The neuroscientist reveals how her lab has decoded the kinematic code and discusses its implications for rehabilitation medicine
The way we move reflects our thoughts. Cristina Becchio, a Professor of Neuroscience at the University Medical Center Hamburg-Eppendorf and a member of the Scientific Committee of our research and innovation institute, firmly believes that. Professor Becchio’s work builds upon her studies in philosophy and neuroscience, followed by a Ph.D. in Cognitive Science and a post-doc in cognitive neuroscience. Indeed, her laboratory has decoded the kinematic code and revealed how information encoded in movement kinematics can be read during action observation. This work answers questions about the computations underlying decision-making, learning, and social interaction, with significant implications for understanding brain disorders and care in Rehabilitation Medicine.
Professor Becchio, could you explain your field of research?
“We investigate the relationship between cognitive and motor processes — specifically, the interplay between thought and movement—two dimensions that have historically been separated since the time of Descartes and continue to be so in Western culture. This perspective has fostered a certain skepticism toward movement, which rarely finds a place in experimental psychology or neuroscience textbooks, as it is often regarded as an output that provides little insight into cognitive and neural processes. Contrary to this view, our research demonstrated that cognitive processes manifest in variations of movement. By analyzing these variations, we can access information about cognitive, decision-making, perceptual, and emotional states. Thus, the idea that some mental states, often described as invisible, are, in fact, not invisible at all: we can observe them through the kinematics of movement”.
So, is movement a key to accessing our brain?
“Yes, it is. We often believe that thought is locked inside our brain, but this is not the case. Instead, thoughts are a deeply embodied experience, and movement serves to encode this information, which we can learn to interpret”.
But every movement is distinct from the others, even when the same gesture is repeated.
“This is a fundamental truth. In fact, the complexity of researching movement arises from the significant individual variability observed one individual to another, and within the same individual, from one trial to another. For instance, if I ask you to perform the same action—such as grasping, lifting and placing an object in a box—ten times, you will execute ten different movements. This variability also complicates the quantification of performance, which is a central concern in Rehabilitation Medicine. So, how do you evaluate a patient’s progress? What metrics do you use?”.
How have you navigated this complexity? How is the analysis of movement conducted?
“We utilize motion capture, a technique that employs infrared cameras to reconstruct the positions of specific reflective markers within a calibrated space. This technique is also commonly used in the field of digital animation, as seen in films like Avatar. The reflective markers are coated with retroreflective material, which reflects infrared light. By analyzing the return signal, we can accurately locate each marker in three-dimensional space. We record data at high frequency (100 Hertz) and spatial resolution to obtain detailed measurements of movement kinematics. To investigate how cognitive states, for example intentions, influence movement kinematics, we ask each participant to perform various sequences that differ only in intention, while the initial part of each sequence remains identical. By examining the differences in the initial kinematics, we can establish a probabilistic mapping between the mental state and the specific movement”.
What exactly are you trying to observe?
“Not the movement per se but rather the information encoded in the movement. For example, we investigate how the motor system anticipates the consequences of an action—predictive control. Before initiating an action, the brain estimates the expected outcomes and adjusts the parameters of the action prospectively to align with these predictions. Using our approach, we can quantify this predictive capacity, measuring how far into the future the motor system plans. This includes determining what the individual intends to do with an object immediately after interacting with it and the subsequent steps. For example, intentional planning, which involves considering the next step after the initial action, corresponds to second-order planning”.
How far can a healthy person predict movement?
“Depending on the task, healthy individuals can plan up to the fourth order. In contrast, in patients affected by a stroke, the ability to plan gestures is often compromised even at the first and second order”.
Could you give us an example?
“If you reach for a bottle at the table with the intention of passing it to another diner, who will then pour themselves a drink, your brain plans the action while considering the entire sequence of events, including the fact that the other person will use the bottle to fill their glass. In other words, the brain represents the chain of motor act, rather than the single act. The ability to measure how far ahead the brain can predict this gesture has dual value in Rehabilitation Medicine: the presence or absence of this predictive ability can provide insights into the patient’s chances of recovery and the effectiveness of rehabilitation exercises that utilize motor planning”.
Can the effects depend on which area of the brain was damaged by the stroke?
“Certainly. We have observed this in basic research utilizing functional magnetic resonance imaging combined with transcranial magnetic stimulation. Specific brain regions are involved in higher order planning. If the stroke has affected these areas, not only is the ability to execute a movement compromised, but the ability to plan it is also impaired. In patients where this ability is at least partially preserved, it can serve as a valuable resource to leverage”.
What other applications can your studies have in Rehabilitation Medicine?
“Our approach allows us to capture the individual kinematic fingerprint, which describes how each person moves in a style that is uniquely their own. This kinematic fingerprint also has predictive value; it can predict, for instance, how a patient with specific movement characteristics will perform a particular task or recover during rehabilitation. By utilizing machine learning models, we can assess the amount of prospective information carried by the patient’s movement and compare it with amount of information estimated, for example, six months later. This comparison allows us to verify whether the treatments are resulting in an increase in prospective information and, consequently, an improvement in the individual’s planning abilities”.
Does movement also play a role in how we communicate and interpret information?
“Yes, it does. We may not realize it, but at every moment, we interpret others’ body language to anticipate their next actions. This ability is fundamental to functional social interactions, which are inherently predictive. When this predictive capacity fails—because we can no longer anticipate the intentions of others—social interaction becomes reactive, resulting in abnormal, slowed, and less fluid exchanges. This is a critical factor to consider when working with patients who have neurological impairments, as their relational abilities are often compromised for this reason. If we aim to restore a patient’s human functioning, we must not overlook the social aspect”.



