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The hippocampus is a gray matter structure in the temporal lobe that plays a key role in memory processes and in many diseases (Alzheimer's disease, epilepsy, depression ...).The development of morphometric models is essential for the study of the functional anatomy and structure alterations associated with different pathologies. The objective of t...
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... Much of the research was devoted primarily to understanding biological mechanisms that make up memory and contribute to its storage. Studies on temporal lobe-dependent memory performed on vertebrates such as Aplysia californica and Drosophila melanogaster prove that molecular changes at all levels (post-translational, translational and transcriptional) have a significant impact on the formation of LTM [2][3][4]. In the near future, it seems necessary to take up steps in order to elucidate molecular mechanisms within RNA (e.g. ...
... To be effective, this process should take no more than a minute -after that time the record will be lost. In this case, memory cannot be improved by training, it can only be improved by stimulating the noradrenergic system [3]. Even if written in a permanent form, it is initially quite unstable and can be easily disturbed by pharmacological factors (long-term use of benzodia- [2][3][4]. ...
... In this case, memory cannot be improved by training, it can only be improved by stimulating the noradrenergic system [3]. Even if written in a permanent form, it is initially quite unstable and can be easily disturbed by pharmacological factors (long-term use of benzodia- [2][3][4]. For more efficient memory recall, all information is coded according to its characteristics. ...
Memory trace is an effect of temporary arousal (perception, experience, action) that causes a specific change in the nervous system. Memory allows to record and recall various information, thus enabling to learn new things. It is an extremely active and dynamic process. The influence of emotions on memory is obvious, largely determined by the close cooperation of the amygdala (responsible for emotions) and the hippocampus (memory processes).
Neurodegenerative disorders are one of the most insidious disorders that affect millions around the world. Presently, these disorders do not have any remedy, however, if detected at an early stage, therapy can prevent further degeneration. This study aims to detect the early onset of one such neurodegenerative disorder called Alzheimer’s Disease, which is the most prevalent neurological disorder using the proposed Convolutional Neural Network (CNN). These MRI scans are pre-processed by applying various filters, namely, High-Pass Filter, Contrast Stretching, Sharpening Filter, and Anisotropic Diffusion Filter to enhance the Biomarkers in MRI images. A total of 21 models are proposed using different preprocessing and enhancement techniques on transverse and sagittal MRI images. The comparative analysis of the proposed five-layer Convolutional Neural Network (CNN) model with Alex Net is presented. The proposed CNN model outperforms AlexNet and achieves an accuracy of 99.40%, with a precision of 0.988, and recall of 1.00, by using an edge enhanced, contrast stretched, anisotropic diffusion filter. The proposed method may be used to implement automated diagnosis of neurodegenerative disorders.
