A data-driven framework for mapping domains of human neurobiology

Beam, Elizabeth; Potts, Christopher; Poldrack, Russell A.; Etkin, Amit

doi:10.1038/s41593-021-00948-9

Cited by 41 publications

(39 citation statements)

References 49 publications

(67 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Rather than requiring only a single region, or depending on large-scale, global signals 69,114,115 , we found that the signature's ability to accurately predict pleasure was driven by local topography within regions. Although prior meta-analytic summaries have proven invaluable for identifying neural correlates of affect [24][25][26][27][28][29]59 , these findings suggest that coordinate-based methods lack the precision necessary to discriminate positively and negatively valenced states 59,116 . It will likely be necessary to move from coordinate-based assessments of the literature to pattern-based frameworks to accurately assess the brain basis of affective phenomena.…”

Section: Discussionmentioning

confidence: 97%

A mesocorticolimbic signature of pleasure in the human brain

Kragel¹,

Treadway²,

Admon³

et al. 2022

Preprint

View full text Add to dashboard Cite

Pleasure is a fundamental driver of human behavior, yet its neural basis remains largely unknown. Rodent studies highlight opioidergic neural circuits connecting the nucleus accumbens, ventral pallidum, insula, and orbitofrontal cortex as critical for the initiation and regulation of pleasure, and human neuroimaging studies exhibit some translational parity. However, whether activation observed across these regions reflects a common, generalizable code for pleasure driven by opioidergic mechanisms remains unclear. Here we use pattern recognition techniques to develop a human functional magnetic resonance imaging signature of mesocorticolimbic activity unique to states of pleasure. In independent validation tests, we find this signature has high sensitivity to pleasant tastes and positive affect evoked by humor. The signature is spatially coextensive with mu-opioid receptor gene expression, and its response is attenuated by the opioid antagonist naloxone. These findings provide evidence of a basis for pleasure derived from primary and secondary rewards in humans that is distributed across brain systems, and suggest that similar mechanisms underlie hedonic impact across mammalian species.

show abstract

Section: Discussionmentioning

confidence: 97%

A mesocorticolimbic signature of pleasure in the human brain

Kragel¹,

Treadway²,

Admon³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Still, the enrichment we used illustrates how enforcing a consistent structure between labels allows for better decoding performance. In general, we can expect that annotations will improve with the use of more standard vocabulary 7 , or the reliance on relevant topics 25 . In the meanwhile, noise in the notations is at least partly overcome by aggregating more data.…”

Section: Discussionmentioning

confidence: 99%

“…A possible extension of this work is to combine it with automated coordinate-based meta-analyses based on the literature 10 , 12 : the latter would provide more comprehensive vocabularies, and guide the model in domains where cognitive labels could not reliably be inferred from annotations. Recent contributions 25 have indeed shown that stable topics could be built from the literature, improving the robustness of image labelling.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive decoding mental processes from Web repositories of functional brain images

Menuet¹,

Meudec

Dockès

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Associating brain systems with mental processes requires statistical analysis of brain activity across many cognitive processes. These analyses typically face a difficult compromise between scope—from domain-specific to system-level analysis—and accuracy. Using all the functional Magnetic Resonance Imaging (fMRI) statistical maps of the largest data repository available, we trained machine-learning models that decode the cognitive concepts probed in unseen studies. For this, we leveraged two comprehensive resources: NeuroVault—an open repository of fMRI statistical maps with unconstrained annotations—and Cognitive Atlas—an ontology of cognition. We labeled NeuroVault images with Cognitive Atlas concepts occurring in their associated metadata. We trained neural networks to predict these cognitive labels on tens of thousands of brain images. Overcoming the heterogeneity, imbalance and noise in the training data, we successfully decoded more than 50 classes of mental processes on a large test set. This success demonstrates that image-based meta-analyses can be undertaken at scale and with minimal manual data curation. It enables broad reverse inferences, that is, concluding on mental processes given the observed brain activity.

show abstract

“…Neural systems support a rich and diverse behavioral repertoire. Findings from both human functional neuroimaging and animal models now point to the low-dimensional structure as a key organizational characteristic that interlinks spatiotemporal neural activity and behavior (Beam et al, 2021; Karolis et al, 2019; MacDowell and Buschman, 2020; Nakai and Nishimoto, 2020; Shine et al, 2019a). For example, a large-scale meta-analysis on more than 10,000 neuroimaging studies found that activity patterns across 83 behavioral tasks can be summarized by 13 latent components (Yeo et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

Thalamocortical contribution to cognitive task activity

Sorenson

Shine

Cole

et al. 2022

Preprint

View full text Add to dashboard Cite

Thalamocortical interaction is a ubiquitous functional motif in the mammalian brain. Previously (Hwang et al., 2021), we reported that lesions to network hubs in the human thalamus are associated with multi-domain behavioral impairments in language, memory, and executive functions. Here we show how task-evoked thalamic activity and thalamocortical interactions are organized to support these broad cognitive abilities. To address this question, we analyzed functional MRI data from human subjects that performed 127 tasks encompassing a broad range of cognitive representations. We first investigated the spatial organization of task-evoked activity and found that multi-task thalamic activity converged onto a low-dimensional structure, through which a basis set of activity patterns are evoked to support processing needs of each task. Specifically, the anterior, medial, and posterior-medial thalamus exhibit hub-like activity profiles that are suggestive of broad functional participation. These thalamic task hubs overlapped with network hubs interlinking cortical systems. To further determine the cognitive relevance of thalamocortical interactions, we built a data-driven thalamocortical interaction model to test whether thalamocortical functional connectivity transformed thalamic activity to cortical task activity. The thalamocortical model predicted task-specific cortical activity patterns, and outperformed comparison models built on cortical, hippocampal, and striatal regions. Simulated lesions to low-dimensional, multi-task thalamic hub regions impaired task activity prediction. This simulation result was further supported by profiles of neuropsychological impairments in human patients with focal thalamic lesions. In summary, our results suggest a general organizational principle of how thalamocortical interactions support cognitive task activity.

show abstract

A data-driven framework for mapping domains of human neurobiology

Cited by 41 publications

References 49 publications

A mesocorticolimbic signature of pleasure in the human brain

A mesocorticolimbic signature of pleasure in the human brain

Comprehensive decoding mental processes from Web repositories of functional brain images

Thalamocortical contribution to cognitive task activity

Contact Info

Product

Resources

About