Sentence examples for instrumental processing from inspiring English sources

The notion of the parallel and serial operation of corticostriatal loops in motivational, pavlovian and instrumental processing raises the issue of how, mechanistically, the loops interact.

In this paper, we focus on advancing classification and data retrieval that are instrumental when processing large macroinvertebrate image datasets.

This procedure includes classic and instrumental conditioning processes that involve both conscious and non-conscious information processing.

The updated version of this model posits that psychopathy is a result of a dysfunction of the amygdala, the almond-shaped bundle of gray matter situated in the midbrain, which is another area instrumental in emotional processing.

And whereas sleep learning offered only the promise of our being able to regurgitate information from the night before, our latest understanding of sleep tells us that it is instrumental in the processing of memory and is vital to insight.

However, recent technological improvements in sample processing, instrumental platforms, data acquisition approaches and informatics capabilities continue to advance MS-based applications.

The instrumental control and data processing were handled by an IBM PC/AT compatible PC.

Optimization using various ideas ranging from combinatorial optimization to image processing is instrumental in solving the paneling problem, that is, the rationalization of freeform shapes via decomposition into simple and repetitive elements.

In our study we observed a discernible tension for panel members between framing cases as complex instances of human suffering, involving moral engagement and emotionally and clinically challenging judgements, and instances of technocratic processing, involving instrumental negotiations over policy fit.

In that situation, widening the eyes increases the scope of one's visual field, which is instrumental in quickly visually processing that stimulus, allowing situation-appropriate reactions (e.g., duck and cover; Shariff & Tracy, 2011; Susskind et al., 2008).

The wavelet based analysis of CHAMP data was able to detect, identify and classify artificial noise sources, such as instrumental problems and pre-processing errors as well as high frequency natural signals of external fields, such as F-region ionospheric plasma bubbles (see Stolle et al. (2006) for a statistical analysis of these events) and lastly but more importantly, magne-tospheric Pc3 waves.