Biomedical subjects

Hiroyuki Nakahara

Publications and source records attributed to Hiroyuki Nakahara.

10 recordsLinked to original sources

PubMed2003

Gene interaction in DNA microarray data is decomposed by information geometric measure.

MOTIVATION: Given the vast amount of gene expression data, it is essential to develop a simple and reliable method of investigating the fine structure of gene interaction. We show how an information geometric measure achieves this. RESULTS: We introduce an information geometric measure of binary random vectors and show how this measure reveals the fine structure of gene interaction. In particular, we propose an iterative procedure by using this measure (called IPIG). The procedure finds higher-order dependencies which may underlie the interaction between two genes of interest. To demonstrate the method, we investigate the interaction between the two genes of interest in the data from human acute lymphoblastic leukemia cells. The method successfully discovered biologically known findings and also selected other genes as hidden causes that constitute the interaction. AVAILABILITY: Softwares are currently not available but are possibly made available in future at http://www.mns.brain.riken.go.jp/~nakahara/DNA_pub.html where all the related information is also linked.

Algorithms↗

PubMed2003

Structure-stability-function relationships of dendritic spines.

Dendritic spines, which receive most of the excitatory synaptic input in the cerebral cortex, are heterogeneous with regard to their structure, stability and function. Spines with large heads are stable, express large numbers of AMPA-type glutamate receptors, and contribute to strong synaptic connections. By contrast, spines with small heads are motile and unstable and contribute to weak or silent synaptic connections. Their structure-stability-function relationships suggest that large and small spines are "memory spines" and "learning spines", respectively. Given that turnover of glutamate receptors is rapid, spine structure and the underlying organization of the actin cytoskeleton are likely to be major determinants of fast synaptic transmission and, therefore, are likely to provide a physical basis for memory in cortical neuronal networks. Characterization of supramolecular complexes responsible for synaptic memory and learning is key to the understanding of brain function and disease.

Animals↗

PubMed2003

Correlation of primate caudate neural activity and saccade parameters in reward-oriented behavior.

Changes in the reward context are associated with changes in neuronal activity in the basal ganglia as well as changes in motor outputs. A typical example is found in the caudate (CD) projection neurons and saccade parameters. It raised the possibility that the changes in CD neuronal activity contribute to the changes in saccade parameters. To examine this possibility, we calculated the correlation coefficients (CORs) of the firing rates of each neuron with saccade parameters (peak saccade velocity and latency) on a trial-by-trial basis. We then calculated the mean CORs separately for two CD populations: reward-enhanced type neurons (RENs) that showed enhanced activity and reward-depressed type neurons (RDNs) that showed depressed activity when reward was expected. The activity of RENs was positively correlated with the saccadic peak velocity and negatively correlated with the saccade latency. The activity of RDNs was not significantly correlated with the saccade parameters. We further analyzed the CORs for RENs, a major type of CD neurons. First, we examined the time courses of the CORs using a moving time window (duration: 200 ms). The positive correlation with the saccade velocity and the negative correlation with the saccade latency were present not only in the peri-saccadic period but also during the pre- and postcue periods. Second, we asked whether the CORs with the saccade parameters were direction-selective. A majority of RENs were more active before contralateral saccades (contralateral-preferring neurons) and their activity was correlated more strongly with contralateral saccades than with ipsilateral saccades. A minority of RENs, ipsilateral-preferring neurons, showed no such preference. These results are consistent with the hypothesis that CD neuronal activity exerts facilitatory effects on contralateral saccades and that the effects start well before saccade execution. Furthermore, a multiple regression analysis indicated that changes in activity of some, but not all, CD neurons could be explained by changes in saccade parameters; a major determinant was reward context (presence or absence of reward). These results suggest that, while a majority of CD neurons receive reward-related signals, only some of them can make a significant contribution to change saccadic outputs based on expected reward.

Animals↗

PubMed2003

Synchronous firing and higher-order interactions in neuron pool.

The stochastic mechanism of synchronous firing in a population of neurons is studied from the point of view of information geometry. Higher-order interactions of neurons, which cannot be reduced to pairwise correlations, are proved to exist in synchronous firing. In a neuron pool where each neuron fires stochastically, the probability distribution q(r) of the activity r, which is the fraction of firing neurons in the pool, is studied. When q(r) has a widespread distribution, in particular, when q(r) has two peaks, the neurons fire synchronously at one time and are quiescent at other times. The mechanism of generating such a probability distribution is interesting because the activity r is concentrated on its mean value when each neuron fires independently, because of the law of large numbers. Even when pairwise interactions, or third-order interactions, exist, the concentration is not resolved. This shows that higher-order interactions are necessary to generate widespread activity distributions. We analyze a simple model in which neurons receive common overlapping inputs and prove that such a model can have a widespread distribution of activity, generating higher-order stochastic interactions.

Neurons↗

PubMed2002

Effects of drug treatment on bone strength and structural changes with aging: an experimental study in rats.

The purpose of the present study was to evaluate the profiles of the bone strength of rats treated from infancy with various drugs. Young female Sprague-Dawley rats were classified into five groups according to the composition of their diets. They underwent resection of their femurs for a three-point flexion test and an impaction test at 6, 8, 12, and 16 months of age. A microcomputed tomography unit was used to evaluate the microstructure of their femoral condyles at 16 months of age. The diet given to the rats in the control group contained 0.5% Ca. The rats in groups A, B, C, and D were placed on the following regimens, respectively: vitamin K mixed diet, vitamin D oral administration, 1.8% Ca-fortified diet, and 1.8% Ca-fortified diet plus vitamin K and vitamin D. In the impaction tests conducted on the rats at each age, the results from groups A and B were nearly the same as those from the control group. At 16 months of age, the rats in groups C and D had significantly higher test results than those in the control group. In the three-point flexion tests at 16 months of age, the results from groups A, B, and C were nearly the same as those from the control group. The results from group D, however, showed a significant increase. Examination of the microstructure of the femoral condyles at 16 months of age revealed controlled destruction of the trabecular structure in groups C and D. These findings suggest that supplementing the diet from infancy with Ca, vitamin K, and vitamin D might prevent bone fractures due to osteoporosis.

Animals↗

PubMed2002

Central mechanisms of motor skill learning.

Recent studies have shown that frontoparietal cortices and interconnecting regions in the basal ganglia and the cerebellum are related to motor skill learning. We propose that motor skill learning occurs independently and in different coordinates in two sets of loop circuits: cortex-basal ganglia and cortex-cerebellum. This architecture accounts for the seemingly diverse features of motor learning.

Animals↗

PubMed2002

Self-organization in the basal ganglia with modulation of reinforcement signals.

Self-organization is one of fundamental brain computations for forming efficient representations of information. Experimental support for this idea has been largely limited to the developmental and reorganizational formation of neural circuits in the sensory cortices. We now propose that self-organization may also play an important role in short-term synaptic changes in reward-driven voluntary behaviors. It has recently been shown that many neurons in the basal ganglia change their sensory responses flexibly in relation to rewards. Our computational model proposes that the rapid changes in striatal projection neurons depend on the subtle balance between the Hebb-type mechanisms of excitation and inhibition, which are modulated by reinforcement signals. Simulations based on the model are shown to produce various types of neural activity similar to those found in experiments.

Algorithms↗

PubMed2002

Information-geometric measure for neural spikes.

This study introduces information-geometric measures to analyze neural firing patterns by taking not only the second-order but also higher-order interactions among neurons into account. Information geometry provides useful tools and concepts for this purpose, including the orthogonality of coordinate parameters and the Pythagoras relation in the Kullback-Leibler divergence. Based on this orthogonality, we show a novel method for analyzing spike firing patterns by decomposing the interactions of neurons of various orders. As a result, purely pairwise, triple-wise, and higher-order interactions are singled out. We also demonstrate the benefits of our proposal by using several examples.

Action Potentials↗

PubMed2002

Population coding and decoding in a neural field: a computational study.

This study uses a neural field model to investigate computational aspects of population coding and decoding when the stimulus is a single variable. A general prototype model for the encoding process is proposed, in which neural responses are correlated, with strength specified by a gaussian function of their difference in preferred stimuli. Based on the model, we study the effect of correlation on the Fisher information, compare the performances of three decoding methods that differ in the amount of encoding information being used, and investigate the implementation of the three methods by using a recurrent network. This study not only rediscovers main results in existing literatures in a unified way, but also reveals important new features, especially when the neural correlation is strong. As the neural correlation of firing becomes larger, the Fisher information decreases drastically. We confirm that as the width of correlation increases, the Fisher information saturates and no longer increases in proportion to the number of neurons. However, we prove that as the width increases further--wider than (sqrt)2 times the effective width of the turning function--the Fisher information increases again, and it increases without limit in proportion to the number of neurons. Furthermore, we clarify the asymptotic efficiency of the maximum likelihood inference (MLI) type of decoding methods for correlated neural signals. It shows that when the correlation covers a nonlocal range of population (excepting the uniform correlation and when the noise is extremely small), the MLI type of method, whose decoding error satisfies the Cauchy-type distribution, is not asymptotically efficient. This implies that the variance is no longer adequate to measure decoding accuracy.

Neural Networks, Computer↗

PubMed2001

Modulation of saccadic eye movements by predicted reward outcome.

Reward is a primary goal of behavior and is crucial for survival of animals. To explore the mechanisms underlying such reward-oriented behavior, we devised a memory-guided saccade task in which only one fixed direction out of four was rewarded, which was called the one-direction-rewarded task (1DR). As the rewarded direction was changed in four blocks, saccades in a given direction were rewarded in one block (constituting reward-oriented behavior), but non-rewarded in the other blocks (non-reward-oriented behavior). As a control, an all-directions-rewarded task (ADR) was used. Using these tasks, we found that the parameters of saccades changed depending on whether or not the saccade was followed by reward. (1) The mean saccadic peak velocity was higher and the mean saccade latency was shorter in the rewarded condition than in the non-rewarded condition. (2) The mean saccade amplitude showed no difference in two out of three monkeys. (3) The variations of saccadic velocity, latency and amplitude were smaller in the rewarded condition. (4) Within a block of 1DR, the saccade velocity remained high in the rewarded condition, but decreased gradually in the non-rewarded condition; it decreased only slightly in ADR. The saccade latency showed the opposite pattern of change, but less clearly. (5) The saccades in the non-rewarded condition tended to have slower velocities and longer latencies in the trials shortly after a rewarded trial. (6) The ratio of error trials was much higher in the non-rewarded condition than the rewarded condition. (7) The errors, which were due to premature or incorrect saccades, showed unique spatiotemporal patterns that would reflect the competition between the cognitive and motivational processes. These results provide important constraints to the neuronal mechanism underlying reward-oriented behavior because it must satisfy these rules.

Animals↗