Ratios and effect size

Responding to a related pair of measurements is often expressed as a single discrimination ratio. Authors have used various discrimination ratios; yet, little information exists to guide their choice. A second use of ratios is to correct for the influence of a nuisance variable on the measurement of interest. I examine four discrimination ratios using simulated data sets. Three ratios, of the form a/(a + b), b/(a + b), and (a - b)/(a + b), introduced distortions to their raw data. The fourth ratio, (b - a)/b largely avoided such distortions and was the most sensitive at detecting statistical differences. Effect size statistics were also often improved with a correction ratio. Gustatory sensory preconditioning experiments involved measurement of rats’ sucrose and saline consumption; these flavors served as either a target flavor or a control flavor and were counterbalanced across rats. However, sensory preconditioning was often masked by a bias for sucrose over saline. Sucrose and saline consumption scores were multiplied by the ratio of the overall consumption to the consumption of that flavour alone, which corrected the bias. The general utility of discrimination and correction ratios for data treatment is discussed

Can existing associative principles explain occasion setting? Some old ideas and some new data

Since occasion setting was identified as a type of learning independent of 'simple' associative processes, a great deal of research has explored how occasion setters are established and operate. Initial theories suggested that they exert hierarchical control over a target CS→US association, facilitating the ease with which a CS can activate the US representation and elicit the CR. Later approaches proposed that occasion setting arises from an association between a configural cue, formed from the conjunction of the occasion setter and CS, and the US. The former solution requires the associative principles dictating how stimuli interact to be modified, while the latter does not. The history of this theoretical distinction, and evidence relating to it, will be briefly reviewed and some novel data presented. In summary, although the contribution of configural processes to learning phenomena is not in doubt, configural theories must make many assumptions to accommodate the existing data, and there are certain classes of evidence that they are logically unable to explain. Our contention is therefore that some kind of hierarchical process is required to explain occasion-setting effects

Familiarity-based stimulus generalization of conditioned suppression

We report that stimulus novelty/familiarity is able to modulate stimulus generalization and discuss the theoretical implications of novelty/familiarity coding. Rats in Skinner boxes received clicker → shock pairings before generalization testing to a tone. Before clicker training, different groups of rats received preexposure treatments designed to systematically modulate the clicker and the tone's novelty and familiarity. Rats whose preexposure matched novelty/familiarity (i.e., either both or neither clicker and tone were pre-exposed) showed enhanced suppression to the tone relative to rats whose preexposure mixed novelty/familiarity (i.e., only clicker or tone was pre-exposed). This was not the result of sensory preconditioning to clicker and tone

A computational implementation of a Hebbian learning network and its application to configural forms of acquired equivalence

We describe and report the results of computer simulations of the three-layer Hebbian network informally described by Honey, Close, and Lin (2010): A general account of discrimination that has been shaped by data from configural acquired equivalence experiments that are beyond the scope of alternative models. Simulations implemented a conditional principle components analysis (CPCA) Hebbian learning algorithm and were of four published experimental demonstrations of configural acquired equivalence. Experiments involved training rats on appetitive bi-conditional discriminations in which discrete cues, (w and x) signaled food delivery (+) or its absence (-) in four different contexts (A, B, C and D): Aw+ Bw- Cw+ Dw- Ax- Bx+ Cx- Dx+. Contexts A and C acquired equivalence. In three of the experiments acquired equivalence was evident from subsequent revaluation, from compound testing or from whole-/part-reversal training. The fourth experiment added concurrent bi-conditional discriminations with the same contexts but a pair of additional discrete cues (y and z). The congruent form of the discrimination, in which A and C provided the same information about y and z, was solved relatively readily. Parametric variation allowed the network to successfully simulate the results of each of the four experiments

Dissociations in the effect of delay on object recognition: evidence for an associative model of recognition memory

Rats were administered 3 versions of an object recognition task: In the spontaneous object recognition task (SOR) animals discriminated between a familiar object and a novel object; in the temporal order task they discriminated between 2 familiar objects, 1 of which had been presented more recently than the other; and, in the object-in-place task, they discriminated among 4 previously presented objects, 2 of which were presented in the same locations as in preexposure and 2 in different but familiar locations. In each task animals were tested at 2 delays (5 min and 2 hr) between the sample and test phases in the SOR and object-in-place task, and between the 2 sample phases in the temporal order task. Performance in the SOR was poorer with the longer delay, whereas in the temporal order task performance improved with delay. There was no effect of delay on object-in-place performance. In addition the performance of animals with neurotoxic lesions of the dorsal hippocampus was selectively impaired in the object-in-place task at the longer delay. These findings are interpreted within the framework of Wagner’s (1981) model of memory

Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction

Unreliable predictions can occur when using artificial intelligence (AI) systems with negative consequences for downstream applications, particularly when employed for decision-making. Conformal prediction provides a model-agnostic framework for uncertainty quantification that can be applied to any dataset, irrespective of its distribution, post hoc. In contrast to other pixel-level uncertainty quantification methods, conformal prediction operates without requiring access to the underlying model and training dataset, concurrently offering statistically valid and informative prediction regions, all while maintaining computational efficiency. In response to the increased need to report uncertainty alongside point predictions, we bring attention to the promise of conformal prediction within the domain of Earth Observation (EO) applications. To accomplish this, we assess the current state of uncertainty quantification in the EO domain and found that only 20% of the reviewed Google Earth Engine (GEE) datasets incorporated a degree of uncertainty information, with unreliable methods prevalent. Next, we introduce modules that seamlessly integrate into existing GEE predictive modelling workflows and demonstrate the application of these tools for datasets spanning local to global scales, including the Dynamic World and Global Ecosystem Dynamics Investigation (GEDI) datasets. These case studies encompass regression and classification tasks, featuring both traditional and deep learning-based workflows. Subsequently, we discuss the opportunities arising from the use of conformal prediction in EO. We anticipate that the increased availability of easy-to-use implementations of conformal predictors, such as those provided here, will drive wider adoption of rigorous uncertainty quantification in EO, thereby enhancing the reliability of uses such as operational monitoring and decision making

An associative analysis of recognition memory: Relative recency effects in an eye-tracking paradigm

We report 2 eye-tracking experiments with human variants of 2 rodent recognition memory tasks, relative recency and object-in-place. In Experiment 1 participants were sequentially exposed to 2 images, A then B, presented on a computer display. When subsequently tested with both images, participants biased looking toward the first-presented image A: the relative recency effect. When contextual stimuli x and y, respectively, accompanied A and B in the exposure phase (xA,yB), the recency effect was greater when y was present at test, than when x was present. In Experiment 2 participants viewed 2 identical presentations of a 4-image array, ABCD, followed by a test with the same array, but in which one of thepairs of stimuli exchanged position (BACD orABDC). Participants looked preferentially at the displaced stimulus pair: the object-in-place effect. Three further conditions replicated Experiment 1’s findings: 2 pairs of images were presented one after the other (AB followed by CD); on a test with AB and CD,relative recency was again evident as preferential looking at AB. Moreover, this effect was greater when the positions of the first-presented A and B were exchanged between exposure and test (BACD), compared with when the positions of second-presented C and D were exchanged (ABDC). The results were interpreted within the theoretical framework of the Sometime Opponent Process model of associative learning (Wagner, 1981)

Test Performance in Optional Shift and Configural Acquired-Equivalence Are Positively Correlated

In 2 experiments, participants completed 2 computer-based tasks: a configural acquired-equivalence procedure and an optional-shift procedure. Both revealed that test performance was positively correlated, even when controlling for non-specific variables. This finding supports the suggestion that a common mechanism underlies performance in both tasks. Experiment 2 included eye-tracking to the stimuli used in the task. We found that participants who attended to the predictive compound elements in the optional-shift training went on to show stronger attentional-set effects in the subsequent test. The relationship between attention and performance is considered by reference to attentional and non-attentional learning theories