Grant: Discovery Grants Program - Individual

The long-term goal of my research program is to understand how billions of neurons in the brain work together to produce sensation and behaviour. Specifically, in this research program, I will analyse neuronal activity in the motor cortex to better understand neuronal coding of motor behaviour. Recently, I have proposed the packet theory, stating that information in the brain is not processed continuously, but rather is divided in 50~500ms long burst of sequential spiking activity, which are called "packets" (Luczak et al. Nature Rev. Neurosci. 2015). Each packet can be conceived of as a discrete `message', with neurons active at the beginning of a packet providing general information (e.g. it is a face), while neurons active in latter phase encode more precise information (e.g. this is face of John). This theory was developed based on data from sensory cortex, and in this proposal I will expand packet theory to explain dynamically changing neuronal coding in the motor cortex. Motor areas are organized as motor maps, where stimulation of particular motor region evokes single muscles response in a corresponding body part (motor homunculus). However, subsequent studies have shown that longer stimulation can evoke more complex, multi-joint movements, like bringing food to the mouth. Moreover, cortical motor neurons were shown to also be involved in motor planning and even in sensory perception. These diverse findings have started a controversy: what exactly are motor maps representing? To reconcile these seemingly contradictory views on this fundamental problem of motor representation, I propose the motor packet theory. I hypothesize that the exact meaning of a single motor neuron activity depends on its timing within a motor packet. Specifically, neurons active at the beginning of a packet may activate single muscles to initiate a particular movement (e.g. upper arm lift to reach for an object). However, as a packet spreads to other cortical areas, it exchanges information about this reaching movement. As a result, neurons which initially represented only upper arm, later in the packet, they will also have information about subsequent forearm or hand movements, thus taking part in representing complex actions. To investigate motor packets, I propose 3 short-term objectives: (1) Record a large number of single neurons in the motor cortex in anesthetized rat, and to use optogenetic stimulations to investigate interactions between neurons within motor packets. (2) Study neuronal packets in awake rats during motor reaching task to directly relate motor packet activity to movement elements. And finally, (3) I will expand our Machine Learning algorithms to combine analyses of large neuronal populations with video analyses of fine motor behaviour. In summary, the novelty of this proposal is to explain function of motor map, not as a static map, but rather as a dynamically changing representation within a single neuronal packet.