Hippocampal formation-inspired probabilistic generative model.

In building artificial intelligence (AI) agents, referring to how brains function in real environments can accelerate development by reducing the design space. In this study, we propose a probabilistic generative model (PGM) for navigation in uncertain environments by integrating the neuroscientific knowledge of hippocampal formation (HF) and the engineering knowledge in robotics and AI, namely, simultaneous localization and mapping (SLAM). We follow the approach of brain reference architecture (BRA) (Yamakawa, 2021) to compose the PGM and outline how to verify the model. To this end, we survey and discuss the relationship between the HF findings and SLAM models. The proposed hippocampal formation-inspired probabilistic generative model (HF-PGM) is designed to be highly consistent with the anatomical structure and functions of the HF. By referencing the brain, we elaborate on the importance of integration of egocentric/allocentric information from the entorhinal cortex to the hippocampus and the use of discrete-event queues.

Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling.

Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation. To better enable a longitudinal investigation into a patient's muscle activation changes during rehabilitation or an inter-subject comparison, EMG normalization is usually applied. However, current normalization methods using maximum voluntary contraction (MVC) or within-task peak/mean EMG may not be feasible when MVC cannot be obtained from stroke survivors due to motor paralysis and the subject of comparison is EMG amplitude. Here, focusing on the paretic side, we first propose a novel, joint torque-based normalization method that incorporates musculoskeletal modeling, forward dynamics simulation, and mathematical optimization. Next, upon method validation, we apply it to quantify changes in muscle tension and muscle synergy activation levels in STS motor control units for patients in subacute stroke rehabilitation. The novel method was validated against MVC-normalized EMG data from eight healthy participants, and it retained muscle activation amplitude differences for inter- and intra-subject comparisons. The proposed joint torque-based method was also compared with the common static optimization based on squared muscle activation and showed higher simulation accuracy overall. Serial STS measurements were conducted with four post-stroke patients during their subacute rehabilitation stay (137 ± 22 days) in the hospital. Quantitative results of patients suggest that maximum muscle tension and activation level of muscle synergy temporal patterns may reflect the effectiveness of subacute stroke rehabilitation. A quality comparison between muscle synergies computed with the conventional within-task peak/mean EMG normalization and our proposed method showed that the conventional was prone to activation amplitude overestimation and underestimation. The contributed method and findings help recapitulate and understand the post-stroke motor recovery process, which may facilitate developing more effective rehabilitation strategies for future stroke survivors.

A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots.

Building a human-like integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthermore, a computational model that enables an artificial system to achieve cognitive development will be an excellent reference for brain and cognitive science. This paper describes an approach to develop a cognitive architecture by integrating elemental cognitive modules to enable the training of the modules as a whole. This approach is based on two ideas: (1) brain-inspired AI, learning human brain architecture to build human-level intelligence, and (2) a probabilistic generative model (PGM)-based cognitive architecture to develop a cognitive system for developmental robots by integrating PGMs. The proposed development framework is called a whole brain PGM (WB-PGM), which differs fundamentally from existing cognitive architectures in that it can learn continuously through a system based on sensory-motor information. In this paper, we describe the rationale for WB-PGM, the current status of PGM-based elemental cognitive modules, their relationship with the human brain, the approach to the integration of the cognitive modules, and future challenges. Our findings can serve as a reference for brain studies. As PGMs describe explicit informational relationships between variables, WB-PGM provides interpretable guidance from computational sciences to brain science. By providing such information, researchers in neuroscience can provide feedback to researchers in AI and robotics on what the current models lack with reference to the brain. Further, it can facilitate collaboration among researchers in neuro-cognitive sciences as well as AI and robotics.

Conveying Intention by Motions With Awareness of Information Asymmetry.

Humans sometimes attempt to infer an artificial agent's mental state based on mere observations of its behavior. From the agent's perspective, it is important to choose actions with awareness of how its behavior will be considered by humans. Previous studies have proposed computational methods to generate such publicly self-aware motion to allow an agent to convey a certain intention by motions that can lead a human observer to infer what the agent is aiming to do. However, little consideration has been given to the effect of information asymmetry between the agent and a human, or to the gaps in their beliefs due to different observations from their respective perspectives. This paper claims that information asymmetry is a key factor for conveying intentions with motions. To validate the claim, we developed a novel method to generate intention-conveying motions while considering information asymmetry. Our method utilizes a Bayesian public self-awareness model that effectively simulates the inference of an agent's mental states as attributed to the agent by an observer in a partially observable domain. We conducted two experiments to investigate the effects of information asymmetry when conveying intentions with motions by comparing the motions from our method with those generated without considering information asymmetry in a manner similar to previous work. The results demonstrate that by taking information asymmetry into account, an agent can effectively convey its intention to human observers.

Classification of Motor Impairments of Post-Stroke Patients Based on Force Applied to a Handrail.

Many patients suffer from declined motor abilities after a brain injury. To provide appropriate rehabilitation programs and encourage motor-impaired patients to participate further in rehabilitation, sufficient and easy evaluation methodologies are necessary. This study is focused on the sit-to-stand motion of post-stroke patients because it is an important daily activity. Our previous study utilized muscle synergies (synchronized muscle activation) to classify the degree of motor impairment in patients and proposed appropriate rehabilitation methodologies. However, in our previous study, the patient was required to attach electromyography sensors to his/her body; thus, it was difficult to evaluate motor ability in daily circumstances. Here, we developed a handrail-type sensor that can measure the force applied to it. Using temporal features of the force data, the relationship between the degree of motor impairment and temporal features was clarified, and a classification model was developed using a random forest model to determine the degree of motor impairment in hemiplegic patients. The results show that hemiplegic patients with severe motor impairments tend to apply greater force to the handrail and use the handrail for a longer period. It was also determined that patients with severe motor impairments did not move forward while standing up, but relied more on the handrail to pull their upper body upward as compared to patients with moderate impairments. Furthermore, based on the developed classification model, patients were successfully classified as having severe or moderate impairments. The developed classification model can also detect long-term patient recovery. The handrail-type sensor does not require additional sensors on the patient's body and provides an easy evaluation methodology.

The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the brain.

The vastness of the design space that is created by the combination of numerous computational mechanisms, including machine learning, is an obstacle to creating artificial general intelligence (AGI). Brain-inspired AGI development; that is, the reduction of the design space to resemble a biological brain more closely, is a promising approach for solving this problem. However, it is difficult for an individual to design a software program that corresponds to the entire brain as the neuroscientific data that are required to understand the architecture of the brain are extensive and complicated. The whole-brain architecture approach divides the brain-inspired AGI development process into the task of designing the brain reference architecture (BRA), which provides the flow of information and a diagram of the corresponding components, and the task of developing each component using the BRA. This is known as BRA-driven development. Another difficulty lies in the extraction of the operating principles that are necessary for reproducing the cognitive-behavioral function of the brain from neuroscience data. Therefore, this study proposes structure-constrained interface decomposition (SCID), which is a hypothesis-building method for creating a hypothetical component diagram that is consistent with neuroscientific findings. The application of this approach has been initiated for constructing various regions of the brain. In the future, we will examine methods for evaluating the biological plausibility of brain-inspired software. This evaluation will also be used to prioritize different computational mechanisms, which should be integrated and associated with the same regions of the brain.

Modified sensory feedback enhances the sense of agency during continuous body movements in virtual reality.

The sense of agency refers to the feeling of control over one's own actions, and through them, the external events. This study examined the effect of modified visual feedback on the sense of agency over one's body movements using virtual reality in healthy individuals whose motor control was disturbed. Participants moved a virtual object using their right hand to trace a trajectory (Experiment 1) or a leading target (Experiment 2). Their motor control was disturbed by a delay in visual feedback (Experiment 1) or a 1-kg weight attached to their wrist (Experiment 2). In the offset conditions, the virtual object was presented at the median point between the desired position and the participants' actual hand position. In both experiments, participants reported improved sense of agency in the offset condition compared to the aligned condition where the visual feedback reflected their actual body movements, despite their motion being less precise in the offset condition. The results show that sense of agency can be enhanced by modifying feedback to motor tasks according to the goal of the task, even when visual feedback is discrepant from the actual body movements. The present study sheds light on the possibility of artificially enhancing body agency to improve voluntary motor control.

Revealing the Computational Meaning of Neocortical Interarea Signals.

To understand the function of the neocortex, which is a hierarchical distributed network, it is useful giving meaning to the signals transmitted between these areas from the computational viewpoint. The overall anatomical structure or organs related to this network, including the neocortex, thalamus, and basal ganglia, has been roughly revealed, and much physiological knowledge, though often fragmentary, is being accumulated. The computational theories involving the neocortex have also been developed considerably. By introducing the assumption "The signals transmitted by interarea axonal projections of pyramidal cells in the neocortex carry different meanings for each cell type, common to all areas," derived from its nature as a distributed network in the neocortex, allows us to specify the computational meanings of interarea signals. In this paper, first, the types of signals exchanged between neocortical areas are investigated, taking into account biological constraints, and employing theories such as predictive coding, reinforcement learning, representation emulation theory, and BDI logic as theoretical starting points, two types of feedforward signals (observation and deviation) and three types of feedback signals (prediction, plan, and intention) are identified. Next, based on the anatomical knowledge of the neocortex and thalamus, the pathways connecting the areas are organized and summarized as three corticocortical pathways and two thalamocortical pathways. Using this summation as preparation, this paper proposes a hypothesis that gives meaning to each type of signals transmitted in the different pathways in the neocortex, from the viewpoint of their functions. This hypothesis reckons that the feedforward corticocortical pathway transmits observation signals, the feedback corticocortical pathway transmits prediction signals, and the corticothalamic pathway mediated by core relay cells transmits deviation signals. The thalamocortical pathway, which is mediated by matrix relay cells, would be responsible for transmitting the signals that activate a part of prediction signals as intentions, due to the reason that the nature of the other available feedback pathways are not sufficient for conveying plans and intentions as signals. The corticocortical pathway, which is projected from various IT cells to the first layer, would be responsible for transmitting signals that activate a part of prediction signals as plans.

Distinct Mechanisms of Over-Representation of Landmarks and Rewards in the Hippocampus.

In the hippocampus, locations associated with salient features are represented by a disproportionately large number of neurons, but the cellular and molecular mechanisms underlying this over-representation remain elusive. Using longitudinal calcium imaging in mice learning to navigate in virtual reality, we find that the over-representation of reward and landmark locations are mediated by persistent and separable subsets of neurons, with distinct time courses of emergence and differing underlying molecular mechanisms. Strikingly, we find that in mice lacking Shank2, an autism spectrum disorder (ASD)-linked gene encoding an excitatory postsynaptic scaffold protein, the learning-induced over-representation of landmarks was absent whereas the over-representation of rewards was substantially increased, as was goal-directed behavior. These findings demonstrate that multiple hippocampal coding processes for unique types of salient features are distinguished by a Shank2-dependent mechanism and suggest that abnormally distorted hippocampal salience mapping may underlie cognitive and behavioral abnormalities in a subset of ASDs.

Identifying Core Regions for Path Integration on Medial Entorhinal Cortex of Hippocampal Formation.

Path integration is one of the functions that support the self-localization ability of animals. Path integration outputs position information after an animal's movement when initial-position and movement information is input. The core region responsible for this function has been identified as the medial entorhinal cortex (MEC), which is part of the hippocampal formation that constitutes the limbic system. However, a more specific core region has not yet been identified. This research aims to clarify the detailed structure at the cell-firing level in the core region responsible for path integration from fragmentarily accumulated experimental and theoretical findings by reviewing 77 papers. This research draws a novel diagram that describes the MEC, the hippocampus, and their surrounding regions by focusing on the MEC's input/output (I/O) information. The diagram was created by summarizing the results of exhaustively scrutinizing the papers that are relative to the I/O relationship, the connection relationship, and cell position and firing pattern. From additional investigations, we show function information related to path integration, such as I/O information and the relationship between multiple functions. Furthermore, we constructed an algorithmic hypothesis on I/O information and path-integration calculation method from the diagram and the information of functions related to path integration. The algorithmic hypothesis is composed of regions related to path integration, the I/O relations between them, the calculation performed there, and the information representations (cell-firing pattern) in them. Results of examining the hypothesis confirmed that the core region responsible for path integration was either stellate cells in layer II or pyramidal cells in layer III of the MEC.

Temporal Features of Muscle Synergies in Sit-to-Stand Motion Reflect the Motor Impairment of Post-Stroke Patients.

Sit-to-stand (STS) motion is an important daily activity, and many post-stroke patients have difficulty performing STS motion. Previous studies found that there are four muscle synergies (synchronized muscle activations) in the STS motion of healthy adults. However, for post-stroke patients, it is unclear whether muscle synergies change and which features primarily reflect motor impairment. Here, we use a machine learning method to demonstrate that temporal features in two muscle synergies that contribute to hip rising and balance maintenance motion reflect the motor impairment of post-stroke patients. Analyzing the muscle synergies of age-matched healthy elderly people ( n = 12 ) and post-stroke patients ( n = 33 ), we found that the same four muscle synergies could account for the muscle activity of post-stroke patients. Also, we were able to distinguish post-stroke patients from healthy people on the basis of the temporal features of these muscle synergies. Furthermore, these temporal features were found to correlate with motor impairment of post-stroke patients. We conclude that post-stroke patients can still utilize the same number of muscle synergies as healthy people, but the temporal structure of muscle synergies changes as a result of motor impairment. This could lead to a new rehabilitation strategy for post-stroke patients that focuses on activation timing of muscle synergies.

Organization of functional modularity in sitting balance response and gait performance after stroke.

BACKGROUND: Recovery of postural adjustment, especially when seated, is important for performing activities of daily living after stroke. However, conventional clinical measures provide little insight into a common strategy for dynamic sitting balance and gait. We aimed to evaluate functional re-organization of posture and ambulatory performance after stroke. METHODS: The subjects of the study included 5 healthy men and 21 post-stroke patients. The spatiotemporal modular organization of ground reaction forces during a balance task in which the leg on the non-affected side was lifted off the ground while seated was quantified by using complex principal component analysis. FINDINGS: A 3% decrease in the temporal strength of the primary module in post-stroke patients was an independent predictor of gait performance in the hospital setting with high sensitivity and specificity. Tuning of the temporal strength was accompanied by the recovery of sitting and ambulation. INTERPRETATION: Our findings suggest that evaluation of the modular characteristics of ground reaction forces during a sitting balance task allows us to predict recovery and functional adaptation through daily physical rehabilitation.

Improvement of Sense of Agency During Upper-Limb Movement for Motor Rehabilitation Using Virtual Reality.

Sense of agency refers to the feeling of controlling one's own body. Many patients surviving from a stroke lose the sense of agency over their body. This is due to impairments in both motor control and sensory brain functions. As a result of this lack in the sense of agency, stroke patients tend to lose the intention of moving the paralyzed limb, which results in further deterioration of brain functions and worsening muscles and joints. The present study proposes a motor rehabilitation system using virtual reality to improve the sense of agency during upper-limb movement which is required for various daily life activities such as eating meals and operating devices. Specifically, participants were instructed to move their hand to track a moving target ball in a virtual reality environment, while the position of their real hand was measured via a motion capture system. Participants were shown another ball presenting the position of their hand in virtual reality. We tested the proposed system with healthy participants, of which the motor control was disturbed by a 1-kg weight attached on the wrist. Participants reported their sense of agency after each trial. The results showed that the sense of agency was enhanced by the proposed intervention. Our results pointed out a potentially useful method to improve the sense of agency during body movements using modified visual feedback, which may contribute to the development of rehabilitation for stroke patients.

The Readiness Potential Reflects the Reliability of Action Consequence.

Humans are capable of associating actions with their respective consequences if there is reliable contingency between them. The present study examined the link between the reliability of action consequence and the readiness potential (RP), which is a negative potential observed from about 1-2 s prior to the onset of an action with electroencephalography. In a condition of constant outcome, the participants' voluntary action always triggered beep sounds; thus, they were able to perceive the contingency between their action and the sound. In contrast, in a condition of inconstant outcome, the participants' actions only triggered the sound in half the trials. We found that both the early and late RPs were larger in the condition of constant compared to the condition of inconstant outcome. Our results showed that the RPs preceding the voluntary action reflected the reliability of action consequence. In other words, the action-effect contingency enhanced neural activities prior to the action.

Visual and Vestibular Inputs Affect Muscle Synergies Responsible for Body Extension and Stabilization in Sit-to-Stand Motion.

The sit-to-stand motion is a common movement in daily life and understanding the mechanism of the sit-to-stand motion is important. Our previous study shows that four muscle synergies can characterize the sit-to-stand motion, and they have specific roles, such as upper body flexion, rising from a chair, body extension, and posture stabilization. The time-varying weight of these synergies are changed to achieve adaptive movement. However, the relationship between sensory input and the activation of the muscle synergies is not completely understood. In this paper, we aim to clarify how vestibular and visual inputs affect the muscle synergy in sit-to-stand motion. To address this, we conducted experiments as follows. Muscle activity, body kinematics, and ground reaction force were measured for the sit-to-stand motion under three different conditions: control, visual-disturbance, and vestibular-disturbance conditions. Under the control condition, the participants stood without any intervention. Under the visual-disturbance condition, the participants wore convex lens glasses and performed the sit-to-stand motion in a dark room. Under the vestibular-disturbance condition, a caloric test was performed. Muscle synergies were calculated for these three conditions using non-negative matrix factorization. We examined whether the same four muscle synergies were employed under each condition, and the changes in the time-varying coefficients were determined. These experiments were conducted on seven healthy, young participants. It was found that four muscle synergies could explain the muscle activity in the sit-to-stand motion under the three conditions. However, there were significant differences in the time-varying weight coefficients. When the visual input was disturbed, a larger amplitude was found for the muscle synergy that activated mostly in the final posture stabilization phase of the sit-to-stand motion. Under vestibular-disturbance condition, a longer activation was observed for the synergies that extended the entire body and led to posture stabilization. The results implied that during human sit-to-stand motion, visual input has less contribution to alter or correct activation of muscle synergies until the last phase. On the other hand, duration of muscle synergies after the buttocks leave are prolonged in order to adapt to the unstable condition in which sense of verticality is decreased under vestibular-disturbance.

Protective Effects of Mekabu Aqueous Solution Fermented by Lactobacillus plantarum Sanriku-SU7 on Human Enterocyte-Like HT-29-luc Cells and DSS-Induced Murine IBD Model.

Most wakame Undaria pinnatifida, a brown algae, products are made from the frond portion. In this study, the polysaccharide content and antioxidant property of aqueous extract solutions (AESs) of the four parts (frond: wakame, stem of the frond: kuki-wakame, sporophyll: mekabu, and kuki-mekabu) of wakame were investigated. Polysaccharide content was high in both the wakame and mekabu. Superoxide anion (O2-) radical-scavenging capacities were high in the mekabu. These AESs could be fermented by Lactobacillus plantarum Sanriku-SU7. The O2- radical-scavenging activity of the kuki-wakame, mekabu, and kuki-mekabu were increased by the fermentation. Fermented mekabu clearly showed a protective effect on human enterocyte-like HT-29-luc cells and in a mouse model of dextran sodium sulphate-induced inflammatory bowel disease (IBD). These results suggest that the mekabu fermented by L. plantarum Sanriku-SU7 has anti-IBD effect related to O2- radical-scavenging.

Strength of Intentional Effort Enhances the Sense of Agency.

Sense of agency (SoA) refers to the feeling of controlling one's own actions, and the experience of controlling external events with one's actions. The present study examined the effect of strength of intentional effort on SoA. We manipulated the strength of intentional effort using three types of buttons that differed in the amount of force required to depress them. We used a self-attribution task as an explicit measure of SoA. The results indicate that strength of intentional effort enhanced self-attribution when action-effect congruency was unreliable. We concluded that intentional effort importantly affects the integration of multiple cues affecting explicit judgments of agency when the causal relationship action and effect was unreliable.

Goal-Directed Movement Enhances Body Representation Updating.

Body representation refers to perception, memory, and cognition related to the body and is updated continuously by sensory input. The present study examined the influence of goals on body representation updating with two experiments of the rubber hand paradigm. In the experiments, participants moved their hidden left hands forward and backward either in response to instruction to touch a virtual object or without any specific goal, while a virtual left hand was presented 250 mm above the real hand and moved in synchrony with the real hand. Participants then provided information concerning the perceived heights of their real left hands and rated their sense of agency and ownership of the virtual hand. Results of Experiment 1 showed that when participants moved their hands with the goal of touching a virtual object and received feedback indicating goal attainment, the perceived positions of their real hands shifted more toward that of the virtual hand relative to that in the condition without a goal, indicating that their body representations underwent greater modification. Furthermore, results of Experiment 2 showed that the effect of goal-directed movement occurred in the active condition, in which participants moved their own hands, but did not occur in the passive condition, in which participants' hands were moved by the experimenter. Therefore, we concluded that the sense of agency probably contributed to the updating of body representation involving goal-directed movement.

Nobiletin improves hyperglycemia and insulin resistance in obese diabetic ob/ob mice.

Nobiletin is a polymethoxylated flavone found in certain citrus fruits that exhibits various pharmacological effects including anti-inflammatory, antitumor and neuroprotective properties. The present study investigated the effects of nobiletin on insulin sensitivity in obese diabetic ob/ob mice, and the possible mechanisms involved. The ob/ob mice were treated with nobiletin (200mg/kg) for 5 weeks. Nobiletin significantly improved the plasma glucose levels, homeostasis model assessment index, glucose tolerance in an oral glucose tolerance test and plasma adiponectin levels. In white adipose tissue (WAT), nobiletin significantly decreased the mRNA expression levels of inflammatory adipokines such as interleukin (IL)-6 and monocyte chemoattractant protein (MCP)-1 and increased the mRNA expression levels of adiponectin, peroxisome proliferator-activated receptor (PPAR)-gamma and its target genes. At the same time, nobiletin increased the glucose transporter (Glut) 4 expression levels in the whole plasma membrane, and Glut1 and phospho-Akt expression in the whole cell lysates in WAT and muscle. Nobiletin also increased Glut4 protein expression level in the whole cell lysates of the muscle. Taken together, the present results suggest that nobiletin improved the hyperglycemia and insulin resistance in obese diabetic ob/ob mice by regulating expression of Glut1 and Glut4 in WAT and muscle, and expression of adipokines in WAT.