Mathematical Modeling of the Learning Curve : A Laboratory Manual and Source Book (De Gruyter Textbook) （2024. XIV, 237 S. 213 b/w ill., 25 b/w tbl. 240 mm）

Abramson, Charles I./Stepanov, Igor Igorevich/Wincheski, Riley J.

DE GRUYTER（2024発売）

DE GRUYTER（2024発売）

• 製本 Paperback:紙装版/ペーパーバック版
• 商品コード 9783111311739

Full Description

The application of mathematical models in the analysis of learning data has a rich tradition in experimental psychology. Such modeling is not only of scientific interest from psychophysiological point of view but very important from clinical point of view because memory impairment is a common symptom that is frequently diagnosed in elder people, persons after traumatic brain injury, patients with type 2 diabetes mellitus, Parkinson disease, multiple sclerosis, and other neurological and psychiatric diseases. Mild memory impairment might be one of the most important symptoms of a future Alzheimer's disease. Thus, early diagnosis of initial signs of memory impairment is of importance. The book offers the reader hands on practical experience using a mathematical model dveloped by the senior authors. Classroom tested experiments are provided which requires the reader to use the model under various conditions such as learning and memory in both humans and animals.

Following an introduction to mathematical models, the book contains 13 experiments. These experiments include those related to animal learning in such organisms as snails, bees, and rats. A variety of human experiments are also presented including those related to short and long term memory, maze learning, classical salivary conditioning, evaluation of sound on memory, and the influence of dietary supplements on memory. We close the section on experiments with and analysis of machine learning curves.



Appendices are provided on how to build apparatus and how to install the software.