Instructions are attached · Respond to at least two (2) peers · 200 words each peer response ·

Instructions are attached 

·
Respond to at least two (2) peers

·
200 words each peer response

·
APA format in-text citations and references

Peer 1: Ashley

After reading this week’s text, the simplicity of a model and its capacity to explain phenomena are critical factors in assessing the merit of a scientific theory or model (Bouton, 2018). The principle of simplicity suggests that a theory should remain as straightforward as possible, adequately explaining the data or observed events. This concept is encapsulated in Occam’s razor, which advises that when faced with competing theories, the one with the fewest assumptions should be chosen (Bouton, 2018). Such simplicity enhances the elegance, comprehensibility, and broader applicability of a theory.

Conversely, explanatory power is the ability of a theory to effectively explain and predict phenomena. A theory with strong explanatory power can encompass a broad spectrum of observations and reliably forecast future events (Bouton, 2018). However, if a theory is overly simplistic, it might not possess sufficient explanatory power to address the full breadth of a phenomenon. Likewise, a theory that is to complex might become cumbersome and challenging to utilize effectively (Bouton, 2018).

The theory of Attention, Emotion, and Somatic Markers Operating in Parallel (AESOP) presents a compelling example of how a theory can effectively balance simplicity with explanatory power. This theory seems to suggest that attention, emotion, and somatic markers function concurrently to influence decision-making and behavior. I feel it is elegantly simple, proposing a unified mechanism for these processes, yet it also accommodates the complex interactions among cognitive, emotional, and psychological elements that shape decision-making. This dual capacity makes it a robust framework for understanding how we navigate choices and actions.

In the context of the journal article “Building a Science of Animal Minds: Lloyd Morgan, Experimentation, and Morgan’s Canon,” I believe Fitzpatrick and Goodrich (2017) discuss Morgan’s contributions to animal psychology, his experimental methodologies, and how Morgan’s Canon shaped the evolution of scientific perspectives in the study of animal minds. It seems that this principle advises that when interpreting animal behavior, researchers should seek the simplest possible explanation and avoid attributing complex human-like cognitive abilities, such as reasoning or consciousness, to animals unless simpler explanations are ruled out. Morgan’s Canon seems to have pushed for more scientifically rigorous methods, promoting observation and experimentation over subjective interpretation (Fitzpatrick & Goodrich, 2017). The incorporation of attention by Mackintosh, and Pearce and Hall, was crucial, given the significant role that attention plays a learning and decision-making (Bouton, 2018). Theorists did not hastily introduce this new element; rather they acknowledged the critical importance of attention in animal behavior and methodically worked to integrate it into the established theoretical framework (Bouton, 2018).

I believe changes in attention can provide a useful perspective for understanding latent inhibition, which involves the diminished ability of a previously irrelevant stimulus to trigger a conditioned response. Additional mechanisms can adjust the prominence of the stimulus, influencing its potential to be linked with conditioned response. Moreover, Wagner’s concept of CS surprisingness, which emphasizes the importance of a stimulus’s novelty or unexpectedness in learning, offers another valuable explanation for latent inhibition.

Bouton, M. E. (2018). Learning and behavior: A contemporary synthesis (2nd ed.). Oxford University Press.

Fitzpatrick, S., & Goodrich, G. (2017). Building a science of animal minds: Lloyd Morgan, experimentation, and Morgan’s Canon.
Journal of the History of Biology,
50(3), 525–569

Peer 2: Mackenzie

A practical explanation should be capable of being reduced to layman’s terms in nearly any subject without losing its explanatory power. Suppose an explanation stretched to its max in terms of complication is the only way to describe the topic. In that case, most people outside of the relevant field can gain no understanding. For example, what if physicians could not simplify the meaning of our X-rays, brain scans, or bloodwork? The answer is, unless we were a physician or in a closely related field, we would never understand what they told us. On the other hand, if a simple explanation cannot be stretched and understood on a more complex level, it might suggest that it is arbitrary or underdeveloped. A “good” theory can be simplified in lay terms but also be examined thoroughly and separated into components that describe the complexity of its framework. That said, Morgan’s Canon is still fundamental today.

In my opinion, AESOP is a “good” model. It extends our understanding of conditioning with the additive power of emotions and how they can affect and contribute to conditioning. Moreover, it helps explain how emotions affect our responses, which can be critical in understanding conditioning and, similarly, how to decondition. Emotions are an enduring aspect of humanity–to negate addressing the importance of them would be a critical error. Despite the innovation of AESOP, later models, like those developed by Mackintosh, and Pearce and Hall, were a bit redundant since concepts like inhibition and surprisingness were already central aspects in models like the Rescorla-Wagner Model. Mackintosh and Pearce and Hall extended what the literature already knew about inhibition and surprisingness, respectively, and added depth to these concepts. Be that as it may, their research added to the framework of how conditioning is understood practically and conceptualized how inhibition, attention, and surprisingness influence it. The changes these theorists provide, specifically about attention and surprisingness, focus on the predictiveness and amount of attention placed on stimuli and the corresponding effectiveness of conditioning. These contributions help explain how latent inhibition occurs through the surprisingness of a US and the attention focused on it, with a consensus referring to decreases in attention and pre-exposure likely leading to slower learning rates.

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