Online Lecture #3

🎙️ Speaker: Prof. Dr. Mark Latash, Pennsylvania State University
📅 Date: Thursday, 21st August 2025
⏰ Time: 12:00-14:00 CET

🖥️ Link to join

 Topic: Structure of Motor variability as a Window into the Neural Control of Action

Biological movements involve numerous elements (joints, digits, muscles, neurons, etc.) at any level of analysis. This feature, addressed as motor redundancy, has been traditionally viewed as a source of computational problems for the brain. An alternative view, the principle of abundance, views the excess of elements as a powerful design that allows the brain to ensure and modify in a task-specific way dynamical stability of salient performance variables. The concept of uncontrolled manifold (UCM) as the solution space for a performance variable in a higher-dimensional space of elemental variables has been developed into a toolbox that allows to quantify features of action stability across tasks, spaces of analysis, and populations (including neurological patients). Its application has led to hypotheses on parallel action- stabilizing loops involving different neural circuitry. Recent developments include the analysis of intra-muscle performance- stabilizing synergies in spaces of individual motor unit firing frequencies, likely based on spinal circuitry, the analysis of synergies in spaces of hypothetical control variables (the reciprocal and coactivation commands) defined at different levels of the hierarchy, and exploration of the properties of the UCM.

Online Lecture #2

🎙️ Speaker: Prof. Dr. Paul Cisek, University of Montreal
📅 Date: Thursday, 3 April 2025
⏰ Time: 12:00-14:00 CET

 Topic: Neural mechanisms of embodied decisions Abstract

Psychological and neurophysiological studies of decision-making have focused primarily on scenarios in which subjects are faced with abstract choices that are stable in time. This has led to serial models of decision-making which begin with the representation of relevant information about costs and benefits, followed by careful deliberation about the choice leading to commitment. These cognitive models are separate from models of motor planning and execution, which normally begin with a single target or goal. However, the brain evolved to interact with a dynamic and constantly changing world, in which the choices themselves as well as their relative costs and benefits are defined by the momentary geometry of the immediate environment and are continuously changing, even during ongoing activity. To deal with the demands of real-time interactive behavior, animals require a neural architecture in which the sensorimotor specification of potential actions, their valuation, selection, and even execution can all take place in parallel. I will describe a general hypothesis for how the brain deals with the challenges of such dynamic and embodied behavior, and present the results of behavioral and neurophysiological experiments in which humans and monkeys make decisions on the basis of sensory information that changes over time. These experiments suggest that sensory information pertinent to decisions is processed quickly and combined with a growing signal related to the urge to act, and the result biases a competition between potential actions that unfolds within the same sensorimotor circuits that guide action. Finally, I will discuss how the processes of deliberation, commitment, and movement execution can be considered as states of an integrated dynamical system distributed across cortical and subcortical circuits.

 

Online Lecture #1

🎙️ Speaker: Prof. Dr. Hermann Müller, Justus Liebig University Gießen
📅 Date: Thursday, 23 January 2025
⏰ Time: 12:00-14:00 CET

Topic: Analyzing Functional Variability – Decomposition and Quantification

Variability is ubiquitous in human movement control, compromising reliable achievement of action goals. Stochastic fluctuations, so-called noise, exist in the environment, in sensory input, in signal transduction, and/or in the functional state of the effectors. Yet, the control system exploits multiple strategies to reduce the negative consequences of such noise. These strategies not only imply pure reduction of noise but can also involve specific adjustments to the task requirements. The variability in different parts of the movements may be shaped in a way that deviations in one part may compensate for deviations in other parts. Such variability can be considered as being “functional”. It does not endanger movement success but rather contributes to a reliable outcome. Furthermore, in case tasks can be solved in different ways, skilled people typically select solutions that are tolerant to variability in movement execution. Overall, these different strategies may all contribute to reducing the negative effects of noise; however, their specific relevance may differ from case to case. Different methods have been introduced to quantify the contribution of each of these factors on overall performance and performance improvements during learning. These methods will be discussed with regard to their usefulness to describe and explain differences in learning and performance across different populations, also including clinical aspects.

Timetable Future Online Lecture Series

Lecture #04: 20th November 2025

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Lecture #05: 5th February 2026

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Lecture #06: 7th May 2026

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Lecture #07: 6th August 2026

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Lecture #08: 5th November 2026

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Lecture #09: 4th February 2027

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Lecture #10: 13th May 2027

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