Does one size fit all? - Towards the optimization and personalization of non-invasive brain stimulation paradigms to enhance motor learning

Laurijn Rianne Draaisma
EPFL, 2022
Thèse EPFL

Résumé

The acquisition and re-acquisition of motor skills is an important aspect of daily life and in the recovery after a stroke. Non-invasive brain stimulation (NIBS) is a technique that is used to improve motor learning and enhance motor recovery in stroke survivors. Although the current results are promising, the outcomes are heterogeneous with responders and non-responders. This thesis aimed to investigate multiple, novel NIBS strategies to enhance stimulation efficacy and to develop approaches for protocol personalization. These alternative strategies include targeting other areas of the motor network than the primary motor cortex (M1), targeting the brain as a network with the use of multifocal stimulation, and using a variety of stimulation techniques (TMS, tACS, tDCS) to study underlying mechanisms. Study 1 explored the methodological implications of TMS for measuring inhibitory and excitatory neurotransmissions. With the use of TMS, short intracortical inhibition (SICI) and intracortical facilitation (ICF) were measured in healthy young adults. SICI and ICF were studied with different stimulators, waveforms, and current directions using a set of interstimulus intervals. Our findings indicated high comparability among the different stimulation paradigms, except for SICI at 3 ms, which enables data sharing across units and facilitates the conduction of multi-center studies.Study 2 measured the effect of 50 Hz tACS applied to the cerebellum on a novel motor learning task in healthy young adults. Targeting the cerebellum with NIBS is a relatively new field of research with open questions that need to be addressed. Therefore, we explored for the first time the effect of CB-tACS on a motor learning task. Our results did not show an improvement of learning with 50 Hz CB-tACS. We argue that this might have been related to the task and/or the selected stimulation frequency. Therefore, this stimulation paradigm requires further optimization to be effective for motor learning.Study 3 compared multifocal sequential stimulation to monofocal tDCS on motor learning in stroke patients. The multifocal paradigm consisted of an orchestrated M1 â CB stimulation setup, the monofocal paradigm targeted the M1. Our results indicated a significant effect of multifocal M1-CB stimulation, mainly driven by CB-tDCS during the early phase of learning. Moreover, baseline performance and neurophysiology were related to stimulation responsiveness that could potentially lead to biomarkers to predict stimulation efficacy in stroke patients.Study 4 measured the effect of personalized bifocal theta tACS applied to the FPN on motor learning in healthy older adults. Sequence learning has a cognitive component related to working memory (WM) capacity, a process mediated by the FPN. We hypothesized that targeting the FPN might be beneficial for motor learning. tACS to the FPN improved performance, when WM load was high, but not when WM-load was low. Therefore, we conclude that the FPN is a promising new target to enhance motor learning which might be most beneficial for individuals with decreased WM capacity due to age or stroke. In conclusion, this thesis demonstrates that targeting alternative motor network areas, and multifocal stimulation is promising. These results expand on the current knowledge of NIBS and identified open questions that require further examination but could ultimately lead towards enhanced efficacy and the personalization of study protocols.

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https://infoscience.epfl.ch/record/294546?ln=fr

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Laurijn Rianne Draaisma
EPFL, 2022
Thèse EPFL

Résumé

Official source

https://infoscience.epfl.ch/record/294546?ln=fr

À propos de ce résultat

Concepts associés (23)

Concepts associés

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Publications associées (64)

Publications associées

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Determining patterns of post-stroke motor recovery through longitudinal multimodal MRI: A step towards patient stratification

Julia Brügger

Motivated by the need for a better understanding of post-stroke recovery and new biomarkers to improve stroke patient stratification and outcomes, this thesis investigated structure-function coupling and its role in post-stroke recovery. Furthermore, in order to increase data comparability between sessions and centers (a critical challenge in contemporary clinical research), this thesis assessed the reproducibility of microstructure-informed structural connectivity measures in a multi-center dataset.Stroke is one of the major sources of permanent impairment, frequently of motor origin. However the clinical picture is very heterogeneous: patients show divergent courses of recovery and the underlying mechanisms are still unclear. In addition, current treatments still have limited success and are restricted to a 'one-fits-all' approach, not considering the individual patient's phenotype. As efforts to stratify patients based on structural or functional biomarkers are still needed, we chose to investigate the potential of a multimodal biomarker, the Structural Decoupling Index (SDI) (Preti & Van De Ville, 2019b), a new metric assessing the structure-function coupling strength in the brain. The first part (Studies 1 and 2) of this thesis investigates the potential of the SDI as a biomarker. In Study 1, the goals were to evaluate the feasibility of applying the SDI on an individual level in healthy older adults and to investigate the effect of an acute stroke on it. Consistent with the literature, we found a network gradient of SDI in healthy older adults, from high coupling in lower-level sensory areas, to low coupling in higher-level cognitive areas. This confirmed the applicability of SDI on an individual level. Furthermore, we showed that stroke impacts the SDI, with a higher decoupling on the ipsi- compared to the contralesional side, and with network-specific effects in RH stroke patients. In Study 2, the goal was to see whether the SDI evolved over time post-stroke and whether it links to behavior. The longitudinal analysis revealed differential network effects of stroke at T1 and T3. Furthermore, we showed that impairment in cognitive and psychological behavioral domains significantly correlates with variations in SDI in a number of key areas including motor regions (e.g., primary motor cortex) and that the brain pattern associated to behavior changes between T1 and T2. Surprisingly, motor performance did not explain variability in key motor areas (e.g., primary motor cortex). The link between post-stroke behavioral performance and SDI underlines its potential clinical relevance.Driven by the quest for more reproducible analysis pipelines in the context of longitudinal and clinical studies, the second part of this thesis (Study 3) addressed the subject-specific reproducibility and repeatability of microstructure-informed tractography. Through a multi-center study, we demonstrated its high reproducibility and subject-specificity, and we found evidence for increased biological accuracy. My thesis made a contribution by showing that the SDI is sensitive to pathophysiological changes that occur following a stroke and that it links to clinically relevant behavioral measures. In addition, it confirms the reproducibility and subject-specificity of microstructure-informed tractography. Together, my findings pave the way towards patient stratification and more personalized treatments in stroke rehabilitation.

EPFL2022

Chargement

Elucidating the role of neuron-astrocyte metabolic coupling in learning and memory

Monika Tadi

The brain has very high energy demands that are mainly met by the circulating blood glucose to ensure its proper functioning. Thus, it is not surprising that though the human brain weighs only 2- 3% of the body weight, it consumes approximately 25% of total body glucose. “Neuro-energetic coupling" is a unique feature of the brain and refers to the existence of the tight coupling between (neuronal) synaptic brain activity and energy metabolism. The main excitatory neurotransmitter in the brain is glutamate and most of the energy requirements at the cortical level are met through glutamate-mediated neurotransmission, suggesting that there is a close relationship between brain activity, glutamatergic neurotransmission and energy metabolism. Until the 80s, blood-borne glucose was thought to be the sole energy substrate of the brain cells and it was assumed that glucose is metabolized by neurons and astrocytes (a type of glial cell) independently. It is only during the last two decades that the concept of compartmentalization of energy metabolism between neurons and astrocytes has become more obvious. The transfer of lactate from astrocytes to neurons termed as the “astrocyte-neuron lactate shuttle (ANLS)” model proposed by Dr. Pellerin and Prof. Magistretti posits that glutamate released during brain activation activates glycolysis (one of glucose metabolic pathways) in astrocytes leading to lactate (a monocarboxylate) release in the extracellular space, and this astrocytic lactate is then captured and used as an energy substrate by the activated neurons to meet their energy requirements. It includes a complex chain of events involved in neuro-metabolic coupling and supports the preferential use of lactate by activated neurons under conditions of increased energy demands. Higher brain functions such as learning a new task are associated with structural changes in brain and are metabolically demanding necessitating the need of an additional energy supply to meet the neurons increased energy requirement. In this context, the current thesis project aimed to elucidate the contribution of metabolic coupling between astrocytes and neurons, known as “neuron-astrocyte metabolic coupling” to learning and memory formation. Using an in vivo approach combined with behavioral, molecular and gene manipulation techniques in mice, we set out to investigate the role of neuron-astrocyte metabolic coupling, particularly ANLS in cognition. The project was divided into two main parts: In the first part, the expression of glucose metabolism-related genes was investigated during long term memory (LTM) formation in fear-motivated inhibitory avoidance (IA) learning paradigm. Using (14C) 2-Deoxyglucose (2-DG) technique, we first defined the brain areas that are involved in IA LTM formation. This technique provides an indirect measurement of brain activity by measuring glucose uptake in different brain areas during the task. The results of brain metabolic mapping show an increase in glucose utilization in the hippocampus, amygdala, anterior cingulate cortex and pre-limbic and infra-limbic cortical areas. Results from the quantitative analysis of mRNA levels in the dorsal hippocampus at different time point’s following IA task highlight a time dependent, learning specific change in the expression of genes related to glucose metabolism. Specific set of genes involved in the synthesis and degradation of glycogen (brain glucose reserve present only in astrocytes), pyruvate metabolism and pentose phosphate shunt as well as the ANLS were induced following the IA task. These early observations indicate that the metabolic interactions between astrocytes and neurons undergo modifications during a learning process and suggest that these adaptations may play a key role in the establishment of long-term memory. In the second part of research project, we focused on investigating the behavioral consequences of down regulating the expression of Monocarboxylate Transporter 1 (MCT1), a key ANLS related gene, on cognition and higher brain functions. Mice heterozygous for the MCT1 gene (MCT1+/-) were characterized in numerous behavioral paradigms such as general wellbeing, reflexive and motor capabilities. After having established that MCT1+/- mice have no alterations in general emotional state or in locomotion, a battery of behavioral tests was performed to study cognition in these mice. Compared with wild-type control mice, the MCT1+/- mice display normal muscle strength and motor coordination. However, when tested for higher brain functions, the MCT1+/- mice exhibit learning and memory deficits in several learning paradigms/tasks that are hippocampus and / or amygdala dependent. The cognitive impairment observed in the MCT1 heterozygous mice further highlights the importance of ANLS in memory and suggest that disruption of lactate transfer from astrocytes to neurons via the MCT1 results in cognitive impairment. The overall results in this thesis demonstrate that cerebral energy metabolism, and in particular the transfer of lactate from astrocytes to neurons not only provides temporal adaptations in the learning process, but it also plays a fundamental role in memory formation.

EPFL2013

Chargement

Spinal Cord Injury (SCI) disrupts the communication between the brain and spinal circuits below the lesion, leading to a plethora of neurological impairments, including the loss of motor function. At present, the only medical practices to enhance recovery after paralysis are activity-based therapies. In severe cases, SCI-patients fail to produce active movements voluntarily and are therefore unable to fully benefit from these therapies. Epidural Electrical Stimulation (EES) applied over the lumbosacral spinal cord has demonstrated to enable locomotion in preclinical animal models and humans with SCI. EES may therefore play a pivotal role in the recovery of locomotion after SCI.However, neither has EES reached the same level of efficacy in humans as in preclinical animal models, nor is there consensus on the definition of clinically meaningful stimulation protocols. In the absence of clear understanding on how EES promotes the formation of motor patterns, stimulation protocols have been largely based on empirical observations. Instead, hypothesis-driven definition of stimulation parameters has demonstrated superior efficacy in other neuromodulation therapies, such as deep brain stimulation.In this thesis, I outline a computational approach to inform EES strategies for the recovery of neurological function after SCI. For this purpose, I leveraged a combination of finite element methods, neurophysical and neuromusculoskeletal models to refine our understanding on how EES promotes locomotion after SCI, inform the design of neuromodulation technologies and develop personalized EES treatments in humans with SCI.In the first part of this thesis, I provide evidence that EES recruits proprioceptive and cutaneous afferents in the dorsal roots. I suggest that the recruitment of proprioceptive feedback circuits promotes the formation of motor patterns. In contrary, the continuous recruitment of cutaneous afferents may disrupt the production of locomotion. In the next chapter, I study interspecies difference of EES. I argue that these differences necessitate the adaption of stimulation protocols to enable translation of EES as a therapy from preclinical models to humans. I propose the application of spatiotemporal protocols with low-amplitude, high-frequency bursts to improve the efficacy of EES in humans. In the following chapter, I describe a technological framework that enables the implementation of such stimulation paradigms in people with SCI. I outline how personalized computational modeling can be used for treatment planning. I then summarize how I advanced this rudimentary computational tool into a computational framework for the rapid elaboration of highly realistic personalizable computational models. I explain how I leveraged this framework to inform the arrangements of electrodes on a paddle lead to enable locomotion in large and diversified patient-cohorts, perform preoperative treatment planning and validate the efficacy of both the lead and treatment planning protocol in individuals with severe, chronic SCI. Finally, I summarize how I translated my computational framework for other use-cases including the control of hemodynamics and the evaluation of an optoelectronic system to enable locomotion in preclinical models.

EPFL2021

Chargement

Determining patterns of post-stroke motor recovery through longitudinal multimodal MRI: A step towards patient stratification

Julia Brügger

EPFL2022

Elucidating the role of neuron-astrocyte metabolic coupling in learning and memory

Monika Tadi

EPFL2013

EPFL2021