PubMed · 9345526
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J M Coggins. 1996. Identifying revolutionary computing technologies.. https://doi.org/10.1006/nimg.1996.0051
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Dense multichannel recordings of scalp electroencephalogram (EEG) were obtained in the vicinity of primary somatosensory cortex, time-locked to repetitive vibrotactile stimulation of sites on the right index finger of a single human subject. Frequency-domain analysis of cross-trial averages revealed prominent 'driving' responses in the EEG at the frequency of stimulation, which under specific stimulus conditions displayed pronounced changes in amplitude and topographic organization over brief (4 s) durations of stimulus exposure. The changes were systematic and physiologically coherent, evolving toward driving-response topographies observed in the same subject in conjunction with periodic microstimulation of single mechanoreceptive afferents whose receptive fields occupied corresponding positions on the digit. This dynamic process was orderly and reproducible, and could be controlled by manipulating factors such as the amplitude, frequency, and temporal spacing of the stimuli. The results are tentatively interpreted in light of a previously proposed neurophysiological model of stimulus-driven response plasticity in mammalian somatosensory cortex.
We propose a hardware and software architecture to respond to crucial problems in the neuroimaging field: storage, retrieval, and processing of large datasets. The B-SPID project, here discussed, concerns the processing of neuroimages and attached components stored in an object-relational multimedia database management system (DBMS). Advanced bioinformation concepts are exploited in this project such as large scale data storage, high level graphical user interfaces and 3D graphical processing and display of data. Our database implementation is based on standard programming components, runs on several UNIX platforms and is written to be evolutive. Queries on this database are designed to obtain and display from neuroimaging data several types of results (pictures, text, or 3D graphical shapes) on heterogeneous systems.
We describe a new, observer-independent procedure for identifying boundaries between cortical areas. The method is useful for images obtained from sections which provide microstructural information on the cortical laminar pattern, e.g., Nissl-, myelin-, or immunohistochemically stained sections or receptor autoradiographs. The laminar pattern is represented by profile curves extending from the cortical surface to the white matter boundary. These profiles are constructed from digitized images. Digitization is based on the grey level index (Nissl) or densitometry (myelin, immunohistochemistry, receptor autoradiography). The shapes of neighboring profiles are compared by calculating their distances according to feature vectors extracted from the profiles. Profiles derived from a homogeneous area can be expected to be similar in shape and hence show low distance values between each other. Maximum distances can be found between profiles which lie on opposite sides of a structural boundary. The Mahalanobis distance was found to be more sensitive and to yield greater spatial resolution than other distance measures such as the Euclidean distance. Cell-stained sections of the human neocortex were analyzed. The method not only verified boundaries which had been defined by visual inspection, it also revealed new ones which had not been detected visually. The procedure offers an important supplement to the traditional methods based on visual inspection which, for the first time, is based on quantitative data and therefore offers a new level of reproducibility and observer independence. Anatomical atlases based on this procedure thus provide a new tool for the interpretation of structural data obtained from functional imaging techniques.