En el marco del Proyecto Anillo CONICYT SOC-1101 de Investigación en Ciencias Sociales de la Universidad del Desarrollo y el Centro de Investigación de Complejidad Social, se realizó un encuentro en el cual se propuso generar un espacio de diálogo multidisciplinario con destacados expertos nacionales provenientes del ámbito clínico y académico.

1. El Cerebro Social
Aproximación de las neurociencias al estudio de la habilidades
sociales
Pablo Billeke
División de Neurociencia
CICS – UDD

2. Presentación
• Introducción
• ¿Por qué estudiar el cerebro social?
• Métodos de investigación
• ¿Cómo estudiar el cerebral social?
• Redes cerebrales sociales
• ¿Cuáles son los componentes del cerebro social?
• Investigación de toma de decisión sociales
• ¿Qué aplicación puede tener el estudio del cerebro social?

3. Introdución
¿Por qué estudiar el cerebro social ?

5. Neocorteza en primates

6. Hipótesis del cerebro
social:
Encefalización y tamaño del
grupo

7. Inteligencia Social
• Tempranamente en el desarrollo (2.5ª), el dominio de
las habilidades sociales nos diferencian del resto de
los primates
1. Herrmann, E., Call, J., Hernàndez-Lloreda, M. V., Hare, B. & Tomasello, M. Humans have evolved specialized skills of social
cognition: the cultural intelligence hypothesis. Science 317, 1360–1366 (2007).
of the tasks, a human experimenter
d a table facing the subject through
ndow (children and some apes) or a
apes only). The window had three
ferent positions, through which
d insert a finger to indicate their
necessary (figs. S1 and S2). On all
ways waited until the subject was
efore beginning a trial. For trials
oice, the position of the reward was
ced across either two or three
ending on the task) but the reward
den for more than two consecutive
ame place. In a few tasks, subjects
other setups, requiring them to do
s to use a simple tool, follow gaze
esture to E1 (25).
responses were initially coded live
for gaze-following trials, which E1
chance of success by guessing, and some tasks
had no possibility for guessing). Statistically, the
humans and chimpanzees did not differ from one
another in the physical domain, but they were
both more skillful than the orangutans (P < 0.001
in both cases). In the social domain, a very
different pattern emerged. Averaging across all
of the tasks in the social domain, the human
children were correct on ~74% of the trials,
whereas the two ape species were correct about
half as often (33 to 36% of the trials). Statistically,
the humans were more skillful than either of the
two ape species (P < 0.001 in both cases), which
did not differ from one another.
Figure 2 presents the results at the level of the
six scales. In the physical domain, there were no
differences among species on the quantities scale.
On both the space and causality scales, however,
humans and chimpanzees did not differ from
children and chimpanzees each were better at some
tasks than the other, with orangutans often repre-
senting an outlier. Within the four spatial tasks,
children were better than chimpanzees at one task
(object permanence), whereas the chimpanzees
outperformed the children at another task (trans-
position). In terms of quantities, all three species
were similar at judging which of two quantities is
larger, but chimpanzees were better than both of
the other species at combining quantities in order
to make a judgment. Children were better than
both ape species at the three causality tasks in
which a judgment must be made before manipu-
lation or choice, whereas chimpanzees were better
than children and orangutans at the one causality
task involving active tool use. Within the social
domain, again the pattern was very different. As
predicted, the human children were consistently
more skillful than both of the ape species (at five
cal domain (A) and
(B). The box plots
distribution of the
correct responses for
ocial domains of the
h species: median,
extreme values. Boxes
interquartile range
50% of values (range
to the 75th percent-
ross the box indicates
he whiskers represent
d minimum values,
tliers [indicated by
t 1.5 times the inter-
(i.e., 1.5 box lengths
r or lower edge of the
remes [indicated by
ast 3 times the inter-
(i.e., >3 box lengths from the edge)]. Statistical comparisons
in were made by multivariate analysis of variance (MANOVA),
nalysis of variance (ANOVA) tests for each domain. Post-hoc
nferroni correction was used when the equality of variances
domains: physical (F2,237 = 19.921, P < 0.001, h2
= 0.14) and social (F2,237 =
311.224, P < 0.001, h2
= 0.72). Univariate analyses for the interaction
between species and gender revealed that there was a significant interaction
for the physical domain (F2,237 = 5.451, P = 0.005, h2
= 0.04) but not for the
A Physical domain
proportionofcorrectresponses
0.00
0.20
0.40
0.60
0.80
1.00
B Social domain
proportionofcorrectresponses
human chimpanzee orangutan human chimpanzee orangutan
0.00
0.20
0.40
0.60
0.80
1.00

8. Flexibilidad Conductual
Integracion de diversas
fuentes de información
para adaptar la conducta
Habilidades Sociales
• Representación de estados
mentales de otros
• Participación en relaciones
triádicas

9. Métodos de Investigación
¿Cómo estudiar el cerebro social?

10. Métodos en Neurociencia Social
• Comportamiento
• Lenguaje
• Toma de
decisiones
Conducta
MODELO
Procesos psíquicos
Procesos cognitivos
Estados mentales
Predisposiciones
morales
Actividad
Biológica
• Activiadad
eléctrica cerebral
• Activiadad
metabólica
cerebral
• Movimientos
oculares
• Dilatación
pupilar …

11. Medición de la actividad
cerebral

12. Actividad metabólica cerebral
(fMRI - BOLD)
Incremento de la actividad metabólica cerebral en relación
a procesos sociales
• Identificar movimientos biológicos
• Identificar la intensiones o creencias detrás de una acción
• Identificar rasgos estables de personalidad o preferencias de otras personas
1. Koster-Hale J, Saxe R. Theory of Mind: A Neural Prediction Problem. Neuron (2013) 79:836–848. doi:10.1016/j.neuron.2013.08.020

13. Actividad eléctrica cerebral
(EEG - MEG)
Cambios en la actividad eléctrica al observar o saber que
otras personas sufren dolor
1. Riečanský I, Paul N, Kölble S, Stieger S, Lamm C. Beta oscillations reveal ethnicity ingroup bias in sensorimotor resonance to pain of
others. Soc Cogn Affect Neurosci (2015) 10:893–901. doi:10.1093/scan/nsu139

14. Actividad eléctrica cerebral
(Actividad evocada - ERP)
Cambios en la actividad eléctrica al observar o saber que
otros sufren dolor
1. Rutgen M, Seidel E-M, Rie ansky I, Lamm C. Reduction of Empathy for Pain by Placebo Analgesia Suggests Functional Equivalence of
Empathy and First-Hand Emotion Experience. J Neurosci (2015) 35:8938–8947. doi:10.1523/JNEUROSCI.3936-14.2015

15. Actividad eléctrica cerebral
(Actividad oscilatoria)
Cambios en la actividad eléctrica al observar o saber que
otros sufren dolor
1. Riečanský I, Paul N, Kölble S, Stieger S, Lamm C. Beta oscillations reveal ethnicity ingroup bias in sensorimotor resonance to pain of
others. Soc Cogn Affect Neurosci (2015) 10:893–901. doi:10.1093/scan/nsu139
2. Billeke P. Negociación social : cómo nuestro cerebro se anticipa a las decisiones de otras personas. Cienc Cogn (2015) 9:22–25.

16. Redes cerebrales implicadas
en los procesamientos
sociales
¿Cuáles son los componentes del cerebro
social?

17. El Cerebro social
Billeke P, Aboi,z F. 2013. Social Cogni,on in Schizophrenia: From Social S,muli Processing to Social Engagement. Fron,ers in Psychiatry. 4:1–12.
Percepción Social

18. Atribución de “mundo
interno” a los agentes sociales
1. Soto-Icaza P, Aboitiz F, Billeke P. Development of social skills in children: neural and behavioral evidence for the elaboration of
cognitive models. Front Neurosci (2015) 9:1–16. doi:10.3389/fnins.2015.00333

19. Unión temporo-parietal y la perspectiva
del otro: intenciones y preferencias
• Seguimiento preferencias de otros en grupos
• El “peso” o importancia de la ganancia de otros en
decisiones altruistas
t motion (Power et al., 2011). Third, as
elwise graphs are dominated at higher
ance relationships, which are logically
on the above considerations. Modified
presented in which all ties terminating
Top right: For both cohorts, plots are shown of the areal
assignments into subgraphs (colors) at tie densities from
10% down to 2% in 1% steps. ROI ordering is identical,
and all subgraphs with fewer than four members are
colored white. The standard measure of subgraph
similarity, normalized mutual information, between node
assignments of the cohorts at identical tie densities
ranged from 0.86 to 0.92, indicating highly similar patterns
across cohorts (1 = identical assignments, 0 = no infor-
mation shared between assignments).
Bottom: subgraphs from three thresholds are shown
for the areal (spheres) and modified voxelwise graphs
(surfaces). Note the similarity of subgraph assignments
between networks, despite the great difference in network
size and cortical coverage, even in different subjects (main
versus replication cohorts). All areal subgraphs with fewer
than four members are colored white, and all modified
voxelwise subgraphs with fewer than 100 voxels are
colored white. Areal networks are shown at 10%, 3%, and
2% tie density (r > 0.16, 0.30, and 0.33), and modified
voxelwise networks are shown at 5%, 2%, and 0.5% tie
density (r > 0.16, 0.23, and 0.31).
shorten addresses of individual nodes). Other
algorithms were tested and yielded similar
results (Figure S2).
Figure 1 illustrates our methodology and high-
lights several important results. The first panel
depicts the areal graph in a spring embedded layout and maps
subgraphs onto nodes using colors, visibly demonstrating the
basis for subgraphs. In spring embedded layouts, ties act as
springs to position nodes in space such that well-connected
groups of nodes are pulled together, providing an intuitive and
1. Hutcherson CA, Bushong B, Rangel A. A Neurocomputational Model of Altruistic Choice and
Its Implications. Neuron (2015) 87:451–462. doi:10.1016/j.neuron.2015.06.0312.
2. Suzuki S, Adachi R, Dunne S, Bossaerts P, O’Doherty JP. Neural Mechanisms Underlying
Human Consensus Decision-Making. Neuron (2015) 86:591–602. doi:10.1016/j.neuron.
2015.03.019

20. Corteza pre-Frontal Medial:
Integración de Perspectivas y Preferencias
• Evaluación de intenciones y comportamiento tanto las de
otras personas, como las propias
• Integración de la ganancia de otros y de uno en
decisiones sociales económicas
t motion (Power et al., 2011). Third, as
elwise graphs are dominated at higher
ance relationships, which are logically
on the above considerations. Modified
presented in which all ties terminating
Top right: For both cohorts, plots are shown of the areal
assignments into subgraphs (colors) at tie densities from
10% down to 2% in 1% steps. ROI ordering is identical,
and all subgraphs with fewer than four members are
colored white. The standard measure of subgraph
similarity, normalized mutual information, between node
assignments of the cohorts at identical tie densities
ranged from 0.86 to 0.92, indicating highly similar patterns
across cohorts (1 = identical assignments, 0 = no infor-
mation shared between assignments).
Bottom: subgraphs from three thresholds are shown
for the areal (spheres) and modified voxelwise graphs
(surfaces). Note the similarity of subgraph assignments
between networks, despite the great difference in network
size and cortical coverage, even in different subjects (main
versus replication cohorts). All areal subgraphs with fewer
than four members are colored white, and all modified
voxelwise subgraphs with fewer than 100 voxels are
colored white. Areal networks are shown at 10%, 3%, and
2% tie density (r > 0.16, 0.30, and 0.33), and modified
voxelwise networks are shown at 5%, 2%, and 0.5% tie
density (r > 0.16, 0.23, and 0.31).
shorten addresses of individual nodes). Other
algorithms were tested and yielded similar
results (Figure S2).
Figure 1 illustrates our methodology and high-
lights several important results. The first panel
depicts the areal graph in a spring embedded layout and maps
subgraphs onto nodes using colors, visibly demonstrating the
basis for subgraphs. In spring embedded layouts, ties act as
springs to position nodes in space such that well-connected
groups of nodes are pulled together, providing an intuitive and
1. Mitchell JP, Macrae CN, Banaji MR. 2006. Dissociable medial prefrontal contributions to judgments of similar and dissimilar others.
Neuron. 50:655–663.
parametric modulation option integrated in SPM5. Subse-
quently, random effects analyses were performed on the
parameter estimate of the parametric regressor for the be-
havioral response. We used the results of the one-sample
t test ( p = .05) reflecting activity modulated by reliving or
understanding as an inclusive mask to determine whether
the regions showing activation differences in self versus
other self-projection were also sensitive to behavior.
Task-related Functional Connectivity Analysis
SeedvoxelsinventralversusdorsalmPFCthatwereidentified
in our previous analysis on self versus other self-projection
were further interrogated to examine the task-related net-
work of brain regions functionally connected with disso-
ciable mPFC regions. We should note that in the present
article we refer to dorsal mPFC (z-axis on Talairach atlas:
>20 mm) and ventral mPFC (z-axis on Talairach atlas:
<20 mm to >−15 mm; e.g., Krueger et al., 2009; Van
Overwalle, 2009), however, the particular naming conven-
tion may differ among authors (e.g., Buckner, Andrews-
Hanna, & Schacter, 2008; Northoff & Bermpohl, 2004).
To find these functional connectivity maps, we employed
a second analysis based on individual trial activity (Rissman,
Gazzaley, & DʼEsposito, 2004). Specifically, we first created
a GLM in which each individual trial was modeled by a
separate covariate, thus yielding different parameter esti-
mates for each individual trial and for each individual
subject. The resulting correlation maps were Fisher trans-
formed to allow for statistical comparison. Then, to exam-
ine differences in functional connectivity of ventral versus
dorsal mPFC regions associated with temporal versus men-
tal self-projection, we conducted a two-sample t test in
SPM5 using an FDR-corrected threshold of p = .05, and a
two-voxel extent threshold.
RESULTS
Behavioral
SPS was associated with a mean reliving rating of 5.04 (SD =
0.56; RT = 1.42 sec, SD = 0.67), and SPO was associated
with a mean understanding rating of 4.50 (SD = 0.86; RT =
1.35 sec, SD = 0.61). There were no significant differ-
encesin the reaction time acrossthetwoconditions(Cohenʼs
d = 0.11). The behavioral results suggest that the Sense-
Cam images evoked a strong ability to re-experience the
personal past and to comprehend another individualʼs
perspective.
Figure 2. Self-projection of self versus other. There was a dorsal (A) versus ventral (B) distinction in the recruitment of mPFC during self versus
other self-projection. BA = Brodmannʼs area.
St. Jacques et al. 1279
In contrast, activation in dorsal mPFC (peak voxel: 29,
45, 42) was greater during judgments of the target with
whom participants less strongly associated themselves
(Figure 2B). That is, participants in the ‘‘similar to liberal’’
group demonstrated greater engagement of dorsal
mPFC while making judgments of the conservative tar-
get, whereas participants in the ‘‘dissimilar from liberal’’
group demonstrated greater dorsal mPFC engagement
while judging the liberal target. This region of dorsal
mPFC was the only area that showed greater activation
for dissimilar than similar targets. Confirming that these
target (liberal, conse
ilar to liberal, dissim
p < 0.0002.
These findings wer
analyses that capitali
participants’ IAT res
activation in ventral
eral target (relative to
icantly correlated wit
associated self with
ning IAT, r(14) = 0.54,
Fig
tai
Int
Lib
era
(A)
ac
wh
to
so
of
wa
ba
red
jud
the
wh
(rig
mP
era
for
tar
(B)
po
va
wh
to
Mentalizing about Similar and Dissimilar Others
657
In contrast, activation in dorsal mPFC (peak voxel
45, 42) was greater during judgments of the target
whom participants less strongly associated themse
(Figure 2B). That is, participants in the ‘‘similar to lib
group demonstrated greater engagement of d
mPFC while making judgments of the conservative
get, whereas participants in the ‘‘dissimilar from lib
group demonstrated greater dorsal mPFC engagem
while judging the liberal target. This region of d
mPFC was the only area that showed greater activa
for dissimilar than similar targets. Confirming that t
two mPFC regions responded differently as a functi
target similarity, we observed a highly significant th
way interaction for region (ventral mPFC, dorsal mPF
Table 1. Coordinates of Peak Activations and Percent Signal
Change for Regions Demonstrating a Significantly Different BO
Mentalizing about Similar and Dissimilar Others
657

21. Corteza pre-Frontal Lateral:
Control de la Integración de Información
de Diversas Fuentes
t motion (Power et al., 2011). Third, as
elwise graphs are dominated at higher
ance relationships, which are logically
on the above considerations. Modified
presented in which all ties terminating
Top right: For both cohorts, plots are shown of the areal
assignments into subgraphs (colors) at tie densities from
10% down to 2% in 1% steps. ROI ordering is identical,
and all subgraphs with fewer than four members are
colored white. The standard measure of subgraph
similarity, normalized mutual information, between node
assignments of the cohorts at identical tie densities
ranged from 0.86 to 0.92, indicating highly similar patterns
across cohorts (1 = identical assignments, 0 = no infor-
mation shared between assignments).
Bottom: subgraphs from three thresholds are shown
for the areal (spheres) and modified voxelwise graphs
(surfaces). Note the similarity of subgraph assignments
between networks, despite the great difference in network
size and cortical coverage, even in different subjects (main
versus replication cohorts). All areal subgraphs with fewer
than four members are colored white, and all modified
voxelwise subgraphs with fewer than 100 voxels are
colored white. Areal networks are shown at 10%, 3%, and
2% tie density (r > 0.16, 0.30, and 0.33), and modified
voxelwise networks are shown at 5%, 2%, and 0.5% tie
density (r > 0.16, 0.23, and 0.31).
shorten addresses of individual nodes). Other
algorithms were tested and yielded similar
results (Figure S2).
Figure 1 illustrates our methodology and high-
lights several important results. The first panel
depicts the areal graph in a spring embedded layout and maps
subgraphs onto nodes using colors, visibly demonstrating the
basis for subgraphs. In spring embedded layouts, ties act as
springs to position nodes in space such that well-connected
groups of nodes are pulled together, providing an intuitive and
• Integrar información diversa, por ejemplo: aspectos
morales y normativos
• Se relaciona con integración de información abstracta y
estrategias a largo plazo
Baumgartner T, Knoch D, Hotz P, Eisenegger C, Fehr E. 2011. Dorsolateral and ventromedial prefrontal cortex orchestrate normative
choice. Nat Neurosci. 14:1468–1474.

22. Investigación en toma de
decisión sociales
¿Qué aplicación puede tener el estudio del cerebro social?

23. Juego del ultimátum
Billeke P, Zamorano F, Cosmelli D,
Aboitiz F. 2013. Oscillatory Brain
Activity Correlates with Risk
Perception and Predicts Social
Decisions. Cereb Cortex. 23:2872–
2883.

24. Estudio de Pacientes con
Esquizofrenia
• Alteración en la activación cerebral durante la anticipación
de las conductas de otras personas
Billeke P, Armijo A, Castillo D,
López T, Zamorano F, Cosmelli D,
Aboitiz F. 2015. Paradoxical
Expectation: Oscillatory Brain
Activity Reveals Social Interaction
Impairment in Schizophrenia. Biol
Psychiatry. 78:421–431.

25. Conclusiones
• La implementación de las habilidades sociales y de flexibilidad
conductual son fundamentales durante nuestro desarrollo
filogenético y ontológico
• Investigaciones en neurociencia han mostrado que la actividad de
diversas áreas cerebrales se relaciona con nuestras conductas
sociales
• Algunas de ellas relacionada a procesos específicamente sociales,
por ejemplo identificar las preferencias de otras personas (unión
temporo-pariental)
• Otras, relacionada a la integración de diversa información (social y
no social) en conductas complejas (prefrontal dorsolateral)
• Investigaciones en esta área pueden ser aplicadas al estudio del
déficit social evidenciado en enfermedades neurológicas y
psiquiátricas, y de esta forma ayudar a elaborar terapias de
rehabilitación