Minimizing within‐experiment and within‐group effects in activation likelihood estimation meta‐analyses

Turkeltaub, Peter E.; Eickhoff, Simon B.; Laird, Angela R.; Fox, Mick; Wiener, Martin; Fox, Peter T.

doi:10.1002/hbm.21186

Cited by 1,012 publications

(1,103 citation statements)

References 26 publications

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“…Foci reported in Montreal Neurological Institute coordinates were transformed into Talairach coordinates according to the ICBM2TAL transformation (154). Foci concordance was assessed by the method of ALE (81) in a randomeffects implementation (155) that controls for within-experiment effects (156). Under ALE, foci are treated as Gaussian probability distributions, which reflect localization uncertainty.…”

Section: Methodsmentioning

confidence: 99%

Phoneme and word recognition in the auditory ventral stream

DeWitt

Rauschecker²

2012

Proc. Natl. Acad. Sci. U.S.A.

419

328

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Spoken word recognition requires complex, invariant representations. Using a meta-analytic approach incorporating more than 100 functional imaging experiments, we show that preference for complex sounds emerges in the human auditory ventral stream in a hierarchical fashion, consistent with nonhuman primate electrophysiology. Examining speech sounds, we show that activation associated with the processing of short-timescale patterns (i.e., phonemes) is consistently localized to left mid-superior temporal gyrus (STG), whereas activation associated with the integration of phonemes into temporally complex patterns (i.e., words) is consistently localized to left anterior STG. Further, we show left midto anterior STG is reliably implicated in the invariant representation of phonetic forms and that this area also responds preferentially to phonetic sounds, above artificial control sounds or environmental sounds. Together, this shows increasing encoding specificity and invariance along the auditory ventral stream for temporally complex speech sounds.functional MRI | meta-analysis | auditory cortex | object recognition | language S poken word recognition presents several challenges to the brain. Two key challenges are the assembly of complex auditory representations and the variability of natural speech (SI Appendix, Fig. S1) (1). Representation at the level of primary auditory cortex is precise: fine-grained in scale and local in spectrotemporal space (2, 3). The recognition of complex spectrotemporal forms, like words, in higher areas of auditory cortex requires the transformation of this granular representation into Gestalt-like, object-centered representations. In brief, local features must be bound together to form representations of complex spectrotemporal contours, which are themselves the constituents of auditory "objects" or complex sound patterns (4, 5). Next, representations must be generalized and abstracted. Coding in primary auditory cortex is sensitive even to minor physical transformations. Object-centered coding in higher areas, however, must be invariant (i.e., tolerant of natural stimulus variation) (6). For example, whereas the phonemic structure of a word is fixed, there is considerable variation in physical, spectrotemporal form-attributable to accent, pronunciation, body size, and the like-among utterances of a given word. It has been proposed for visual cortical processing that a feed-forward, hierarchical architecture (7) may be capable of simultaneously solving the problems of complexity and variability (8-12). Here, we examine these ideas in the context of auditory cortex.In a hierarchical pattern-recognition scheme (8), coding in the earliest cortical field would reflect the tuning and organization of primary auditory cortex (or core) (2, 3, 13). That is, single-neuron receptive fields (more precisely, frequency-response areas) would be tuned to particular center frequencies and would have minimal spectrotemporal complexity (i.e., a single excitatory zone and one-to-two inhibitory side bands). ...

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Section: Methodsmentioning

confidence: 99%

Phoneme and word recognition in the auditory ventral stream

DeWitt

Rauschecker²

2012

Proc. Natl. Acad. Sci. U.S.A.

419

328

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“…ALE was performed using the modified algorithm of Turkeltaub and colleagues (48). ALE aims to identify areas showing a convergence of findings across experiments, which is higher than expected under a random spatial association.…”

Section: Methodsmentioning

confidence: 99%

Connectivity profiles reveal the relationship between brain areas for social cognition in human and monkey temporoparietal cortex

Mars

Sallet

Neubert

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

158

165

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The human ability to infer the thoughts and beliefs of others, often referred to as "theory of mind," as well as the predisposition to even consider others, are associated with activity in the temporoparietal junction (TPJ) area. Unlike the case of most human brain areas, we have little sense of whether or how TPJ is related to brain areas in other nonhuman primates. It is not possible to address this question by looking for similar task-related activations in nonhuman primates because there is no evidence that nonhuman primates engage in theory-of-mind tasks in the same manner as humans. Here, instead, we explore the relationship by searching for areas in the macaque brain that interact with other macaque brain regions in the same manner as human TPJ interacts with other human brain regions. In other words, we look for brain regions with similar positions within a distributed neural circuit in the two species. We exploited the fact that human TPJ has a unique functional connectivity profile with cortical areas with known homologs in the macaque. For each voxel in the macaque temporal and parietal cortex we evaluated the similarity of its functional connectivity profile to that of human TPJ. We found that areas in the middle part of the superior temporal cortex, often associated with the processing of faces and other social stimuli, have the most similar connectivity profile. These results suggest that macaque face processing areas and human mentalizing areas might have a similar precursor.comparative anatomy | cooperation | comparative cognition F or a social species like our own, evolutionary success necessitates the ability to navigate a world full of conspecifics. Consequently, humans are extremely sensitive to information about others' emotional states or intentions as provided by cues such as facial expression or body movement. Supporting these abilities, the human temporal cortex contains a number of areas involved in the processing of such social information (1-5). An area that has received particular emphasis in the study of human social abilities is located at the posterior end of the superior temporal sulcus (STS), at the junction with the parietal cortex. This temporoparietal junction (TPJ) area has been implicated in the human ability to attribute belief states to others, so-called "mentalizing" or "theory of mind" (ToM). It has been argued that this ability is uniquely human (6) and forms the basis of our distinctive ability to cooperate, leading to culture and ultimately language (7). TPJ is also associated with "social preferences" and the predisposition to take into account the benefit that might accrue to others as well as to oneself when making a decision (8, 9). Such predispositions are present in monkeys but their neural basis is only beginning to be elucidated (10, 11).In trying to establish the evolutionary origin of human social abilities, research into the processing of social information in the macaque temporal cortex has demonstrated the existence of a number of areas responsive to fac...

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“…Probability distributions within an experiment are merged into a "modelled activation" (MA) map, which reflects the probability for each (2 mm³) voxel that at least one of the foci is located within that voxel. The individual MA maps are then combined into an ALE-map on a voxel-by-voxel basis, controlling for within-experiment effects (Turkeltaub, Eickhoff et al 2012). The ALE-map reflects the combined activation patterns across all experiments included in the meta-analysis.…”

Section: Ale Analysismentioning

confidence: 99%

Probing emotional influences on cognitive control: an ALE meta-analysis of cognition emotion interactions

2013

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Increasing research documents an integration of cognitive control and affective processes. Despite a surge of interest in investigating the exact nature of this integration, no consensus has been reached on the precise neuroanatomical network involved. Using the Activation Likelihood Estimation meta-analysis method, we examined 43 functional Magnetic Resonance Imaging (fMRI) studies (total number of foci = 332; total number of participants, N =820) from the literature that have reported significant interactions between emotion and cognitive control. Metaanalytic results revealed that concurrent emotion (relative to emotionally neutral trials) consistently increased neural activation during high relative to low cognitive control conditions across studies and paradigms. Specifically, these activations emerged in regions commonly implicated in cognitive control such as the lateral prefrontal cortex (inferior frontal junction, inferior frontal gyrus), the medial prefrontal cortex, and the basal ganglia. In addition, some areas emerged during the interaction contrast that were not present during one of the main effects and included the subgenual anterior cingulate cortex and the precuneus. These data provide new evidence for a network of cognition emotion interaction within a cognitive control setting. The findings are discussed within current theories of cognitive and attentional control.

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Minimizing within‐experiment and within‐group effects in activation likelihood estimation meta‐analyses

Cited by 1,012 publications

References 26 publications

Phoneme and word recognition in the auditory ventral stream

Phoneme and word recognition in the auditory ventral stream

Connectivity profiles reveal the relationship between brain areas for social cognition in human and monkey temporoparietal cortex

Probing emotional influences on cognitive control: an ALE meta-analysis of cognition emotion interactions

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