*4.2.1.2 Progressively improving deployment requires relative stability of neuronal groups*

Deployment strategy progresses from deploying individual neurons to deploying neuronal groups, to deploying groups of groups, etc., which requires a degree of stability in all the elements of the growing organization. This intuition entailed the notion of "neuronal packets" that is pivotal in the theory.

A neuronal packet is Hebb's assembly (i.e., comprises neurons connected by associative links) that is synergistic and is separated by a boundary energy barrier from the surrounding associative network.

It was hypothesized that packets form as a result of phase transition in associative networks, not unlike raindrops form in vapor. Accordingly, energy barrier is determined by surface tension, that is, the amount of free energy per unit surface (presumably, surface comprises cell membranes in the boundary neurons. Accordingly, surface energy is determined by the distribution of membrane potential across the surface). Neurons at the packet boundary constitute packet's Markov Blanket, surface tension in the boundary holds neurons together. Mapping these notions on the process in **Figure 4** will help appreciating its crucial consequences: first, combining neurons responding to A, B, C, D, E… in a quasi-stable bounded packet amounts to asserting existence (perceiving) some bounded entity (object) α comprising features α= {A, B, C, D, E…} and, second, synergistic packets allow 'tuning' to their

#### **Figure 8.**

*Neurons xi and xj are selected in the neuronal pool and tuned to stimulus C in the stimuli stream. Neuron xi responds to A, B, C stimuli, tuning amplifies its response to C. Sensing and motor actions are both products of active deployment (e.g. one sees color C because some neurons were selected, mobilized and tuned to C). Imagining color C involves the same process. Imagining A, or B, or C involves shifts in tuning, which can be expressed as rotating neuron's response vector. Co-firing of xi and xj establishes an associative link between them.*

individual constituents (rotating packet vector) which is experienced as envisioning different states, or facets of object α (e.g., rotating the image). Energy barriers 'anchor' determinations in Figure 4, e.g., once feature A has been attributed to objectα , the barriers will resist (require energy investment in) separating A from α . As a result, barriers serve the dual function of binding neurons together in stable groups and binding those groups to 'objects.' **Figure 9** illustrates these notions.
