Spike-Timing Theory of Working Memory

Working memory (WM) is the part of the brain's memory system that provides temporary storage and manipulation of information necessary for cognition. Although WM has limited capacity at any given time, it has vast memory content in the sense that it acts on the brain's nearly infinite repertoire of lifetime long-term memories. Using simulations, we show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. Here, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatiotemporal spike-timing patterns, called polychronous patterns; and synapses forming such polychronous neuronal groups (PNGs) are subject to associative synaptic plasticity in the form of both long-term and short-term spike-timing dependent plasticity. While long-term potentiation is essential in PNG formation, we show how short-term plasticity can temporarily strengthen the synapses of selected PNGs and lead to an increase in the spontaneous reactivation rate of these PNGs. This increased reactivation rate, consistent with in vivo recordings during WM tasks, results in high interspike interval variability and irregular, yet systematically changing, elevated firing rate profiles within the neurons of the selected PNGs. Additionally, our theory explains the relationship between such slowly changing firing rates and precisely timed spikes, and it reveals a novel relationship between WM and the perception of time on the order of seconds

glossaLAB: Co-Creating Interdisciplinary Knowledge

The paper describes the glossaLAB international project as a contribution to confront the urgent need of knowledge integration frameworks, as required to face global challenges that overwhelm disciplinary knowledge capacity. Under this scope, glossaLAB is devised to make contributions in three main aspects of such endeavor: (i) development of a sound theoretical framework for the unification of knowledge, (ii) establishment of broadly accepted methodologies and tools to facilitate the integration of knowledge, (iii) development of assessment criteria for the qualification of interdisciplinarity undertakings. The paper discusses the main components of the project and the solutions adopted to achieve the intended objectives at three different levels: at the technical level, glossaLAB aims at developing a platform for knowledge integration based on the elucidation of concepts, metaphors, theories and problems, including a semantically- operative recompilation of valuable scattered encyclopedic contents devoted to two entangled transdisciplinary fields: the sciences of systems and information. At the theoretical level, the goal is reducing the redundancy of the conceptual system (defined in terms of “intensional performance” of the contents recompiled), and the elucidation of new concepts. Finally, at the meta-theoretical level, the project aims at assessing the knowledge integration achieved through the co-creation process based on (a) the diversity of the disciplines involved and (b) the integration properties of the conceptual network stablished through the elucidation process.2019-2

Simple model of spiking neurons

Abstract—A model is presented that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin–Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC. Index Terms—Bursting, cortex, Hodgkin–Huxley, PCNN, quadratic integrate-and-fire, spiking, thalamus