Week 8

There are a few topics this week: intelligence, tool using and mental imagery.

Chapter 35 first discussed a little bit about individual differences in animal intelligence, such as one pigeon being able to solve problems within a fraction of the time that other pigeons could, and that certain birds’ ability is correlated with their plumage colorfulness. I think these are super interesting and also largely overlooked in the other review articles we have read so far. It would be great to see more animal studies with larger sample sizes and more analyses on individual differences, because I think the variance itself could be an interesting topic to discuss.

Chapter 35 also presented various approaches to study “intelligence”, such as discrimination learning, serial reversal learning, transitive responding, mental rotation, etc. However, overall it seems like the tasks cover a wide range of different mental abilities, yet it’s somewhat unclear (and probably debatable) how “intelligence” is defined. For example, pigeons seem better than humans at mental rotation, but they are also worse than humans at many other tasks, so it’s hard to say based on these results how pigeons and humans compare in terms of “intelligence”, and it seems like “intelligence” is just an umbrella term that doesn’t really refer to anything specifically.

The evolutionary explanations of brain/intelligence development in the rest of Chapter 35 is a super interesting topic. In terms of brain sizes, the authors mentioned that larger animals have larger brains mainly because of the necessity to connect more sensory, secretory, and motor elements. However, they also said that larger animals, such as dolphins, whales, and elephants, may “benefit from the absolute size of their brains giving them a straight advantage of scale”. These seem a bit contradictory to each other, and I wonder to what extent being larger in size has a benefit on intelligence. I assume it is more difficult to study larger animals than smaller ones, though, so maybe the data is limited (?). Additionally, the authors also compared brain structures between birds and mammals, and found structures that evolved in parallel (mammalian neocortex and birds’ dorsal pallium). I’m not very familiar with birds’ brain structures, though. How much are they different from human brains? It would be nice if there is a brief introduction to this…

Bluff et al. (2007) talked about the impressive tool-oriented behaviors (TOB) in New Caledonian crows. However, the authors’ major argument was that these impressive behaviors were not due to particularly high-level cognition. They designed a ingenious studies to examine the emergence of tool using, and found that the crows didn’t show much social learning from experimenters’ tool using, but they were able to start manipulating the tool by default. They were also able to learn through mere exposure to the tools made by human. In later experiments, they demonstrated that the crows didn’t have much reasoning on the causal relationship between their tools/actions and rewards, but might be merely learning the stimuli associatively based on trial-and-error. However, here I wonder how much we could say that humans actually “understand” causal relationships rather than simply learning the associative nature between actions and stimuli. Of course, humans are more advanced in terms of making and using tools, yet it could be due to other factors, such as that we are better at imagining or mentally simulating the results based on the physical rules of the world (which we could memorize well), and that we are better at memorizing various previous solutions and generalizing to similar problems. I think humans for sure can have a lot of trouble distinguishing between causation and correlation in the real world, and sometimes people do demonstrate the same behaviors as the crows, such as trying different things to solve a problem without knowing why it should work. For example, I have tutored math and programming before, and it was extremely frequently that I saw people attempting a problem with methods that they simply knew exist (such as the solution to another problem they just encountered), but in fact completely irrelevant to the current problem. Moreover, although I could do better on these problems than the students I was tutoring (for example I might be able to find the correct method to a problem quickly and knew why I should apply a certain method to a particular problem), I am not sure if that’s only because I’ve had more practice on those problems and thus knew the associations better. Therefore, I feel like it’s hard to say that humans reason about causality because we “understand” (as opposed to that we simply make better associations and feel like we understand), even though we could reason correctly more often than animals. In other words, based on the findings in this paper, I would agree that crows may not be as good as humans in terms of reasoning about tool usage, but I am not sure that’s because crows didn’t not understand causality while we do — it could be just that we are better at making associations and transitive reasoning.

This is also relevant to the next paper on mental imagery, which entails reasoning about missing information.