[Eeglablist] Fw: Re: Joint ICA in social interaction paradigm

Tue Jan 31 07:06:24 PST 2012

--- On Tue, 31/1/12, muhammad naeem <naeem6500 at yahoo.com> wrote:

From: muhammad naeem <naeem6500 at yahoo.com>
Subject: Re: [Eeglablist] Joint ICA in social interaction paradigm
To: tarikbelbahar at gmail.com
Date: Tuesday, 31 January, 2012, 10:05 PM

Hi Tarik,

Thank you very much for your reply and references.

You may like to see the experimental paradigm which is available in Naeem et al 2012- Neuroimage (http://dx.doi.org/10.1016/j.neuroimage.2011.08.010). Briefly, a typical trial consist of a  no-vision (20 sec) and vision period
 (20 sec)- in the vision period three task instructions are given to 
dyads: ignore (intrinsic), synchronize (inphase) and syncopate 
(antiphase) their right finger movement.  I am now interested in connectivity analysis (Mutual information (phase, power), inter brain coherence etc) with respect to distant sources. In addition to EEG, movement profiles of  dyads are also collected- it  would be interesting to see how and where inter-brain connectivity maps with behavioral metrics.

Your advice regarding separate ICA decomposition and then accumulating  similar components with cluster analysis is clearly possible. Another approach could be based on Groppe's reliability test by estimating similar scalp topography and activations of dyads ICs after separate decomposition ( Groppe et al http://dx.doi.org/10.1016/j.neuroimage.2008.12.038). Although feasible but these may be indirect approaches perhaps more suitable for group analysis in paradigms where in general observer/individual is presented
with a  stimulus (snap-shots ) and their response recorded and analyzed. Clearly, post- processing is required to ascertain which ICs are contributing to group behaviour or otherwiswe. 

My be in some contrast, real-time continuous social interaction requires dyads to be tightly bound in mutual information exchange providing an oppurtunity to consider them in a shared or we-centric space. From this perspective, joint ICA  decomposition (e.g: Infomax) may be more suitable as intutively (to me) individual activity modes are likely to be parsed out from interacting modes thus connecting  joint actions with neuro-electric co-modulation and  source localization. 

This is what I was thinking which offcourse amenable with your's and other's suggestions. Below, two approaches of ICA decompositions are referenced. Calhoun et al. approach is  perhaps theoretically more consistent- however, the PCA processing is an issue
 althogh a way round could be spectral decomposition as they themselves have suggested in previous works. Montague et al. on the other hand have directly concatenated the data (in present context (for example) Fz of one to Fz of the other member of the pair..so on). I am wondering how this jives with underlying generative model of ICA.

Thanks again and best regards,

Naeem.

--- On Mon, 30/1/12, Tarik S Bel-Bahar <tarikbelbahar at gmail.com> wrote:

From: Tarik S Bel-Bahar <tarikbelbahar at gmail.com>
Subject: Re: [Eeglablist] Joint ICA in social interaction paradigm
To: "muhammad naeem" <naeem6500 at yahoo.com>
Cc: eeglablist at sccn.ucsd.edu
Date: Monday, 30 January, 2012, 8:29 AM

Hello Naeem, Some quick thoughts...These are very early days indeed for two-or more brain studies,especially using EEG, although various groups are making inroads,see recent work Dumas, from Tognoni, and from Babiloni's groups,

among others, all of which use diverse methods with EEG.If you are using ICA, why not decomposeeach person's data separately, without PCA,and then analyze correlations
between similar ICs across the 
two individuals, across particularconditions. "Similar" ICs may be determined via eeglab's study clustering function (which uses PCA)or with the CORRMAP plugin.

Calhoun et al.'s EEGIFT with group-ICAcertainly looks like an interestingoption (attached). Overall, the field is wide open for suggestions,so if you come across some new solutions,

please let the list know!An important point is whether you use measures external to EEG to assess some behavioral metric coordination.Overall the issue is what you are hunting for.

See also Hasson and others' forays into cross-correlation across brains.I've included some brain based citation below which might be of use to you,as well as some non-brain literature that bears directly on two-person or more studies. good luck

Anders et al., (2011). Flow of affective information between communicating brains. NeuroImage 54, 439–446.

Astolfi L, Toppi J, De Vico Fallani F, Vecchiato G, Salinari S, Mattia D, Cincotti F, Babiloni F. (2010). Neuroelectrical Hyperscanning Measures Simultaneous Brain Activity in Humans. Brain Topography, 23 (3), 243-256, 2010.

Dumas G, Nadel J, Soussignan R, Martinerie J, Garnero L (2010) Inter-Brain Synchronization during Social Interaction. PLoS ONE 5(8): e12166

Schilbach L, Wilms M, Eickhoff SB, Romanzetti S, Tepest R, Bente G, Shah NJ, Fink GR, Vogeley K (2009) Minds Made for Sharing: Initiating Joint Attention Recruits Reward-related Neurocircuitry. Journal of Cognitive Neuroscience 0:1-14. 

Schippers MB, Roebroeck A, Renken R, Nanetti L, Keysers C. (2010). "Mapping the Information flow from one brain to another during gestural communication". Proc Natl Acad Sci U S A. 2010 May 18;107(20):9388-93.

Stephens, J. G., Silbert, J. L. & Hasson, U. (2010). Speaker–listener neural coupling underlies successful communication. PNAS, July 27.

Tognoli, E., J. Lagarde, et al. (2007). "The phi complex as a neuromarker of human social coordination." Proc Natl Acad Sci U S A 104(19): 8190-5.

Carletta, J., Hill, R. L., Nicol, C., Taylor, T., de Ruiter, J. P., & Bard, E. G. (2010). Eye tracking for two-person tasks with manipulation of a virtual world. Behavior Research Methods, 42, 254-265. 

Wilms M, Schilbach L, Pfeiffer U, Bente G, Fink GR, Vogeley K: (2010). It´s in your eyes. Using gaze-contingent stimuli to create truly interactive paradigms for social cognitive and affective neuroscience. Social Cognitive and Affective Neuroscience 5, 98-107

Kelso J.A.S, de Guzman G.C., Reveley C., Tognoli E. (2009) Virtual Partner Interaction (VPI): Exploring Novel Behaviors via Coordination Dynamics. PLoS ONE 4(6) e5749.

Keysers C, Kaas J, Gazzola V. (2010). "Somatosensation in Social Perception." Nature Reviews Neuroscience. 2010 Jun;11(6):417-28. 

Knoblich, G., Butterfill, S., & Sebanz, N. (2011). Psychological research on joint action: theory and data . In B. Ross (Ed.),The Psychology of Learning and Motivation, 54 (pp. 59-101), Burlington: Academic Press.

Kokal I, Keysers C. Granger causality mapping during joint actions reveals evidence for forward models that could overcome sensory-motor delays. PLoS One. 2010 Oct 21;5(10):e13507.

Marsh, K. L., Johnston, L., Richardson, M. J., & Schmidt, R. C. (2009). Hop off the mirror neuron bandwagon and join ours, it’s less crowded! European Journal of Social Psychology, 39, 1234-1235.

Oullier, O., G. C. de Guzman, et al. (2007). "Social coordination dynamics: Measuring human bonding." Social Neuroscience 99999(1): 1 – 15.

Perry, A., Stein, L., & Bentin, S. (2011). Motor and attentional mechanisms involved in social interaction: Evidence from mu and alpha EEG suppression. Neuroimage, 58, 895-904. DOI http://dx.doi.org/10.1016/j.neuroimage.2011.06.060

Richardson, M. J., K. L. Marsh, et al. (2007). "Rocking together: dynamics of intentional and unintentional interpersonal coordination." Hum Mov Sci (6): 867-91.

Richardson, M. J., Marsh, K. L., & Schmidt, R. C. (2010). Challenging the egocentric view of perceiving, acting, and knowing. In L. Feldman Barrett, B. Mesquita, & E. Smith (Eds), The mind in context (pp. 307-333). New York: Guilford Press.

Richardson, M. J., Marsh, K. L., Isenhower, R., Goodman, J., & Schmidt, R. C. (2007). Rocking together: Dynamics of intentional and unintentional interpersonal coordination. Human Movement Science, 26, 867-891.

Richardson, MJ., van der Wel, R.P.R.D., Knoblich, G., & Sebanz, N. (in press). Let the force be with us: Dyads exploit haptic coupling for coordination . Journal of Experimental Psychology: Human Perception and Performance.

On Tue, Jan 24, 2012 at 5:31 AM, muhammad naeem <naeem6500 at yahoo.com> wrote:

Hi EEGlablist,

In an EEG paradigm concerning two-person social interaction I am trying a
 joint ICA approach (e.g: Calhoun and colleagues-NeuroImage 45 (2009) 
S163–S172 and computational Intelligence and Neuroscience 
doi:10.1155/2011/129365 ). A similar approach has been used in other 
studies (e.g Montague and colleagues- NeuroImage 16, 1159–1164 
(2002)doi:10.1006/nimg.2002.1150). Essential difference between two is 
the arrangement of Data. In the first, virtual channels have been 
created (separate sphering process and PCA ) whereas in the second data of two subjects were concatenated 
giving lesser (half  ) IC's to investigate. I am wondering which 
approach is more appropriate and why? 

A subsequent question is regarding data reduction- PCA is usually used 
but as mentioned in the first references may not be suitable for the 
activities which are not time/phase-locked(as the case with my data). 
What are the other options?

Looking forward to your insight.

Best regards,

Naeem.
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