0000000000930385
AUTHOR
Emiliano Spera
On the cellular mechanisms underlying working memory capacity in humans
The cellular processes underlying individual differences in the Working Memory Capacity (WMC) of humans are essentially unknown. Psychological experiments suggest that subjects with lower working memory capacity (LWMC), with respect to subjects with higher capacity (HWMC), take more time to recall items from a list because they search through a larger set of items and are much more susceptible to interference during retrieval. However, a more precise link between psychological experiments and cellular properties is lacking and very difficult to investigate experimentally. In this paper, we investigate the possible underlying mechanisms at the single neuron level by using a computational mod…
Segmentation and feature extraction in capillaroscopic videos
This contribution describes a method to select regions of interest as capillaries of the oral mucosa and to extract their main features useful for real diagnosis purposes. A discrete version of the wavelet transform has been adopted for segmenting the images coming from video sequences acquired by a prototype capillaroscopic, able to put in evidence the red blood flow. A set of proper characteristics is automatically computed for a correct evaluation of the peripheral microcirculation.
On the structural connectivity of large-scale models of brain networks at cellular level
AbstractThe brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the …