NeuroImage

Journal: NeuroImage

Abbreviation

NeuroImage

Publisher

Elsevier

ISSN

1053-8119
1095-9572

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Publications 1 - 10 of 211

Examining the value of body gestures in social reward contexts
Williams, Elin H.; Bilbao-Broch, Laura; Downing, Paul E.; et al. (2020)
NeuroImage
Brain regions associated with the processing of tangible rewards (such as money, food, or sex) are also involved in anticipating social rewards and avoiding social punishment. To date, studies investigating the neural underpinnings of social reward have presented feedback via static or dynamic displays of faces to participants. However, research demonstrates that participants find another type of social stimulus, namely, biological motion, rewarding as well, and exert effort to engage with this type of stimulus. Here we examine whether feedback presented via body gestures in the absence of facial cues also acts as a rewarding stimulus and recruits reward-related brain regions. To achieve this, we investigated the neural underpinnings of anticipating social reward and avoiding social disapproval presented via gestures alone, using a social incentive delay task. As predicted, the anticipation of social reward and avoidance of social disapproval engaged reward-related brain regions, including the nucleus accumbens, in a manner similar to previous studies’ reports of feedback presented via faces and money. This study provides the first evidence that human body motion alone engages brain regions associated with reward processing in a similar manner to other social (i.e. faces) and non-social (i.e. money) rewards. The findings advance our understanding of social motivation in human perception and behavior.
Speech sound categorization: The contribution of non-auditory and auditory cortical regions
Preisig, Basil C.; Riecke, Lars; Hervais-Adelman, Alexis (2022)
NeuroImage
Which processes in the human brain lead to the categorical perception of speech sounds? Investigation of this question is hampered by the fact that categorical speech perception is normally confounded by acoustic differences in the stimulus. By using ambiguous sounds, however, it is possible to dissociate acoustic from perceptual stimulus representations. Twenty-seven normally hearing individuals took part in an fMRI study in which they were presented with an ambiguous syllable (intermediate between /da/ and /ga/) in one ear and with disambiguating acoustic feature (third formant, F3) in the other ear. Multi-voxel pattern searchlight analysis was used to identify brain areas that consistently differentiated between response patterns associated with different syllable reports. By comparing responses to different stimuli with identical syllable reports and identical stimuli with different syllable reports, we disambiguated whether these regions primarily differentiated the acoustics of the stimuli or the syllable report. We found that BOLD activity patterns in left perisylvian regions (STG, SMG), left inferior frontal regions (vMC, IFG, AI), left supplementary motor cortex (SMA/pre-SMA), and right motor and somatosensory regions (M1/S1) represent listeners’ syllable report irrespective of stimulus acoustics. Most of these regions are outside of what is traditionally regarded as auditory or phonological processing areas. Our results indicate that the process of speech sound categorization implicates decision-making mechanisms and auditory-motor transformations.
Good practices in EEG-MRI
Mandelkow, H.; Brandeis, D.; Bösiger, Peter (2010)
NeuroImage
Whispering - The hidden side of auditory communication
Fruhholz, Sascha; Trost, Wiebke; Grandjean, Didier (2016)
NeuroImage
Atlas-independent brain connectome analysis at voxel-level granularity: graph convolutional networks for etiology classification in newborns
Speckert , Anna; Gianinazzi , Lukas; Kollmorgen , Sepp; et al. (2025)
NeuroImage
Early identification of altered brain networks in neonates at risk for neurodevelopmental impairments is critical for timely intervention and improving outcomes. This study explores the potential of graph neural networks (GNNs) applied to structural brain connectomes at the voxel level granularity to classify neonatal connectomes by their underlying etiology: 51 children with congenital heart disease (CHD), 100 children born very preterm (PB), and 43 children with spina bifida aperta (SBA). Leveraging the flexibility of voxel-level parcellation, we captured fine-grained connectomic differences that improved classification performance (F1 = 0.78) compared to both atlas-based methods (F1 = 0.62) and a multilayer perceptron baseline model (F1 = 0.69). This approach enables subject-specific parcellation without the need for predefined anatomical templates, facilitating the analysis of diverse brain morphologies and age ranges. Attribution analysis using integrated gradients provided interpretable insights into etiology-specific connectomic patterns, highlighting regions of potential neurodevelopmental importance, such as the Rolandic operculum, inferior parietal lobule, and inferior frontal gyrus. Lateralized attribution patterns in PB reflected known neurodevelopmental alterations, underscoring the value of interpretable graph learning for understanding etiology-specific connectomic features. This work represents an important step toward atlas-independent connectome analysis, offering a novel framework for studying diverse neonatal populations and advancing our understanding of early brain development.
Altered regional connectivity reflecting effects of different anaesthesia protocols in the mouse brain
Wu, Tong; Grandjean, Joanes; Bosshard, Simone C.; et al. (2017)
NeuroImage
Heart beats Brain
Mandelkow, H.; Halder, P.; Brandeis, D.; et al. (2007)
NeuroImage
The hemodynamic response to somatosensory stimulation in mice depends on the anesthetic used: Implications on analysis of mouse fMRI data
Schlegel, Felix; Schroeter, Aileen; Rudin, Markus (2015)
NeuroImage
Sensorimotor tongue representation in individuals with unilateral upper limb amelia
Funk, Marion; Lutz, Kai; Hotz-Boendermaker, Sabina; et al. (2008)
NeuroImage
Effects of ketamine on cognition-emotion interaction in the brain
Scheidegger, Milan; Henning, Anke; Walter, Martin; et al. (2016)
NeuroImage

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Journal: NeuroImage

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