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A G Siapas

Publications and source records attributed to A G Siapas.

3 recordsLinked to original sources

Coordinated interactions between hippocampal ripples and cortical spindles during slow-wave sleep.

Sleep is characterized by a structured combination of neuronal oscillations. In the hippocampus, slow-wave sleep (SWS) is marked by high-frequency network oscillations (approximately 200 Hz "ripples"), whereas neocortical SWS activity is organized into low-frequency delta (1-4 Hz) and spindle (7-14 Hz) oscillations. While these types of hippocampal and cortical oscillations have been studied extensively in isolation, the relationships between them remain unknown. Here, we demonstrate the existence of temporal correlations between hippocampal ripples and cortical spindles that are also reflected in the correlated activity of single neurons within these brain structures. Spindle-ripple episodes may thus constitute an important mechanism of cortico-hippocampal communication during sleep. This coactivation of hippocampal and neocortical pathways may be important for the process of memory consolidation, during which memories are gradually translated from short-term hippocampal to longer-term neocortical stores.

Action Potentials

Criticality and parallelism in combinatorial optimization.

Local search methods constitute one of the most successful approaches to solving large-scale combinatorial optimization problems. As these methods are increasingly parallelized, optimization performance initially improves but then abruptly degrades to no better than that of random search beyond a certain point. The existence of this transition is demonstrated for a family of generalized spin-glass models and the traveling salesman problem. Finite-size scaling is used to characterize size-dependent effects near the transition, and analytical insight is obtained through a mean-field approximation.

Algorithms

A local circuit approach to understanding integration of long-range inputs in primary visual cortex.

Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we have examined how primary visual cortical neurons integrate classical and nonclassical receptive field inputs. The effect of nonclassical receptive field stimuli and, correspondingly, of long-range intracortical inputs is known to be context-dependent: the same long-range stimulus can either facilitate or suppress responses, depending on the level of local activation. By constructing a large-scale model of primary visual cortex, we demonstrate that this effect can be understood in terms of the local cortical circuitry. Each receptive field position contributes both excitatory and inhibitory inputs; however, the inhibitory inputs have greater influence when overall receptive field drive is greater. This mechanism also explains contrast-dependent modulations within the classical receptive field, which similarly switch between excitatory and inhibitory. In order to simplify analysis and to explain the fundamental mechanisms of the model, self-contained modules that capture nonlinear local circuit interactions are constructed. This work supports the notion that receptive field integration is the result of local processing within small groups of neurons rather than in single neurons.

Contrast Sensitivity