The cortical column, also known as the minicolumn, is the basic functional unit of the cerebral cortex. The column is oriented perpendicular to the cortical surface, and consists of six distinct layers of neurons. Each cortical column consists of about 100 neurons. All neurons inside the column are tightly connected, although neurons connections extend to adjacent columns and columns far across the cortex and into subcortical areas, particularly the thalamus. Cortical columns are capable of memorizing relations and performing more complex operations than individual neurons; to extend the information processing analogy, if a neuron is analogous to a logic gate, a cortical column is more analogous to a small subroutine.
Other scientists are also arriving at similar conclusions as Burnod; Vernon B. Mountcastle's The Cerebral Cortex (1998) offers a good discussion of the structure and role of the cortical minicolumn.
Layer IV, which divides the column into supragranular and infragranular parts, receives its inputs from the thalamus and transmits signals to the rest of the column. The thalamus receives information from all parts of the cortex and subcortical areas. It works together with the cerebral cortex to create a feedback circuit by passing information from the infragranular cells of the cortex to the thalamus and then back to the layer IV cells of the cortex, with integration occuring both on in the thalamic and cortical centers.
Information flow in the cortex is mediated by the action of the supragranular cells, while additional information from the external and internal environment is integrated by the thalamus and arrives in layer IV of the cortical columns.
A fully activated column corresponds to an action. For instance, if the column is in a motor area, the layer V and VI cells are likely to project to a sequence of neurons that leads to the contraction of muscle fibers.
On the other hand, a partially activated column corresponds to anticipation or searching, and waits for the infragranular levels to become active.
Outputs: to other columns (II for distant, III for nearby) or to extracortical output (V, VI)
Inputs: Reticular, Thalamic (IV), Cortical (I, II, III, V, VI) and Existing State (results from local cellular memorization, both short-term and long-term)
Cortical columns represent goal, initial and intermediate states. When a goal is defined, activations spread from the goal column along the supragranular levels (I-III). These spreading activations eventually find a column which is simultaneously receiving the proper extracortical thalamic inputs.
Stimulated by both supragranular and infragranular inputs, the column becomes fully active, and effects extracortical action. This extracortical action modifies the environment and thus changes the new thalamic inputs. As a result, other columns which have up to now been supragranularly activated, but have not yet received the right thalamic inputs, become fully activated. The process continues until the original goal becomes fully activated.
The problem solving process under PDP parallels the sequential version, with the full activation of an intermediate column being analogous to solving a subgoal, and the spreading activation similar to searching. However, within the cortex many goals will be under progress simultaneously. The spreading activations and sub-actions are always interacting and interfering with each other.
Anything can be a goal: a motor or internal activity, the occurence of a certain sensory pattern, or a certain activity pattern of the cortex itself Note that there is no functional difference between a “goal” and a “subgoal”
Most importantly, call trees are a direct explanation for the cerebral cortex’s flexibility and adaptability in solving problems with great variation, i.e. pattern recognition, fine motor control. These tasks require the cortex to reach a certain goal given any initial state.
More Evidence for Call Trees: