Associative Trails, Connectivity, Networks, Rhizomes, Learning

[865 words]

As is my wont, I’m throwing together a bunch of semantically charged bits, following an only partially conscious, mostly intuitive process, a kind of ADHD fluttermind effect that arises from neural activity in my brain. To nail down some of these flighty connections and intuitions, I will explore it further here and, as much as possible, make the gist of my “associative trail” meaningful for others. This post follows my having watched Gardner Campbell’s conversation with Jon Udell and Jeremy Dean about [Vannaver Bush’s] “As You May Think,” Annotation and Liberal Learning, along with other texts and videos on cognition, on neuroplasticity, on technology, on memory and on learning. I have not marked the various intellectual rabbit trails that I’m pulling together here, but will seek to do so, over time, probably using Hypothes.is.

Part of the way that I’m thinking about this is straightforward “old-school” analogy (which is a kind of connection across difference). Here’s the way I’m thinking: I know that brains work through a complex mechanism of dynamic networks. We still don’t know exactly how consciousness and thinking arise from large numbers of interconnected neurons stimulating each other in certain ways, but that seems to be how our brains — our mind-generators — work. It amounts to connections that are dynamically self-managed and networks that produce certain cognitive functions. Those neural networks collaborate and connect with other networks to produce increasingly complex cognitive functions, and those dynamic structures are iterated and reiterated dynamically, scaling up until they generate those effects or results or entities that we identify as “thought,” “learning” and “mind.”

Learning takes place by making new connections, by building networks of meaning, by noting and reiterating the way in which certain stimuli produce a kind of “pow!” that is impactful and meaningful. If, in my analogy, individual human beings function as if they were neurons, what they do, then, is respond to stimuli. Once a stimulus reaches a certain level, the person/neuron unit acts in a way that stimulates one or more others in a network, which can then produce cascades neurons and networks firing, reacting, interacting with other neural nodes or concepts or cognitive bits and pieces. Over time, connections are forged, then strengthened or pruned, leading to a dynamic yet stable pattern of learning.

What I’m trying to suggest is that there may be ways in which learning is both individual, but also collective. There may be ways in which this whole process of associative trails builds significant patterns over time. And from those patterns emerge the dynamic yet stable results of collaborative learning. Individual learning, intuitions and associative trails count. But perhaps, they are all the more impactful when they connect to others. After all, if we think about scholarship, or even about intellectual culture more generally, it is about individual cognitive processing, but also about connection. It’s about communities of learning, of research, of thought. And now, with emerging open technologies and new tools that facilitate collaborative learning over time — from traditional scholarship, for example, to online learning communities and web-based annotation tools like Hypothe.is — we have have better modalities of learning, new ways of making connections and associations of deep and resonant value that shape communal thinking. Such tools help construct layers that may ultimately result in more complex, more meaningful, more impactful learning.

(I guess the question to ask is how one goes about pruning those associative trails or those connections that are not helpful or productive. How does one choose or discern? A difficult question.)

Another way to think of it is as a kind of learning ecosystem. Each part of that system can function individually, but the true beauty of the ecosystem is the way in which everything is interconnected in a kind of dynamic but generally stable system of interchange, mutual benefit, exchange, stimulus and reaction. I think of the vast mycorrhizal networks, loosely connected with tree root systems that help regulate forests, for example. (One suggestive video to watch on this topic is Susan Simard’s TED Talk on “How Trees Talk to Each Other.”) This way of thinking about it — seeing analogies and correspondences between neural networks, mycorrhizal networks, communication networks, networks of learners — resonates in significant ways with Gilles Deleuze and Félix Guattari’s  Mille Plateaux (Paris: Éditions de Minuit, 1980) [A Thousand Plateaus, trans. Brian Massumi (Minneapolis: U of Minnesota, 1987)].

If the modality that I am talking about amounts to facilitating the growth of complex, multilayered, interconnecting and interpenetrating ecosystems of thought, of learning, of mind, my earlier difficult question can be rephrased to wonder what the analog for biochemical mechanisms that regulate or shape the overarching system might be. What complex dynamic process will “select” the strong and meaningful nodes and connections for building resiliency? What processes will target those connections that are destined to be pruned because they contribute too little to the long-term survival of the complex system?

Is there, in fact, a way in which learning, technology and connection are weaving themselves together for the construction of some greater learning/thinking entity? (Teilhard de Chardin’s noosphere?) Is this thread simply delusional? Those questions merit further thought. I’d be interested to hear other perspectives on these random musings.