About BLAM

1. Motor learning and motor memory

Model-free vs Model-based
Motor learning is a blanket term that covers several component processes that include adaptation, use-dependent plasticity, and motor acuity (shifts in the speed-accuracy trade-off function and reductions in movement variability). We investigate these processes using a combination of psychophysical experiments in healthy subjects and patients, theoretical approaches, brain imaging, and non-invasive brain stimulation. In this way we hope to map behaviors onto their underlying computational processes and their neural substrates. A useful framework that we have recently promoted distinguishes between forward model-based and model-free learning, and their relative reliance on vector error and binary reward.

2. Motor skill learning

Diving Skill
Motor skill is a fuzzy and colloquial term that defies easy definition. Rather than getting bogged down in definitions we prefer to ask a few fundamental questions: Why does it take so long to become an expert musician or athlete? What it is that practice is making better? What is the role of verbal instruction and declarative/explicit processes in acquiring motor skills? There is a huge divide, for example, between motor learning experiments in the lab and motor skills in the outside world. At least two reasons for this divide can be conjectured. The first is that the seminal case of HM led to the unintended consequence of separating motor learning from the rest of cognitive neuroscience. This is very misleading because in our view motor skill requires just as much “cognition” as any other activity such as chess, mathematics or language. The second is that lab-based motor learning tasks have predominantly focused on adaptation or sequence learning. We think that tasks need to be more multifaceted, like sports, and tracked over longer periods. We are currently developing video games to accomplish this.

3. The influence of explicit knowledge , decision making, and abstraction on motor control, motor planning and motor learning

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We are currently investigating (1) how instruction and explicit knowledge of task structure influence movement kinematics and motor adaptation. (2) How humans plan trajectories in visual space and how this ability may be compromised in apraxia. (3). How decisions about context and perceptual uncertainty determine how an action is selected in the reaction time.

4. Recovery from brain injury

Robotic Stroke Recovery
Our work can be broken down into 4 main areas. (1) Tracking recovery after stroke using functional and structural imaging, non-invasive brain stimulation, psychophysics and clinical scales. (2) A mouse model of stroke to examine the interaction between spontaneous biological recovery, training protocols, and drugs such as SSRIs. (3) The development of interventions early after stroke that combine immersive gaming environments with 3D exoskeletal robotics and non-invasive brain stimulation. (4) Tracking recovery of multi-tasking using video-games in patients who recover and return home after TBI-induced coma.