Periodic Reporting for period 1 - Laminar-PL (Ultra-high field imaging of perceptual learning and human brain plasticity)
Reporting period: 2019-04-01 to 2021-03-31
The human brain has extraordinary capacity to adapt to changes in noisy and variable environments. Learning and experience have been shown to shape critical functions of the adult brain to support our interactions in complex and dynamic environments. Investigating the brain mechanisms that mediate perceptual learning – that is, our ability to improve our performance when making perceptual judgments due to training – is at the core of understanding plastic brain changes. Understanding this learning-dependent plasticity not only has potential practical implications for designing training programmes for lifelong learning, but may also aid remediation and recovery in brain dysfunction.
Objectives of the Ultra-high field imaging of perceptual learning and human brain plasticity (Laminar-PL) project have been to combine interdisciplinary methods to investigate the neural mechanisms that mediate perceptual learning. First, the Fellow has combined psychophysical experiments, machine learning and ultra-high field imaging to investigate the neural locus of learning-dependent brain plasticity after extensive training and test competing theories of learning (i.e. learning-dependent changes at early stages of information encoding vs. later stages of decision making). Second, he has used cutting-edge computational neuroimaging methods to demonstrate the computational processes underlying perceptual learning (e.g. feedforward vs. recurrent vs. feedback). Third, he has measured laminar connectivity across brain areas based on task-related measurements (i.e. how different brain areas work together) that supports behavioral improvement due to training. Beyond the neural mechanisms of perceptual learning, the Fellow has also combined these cutting-edge techniques and constructed a working protocol for laminar imaging data analyses, which will provide valuable insights into the future development of software for MRI data analysis (e.g. BrainVoyager developed by Brain Innovation-secondment partner). Another parallel goal of this MSCA Individual Fellowship is to foster the development of the individual researcher.
Objectives of the Ultra-high field imaging of perceptual learning and human brain plasticity (Laminar-PL) project have been to combine interdisciplinary methods to investigate the neural mechanisms that mediate perceptual learning. First, the Fellow has combined psychophysical experiments, machine learning and ultra-high field imaging to investigate the neural locus of learning-dependent brain plasticity after extensive training and test competing theories of learning (i.e. learning-dependent changes at early stages of information encoding vs. later stages of decision making). Second, he has used cutting-edge computational neuroimaging methods to demonstrate the computational processes underlying perceptual learning (e.g. feedforward vs. recurrent vs. feedback). Third, he has measured laminar connectivity across brain areas based on task-related measurements (i.e. how different brain areas work together) that supports behavioral improvement due to training. Beyond the neural mechanisms of perceptual learning, the Fellow has also combined these cutting-edge techniques and constructed a working protocol for laminar imaging data analyses, which will provide valuable insights into the future development of software for MRI data analysis (e.g. BrainVoyager developed by Brain Innovation-secondment partner). Another parallel goal of this MSCA Individual Fellowship is to foster the development of the individual researcher.
Work was conducted via 5 work packages (WPs). WP2 sought to build skills with multiple research methodologies. The Fellow delivered 2 conference presentations and 1 published journal article. WP3 comprised 3 research studies that yielded 2 published journal articles, with an additional 2 journal manuscripts underway. The data sets collected and the methods developed during this MSCA are expected to inform a large number of publications in the coming years, in addition to the ones produced and published during the fellowship itself. In WP5, for researcher training and transfer-of-knowledge, the Fellow attended 11 intensive training workshops and multi-day conferences. With respect to knowledge transfer, the fellow worked with the MR physics team at the Wolfson Brain Image Centre to optimize the MR sequences, delivered 4 workshops at the Cambridge Neuroscience community to share the optimized data analysis protocol, and provided supervision and mentoring for early career researchers. The project was managed under WP1 and WP4.
Results of this MSCA are reported in: (1) published methods paper on how to preprocess the ultra-high field fMRI data and correct for vasculature-related confounds, improving the spatial accuracy of the fMRI signal. The same methods have already been used in 2 other high profile journal papers. (2) published paper on fine scale computations that support adaptive behaviour. This work revealed new recurrent mechanisms for learning-dependent plasticity in sensory circuits that forward information to decision related circuits for optimized perceptual decisions. This work has high impact in bridging the gap between animal studies interrogating microcircuits and large-scale brain networks revealed by human fMRI. This work was recently published in Current Biology and has already attracted lots of interest including a Dispatch.
Results of this MSCA are reported in: (1) published methods paper on how to preprocess the ultra-high field fMRI data and correct for vasculature-related confounds, improving the spatial accuracy of the fMRI signal. The same methods have already been used in 2 other high profile journal papers. (2) published paper on fine scale computations that support adaptive behaviour. This work revealed new recurrent mechanisms for learning-dependent plasticity in sensory circuits that forward information to decision related circuits for optimized perceptual decisions. This work has high impact in bridging the gap between animal studies interrogating microcircuits and large-scale brain networks revealed by human fMRI. This work was recently published in Current Biology and has already attracted lots of interest including a Dispatch.
The primary impact of Laminar-PL is the analysis pipeline for laminar fMRI data. This is the first pipeline to cover from data acquisition to data preprocessing and will benefit the future use of laminar fMRI for investigating the neural mechanisms underlying different cognitive processes. Second, understanding the neural computations that support brain plasticity is critical for designing training programmes that boost learning capacity and support functional brain enhancement, providing effective tools for promoting learning in real-world situations. In this framework, Laminar-PL advances our understanding of human brain plasticity, with potential implications for the remediation of cognitive functions through training in lifelong health and disease (brain injury, neurodegenerative disease).
The third impact of Laminar-PL is the training of the Fellow. During the fellowship, the fellow received advanced training to enhance his career development, with particular emphasis on support in grant writing, preparation of manuscripts for publication, and guidance for effective oral presentations. By gaining expertise with state-of-the-art methods, the Fellow advanced in his research in cognitive neuroscience at a globally competitive level. More importantly, by working with PhD students, and taking a role in supervising undergraduate and Masters students, the Fellow has also gained valuable experience in team working and research group management. Further, although the secondment was not possible in person due to travel restrictions during the pandemic, the Fellow interacted extensively with the secondment host and published his work in collaboration with the industrial stakeholder. Interactions with Brain Innovation BV provided the Fellow with critical insight into entrepreneurship, and research with commercial application. This experience has significantly broadened his future career prospects by enabling him to pursue work that has academic and/or commercial aspects. In sum, the independence in performing these roles has helped the Fellow to achieve the experience necessary for building his own laboratory and research team in the near future.
The third impact of Laminar-PL is the training of the Fellow. During the fellowship, the fellow received advanced training to enhance his career development, with particular emphasis on support in grant writing, preparation of manuscripts for publication, and guidance for effective oral presentations. By gaining expertise with state-of-the-art methods, the Fellow advanced in his research in cognitive neuroscience at a globally competitive level. More importantly, by working with PhD students, and taking a role in supervising undergraduate and Masters students, the Fellow has also gained valuable experience in team working and research group management. Further, although the secondment was not possible in person due to travel restrictions during the pandemic, the Fellow interacted extensively with the secondment host and published his work in collaboration with the industrial stakeholder. Interactions with Brain Innovation BV provided the Fellow with critical insight into entrepreneurship, and research with commercial application. This experience has significantly broadened his future career prospects by enabling him to pursue work that has academic and/or commercial aspects. In sum, the independence in performing these roles has helped the Fellow to achieve the experience necessary for building his own laboratory and research team in the near future.