A model of stimulus-specific neural assemblies in the insect antennal lobe

It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A)-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A) and GABA(B) inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B) synapses make the neural response unpredictable. Depending on the balance between GABA(A) and GABA(B) inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.     

Resistance of frog olfactory bulb slow potential and afferent input inhibition to hypoxia and synaptic transmission blockade by manganese,cobalt, and magnesium ions

The effect of hypoxia and application of manganese, cobalt, and magnesium ions on electrical responses of the frog olfactory bulb to adequate stimulation and to direct electrical stimulation of the olfactory nerve were studied. The slow potential evoked by adequate stimulation and the associated inhibition of the afferent input of the olfactory bulb were found to be much more resistant to inhibition of synaptic transmission by all methods used than the postsynaptic components of the orthodromic response and associated postsynaptic inhibition. A slow potential was recorded even when synaptic transmission in the olfactory bulb was completely blocked by magnesium ions. It is concluded that the slow potential of the olfactory bulb and inhibition of its afferent input are nonsynaptic in nature. It is postulated that the slow potential reflects mainly depolarization of glial cells in the glomerular layer of the bulb evoked by accumulation of potassium ions. The possible mechanisms of inhibition of the afferent input are discussed.     

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns.     

Neuromodulation by Glutamate and Acetylcholine can Change Circuit Dynamics by Regulating the Relative Influence of Afferent Input and Excitatory Feedback

Substances such as acetylcholine and glutamate act as both neurotransmitters and neuromodulators. As neuromodulators, they change neural information processing by regulating synaptic transmitter release, altering baseline membrane potential and spiking activity, and modifying long-term synaptic plasticity. Slice physiology research has demonstrated that many neuromodulators differentially modulate afferent, incoming information compared to intrinsic and recurrent processing in cortical structures such as piriform cortex, neocortex, and the hippocampus. The enhancement of afferent (external) pathways versus the suppression at recurrent (internal) pathways could cause cortical dynamics to switch between a predominant influence of external stimulation to a predominant influence of internal recall. Modulation of afferent versus intrinsic processing could contribute to the role of neuromodulators in regulating attention, learning, and memory effects in behavior.     

Ultrastructure of the lateral-line sense organs of the ratfish,Chimaera monstrosa

Summary The ultrastructure of the lateral-line neuromasts in the ratfish, Chimaera monstrosa is described. The neuromasts rest at the bottom of open grooves and consist of sensory, supporting, basal and mantle cells. Each sensory cell is equipped with sensory hairs consisting of a single kinocilium and several stereocilia. There are several types of sensory hair arrangement, and cells with a particular arrangement form patches within the neuromast. There are two types of afferent synapse. The most common afferent synapse has a presynaptic body and is typically associated with an extensive system of anastomosing tubules on the presynaptic side. When the tubules are absent, vesicles surround the presynaptic body. These synapses are often associated into synaptic fields, containing up to 35 synaptic sites. The second type of afferent synapse does not have a presynaptic body and is not associated with the tubular system. The afferent synapses of the second type do not form synaptic fields and are uncommon. The efferent synapses are either associated with a postsynaptic sac or more commonly with a strongly osmiophilic postsynaptic membrane. The accessory cells are similar to those in the acoustico-lateralis organs of other aquatic vertebrates. A possibility of movement of the presynaptic bodies and of involvement of the tubular system in the turnover of the transmitter is discussed. A comparison of the hair tuft types in the neuromasts of Ch. monstrosa with those in the labyrinth of the goldfish and of the frog is attempted.     

Efferent fibers innervate gustatory and mechanosensitive afferent fibers in frog fungiform papillae

A possibility of efferent innervation of gustatory and mechanosensitive afferent fiber endings was studied in frog fungiform papillae with a suction electrode. The amplitude of antidromic impulses in a papillary afferent fiber induced by antidromically stimulating an afferent fiber of glossopharyngeal nerve (GPN) with low voltage pulses was inhibited for 40 s after the parasympathetic efferent fibers of GPN were stimulated orthodromically with high voltage pulses at 30 Hz for 10 s. This implies that electrical positivity of the outer surface of papillary afferent membrane was reduced by the efferent fiber-induced excitatory postsynaptic potential. The inhibition of afferent responses in the papillae was blocked by substance P receptor blocker, L-703,606, indicating that substance P is probably released from the efferent fiber terminals. Slow negative synaptic potential, which corresponded to a slow depolarizing synaptic potential, was extracellularly induced in papillary afferent terminals for 45 s by stimulating the parasympathetic efferent fibers of GPN with high voltage pulses at 30 Hz for 10 s. This synaptic potential was also blocked by L-703,606. These data indicate that papillary afferent fiber endings are innervated by parasympathetic efferent fibers.     

Noisy neural nets exhibiting memory domains

Previous studies with probabilistic neural nets in which the neural connections are set up by means of chemical markers, revealed the existence of multiple memory domains. We generalized these studies by considering the intrinsic noise of the systems, caused by the spontaneous release of synaptic transmitter substance. A simple mathematical model is developed, which yields characteristics of multiple memory domains analogous to those occurring in noiseless nets.     

Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell

It is widely believed that synaptic modifications underlie learning and memory. However, few studies have examined what can be deduced about the learning process from the distribution of synaptic weights. We analyze the perceptron, a prototypical feedforward neural network, and obtain the optimal synaptic weight distribution for a perceptron with excitatory synapses. It contains more than 50% silent synapses, and this fraction increases with storage reliability: silent synapses are therefore a necessary byproduct of optimizing learning and reliability. Exploiting the classical analogy between the perceptron and the cerebellar Purkinje cell, we fitted the optimal weight distribution to that measured for granule cell-Purkinje cell synapses. The two distributions agreed well, suggesting that the Purkinje cell can learn up to 5 kilobytes of information, in the form of 40,000 input-output associations.     

Cyclin-dependent kinase 5 in synaptic plasticity, learning and memory

Cyclin-dependent kinase 5 (Cdk5) is a serine/threonine kinase with a multitude of functions. Although Cdk5 is widely expressed, it has been studied most extensively in neurons. Since its initial characterization, the fundamental contribution of Cdk5 to an impressive range of neuronal processes has become clear. These phenomena include neural development, dopaminergic function and neurodegeneration. Data from different fields have recently converged to provide evidence for the participation of Cdk5 in synaptic plasticity, learning and memory. In this review, we consider recent data implicating Cdk5 in molecular and cellular mechanisms underlying synaptic plasticity. We relate these findings to its emerging role in learning and memory. Particular attention is paid to the activation of Cdk5 by p25, which enhances hippocampal synaptic plasticity and memory, and suggests formation of p25 as a physiological process regulating synaptic plasticity and memory.     

Molecular mechanisms underlying emotional learning and memory in the lateral amygdala

Fear conditioning is a valuable behavioral paradigm for studying the neural basis of emotional learning and memory. The lateral nucleus of the amygdala (LA) is a crucial site of neural changes that occur during fear conditioning. Pharmacological manipulations of the LA, strategically timed with respect to training and testing, have shed light on the molecular events that mediate the acquisition of fear associations and the formation and maintenance of long-term memories of those associations. Similar mechanisms have been found to underlie long-term potentiation (LTP) in LA, an artificial means of inducing synaptic plasticity and a physiological model of learning and memory. Thus, LTP-like changes in synaptic plasticity may underlie fear conditioning. Given that the neural circuit underlying fear conditioning has been implicated in emotional disorders in humans, the molecular mechanisms of fear conditioning are potential targets for psychotherapeutic drug development.     

Short-term plasticity at primary afferent synapse in rat spinal dorsal horn and its biological function

Short-term plasticity (STP) is an important element of information processing in neuronal networks. As the first synaptic relay between primary afferent fibers (PAFs) and central neurons, primary afferent synapses in spinal dorsal horn (DH) are essential to the initial processing of somatosensory information. In this research, we examined the STP between Adelta-PAFs and spinal DH neurons by patch-clamp recording. Our results showed that depression dominated the STP at primary afferent synapses. The curves of STP had no significant changes in the presence of bicuculline, CTZ or AP-5. Lowering extracellular Ca(2+) concentration ([Ca(2+)](o)) from 2.4 to 0.8 mM reduced the depression of synaptic responses at all stimulus rates, while raising [Ca(2+)](o) from 2.4 to 4.0 mM increased the synaptic depression. Increasing the bath temperature from 24 to 32 degrees C clearly reduced the depression of all responses. These results indicate that the observed STP is of presynaptic origin and depends on transmitter release. By fitting the experimental data recorded under different conditions, a model of STP was used to quantitatively characterize the observed STP and to analyze the possible mechanisms underlying the effects of [Ca(2+)](o) and temperature. Furthermore, using a model neuron receiving synaptic inputs, we found that with this form of STP, postsynaptic DH neurons could detect rate changes in both rapidly- and slowly-firing afferents with equal sensitivity. The present study links the intrinsic STP properties of primary afferent synapses with their role in processing neural information, and provides a basis for further research on the STP in spinal DH and its biological function under in vivo conditions.     

Effects of hyperdynamic fields on input-output relationships and long-term potentiation in the rat hippocampus

The effects of a 2G force environment on synaptic plasticity were examined in the rat hippocampus. Field potentials from neurons in the CA1 pyramidal cell layer were evoked by stimulation of the afferent Schaffer collateral/commissural fibers in an in vitro slice preparation. Input-output (I-O) relationships of the circuit were determined before and after tetanizing stimuli given to induce long term potentiation (LTP), a form of neural plasticity. I-O curves from animals exposed to 2G via centrifugation for either 2 or 14 days were not different from those obtained in control (1G) animals. Similarly, induction of LTP was equivalent in all groups, showing increases in maximum amplitude, slope and midpoint response of the fitted Boltzmann functions compared to un-tetanized controls. Comparison of slices from dorsal and ventral hippocampus showed the location of the slice had no effect of LTP expression. We conclude that, in contrast to other reports of functional changes in the central nervous system under altered force environments, cellular mechanisms of synaptic plasticity, which may underlie learning and memory, are preserved in the hippocampus.     

RNA aptamers to initiation factor 4A helicase hinder cap-dependent translation by blocking ATP hydrolysis

The mammalian translation initiation factor 4A (eIF4A) is a prototype member of the DEAD-box RNA helicase family that couples ATPase activity to RNA binding and unwinding. In the crystal form, eIF4A has a distended "dumbbell" structure consisting of two domains, which probably undergo a conformational change, on binding ATP, to form a compact, functional structure via the juxtaposition of the two domains. Moreover, additional conformational changes between two domains may be involved in the ATPase and helicase activity of eIF4A. The molecular basis of these conformational changes, however, is not understood. Here, we generated RNA aptamers with high affinity for eIF4A by in vitro RNA selection-amplification. On binding, the RNAs inhibit ATP hydrolysis. One class of RNAs contains members that exhibit dissociation constant of 27 nM for eIF4A and severely inhibit cap-dependent in vitro translation. The binding affinity was increased on Arg substitution in the conserved motif Ia of eIF4A, which probably improves a predicted arginine network to bind RNA substrates. Selected RNAs, however, failed to bind either domain of eIF4A that had been split at the linker site. These findings suggest that the selected RNAs interact cooperatively with both domains of eIF4A, either in the dumbbell or the compact form, and entrap it into a dead-end conformation, probably by blocking the conformational change of eIF4A. The selected RNAs, therefore, represent a new class of specific inhibitors that are suitable for the analysis of eukaryotic initiation, and which pose a potential therapeutic against malignancies that are caused by aberrant translational control.     

The possible molecular basis for memory processes in the central nervous system

The brain is able to record the messages that arrive from the external world and memory is the specific mechanism of this recording which can leave either a transient or a permanent trace.It is likely that the structural basis of such a mechanism is a modification of macromolecular conformation induced by electric events concomitant with the neural discharge.Nucleic acids and proteins are candidates for the role of basic molecules in the engram because of their ability to undergo transient structural modifications such as conformational changes and to render permanent the above modifications through the system of protein biosynthesis.Short-term memory is a transient modification established within very short time intervals which can be wiped out quite easily. It might in fact correspond to a single interference with the synaptic activity, dependent on a transient and labile influence of macromolecules present in synaptic membrane and modified by the electric field created by neural discharge within the membrane.Long-term memory is the basis of a global condition referred to as experience and requires longer times to be established. It is definitely associated with protein synthesis and results as a permanent modification of the number and structure of the synapses.The mechanism of the recording and retrieval of information has been described with an attempt to inter-relate different models and hypotheses.     

Cellular and molecular mechanisms of memory

There has been nearly a century of interest in the idea that information is encoded in the brain as specific spatio-temporal patterns of activity in distributed networks and stored as changes in the efficacy of synaptic connections on neurons that are activated during learning. The discovery and detailed report of the phenomenon generally known as long-term potentiation opened a new chapter in the study of synaptic plasticity in the vertebrate brain, and this form of synaptic plasticity has now become the dominant model in the search for the cellular bases of learning and memory. To date, the key events in the cellular and molecular mechanisms underlying synaptic plasticity are starting to be identified. They require the activation of specific receptors and of several molecular cascades to convert extracellular signals into persistent functional changes in neuronal connectivity. Accumulating evidence suggests that the rapid activation of the genetic machinery is a key mechanism underlying the enduring modification of neural networks required for the laying down of memory. The recent developments in the search for the cellular and molecular mechanisms of memory storage are reviewed.     

BDNF boosts spike fidelity in chaotic neural oscillations

Oscillatory activity and its nonlinear dynamics are of fundamental importance for information processing in the central nervous system. Here we show that in aperiodic oscillations, brain-derived neurotrophic factor (BDNF), a member of the neurotrophin family, enhances the accuracy of action potentials in terms of spike reliability and temporal precision. Cultured hippocampal neurons displayed irregular oscillations of membrane potential in response to sinusoidal 20-Hz somatic current injection, yielding wobbly orbits in the phase space, i.e., a strange attractor. Brief application of BDNF suppressed this unpredictable dynamics and stabilized membrane potential fluctuations, leading to rhythmical firing. Even in complex oscillations induced by external stimuli of 40 Hz (gamma) on a 5-Hz (theta) carrier, BDNF-treated neurons generated more precisely timed spikes, i.e., phase-locked firing, coupled with theta-phase precession. These phenomena were sensitive to K252a, an inhibitor of tyrosine receptor kinases and appeared attributable to BDNF-evoked Na(+) current. The data are the first indication of pharmacological control of endogenous chaos. BDNF diminishes the ambiguity of spike time jitter and thereby might assure neural encoding, such as spike timing-dependent synaptic plasticity.     

Unsupervised learning for robust working memory

Working memory is a core component of critical cognitive functions such as planning and decision-making. Persistent activity that lasts long after the stimulus offset has been considered a neural substrate for working memory. Attractor dynamics based on network interactions can successfully reproduce such persistent activity. However, it requires a fine-tuning of network connectivity, in particular, to form continuous attractors which were suggested for encoding continuous signals in working memory. Here, we investigate whether a specific form of synaptic plasticity rules can mitigate such tuning problems in two representative working memory models, namely, rate-coded and location-coded persistent activity. We consider two prominent types of plasticity rules, differential plasticity correcting the rapid activity changes and homeostatic plasticity regularizing the long-term average of activity, both of which have been proposed to fine-tune the weights in an unsupervised manner. Consistent with the findings of previous works, differential plasticity alone was enough to recover a graded-level persistent activity after perturbations in the connectivity. For the location-coded memory, differential plasticity could also recover persistent activity. However, its pattern can be irregular for different stimulus locations under slow learning speed or large perturbation in the connectivity. On the other hand, homeostatic plasticity shows a robust recovery of smooth spatial patterns under particular types of synaptic perturbations, such as perturbations in incoming synapses onto the entire or local populations. However, homeostatic plasticity was not effective against perturbations in outgoing synapses from local populations. Instead, combining it with differential plasticity recovers location-coded persistent activity for a broader range of perturbations, suggesting compensation between two plasticity rules.     

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.