Implementing neural architectures using analog VLSI circuits

Analog very large-scale integrated (VLSI) technology can be used not only to study and simulate biological systems, but also to emulate them in designing artificial sensory systems. A methodology for building these systems in CMOS VLSI technology has been developed using analog micropower circuit elements that can be hierarchically combined. Using this methodology, experimental VLSI chips of visual and motor subsystems have been designed and fabricated. These chips exhibit behavior similar to that of biological systems, and perform computations useful for artificial sensory systems

GENDER DIFFERENCES IN AWARENESS OF COURTSHIP INITIATION TACTICS

In this study, two phases of the initiation of courtship behavior are distinguished, namely the first move of making the contact, and the self-presentation after the contact has been established. Gender differences with respect to cognitions and expectations of courtship behavior were analyzed through self-report in a Dutch Caucasian student population. Our goal was to assess male and female roles in these two phases, and to relate the findings to hypothesized gender role changes. It appeared that both men and women were apparently unaware of which gender usually initiates courtship. Furthermore, both genders reported eye contact as the most frequently used initiation tactic. However the genders differed in other tactics, women reporting the use of indirect nonverbal tactics more often than men, and men reporting their engagement in direct verbal ones more often than women. In presenting themselves, men stressed personal characteristics that are traditionally interpreted as female-valued (such as tenderness) more than women did, whereas women stressed characteristics that are traditionally interpreted as male-valued (such as being prestigiously occupied) more than men did. This apparent change in gender role pattern is discussed against the background of the assumed function of courtship behavior and societal developments

A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identifica-tion of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classi-fying features in 2-D and merging these classifications into 3-D objects, the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the plat-form provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological com-plexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥ 95%. We demonstrated the robustness of these algorithms in a more complex are-na through the automated segmentation of neural cells in ex vivo brain slices. The novel methods surpass previous research improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions

AN ELECTRONIC SYSTEM FOR EXTRACELLULAR NEURAL STIMULATION AND RECORDING Approved by:

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