Membrane potential response profiles of CA1 pyramidal cells probed with voltage-sensitive dye optical imaging in rat hippocampal slices reveal the impact of GABA(A)-mediated feed-forward inhibition in signal propagation.

The spatial and temporal distribution of excitatory and inhibitory membrane potential responses on a cell plays an important role in neuronal calculations in local neuronal circuits in the brain. The electrical dynamics of excitatory and inhibitory inputs along the somatodendritic extent of CA1 pyramidal cells during circuit activation were examined by stimulating strata radiatum (SR), oriens (SO), and lacunosum-moleculare (SLM) and measuring laminar responses with voltage-sensitive dye (VSD) optical recording methods. We first confirmed the linearity of the optical signal by comparing fluorescence changes in CA1 to global membrane potential changes when slices were bathed in high-potassium ([K+](O)=25 mM) solution. Except for a TTX-sensitive component in stratum pyramidale, fluorescence changes were equal in all strata, indicating that VSD sensitivity had reasonable linearity across layers. We then compared membrane potential profiles in slices exposed to picrotoxin, a GABA(A) receptor antagonist. We attributed the picrotoxin-induced changes in the first peak of the excitatory membrane potential to feed-forward inhibition and the later response (appearing 30 ms after stimulation) to feedback inhibition. A difference in feed-forward components was observed in perisomatic and distal apical dendritic regions after SR stimulation. SLM stimulation produced large differences in perisomatic and apical dendritic regions. SO stimulation, however, produced no feed-forward inhibition at the perisomatic region, but produces feed-forward inhibition in distal dendritic regions. These results suggest that actual inhibition of membrane potential response by feed-forward inhibition is greater at perisomatic regions after SR or SLM stimulation but is smaller at distal dendritic regions after SR, SO, and SLM stimulation.

Imaging of molecular dynamics regulated by electrical activities in neural circuits and in synapses.

One of the major challenges in brain research is to unravel a network of molecules, neurons, circuits and systems that are responsible for dynamic and hierarchical brain functions. To understand molecular events that occur in synapses could be an important key to exploring the mechanism of information processing. A spatiotemporal recording method is required to observe neuronal activities in a particular local circuit and to resolve single synaptic potential with high resolution. As alternative methods, real-time imaging using fluorescent probes and optical recording methods are also a powerful approach for investigating the molecular dynamics of biological events in neurons in vitro and in vivo. Recently, optical imaging techniques have become of great importance to visualize the molecular dynamics in a micron-sized compartment of a single neuron such as neuronal synapse. In general, the presynaptic axon forms synapses at the postsynaptic site on the dendritic spines in the mammalian central nervous system. Subsets of the synapses undergo a series of enduring changes in spine shape and density as well as alterations in electrophysiological functions. Here we describe recent optical imaging studies conducted by elaborate methods and techniques that provide evidence for the link between neural activity and molecular dynamics.

Cholinergic modulation of the spatiotemporal pattern of hippocampal activity in vitro.

The aim of this study was to use optical imaging with voltage-sensitive dyes (Di-4-ANEPPS), to examine the cholinergic modulation of CA1 network responses to Schaffer collateral input. By comparing responses recorded with optical imaging and field recordings across the proximodistal axis of CA1, it was initially demonstrated that voltage-sensitive dyes could report reliably both the pattern of activation and cholinergic modulation. The higher spatial resolution of optical imaging was used to explore the somatodendritic profile of cholinergic modulation. It was found that activation of muscarinic acetylcholine receptors (mAChR) (1-10 microM carbachol), inhibited evoked responses across all layers of CA1. This was accompanied by an increase in paired-pulse facilitation in the apical and distal dendritic layers (40 ms inter-stimulus interval), but not in perisomatic regions. The mAChR antagonist, 20 microM atropine, alone increased facilitation at perisomatic sites, suggesting that muscarinic signalling pathways actively suppress perisomatic responses to repetitive stimulation. In contrast, the activation of nicotinic acetylcholine receptors (10 microM nicotine) had no significant effect on single evoked responses, but selectively increased facilitation at perisomatic sites. These results suggest that cholinergic modulation of the hippocampal CA1 network has multiple differential effects on the somatodendritic processing of the Schaffer collateral input.

Editorial. The late professor Gen Matsumoto.

At the opening of this special issue dedicated to the work of the late Prof. Gen Matsumoto, I would like to look back at Gen Matsumoto's research life and to personally share with the readers of this journal his dream of creating a real brain-like computer. Gen Matsumoto had been planning to create a brain-like computer for thirty years. I have been most fortunate in being able to personally see progress toward Gen Matsumoto's ultimate goal, and have been inspired by his persistence, perseverance, and full belief that one day a brain-like computer would be operative. Gen Matsumoto left a definite impression on me so much, so that I considered him my reference of life rather than just my research partner.

The brain-computer: origin of the idea and progress in its realization.

The Brain-Computer is a physical analogue of a real organism which uses both a brain-inspired memory-based architecture and an output-driven learning algorithm. This system can be realized by creating a scaled-down model car that learns how to drive by heuristically connecting image processing with behavior control. This study proves that learning efficiency progresses rapidly when the acquired behaviors are prioritized. We develop a small real-world device that moves about purposefully in an artificial environment. The robot uses imaging information acquired through its random actions to make a mental map. This map, then, provides the cognitive structure for acquiring necessary information for autonomous behavior.

Expanded dynamic range of fluorescent indicators for Ca(2+) by circularly permuted yellow fluorescent proteins.

Fluorescence resonance energy transfer (FRET) technology has been used to develop genetically encoded fluorescent indicators for various cellular functions. Although most indicators have cyan- and yellow-emitting fluorescent proteins (CFP and YFP) as FRET donor and acceptor, their poor dynamic range often prevents detection of subtle but significant signals. Here, we optimized the relative orientation of the two chromophores in the Ca(2+) indicator, yellow cameleon (YC), by fusing YFP at different angles. We generated circularly permuted YFPs (cpYFPs) that showed efficient maturation and acid stability. One of the cpYFPs incorporated in YC absorbs a great amount of excited energy from CFP in its Ca(2+)-saturated form, thereby increasing the Ca(2+)-dependent change in the ratio of YFP/CFP by nearly 600%. Both in cultured cells and in the nervous system of transgenic mice, the new YC enables visualization of subcellular Ca(2+) dynamics with better spatial and temporal resolution than before. Our study provides an important guide for the development and improvement of indicators using GFP-based FRET.

Massively parallel classification of single-trial EEG signals using a min-max modular neural network.

This paper presents a method for classifying single-trial electroencephalogram (EEG) signals using min-max modular neural networks implemented in a massively parallel way. The method has three main steps. First, a large-scale, complex EEG classification problem is simply divided into a reasonable number of two-class subproblems, as small as needed. Second, the two-class subproblems are simply learned by individual smaller network modules in parallel. Finally, all the individual trained network modules are integrated into a hierarchical, parallel, and modular classifier according to two module combination laws. To demonstrate the effectiveness of the method, we perform simulations on fifteen different four-class EEG classification tasks, each of which consists of 1491 training and 636 test data. These EEG classification tasks were created using a set of non-averaged, single-trial hippocampal EEG signals recorded from rats; the features of the EEG signals are extracted using wavelet transform techniques. The experimental results indicate that the proposed method has several attractive features. 1) The method is appreciably faster than the existing approach that is based on conventional multilayer perceptrons. 2) Complete learning of complex EEG classification problems can be easily realized, and better generalization performance can be achieved. 3) The method scales up to large-scale, complex EEG classification problems.

Activity-dependent depression of excitability and calcium transients in the neurohypophysis suggests a model of "stuttering conduction".

Using millisecond time-resolved optical recordings of transmembrane voltage and intraterminal calcium, we have determined how activity-dependent changes in the population action potential are related to a concurrent modulation of calcium transients in the neurohypophysis. We find that repetitive stimulation dramatically alters the amplitude of the population action potential and significantly increases its temporal dispersion. The population action potentials and the calcium transients exhibit well correlated frequency-dependent amplitude depression, with broadening of the action potential playing only a limited role. High-speed camera recordings indicate that the magnitude of the spike modulation is uniform throughout the neurohypophysis, thereby excluding propagation failure as the underlying mechanism. In contrast, temporal dispersion and latency of the population spike do increase with distance from the stimulation site. This increase is enhanced during repeated stimulation and by raising the stimulation frequency. Changes in Ca influx directly affect the decline in population spike amplitude, consistent with electrophysiological measurements of the local loss of excitability in nerve terminals and varicosities, mediated by a Ca-activated K conductance. Our observations suggest a model of "stuttering conduction": repeated action potential stimulation causes excitability failures limited to nerve terminals and varicosities, which account for the rapid decline in the population spike amplitude. These failures, however, do not block action potential propagation but generate the cumulative increases in spike latency.

Optical imaging of long-lasting depolarization on burst stimulation in area CA1 of rat hippocampal slices.

Postsynaptic depolarization of dendrites paired with spike generation at the soma is considered to be a central mechanism of long-term potentiation (LTP) induction and a prime example of a Hebbian synapse. This pairing, however, has never been actually demonstrated on tetanic stimulation. Optical imaging of neural activity with a voltage-sensitive dye (VSD) is one potentially suitable method for examining this pairing. It is possible with optical recording to examine simultaneously the excitation of postsynaptic neurons at multiple sites. Thus the pairing of spike generation at the soma and dendritic depolarization can be examined with population level optical recording in highly laminar structures such as the hippocampal slice preparation. For example, one can correlate the optical signals obtained from cell layers with the activity of the soma, and, similarly, optical signals from stratum radiatum can be correlated with the activity of the apical dendrite, even though one cannot calibrate the optical signals in terms of actual membrane potential. Using the VSD aminonaphthylethenylpyridinium in rat hippocampal slices, we aimed to examine the pairing. Standard tetanic stimulation (100 Hz, 1 s) that elicited LTP in the field excitatory postsynaptic potential (fEPSP) resulted in a long-lasting depolarizing optical signal (about 2 s) that spread progressively along the known input pathway of CA1. The time course of this long-lasting depolarization was similar to that recorded intracellularly and to that reflected in the fEPSP. The long-lasting depolarization was insensitive to D,L-2-amino-5-phosphonovaleric acid (D,L-APV, 50 microM), but D,L-APV inhibited the induction of LTP; this allowed us to increase the signal-to-noise ratio of the optical signal by averaging several trials. Using this improved optical signal, we confirmed that postsynaptic cells practically "missed" spikes during tetanic stimulation in most parts of CA1, which had been suggested in the intracellular recordings. Intracellular recordings revealed a 23% reduction in input resistance, which might explain the failed spike generation at the soma via shunting. A steep spatial convergence of the depolarization along the transverse axis of area CA1 was observed. In contrast to the response resulting from a standard 100-Hz tetanus, broader activation, and paired depolarization with somatic spikes was observed on theta-burst stimulation. Overall we concluded that postsynaptic spike generation, at least in synchronous form, has less effect on LTP induction with standard tetanic stimulation, while theta-burst tetanic stimulation can elicit pairing of dendritic depolarization and somatic discharge.

Neurodegeneration with tau accumulation in a transgenic mouse expressing V337M human tau.

Formation of neurofibrillary tangles (NFTs) is a common neuropathological feature found in several neurodegenerative diseases, including Alzheimer's disease. We have developed a transgenic (Tg) mouse expressing mutant human tau (V337M), derived from frontotemporal dementia parkinsonism-17. V337M Tg mice revealed tau aggregations in the hippocampus, which fulfills the histological criteria for NFTs in human neurodegenerative diseases. Concurrent with the accumulation of RNA and phosphorylated tau, neurons exhibited morphological characteristics of degenerating neurons, which include a loss of microtubules, accumulation of ribosomes, plasma and nuclear membrane ruffling, and swelling of the Golgi network. Thus, mutant tau induces neuronal degeneration associated with the accumulation of RNA and phosphorylated tau. The functional consequences of this neuronal degeneration was evidenced by the reduction of hippocampal neural activity and behavioral abnormality in Tg mice.