<p>An effective method for examining neuronal characteristics, interpreting neural mechanisms, and creating treatment plans for neurological conditions is the introduction of external stimuli to biological neurons. In this article, Hopfield neural network model is constructed with three neurons under the influence of electromagnetic radiation. Discrete time fractional order memcapacitor element is introduced in this article to represent the electromagnetic effect in the model. Additionally, a novel memristor element is developed with Caputo type fractional difference operator and is employed to investigate the synaptic plasticity between the neurons. Capacitance of memcapacitor changes with its internal voltage and historical charge. This introduction allows the network to exhibit memory-dependent, nonlinear behavior influenced by its past states. Many benefits are brought about by this change, especially with regard to memory retention and the capacity of the network to simulate more intricate, physiologically inspired brain processes. Article performs nonlinear dynamical analysis like stability, bifurcation and coexistence nature supported with phase plane portraits and basin diagrams. It is found that the system exhibit a significant type of bifurcation known as crisis bifurcation, resulting in sudden disappearance of the attractors. These occurrences were identified using analytical and numerical methods like as bifurcation diagrams and Lyapunov exponents. Understanding crisis bifurcation improves our understanding of biological and artificial neural systems. Neural firing patterns are investigated for emphasizing the significance of the fractional order and understanding the effect of memcapacitor on neuron.</p>