Tag Archives: Neuroscience

Cognitive psychology and the Jungian mental processes, Pt. I: Ni/Si (“introverted intuition”/”introverted sensing”) and long-term memory

[Addressed to the INTJforum ‘MBTI and Personality Theories’ sub-forum]:


Easily the most prevalent complaint about the so-called Jungian or ‘cognitive’ functions is that they lack too much empirical support to warrant the frequently charitable assumptions made in discussions surrounding them. Many of the frustrations of people who remain skeptical of the functions thesis can be captured by the fact that, at least at present, the functions do not (easily) lend themselves or stand up to scientific scrutiny or testing (or funding).

The idea behind this post (and possibly future ones like it) represents a desire on my part to hopefully mitigate some of the above-named concerns, by highlighting just a few of the real connections between our accepted understandings in cognitive psychology, and how we (viz. casual and expert commentators, and typologists like Berens and Nardi) generally conceptualize the functions. As this can be approached in a number of ways, for the purpose of not rambling myself to death at one time, I will narrow the scope of this post to Ni, Si, (as much about them as we think we might know, in this preliminary stage) and how modern-day cognitive scientists understand memory.

Chapter 1:

The Jungian functions

It is commonly considered that Si has a memory component to it. Indeed, Dario Nardi’s own observations on the subject seem to validate this when he notes that:

“Si types may get ‘in the zone’ when reviewing past events…ISTJ and ISFJ easily enter an expert flow state while recalling, particularly if they close their eyes and take the time to immerse themselves in the memory, reliving it in rich detail” (Neuroscience of Personality, p. 94).


“[Si types] have a propensity for rote memorization, repetition, and in-depth reviews of daily events…Si types are highly capable at recalling information that has little or no context, such as lists of random words…” (NoP, p. 94)

But what most seem to leave out in their examination of Si is that, like Ni, it is predictive and allows users of it to “consider the future” (NoP, p. 95). Nardi notes that both Si and Ni types show moderate-high activity in a brain region that helps us do this, especially insofar as it is helping us plan our own actions ahead of time.

Conversely from Si, Ni is most commonly thought of as the ‘predictive’ function, or the one that most often and accurately allows us to predict what will occur in the future. Though Ni’s power to do this is clearly exaggerated in the mainstream typology culture, I will not attempt to dispel this misconception at the present time. Suffice it instead to point out what Nardi observes about Ni types, who “may easily show a zen state [overall brain pattern] when tasked to envision the future” (NoP, p. 102). And whether you want to call them Ni or NJ types, it is common for these types to self-report in confirmation of this observation made by Nardi in his MBTI-EEG studies.

But Nardi doesn’t mention how Ni looks back in time, or even how Si looks ahead. Probably our forum’s leading proponent of the functions model, whom we all know (to varying degrees of reverence) as […], stated it thusly:

“Ni can deduce the past from the present, and predict the future from the present, in terms of dynamics. Si instead sees things as mostly constant, and tends to be surprised by change. Both Si and Ni are predictive, but Ni types tend to impress others in terms of predicting things that were not ‘obvious’. (I.e., it’s obvious that if this is a rock, then it was a rock, and it will be a rock in the future; it’s not obvious that this is/was a meteorite that fell from the sky, and contains metals/isotopes that aren’t commonly found on Earth.)

And while his example regarding the rock, there, might receive mixed responses from the subforum community, the important point to focus on is that both Ni and Si are predictive and backward-looking functions, though they differ greatly in how they go about fulfilling those purposes.

Now, for those of you who have had enough Nardian ‘pseudoscience’ for one post, you can rest assured that from this point, we will be moving on to ‘actual’ cognitive psychology (though we will still be establishing its relations with Ni and Si in their primitive, abstract forms).

Chapter 2:

Mainstream cognitive psychology

In going forward, readers might find it helpful to keep this handy reference chart in view–but they should note that for the purposes of this post, we will be restricting our scope specifically to declarative (or “explicit”) memory:

(For more on long-term memory’s sub-systems, see here: http://en.wikipedia.org/wiki/Long-term_memory#Divisions_of_long_term_memory)

The important things to keep in mind (or commit to memory, as it were!) are that:

  • Explicit memory includes all memories that we consciously seek to store and retrieve. These memories are also called declarative memories because they include events that we have deliberately learned, such as ‘I enjoyed playing poohsticks in Sussex’ or facts, such as ‘they grow coffee in Brazil’, and can be described or ‘declared’ to others (Milner, 1965). Explicit/declarative memory is further divided into semantic and episodic memory” (Revlin, Cognition: Theory and Practice p. 152-3).
  • Episodic memory stores and connects the specific times, places, and events in an individual’s life…our episode memory gives rise to the conscious experience of recollection (Tulving, 1982, 1985; Wheeler, Stuss, & Tulving, 1995, 1997)…[and] allows us to travel back mentally in time to earlier moments in our lives not only to retrieve a fact, but in many cases, to relive the experience [retrospective memory]…episodic memory also allows us to travel forward mentally in time in order to remember to do things in the future [prospective memory]” (Revlin, C:T&P p. 153).
  • Semantic memory retains conceptual knowledge stored as an independent knowledge base. It is the library where discrete facts like ‘dogs bark’ and ‘robins are birds’ are stored. Your memories of where you were when you first learned such facts, however, are considered part of episodic memory” (Revlin, C:T&P p. 153).

“As a result of implicit memory‘s functioning, we are able to learn without being aware that we are doing so (e.g., Graf & Schacter 1985), and we can retrieve or use that information without being aware that we have stored it in memory” (Revlin, C:T&P p. 153).

I believe that understanding the two types of declarative/explicit memory presented is key to understanding the memory components of Ni and Si. (For those interested in why I don’t consider implicit memory relevant to the present discussion, see the paragraph below and feel free to comment on its contents.)

[[[I don’t believe implicit memory is particularly important to understand, here, since it functions “semiautonomously”, meaning that its mental functions operate automatically and “in the background”. Treatments of the Jungian functions as unconscious processes are more apt to describe how each type’s tertiary and inferior functions work (in generally inopportune ways), whereas the dominant and auxiliary functions are those that we are conscious of (though it is true that we tend to take the dominant’s operation for granted, as it’s essentially the ‘water we swim in’ and we’re too used to it to take much ‘conscious’ notice). Further, the EEG technology which Nardi utilized only measured neocortical brain activity, meaning it could only be used to analyze the topmost (and newest) layer. As this layer corresponds most closely with conscious and observable thought processes, implicit memory’s mechanics are a little trickier to uncover without more sophisticated brain-imaging technology.]]]

Based on the quotes whose respective authors I’ve cited, the connections between Ni/Si and explicit memory should become clearer. Si thrives on reviewing past events in rich detail, which correlates strongly with our understanding of episodic memory. Both Ni and Si engage in prospective memory, and at least Si engages in retrospective memory (“reliving [past experiences] in rich detail”, as Nardi observed). Finally, Si certainly utilizes semantic memory, which serves as a “library where discrete facts are stored”.

The above seems to leave Ni a bit in the dark, however. Specifically, two questions are left unanswered: 1) Assuming it can equally well engage in retrospective memory, how does it do so in a manner distinct from Si?; and 2) Given that Ni is far more apt to store relations and abstract principles than “discrete facts”, what is Ni’s relation to semantic memory? Might it be that there is some other memory bank which has been either unexplored in cognitive psychology, or left out of the present discussion? For now, I will leave these questions to readers to examine, though I will do so myself in a (hopefully, though not necessarily) timely manner.

In closing

My point here hasn’t been to ‘prove’ or ‘disprove’ the functions. Rather, I went forward with the assumption that the functions are worthy of further refinement and scrutiny, and in this early stage of their treatment the best we can do is ensure that they be defined in terms as technically precise as possible. If this can be done, then perhaps the functions can someday be studied in a more rigorous and scientifically-respectable manner–and there are, for purposes of better understanding ourselves and others, very compelling reasons for the rich variety in cognitive modes across humans to be elucidated and properly accounted for.

Artificial Intelligence: Can Science Truly Recreate You? [Daily Nexus//Science & Tech, 8.28.2014]

With the unprecedented rise of millennial computing, lightning fast telecommunication, vibrant social media and virtually limitless access to information, our lives are consumed by a torrent of powerful technological influences.

The gap between who we are at a deeper, more philosophical level and who we appear to be on our various web profiles is simultaneously widened and blurred by recent scientific and technological advancements. “Who we are” has become a vexing and tiresomely complex concept, and in our push toward increasingly more efficient modes of survival, we seem to have run out of collective patience with it.

Yet in spite of this, debates over what makes us who we are continue today. The age-old question of how our minds interact with our bodies has been passed off from philosophers to computer scientists and engineers. Some of the latter figures claim that the advent of robotics and more sophisticated computing methods has made inevitable what Google engineering director Ray Kurzweil refers to as our “next stage of evolution”— by which he means artificial intelligence. A.I. is, in simplified terms, a rapidly accelerating field that tries replicating human functions and capabilities in machines to the fullest extent that current technology allows.

But is it possible for machines to exhibit complete human intelligence and consciousness?

UC Santa Barbara Psychology professor Stan Klein, whose research focuses on issues related to social knowledge representation, said that mainstream psychology believes that humans are machines, and thus can be understood from principles that comprise the backbone of modern applications in machine technology.

“The materialist dogma of modern science threatens to remove the [mind-body] issue from discussion, since it does not fit their metaphysical presumptions,” Klein said. “Perhaps they are right — or perhaps one can intelligently widen the scope of physicalism to encompass experience.”

At the forefront of such “physicalist” groups today are neuroscientists, many of whom believe that the mind can be fully reduced to electrochemical and mechanical bodily functions. From this perspective, replicating human consciousness in machines may prove less difficult than expected.

This possibility once pondered only in science fiction thrillers (in which the robots typically end up rebelling against their creators and destroying humanity) is becoming more compelling with the integration of technology and automation into nearly every facet of our lives, and may even become perfectly natural.

But is it scientifically feasible?

Albert Shin, a UC Santa Barbara Philosophy doctorate alumni and visiting assistant professor at Villanova University, said that even if we can explain the various workings of the brain, we are still missing something in our explanation of day-to-day conscious experience.

“With recent developments in cognitive and neuroscience, it is easy to think that all there is to the mind is a collection of brain cells,” Shin said. “Admittedly, the evidence suggests that there is a much closer relationship between mind and body than was argued by dualists like Descartes. But it would be a mistake to jump to the conclusion that all there is to the mind is simply matter.”

How these debates will pan out is still yet to be determined. But in proceeding, we should not forget to keep asking ourselves two basic questions. Who are we? And to what extent can — or more aptly, should — we allow science to answer that question for us?

[Feature image courtesy of Christine Daniloff/MIT]