Masoud Talebi Amiri

Abstract Dopamine shapes how the prefrontal cortex filters incoming information, maintains it in working memory, and releases it for action — three computational roles that closely parallel the input, state, and output stages of a sequence model. Here we ask whether formalizing this correspondence yields a sequence architecture that is both computationally competitive and mechanistically interpretable in biological terms.

An unexpected headline appeared across the media: Ukraine attacked an Iranian vessel in the Caspian Sea. Beyond the military dimensions of the incident, however, a more consequential question emerged: What is Ukraine doing in the Caspian Sea? Is this merely the decision of a country at war seeking to expand the geographical scope of its military operations, or should it be understood within the framework of a new set of geopolitical equations that are gradually taking shape?

Abstract The primary focus of accurate and cost-effective computation in machines endowed with advanced cognitive abilities is to enhance the accuracy and speed of learning in the bio-inspired spiking machine vision networks. This paper introduces a novel reinforcement burst time dependent plasticity (RBTDP) learning algorithm, implemented as a digital circuit within a spiking network that utilizes low-cost neuron circuits.