Contribution of GABAA receptor-mediated inhibition to the determination of the velocity tuning of low pass-tuned neurons of the Superior Colliculus

The participation of intrinsic inhibitory networks in providing the velocity selectivity of neurons of the superior colliculus (SC) of the Syrian hamster was tested using iontophoretic application of bicuculline methiodide, a GABA_A receptor competitive antagonist. The impulse activity of 22 low pass-tuned (LP) cells was recorded extracellularly. Following application of bicuculline, 10 cells exhibited an increase in the velocity selectivity, while the other 12 units showed decreases in their tuning. We assume that SC intrinsic inhibitory networks contributing to the velocity tuning of neurons of this structure are driven in a dissimilar way by afferent volleys arriving from the retina through “fast” Y and “slow” W channels. Neirofiziologiya/Neurophysiology, Vol. 39, Nos. 4/5, pp. 385–387, July–October, 2007.     

A neural mechanism of hyperaccurate detection of phase advance and delay in the jamming avoidance response of weakly electric fish

 The weakly electric fish Eigenmannia can detect the phase difference between a jamming signal and its own signal down to 1 s. To clarify the neuronal mechanism of this hyperaccurate detection of phase difference, we present a neural network model of the torus of the midbrain which plays an essential role in the detection of phase advances and delays. The small-cell model functions as a coincidence detector and can discriminate a time difference of more than 100 s. The torus model consists of laminae 6 and 8. The model of lamina 6 is made with multiple encoding units, each of which consists of a single linear array of small cells and a single giant cell. The encoding unit encodes the phase difference into its spatio-temporal firing pattern. The spatially random distribution of small cells in each encoding unit improves the encoding ability of phase modulation. The neurons in lamina 8 can discriminate the phase advance and delay of jamming electric organ discharges (EODs) compared with the phase of the fish's own EOD by integrating simultaneously the outputs from multiple encoding units in lamina 6. The discrimination accuracy of the feature-detection neurons is of the order of 1 s. The neuronal mechanism generating this hyperacuity arises from the spatial feature of the system that the innervation sites of small cells in different encoding units are distributed randomly and differently on the dendrites of single feature-detection neurons. The mechanism is similar to that of noise-enhanced information transmission. Received: 10 July 2000 / Accepted in revised form: 19 January 2001     

Dynamics of two electrically coupled chaotic neurons: Experimental observations and model analysis

Conductance-based models of neurons from the lobster stomatogastric ganglion (STG) have been developed to understand the observed chaotic behavior of individual STG neurons. These models identify an additional slow dynamical process – calcium exchange and storage in the endoplasmic reticulum – as a biologically plausible source for the observed chaos in the oscillations of these cells. In this paper we test these ideas further by exploring the dynamical behavior when two model neurons are coupled by electrical or gap junction connections. We compare in detail the model results to the laboratory measurements of electrically-coupled neurons that we reported earlier. The experiments on the biological neurons varied the strength of the effective coupling by applying a parallel, artificial synapse, which changed both the magnitude and polarity of the conductance between the neurons. We observed a sequence of bifurcations that took the neurons from strongly synchronized in-phase behavior, through uncorrelated chaotic oscillations to strongly synchronized – and now regular – out-of-phase behavior. The model calculations reproduce these observations quantitatively, indicating that slow subcellular processes could account for the mechanisms involved in the synchronization and regularization of the otherwise individual chaotic activities. Received: 28 June 1999 / Accepted in revised form: 30 June 2000     

Temporal selectivity for complex signals by single neurons in the torus semicircularis of Pleurodema thaul (Amphibia: Leptodactylidae)

Responses of auditory neurons in the torus semicircularis (TS) of Pleurodema thaul, a leptodactylid from Chile, to synthetic stimuli having diverse temporal patterns and to digitized advertisement calls of P. thaul and three sympatric species, were recorded to investigate their temporal response selectivities. The advertisement call of this species consists of a long sequence of sound pulses (a pulse-amplitude-modulated, or PAM, signal) having a dominant frequency of about 2000 Hz. Each of the sound pulses contains intra-pulse sinusoidal-amplitude-modulations (SAMs). Synthetic stimuli consisted of six series in which the following acoustic parameters were systematically modified, one at a time: PAM rate, pulse duration, number of pulses, and intra-pulse SAM rate. The carrier frequency of these stimuli was set at the characteristic frequency (CF) of the isolated units (n = 47). Response patterns of TS units to synthetic call variants reveal different degrees of selectivities for each of the temporal variables, with populations of neurons responding maximally to specific values found in the advertisement call of this species. These selectivities are mainly shaped by neuronal responsiveness to the overall sound energy of the stimulus and by the inability of neurons to discharge to short inter-pulse gaps. Accepted: 30 October 1996     

Mechanisms to synchronize neuronal activity

 Temporal aspects of neuronal activity have received increasing attention in recent years. Oscillatory dynamics and the synchronization of neuronal activity are hypothesized to be of functional relevance to information processing in the brain. Here we review theoretical studies of single neurons at different levels of abstraction, with an emphasis on the implications for properties of networks composed of such units. We then discuss the influence of different types of couplings and choices of parameters to the existence of a stable state of synchronous or oscillatory activity. Finally we relate these theoretical studies to the available experimental data, and suggest future lines of research. Received: 20 July 1999 / Accepted in revised form: 23 August 2000     

Capacity analysis in multi-state synaptic models: a retrieval probability perspective

We define the memory capacity of networks of binary neurons with finite-state synapses in terms of retrieval probabilities of learned patterns under standard asynchronous dynamics with a predetermined threshold. The threshold is set to control the proportion of non-selective neurons that fire. An optimal inhibition level is chosen to stabilize network behavior. For any local learning rule we provide a computationally efficient and highly accurate approximation to the retrieval probability of a pattern as a function of its age. The method is applied to the sequential models (Fusi and Abbott, Nat Neurosci 10:485–493, 2007) and meta-plasticity models (Fusi et al., Neuron 45(4):599–611, 2005; Leibold and Kempter, Cereb Cortex 18:67–77, 2008). We show that as the number of synaptic states increases, the capacity, as defined here, either plateaus or decreases. In the few cases where multi-state models exceed the capacity of binary synapse models the improvement is small.     

The amelioration of aluminium toxicity by silicon in wheat (Triticum aestivum L.): malate exudation as evidence for an in planta mechanism

Two wheat (Triticum aestivum L.) cultivars, one aluminium tolerant (Atlas 66) and one sensitive (Scout 66), were grown in a continuous-flow culture system (≤pH 5.0) containing aluminium (0–100 μM) and silicon (0–2000 μM) in factorial combination. Treatment with silicon resulted in a highly significant amelioration of aluminium toxicity as assessed by root growth in both cultivars. Amelioration was influenced by wheat cultivar and silicon concentration, as 2000 μM silicon significantly ameliorated the toxic effects of 100 μM aluminium in Atlas 66, and only 5 μM silicon alleviated the effect of 1.5 μM aluminium on Scout 66. Nutrient medium pH was critical, as an amelioration by silicon was apparent only at pH > 4.2 for Atlas 66, and at pH > 4.6 for Scout 66. Silicon neither reduced levels of toxic aluminium species in the growth solutions, nor the amount of aluminium taken up by roots. In experiments to assess exudation of malate by Atlas 66 roots treated with 100 μM aluminium, the presence of 2000 μM silicon (pH 4.6) was found to have a negligible effect on exudation. In contrast, citrate, a known aluminium chelator, reduced aluminium-induced exudation of malate at 5–40 μM and completely inhibited it at 100 μM citrate. The results indicate that silicon does not reduce aluminium phytotoxicity as a result of aluminium/silicon interactions in the external media, and that the mechanism of amelioration has an in planta component. Received: 22 April 1997 / Accepted: 16 August 1997     

Spike-time reliability of layered neural oscillator networks

We study the reliability of layered networks of coupled “type I” neural oscillators in response to fluctuating input signals. Reliability means that a signal elicits essentially identical responses upon repeated presentations, regardless of the network’s initial condition. We study reliability on two distinct scales: neuronal reliability, which concerns the repeatability of spike times of individual neurons embedded within a network, and pooled-response reliability, which concerns the repeatability of total synaptic outputs from a subpopulation of the neurons in a network. We find that neuronal reliability depends strongly both on the overall architecture of a network, such as whether it is arranged into one or two layers, and on the strengths of the synaptic connections. Specifically, for the type of single-neuron dynamics and coupling considered, single-layer networks are found to be very reliable, while two-layer networks lose their reliability with the introduction of even a small amount of feedback. As expected, pooled responses for large enough populations become more reliable, even when individual neurons are not. We also study the effects of noise on reliability, and find that noise that affects all neurons similarly has much greater impact on reliability than noise that affects each neuron differently. Qualitative explanations are proposed for the phenomena observed.

Elements for a general memory structure: properties of recurrent neural networks used to form situation models

We study how individual memory items are stored assuming that situations given in the environment can be represented in the form of synaptic-like couplings in recurrent neural networks. Previous numerical investigations have shown that specific architectures based on suppression or max units can successfully learn static or dynamic stimuli (situations). Here we provide a theoretical basis concerning the learning process convergence and the network response to a novel stimulus. We show that, besides learning “simple” static situations, a nD network can learn and replicate a sequence of up to n different vectors or frames. We find limits on the learning rate and show coupling matrices developing during training in different cases including expansion of the network into the case of nonlinear interunit coupling. Furthermore, we show that a specific coupling matrix provides low-pass-filter properties to the units, thus connecting networks constructed by static summation units with continuous-time networks. We also show under which conditions such networks can be used to perform arithmetic calculations by means of pattern completion.     

Analysis of the exponential decay model of the neuron showing frequency threshold effects

The exponential decay model of a neuron has been analyzed using the “random walk” approach of stochastic processes and an “absorbing barrier” solution is obtained forg ^T (s)—the Laplace transform of the output pulse interval density function. An expression for the mean output frequency is derived from this and a variety of input-output curves plotted which show frequency threshold effects in single neurons. Our results are compared with those of other authors obtained by computer simulation techniques, and the significance of these results discussed with reference to the possible behavior of networks constructed of such neuron units.     

Receptive Fields of Visually Sensitive Neurons of the Extrastriate Associative Area 21b of the Cat Cerebral Cortex

Organization of the receptive fields (RFs) of neurons of the extrastriate associative region 21b of the cerebral cortex was studied in cats. Most neurons under study (63%) were “monocular,” while 37% of the cells were “binocular” units. Among 178 neurons examined in detail, heterogeneous RF functional organization was typical of about 76% of the units; point-to-point testing of the entire RF area by stationary stimuli resulted in the generation of various types of responses (on, off, or on-off). The rest of the neurons (24%) generated homogeneous responses. The dimension, form, and functional organization of RFs of the neurons under study depended to a certain extent on the parameters of visual stimuli used for the measurements. Examination of the influence of the visual space, which surrounded the RF, on responses of the neurons evoked by stimulation of the RF per se showed that darkening of the visual space adjacent to the RF inhibited neuronal responses to moving stimuli; in some cases the responses were totally suppressed. Analysis of spatial overlapping of the RF sequentially recorded in the course of each insertion of the electrode showed that the density of distribution of the overlapping RF areas of neighboring neurons with the RF of the examined neuron is irregular, and that the RF is of a mosaic nature. We hypothesize that the visual space surrounding the RF plays a significant role in the formation of responses of visually sensitive neurons to presentation of moving stimuli. Neirofiziologiya/Neurophysiology, Vol. 37, No. 3, pp. 223–234, May–June, 2005.     

A CMOS neuroelectronic interface based on two-dimensional transistor arrays with monolithically-integrated circuitry

The ability to monitor and to elicit neural activity with a high spatiotemporal resolution has grown essential for studying the functionality of neuronal networks. Although a variety of microelectrode arrays (MEAs) has been proposed, very few MEAs are integrated with signal-processing circuitry. As a result, the maximum number of electrodes is limited by routing complexity, and the signal-to-noise ratio is degraded by parasitics and noise interference. This paper presents a single-chip neuroelectronic interface integrating oxide-semiconductor field-effect transistors (OSFETs) with signal-processing circuitry. After the chip was fabricated with the standard complementary-metal-oxide-semiconductor (CMOS) process, polygates of specific transistors were etched at die-level to form OSFETs, while metal layers were retained to connect the OSFETs into two-dimensional arrays. The complete removal of polygates was confirmed by high-resolution image scanners, and the reliability of OSFETs was examined by measuring their electrical characteristics. Through a gate oxide of only 7nm thick, each OSFET can record and stimulate neural activity extracellularly by capacitive coupling. The capability of the full chip in neural recording and stimulation was further experimented using the well-characterised escape circuit of the crayfish. Experimental results indicate that the OSFET-based neuroelectronic interface can be used to study neuronal networks as faithfully as conventional electrophysiological tools. Moreover, the proposed simple, die-level fabrication process of the OSFETs underpins the development of various field-effect biosensors on a large scale with on-chip circuitry.     

A computational model of action selection in the basal ganglia. I. A new functional anatomy

 We present a biologically plausible model of processing intrinsic to the basal ganglia based on the computational premise that action selection is a primary role of these central brain structures. By encoding the propensity for selecting a given action in a scalar value (the salience), it is shown that action selection may be re-cast in terms of signal selection. The generic properties of signal selection are defined and neural networks for this type of computation examined. A comparison between these networks and basal ganglia anatomy leads to a novel functional decomposition of the basal ganglia architecture into `selection' and `control' pathways. The former pathway performs the selection per se via a feedforward off-centre on-surround network. The control pathway regulates the action of the selection pathway to ensure its effective operation, and synergistically complements its dopaminergic modulation. The model contrasts with the prevailing functional segregation of basal ganglia into `direct' and `indirect' pathways. Received: 16 February 2000 / Accepted in revised form: 30 October 2000     

A stochastic model and a functional central limit theorem for information processing in large systems of neurons

The paper deals with information transmission in large systems of neurons. We model the membrane potential in a single neuron belonging to a cell tissue by a non time-homogeneous Cox-Ingersoll-Ross type diffusion; in terms of its time-varying expectation, this stochastic process can convey deterministic signals. We model the spike train emitted by this neuron as a Poisson point process compensated by the occupation time of the membrane potential process beyond the excitation threshold. In a large system of neurons 1≤i≤N processing independently the same deterministic signal, we prove a functional central limit theorem for the pooled spike train collected from the N neurons. This pooled spike train allows to recover the deterministic signal, up to some shape transformation which is explicit.     

The potential role of presenilin 1 in regulation of synaptic function

One of the earliest neuropathological symptoms of Alzheimer’s disease is the loss of synapses that precedes the formation of amyloid plaques and neurodegeneration. Although most cases of early-onset familial Alzheimer’s disease are caused by mutations in the presenilin 1 (PS1) gene, the functions of PS1 and its role in synaptic dysfunction are not yet completely understood. In this paper, we analyzed PS1 intra- and extracellular distribution in cultures of mouse cortical embryonic neurons. We found that PS1 was concentrated on the surface of the growth cone and neurite contact sites. PS1 was also found in synapses where it was colocalized with synaptophysin. We obtained independent evidence of PS1 involvement in synaptic function by transfection of neurons with GFP-PS1cDNA. GFP was colocalized with synaptophysin in transfected cultures. GFP-immunoprecepitates from transfected neurons contained N-cadherin. This finding represents additional evidence of PS1 participation in the synapse formation. To evaluate the role of PS1 inactivation in the synaptic functions, we compare the synaptic density in neuronal cell cultures from knockout mice PS1 (−/−) and wild type mice PS1 (+/+). Our results obviously show that PS1 (−/−) cultures displayed lower number of morphological synapses compared to wild type culture PS1 (+/+). In summary, our findings show the role of PS1 in synaptic function.     

The molecular signals that regulate activity-dependent synapse refinement in the brain

The formation of appropriate synaptic connections is critical for the proper functioning of the brain. Early in development, neurons form a surplus of immature synapses. To establish efficient, functional neural networks, neurons selectively stabilize active synapses and eliminate less active ones. This process is known as activity-dependent synapse refinement. Defects in this process have been implicated in neuropsychiatric disorders such as schizophrenia and autism. Here we review the manner and mechanisms by which synapse elimination is regulated through activity-dependent competition. We propose a theoretical framework for the molecular mechanisms of synapse refinement, in which three types of signals regulate the refinement. We then describe the identity of these signals and discuss how multiple molecular signals interact to achieve appropriate synapse refinement in the brain.     

Long-term electrophysiological activity and pharmacological response of a human induced pluripotent stem cell-derived neuron and astrocyte co-culture

Human induced pluripotent stem cell (hiPSC)-derived neurons may be effectively used for drug discovery and cell-based therapy. However, the immaturity of cultured human iPSC-derived neurons and the lack of established functional evaluation methods are problematic. We here used a multi-electrode array (MEA) system to investigate the effects of the co-culture of rat astrocytes with hiPSC-derived neurons on the long-term culture, spontaneous firing activity, and drug responsiveness effects. The co-culture facilitated the long-term culture of hiPSC-derived neurons for >3 months and long-term spontaneous firing activity was also observed. After >3 months of culture, we observed synchronous burst firing activity due to synapse transmission within neuronal networks. Compared with rat neurons, hiPSC-derived neurons required longer time to mature functionally. Furthermore, addition of the synapse antagonists bicuculline and 6-cyano-7-nitroquinoxaline-2,3-dione induced significant changes in the firing rate. In conclusion, we used a MEA system to demonstrate that the co-culture of hiPSC-derived neurons with rat astrocytes is an effective method for studying the function of human neuronal cells, which could be used for drug screening.     

Changes in the levels of activity of spinal neurons after long-lasting vibrational stimulation of the shin muscles in rats

Vibrational stimulation of the tendon of the mm.gastrocnemius+soleus (100 sec^–1) in rats anesthetized with chloral hydrate (400 mg/kg) resulted in the appearance of considerable Fos immunoreactivity in the lumbar spinal cord (L1-L6), as compared with that in intact animals. Total densities of Fos-immunopositive (Fos-ip) neurons in each of the examined segments were higher than 40 units per 40-μm-thick slice; the respective index reached the maximum at the L4 level (78.9 ± 2.3 cells). Most Fos-ip neurons were localized in laminae 4 to 7 of the gray matter, both ipsi- and contralaterally with respect to the side of stimulation (28.5 ± 0.6 and 28.4 ± 0.6, respectively). Single Fos-ip motoneurons were found bilaterally in the ventral horn motor nuclei. Thus, activation of muscle spindle receptors induced by vibrational stimulation applied to the Achilles tendon induces noticeable bilateral c-fos expression in spinal neuronal networks related to transmission of proprioceptive muscle-born impulsation.     

Catalysis in Reaction Networks

We define catalytic networks as chemical reaction networks with an essentially catalytic reaction pathway: one which is “on” in the presence of certain catalysts and “off” in their absence. We show that examples of catalytic networks include synthetic DNA molecular circuits that have been shown to perform signal amplification and molecular logic. Recall that a critical siphon is a subset of the species in a chemical reaction network whose absence is forward invariant and stoichiometrically compatible with a positive point. Our main theorem is that all weakly-reversible networks with critical siphons are catalytic. Consequently, we obtain new proofs for the persistence of atomic event-systems of Adleman et al., and normal networks of Gnacadja. We define autocatalytic networks, and conjecture that a weakly-reversible reaction network has critical siphons if and only if it is autocatalytic.     

Crustacean phasic and tonic motor neurons

Crustacean motor neurons subserving locomotion are specializedfor the type of activity in which they normally participate.Neurons responsible for maintained activity (‘tonic’neurons) support moderate to high frequencies of nerve impulsesintermittently or continuously during locomotion, while thoserecruited for short-lasting rapid responses (‘phasic’neurons) generally fire a few impulses in a rapid burst duringrapid locomotion and are otherwise silent. The synaptic responsesof the two types, recorded at their respective neuromuscularjunctions, differ enormously: phasic neurons exhibit much higherquantal release per synapse and per muscle fibre, along withmore rapid synaptic depression and less short-term facilitation.We have analyzed the factors that are responsible for the largedifference in initial release of neurotransmitter. Several possibilities,including synapse and active zone size differences, entry ofcalcium at active zones, and immediately releasable vesiclepools, could not account for the large phasic-tonic differencein initial transmitter output. The most likely feature thatdifferentiates synaptic release is the sensitivity of the exocytoticmachinery to intracellular calcium. Molecular features of thephasic and tonic presynaptic nerve terminals are currently underinvestigation.