Journal of Integrative Neuroscience

The development of relational databases has significantly improved the performance of storage, search, and retrieval functions and has made it possible for applications that perform real-time data acquisition and analysis to interact with these types of databases. The purpose of this research was to develop a user interface for interaction between a data acquisition and analysis application and a relational database using the Oracle9i system. The overall system was designed to have an indexing capability that threads into the data acquisition and analysis programs. Tables were designed and relations within the database for indexing the files and information contained within the files were established. The system provides retrieval capabilities over a broad range of media, including analog, event, and video data types. The system's ability to interact with a data capturing program at the time of the experiment to create both multimedia files as well as the meta-data entries in the relational database avoids manual entries in the database and ensures data integrity and completeness for further interaction with the data by analysis applications.

Via a detailed case study of mesial temporal lobe epilepsy, we show that a method of determining the direction of information flow among signals is able to provide focal localization via the simultaneous analysis of multiple EEG channels. This determination is accomplished by representing information flow direction via directed graphs, where focal electrodes are associated with high observed rates of pertinence to strongly connected subgraphs. Further clinical support to this finding is provided by results for an additional 9 cases of focal epilepsy cases. The graph theoretical approach is a tool for describing and analyzing the effective connectivity dynamics behind epileptic seizures and may provide a common language for studying other complex dynamic relationships between neural structures.

Natural, everyday sensorimotor behaviors, such as rising from sitting, typically have an intrinsic organization of several levels of analysis. Taking this intrinsic organization as key to understanding neural dynamics is neither a top-down nor a bottom-up approach, but rather a meshing of multiple centers and levels of analysis. Motor control requires body dynamics that are consistent with physical dynamics, besides the more microscopic levels of neural dynamics. The dynamics of separate movements have been investigated as if the ends can be capped off, separated from the rest of the individual's life. Is this dynamically correct? Even chaotic behavior is deterministic. However, the mathematics of nonlinear oscillations is not all of dynamics. This paper relates Bloch's dynamical theorem to the modular, conditional approach to sensorimotor and other neural functioning.

Bloch's dynamical theorem lays a foundation for the piecewise study of structurally accurate dynamics in theoretical neurobiology. Piecewise studies can be used as a modeling option complementary to the methods of nonlinear oscillator dynamics. By applying Bloch's theorem, dynamics of movements analyzed piecewise can be extended into a smooth flow on any manifold, either as a whole or conditionally. Conditional dynamics makes dynamical modeling options explicit, often depending on what variables the organism can control, and allows one to take different modeling options at different junctures in analyzing the same phenomenon. For example, this approach allows the study of complex motor control problems to be reduced to modular constructions using singularities and flow lines. Dynamical contingencies are expressed using the mathematics of ordered structures. This paper presents Bloch's dynamical theorem and its relevance to model construction in theoretical neurobiology. Specific examples, integrated into physiological and behavioral context, are cited from the literature.

Computational morphological analysis comprises the development of measures (indicators) that describe different form attributes of a neuron and provides additional parameters for classification algorithms. Our work addressed the problem of small group sizes often encountered in neuromorphological and neurophysiological research, automated classification tasks (unsupervised learning) and introduced a new morphological measure: the wavelet statistical moment. We analysed cat α/Y, β/X and δ Golgi-stained retinal ganglion cells using six different shape features (circularity, 2^nd statistical moment and entropy of Gaussian blurred images, wavelet statistical moment, number of terminations and the fractal dimension). This allowed us to compare the sensitivity of the methods in uniquely describing morphological attributes of these cells.

To assess the effects of changes in somesthetic plantar information on upright quiet stance, a rotary plantar massage was applied under the feet of healthy subjects for ten minutes. The controlling variable, the centre of pressure (CP) displacements, were recorded, before and after massage, through a force platform and decomposed into two elementary motions: the vertical projection of the centre of gravity (CG_v) and the difference between the latter and the CP (CP-CG_v) along medio-lateral ML and antero-posterior AP directions. These motions were processed through frequency analysis and modelled as fractional Brownian motion. For CP-CG_v motions, the frequency analysis shows that massage under the plantar soles induces a decrease of the amplitudes along the ML direction suggesting reduced overall muscular activity (abductor-adductor muscles of the hip according to Winter et al. [49]). A general trend is that the CG_v amplitudes are also diminished after massage especially in the ML direction, indicating a better distribution of the body weight on the two supports. On the other hand, the effects tend to vanish after about 8 minutes. Conversely, when the massage was given under the toes, no particular effect on any elementary motion was observed, suggesting that the plantar mechanoreceptors under the toes necessitate stronger stimulation to respond significantly and/or that the greater sensitivity obtained was not used by the CNS. Overall, this data emphasises the fact that a recalibration of somesthetic cues may occur when enhanced afferent information is fed to the postural system.

A recently developed quantitative model of cortical activity is used that permits data comparison with experiment using a quantitative and standardized means. The model incorporates properties of neurophysiology including axonal transmission delays, synapto-dendritic rates, range-dependent connectivities, excitatory and inhibitory neural populations, and intrathalamic, intracortical, corticocortical and corticothalamic pathways. This study tests the ability of the model to determine unique physiological properties in a number of different data sets varying in mean age and pathology. The model is used to fit individual electroencephalographic (EEG) spectra from post-traumatic stress disorder (PTSD), schizophrenia, first episode schizophrenia (FESz), attention deficit hyperactivity disorder (ADHD), and their age/sex matched controls. The results demonstrate that the model is able to distinguish each group in terms of a unique cluster of abnormal parameter deviations. The abnormal physiology inferred from these parameters is also consistent with known theoretical and experimental findings from each disorder. The model is also found to be sensitive to the effects of medication in the schizophrenia and FESz group, further supporting the validity of the model.