Hiroaki Wagatsuma

Neural dynamics of the cognitive map in the hippocampus

The rodent hippocampus has been thought to represent the spatial environment as a cognitive map. In the classical theory, the cognitive map has been explained as a consequence of the fact that different spatial regions are assigned to different cell populations in the framework of rate coding. Recently, the relation between place cell firing and local field oscillation theta in terms of theta phase precession was experimentally discovered and suggested as a temporal coding mechanism leading to memory formation of behavioral sequences accompanied with asymmetric Hebbian plasticity. The cognitive map theory is apparently outside of the sequence memory view. Therefore, theoretical analysis is necessary to consider the biological neural dynamics for the sequence encoding of the memory of behavioral sequences, providing the cognitive map formation. In this article, we summarize the theoretical neural dynamics of the real-time sequence encoding by theta phase precession, called theta phase coding, and review a series of theoretical models with the theta phase coding that we previously reported. With respect to memory encoding functions, instantaneous memory formation of one-time experience was first demonstrated, and then the ability of integration of memories of behavioral sequences into a network of the cognitive map was shown. In terms of memory retrieval functions, theta phase coding enables the hippocampus to represent the spatial location in the current behavioral context even with ambiguous sensory input when multiple sequences were coded. Finally, for utilization, retrieved temporal sequences in the hippocampus can be available for action selection, through the process of reverting theta rhythm-dependent activities to information in the behavioral time scale. This theoretical approach allows us to investigate how the behavioral sequences are encoded, updated, retrieved and used in the hippocampus, as the real-time interaction with the external environment. It may indeed be the bridge to the episodic memory function in human hippocampus.

SYNCHRONIZATION OF NEURAL OSCILLATIONS AS A POSSIBLE MECHANISM UNDERLYING EPISODIC MEMORY: A STUDY OF THETA RHYTHM IN THE HIPPOCAMPUS

Rat hippocampal cells exhibit characteristic phase-dependent firings when oscillation in frequency range around 8Hz is present. Based on the hypothesis that theta phase coding is generated by synchronization of neural activities, an autoassociative network model of the hippocampus and the entorhinal cortex was analyzed to explore mechanisms underlying episodic memory. Phase coding in theta rhythm enables instantaneous acquisition of experienced events including temporal and spatial contents. Further comparison with electrophysiological data from both rodents and primates suggests a possible role of theta oscillations in memory encoding and online processing of episodic events.

Cognitive Map Formation Through Sequence Encoding by Theta Phase Precession

The rodent hippocampus has been thought to represent the spatial environment as a cognitive map. The associative connections in the hippocampus imply that a neural entity represents the map as a geometrical network of hippocampal cells in terms of a chart. According to recent experimental observations, the cells fire successively relative to the theta oscillation of the local field potential, called theta phase precession, when the animal is running. This observation suggests the learning of temporal sequences with asymmetric connections in the hippocampus, but it also gives rather inconsistent implications on the formation of the chart that should consist of symmetric connections for space coding. In this study, we hypothesize that the chart is generated with theta phase coding through the integration of asymmetric connections. Our computer experiments use a hippocampal network model to demonstrate that a geometrical network is formed through running experiences in a few minutes. Asymmetric connections are found to remain and distribute heterogeneously in the network. The obtained network exhibits the spatial localization of activities at each instance as the chart does and their propagation that represents behavioral motions with multidirectional properties. We conclude that theta phase precession and the Hebbian rule with a time delay can provide the neural principles for learning the cognitive map.

Neuromorphic and Brain-Based Robots

Neuromorphic and brain-based robotics have enormous potential for furthering our understanding of the brain. By embodying models of the brain on robotic platforms, researchers can investigate the roots of biological intelligence and work towards the development of truly intelligent machines. This book provides a broad introduction to this groundbreaking area for researchers from a wide range of fields, from engineering to neuroscience. Case studies explore how robots are being used in current research, including a whisker system that allows a robot to sense its environment and neurally inspired navigation systems that show impressive mapping results. Looking to the future, several chapters consider the development of cognitive, or even conscious robots that display the adaptability and intelligence of biological organisms. Finally, the ethical implications of intelligent robots are explored, from morality and Asimovs three laws to the question of whether robots have rights.

Context-Dependent Adaptive Behavior Generated in the Theta Phase Coding Network

The real world changes in space over time. Our brains need real-time interaction with the external world and will update various internal representations even when events happen only one-time. Such one-time experiences are evaluated in relation to what happens for us in joy and sorrow. Recent brain studies suggest that the dynamic coordination of different representations in brain areas is governed by the synchronization of the brain oscillation, such as theta rhythms. In the rodent hippocampus, the temporal coding mechanism with the theta rhythm, theta phase coding, provides the ability to encode and retrieve behavioral sequences even in the one-time experience, by using successive firing phases in every theta cycle. We here extended the theory to the large-scale brain network and hypothesized that the phase coding not only represents the current behavioral context, but also properly associates it with the evaluation of what happened in the external environment. It is necessary for the animal to predict events in the near future and to update the current and next executive action. In a maze task on our robotic platform, the acquisition of spatial-temporal sequences and spatial-reward associations were demonstrated, even in few trials, and the association contributes to the current action selection. This result suggests that theta rhythms may contribute to coordinate different neural activities to enable contextual decision-making in the real environment.

A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis

EEG signals contain a large amount of ocular artifacts with different time-frequency properties mixing together in EEGs of interest. The artifact removal has been substantially dealt with by existing decomposition methods known as PCA and ICA based on the orthogonality of signal vectors or statistical independence of signal components. We focused on the signal morphology and proposed a systematic decomposition method to identify the type of signal components on the basis of sparsity in the time-frequency domain based on Morphological Component Analysis (MCA), which provides a way of reconstruction that guarantees accuracy in reconstruction by using multiple bases in accordance with the concept of “dictionary.” MCA was applied to decompose the real EEG signal and clarified the best combination of dictionaries for this purpose. In our proposed semirealistic biological signal analysis with iEEGs recorded from the brain intracranially, those signals were successfully decomposed into original types by a linear expansion of waveforms, such as redundant transforms: UDWT, DCT, LDCT, DST, and DIRAC. Our result demonstrated that the most suitable combination for EEG data analysis was UDWT, DST, and DIRAC to represent the baseline envelope, multifrequency wave-forms, and spiking activities individually as representative types of EEG morphologies.

Designing Humanoid Robots with Novel Roles and Social Abilities

This mini-review describes aspects of human-robot interaction to be taken into account when designing humanoid robots with novel roles and social abilities. The review accentuates the psychological complexity that is necessary to be made inherent in the design of humanoid robotic technology. Some recent studies of robot acceptance are summarized leading to the proposal for more complex synthetic sensors being needed in novel humanoid robots. The perspective is designing based on modeling attitude (the social level of human robot interaction), but not opinion (psychological level), which can be a valuable aim for humanoid robotics.

Singular configurations analyses of the modifiable Theo Jansen-like mechanism by focusing on the Jacobian determinant — A finding limitations to exceed normal joint range of motion

Adaptive locomotion is an important topic for the design of mobile robots, and smooth leg movement is of interest for investigating an indicator of how much bio-inspired robot represents the essential mechanism in animal walking. Using the multibody dynamics approach, we have investigated a potential extension of the Theo Jansen mechanism, an eleven-bar linkage that generates the locomotion pattern of multi-legged animals. Our extension highlighted a flexibility of the mechanisms trajectory, but an unclear limitation beyond normal joint range of motion was found. In this study, we examined the theoretical limitation of joint range of motion by singular configuration analysis. Multibody dynamics provide the Jacobian matrix to represent whole kinetics with constraints from close linkages and enables a singularity from the Jacobian determinant to be found. The method of finding a singularity in the mechanism may help to understand spatio-temporal properties of the control parameter, thus generating various stable motions toward mobility in an uneven ground.

Direction and viewing area-sensitive influence of EOG artifacts revealed in the EEG topographic pattern analysis

The influence of eye movement-related artifacts on electroencephalography (EEG) signals of human subjects, who were requested to perform a direction or viewing area dependent saccade task, was investigated by using a simultaneous recording with ocular potentials as electro-oculography (EOG). In the past, EOG artifact removals have been studied in tasks with a single fixation point in the screen center, with less attention to the sensitivity of cornea-retinal dipole orientations to the EEG head map. In the present study, we hypothesized the existence of a systematic EOG influence that differs according to coupling conditions of eye-movement directions with viewing areas including different fixation points. The effect was validated in the linear regression analysis by using 12 task conditions combining horizontal/vertical eye-movement direction and three segregated zones of gaze in the screen. In the first place, event-related potential topographic patterns were analyzed to compare the 12 conditions and propagation coefficients of the linear regression analysis were successively calculated in each condition. As a result, the EOG influences were significantly different in a large number of EEG channels, especially in the case of horizontal eye-movements. In the cross validation, the linear regression analysis using the appropriate dataset of the target direction/viewing area combination demonstrated an improved performance compared with the traditional methods using a single fixation at the center. This result may open a potential way to improve artifact correction methods by considering the systematic EOG influence that can be predicted according to the view angle such as using eye-tracker systems.

Disambiguation in spatial navigation with theta phase coding

It is an open question whether the hippocampal cognitive map is useful for navigation with ambiguity in space representation. The hippocampus might need to assign different contexts to cell populations in the same place, according to the traditional rate coding scheme. Recent experimental observations on theta phase precession, the theta rhythm-dependent activity in the hippocampus, demonstrate that behavioral sequences are represented in a compressed form in the theta cycle, suggesting the possibility of phase coding of context-dependent information in the hippocampus. Here we elucidated memory-guided locomotor behaviors by a hippocampal model with theta phase coding. We hypothesized that current sensory input, spatial memory and motion are concurrently coded in the phase of every theta cycle to compute a possible direction of motion. Computer experiments demonstrated that our simple model of the hippocampal-locomotor system with theta phase coding can generate context-dependent behavioral information.