Long-term depression in rat CA1-subicular synapses depends on the G-protein coupled mACh receptors

The subiculum, which is the primary target of CA1 pyramidal neurons and sending efferent fibres to many brain regions, serves as a hippocampal interface in the neural information processes between hippocampal formation and neocortex. Long-term depression (LTD) is extensively studied in the hippocampus, but not at the CA1-subicular synaptic transmission. Using whole-cell EPSC recordings in the brain slices of young rats, we demonstrated that the pairing protocols of low frequency stimulation (LFS) at 3 Hz and postsynaptic depolarization of -50 mVelicited a reliable LTD in the subiculum. The LTD did not cause the changes of the paired-pulse ratio of EPSC. Furthermore, it did not depend on either NMDA receptors or voltage-gated calcium channels (VGCCs). Bath application of the G-protein coupled muscarinic acetylcholine receptors (mAChRs) antagonists, atropine or scopolamine, blocked the LTD, suggesting that mAChRs are involved in the LTD. It was also completely blocked by either the Ca2+ chelator BAPTA or the G-protein inhibitor GDP-beta-S in the intracellular solution. This type of LTD in the subiculum may play a particular role in the neural information processing between the hippocampus and neocortex. (c) 2005 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Opiate withdrawal modifies synaptic plasticity in subicular-nucleus accumbens pathway in vivo

Subiculum receives output of hippocampal CAI neurons and projects glutamatergic synapses onto nucleus accumbens (NAc), the subicular-NAc pathway linking memory and reward system. It is unknown whether morphine withdrawal influences synaptic plasticity in

Feedback modulation: a window into cortical function.

A recent study demonstrates involvement of primary motor cortex in task-dependent modulation of rapid feedback responses; cortical neurons resolve locally ambiguous sensory information, producing sophisticated responses to disturbances.

衰老及促智药影响神经细胞膜流动性机制的研究进展

细胞膜流动性通常是指膜脂质的流动性。神经细胞膜功能的正常进行要求膜脂质保持适宜的流动状 态。膜流动性改变将导致膜电位、离子通透性、跨膜物质运输、信号转导等一系列改变。老年动物及阿尔茨海 默氏病(AD) 患者脑神经细胞膜流动性显著降低, 主要与自由基增多引起的脂质过氧化反应、神经细胞钙平衡 失调有关, 此外, 还与其脑内神经元上的受体密度、β- 淀粉样蛋白沉积有关。促智药(吡咯烷酮类、人参皂 甙、银杏叶提取物EGb761) 能明显增强老年动物及AD 患者脑神经细胞膜的流动性。

The effects of centrally administered fluorocitrate via inhibiting glial cells on working memory in rats

Although prefrontal and hippocampal neurons are critical for spatial working memory, the function of glial cells in spatial working memory remains uncertain. In this study we investigated the function of glial cells in rats' working memory. The glial cell

SynGAP isoforms exert opposing effects on synaptic strength.

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

Active dendrites: Adaptation to spike-based communication

Computational analyses of dendritic computations often assume stationary inputs to neurons, ignoring the pulsatile nature of spike-based communication between neurons and the moment-to-moment fluctuations caused by such spiking inputs. Conversely, circuit computations with spiking neurons are usually formalized without regard to the rich nonlinear nature of dendritic processing. Here we address the computational challenge faced by neurons that compute and represent analogue quantities but communicate with digital spikes, and show that reliable computation of even purely linear functions of inputs can require the interplay of strongly nonlinear subunits within the postsynaptic dendritic tree.Our theory predicts a matching of dendritic nonlinearities and synaptic weight distributions to the joint statistics of presynaptic inputs. This approach suggests normative roles for some puzzling forms of nonlinear dendritic dynamics and plasticity.

A neuro-inspired method for data rate limited feedback control

The nervous system implements a networked control system in which the plants take the form of limbs, the controller is the brain, and neurons form the communication channels. Unlike standard networked control architectures, there is no periodic sampling, and the fundamental units of communication contain little numerical information. This paper describes a novel communication channel, modeled after spiking neurons, in which the transmitter integrates an input signal and sends out a spike when the integral reaches a threshold value. The reciever then filters the sequence of spikes to approximately reconstruct the input signal. It is shown that for appropriate choices of channel parameters, stable feedback control over these spiking channels is possible. Furthermore, good tracking performance can be achieved. The data rate of the channel increases linearly with the size of the inputs. Thus, when placed in a feedback loop, small loop gains imply a low data rate. ©2010 IEEE.

Neural representations of courtship song in the Drosophila brain.

Acoustic communication in drosophilid flies is based on the production and perception of courtship songs, which facilitate mating. Despite decades of research on courtship songs and behavior in Drosophila, central auditory responses have remained uncharacterized. In this study, we report on intracellular recordings from central neurons that innervate the Drosophila antennal mechanosensory and motor center (AMMC), the first relay for auditory information in the fly brain. These neurons produce graded-potential (nonspiking) responses to sound; we compare recordings from AMMC neurons to extracellular recordings of the receptor neuron population [Johnston's organ neurons (JONs)]. We discover that, while steady-state response profiles for tonal and broadband stimuli are significantly transformed between the JON population in the antenna and AMMC neurons in the brain, transient responses to pulses present in natural stimuli (courtship song) are not. For pulse stimuli in particular, AMMC neurons simply low-pass filter the receptor population response, thus preserving low-frequency temporal features (such as the spacing of song pulses) for analysis by postsynaptic neurons. We also compare responses in two closely related Drosophila species, Drosophila melanogaster and Drosophila simulans, and find that pulse song responses are largely similar, despite differences in the spectral content of their songs. Our recordings inform how downstream circuits may read out behaviorally relevant information from central neurons in the AMMC.

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

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

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

A Balance Equation Determines a Switch in Neuronal Excitability

We use the qualitative insight of a planar neuronal phase portrait to detect an excitability switch in arbitrary conductance-based models from a simple mathematical condition. The condition expresses a balance between ion channels that provide a negative feedback at resting potential (restorative channels) and those that provide a positive feedback at resting potential (regenerative channels). Geometrically, the condition imposes a transcritical bifurcation that rules the switch of excitability through the variation of a single physiological parameter. Our analysis of six different published conductance based models always finds the transcritical bifurcation and the associated switch in excitability, which suggests that the mathematical predictions have a physiological relevance and that a same regulatory mechanism is potentially involved in the excitability and signaling of many neurons. © 2013 Franci et al.

A novel phase portrait for neuronal excitability

Fifty years ago, FitzHugh introduced a phase portrait that became famous for a twofold reason: it captured in a physiological way the qualitative behavior of Hodgkin-Huxley model and it revealed the power of simple dynamical models to unfold complex firing patterns. To date, in spite of the enormous progresses in qualitative and quantitative neural modeling, this phase portrait has remained a core picture of neuronal excitability. Yet, a major difference between the neurophysiology of 1961 and of 2011 is the recognition of the prominent role of calcium channels in firing mechanisms. We show that including this extra current in Hodgkin-Huxley dynamics leads to a revision of FitzHugh-Nagumo phase portrait that affects in a fundamental way the reduced modeling of neural excitability. The revisited model considerably enlarges the modeling power of the original one. In particular, it captures essential electrophysiological signatures that otherwise require non-physiological alteration or considerable complexification of the classical model. As a basic illustration, the new model is shown to highlight a core dynamical mechanism by which calcium channels control the two distinct firing modes of thalamocortical neurons. © 2012 Drion et al.

Differentiated adipose-derived stem cells act synergistically with RGD-modified surfaces to improve neurite outgrowth in a co-culture model.

Peripheral nerve damage is a problem encountered after trauma and during surgery and the development of synthetic polymer conduits may offer a promising alternative to autografts. In order to improve the performance of the polymer to be used for nerve conduits, poly-ε-caprolactone (PCL) films were chemically functionalized with RGD moieties, using a chemical reaction previously developed. In vitro cultures of dissociated dorsal root ganglion (DRG) neurons provide a valid model to study different factors affecting axonal growth. In this work, DRG neurons were cultured on RGD-functionalized PCL films. Adult adipose-derived stem cells differentiated to Schwann cells (dASCs) were initially cultured on the functionalized PCL films, resulting in improved attachment and proliferation. dASCs were also co-cultured with DRG neurons on treated and untreated PCL to assess stimulation by dASCs on neurite outgrowth. Neuron response was generally poor on untreated PCL films, but long neurites were observed in the presence of dASCs or RGD moieties. A combination of the two factors enhanced even further neurite outgrowth, acting synergistically. Finally, in order to better understand the extracellular matrix (ECM)-cell interaction, a β1 integrin blocking experiment was carried out. Neurite outgrowth was not affected by the specific antibody blocking, showing that β1 integrin function can be compensated by other molecules present on the cell membrane. Copyright © 2013 John Wiley & Sons, Ltd.

Encoding of mixtures in a simple olfactory system.

Natural odors are usually mixtures; yet, humans and animals can experience them as unitary percepts. Olfaction also enables stimulus categorization and generalization. We studied how these computations are performed with the responses of 168 locust antennal lobe projection neurons (PNs) to varying mixtures of two monomolecular odors, and of 174 PNs and 209 mushroom body Kenyon cells (KCs) to mixtures of up to eight monomolecular odors. Single-PN responses showed strong hypoadditivity and population trajectories clustered by odor concentration and mixture similarity. KC responses were much sparser on average than those of PNs and often signaled the presence of single components in mixtures. Linear classifiers could read out the responses of both populations in single time bins to perform odor identification, categorization, and generalization. Our results suggest that odor representations in the mushroom body may result from competing optimization constraints to facilitate memorization (sparseness) while enabling identification, classification, and generalization.