Use of Size Stratification and Differential Weighting to Measure Forest Trends

1968 ◽  
Vol 79 (2) ◽  
pp. 402 ◽  
Author(s):  
F. Glenn Goff
Keyword(s):  
Differential Weighting

scholarly journals Salience-driven value construction for adaptive choice under risk

2018 ◽  
Author(s):  
Mehran Spitmaan ◽  
Emily Chu ◽  
Alireza Soltani
Keyword(s):  
Reward Magnitude ◽  
Human Subjects ◽  
Real Life ◽  
Individual Outcomes ◽  
Single Piece ◽  
Differential Weighting ◽  
Adaptive Choice ◽  
Plausible Mechanism ◽  
Reward Information ◽  
Adaptive Decision Making

Decisions we face in real life are inherently risky and can result in one of many possible outcomes. However, most of what we know about choice under risk is based on studies that use options with only two possible outcomes (simple gambles), so it remains unclear how the brain constructs reward values for more complex risky options faced in real life. To address this question, we combined experimental and modeling approaches to examine choice between pairs of simple gambles and pairs of three-outcome gambles in male and female human subjects. We found that subjects evaluated individual outcomes of three-outcome gambles by multiplying functions of reward magnitude and probability. To construct the overall value of each gamble, however, most subjects differentially weighted possible outcomes based on either reward magnitude or probability. These results reveal a novel dissociation between how reward information is processed when evaluating complex gambles: valuation of each outcome is based on an integrated value whereas combination of possible outcomes relies on a single piece of reward information. We show that differential weighting of possible outcomes enabled subjects to make decisions more easily and quickly. Together, these findings reveal a plausible mechanism for how salience, in terms of possible reward magnitude or probability, can influence the construction of subjective values for complex gambles. They also point to separable neural mechanisms for how reward value controls choice and attention in order to allow for more adaptive decision making.

Saccadic Localisation of Random Dot Targets

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 101-101 ◽  
Author(s):  
J W McGowan ◽  
E Kowler ◽  
A Sharma ◽  
C Chubb
Keyword(s):  
Saccadic Eye Movements ◽  
Natural Scenes ◽  
Landing Position ◽  
Local Pattern ◽  
Centre Of Gravity ◽  
Local Characteristics ◽  
Spatial Pooling ◽  
Initial Fixation ◽  
Single Target ◽  
Differential Weighting

Saccadic eye movements land at precise places within simple target forms implying that a spatial pooling process operates over attended regions to determine the saccadic endpoint. To study pooling, we used large, unstructured targets and looked for evidence of differential spatial weighting based on local pattern characteristics. Subjects made a saccade to targets composed of 19 dots scattered randomly within a 4 deg diameter region horizontally displaced 3.8 – 4.2 deg to the left or right of initial fixation. Dot intensity was either uniform or variable. Saccadic landing positions were close to the centre-of-gravity (overshooting or under- shooting by 5% – 10% depending on subject, direction and eccentricity). Precision was excellent (SD=10% ecc), although not as good as with single target points (SD=7% ecc). Correlations between the presence of a dot and saccadic landing position showed that all regions of the pattern contributed. Differential weighting of dots according to location (eg near vs far; central vs boundary) did not yield better predictions of the saccadic landing position. However, predictions of the landing position were improved by assigning more weight to higher-intensity dots. Local dot clusters contributed less than would be expected from the contributions of individual dots. Spatial pooling is highly effective over a large region. Saccadic overshoots or undershoots were not due to differential spatial weighting, and may originate after the centre-of-gravity computation. The differential weighting of high-intensity dots and dot clusters demonstrates sensitivity to local characteristics, and implies that the saccadic endpoint may be determined by pooling the activity of units centred on different subregions of the target. The pooling mechanism supports precise saccadic localisation of large, unstructured targets, and accounts for the ease with which we direct saccades to chosen objects in natural scenes.

Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables

Psychometrika ◽  
1984 ◽  
Vol 49 (1) ◽  
pp. 57-78 ◽  
Author(s):  
Wayne S. DeSarbo ◽  
J. Douglas Carroll ◽  
Linda A. Clark ◽  
Paul E. Green
Keyword(s):  
Alternative Clustering ◽  
Differential Weighting
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