Luiz Pessoa
Department of Psychology
Maryland Neuroimaging Center
University of Maryland, College Park
 Michael
 Lucina
 Josh
Anderson: Franklin & Marshall
Uddin: Stanford/University of Miami
Kinnison: University of Maryland
 One-to-one
mapping
“fear”
F1
F2
F3
F4
A1
A2
A3
A4
amygdala
 Many-to-many
mapping
“fear”
“value”
F1
F2
F3
F4
A1
A2
A3
A4
amygdala
ventral striatum
?
Emotion
Cognition
Motivation
Perception
Action
…
 Understanding
brain regions via functional
repertoires: multidimensional
Passingham et al. (2002)
Regions
 Understanding
brain regions via functional
repertoires: imaging data
Task domains
(ontology)
BrainMap
NeuroSynth
 Understanding
brain regions via functional
repertoires: imaging data
 Regions
 Use
will be more or less “diverse”
Shannon Entropy
Anderson, Kinnison, and Pessoa (2013), Neuroimage
Network fingerprint
Toro et al. (2008)
Fronto-parietal “attention” network
(co-activation of BrainMap data)
Toro et al. (2008)
Cingulo-parietal “resting-state” network
(co-activation of BrainMap data)
Deen et al. (2010)
Determine co-activation partners
(using NeuroSynth)
Uddin et al. (submitted)
Determine co-activation partners
(using NeuroSynth)
Uddin et al. (submitted)
Determine co-activation partners
(using NeuroSynth)
Uddin et al. (submitted)
Common fingerprint
All insula sub-sectors are highly diverse
(cf. tripartite cognitive-affective-interoceptive scheme)
“Specific” fingerprint components
mean
Sadness
Happiness
Fear
…
Phonology
Working memory
Reasoning
…
Left dorsal anterior insula
“Specific” fingerprint components
Dorsal
“Cognitive”
Posterior
Ventral
“Affective”
 Fronto-parietal:
“attention”
Toro et al. (2008)
 Cingulo-opercular:“resting-state”
 Dorsal attention:
“endogenous attention”
 Ventral attention:
“exogenous attention”
 Fronto-parietal:
“rapid adaptive control”
 Cingulo-opercular: “stable set control”
 List
goes on and on…
Task positive
Task negative
 Evaluate
whether two sets (i.e., networks)
of fingerprints are drawn from the same
parent distribution
• “Statistical energy” (Aslan and Zech, 2005)
 Statistical
energy
X
Y
 Permutation
testing of ϕXY
Task-positive
Task-positive vs.
Task-negative (co-activation; Toro et al. 2008)
vs.
(co-activation data)
Dorsal attention
(resting-state; Yeo et al. 2011)
 Assortativity:“like
connects with like”
 Statistical
energy
 “Functional distance”
• Pairs of regions within a network
• Pairs of regions between networks
X
Z
Y
Networks
“Dorsal attention”
“Ventral attention”
Dis-assortative
“Default network”
Dis-assortative
“Default network”: should fragment into
several subnetworks
 Characterize
contributions of individual
brain regions and networks without using
singular task-bound functional
attributions
 Described
quantitative property of
networks – functional assortativity – that
can be useful in understanding the
functional and compositional similarities
and differences between networks
Structure-function mapping
Behaviors
Cognitive
Neural
computations
Brain areas
NC1
NC2
A1
NC3
A2
Network 1
NC4
A3
Network 2
A4
Network 3
Pessoa (2008), Nature Reviews Neuroscience
• Michael Anderson
• Josh Kinnison
• Lucina Uddin
National Institute of
Mental Health
emotioncognition.org