- PreprintIndividual Brain Charting third release, probing brain activity during Movie Watching and Retinotopic MappingAna Luísa Pinho, Hugo Richard, Michael Eickenberg, Alexis Amadon, Elvis Dohmatob, Isabelle Denghien, and 20 more authorsNov 2023
The Individual Brain Charting (IBC) is a multi-task functional Magnetic Resonance Imaging dataset acquired at high spatialresolution, which is intended to facilitate the cognitive mapping of the human brain. It consists in the deep phenotyping of twelve individuals in a fixed environment, covering a broad range of psychological domains that allows, in turn, the investigation of atlasing techniques in functional neuroimaging. Here, we present the inclusion of task data from both naturalistic stimuli and trial-based designs, to uncover core structures of brain activation. We rely on the Fast Shared Response Model (FastSRM): an analytical tool that provides a data-driven solution to model naturalistic stimuli, typically containing many features. We show that data from left-out runs can be reconstructed using FastSRM, thus enabling the extraction of functional networks pertaining to vision, audio and language systems. We also present an in-depth study of the topographic organization of the visual system through a retinotopy task. IBC is open access: source plus derivatives imaging data and meta-data are available in public repositories.
- Journal ArticleControversies and progress on standardization of large-scale brain network nomenclatureLucina Q. Uddin, Richard F. Betzel, Jessica R. Cohen, Jessica S. Damoiseaux, Felipe De Brigard, Simon B. Eickhoff, and 16 more authorsNetw Neurosci May 2023
The idea that the brain is composed of multiple large-scale networks has steadily gained traction over the past decade. Still, the field has not yet reached consensus on key issues regarding terminology. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide concrete recommendations and reporting guidelines for the scientific community. WHATNET members engaged in regular discussions, conducted a survey to catalog current practices in large-scale brain network nomenclature, identified barriers to progress, and brainstormed tools that could be developed to help standardize reporting in future studies. Here we summarize these activities and provide important considerations and initial recommendations for the network neuroscience community, noting open questions and controversies that require further empirical and theoretical investigation.Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macro-scale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field towards standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including 1) network scale, resolution, and hierarchies; 2) inter-individual variability of networks; 3) dynamics and non-stationarity of networks; 4) consideration of network affiliations of subcortical structures; and 5) consideration of multi-modal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.
- preprintA hierarchical Bayesian brain parcellation framework for fusion of functional imaging datasetsDa Zhi, Ladan Shahshahani, Caroline Nettekoven, Ana Luísa Pinho, Danilo Bzdok, and Jörn DiedrichsenbioRxiv May 2023
One important barrier in the development of complex models of human brain organization is the lack of a large and comprehensive task-based neuro-imaging dataset. Therefore, current atlases of functional brain organization are mainly based on single and homogeneous resting-state datasets. Here, we propose a hierarchical Bayesian framework that can learn a probabilistically defined brain parcellation across numerous task-based and resting-state datasets, exploiting their combined strengths. The framework is partitioned into a spatial arrangement model that defines the probability of a specific individual brain parcellation, and a set of dataset-specific emission models that defines the probability of the observed data given the individual brain organization. We show that the framework optimally combines information from different datasets to achieve a new population-based atlas of the human cerebellum. Furthermore, we demonstrate that, using only 10 min of individual data, the framework is able to generate individual brain parcellations that outperform group atlases.Competing Interest StatementThe authors have declared no competing interest.
- Journal ArticleBrain topography beyond parcellations: Local gradients of functional mapsElvis Dohmatob, Hugo Richard, Ana Luísa Pinho, and Bertrand ThirionNeuroimage May 2021
Functional neuroimaging provides the unique opportunity to characterize brain regions based on their response to tasks or ongoing activity. As such, it holds the premise to capture brain spatial organization. Yet, the conceptual framework to describe this organization has remained elusive: on the one hand, parcellations build implicitly on a piecewise constant organization, i.e. flat regions separated by sharp boundaries; on the other hand, the recently popularized concept of functional gradient hints instead at a smooth structure. Noting that both views converge to a topographic scheme that pieces together local variations of functional features, we perform a quantitative assessment of local gradient-based models. Using as a driving case the prediction of functional Magnetic Resonance Imaging (fMRI) data —concretely, the prediction of task-fMRI from rest-fMRI maps across subjects— we develop a parcel-wise linear regression model based on a dictionary of reference topographies. Our method uses multiple random parcellations —as opposed to a single fixed parcellation— and aggregates estimates across these parcellations to predict functional features in left-out subjects. Our experiments demonstrate the existence of an optimal cardinality of the parcellation to capture local gradients of functional maps.
- Journal ArticleCentering inclusivity in the design of online conferences—An OHBM–Open Science perspectiveElizabeth Levitis, Cassandra D Gould van Praag, Rémi Gau, Stephan Heunis, Elizabeth DuPre, Gregory Kiar, and 104 more authorsGigascience Aug 2021
As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities.Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design.Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.
- Journal ArticleSubject-specific segregation of functional territories based on deep phenotypingAna Luísa Pinho, Alexis Amadon, Murielle Fabre, Elvis Dohmatob, Isabelle Denghien, Juan Jesús Torre, and 15 more authorsHum Brain Mapp Aug 2021
Functional magnetic resonance imaging (fMRI) has opened the possibility to investigatehow brain activity is modulated by behavior. Most studies so far are bound to one singletask, in which functional responses to a handful of contrasts are analyzed and reported asa group average brain map. Contrariwise, recent data-collection efforts have started to tar-get a systematic spatial representation of multiple mental functions. In this paper, weleverage the Individual Brain Charting (IBC) dataset—a high-resolution task-fMRI datasetacquired in a fixed environment—in order to study the feasibility of individual mapping.First, we verify that the IBC brain maps reproduce those obtained from previous, large-scale datasets using the same tasks. Second, we confirm that the elementary spatial com-ponents, inferred across all tasks, are consistently mapped within and, to a lesser extent,across participants. Third, we demonstrate the relevance of the topographic informationof the individual contrast maps, showing that contrasts from one task can be predicted bycontrasts from other tasks. At last, we showcase the benefit of contrast accumulation forthe fine functional characterization of brain regions within a prespecified network. To thisend, we analyze the cognitive profile of functional territories pertaining to the languagenetwork and prove that these profiles generalize across participants.
- Journal ArticleFrom deep brain phenotyping to functional atlasingBertrand Thirion, Alexis Thual, and Ana Luísa PinhoCurr Opin Behav Sci Aug 2021
How can neuroimaging inform us about the function of brain structures? This simple question immediately brings out two pertinent issues: Firstly, an inference problem, namely the fact that the function of a region can only be asserted after observing a large array of experimental conditions or contrasts; and second, the fact that the identity of a region can only be defined with accuracy at the individual level, because of intrinsic differences between subjects. To overcome this double challenge, we consider an approach based on the deep phenotyping of behavioral responses from task data acquired using functional magnetic resonance imaging. The concept of functional fingerprint—which subsumes the accumulation of functional information at a given brain location—is herein discussed in detail through concrete examples taken from the Individual Brain Charting dataset.
- DatasetIBCAna Luísa Pinho, A. Amadon, T. Ruest, M. Fabre, B. Gauthier, N. Clairis, and 27 more authorsAug 2020
Overview: Functional Magnetic Resonance Imaging (fMRI) has opened the door to brain mapping of perceptual, motor, or cognitive functions. As such, it provides an instrumental basis for the whole field of cognitive neuroimag- ing. However, there exists to date no data collection that systematically maps representations for a wide-variety of mental functions at a fine spa- tial scale. The Individual Brain Charting (IBC) project is collecting a high-resolution multi-task-fMRI dataset, to provide an objective basis for a comprehensive atlas of brain responses. The data refer to a cohort of twelve participants performing many different tasks. Acquiring a large amount of tasks on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. Additionally, the dataset comes with high-resolution anatomical and diffusion images, to achieve a fine anatomical characterization of these brains.
- DatasetIndividual Brain Charting (IBC, release 2)Ana Luísa Pinho, A. Amadon, T. Ruest, M. Fabre, B. Gauthier, N. Clairis, and 27 more authorsAug 2020
We present an extension of the Individual Brain Charting dataset – a high spatial-resolution, multi-task, functional Magnetic Resonance Imaging dataset, intended to support the investigation on the functional principles governing cognition in the human brain. The concomitant data acquisition from the same 12 participants, in the same environment, allows to obtain in the long run finer cognitive topographies, free from inter-subject and inter-site variability. This second release provides more data from psychological domains present in the first release, and also yields data featuring new ones. It includes tasks on e.g. mental-time travel, reward, theory-of-mind, pain, numerosity, self-reference effect and speech recognition. In total, 13 tasks with 86 contrasts were added to the dataset and 63 new components were included in the cognitive description of the ensuing contrasts. As the dataset becomes larger, the collection of corresponding topographies becomes more comprehensive, leading to better brain-atlasing frameworks. This dataset is an open-access facility; raw data and derivatives are also publicly available in NeuroVault repositories. NeuroVault persistent identifier: https://identifiers.org/neurovault.collection:6618
- DatasetIndividual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mappingAna Luísa Pinho, A. Amadon, T. Ruest, M. Fabre, B. Gauthier, N. Clairis, and 27 more authorsAug 2020
The individual Brain Charting (IBC) Project is using high resolution fMRI to map 13 subjects that undergo a large number of tasks: the HCP tasks, the so-called ARCHI tasks, a specific language task, video watching, low-level visual stimulation etc. The native resolution of the data is 1.5mm isotropic. Their main value lies in the large number of contrasts probed, the level of detail and the high SNR per subject. This dataset is meant to provide the basis of a functional brain atlas. We upload here smoothed individual SPMs. The uploaded maps comprise session-specific and fixed effects across maps acquired with AP and PA phase encoding directions. Note that Neurovault collection #4438 is a subset of that one. In the present collections, some details have been fixed, including mroe accurate and unique file naming. Related article: http://doi.org/10.1038/s41597-020-00670-4
- Journal ArticleIndividual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mappingAna Luísa Pinho, Alexis Amadon, Baptiste Gauthier, Nicolas Clairis, André Knops, Sarah Genon, and 22 more authorsSci Data Aug 2020
We present an extension of the Individual Brain Charting dataset –a high spatial-resolution, multi-task, functional Magnetic Resonance Imaging dataset, intended to support the investigation on the functional principles governing cognition in the human brain. The concomitant data acquisition from the same 12 participants, in the same environment, allows to obtain in the long run finer cognitive topographies, free from inter-subject and inter-site variability. This second release provides more data from psychological domains present in the first release, and also yields data featuring new ones. It includes tasks on e.g. mental time travel, reward, theory-of-mind, pain, numerosity, self-reference effect and speech recognition. In total, 13 tasks with 86 contrasts were added to the dataset and 63 new components were included in the cognitive description of the ensuing contrasts. As the dataset becomes larger, the collection of the corresponding topographies becomes more comprehensive, leading to better brain-atlasing frameworks. This dataset is an open-access facility; raw data and derivatives are publicly available in neuroimaging repositories.
- PreprintFast shared response model for fMRI dataHugo Richard, Lucas Martin, Ana Luísa Pinho, Jonathan W. Pillow, and Bertrand ThirionCoRR Aug 2019
The shared response model provides a simple but effective framework to analyse fMRI data of subjects exposed to naturalistic stimuli. However when the number of subjects or runs is large, fitting the model requires a large amount of memory and computational power, which limits its use in practice. In this work, we introduce the FastSRM algorithm that relies on an intermediate atlas-based representation. It provides considerable speed-up in time and memory usage, hence it allows easy and fast large-scale analysis of naturalistic-stimulus fMRI data. Using four different datasets, we show that our method matches the performance of the original SRM algorithm while being about 5x faster and 20x to 40x more memory efficient. Based on this contribution, we use FastSRM to predict age from movie watching data on the CamCAN sample. Besides delivering accurate predictions (mean absolute error of 7.5 years), FastSRM extracts topographic patterns that are predictive of age, demonstrating that brain activity during free perception reflects age.
- Journal ArticleGender bias in (neuro) science: facts, consequences, and solutionsJessica Schrouff, Doris Pischedda, Sarah Genon, Gregory Fryns, Ana Luísa Pinho, Eliana Vassena, and 2 more authorsEur J Neurosci Aug 2019
- Book ChapterThe Neuropsychological Aspects of Musical CreativityAna Luísa PinhoAug 2018
Creativity emerges from the individual or collective intellect, in order to unfold the conundrum of life and give rise to meaningful deliberations for the attainment of a flourishing life. More specifically, creativity is commonly defined, within the framework of psychology, as an act or product that shall fulfill three main criteria: originality, unexpectedness, and usefulness. The cognitive science approach to creativity investigates the intellectual processes and representations concerned with the creative thinking. The methodologies of cognitive science, derived from the technological advancements of the past sixty years, have begun to adopt a more definitive and systemic perspective. Neuroscience has emerged, under this context, as the scientific study dedicated to explore the biological substrates of the nervous system, by utilizing a multitude of techniques such as neuroimaging. Cognitive neuroscience, in particular, studies the neural correlates of mental processes, and it constitutes the central approach herein adopted to examine musical creativity as a product of the human mind. In the present section, a definition plus historical evolvement of creativity are firstly provided together with an overview of its developments in psychometry. Secondly, a comprehensive description regarding the scientific advances about the topic, and within the field of cognitive neuroscience, is described according to: (1) the model on the four types of creativity and (2) the main categories of experimental designs implemented so far. Lastly, the latest advancements on the study of musical creativity, in particular musical improvisation, will be addressed under the neuroimaging framework.
- Journal ArticleIndividual Brain Charting, a high-resolution fMRI dataset for cognitive mappingAna Luísa Pinho, Alexis Amadon, Torsten Ruest, Murielle Fabre, Elvis Dohmatob, Isabelle Denghien, and 15 more authorsSci Data Jun 2018
Functional Magnetic Resonance Imaging (fMRI) has furthered brain mapping on perceptual, motor, as well as higher-level cognitive functions. However, to date, no data collection has systematically addressed the functional mapping of cognitive mechanisms at a fine spatial scale. The Individual Brain Charting (IBC) project stands for a high-resolution multi-task fMRI dataset that intends to provide the objective basis toward a comprehensive functional atlas of the human brain. The data refer to a cohort of 12 participants performing many different tasks. The large amount of task-fMRI data on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. The present article gives a detailed description of the first release of the IBC dataset. It comprises a dozen of tasks, addressing both low- and high- level cognitive functions. This openly available dataset is thus intended to become a reference for cognitive brain mapping.
- Conference PaperOptimizing deep video representation to match brain activityHugo Richard, Ana Luísa Pinho, Bertrand Thirion, and Guillaume CharpiatIn CCN 2018 - Conference on Cognitive Computational Neuroscience Sep 2018
The comparison of observed brain activity with the statistics generated by artificial intelligence systems is useful to probe brain functional organization under ecological conditions. Here we study fMRI activity in ten subjects watching color natural movies and compute deep representations of these movies with an architecture that relies on optical flow and image content. The association of activity in visual areas with the different layers of the deep architecture displays complexity-related contrasts across visual areas and reveals a striking foveal/peripheral dichotomy.
- Journal ArticleAddressing a paradox: dual strategies for creative performance in introspective and extrospective networksAna Luísa Pinho, Fredrik Ullén, Miguel Castelo-Branco, Peter Fransson, and Örjan ManzanoCereb Cortex Sep 2015
Neuroimaging studies of internally generated behaviors have shown seemingly paradoxical results regarding the dorsolateral prefrontal cortex (DLPFC), which has been found to activate, not activate or even deactivate relative to control conditions. On the one hand, the DLPFC has been argued to exert top–down control over generative thought by inhibiting habitual responses; on the other hand, a deactivation and concomitant decrease in monitoring and focused attention has been suggested to facilitate spontaneous associations and novel insights. Here, we demonstrate that prefrontal engagement in creative cognition depends dramatically on experimental conditions, that is, the goal of the task. We instructed professional pianists to perform improvisations on a piano keyboard during fMRI and play, either with a certain emotional content (happy/fearful), or using certain keys (tonal/atonal pitch-sets). We found lower activity in primarily the right DLPFC, dorsal premotor cortex and inferior parietal cortex during emotional conditions compared with pitch-set conditions. Furthermore, the DLPFC was functionally connected to the default mode network during emotional conditions and to the premotor network during pitch-set conditions. The results thus support the notion of two broad cognitive strategies for creative problem solving, relying on extrospective and introspective neural circuits, respectively.
- Journal ArticleConnecting to create: expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areasAna Luísa Pinho, Örjan Manzano, Peter Fransson, Helene Eriksson, and Fredrik UllénJ Neurosci Sep 2014
Musicians have been used extensively to study neural correlates of long-term practice, but no studies have investigated the specific effects of training musical creativity. Here, we used human functional MRI to measure brain activity during improvisation in a sample of 39 professional pianists with varying backgrounds in classical and jazz piano playing. We found total hours of improvisation experience to be negatively associated with activity in frontoparietal executive cortical areas. In contrast, improvisation training was positively associated with functional connectivity of the bilateral dorsolateral prefrontal cortices, dorsal premotor cortices, and presupplementary areas. The effects were significant when controlling for hours of classical piano practice and age. These results indicate that even neural mechanisms involved in creative behaviors, which require a flexible online generation of novel and meaningful output, can be automated by training. Second, improvisational musical training can influence functional brain properties at a network level. We show that the greater functional connectivity seen in experienced improvisers may reflect a more efficient exchange of information within associative networks of importance for musical creativity.