psychological behavior, which we demonstrate via eight diverse tasks.

Thinking outside the cleft to understand synaptic activity: contribution of the cystine-glutamate antiporter (System xc-) to normal and pathological glutamatergic signaling

System x(c)(-) represents an intriguing target in attempts to understand the pathological states of the central nervous system. Also called a cystine-glutamate antiporter, system x(c)(-) typically functions by exchanging one molecule of extracellular cystine for one molecule of intracellular glutamate. Nonvesicular glutamate released during cystine-glutamate exchange activates extrasynaptic glutamate receptors in a manner that shapes synaptic activity and plasticity. These findings contribute to the intriguing possibility that extracellular glutamate is regulated by a complex network of release and reuptake mechanisms, many of which are unique to glutamate and rarely depicted in models of excitatory signaling. Because system x(c)(-) is often expressed on non-neuronal cells, the study of cystine-glutamate exchange may advance the emerging viewpoint that glia are active contributors to information processing in the brain. It is noteworthy that system x(c)(-) is at the interface between excitatory signaling and oxidative stress, because the uptake of cystine that results from cystine-glutamate exchange is critical in maintaining the levels of glutathione, a critical antioxidant. As a result of these dual functions, system x(c)(-) has been implicated in a wide array of central nervous system diseases ranging from addiction to neurodegenerative disorders to schizophrenia. In the current review, we briefly discuss the major cellular components that regulate glutamate homeostasis, including glutamate release by system x(c)(-). This is followed by an in-depth discussion of system x(c)(-) as it relates to glutamate release, cystine transport, and glutathione synthesis. Finally, the role of system x(c)(-) is surveyed across a number of psychiatric and neurodegenerative disorders.

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity.

Simulation of postsynaptic glutamate receptors reveals critical features of glutamatergic transmission

Activation of several subtypes of glutamate receptors contributes to changes in postsynaptic calcium concentration at hippocampal synapses, resulting in various types of changes in synaptic strength. Thus, while activation of NMDA receptors has been shown to be critical for long-term potentiation (LTP) and long term depression (LTD) of synaptic transmission, activation of metabotropic glutamate receptors (mGluRs) has been linked to either LTP or LTD. While it is generally admitted that dynamic changes in postsynaptic calcium concentration represent the critical elements to determine the direction and amplitude of the changes in synaptic strength, it has been difficult to quantitatively estimate the relative contribution of the different types of glutamate receptors to these changes under different experimental conditions. Here we present a detailed model of a postsynaptic glutamatergic synapse that incorporates ionotropic and mGluR type I receptors, and we use this model to determine the role of the different receptors to the dynamics of postsynaptic calcium with different patterns of presynaptic activation. Our modeling framework includes glutamate vesicular release and diffusion in the cleft and a glutamate transporter that modulates extracellular glutamate concentration. Our results indicate that the contribution of mGluRs to changes in postsynaptic calcium concentration is minimal under basal stimulation conditions and becomes apparent only at high frequency of stimulation. Furthermore, the location of mGluRs in the postsynaptic membrane is also a critical factor, as activation of distant receptors contributes significantly less to calcium dynamics than more centrally located ones. These results confirm the important role of glutamate transporters and of the localization of mGluRs in postsynaptic sites in their signaling properties, and further strengthen the notion that mGluR activation significantly contributes to postsynaptic calcium dynamics only following high-frequency stimulation. They also provide a new tool to analyze the interactions between metabotropic and ionotropic glutamate receptors.

Cholinergic control of cortical network interactions enables feedback-mediated attentional modulation

Attention increases our ability to detect behaviorally relevant stimuli. At the neuronal level this is supported by increased firing rates of neurons representing the attended object. In primary visual cortex an attention-mediated activity increase depends on the presence of the neuromodulator acetylcholine. Using a spiking network model of visual cortex we have investigated how acetylcholine interacts with biased feedback to enable attentional processing. Although acetylcholine affects cortical processing in a multitude of manners, we restricted our analysis to four of its main established actions. These were (i) a reduction in firing rate adaptation by reduction in M-currents (muscarinic), (ii) an increase in thalamocortical synaptic efficacy by nicotinic presynaptic receptors, (iii) a reduction in lateral interactions by muscarinic presynaptic receptors, and (iv) an increase in inhibitory drive by muscarinic receptors located on inhibitory interneurons. We found that acetylcholine contributes to feedback-mediated attentional modulation, mostly by reducing intracortical interactions and also to some extent by increasing the inhibitory drive. These findings help explain why acetylcholine is necessary for top-down-driven attentional modulation, and suggest a close interdependence of cholinergic and feedback drive in mediating cognitive function.

Spatiotemporal characteristics of synaptic EPSP summation on the dendritic trees of hippocampal CA1 pyramidal neurons as revealed by laser uncaging stimulation

Synaptic strength is modified by the temporal coincidence of synaptic inputs without back-propagating action potentials (BPAPs) in CA1 pyramidal neurons. In order to clarify the interactive mechanisms of associative long-term potentiation (LTP) without BPAPs, local paired stimuli were applied to the dendrites using high-speed laser uncaging stimulation equipment. When the spatial distance between the paired stimuli was <10 micrometer, nonlinear amplification in excitatory postsynaptic potential summation was observed. In the time window from -20 to 20 ms, supralinear amplification was observed. Supralinear amplification was modulated by antagonist of voltage-gated Na(+)/Ca(2+) channels and NMDA-type glutamate receptors. These results are closely related to the spatiotemporal-characteristics of associative LTP without BPAPs. This study proposes an essential aspect of dendritic information processing.

Prediction of Decisions from Noise in the Brain before the Evidence is Provided

Can decisions be predicted from brain activity? It is frequently difficult in neuroimaging studies to determine this, because it is not easy to establish when the decision has been taken. In a rigorous approach to this issue, we show that in a neurally plausible integrate-and-fire attractor-based model of decision-making, the noise generated by the randomness in the spiking times of neurons can be used to predict a decision for 0.5 s or more before the decision cues are applied. The ongoing noise at the time the decision cues are applied influences which decision will be taken. It is possible to predict on a single trial to more than 68% correct which of two decisions will be taken. The prediction is made from the spontaneous firing before the decision cues are applied in the two populations of neurons that represent the decisions. Thus decisions can be partly predicted even before the decision cues are applied, due to noise in the decision-making process. This analysis has interesting implications for decision-making and free will, for it shows that random neuronal firing times can influence a decision before the evidence for the decision has been provided.

Contribution of astrocytic glutamate and GABA uptake to corticostriatal information processing

The astrocytes, active elements of the tripartite synapse, remove most of the neurotransmitter that spills over the synaptic cleft. Neurotransmitter uptake operated by astrocytes contributes to the strength and timing of synaptic inputs. The striatum, the main input nucleus of basal ganglia, extracts pertinent cortical signals from the background noise and relays cortical information toward basal ganglia output structures. We investigated the role of striatal astrocytic uptake in the shaping of corticostriatal transmission.We performed dual patch-clamp recordings of striatal output neuron (the medium-sized spiny neurons, MSNs)–astrocyte pairs while stimulating the somatosensory cortex. Cortical activity evoked robust synaptically activated transporter-mediated currents (STCs) in 78% of the recorded astrocytes. STCs originated equally from the activities of glutamate transporters and GABA transporters (GATs). Astrocytic STCs reflected here a presynaptic release of neurotransmitters. STCs displayed a large magnitude associated with fast kinetics, denoting an efficient neurotransmitter clearance at the corticostriatal pathway. Inhibition of glutamate transporters type-1 (GLT-1) and GATs decreased the corticostriatal synaptic transmission, through, respectively, desensitization of AMPA receptors and activation of GABAA receptor. STCs displayed a bidirectional short-term plasticity (facilitation for paired-pulse intervals less than 100 ms and depression up to 1 s).We report a genuine facilitation of STCs for high-frequency cortical activity, which could strengthen the detection properties of cortical activity operated by MSNs. MSN EPSCs showed a triphasic short-term plasticity, which was modified by the blockade of GLT-1 or GATs. We show here that neurotransmitter uptake by astrocytes plays a key role in the corticostriatal information processing.

Thermally active TRPV1 tonically drives central spontaneous glutamate release

Central synapses spontaneously release neurotransmitter at low rates. In the brainstem, cranial visceral afferent terminals in caudal solitary tract nucleus (NTS) display pronounced, activity-dependent, asynchronous release of glutamate and this extra release depends on TRPV1 receptors (TRPV1+). Asynchronous release is absent for afferents lacking TRPV1 (TRPV1-) and resting EPSC frequency was greater in TRPV1+. Here, we studied this basal activity difference by assessing thermal sensitivity of spontaneous and miniature synaptic events in TRPV1+ and TRPV1- second-order NTS neurons. The spontaneous EPSC rate decreased when temperature was decreased, increased steeply between 30 and 42°C only in TRPV1+ neurons, and was calcium-dependent. TRPV1-specific antagonist SB366791, but not TTX, strongly attenuated thermal responses. Temperature changes failed to alter EPSC frequency in TRPV1- neurons. EPSC amplitudes and decay kinetics changed little with temperature. IPSCs in these second-order NTS neurons were unaltered by temperature. Such results suggest that activated, presynaptic TRPV1+ receptors trigger continuous resting release of glutamate vesicles at physiological temperatures only in capsaicin-responsive terminals. In mechanically isolated individual neurons harvested from medial NTS, increases in temperature increased the rate of glutamate release only in TRPV1+ neurons, whereas IPSC rates were unaffected. Cadmium failed to block thermal increases in glutamate release, suggesting that calcium entry through TRPV1 channels may trigger glutamate release independently of voltage-activated calcium channels. Together, our findings indicate a new form of afferent signaling in which TRPV1 channels within central terminals of peripheral afferents tonically generate glutamate release in NTS at 37°C in the absence of afferent action potentials.

Path integration of head direction: updating a packet of neural activity at the correct speed using neuronal time constants

A key question in understanding the neural basis of path integration is how individual, spatially responsive, neurons may self-organize into networks that can, through learning, integrate velocity signals to update a continuous representation of location within an environment. It is of vital importance that this internal representation of position is updated at the correct speed, and in real time, to accurately reflect the motion of the animal. In this article, we present a biologically plausible model of velocity path integration of head direction that can solve this problem using neuronal time constants to effect natural time delays, over which associations can be learned through associative Hebbian learning rules. The model comprises a linked continuous attractor network and competitive network. In simulation, we show that the same model is able to learn two different speeds of rotation when implemented with two different values for the time constant, and without the need to alter any other model parameters. The proposed model could be extended to path integration of place in the environment, and path integration of spatial view.

Realistic modelling of receptor activation in hippocampal excitatory synapses: analysis of multivesicular release, release location, temperature and synaptic cross-talk

Chemically mediated synaptic transmission results from fusion of synaptic vesicles with the presynaptic plasma membrane, subsequent release of the vesicular content into the cleft and binding to postsynaptic receptors. Previous modelling studies of excitatory neurotransmitter glutamate were based on simplified geometries failing to account for the biologically realistic synaptic environment, in particular, the presence of astrocytes, the geometry of extracellular space, and the neurotransmitter uptake mechanism. Using 3-dimensional reconstructions of hippocampal glutamatergic synapses including the surrounding astrocytic processes we have developed a biologically realistic model to analyse receptor activation in different conditions. We used the finite element method to simulate glutamate release, analyse glutamate diffusion following single and multiple vesicle release and binding at the postsynaptic site to AMPA and NMDA receptors. We demonstrate that: (1) the transmitter diffusion is highly temperature-sensitive; (2) release conditions and geometry more specifically affect AMPARs than NMDARs; (3) the sensitivities of AMPARs and NMDARs to simultaneous vesicular release are different; (4) in the case of multivesicle neurotransmitter release with variable delays, the binding of glutamate to AMPARs is additive up to 1 ms after the release, then becomes independent, but to NMDARs the binding is additive up to 33 ms; (5) the number of AMPARs varies more than the number of NMDRs in response to the input firing patterns; (6) the presence of astrocytes effectively blocks synaptic cross-talk; and (7) synaptic cross-talk, mediated by NMDARs but not AMPARs, is only possible after quasi-simultaneous multivesicular release at physiological temperature (35 degrees C) without intervening astrocytes, but not at 25 degrees C. Our simulations demonstrate the importance of temperature and ultrastructural synaptic environment in synaptic transmission and synaptic cross-talk.

An intrinsic neuronal oscillator underlies dopaminergic neuron bursting

Dopaminergic neurons of the ventral midbrain fire high-frequency bursts when animals are presented with unexpected rewards, or stimuli that predict reward. To identify the afferents that can initiate bursting and establish therapeutic strategies for diseases affected by altered bursting, a mechanistic understanding of bursting is essential. Our results show that bursting is initiated by a specific interaction between the voltage sensitivity of NMDA receptors and voltage-gated ion channels that results in the activation of an intrinsic, action potential-independent, high-frequency membrane potential oscillation. We further show that the NMDA receptor is uniquely suited for this because of the rapid kinetics and voltage dependence imparted to it by Mg(2+) ion block and unblock. This mechanism explains the discrete nature of bursting in dopaminergic cells and demonstrates how synaptic signals may be reshaped by local intrinsic properties of a neuron before influencing action potential generation.

Optimal performance in a countermanding saccade task

Countermanding an action is a fundamental form of cognitive control. In a saccade-countermanding task, subjects are instructed that, if a stop signal appears shortly after a target, they are to maintain fixation rather than to make a saccade to the target. In recent years, recordings in the frontal eye fields and superior colliculus of behaving non-human primates have found correlates of such countermanding behavior in movement and fixation neurons. In this work, we extend a previous neural network model of countermanding to account for the high pre-target activity of fixation neurons. We propose that this activity reflects the functioning of control mechanisms responsible for optimizing performance. We demonstrate, using computer simulations and mathematical analysis, that pre-target fixation neuronal activity supports countermanding behavior that maximizes reward rate as a function of the stop signal delay, fraction of stop signal trials, intertrial interval, duration of timeout, and relative reward value. We propose experiments to test these predictions regarding optimal behavior.

A unified and quantitative network model for spatial attention in area V4

Electrophysiological experiments in visual area V4 have shown that spatial attention induces a number of neural activity modulations. Depending on the stimulus characteristics, neuronal firing rates either increase or decrease. At the network level, the oscillatory activity in the gamma frequency range (30-70Hz) is enhanced by attention. Recently, pyramidal neurons and interneurons have been surmised to respond differently, but have been shown to have both a high firing variability. These results raise the question of the nature of the modulatory attentional input to V4 and of the network mechanisms that lead to the emergence of these different modulations. Here, we propose a biophysical network model of V4. We first reproduce the neural activity observed in response to different stimulus configurations. We found that different forms of the attentional input are possible, and that this fact could explain the observed multiplicity of modulations when stimulus contrast is varied. Our model offers a unified and quantitative picture, from which the cognitive roles played by these attentional modulations can be investigated.

Temperature dependence of N-methyl-D-aspartate receptor channels and N-methyl-D-aspartate receptor excitatory postsynaptic currents

N-methyl-d-aspartate (NMDA) receptors (NMDARs) are highly expressed in the CNS and mediate the slow component of excitatory transmission. The present study was aimed at characterizing the temperature dependence of the kinetic properties of native NMDARs, with special emphasis on the deactivation of synaptic NMDARs. We used patch-clamp recordings to study synaptic NMDARs at layer II/III pyramidal neurons of the rat cortex, recombinant GluN1/GluN2B receptors expressed in human embryonic kidney (HEK293) cells, and NMDARs in cultured hippocampal neurons. We found that time constants characterizing the deactivation of NMDAR-mediated excitatory postsynaptic currents (EPSCs) were similar to those of the deactivation of responses to a brief application of glutamate recorded under conditions of low NMDAR desensitization (whole-cell recording from cultured hippocampal neurons). In contrast, the deactivation of NMDAR-mediated responses exhibiting a high degree of desensitization (outside-out recording) was substantially faster than that of synaptic NMDA receptors. The time constants characterizing the deactivation of synaptic NMDARs and native NMDARs activated by exogenous glutamate application were only weakly temperature sensitive (Q(10)=1.7-2.2), in contrast to those of recombinant GluN1/GluN2B receptors, which are highly temperature sensitive (Q(10)=2.7-3.7). Ifenprodil reduced the amplitude of NMDAR-mediated EPSCs by approximately 50% but had no effect on the time course of deactivation. Analysis of GluN1/GluN2B responses indicated that the double exponential time course of deactivation reflects mainly agonist dissociation and receptor desensitization. We conclude that the temperature dependences of native and recombinant NMDAR are different; in addition, we contribute to a better understanding of the molecular mechanism that controls the time course of NMDAR-mediated EPSCs.

Synaptic NR2A- but not NR2B-Containing NMDA Receptors Increase with Blockade of Ionotropic Glutamate Receptors

NMDA receptors (NMDAR) are key molecules involved in physiological and pathophysiological brain processes such as plasticity and excitotoxicity. Neuronal activity regulates NMDA receptor levels in the cell membrane. However, little is known on which time scale this regulation occurs and whether the two main diheteromeric NMDA receptor subtypes in forebrain, NR1/NR2A and NR1/NR2B, are regulated in a similar fashion. As these differ considerably in their electrophysiological properties, the NR2A/NR2B ratio affects the neurons’ reaction to NMDA receptor activation. Here we provide evidence that the basal turnover rate in the cell membrane of NR2A- and NR2B-containing receptors is comparable. However, the level of the NR2A subtype in the cell membrane is highly regulated by NMDA receptor activity, resulting in a several-fold increased insertion of new receptors after blocking NMDAR for 8 h. Blocking AMPA receptors also increases the delivery of NR2A-containing receptors to the cell membrane. In contrast, the amount of NR2B-containing receptors in the cell membrane is not affected by ionotropic glutamate receptor block. Moreover, electrophysiological analysis of synaptic currents in hippocampal cultures and CA1 neurons of hippocampal slices revealed that after 8 h of NMDA receptor blockade the NMDA EPSCs increase as a result of augmented NMDA receptor-mediated currents. In conclusion, synaptic NR2A- but not NR2B-containing receptors are dynamically regulated, enabling neurons to change their NR2A/NR2B ratio within a time scale of hours.

Astrocytic dysfunction in epileptogenesis: consequence of altered potassium and glutamate homeostasis?

Focal epilepsy often develops following traumatic, ischemic, or infectious brain injury. While the electrical activity of the epileptic brain is well characterized, the mechanisms underlying epileptogenesis are poorly understood. We have recently shown that in the rat neocortex, long-lasting breakdown of the blood-brain barrier (BBB) or direct exposure of the neocortex to serum-derived albumin leads to rapid upregulation of the astrocytic marker GFAP (glial fibrillary acidic protein), followed by delayed (within 4-7 d) development of an epileptic focus. We investigated the role of astrocytes in epileptogenesis in the BBB-breakdown and albumin models of epileptogenesis. We found similar, robust changes in astrocytic gene expression in the neocortex within hours following treatment with deoxycholic acid (BBB breakdown) or albumin. These changes predict reduced clearance capacity for both extracellular glutamate and potassium. Electrophysiological recordings in vitro confirmed the reduced clearance of activity-dependent accumulation of both potassium and glutamate 24 h following exposure to albumin. We used a NEURON model to simulate the consequences of reduced astrocytic uptake of potassium and glutamate on EPSPs. The model predicted that the accumulation of glutamate is associated with frequency-dependent (>100 Hz) decreased facilitation of EPSPs, while potassium accumulation leads to frequency-dependent (10-50 Hz) and NMDA-dependent synaptic facilitation. In vitro electrophysiological recordings during epileptogenesis confirmed frequency-dependent synaptic facilitation leading to seizure-like activity. Our data indicate a transcription-mediated astrocytic transformation early during epileptogenesis. We suggest that the resulting reduction in the clearance of extracellular potassium underlies frequency-dependent neuronal hyperexcitability and network synchronization.

Mean-field modeling of the basal ganglia-thalamocortical system. I Firing rates in healthy and parkinsonian states

Parkinsonism leads to various electrophysiological changes in the basal ganglia-thalamocortical system (BGTCS), often including elevated discharge rates of the subthalamic nucleus (STN) and the output nuclei, and reduced activity of the globus pallidus external (GPe) segment. These rate changes have been explained qualitatively in terms of the direct/indirect pathway model, involving projections of distinct striatal populations to the output nuclei and GPe. Although these populations partly overlap, evidence suggests dopamine depletion differentially affects cortico-striato-pallidal connection strengths to the two pallidal segments. Dopamine loss may also decrease the striatal signal-to-noise ratio, reducing both corticostriatal coupling and striatal firing thresholds. Additionally, nigrostriatal degeneration may cause secondary changes including weakened lateral inhibition in the GPe, and mesocortical dopamine loss may decrease intracortical excitation and especially inhibition. Here a mean-field model of the BGTCS is presented with structure and parameter estimates closely based on physiology and anatomy. Changes in model rates due to the possible effects of dopamine loss listed above are compared with experiment. Our results suggest that a stronger indirect pathway, possibly combined with a weakened direct pathway, is compatible with empirical evidence. However, altered corticostriatal connection strengths are probably not solely responsible for substantially increased STN activity often found. A lower STN firing threshold, weaker intracortical inhibition, and stronger striato-GPe inhibition help explain the relatively large increase in STN rate. Reduced GPe-GPe inhibition and a lower GPe firing threshold can account for the comparatively small decrease in GPe rate frequently observed. Changes in cortex, GPe, and STN help normalize the cortical rate, also in accord with experiments. The model integrates the basal ganglia into a unified framework along with an existing thalamocortical model that already accounts for a wide range of electrophysiological phenomena. A companion paper discusses the dynamics and oscillations of this combined system.

The effects of NR2 subunit-dependent NMDA receptor kinetics on synaptic transmission and CaMKII activation

N-Methyl-D-aspartic acid (NMDA) receptors are widely expressed in the brain and are critical for many forms of synaptic plasticity. Subtypes of the NMDA receptor NR2 subunit are differentially expressed during development; in the forebrain, the NR2B receptor is dominant early in development, and later both NR2A and NR2B are expressed. In heterologous expression systems, NR2A-containing receptors open more reliably and show much faster opening and closing kinetics than do NR2B-containing receptors. However, conflicting data, showing similar open probabilities, exist for receptors expressed in neurons. Similarly, studies of synaptic plasticity have produced divergent results, with some showing that only NR2A-containing receptors can drive long-term potentiation and others showing that either subtype is capable of driving potentiation. In order to address these conflicting results as well as open questions about the number and location of functional receptors in the synapse, we constructed a Monte Carlo model of glutamate release, diffusion, and binding to NMDA receptors and of receptor opening and closing as well as a model of the activation of calcium-calmodulin kinase II, an enzyme critical for induction of synaptic plasticity, by NMDA receptor-mediated calcium influx. Our results suggest that the conflicting data concerning receptor open probabilities can be resolved, with NR2A- and NR2B-containing receptors having very different opening probabilities. They also support the conclusion that receptors containing either subtype can drive long-term potentiation. We also are able to estimate the number of functional receptors at a synapse from experimental data. Finally, in our models, the opening of NR2B-containing receptors is highly dependent on the location of the receptor relative to the site of glutamate release whereas the opening of NR2A-containing receptors is not. These results help to clarify the previous findings and suggest future experiments to address open questions concerning NMDA receptor function.

Decision making in recurrent neuronal circuits

Decision making has recently emerged as a central theme in neurophysiological studies of cognition, and experimental and computational work has led to the proposal of a cortical circuit mechanism of elemental decision computations. This mechanism depends on slow recurrent synaptic excitation balanced by fast feedback inhibition, which not only instantiates attractor states for forming categorical choices but also long transients for gradually accumulating evidence in favor of or against alternative options. Such a circuit endowed with reward-dependent synaptic plasticity is able to produce adaptive choice behavior. While decision threshold is a core concept for reaction time tasks, it can be dissociated from a general decision rule. Moreover, perceptual decisions and value-based economic choices are described within a unified framework in which probabilistic choices result from irregular neuronal activity as well as iterative interactions of a decision maker with an uncertain environment or other unpredictable decision makers in a social group.

Decreased glutamate transport enhances excitability in a rat model of cortical dysplasia

Glutamate transporters function to maintain low levels of extracellular glutamate and play an important role in synaptic transmission at many synapses. Disruption of glutamate transporter function or expression can result in increased extracellular glutamate levels. Alterations in glutamate transporter expression have been reported in human epilepsy and animal seizure models. Functional electrophysiological changes that occur when transporter expression is disrupted in chronic epilepsy models have not been examined. Here, we used a freeze-induced model of cortical dysplasia to test the role of glutamate transporters in synaptic hyperexcitability. We report that inhibiting glutamate transporters with the non-selective antagonist, DL-threo-beta-benzylozyaspartic acid (TBOA) preferentially prolongs postsynaptic currents (PSCs) and decreases the threshold for evoking epileptiform activity in lesioned compared to control cortex. The effect of inhibiting uptake is mediated primarily by the glia glutamate transporter (GLT-1) since the selective antagonist dihydrokainate (DHK) mimicked the effects of TBOA. The effect of uptake inhibition is mediated by activation of N-methyl-D-aspartate (NMDA) receptors since D-(-)-2-amino-5-phosphonovaleric acid (APV) prevents TBOA-induced effects. Neurons in lesioned cortex also have a larger tonic NMDA current. These results indicate that chronic changes in glutamate transporters and NMDA receptors contribute to hyperexcitability in cortical dysplasia.

Lexical plasticity in early bilinguals does not alter phoneme categories: I. Neurodynamical modeling

Abstract Sebastián-Gallés et al. [The influence of initial exposure on lexical representation: Comparing early and simultaneous bilinguals. Journal of Memory and Language, 52, 240-255, 2005] contrasted highly proficient early Spanish-Catalan and Catalan-Spanish bilinguals, using Catalan materials in a lexical decision task (LDT). They constructed two types of experimental pseudowords, substituting Catalan phoneme /e/ for Catalan /epsilon/, or vice versa. Catalan-dominant bilinguals showed a performance asymmetry across experimental conditions, making more mistakes for /epsilon/-->/e/ changes, than for /e/-->/epsilon/ ones. This was considered evidence of a developed acceptance of mispronounced Catalan /epsilon/-words, caused by exposure to a bilingual environment where mispronunciations by Spanish-dominant bilinguals using their /e/-category abound. Although this indicated modified or added lexical representations, an open issue is whether such lexical information also modifies phoneme categories. We address this using a biophysically realistic neurodynamic model, describing neural activity at the synaptic and spiking levels. We construct a network of pools of neurons, representing phonemic and lexical processing. Carefully analyzing the dependency of network dynamics on connection strengths, by first exploring parameter space under steady-state assumptions (mean-field scans), then running spiking simulations, we investigate the neural substrate role in a representative LDT. We also simulate a phoneme discrimination task to address whether lexical changes affect the phonemic level. We find that the same network configuration which displays asymmetry in the LDT shows equal performance discriminating the two modeled phonemes. Thus, we predicted that the Catalan-dominant bilinguals do not alter their phoneme categories, although showing signs of having stored a new word variation in the lexicon. To explore this prediction, a syllable discrimination task involving the /e/-/epsilon/ contrast was set up, using Catalan-dominants displaying performance asymmetry in a repetition of the original LDT. Discrimination task results support the prediction, showing that these subjects discriminate both categories equally well. We conclude that subjects often exposed to dialectal word variations can store these in their lexicons, without altering their phoneme representations.

Glutamate transporters: confining runaway excitation by shaping synaptic transmission

Traditionally, glutamate transporters have been viewed as membrane proteins that harness the electrochemical gradient to slowly transport glutamate from the extracellular space into glial cells. However, recent studies have shown that glutamate transporters on glial and neuronal membranes also rapidly bind released glutamate to shape synaptic transmission. In this Review, we summarize the properties of glutamate transporters that influence synaptic transmission and are subject to regulation and plasticity. We highlight how the diversity of glutamate-transporter function relates to transporter location, density and affinity.

Neural circuit dynamics underlying accumulation of time-varying evidence during perceptual decision making

How do neurons in a decision circuit integrate time-varying signals, in favor of or against alternative choice options? To address this question, we used a recurrent neural circuit model to simulate an experiment in which monkeys performed a direction-discrimination task on a visual motion stimulus. In a recent study, it was found that brief pulses of motion perturbed neural activity in the lateral intraparietal area (LIP), and exerted corresponding effects on the monkey's choices and response times. Our model reproduces the behavioral observations and replicates LIP activity which, depending on whether the direction of the pulse is the same or opposite to that of a preferred motion stimulus, increases or decreases persistently over a few hundred milliseconds. Furthermore, our model accounts for the observation that the pulse exerts a weaker influence on LIP neuronal responses when the pulse is late relative to motion stimulus onset. We show that this violation of time-shift invariance (TSI) is consistent with a recurrent circuit mechanism of time integration. We further examine time integration using two consecutive pulses of the same or opposite motion directions. The induced changes in the performance are not additive, and the second of the paired pulses is less effective than its standalone impact, a prediction that is experimentally testable. Taken together, these findings lend further support for an attractor network model of time integration in perceptual decision making.

Neuronal firing rates account for distractor effects on mnemonic accuracy in a visuo-spatial working memory task

Persistent neural activity constitutes one neuronal correlate of working memory, the ability to hold and manipulate information across time, a prerequisite for cognition. Yet, the underlying neuronal mechanisms are still elusive. Here, we design a visuo- spatial delayed-response task to identify the relationship between the cue-distractor spatial distance and mnemonic accuracy. Using a shared experimental and computational test protocol, we probe human subjects in computer experiments, and subsequently we evaluate different neural mechanisms underlying persistent activity using an in silico prefrontal network model. Five modes of action of the network were tested: weak or strong synaptic interactions, wide synaptic arborization, cellular bistability and reduced synaptic NMDA component. The five neural mechanisms and the human behavioral data, all exhibited a significant deterioration of the mnemonic accuracy with decreased spatial distance between the distractor and the cue. A subsequent computational analysis revealed that the firing rate and not the neural mechanism per se, accounted for the positive correlation between mnemonic accuracy and spatial distance. Moreover, the computational modeling predicts an inverse correlation between accuracy and distractibility. In conclusion, any pharmacological modulation, pathological condition or memory training paradigm targeting the underlying neural circuitry and altering the net population firing rate during the delay is predicted to determine the amount of influence of a visual distraction.

Spike timing and reliability in cortical pyramidal neurons: effects of EPSC kinetics, input synchronization and background noise on spike timing

In vivo studies have shown that neurons in the neocortex can generate action potentials at high temporal precision. The mechanisms controlling timing and reliability of action potential generation in neocortical neurons, however, are still poorly understood. Here we investigated the temporal precision and reliability of spike firing in cortical layer V pyramidal cells at near-threshold membrane potentials. Timing and reliability of spike responses were a function of EPSC kinetics, temporal jitter of population excitatory inputs, and of background synaptic noise. We used somatic current injection to mimic population synaptic input events and measured spike probability and spike time precision (STP), the latter defined as the time window (Δt) holding 80% of response spikes. EPSC rise and decay times were varied over the known physiological spectrum. At spike threshold level, EPSC decay time had a stronger influence on STP than rise time. Generally, STP was highest (≤2.45 ms) in response to synchronous compounds of EPSCs with fast rise and decay kinetics. Compounds with slow EPSC kinetics (decay time constants>6 ms) triggered spikes at lower temporal precision (≥6.58 ms). We found an overall linear relationship between STP and spike delay. The difference in STP between fast and slow compound EPSCs could be reduced by incrementing the amplitude of slow compound EPSCs. The introduction of a temporal jitter to compound EPSCs had a comparatively small effect on STP, with a tenfold increase in jitter resulting in only a five fold decrease in STP. In the presence of simulated synaptic background activity, precisely timed spikes could still be induced by fast EPSCs, but not by slow EPSCs.

Vesicular release of glutamate from unmyelinated axons in white matter

Directed fusion of transmitter-laden vesicles enables rapid intercellular signaling in the central nervous system and occurs at synapses within gray matter. Here we show that action potentials also induce the release of glutamate from axons in the corpus callosum, a white matter region responsible for interhemispheric communication. Callosal axons release glutamate by vesicular fusion, which induces quantal AMPA receptor-mediated currents in NG2(+) glial progenitors at anatomically distinct axo-glial synaptic junctions. Glutamate release from axons was facilitated by repetitive stimulation and could be inhibited through activation of metabotropic autoreceptors. Although NG2(+) cells form associations with nodes of Ranvier in white matter, measurements of conduction velocity indicated that unmyelinated fibers are responsible for glutamatergic signaling with NG2(+) glia. This activity-dependent secretion of glutamate was prevalent in the developing and mature mouse corpus callosum, indicating that axons within white matter both conduct action potentials and engage in rapid neuron-glia communication.

Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction

A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations.

A computational model of visual marking using an inter-connected network of spiking neurons: the spiking search over time & space model (sSoTS)

In the real world, visual information is selected over time as well as space, when we prioritise new stimuli for attention. Watson and Humphreys [Watson, D., Humphreys, G.W., 1997. Visual marking: prioritizing selection for new objects by top-down attentional inhibition of old objects. Psychological Review 104, 90-122] presented evidence that new information in search tasks is prioritised by (amongst other processes) active ignoring of old items - a process they termed visual marking. In this paper we present, for the first time, an explicit computational model of visual marking using biologically plausible activation functions. The "spiking search over time and space" model (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca(2+)] sensitive K(+) current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. We show that, when coupled with a process of active inhibition applied to old items, frequency adaptation leads to old items being de-prioritised (and new items prioritised) across time in search. Furthermore, the time course of these processes mimics the time course of the preview effect in human search. The results indicate that the sSoTS model can provide a biologically plausible account of human search over time as well as space.

Decision‐making and Weber's law: a neurophysiological model

We describe an integrate-and-fire attractor model of the decision-related activity of ventral premotor cortex (VPC) neurons during a vibrotactile frequency comparison task [Romo et al. (2004)Neuron, 41, 165-173]. Populations of neurons for each decision in a biased competition attractor network receive a bias input that depends on the firing rates of VPC neurons that code for the two vibrotactile frequencies. The firing rate of the neurons in whichever attractor wins, reflects the sign of the difference in the frequencies (Deltaf) being compared but not the absolute frequencies. However, the transition from the initial spontaneous firing state to one of the two possible attractor states depends probabilistically on the difference of the vibrotactile frequencies scaled by the base frequency. This is due to finite size noise effects related to the spiking activity in the network, and the divisive feedback inhibition implemented through inhibitory interneurons. Thus the neurophysiological basis for a psychophysical effect, Weber's Law, can be related to statistical fluctuations and divisive inhibition in an attractor decision-making network.

NMDA depresses glutamatergic synaptic transmission in the striatum through the activation of adenosine A1 receptors: evidence from knockout mice

N-methyl-D-aspartate (NMDA) receptors play several essential roles in the physiology and pathophysiology of the brain. Their activation results in long-term changes in glutamatergic synaptic transmission in several brain areas, but excessive activation of these receptors induces neurotoxicity. Some of NMDA-mediated actions are critically dependent on functional interactions with the neuromodulator adenosine. In the present study, we have examined whether pharmacological activation of NMDA receptors induces long-term changes in synaptic strength in the striatum. We found that NMDA depressed the amplitude of the field excitatory postsynaptic potential/population spike (fEPSP/PS) recorded in corticostriatal mouse brain slices in a concentration-dependent manner. Inhibition of synaptic transmission was more pronounced at room temperature (22 degrees C) than at 32 degrees C and long lasting (> 2 h) depression of the fEPSP/PS was observed only at room temperature. NMDA-induced depression of the fEPSP/PS was reduced or abolished in the presence of an A1 receptor antagonist and in A1 receptor knockout mice. In addition, exogenous application of adenosine depressed fEPSP/PS amplitude in wild-type mice, but not in A1 receptor knockout mice, in a concentration-dependent manner. Our results demonstrate that NMDA depresses synaptic transmission in a concentration- and temperature-dependent manner via release of adenosine and activation of adenosine A1 receptors.

Synaptic basis for whisker deprivation-induced synaptic depression in rat somatosensory cortex

Whisker deprivation weakens excitatory layer 4 (L4) inputs to L2/3 pyramidal cells in rat primary somatosensory (S1) cortex, which is likely to contribute to whisker map plasticity. This weakening has been proposed to represent long-term depression (LTD) induced by sensory deprivation in vivo. Here, we studied the synaptic expression mechanisms for deprivation-induced weakening of L4-L2/3 inputs and assessed its similarity to LTD, which is known to be expressed presynaptically at L4-L2/3 synapses. Whisker deprivation increased the paired pulse ratio at L4-L2/3 synapses and slowed the use-dependent block of NMDA receptor currents by MK-801 [(5S,10R)-(+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine maleate], indicating that deprivation reduced transmitter release probability at these synapses. In contrast, deprivation did not alter either miniature EPSC amplitude in L2/3 neurons or the amplitude of quantal L4-L2/3 synaptic responses measured in strontium, indicating that postsynaptic responsiveness was unchanged. In young postnatal day 12 (P12) rats, at least 4 d of deprivation were required to significantly weaken L4-L2/3 synapses. Similar weakening occurred when deprivation began at older ages (P20), when synapses are mostly mature, indicating that weakening is unlikely to represent a failure of synaptic maturation but instead represents a reduction in the strength of existing synapses. Thus, whisker deprivation weakens L4-L2/3 synapses by decreasing presynaptic function, similar to known LTD mechanisms at this synapse.

Physiological role for casein kinase 1 in glutamatergic synaptic transmission

Casein kinase 1 (CK1) is a highly conserved serine/threonine kinase, present in virtually all cell types, in which it phosphorylates a wide variety of substrates. So far, no role has been found for this ubiquitous protein kinase in the physiology of nerve cells. In the present study, we show that CK1 regulates fast synaptic transmission mediated by glutamate, the major excitatory neurotransmitter in the brain. Through the use of CK1 inhibitors, we present evidence that activation of CK1 decreases NMDA receptor activity in the striatum via a mechanism that involves activation by this kinase of protein phosphatase 1 and/or 2A and resultant increased dephosphorylation of NMDA receptors. Indeed, inhibition of CK1 increases NMDA-mediated EPSCs in medium spiny striatal neurons. This effect is associated with an increased phosphorylation of the NR1 and NR2B subunits of the NMDA receptor and is occluded by the phosphatase inhibitor okadaic acid. The mGluR1, but not mGluR5, subclass of metabotropic glutamate receptors uses CK1 to inhibit NMDA-mediated synaptic currents. These results provide the first evidence for a role of CK1 in the regulation of synaptic transmission in the brain.

Relation between single neuron and population spiking statistics and effects on network activity

To simplify theoretical analyses of neural networks, individual neurons are often modeled as Poisson processes. An implicit assumption is that even if the spiking activity of each neuron is non-Poissonian, the composite activity obtained by summing many spike trains limits to a Poisson process. Here, we show analytically and through simulations that this assumption is invalid. Moreover, we show with Fokker-Planck equations that the behavior of feedforward networks is reproduced accurately only if the tendency of neurons to fire periodically is incorporated by using colored noise whose autocorrelation has a negative component.

Cognitive flexibility and decision-making in a model of conditional visuomotor associations

Arbitrary visuomotor associations map a stimulus onto a particular response upon reinforcing rewards. Changes in the associations between stimuli and responses require the neural networks to discard the already learned mappings and build new ones. This is a key aspect of cognitive flexibility. In addition, learning within this experimental paradigm requires a trial-and-error exploration strategy of the available stimulus-response associations. A system performing this task must be able to both build up mappings for stimulus-response associations and at the same time perform non-deterministically to explore the behavioural space until it reaches certainty. We hypothesize an integrate-and-fire network model that accounts for the neurophysiological data of a conditional visuomotor association task and is able to show non-deterministic behaviour. We aim at identifying multistable attractor regimes in the network dynamics, which intrinsically enable the system to make errors and thereby to perform trial-and-error exploration. Our model combines cognitive flexibility with multistable attractors in neurodynamical systems, believed to be the basis of decision-making. If multistable attractors support the exploration of the behavioural space, then our model predicts that the brain should respond stochastically with correct or incorrect activity to visuomotor associations until it has reached certainty. This should be visible not only in the corresponding activity in the premotor area, but also in activity corresponding to other associations or even other stimuli in the prefrontal cortex.

A recurrent network mechanism of time integration in perceptual decisions

Recent physiological studies using behaving monkeys revealed that, in a two-alternative forced-choice visual motion discrimination task, reaction time was correlated with ramping of spike activity of lateral intraparietal cortical neurons. The ramping activity appears to reflect temporal accumulation, on a timescale of hundreds of milliseconds, of sensory evidence before a decision is reached. To elucidate the cellular and circuit basis of such integration times, we developed and investigated a simplified two-variable version of a biophysically realistic cortical network model of decision making. In this model, slow time integration can be achieved robustly if excitatory reverberation is primarily mediated by NMDA receptors; our model with only fast AMPA receptors at recurrent synapses produces decision times that are not comparable with experimental observations. Moreover, we found two distinct modes of network behavior, in which decision computation by winner-take-all competition is instantiated with or without attractor states for working memory. Decision process is closely linked to the local dynamics, in the "decision space" of the system, in the vicinity of an unstable saddle steady state that separates the basins of attraction for the two alternative choices. This picture provides a rigorous and quantitative explanation for the dependence of performance and response time on the degree of task difficulty, and the reason for which reaction times are longer in error trials than in correct trials as observed in the monkey experiment. Our reduced two-variable neural model offers a simple yet biophysically plausible framework for studying perceptual decision making in general.

Multivesicular release at Schaffer collateral-CA1 hippocampal synapses

Whether an individual synapse releases single or multiple vesicles of transmitter per action potential is contentious and probably depends on the type of synapse. One possibility is that multivesicular release (MVR) is determined by the instantaneous release probability (Pr) and therefore can be controlled by activity-dependent changes in Pr. We investigated transmitter release across a range of Pr at synapses between Schaffer collaterals (SCs) and CA1 pyramidal cells in acute hippocampal slices using patch-clamp recordings. The size of the synaptic glutamate transient was estimated by the degree of inhibition of AMPA receptor EPSCs with the rapidly equilibrating antagonist gamma-D-glutamylglycine. The glutamate transient sensed by AMPA receptors depended on Pr but not spillover, indicating that multiple vesicles are essentially simultaneously released from the same presynaptic active zone. Consistent with an enhanced glutamate transient, increasing Pr prolonged NMDA receptor EPSCs when glutamate transporters were inhibited. We suggest that MVR occurs at SC-CA1 synapses when Pr is elevated by facilitation and that MVR may be a phenomenon common to many synapses throughout the CNS.

A biophysical model of multiple-item working memory: A computational and neuroimaging study

Biophysically based computational models have successfully accounted for the persistent neural activity underlying the maintenance of single items of information in working memory. The aim of the present study was to extend previous models in order to retain multiple items, in agreement with the observed human storage capacity. This was done by implementing cellular mechanisms known to occur during the childhood development of working memory, such as an increased synaptic strength and improved contrast and specificity of the neural response. Our computational study shows that these mechanisms are sufficient to create a neural network which can store information about multiple items through sustained neural activity. Furthermore, by using functional magnetic resonance imaging, we found that the information-activity curve predicted by the model corresponds to that in the human posterior parietal cortex during performance of working memory tasks, which is consistent with previous studies of brain activity related to working memory capacity in humans.

Glutamate transporter studies reveal the pruning of metabotropic glutamate receptors and absence of AMPA receptor desensitization at mature calyx of Held synapses

We examined the effect of glutamate transporter blockade at the calyx of Held synapse. In immature synapses [defined as postnatal day 8 (P8) to P10 rats], transporter blockade causes tonic activation of NMDA receptors and strong inhibition of the AMPA receptor-mediated EPSC amplitude. EPSC inhibition was blocked with a metabotropic glutamate receptor (mGluR) antagonist [1 microm LY341495 (2S-2-amino-2-(1S,2S-2-carboxycycloprop-1-yl)-3-(xanth-9-yl)propanoic acid)], suggesting that elevated resting glutamate concentration specifically activates group II and group III mGluRs. Using mGluR subtype-specific agonists and antagonists, we determined that increased glutamate activates presynaptic mGluR2/3 and mGluR8 receptors but not mGluR4, although this receptor is present. Surprisingly, in older animals (P16-P18), transporter blockade had no effect on EPSC amplitude because of a developmental downregulation of group II/III mGluR activation in rats and mice. In contrast to other CNS synapses, we observed no effect of transporter blockade on EPSC decay kinetics, although expression of glutamate transporters was strong in nearby glial processes at both P9 and P17. Finally, using a low-affinity AMPA receptor antagonist (gamma-D-glutamylglycine), we show that desensitization occurs at P8-P10 but is absent at P16-P18, even during trains of high-frequency (100-300 Hz) stimulation. We suggest that diffusion and transporter activation are insufficient to clear synaptically released glutamate at immature calyces, resulting in significant desensitization. Thus, mGluRs may be expressed in the immature calyx to help limit glutamate release. In the more mature calyx, there is a far smaller diffusional barrier attributable to the highly fenestrated synaptic terminal morphology, so AMPA receptor desensitization is avoided and mGluR-mediated inhibition is not necessary.

Glutamate transporter type 3 attenuates the activation of N-methyl-D-aspartate receptors co-expressed in Xenopus oocytes

We studied the regulation of N-methy-D-aspartate receptor (NMDAR) current/activation by glutamate transporter type 3 (EAAT3), a neuronal EAAT in vivo, in the restricted extracellular space of a biological model. This model involved co-expressing EAAT3 and NMDAR (composed of NMDAR1-1a and NMDAR2A) in Xenopus oocytes. The NMDAR current was reduced in the co-expression oocytes but not in oocytes expressing NMDAR only when the flow of glutamate-containing superfusate was stopped. The degree of this current reduction was glutamate concentration-dependent. No reduction of NMDAR current was observed in Na+-free solution or when NMDA, a non-substrate for EAATs, was used as the agonist for NMDAR. In the continuous flow experiments, the dose-response curve of glutamate-induced current was shifted to the right-hand side in co-expression oocytes compared with oocytes expressing NMDAR alone. The degree of this shift depended on the abundance of EAAT3 in the co-expression oocytes. Thus, the glutamate concentrations sensed by NMDAR locally were lower than those in the superfusates. These results suggest that EAAT3 regulates the amplitude of NMDAR currents at pre-saturated concentrations of glutamate to EAAT3. Thus, EAATs, by rapidly regulating glutamate concentrations near NMDAR, modulate NMDAR current/activation.

Neurodynamics of Biased Competition and Cooperation for Attention: A Model With Spiking Neurons

Recent neurophysiological experiments have led to a promising “ biased competition hypothesis” of the neural basis of attention. According to this hypothesis, attention appears as a sometimes nonlinear property that results from a top-down biasing effect that influences the competitive and cooperative interactions that work both within cortical areas and between cortical areas. In this paper we describe a detailed dynamical analysis of the synaptic and neuronal spiking mechanisms underlying biased competition. We perform a detailed analysis of the dynamical capabilities of the system by exploring the stationary attractors in the parameter space by a mean-field reduction consistent with the underlying synaptic and spiking dynamics. The nonstationary dynamical behavior, as measured in neuronal recording experiments, is studied by an integrate-and-fire model with realistic dynamics. This elucidates the role of cooperation and competition in the dynamics of biased competition and shows why feedback connections between cortical areas need optimally to be weaker by a factor of about 2.5 than the feedforward connections in an attentional network. We modeled the interaction between top-down attention and bottom-up stimulus contrast effects found neurophysiologically and showed that top-down attentional effects can be explained by external attention inputs biasing neurons to move to different parts of their nonlinear activation functions. Further, it is shown that, although NMDA nonlinear effects may be useful in attention, they are not necessary, with nonlinear effects (which may appear multiplicative) being produced in the way just described.