Mental Murmuration: A Metaphor for the Workings of the Brain

"Employing the suggestive metaphor of neuroscientist Luiz Pessoa, David Brooks, in the New York Times, describes neural processing as "a flock of swirling starlings," otherwise known as a murmuration. That metaphor alludes to the continuously changing patterns of activation across the plethora of complex, interconnected neuronal networks that populate both the cerebral cortex and the brain's various subcortical structures. Such networks can contain anywhere from dozens to many tens of thousands of neurons."

"Those networks integrate inputs about: the current environment in which the person is situated and through which the person is navigating, the recent and current states of the person's body and motor activities, and the host of the person's mostly unconscious but potentially relevant cognitive and affective states (memories, emotions, desires, inferences, decisions, etc.). These networks are also constantly forwarding the results of their integrative activities with all of that information on to other networks with which they are directly connected,"

"Such endlessly changing patterns of activation are just like, for the swirling flock, the collective consequences of the many movements of the individual starlings, who are primarily influenced by the motions of the six or seven other starlings closest to them. It is worth noting that it is precisely the computational modeling four decades ago of these dynamics of neural networks that provided the foundational insights, tools, and techniques that have spawned the large language models that drive the new AI systems that have attracted"

Neural activity consists of continuously changing, distributed patterns of activation across complex, interconnected neuronal networks in cortex and subcortical structures. Networks can contain dozens to many tens of thousands of neurons. They integrate inputs about the current environment, bodily and motor states, and a host of mostly unconscious cognitive and affective states such as memories, emotions, desires, inferences, and decisions. Networks forward the results of their integrations to connected networks, producing downstream signaling and upstream feedback. The emergent collective dynamics resemble a murmuration, resulting from local interactions among neighboring units. Early computational modeling of these dynamics provided foundations for modern large language models and AI, showing the inadequacy of a container view of the mind.

Read at Psychology Today