The Tree of Self

Diving into the Internal Family Systems (IFS) concepts and methodology led to these four insights at the intersection of the Four Needs Framework (4NF), IFS, and Adult Development Theory (ADT). 

Shearing Forces Lead to Multiplicity

At the core of the first insight is that the ever-present tension of the Four Needs and the resulting maelstrom of Existential Anxieties acts a powerful shearing force. I have been wondering before about the effect of the tug and pull of the Anxieties, and how there seems to be this rapid switching of Anxieties from one polar opposite to another. The framing of the internal family of Self, surrounded by Protectors and Exiles offered by Richard Schwartz provided a clarifying perspective: this process of rapid switching can be viewed as different, distinct parts within me taking the seat of consciousness one at a time. This idea hints at the notion that somehow, there’s an entire population of parts within me that emerged from my life experience. 
This is where it clicked: these parts are the outcome of my mind’s attempts to do its best to resolve the tension. Unable to bring coherence, especially at the earlier stages of my development, a split develops, creating two distinct parts. Each part embodies the respective Anxieties within the tension. Whenever the pull of Existential Anxieties proves impossible to resolve, the split repeats. Over time, the number of parts grows, populating the Internal Family System. Thus, the Fundamental Needs act as the part-splitting force, leading to multiplicity of agents within the System of Self that I was vaguely sensing last year. Unlike my early guesses back then, Dr. Schwartz provided a clear path to explore these parts and show that their formation does not correspond one-to-one to each Existential Anxiety (née Fear), but rather forms a unique sub-personality.

Branches Form a Tree

Taking this part-splitting idea further, it is evident that the splits form branches. The sub-personalities live the same story (that is, share identical models and sense-making capacity) until the split, but continue separate developmental journeys thereafter. When I have a conversation with a part–especially an Exile!–it is often a younger version of me, stuck in some past traumatic event. Unlike the branch that developed into a trunk to grow further, this branch remained undeveloped.

This is where the second insight arrived: these parts, these sub-personalities, branch by branch, form a Tree of Self. Some branches stop growing. Some turn into trunks to sprout new branches. This tree is a whole that is both coherent and disjoint. It is coherent, because every two parts share the same beginning of their life story. It is disjoint, because at some point, the story unfolds differently for each of the two. 

In this way, the Tree of Self is not like a tribe or a family. A tribe comes together as separate people deciding to become whole. When a family is formed, an offspring does not share the story of their parents: the story is conveyed through words, but not lived experience. In the Tree of Self, all parts are rooted in the same life story.

This same-rootedness is why the IFS practice appears so effective: at the core, all my parts recognize themselves in each other. They are innately connected in the ultimate kinship, and want to be whole. Unlike a tribe or a family, there is no “before” where the parts existed separately. The story began with oneness, and the part-splitting is just the middle of their hero’s journey. The happy ending that every part yearns for is togetherness.

The Tree Evolves as it Grows

This tree-like arrangement led to the third insight. The Tree of Self grows across developmental stages. Continuing the tree metaphor, each transformation to the next stage is a material change. New growth becomes more capable of managing the shearing forces. At earlier stages, the strategy for managing these forces might be the part-splitting. The later stages bring more resilience, leading to fewer splits. I am picturing this as the tree growing upward through the layers of atmosphere, drawing on the idea of “vertical development.” Each layer represents a developmental stage, starting with the earlier stages closer to the ground and later stages stacking on top.

Some branches reach into the later stages, and some are stuck at the earlier. Since each branch represents a sub-personality, each may occupy the seat of consciousness. As a result, what I show up like may appear as a scattering of selves across multiple stages of development. The ADT phenomenon of fallback effect speaks to the idea that in some situations, the lower-to-the-ground branches are more likely to claim the seat. 

Self-work as the Journey toward Wholeness

Recognizing this multiplicity and diversity across stages has been very clarifying and produced the fourth insight. The aim of self-work might not be about learning how to reach the higher stages faster, willing my branches to reach higher and higher. This process of growth seems to happen regardless of whether I want it or not. Instead, self-work might be about nurturing the Tree of Self to wholeness. The Tree of Self is whole when each branch has been examined and given attention, support and room to grow. IFS session transcripts often talk about how a healed Exile rapidly matures, as if catching up. My guess is that moment and the feeling of closure and quiet satisfaction that accompanies is the increase in wholeness of the Tree of Self. The previously-shunned branch soars to join the rest of its kin. 

There’s something very peaceful about this framing. Self-work is revealed as gardening, an infinite game of nourishing all branches of the Tree of Self, and helping it become whole even as each branch continues to grow.

Transformational Learning

Building on the ideas in The Suffering of Expectations, I want to look more closely at the expectation gradients. These are predictions of future experiences, and they can have negative or positive values. Negative values indicate that I expect a future that is worse for me than it is now, and positive values are the opposite: I expect the future to be better than the present. The steeper the slope, the more dramatic the future outlook. Worse outcomes look catastrophic, and better outcomes promise pure bliss. The gentler slope leads to a slightly worse or slightly better future. The way I like to imagine it is gauging how quickly a murky lake gets deep as I wade into it.

Expectation gradients are shaped by my previous experiences. My mind subconsciously sifts all of my past experiences, finds–or synthesizes!–the best match and this match now becomes the expectation gradient. So, if I had a really terrible experience and the situation appears to match the beginning of that experience, I will feel a steep negative expectation gradient — whoa, that lake bed is dropping away fast! Conversely, if the present appears to match the start of a mild or pleasant experience, I will feel a gentle or upward-sloping gradient.

Sifting through all past experiences can be expensive, and I am not blessed with a source of infinite energy, so there’s an optimization process at play that relies on prediction errors. Each prediction is compared with the actual outcome, and a prediction error is computed. Prediction errors are a signal to organize my past experiences. Lower prediction errors reinforce the value of the experience used to make the prediction. Higher errors weaken that value.  This continuous process fine-tunes how my mind makes predictions. Higher-valued past experiences are looked at first, as they are more likely to repeat. The experiences with the lower value are gently pushed to the bottom. This process of ranking allows my mind to work more efficiently: skim the top hits, and ignore the rest. Energy saved! Another word for this optimization process is informational learning: every bit of new information is incorporated to improve my ability to make accurate predictions.

At this point, I want to introduce the concept of prediction confidence. I continue to have experiences, and they fuel the learning. Ideally, this process results in effective predictions: a clear winner of a prediction for every situation. A less comfortable situation happens when there does not seem to be a clear winner. Here, matching past experiences to the present produces not one, but multiple predictions that vary in their slope. Expanding the wading-into-lake analogy, it feels like even though I took the same exact path, the lake bed had a different shape at times. Most times, it had a nice and gentle slope, but every so often, the same exact bed somehow felt steeper. I swear, it’s like the lake bed had shifted! Now that’s a puzzler.

To reflect on the nature of prediction confidence, consider the framing of complexity of the environment. If the environment is simple, then my experiential journey quickly produces a perfect map of this environment and I am able to make exact, 100% confidence predictions. If this then that — bam! In a simple environment, the list of my experiences wading into the lake has only one item, because it repeats every time with clockwork precision.

The more complex the environment, the more fuzzy the prediction matching. If the environment is highly complex, I may find myself in a situation where I have near-zero confidence predictions: every situation might as well be brand new, because I can’t seem to find a match that isn’t the whole set of my experiences. Walking into the lake is a total surprise. Each time, I find a seemingly differently-shaped lake bed. What the heck is going on?

In such an environment, energy-saving optimizations no longer seem to work, and if anything, hinder the progress. It’s clear that something is amiss, but the existing machinery just keeps chugging away trying to build that stack rank — and failing. How can the stupid lake bed be so different… Every. Fricking. Time?!

This crisis of confidence is an indicator that it’s time for change, for another kind of learning. Unlike informational learning, which is all about improving my ability to make predictions within a situation, the process of transformational learning is about uncovering a different way to see the situation. The outcome of transformational learning is a profound reevaluation of how I perceive the environment. It is by definition mind-boggling. Transformational learning feels like discovering that all this time, when I was feeling the lake bed shift under my feet, I was actually only perceiving my own movement along one axis. I was assuming a two-dimensional space, unaware that there’s another dimension! Whoa. So the lake bed isn’t moving. Instead, I wasn’t accounting for my own movements across the shore. If I incorporate the “lake shore” axis, all of these past experiences suddenly snap into a static, three-dimensional map of a lake bed.

Transformational learning is a rearrangement of my past experiences into a new structure, a new way to organize them and produce a whole different set of predictions. Also necessarily, the letting go of the old way and the acceptance of the uncertainty that comes with that. A three-dimensional map of the lake bed represents the environment more usefully, but it is also more complex, allowing for more degrees of freedom and requiring more energy to operate. Another long journey of informational learning awaits to optimize my prediction-making machinery and turn this novel perspective into a familiar surrounding — until the next transformation time.

Whenever I get that sense of the shape-shifting lake bed, in these “what the heck just happened, this is wrong!” moments, I take comfort in the notion that transformational learning awaits. Though it might not offer immediate insight right then and there, this movement of the surface, a seemingly exogenous change is a signal. It tells me that I am approaching yet another edge of my current understanding of the environment, and a new perspective beckons to be revealed.