AbstractsBiology & Animal Science

Current technological demands look for smaller, faster and more efficient systems. However, such demands are limited mainly by physical properties of devices (e.g. size of transistors, increase of electrical noise, etc.). At this point alternative solutions may have a response for such demands. The study of biological systems may offer a different perspective to fulfill such requirements. Biological structures have been optimized during millions of years of evolution resulting in power-efficient, fast and compact systems that are resilient against noisy and hostile environments. Although, no electrical system has been able to emulate any biological structure in their totality, neuromorphic systems have already proved to be efficient in many engineering applications. This thesis is inspired specifically by how some biological structures use noise to improve determined tasks. The utilization of noise to enhance performance is a well-studied phenomenon and it is known as Stochastic Resonance (abbreviated as SR). Examples of SR in nature are found inside mechanoreceptors of some insects and fishes to detect weak signals from the environment, it is also observed in the human sensory system, as well as at molecular level to detect low-amplitude stimuli inside nervous system. And at system level, it is also involved in the evolution of human creativity, imagination and decision-making processes. At large-scale natural phenomena, SR has an effect in the ice age transitions. The use of noise to improve certain tasks could seem counterintuitive from the electrical engineering point of view; however nature has given us many examples of the positive utilization of noise. Noise and uctuations are inherently part of nature; and biological systems have already self-adapted to include external and internal uctuations in their processing as a positive factor; in this sense, SR has been already exploited by biomedical engineers, just to mention some remarkable examples on the improvement of silicon cochlea, balance control systems and life-support ventilators, where the introduction of noise is a key factor for a more precise emulation of these artificial systems. Moreover, it has been also utilized in engineering systems such as electrical sensors to detect weak stimuli, signal amplification and noise-induced synchronization circuits. In this thesis it is presented two main applications related with SR and its applications. The first case is based on the study on how electrical spikes are transmitted along long axons inside the nervous systems. In this process, due to the variability of conductance among stages, the amplitude of electrical spikes may not be enough to excite next stage. However, it has been discovered that internal uctuations inside node axons may enhance signal transmission. This idea could be mimicked by electrical systems to transmit signals efficiently in the presence of mismatches. Simulation results show that with the introduction of an optimal amount of noise, signal transmission is improved in the presence of…