El Cerebro Social
Aproximación de las neurociencias al estudio de la habilidades
sociales
Pablo Billeke
División de Neuroc...
Presentación
•  Introducción
•  ¿Por qué estudiar el cerebro social?
•  Métodos de investigación
•  ¿Cómo estudiar el cere...
Introdución
¿Por qué estudiar el cerebro social ?
Neocorteza en primates
Hipótesis del cerebro
social:
Encefalización y tamaño del
grupo
Inteligencia Social
•  Tempranamente en el desarrollo (2.5ª), el dominio de
las habilidades sociales nos diferencian del r...
Flexibilidad Conductual
Integracion de diversas
fuentes de información
para adaptar la conducta
Habilidades Sociales
•  Re...
Métodos de Investigación
¿Cómo estudiar el cerebro social?
Métodos en Neurociencia Social
•  Comportamiento
•  Lenguaje
•  Toma de
decisiones
Conducta
MODELO
Procesos psíquicos
Proc...
Medición de la actividad
cerebral
Actividad metabólica cerebral
(fMRI - BOLD)
Incremento de la actividad metabólica cerebral en relación
a procesos sociales...
Actividad eléctrica cerebral
(EEG - MEG)
Cambios en la actividad eléctrica al observar o saber que
otras personas sufren d...
Actividad eléctrica cerebral
(Actividad evocada - ERP)
Cambios en la actividad eléctrica al observar o saber que
otros suf...
Actividad eléctrica cerebral
(Actividad oscilatoria)
Cambios en la actividad eléctrica al observar o saber que
otros sufre...
Redes cerebrales implicadas
en los procesamientos
sociales
¿Cuáles son los componentes del cerebro
social?
El Cerebro social
Billeke	P,	Aboi,z	F.	2013.	Social	Cogni,on	in	Schizophrenia:	From	Social	S,muli	Processing	to	Social	Eng...
Atribución de “mundo
interno” a los agentes sociales
1. Soto-Icaza P, Aboitiz F, Billeke P. Development of social skills i...
Unión temporo-parietal y la perspectiva
del otro: intenciones y preferencias
•  Seguimiento preferencias de otros en grupo...
Corteza pre-Frontal Medial:
Integración de Perspectivas y Preferencias
•  Evaluación de intenciones y comportamiento tanto...
Corteza pre-Frontal Lateral:
Control de la Integración de Información
de Diversas Fuentes
t motion (Power et al., 2011). T...
Investigación en toma de
decisión sociales
¿Qué aplicación puede tener el estudio del cerebro social?
Juego del ultimátum
Billeke P, Zamorano F, Cosmelli D,
Aboitiz F. 2013. Oscillatory Brain
Activity Correlates with Risk
Pe...
Estudio de Pacientes con
Esquizofrenia
•  Alteración en la activación cerebral durante la anticipación
de las conductas de...
Conclusiones
•  La implementación de las habilidades sociales y de flexibilidad
conductual son fundamentales durante nuest...
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El Cerebro Social por Pablo Billeke

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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.

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El Cerebro Social por Pablo Billeke

  1. 1. El Cerebro Social Aproximación de las neurociencias al estudio de la habilidades sociales Pablo Billeke División de Neurociencia CICS – UDD
  2. 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. 3. Introdución ¿Por qué estudiar el cerebro social ?
  4. 4. Neocorteza en primates
  5. 5. Hipótesis del cerebro social: Encefalización y tamaño del grupo
  6. 6. 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
  7. 7. Flexibilidad Conductual Integracion de diversas fuentes de información para adaptar la conducta Habilidades Sociales •  Representación de estados mentales de otros •  Participación en relaciones triádicas
  8. 8. Métodos de Investigación ¿Cómo estudiar el cerebro social?
  9. 9. 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 …
  10. 10. Medición de la actividad cerebral
  11. 11. 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
  12. 12. 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
  13. 13. 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
  14. 14. 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.
  15. 15. Redes cerebrales implicadas en los procesamientos sociales ¿Cuáles son los componentes del cerebro social?
  16. 16. 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
  17. 17. 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
  18. 18. 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
  19. 19. 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
  20. 20. 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.
  21. 21. Investigación en toma de decisión sociales ¿Qué aplicación puede tener el estudio del cerebro social?
  22. 22. 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.
  23. 23. 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.
  24. 24. 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

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