Rav - Revision history

imported>Psych204B at 19:05, 12 March 2012

2012-03-12T19:05:25Z

@@ Line 117: / Line 117: @@
 [[File:valence_insula.jpg | Figure 4]]
-== Retinotopic models in individual subjects transformed into MNI space ==
+== Arousal ==
-Some text. Some analysis. Some figures.
+There were no reliable sub-cortical activations for arousal. However we did observe PFC and mPFC activations for low arousal pictures. (Figure 5)
-== Retinotopic models in group-averaged data on the MNI template brain ==
+[[File:arousal_pfc_mpfc.jpg | Figure 5]]
-=== Equations===
+Similarly, negative images with lower insula activation are chosen over images with higher insula activation.
 = Conclusions =
-Here is where you say what your results mean.
+It has long been clear that valence plays a role in choice (Schneirla, 1959). Research on the role of arousal in choice is more recent (quantified for the first time in the present work), and unsurprisingly, less settled. Ariely and Loewenstein (2006) have demonstrated that arousal broadens the category of things “that are attractive.” Such a broadening could impact approach/avoidance behaviors. A related explanation is that arousal is associated with the salience of a stimulus. Salient events require immediate behavioral responses and therefore impact motivation (Cooper & Knutson, 2008).
+The best-fit model (behaviorally derived) and the current imaging work offers new insights regarding the mechanisms underlying affective choice. We believe that these insights have broad implications across many other fields in psychology. For example, neuroeconomists have suggested that various neural systems are involved in decision making, but little is known about how options with different values are compared with each other (Rangel, Camerer & Montague, 2008). The best-fit model provides a plausible ‘common currency’ to address these issues.

imported>Psych204B at 18:50, 12 March 2012

2012-03-12T18:50:37Z

← Older revision		Revision as of 18:50, 12 March 2012
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	== Valence ==		== Valence ==
	The ventral striatum was reliably activated for positively valenced pictures compared to negatively valenced pictures(Figure 2)		The ventral striatum was reliably activated for positively valenced pictures compared to negatively valenced pictures (Figure 2)

	[[File:valence_nacc.jpg \| Figure 2]]		[[File:valence_nacc.jpg \| Figure 2]]

	We also saw de-activation in the mPFC for highly valenced pictures -- indicating that low valenced pictures are cognitively processed to a greater extent than high valenced pictures		We also saw de-activation in the mPFC for highly valenced pictures -- indicating that low valenced pictures are cognitively processed to a greater extent than high valenced pictures (Figure 3)

	[[File:valence_mpfc.jpg \| Figure 3]]		[[File:valence_mpfc.jpg \| Figure 3]]

			Expectedly we also observed insula activation for negatively valenced pictures (Figure 4)

			[[File:valence_insula.jpg \| Figure 4]]

	== Retinotopic models in individual subjects transformed into MNI space ==		== Retinotopic models in individual subjects transformed into MNI space ==

imported>Psych204B at 18:46, 12 March 2012

2012-03-12T18:46:12Z

← Older revision		Revision as of 18:46, 12 March 2012
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	[[File:valence_nacc.jpg \| Figure 2]]		[[File:valence_nacc.jpg \| Figure 2]]

			We also saw de-activation in the mPFC for highly valenced pictures -- indicating that low valenced pictures are cognitively processed to a greater extent than high valenced pictures

			[[File:valence_mpfc.jpg \| Figure 3]]

	== Retinotopic models in individual subjects transformed into MNI space ==		== Retinotopic models in individual subjects transformed into MNI space ==

imported>Psych204B at 18:37, 12 March 2012

2012-03-12T18:37:30Z

← Older revision		Revision as of 18:37, 12 March 2012
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	== Valence ==		== Valence ==
	The ventral striatum was reliably activated for ~~positive~~ pictures (Figure 2)		The ventral striatum was reliably activated for positively valenced pictures compared to negatively valenced pictures(Figure 2)

	[[File:valence_nacc \| Figure 2]]		[[File:valence_nacc.jpg \| Figure 2]]

	== Retinotopic models in individual subjects transformed into MNI space ==		== Retinotopic models in individual subjects transformed into MNI space ==

imported>Psych204B at 18:29, 12 March 2012

2012-03-12T18:29:05Z

← Older revision		Revision as of 18:29, 12 March 2012
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	Finally we took the normalized functional data and ran a regression with the contrasts (as long as all contrasts are orthogonal, or aka non-covariance between contrasts). We examined the contrasts in AFNI		Finally we took the normalized functional data and ran a regression with the contrasts (as long as all contrasts are orthogonal, or aka non-covariance between contrasts). We examined the contrasts in AFNI

	= Results ~~- What you found~~ =		= Results =

	== ~~Retinotopic models in native space~~ ==		== Valence ==
	~~Some text. Some analysis. Some figures.~~		The ventral striatum was reliably activated for positive pictures (Figure 2)

			[[File:valence_nacc \| Figure 2]]

	== Retinotopic models in individual subjects transformed into MNI space ==		== Retinotopic models in individual subjects transformed into MNI space ==

imported>Psych204B at 05:59, 12 March 2012

2012-03-12T05:59:20Z

← Older revision		Revision as of 05:59, 12 March 2012
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	Anatomical and functional scans were wrapped to talairach space		Anatomical and functional scans were wrapped to talairach space

			=== Post-processing ===

			We used regressors and self ratings to do the analysis.

			First we created contrasts (1 0 or 1 0 -1 or parametric) that described the effects.

			1,0 -> picture on, picture off

			1,0,-1 -> high valence picture, no picture, low valence picture (similarly for arousal)

			3,2,1,0,-1,-2,-3 --> exact ratings of valence/arousal deviating from mean 0

			Next we convolved the contrasts with the hemodynamic response function

			Finally we took the normalized functional data and ran a regression with the contrasts (as long as all contrasts are orthogonal, or aka non-covariance between contrasts). We examined the contrasts in AFNI

	= Results - What you found =		= Results - What you found =

imported>Psych204B at 05:29, 12 March 2012

2012-03-12T05:29:16Z

← Older revision		Revision as of 05:29, 12 March 2012
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	=== MR acquisition ===		=== MR acquisition ===
	Data were obtained on the CNI scanner at Stanford University. Functional and Anatomicals were reconstructed using CNI algorithms.		Data were obtained on the CNI scanner at Stanford University. Functional and Anatomicals were reconstructed using CNI algorithms.

			AFNI was used to process and analyze the data.

	=== Trial Structure & Shaving of Leading TRs ===		=== Trial Structure & Shaving of Leading TRs ===
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	=== Pre-processing ===		=== Pre-processing ===
	All data were ~~slice-time~~ corrected, ~~motion~~ corrected, and ~~repeated scans were averaged together to create a single average scan~~ for ~~each subject~~. ~~Et cetera~~.		All data were motion corrected, smoothed, drift corrected, normalized and warped.

			==== Motion Corrected ====
			The AFNI command '''3dvolreg''' was used for motion correction.

			==== Smoothing ====
			A blurring kernel of 4mm was used.

			==== Drift Correction ====
			A Fourier highpass filter of 0.011 was used to drift-correct


			Additionally:

	~~==== PRF model fits ====~~		Data was normalized to percent signal change
	~~PRF models~~ were ~~fit with a 2-gaussian model.~~		Anatomical and functional scans were wrapped to talairach space

	~~==== MNI space ====~~
	After a pRF model was solved for each subject, the model was trasnformed into MNI template space. This was done by first aligning the high resolution t1-weighted anatomical scan from each subject to an MNI template. Since the pRF model was coregistered to the t1-anatomical scan, the same alignment matrix could then be applied to the pRF model. <br>
	~~Once each pRF model was aligned to MNI space, 4 model parameters - x, y, sigma, and r^2 - were averaged across each of the 6 subjects in each voxel.~~

	~~Et cetera.~~

imported>Psych204B at 04:43, 12 March 2012

2012-03-12T04:43:24Z

← Older revision		Revision as of 04:43, 12 March 2012
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	=== Trial Structure & Shaving of Leading TRs ===		=== Trial Structure & Shaving of Leading TRs ===
	In this experiment we used the following presentation schedule:		In this experiment we used the following presentation schedule:

	Pic 1: 500MS followed by fixation for 500MS		Pic 1: 500MS followed by fixation for 500MS

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	Variable ITI: 2/4/6s		Variable ITI: 2/4/6s

	Due to this Trial Structure we chose at TR = 1s		Due to this Trial Structure we chose at TR = 1s.

			Further we chose to have 8 leading and 8 trialing TRs to adjust for fMRI start up effects. We eliminated these TRs prior to pre-processing.

	==== Pre-processing ====		=== Pre-processing ===
	All data were slice-time corrected, motion corrected, and repeated scans were averaged together to create a single average scan for each subject. Et cetera.		All data were slice-time corrected, motion corrected, and repeated scans were averaged together to create a single average scan for each subject. Et cetera.

imported>Psych204B at 04:39, 12 March 2012

2012-03-12T04:39:02Z

← Older revision		Revision as of 04:39, 12 March 2012
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	In this experiment we used the following presentation schedule:		In this experiment we used the following presentation schedule:
	Pic 1: 500MS followed by fixation for 500MS		Pic 1: 500MS followed by fixation for 500MS

	Pic 2: 500MS followed by fixation for 500MS		Pic 2: 500MS followed by fixation for 500MS

	Consider Your Choice: 2s		Consider Your Choice: 2s

	Make Your Selection: 2s		Make Your Selection: 2s

	Variable ITI: 2/4/6s		Variable ITI: 2/4/6s

imported>Psych204B at 04:37, 12 March 2012

2012-03-12T04:37:29Z

← Older revision		Revision as of 04:37, 12 March 2012
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	Consider Your Choice: 2s		Consider Your Choice: 2s
	Make Your Selection: 2s		Make Your Selection: 2s
	Variable ITI: 2/4/6		Variable ITI: 2/4/6s

	Due to this Trial Structure		Due to this Trial Structure we chose at TR = 1s

	==== Pre-processing ====		==== Pre-processing ====