It is widely held that long-term memory gradually develops in the temporal neocortex after initial memory encoding into the hippocampus. However, little is known as to whether and where long-term memory can be newly created in the human temporal neocortex. In this functional magnetic resonance imaging study, we detected brain activity in the temporal neocortex that was developed ∼8 weeks after study of unfamiliar pictorial paired associates. Two sets of paired Fourier figures were studied, one ∼8 weeks before test and the other immediately before test, keeping the correct performance during the tests balanced across the two sets of stimuli. Significant signal increase was observed in the right hippocampus during retrieval of newly studied pairs relative to initially studied pairs. In contrast, significant signal increase was observed in the anterior temporal cortex during retrieval of initially studied pairs relative to newly studied pairs. The greater activity during retrieval of older memory developed in the temporal neocortex provides direct evidence of formation of temporal neocortical representation for stable long-term memory.
Abstract In people with normal sight, mental simulation (motor imagery) of an experienced action involves a multisensory (especially kinesthetic and visual) emulation process associated with the action. Here, we examined how long-term blindness influences sensory experience during motor imagery and its neuronal correlates by comparing data obtained from blind and sighted people. We scanned brain activity with functional magnetic resonance imaging (fMRI) while 16 sighted and 14 blind male volunteers imagined either walking or jogging around a circle of 2 m radius. In the training before fMRI, they performed these actions with their eyes closed. During scanning, we explicitly instructed the blindfolded participants to generate kinesthetic motor imagery. After the experimental run, they rated the degree to which their motor imagery became kinesthetic or spatio-visual. The imagery of blind people was more kinesthetic as per instructions, while that of the sighted group became more spatio-visual. The imagery of both groups commonly activated bilateral frontoparietal cortices including supplementary motor areas (SMA). Despite the lack of group differences in degree of brain activation, we observed stronger functional connectivity between the SMA and cerebellum in the blind group compared to that in the sighted group. To conclude, long-term blindness likely changes sensory emulation during motor imagery to a more kinesthetic mode, which may be associated with stronger functional coupling in kinesthetic brain networks compared with that in sighted people. This study adds valuable knowledge on motor cognition and mental imagery processes in the blind.
In functional magnetic resonance imaging (fMRI) decoding studies using pattern classification, a second-level group statistical test is typically performed after first-level decoding analyses for individual participants. In the second-level test, the mean decoding accuracy across participants is often tested against the chance-level accuracy (for example, one-sample Student t-test) to check whether information about the label, such as, experimental condition or cognitive content, is included in brain activation. Meanwhile, Allefeld et al., (2016) highlighted that significant results for such tests only indicate that "there are some people in the population whose fMRI data carry information about the experimental condition." Therefore, such tests failed to conclude whether the effect is typical in the population. Based on this argument, they proposed an alternative method implementing the prevalence inference. In the present study, that method is extended to propose a novel statistical test called as the "information prevalence inference using the i-th order statistic" (i-test). The i-test has a high statistical power compared with the method proposed in Allefeld et al., (2016) and provides an inference regarding the typical effect in the population. In the i-test, the i-th lowest sample decoding accuracy (the i-th order statistic) is compared to the null distribution to verify whether the proportion of higher-than-chance decoding accuracy in the population (information prevalence) is higher than the threshold. Hence, a significant result in the i-test is interpreted as a majority of the population has information about the label in the brain. Theoretical details of the i-test are provided, its high statistical power is identified by numerical calculation, and the application of this method in an fMRI decoding is demonstrated.
During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs) including the default-mode network (DMN) and frontoparietal network (FPN). Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics), the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant energy were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.
Abstract Improving deteriorated sensorimotor functions in older individuals is a social necessity in a super-aging society. Previous studies suggested that the declined interhemispheric sensorimotor inhibition observed in older adults is associated with their deteriorated hand/finger dexterity. Here, we examined whether bimanual digit exercises, which can train the interhemispheric inhibitory system, improve deteriorated hand/finger dexterity in older adults. Forty-eight healthy, right-handed, older adults (65-78 years old) were divided into two groups, i.e., the bimanual (BM) digit training and right-hand (RH) training groups, and intensive daily training was performed for 2 months. Before and after the training, we evaluated individual right hand/finger dexterity using a peg task, and the individual state of interhemispheric sensorimotor inhibition by analyzing ipsilateral sensorimotor deactivation via functional magnetic resonance imaging when participants experienced a kinesthetic illusory movement of the right-hand without performing any motor tasks. Before training, the degree of reduction/loss of ipsilateral motor-cortical deactivation was associated with dexterity deterioration. After training, the dexterity improved only in the BM group, and the dexterity improvement was correlated with reduction in ipsilateral motor-cortical activity. The capability of the brain to inhibit ipsilateral motor-cortical activity during a simple right-hand sensory-motor task is tightly related to right-hand dexterity in older adults.
In recent years, several Japanese companies have attempted to improve the efficiency of their meetings, which has been a significant challenge. For instance, voice recognition technology is used to considerably improve meeting minutes creation. In an automatic minutes-creating system, identifying the speaker to add speaker information to the text would substantially improve the overall efficiency of the process. Therefore, a few companies and research groups have proposed speaker estimation methods; however, it includes challenges, such as requiring advance preparation, special equipment, and multiple microphones. These problems can be solved by using speech sections that are extracted from lip movements and voice information. When a person speaks, voice and lip movements occur simultaneously. Therefore, the speaker’s speech section can be extracted from videos by using lip movement and voice information. However, when this speech section contains only voice information, the voiceprint information of each meeting participant is required for speaker identification. When using lip movements, the speech section and speaker position can be extracted without the voiceprint information. Therefore, in this study, we propose a speech-section extraction method that uses image and voice information in Japanese for speaker identification. The proposed method consists of three processes: i) the extraction of speech frames using lip movements, ii) the extraction of speech frames using voices, and iii) the classification of speech sections using these extraction results. We used video data to evaluate the functionality of the method. Further, the proposed method was compared with state-of-the-art techniques. The average F-measure of the proposed method is determined to be higher than that of the conventional methods that are based on state-of-the-art techniques. The evaluation results showed that the proposed method achieves state-of-the-art performance using a simpler process compared to the conventional method.
We have succeeded in the first versatile iodoarene-catalyzed C−C bond-forming reactions by development of a new reoxidation system at low temperatures using stoichiometric bis(trifluoroacetyl) peroxide A in 2,2,2-trifluoroethanol (TFE). The catalytic system supplies a wide range of substrates and functional availabilities sufficient to be used in the key synthetic process of producing biologically important Amaryllidaceae alkaloids.
