Modeling of Dendritic Spine Structural Change During Learning in Terms of Shortand Long-Term Memory Behavior

Studies on learning and memory in life have gained a significant boost in technological developments. The images made in the large network environment created by the nerve cells of the brain show the changes in the learning process of the intercellular connections. Structural changes of the dendritic spine are observed, especially in the synaptic region. These changes frequently seen in the young living brain are the formation of new dendritic spines or the growth of existing ones during the synaptic stimulation. This change, which occurs due to synaptic stimulation, is in the form of a permanent or return to the previous state. These cases are structured and biophysically interpreted and modeled in various studies. In our work, a method is proposed for modeling the structural change of spine by computational methods. Structural change of dendritic spine during learning in our model: It is modeled by the time constant parameter of the synaptic conductivity function. At this point, the values of the synaptic conductivity time constant are given to model the growth, persistence, shrinkage or extinction of dendritic spines. Dendritic spine growth occurs as the stimulus arrives, increasing the time constant value to model this event. If the spine structure was permanent when the stimulation was interrupted, the time constant value was kept constant. In this case, the motifs that make up the memory behave like long term memory. If the spine has shrunk again, the time constant value has also shrunk. In this case, the motifs that make up the memory behave like short term memory. As a result, it has been shown in our model that dendritic spine growth can be modeled by changing the time constants