maandag 18 juni 2012

An Article from PLoS: The Effects of FreeSurfer Version, Workstation Type, and Macintosh Operating System Version on Anatomical Volume and Cortical Thickness Measurements

Jonas Kubilius has sent you an open-access article from PLoS ONE.

The sender added this:

This is a rather crazy paper stating that your fMRI analysis results can depend on your computer and operating system. Not sure what to think about that...

Read the open-access, full-text article here:
http://dx.plos.org/10.1371/journal.pone.0038234

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The Effects of FreeSurfer Version, Workstation Type, and Macintosh Operating System Version on Anatomical Volume and Cortical Thickness Measurements

Abstract:

FreeSurfer is a popular software package to measure cortical thickness and volume of neuroanatomical structures. However, little if any is known about measurement reliability across various data processing conditions. Using a set of 30 anatomical T1-weighted 3T MRI scans, we investigated the effects of data processing variables such as FreeSurfer version (v4.3.1, v4.5.0, and v5.0.0), workstation (Macintosh and Hewlett-Packard), and Macintosh operating system version (OSX 10.5 and OSX 10.6). Significant differences were revealed between FreeSurfer version v5.0.0 and the two earlier versions. These differences were on average 8.8±6.6% (range 1.3–64.0%) (volume) and 2.8±1.3% (1.1–7.7%) (cortical thickness). About a factor two smaller differences were detected between Macintosh and Hewlett-Packard workstations and between OSX 10.5 and OSX 10.6. The observed differences are similar in magnitude as effect sizes reported in accuracy evaluations and neurodegenerative studies.

The main conclusion is that in the context of an ongoing study, users are discouraged to update to a new major release of either FreeSurfer or operating system or to switch to a different type of workstation without repeating the analysis; results thus give a quantitative support to successive recommendations stated by FreeSurfer developers over the years. Moreover, in view of the large and significant cross-version differences, it is concluded that formal assessment of the accuracy of FreeSurfer is desirable.

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maandag 19 maart 2012

Fwd: Similar spatial patterns of neural coding of category selectivity in FFA and VWFA under different attention conditions



------- Forwarded message -------
From: "ScienceDirect Publication: Neuropsychologia" <>
To:
Cc:
Subject: Similar spatial patterns of neural coding of category selectivity in FFA and VWFA under different attention conditions
Date: Mon, 19 Mar 2012 10:01:34 +0100

Publication year: 2012
Source:Neuropsychologia, Volume 50, Issue 5

Guifang Xu, Yi Jiang, Lifei Ma, Zhi Yang, Xuchu Weng

It has long been debated whether attention alters the categorical selectivity in regions such as the fusiform face area (FFA) and the visual word form area (VWFA). We addressed this issue by examining whether the spatial pattern of neural representations for certain stimulus categories in these regions would change under different attention conditions. Faces, Chinese characters, and textures were presented in a block design fMRI experiment where participants in different runs attended to the stimuli under different conditions of attention. After localizing regions of interest (ROIs) in FFA and VWFA using general linear models, we performed spatial pattern analyses to examine both within- and cross-condition classification in these ROIs. The within-condition results replicated previous findings showing significant classification accuracy reduction when there was less attention compared with more attention. Critically, cross-condition classification in both FFA and VWFA revealed significantly above-chance accuracy for all stimulus categories, suggesting similar spatial neural representations across different attention conditions. Further strengthening this conclusion, when the contrast-to-noise ratio (CNR) of the signals was adjusted to increase signal strength, cross-condition classification accuracy for faces in FFA and for Chinese characters in VWFA improved significantly, even approaching within-condition accuracy. This indicates that attention does not modulate the spatial pattern of neural representations involved in category selectivity, but only changes the signal strength relative to the noise level.




Full article



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Suggested reading by Kathleen
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maandag 12 maart 2012

Fwd: Computational advances towards linking BOLD and behavior



------- Forwarded message -------
From: "ScienceDirect Publication: Neuropsychologia" <>
To:
Cc:
Subject: Computational advances towards linking BOLD and behavior
Date: Mon, 12 Mar 2012 11:48:19 +0100

Publication year: 2012
Source:Neuropsychologia, Volume 50, Issue 4

John T. Serences, Sameer Saproo

Traditionally, fMRI studies have focused on analyzing the mean response amplitude within a cortical area. However, the mean response is blind to many important patterns of cortical modulation, which severely limits the formulation and evaluation of linking hypotheses between neural activity, BOLD responses, and behavior. More recently, multivariate pattern classification analysis (MVPA) has been applied to fMRI data to evaluate the information content of spatially distributed activation patterns. This approach has been remarkably successful at detecting the presence of specific information in targeted brain regions, and provides an extremely flexible means of extracting that information without a precise generative model for the underlying neural activity. However, this flexibility comes at a cost: since MVPA relies on pooling information across voxels that are selective for many different stimulus attributes, it is difficult to infer how specific sub-sets of tuned neurons are modulated by an experimental manipulation. In contrast, recently developed encoding models can produce more precise estimates of feature-selective tuning functions, and can support the creation of explicit linking hypotheses between neural activity and behavior. Although these encoding models depend on strong – and often untested – assumptions about the response properties of underlying neural generators, they also provide a unique opportunity to evaluate population-level computational theories of perception and cognition that have previously been difficult to assess using either single-unit recording or conventional neuroimaging techniques.




Full article



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Suggested reading by Kathleen
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woensdag 30 november 2011

Attention Reverses the Effect of Prediction in Silencing Sensory Signals

Abstract

Predictive coding models suggest that predicted sensory signals are attenuated (silencing of prediction error). These models, though influential, are challenged by the fact that prediction sometimes seems to enhance rather than reduce sensory signals, as in the case of attentional cueing experiments. One possible explanation is that in these experiments, prediction (i.e., stimulus probability) is confounded with attention (i.e., task relevance), which is known to boost rather than reduce sensory signal. However, recent theoretical work on predictive coding inspires an alternative hypothesis and suggests that attention and prediction operate synergistically to improve the precision of perceptual inference. This model posits that attention leads to heightened weighting of sensory evidence, thereby reversing the sensory silencing by prediction. Here, we factorially manipulated attention and prediction in a functional magnetic resonance imaging study and distinguished between these 2 hypotheses. Our results support a predictive coding model wherein attention reverses the sensory attenuation of predicted signals.



http://cercor.oxfordjournals.org/content/early/2011/11/01/cercor.bhr310.full.pdf+html




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donderdag 6 oktober 2011

Emergence of Perceptual Gestalts in the Human Visual Cortex: The Case of the...

 
 

Sent to you by Frouke via Google Reader:

 
 

via Psychological Science current issue by Kubilius, J., Wagemans, J., Op de Beeck, H. P. on 10/6/11

Many Gestalt phenomena have been described in terms of perception of a whole being not equal to the sum of its parts. It is unclear how these phenomena emerge in the brain. We used functional MRI to study the neural basis of the behavioral configural-superiority effect (i.e., visual search is more efficient when an odd element is part of a configuration than when it is presented by itself). We found that searching for the odd element in a display of four line segments (parts) was facilitated by adding two additional line segments to each of them (creating whole shapes). Functional MRI–based decoding of neural responses to the position of the odd element revealed a neural configural-superiority effect in shape-selective regions but not in low-level retinotopic areas, where decoding of parts was more pronounced. These results show how at least some Gestalt phenomena in vision emerge only at the higher stages of visual information processing and suggest that feed-forward processing might be sufficient to produce such phenomena.


 
 

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dinsdag 27 september 2011

Constructing scenes from objects in human occipitotemporal cortex

Obviously, a must read!

 
 

Naudojant „Google Reader" atsiųsta jums nuo Jonas:

 
 

per Nature Neuroscience - Issue - nature.com science feeds autorius Russell A Epstein 11.9.4

Constructing scenes from objects in human occipitotemporal cortex

Nature Neuroscience 14, 1323 (2011). doi:10.1038/nn.2903

Authors: Sean P MacEvoy & Russell A Epstein


 
 

Veiksmai, kuriuos dabar galite atlikti:

 
 
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vrijdag 23 september 2011

Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies

For those browsing their RSS feeds from home, more information on this story here:

https://sites.google.com/site/gallantlabucb/publications/nishimoto-et-al-2011

 
 

Sent to you by Frouke via Google Reader:

 
 

via Gestalt Revision fMRI by Gestalt Revision on 9/23/11

This is really fun! I encourage everybody to look up their supplementary movie.

 
 

Naudojant „Google Reader" atsiųsta jums nuo Jonas:

 
 

per CURRENT BIOLOGY 11.9.21

Shinji Nishimoto, An T. Vu, Thomas Naselaris, Yuval Benjamini, Bin Yu, Jack L. Gallant. Quantitative modeling of human brain activity can provide crucial insights about cortical representations [1, 2] and can form the basis for brain decoding devices [3–5]. Recent functional magnetic....

 
 

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