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effect is asymmetric, such that area B is more active when area A is active, but not
the reverse.)
Figure 2.1 shows the results of one such analysis, for a set of action and at-
tention tasks. The graphs represent Brodmann areas that are significantly more
likely than chance to be co-active
2
; it is hypothesized that the net-
work of co-activated areas revealed by such analysis represents those areas of the
cortex that cooperate to perform the cognitive tasks in the given domain. The co-
activation graphs are superimposed on an adjacency graph (where edges indicate
that the Brodmann areas share a physical border in the brain) for ease of visual
comparison.
(
χ
>
3
.
84
)
Action
Attention
Fig. 2.1: Cortex represented as adjacency
co-activation graphs. Here the Brod-
mann areas are nodes, with
black lines
between adjacent areas and
orange lines
between areas showing significant co-activation. The graph on the
left
shows co-
activations from 56 action tasks, and the graph on the
right
shows co-activations
from 77 attention tasks. Edges determined using the threshold
+
2
χ
>
3
.
84. Graphs
rendered with aiSee v. 2.2.
Note that co-activation analysis is similar to, but distinct from, the approach
adopted by [31] in discovering “functional connectivity.” The main difference is
that edges in functional connectivity graphs indicate temporal co-variation between
brain regions. Moreover, the results they report generally represent the dynamics
of simulated neural networks (based on the structure of biological brain networks),
rather than the static analysis of data-mining imaging experiments. Hence we adopt
the term “functional cooperation” to distinguish our results from theirs. Neverthe-
less, there is presumably much to be gained by leveraging both sorts of analysis;
in a later section we describe one such future project for bringing co-activation and
co-variation graphs together.
The results of such analysis are not just visually striking, but afford the applica-
tion of some well-understood mathematical techniques to better understand features
of brain organization and functional cooperation. Of course, exactly what sorts of
