scholarly journals Mechanisms of Human Motor Learning Do Not Function Independently

2022 ◽  
Vol 15 ◽  
Author(s):  
Amanda S. Therrien ◽  
Aaron L. Wong
Keyword(s):  
Reinforcement Learning ◽  
Motor Learning ◽  
Neural Circuits ◽  
Future Research ◽  
Learning Mechanisms ◽  
Learning Mechanism ◽  
Overt Behavior ◽  
Human Motor ◽  
Sensory Prediction ◽  
Review Current

Human motor learning is governed by a suite of interacting mechanisms each one of which modifies behavior in distinct ways and rely on different neural circuits. In recent years, much attention has been given to one type of motor learning, called motor adaptation. Here, the field has generally focused on the interactions of three mechanisms: sensory prediction error SPE-driven, explicit (strategy-based), and reinforcement learning. Studies of these mechanisms have largely treated them as modular, aiming to model how the outputs of each are combined in the production of overt behavior. However, when examined closely the results of some studies also suggest the existence of additional interactions between the sub-components of each learning mechanism. In this perspective, we propose that these sub-component interactions represent a critical means through which different motor learning mechanisms are combined to produce movement; understanding such interactions is critical to advancing our knowledge of how humans learn new behaviors. We review current literature studying interactions between SPE-driven, explicit, and reinforcement mechanisms of motor learning. We then present evidence of sub-component interactions between SPE-driven and reinforcement learning as well as between SPE-driven and explicit learning from studies of people with cerebellar degeneration. Finally, we discuss the implications of interactions between learning mechanism sub-components for future research in human motor learning.

scholarly journals Brain activity reveals multiple motor-learning mechanisms in a real-world task

2020 ◽  
Author(s):  
Shlomi Haar ◽  
A. Aldo Faisal
Keyword(s):  
Motor Learning ◽  
Real World ◽  
Brain Activity ◽  
Skill Learning ◽  
Neural Dynamics ◽  
Complex Task ◽  
Motor Skill Learning ◽  
Learning Mechanisms ◽  
Learning Mechanism ◽  
Eeg Recordings

AbstractMany recent studies found signatures of motor learning in neural Beta oscillations (13– 30Hz), and specifically in the post-movement Beta rebound (PMBR). All these studies were in controlled laboratory-tasks in which the task designed to induce the studied learning mechanism. Interestingly, these studies reported opposing dynamics of the PMBR magnitude over learning for the error-based and reward-based tasks (increase versus decrease, respectively). Here we explored the PMBR dynamics during real-world motor-skill-learning in a billiards task using mobile-brain-imaging. Our EEG recordings highlight the opposing dynamics of PMBR magnitudes (increase versus decrease) between different subjects performing the same task. The groups of subjects, defined by their neural dynamics, also showed behavioural differences expected for different learning mechanisms. Our results suggest that when faced with the complexity of the real-world different subjects might use different learning mechanisms for the same complex task. We speculate that all subjects combine multi-modal mechanisms of learning, but different subjects have different predominant learning mechanisms.

Transferrin-Conjugated Nanocarriers as Active-Targeted Drug Delivery Platforms for Cancer Therapy

2017 ◽  
Vol 23 (3) ◽  
pp. 454-466 ◽  
Author(s):  
Daniele R. Nogueira-Librelotto ◽  
Cristiane F. Codevilla ◽  
Ammad Farooqi ◽  
Clarice M. B. Rolim
Keyword(s):  
Drug Delivery ◽  
Cancer Therapy ◽  
Tumor Cells ◽  
Therapeutic Benefit ◽  
Active Targeting ◽  
Future Research ◽  
Passive Targeting ◽  
The Right ◽  
Review Current ◽  
Target Effects

A lot of effort has been devoted to achieving active targeting for cancer therapy in order to reach the right cells. Hence, increasingly it is being realized that active-targeted nanocarriers notably reduce off-target effects, mainly because of targeted localization in tumors and active cellular uptake. In this context, by taking advantage of the overexpression of transferrin receptors on the surface of tumor cells, transferrin-conjugated nanodevices have been designed, in hope that the biomarker grafting would help to maximize the therapeutic benefit and to minimize the side effects. Notably, active targeting nanoparticles have shown improved therapeutic performances in different tumor models as compared to their passive targeting counterparts. In this review, current development of nano-based devices conjugated with transferrin for active tumor-targeting drug delivery are highlighted and discussed. The main objective of this review is to provide a summary of the vast types of nanomaterials that have been used to deliver different chemotherapeutics into tumor cells, and to ultimately evaluate the progression on the strategies for cancer therapy in view of the future research.

scholarly journals MEG signatures of long-term effects of agreement and disagreement with the majority

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. Gorin ◽  
V. Klucharev ◽  
A. Ossadtchi ◽  
I. Zubarev ◽  
V. Moiseeva ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Social Influence ◽  
Temporal Dynamics ◽  
Peer Group ◽  
Long Term Effects ◽  
Learning Mechanisms ◽  
Source Imaging ◽  
The Face ◽  
First Session

AbstractPeople often change their beliefs by succumbing to an opinion of others. Such changes are often referred to as effects of social influence. While some previous studies have focused on the reinforcement learning mechanisms of social influence or on its internalization, others have reported evidence of changes in sensory processing evoked by social influence of peer groups. In this study, we used magnetoencephalographic (MEG) source imaging to further investigate the long-term effects of agreement and disagreement with the peer group. The study was composed of two sessions. During the first session, participants rated the trustworthiness of faces and subsequently learned group rating of each face. In the first session, a neural marker of an immediate mismatch between individual and group opinions was found in the posterior cingulate cortex, an area involved in conflict-monitoring and reinforcement learning. To identify the neural correlates of the long-lasting effect of the group opinion, we analysed MEG activity while participants rated faces during the second session. We found MEG traces of past disagreement or agreement with the peers at the parietal cortices 230 ms after the face onset. The neural activity of the superior parietal lobule, intraparietal sulcus, and precuneus was significantly stronger when the participant’s rating had previously differed from the ratings of the peers. The early MEG correlates of disagreement with the majority were followed by activity in the orbitofrontal cortex 320 ms after the face onset. Altogether, the results reveal the temporal dynamics of the neural mechanism of long-term effects of disagreement with the peer group: early signatures of modified face processing were followed by later markers of long-term social influence on the valuation process at the ventromedial prefrontal cortex.

Hierarchical Reinforcement Learning

2021 ◽  
Vol 54 (5) ◽  
pp. 1-35
Author(s):  
Shubham Pateria ◽  
Budhitama Subagdja ◽  
Ah-hwee Tan ◽  
Chai Quek
Keyword(s):  
Reinforcement Learning ◽  
Future Research ◽  
Comprehensive Overview ◽  
Open Problems ◽  
Practical Applications ◽  
Hierarchical Reinforcement Learning ◽  
The Past ◽  
Agent Learning ◽  
Multi Agent ◽  
Supplementary Material

Hierarchical Reinforcement Learning (HRL) enables autonomous decomposition of challenging long-horizon decision-making tasks into simpler subtasks. During the past years, the landscape of HRL research has grown profoundly, resulting in copious approaches. A comprehensive overview of this vast landscape is necessary to study HRL in an organized manner. We provide a survey of the diverse HRL approaches concerning the challenges of learning hierarchical policies, subtask discovery, transfer learning, and multi-agent learning using HRL. The survey is presented according to a novel taxonomy of the approaches. Based on the survey, a set of important open problems is proposed to motivate the future research in HRL. Furthermore, we outline a few suitable task domains for evaluating the HRL approaches and a few interesting examples of the practical applications of HRL in the Supplementary Material.

Extended dosing of monoclonal antibodies in multiple sclerosis

2021 ◽  
pp. 135245852110657
Author(s):  
Zoé LE van Kempen ◽  
Alyssa A Toorop ◽  
Finn Sellebjerg ◽  
Gavin Giovannoni ◽  
Joep Killestein
Keyword(s):  
Multiple Sclerosis ◽  
Monoclonal Antibodies ◽  
Treatment Options ◽  
Future Research ◽  
Therapeutic Drug ◽  
Therapeutic Landscape ◽  
Anti Cd20 ◽  
Dosing Intervals ◽  
Care Costs ◽  
Review Current

Over the past two decades, treatment options for patients with multiple sclerosis (MS) have increased exponentially. In the current therapeutic landscape, “no evidence of MS disease activity” is within reach in many of our patients. Minimizing risks of complications, improving treatment convenience, and decreasing health care costs are goals that are yet to be reached. One way to optimize MS therapy is to implement personalized or extended interval dosing. Monoclonal antibodies are suitable candidates for personalized dosing (by therapeutic drug monitoring) or extended interval dosing. An increasing number of studies are performed and underway reporting on altered dosing intervals of anti-α4β1-integrin treatment (natalizumab) and anti-CD20 treatment (ocrelizumab, rituximab, and ofatumumab) in MS. In this review, current available evidence regarding personalized and extended interval dosing of monoclonal antibodies in MS is discussed with recommendations for future research and clinical practice.

scholarly journals HYPOXIA AND REPRODUCTIVE HEALTH: The presence and role of hypoxia in the endometrium

Reproduction ◽  
2021 ◽  
Vol 161 (1) ◽  
pp. F1-F17
Author(s):  
Rocío Martínez-Aguilar ◽  
Lucy E Kershaw ◽  
Jane J Reavey ◽  
Hilary O D Critchley ◽  
Jacqueline A Maybin
Keyword(s):  
Current Knowledge ◽  
Abnormal Uterine Bleeding ◽  
Future Research ◽  
Hypoxic Episode ◽  
Optimal Function ◽  
Pros And Cons ◽  
The Impact ◽  
Review Current

The endometrium is a multicellular tissue that is exquisitely responsive to the ovarian hormones. The local mechanisms of endometrial regulation to ensure optimal function are less well characterised. Transient physiological hypoxia has been proposed as a critical regulator of endometrial function. Herein, we review the literature on hypoxia in the non-pregnant endometrium. We discuss the pros and cons of animal models, human laboratory studies and novel in vivo imaging for the study of endometrial hypoxia. These research tools provide mounting evidence of a transient hypoxic episode in the menstrual endometrium and suggest that endometrial hypoxia may be present at the time of implantation. This local hypoxia may modify the inflammatory environment, influence vascular remodelling and modulate endometrial proliferation to optimise endometrial function. Finally, we review current knowledge of the impact of this hypoxia on endometrial pathologies, with a focus on abnormal uterine bleeding. Throughout the manuscript areas for future research are highlighted with the aim of concentrating research efforts to maximise future benefits for women and society.

scholarly journals Winners and losers - communicating the potential impacts of policies

2018 ◽  
Author(s):  
Cameron Brick ◽  
William John Skylark ◽  
Alexandra Lee Jessica Freeman ◽  
Theresa Marteau
Keyword(s):  
Policy Decision ◽  
Policy Option ◽  
Decision Makers ◽  
Future Research ◽  
Communication Effectiveness ◽  
Policy Options ◽  
Effective Policy ◽  
Policy Decision Making ◽  
Long Timescales ◽  
Review Current

Individual decision-makers need communications that succinctly describe potential harms and benefits of different options, but policymakers or citizens evaluating a policy are rarely given a balanced and easily understood summary of the potential outcomes of their decision. We review current policy option communication across diverse domains such as taxes, health, climate change, and international trade, followed by reviews of guidance and evidence for communication effectiveness. Our conceptual synthesis identifies four characteristics of policy options that make their communication particularly difficult: heterogeneous impacts on different segments of the population, multiple outcomes, long timescales, and large uncertainties. For communicators that are trying to inform rather than persuade, these complexities reveal a core tension between issue coverage and comprehensibility. We find little empirical evidence for how to communicate policy options effectively. We identify promising current communications, analyze them based on the above synthesis, and suggest priorities for future research. Recognizing the particular challenges of balanced, effective policy option communications could lead to better guidelines and support for policy decision-making. https://www.nature.com/articles/s41599-018-0121-9

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