For the past half century, neuroscience has greatly advanced by parcellating the brain into many functionally distinct areas and by decomposing the neural circuit into neurons and genotypes. However, reduction approaches to correlate human intellects with neural elements (brain areas, neurons, or genes) have limitations, since signal/information flow in the cerebral cortex, an ultimate complex system, is dynamic, hierarchical and distributed. We have been exploring an alternative approach to capture spatiotemporal dynamics of signals propagation and interactions underlying visual categorization and memory along the distributed cortical neural network using a flexible "mesh" electrocorticographic probe. Our research aims to revise the functional localization theory, accounting for the non-linear, parallel-distributed, and dynamic nature of the cortical processing.
In the study of functional neuroimaging, functional integration analysis is able to address and characterize what and how local brain areas interact with each other. There are two types of the analysis; functional connectivity and effective connectivity. Functional connectivity examines functional networks in terms of temporal correlation between spatially remote brain regions, whereas effective connectivity is defined as the causal influences that neural units exert over another. Dynamic causal modeling (DCM) is a most famous analytical scheme to examine effective connectivity. A key characteristic of DCM is that it allows for generating plausible models of neural population dynamics, and uses a biophysical forward model that describes the transformation from neural activity to hemodynamic response. A variety of Bayesian model selection and average procedure is an additional benefit of this scheme. In this article, I review the conceptual and mathematical basis of DCM, then introduce network model construction and selection process in the DCM. Finally, I touch tips and limitation in the practical use of DCM.
Graph is one of mathematics dealing with topology composed of nodes and links, and in recent years it has been drawing attention as a basic theory of network analysis also in the field of brain research. In networks such as friendship and the Internet, nodes and links are already defined. However, in the case of a brain network, we must start with the definition and estimation of nodes and links.
In this paper, we first introduce the minimum graph theory necessary for brain network analysis. Furthermore, we describe problems specific to brain network analysis, such as definition and estimation of nodes and links. For example, in the case of functional connectivity, the link is estimated from the correlation coefficient of the time series data obtained from each of the two brain parts. If the correlation coefficient is higher than a certain threshold, the two nodes are connected. There are many ways to apply such thresholds, and the method chosen may have a significant impact on conclusions. In this paper, we introduce and explain these various methodologies related to thresholds.
One of the basic approaches in neuropsychology is the thorough examination of the relationship between an identified lesion and patient symptoms. Detailed studies of single cases, such as Tan, HM, and others allow us to model the relationship between the brain and its functional outcomes. However, group studies of patients are often required for assessing the validity of the relationships derived from single case studies. Voxel-based lesion-symptom mapping (VLSM) is a method that can be used to statistically validate such relationships in group studies of patients. However, at the same time, there is a risk of statistical errors in the VLSM analysis in such group studies of patients. Therefore, special attention should be paid while interpreting VLSM results.
Methodologically, cognitive psychology (or cognitive neuropsychology) has adopted the information-processing approach to understand and appreciate human cognition. On this approach, human cognitive system is viewed as being analogous to a computer. Instead of the computer metaphor approach, connectionist approach seeks a source of metaphors from brain, offers brain-style computational system which has an architecture based on consideration of how brains might function, and investigates mechanisms how mental operations might be accomplished. The present review aims to indicate some important features of connectionist approach through our simulation studies using connectionist model for reading words, to show the difference with the conventional approach, and to introduce recent trends in the research aria.
Rizzolatti et al. proposed three stream model of visual information processing in man, ie. ventral stream, ventro-dorsal stream, and dorso-dorsal stream. Dorso-dorsal stream directed to the superior parietal lobule and the intraparietal sulcus for processing location movement and shape of the object to control actions toward the object unconsciously. Lesions on the dorso-dorsal stream can produce visuomotor ataxia defective prehension or orienting disability of one's own body. Here I describe two symptoms which are reported for the first time as the results of lesions in the intraparietal sulcus, impairment of direction of saccadic eye movement toward the contralesional sounds and impaired perception of radial optic flow with the focus of expansion located on the contralesional visual field. Features of these symptoms are discussed with reference to the functions of dorso-dorsal stream.
We investigated the relation between the functional impairment and different types of cognitive dysfunction in patients with Alzheimer's disease (AD). We stratified the patients according to overall cognitive severity, that is, 232 AD patients with a Mini-Mental State Examination (MMSE) score of 15 to 26 were classified into 4 groups, and evaluated correlations between the Sum of Boxes in Clinical Dementia Rating (CDR-SOB) and the indices of different cognitive dysfunction in each patient group. The CDR-SOB correlated with the score of the backward digit span task in the group with MMSE scores of 15 to 17, the score of the recent memory task in the group with MMSE scores of 18 to 20, and the score of the orientation task in the group with MMSE scores of 24 to 26. Different types of cognitive dysfunction strongly affect functional impairment in patients with different severities of overall cognitive dysfunction, because patients with different cognitive severities have differently preserved amounts of community, home and self-care affairs.