Detecting Comparative Features of Comprehensive Geriatric Assessment through the International Classification of Functioning, Disability, and Health Linkage: A Web-Based Survey.

Multidimensional assessments are important in evaluating the overall health of older adults. The comprehensive geriatric assessment (CGA) is a representative framework; however, the burden associated with the CGA has led to the development of simplified multidimensional tools. Comparing these tools to the CGA can help utilize them effectively. However, a direct comparison is challenging owing to the conceptual nature of the CGA. In this study, we conducted a web-based survey to identify essential CGA components by linking International Classification of Functioning, Disability, and Health (ICF) category level 2 items and "not defined/not covered" (nd/nc) items. Healthcare professionals and individuals aged >65 years participated in a two-stage Delphi study. In total, 182 respondents (7 geriatricians, 22 nurses, 20 therapists, and 4 case managers) completed the survey. Sixty-one essential components for CGA were identified, including 55 ICF categories. Additionally, personal factors (i.e., proactiveness) and nd/nc items (i.e., subjective perceptions) were aggregated. The results suggest that the CGA includes objective conditions of intrinsic capacity, functional ability, and environment as well as subjective perceptions and proactiveness toward those conditions. Thus, CGA is not merely expected to assess geriatric syndrome but also to estimate broader concepts, such as interoception, resilience, and quality of life.

A computational model to explore how temporal stimulation patterns affect synapse plasticity.

Plasticity-related proteins (PRPs), which are synthesized in a synapse activation-dependent manner, are shared by multiple synapses to a limited spatial extent for a specific period. In addition, stimulated synapses can utilize shared PRPs through synaptic tagging and capture (STC). In particular, the phenomenon by which short-lived early long-term potentiation is transformed into long-lived late long-term potentiation using shared PRPs is called "late-associativity," which is the underlying principle of "cluster plasticity." We hypothesized that the competitive capture of PRPs by multiple synapses modulates late-associativity and affects the fate of each synapse in terms of whether it is integrated into a synapse cluster. We tested our hypothesis by developing a computational model to simulate STC, late-associativity, and the competitive capture of PRPs. The experimental results obtained using the model revealed that the number of competing synapses, timing of stimulation to each synapse, and basal PRP level in the dendritic compartment altered the effective temporal window of STC and influenced the conditions under which late-associativity occurs. Furthermore, it is suggested that the competitive capture of PRPs results in the selection of synapses to be integrated into a synapse cluster via late-associativity.

Multimodal Functional Analysis Platform: 3. Spherical Treadmill System for Small Animals.

In the application of advanced neuroscience techniques including optogenetics to small awake animals, it is often necessary to restrict the animal's movements. A spherical treadmill is a beneficial option that enables virtual locomotion of body- or head-restrained small animals. Besides, it has a wide application range, including virtual reality experiments. This chapter describes the fundamentals of a spherical treadmill for researchers who want to start experiments with it. First, we describe the physical aspect of a spherical treadmill based on the simple mechanical analysis. Next, we explain the basics of data logging and preprocessing for behavioral analysis. We also provide simple computer programs that work for the purpose.

Resting-state functional connectivity analysis of the mouse brain using intrinsic optical signal imaging of cerebral blood volume dynamics.

OBJECTIVE: Resting-state functional connectivity (rsFC) of the human brain is closely related with neurological and psychiatric disorders. Mice are widely used to investigate the physiological mechanisms of such disorders, because of the applicability of invasive experimental techniques. Thus, studies on rsFC of the mouse brain are essential to link physiological mechanisms with these disorders in humans. In this study, we investigated the applicability of intrinsic optical signal imaging of cerebral blood volume (IOSI-CBV) for rsFC analysis of the mouse brain. APPROACH: Transcranial IOSI-CBV images were collected from the brains of un-anesthetized wild-type mice with a cooled-CCD camera. The time traces of all pixels were averaged to create a global signal (GS). Marginal and partial correlation analyses were performed to estimate the rsFC based on CBV signals both with and without GS removal. The consistency of the results were confirmed by comparing them with to the rsFCs data reported in the previous studies. MAIN RESULTS: We confirmed that GS correlated with heart rate fluctuation in the FC frequency band. The marginal correlation coefficient of CBV with GS removal was consistent with measurements using conventional optical imaging methods relying on oxygenated hemoglobin concentration and cerebral blood flow. SIGNIFICANCE: These results suggest the applicability and usefulness of the transcranial IOSI-CBV method to estimate rsFC of the mouse brain.

Evaluation of multidrug cancer chronotherapy based on cell cycle model under influences of circadian clock.

The intracellular circadian clock mechanisms are known to affect various substantial cellular machinery such as cell cycle progression, inflammatory response, apoptosis, and DNA repair. Cancer growth in various tissues is still under circadian control, which may be at least partly underlain by the survived connections between the intracellular machinery and the clock. Considering such findings, chronotherapy has been applied to cancer treatments, in which anti-cancer drugs are administered in scheduled circadian times so as to resolve the trade-off between damages against the normal and cancer cells. However, any effective administration strategy has not yet been established especially in a quantitative sense. In this study, we develop an automaton model of cell division cycle interacting with circadian clock and suffering from a probability of cell death. A cancer cell is modeled by shortening/ lengthening the cell division interval and a transition to motility state under starving condition. Population proliferating dynamics in 3D space are simulated under the diffusion of nutrient factor and the anti-cancer drugs from a vessel. The simulation results show that the drug administration schedule could differentiate the damages against proliferation of normal and cancer cells. This implies the existence of optimal timing for the drug administration, which could provide an efficient strategy of chronotherapeutic treatment of cancer.

Reduction of light source noise from optical intrinsic signals of mouse neocortex by using independent component analysis.

Because the optical intrinsic signal (OIS) of the brain is very weak, noise reduction is essential. Independent component analysis (ICA) is widely used for noise reduction. However, the applicability of ICA to the reduction of light source (LS) noise has not been discussed in detail. In addition, determining the proper number of independent components (ICs) for decomposition is very important to a reasonable classification of the ICs. In this study, we considered the applicability of ICA to LS noise reduction by modeling the impact of LS noise on OIS data. We propose a method for determining the number of ICs that uses the power spectral density of LS noise. To evaluate its usefulness, the method was applied to real OIS data of a mouse's cerebral cortex.

Entrainability of cell cycle oscillator models with exponential growth of cell mass.

Among various aspects of cell cycle, understanding synchronization mechanism of cell cycle is important because of the following reasons. (1)Cycles of cell assembly should synchronize to form an organ. (2) Synchronizing cell cycles are required to experimental analysis of regulatory mechanisms of cell cycles. (3) Cell cycle has a distinct phase relationship with the other biological rhythms such as circadian rhythm. However, forced as well as mutual entrainment mechanisms are not clearly known. In this study, we investigated entrainability of cell cycle models of yeast cell under the periodic forcing to both of the cell mass and molecular dynamics. Dynamics of models under study involve the cell mass growing exponentially. In our result, they are shown to allow only a limited frequency range for being entrained by the periodic forcing. In contrast, models with linear growth are shown to be entrained in a wider frequency range. It is concluded that if the cell mass is included in the cell cycle regulation, its entrainability is sensitive to a shape of growth curve assumed in the model.

Development of distance-selective nerve recruitment for subcortical brain mapping by controlling stimulation waveforms.

During brain surgery, it is important to determine the functional brain area and cortico-cortical pathways so as to keep them intact and preserve patients' quality of life. Cortical and subcortical brain mappings are techniques that deliver direct current stimulation to the brain surface and beneath gray matter to identify the brain area and nerve fibers related to higher-order functions. However, because of the non-selective effect of conventional electrical stimulation methods, it has been difficult to obtain precise spatial distribution of nerve fibers in the subcortical region. We investigated the electrical stimulation of subcortical mapping to evaluate axon-to-electrode distance-selectivity. It was clarified that a conventional rectangular biphasic pulse activates axons non-selectively. We propose double exponential waveforms and show that they can recruit targeted fibers and change the location of a target by manipulating stimulus intensity. These results suggest the usefulness of introducing distance-selective stimulation into subcortical brain mapping.

Reconstruction of fetal vector electrocardiogram from maternal abdominal signals under fetus body rotations.

Fetal electrocardiogram (fECG) and its vector form (fVECG) could provide significant clinical information concerning physiological conditions of a fetus. So far various independent component analysis (ICA)-based methods for extracting fECG from maternal abdominal signals have been proposed. Because full extraction of component waves such as P, Q, R, S, and T, is difficult to be realized under noisy and nonstationary situations, the fVECG is further hard to be reconstructed, where different projections of the fetal heart vector are required. In order to reconstruct fVECG, we proposed a novel method for synthesizing different projections of the heart vector, making good use of the fetus movement. This method consists of ICA, estimation of rotation angles of fetus, and synthesis of projections of the heart vector. Through applications to the synthetic and actual data, our method is shown to precisely estimate rotation angle of the fetus and to successfully reconstruct the fVECG.

Suppression of anodal break excitation by electrical stimulation with down-staircase waveform for distance-selective nerve recruitment.

Electrical nerve stimulation using extracellular electrodes is widely performed in clinical medicine as well as basic medical science. It has been reported that selective recruitment of nerve fibers on the basis of the distance between the electrode and the axon is possible without moving the electrode and only by modifying the waveform of electrical stimulation. However, computer simulations have not reproduced the complete nature of the distance-selectivity of the stimulus owing to the difficulty in numerical analysis. In this paper, we propose a minor modification to the myelinated axon model to overcome this difficulty. We confirm that this modification improves the numerical stability of the simulation and enables us to obtain the spatio-temporal dynamics of axons, including the electrode-to-axon distance-dependency. In addition, we propose a novel stimulation method using a down-staircase waveform for distance-selective nerve recruitment. Simulations confirm that the method works well. We show the spatial distribution of axons activated by the down-staircase stimulation, which would be helpful to determine the stimulation parameters for distance-selective nerve recruitment.

Separation of multiunit signals by independent component analysis in complex-valued time-frequency domain.

Multiunit recording with a multi-electrode in the brain has been widely used in neuroscience studies. After the data recording, neuronal spikes should be sorted according to spike waveforms. For the spike sorting, independent component analysis (ICA) has recently been used because ICA potentially solves the problem to separate even overlapped multiple neuronal spikes into the single. However, we found that multiunit signals are recorded in each electrode channel with channel-specific delay. This situation does not satisfy the instantaneous mixture condition prerequisite for most of ICA algorithms. Actually, this delayed mixture situation was shown to degrade the performance of an ordinary ICA. In this study, in order to overcome this problem, complex-valued processing in the time-frequency domain is applied to multiunit signals by the wavelet transform. In the space spanned by the wavelet coefficients, the condition of instantaneous mixture is almost fulfilled. By application to a synthetic multiunit signal, the ICA algorithm extended to complex-valued signals makes much improvement in spike sorting performance so that even overlapped multiple spikes are successfully separated. Taken together, the complex-valued method could be a powerful tool for spike sorting.

Parameter exploration of staircase-shape extracellular stimulation for targeted stimulation of myelinated axon.

Spatio-temporal dynamics of a mathematical model of myelinated axon in response to staircase-shape extracellular electrical stimulation, which was developed for selective nerve stimulation, is investigated by the computer simulation. It is shown that the response is classified into four types: subthreshold response, cathodic excitation, anodal block and anodal break excitation. Based on the simulation results, simple diagrams representing the response characteristics of the axon are constructed as functions of stimulation parameters and distance between the axon and electrode. The diagram would be useful for determining simulation parameters for dynamic targeted stimulation of myelinated axon.

Enhancement of synchronization between hippocampal and amygdala theta waves associated with pontine wave density.

Theta waves in the amygdala are known to be synchronized with theta waves in the hippocampus. Synchronization between amygdala and hippocampal theta waves is considered important for neuronal communication between these regions during the memory-retrieval process. These theta waves are also observed during rapid eye movement (REM) sleep. However, few studies have examined the mechanisms and functions of theta waves during REM sleep. This study examined correlations between the dynamics of hippocampal and amygdala theta waves and pontine (P) waves in the subcoeruleus region, which activates many brain areas including the hippocampus and amygdala, during REM sleep in rats. We confirmed that the frequency of hippocampal theta waves increased in association with P wave density, as shown in our previous study. The frequency of amygdala theta waves also increased with in associated with P wave density. In addition, we confirmed synchronization between hippocampal and amygdala theta waves during REM sleep in terms of the cross-correlation function and found that this synchronization was enhanced in association with increased P wave density. We further studied theta wave synchronization associated with P wave density by lesioning the pontine subcoeruleus region. This lesion not only decreased hippocampal and amygdala theta frequency, but also degraded theta wave synchronization. These results indicate that P waves enhance synchronization between regional theta waves. Because hippocampal and amygdala theta waves and P waves are known to be involved in learning and memory processes, these results may help clarify these functions during REM sleep.

Multi-neuron action potentials recorded with tetrode are not instantaneous mixtures of single neuronal action potentials.

Multiunit recording with multi-site electrodes in the brain has been widely used in neuroscience studies. After the data recording, neuronal spikes should be sorted according to the pattern of spike waveforms. For the spike sorting, independent component analysis (ICA) has recently been used because ICA has potential for resolving the problem to separate the overlapped multiple neuronal spikes. However the performance of spike sorting by using ICA has not been examined in detail. In this study, we quantitatively evaluate the performance of ICA-based spike sorting method by using simulated multiunit signals. The simulated multiunit signal is constructed by compositing real extracellular action potentials recorded from guinea-pig brain. It is found that the spike sorting by using ICA hardly avoids significant false positive and negative errors due to the cross-talk noise contamination on the separated signals. The cross-talk occurs when the multiunit signal of each recording channel have significant time difference; this situation does not satisfy the assumption of instantaneous source mixture for the major ICA algorithms. Since the channel delay problem is hardly resolved, an ICA algorithm which does not require the instantaneous source mixing assumption would be appropriate for use of spike sorting.

Robustness of the blind source separation with reference against uncertainties of the reference signals.

The fetal electrocardiogram (ECG) could provide clinical information concerning physiological conditions of the fetus. In order to extract fetal ECG, we proposed the novel algorithm, the blind source separation with reference (BSSR), which successfully extracts a complete waveform of QRS complex and avoids uncertainty in the order of the extracted signals. In the BSSR, the reference signal is supposed to be generated from the ultrasonic Doppler signal. Thus generated reference is expected to suffer from uncertainties in waveform and occurrence timing. Based on simulations, the BSSR is shown to have robustness against the uncertainties of reference signals. In addition, it is shown how the robustness depends on the order of power of correlation function between the reference and extracted signals, which composes a performance function of the BSSR.

The 3D position estimation of neurons in the hippocampus based on the multi-site multi-unit recordings with silicon tetrodes.

The mechanical strain of the neural tissue induced by the implant of neuronal electrode is one of the important factors responsible for the quality and performance of extracellular recording of neuronal activities in the brain because the mechanical strain could kill or inactivate the neurons. In order to evaluate the effect of the implant of neural electrode, we propose a method to estimate the three-dimensional distribution of electrophysiologically active neurons near the electrode based on the multi-site multi-unit recording data. The spatial distribution of the active neurons emerges the region in the neural tissue that could be killed or inactivated by the implant of the electrode. The proposed method will be useful for the in situ assessment of the neural electrode implanted in the brain.

Phase-locking of spontaneous and tone-elicited pontine waves to hippocampal theta waves during REM sleep in rats.

Temporal relationships between hippocampal theta waves and pontine waves (P waves) during rapid-eye-movement (REM) sleep were investigated in rats. P waves were phase-locked to the positive theta peak. The phase relationships of P waves elicited by a tone stimulus (P(E) waves) to hippocampal theta waves were also analyzed to qualitatively clarify the mechanism of phase-locking between these two phenomena. P(E) waves occurred at the positive theta peak, as seen for spontaneous P waves. This phase preference of P(E) waves could be understood as that of the response probability to tone stimulus. These data suggest that the P-wave generator receives inputs that mimic theta waves. As hippocampal theta waves and P waves are known to be involved in learning and memory processes during REM sleep, the present studies could help to clarify these functions.

A novel extraction method of fetal electrocardiogram from the composite abdominal signal.

In contrast to the ultrasonic measurement of fetal heart motion, the fetal electrocardiogram (ECG) provides clinically significant information concerning the electrophysiological state of a fetus. In this paper, a novel method for extracting the fetal ECG from abdominal composite signals is proposed. This method consists of the cancellation of the mother's ECG and blind source separation with the reference signal (BSSR). The cancellation of the mother's ECG component was performed by subtracting the linear combination of mutually orthogonal projections of the heart vector. The BSSR is a fixed-point algorithm, the Lagrange function of which includes the higher order cross-correlation between the extracted signal and the reference signal as the cost term rather than a constraint. This realizes the convexity of the Lagrange function in a simple form, which guarantees the convergence of the algorithm. By practical application, the proposed method has been shown to be able to extract the P and T waves in addition to the R wave. The reliability and accuracy of the proposed method was confirmed by comparing the extracted signals with the directly recorded ECG at the second stage of labor. The gestational age-dependency of the physiological parameters of the extracted fetal ECG also coincided well with that of the magnetocardiogram, which proves the clinical applicability of the proposed method.

Measurement method for the fetal electrocardiogram.

A fetal electrocardiogram (ECG) provides clinically significant information concerning the electrophysiological states of a fetus. Since the first attempt by Cremer in 1906, for about 100 years nobody has been able to non-invasively extract the fetal ECG popularly used in clinical situations. The low amplitude of the fetal signals and the high background noise and the non-linearity of the ECG signals mainly have been interfering with the noninvasive extraction of the fetal ECG. The aim of this paper is to introduce a new nonlinear filtering method to extract the fetal electrocardiogram detected from the mother's abdominal wall. This method consists of two steps: The rough extraction step performed by blind source separation (BSS) with references and the precise extraction step with fast non-linear state space projection (FNSSP) based on a nonlinear state space projection (NSSP), which needs several complicated conditions or has limitations. So, it takes a lot of time to calculate. Our new method does not require such conditions, and it has about a thirty-fold speedup when compared with the previous method. Our new method has been successfully applied to on-line recordings with fetal components and will be useful for monitoring the fetal electrocardiogram in clinical applications.

A quartet neural system model orchestrating sleep and wakefulness mechanisms.

Physiological knowledge of the neural mechanisms regulating sleep and wakefulness has been advanced by the recent findings concerning sleep/wakefulness-related preoptic/anterior hypothalamic and perifornical (orexin-containing)/posterior hypothalamic neurons. In this paper, we propose a mathematical model of the mechanisms orchestrating a quartet neural system of sleep and wakefulness composed of the following: 1) sleep-active preoptic/anterior hypothalamic neurons (N-R group); 2) wake-active hypothalamic and brain stem neurons exhibiting the highest rate of discharge during wakefulness and the lowest rate of discharge during paradoxical or rapid eye movement (REM) sleep (WA group); 3) brain stem neurons exhibiting the highest rate of discharge during REM sleep (REM group); and 4) basal forebrain, hypothalamic, and brain stem neurons exhibiting a higher rate of discharge during both wakefulness and REM sleep than during nonrapid eye movement (NREM) sleep (W-R group). The WA neurons have mutual inhibitory couplings with the REM and N-R neurons. The W-R neurons have mutual excitatory couplings with the WA and REM neurons. The REM neurons receive unidirectional inhibition from the N-R neurons. In addition, the N-R neurons are activated by two types of sleep-promoting substances (SPS), which play different roles in the homeostatic regulation of sleep and wakefulness. The model well reproduces the actual sleep and wakefulness patterns of rats in addition to the sleep-related neuronal activities across state transitions. In addition, human sleep-wakefulness rhythms can be simulated by manipulating only a few model parameters: inhibitions from the N-R neurons to the REM and WA neurons are enhanced, and circadian regulation of the N-R and WA neurons is exaggerated. Our model could provide a novel framework for the quantitative understanding of the mechanisms regulating sleep and wakefulness.