Activation Likelihood Estimation (ALE)
Meta-analyses
of human neuroimaging data was for a long time confined to either summaries
of label-based activation or descriptive statistics of activation centers
originating from plotting available activations on a template brain.
However, recent advances in statistical handling of 3D data have allowed
the emergence of new types of meta-analytic techniques. Our group has
experience from using one of these new methods, used to estimate the
likelihood of brain activations across multiple studies, the method
of Activation Likelihood Estimates (ALE; Eickhoff et al., 2009; Laird
et al., 2005; Turkeltaub, Eden, Jones, & Zeffiro, 2002).
The
ALE technique has three important advantages over traditional label-based
regional reviews and meta-analyses. First, foci of activation are the
input into the analysis, instead of labels. Labeling of anatomical areas
does not occur until after data pooling, and thus is independent of
differences in labeling among studies. Second, the foci that serve as
the input for the analysis are weighted by the number of participants
in each study. Third, this method yields a quantitative estimate of
the probability of activation, which is statistically analyzed for significance
and corrected for the observation of false positives. Forth, the ALE
algorithm identifies common activations, and thereby factors out effects
not related to the process of interest, such as different methodologies
that are used by different research groups.
The
ALE software (GingerALE; http://www.brainmap.org/ale)
does an automated analysis that has been described in detail elsewhere
(Eickhoff et al., 2009; Laird et al., 2005; Turkeltaub et al., 2002)
and we refer the interested reader to the Ginger ALE homepage.
Below, we are providing output maps in nii format from three of our recent meta-analyses of intranasal trigeminal stimulation (Albrecht, et al., 2010), gustatory stimulation (Veldhousen, et al., 2011), and olfactory processing (Seubert et al., in press). Please refer to the original papers above for details of how data were gathered, processed, and analyzed. We are below providing ALE maps as final ALE statistical output, saved as a nifti file, in both Talairach and MNI stereotactic space [to download, click on specific link below]. The result file can either be used as an inclusive mask in analyses where only voxels known to process gustatory/trigeminal stimulus should be included [note that a binarized map is needed] or as a tool to view where typical location are located at certain statistical probabilities. If the latter is of interest, we recommend that the ALE result file is loaded as a functional overlay using either MRIcroN or MANGO, both freely available online.
To download the Nifti files, right click on the respective link below, then choose Save Target As... Alternatively, you can just click on the link and you will find the nii file in your 'download' folder.
Albrecht, J.,
Kopietz, R., Frasnelli, J., Wiesmann, M., Hummel, T., & Lundstrom,
J. N. (2010). The neuronal correlates of intranasal trigeminal function-an
ALE meta-analysis of human functional brain imaging data. Brain Res
Rev, 62(2), 183-196.
Result Summary
From Abstract:
We found significant ALE scores, thus indicating consistent activation
across studies, in the brainstem, ventrolateral posterior thalamic
nucleus, anterior cingulate cortex, insula, precentral gyrus, as well
as in primary and secondary somatosensory cortices - a network known
for the processing of intranasal nociceptive stimuli. Significant
ALE values was also observed in the piriform cortex, insula, and the
orbitofrontal cortex, areas known to process chemosensory stimuli,
and in association cortices. Additionally, the trigeminal ALE statistics
were directly compared with ALE statistics originating from olfactory
stimulation demonstrating considerable overlap in activation. In conclusion,
the results of this meta-analysis map the human neuronal correlates
of intranasal trigeminal stimulation with high statistical certainty
and demonstrate that the cortical areas recruited during the processing
of intranasal CO2 stimuli include those outside traditional trigeminal
areas.
ALE of Gustatory Stimuli
Veldhuizen, M. G.,
Albrecht, J., Zelano, C., Boesveldt, S., Breslin, P., & Lundstrom,
J. N. (2011). Identification of human gustatory cortex by activation likelihood
estimation. Hum Brain Mapp. 32(12), 2256-66.
Result Summary
From Abstract:
We observed significant cortical activation probabilities in: bilateral
anterior insula and overlying frontal operculum, bilateral mid dorsal
insula and overlying Rolandic operculum, and bilateral posterior insula/parietal
operculum/postcentral gyrus, left lateral orbitofrontal cortex (OFC),
right medial OFC, pregenual anterior cingulate cortex (prACC) and right
mediodorsal thalamus. This analysis confirms the involvement of multiple
cortical areas within insula and overlying operculum in gustatory processing
and provides a functional "taste map" which can be used as an
inclusive mask in the data analyses of future studies. In light of this
new analysis, we discuss human central processing of gustatory stimuli
and identify topics where increased research effort is warranted.
[download ALE result output in Talairach space]
[download ALE result output in MNI space]
ALE of Olfactory Stimuli
Seubert, J., Freiherr, J., Djordjevic, J., & Lundström, J.N. (in press). Statistical localization of human olfactory cortex. NeuroImage.
Result Summary
From Abstract:
Significant ALE peaks for odor against baseline were observed in areas
commonly labeled as primary and secondary olfactory cortex, such as the
piriform and orbitofrontal cortex, amygdala, anterior insula, and ventral
putamen. In addition, differences were observed in the extent to which
different methods were able to induce activation in these different nodes
of the olfactory network.
SPM Masks of Olfactory Cortex
Seubert, J., Freiherr, J., Frasnelli, J., Hummel, T., & Lundström, J.N. (in press). Orbitofrontal Cortex and Olfactory Bulb Volume Predict Distinct Aspects of Olfactory Performance in Healthy Subjects. Cerebral Cortex.
Result Summary :
We assessed the link between the underlying neuroanatomy and olfactory performance by correlating voxel-based morphometry data from 90 healthy adults with olfactory performance measures. Supplementing this approach with region of interest (ROI) analyses of functionally defined olfactory cortical regions and olfactory bulb volume, we sought to disentangle the relative contribution of central and peripheral areas to behavioral variability. Whole-brain analyses revealed a significant positive correlation of gray matter volume and olfactory function scores in the right orbital sulcus. This effect was confirmed by the ROI analyses of piriform and orbitofrontal cortex based on olfacory ALE analyses. These data suggest an important role of regional gray matter volume in the right orbitofrontal cortex and olfactory bulb volume for olfactory performance in healthy individuals.
References
Albrecht, J., Kopietz, R., Wiesmann, M., Hummel, T., & Lundström,
J. N. (2010). The neuronal correlates of intranasal trigeminal function
- An ALE meta-analysis of human functional brain imaging data. Brain Research
Review. 62, 183-196.
Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., &
Fox, P. T. (2009). Coordinate-based activation likelihood estimation meta-analysis
of neuroimaging data: a random-effects approach based on empirical estimates
of spatial uncertainty. Hum Brain Mapp, 30(9), 2907-2926.
Laird, A. R., Fox, P. M., Price, C. J., Glahn, D. C., Uecker, A. M., Lancaster,
J. L., et al. (2005). ALE meta-analysis: controlling the false discovery
rate and performing statistical contrasts. Hum Brain Mapp, 25(1), 155-164.
Seubert, J., Freiherr, J., Djordjevic, J., & Lundström, J.N. (in press). Statistical localization of human olfactory cortex. NeuroImage.
Seubert,
J., Freiherr, J., Frasnelli, J., Hummel, T., & Lundström, J.N.
(in
press). Orbitofrontal Cortex and Olfactory Bulb Volume Predict Distinct
Aspects of Olfactory Performance in Healthy Subjects. Cerebral Cortex.
Turkeltaub, P. E., Eden, G. F., Jones, K. M., & Zeffiro, T. A. (2002).
Meta-analysis of the functional neuroanatomy of single-word reading: method
and validation. Neuroimage, 16(3 Pt 1), 765-780.
Veldhuizen, M. G., Albrecht, J., Zelano, C., Boesveldt, S., Breslin, P.,
& Lundstrom, J. N. (2011). Identification of Human Gustatory Cortex
by Activation Likelihood Estimation. Human Brain Mapping. 32(3),
450-460.