Brain-computer interfaces (BCIs) can restore communication to people who have lost the ability to move or speak. To date, a major focus of BCI research has been on restoring gross motor skills, such as reaching and grasping 1-5 or point-and-click typing with a 2D computer cursor 6,7 . However, rapid sequences of highly dexterous behaviors, such as handwriting or touch typing, might enable faster communication rates. Here, we demonstrate an intracortical BCI that decodes attempted handwriting movements from neural activity in motor cortex and translates it to text in real-time, using a novel recurrent neural network decoding approach. With this BCI, our study

Neural activity in monkey motor cortex (M1) and dorsal premotor cortex (PMd) can reflect a chosen movement well before that movement begins. The pattern of neural activity then changes profoundly just before movement onset. We considered the prediction, derived from formal considerations, that the transition from preparation to movement might be accompanied by a large overall change in the neural state that reflects when movement is made rather than which movement is made. Specifically, we examined “components” of the population response: time-varying patterns of activity from which each neuron’s response is approximately composed. Amid the response complexity of individual M1 and PMd neurons, we identified robust response components that were “condition-invariant”: their magnitude and time course were nearly identical regardless of reach direction or path. These condition-invariant response components occupied dimensions orthogonal to those occupied by the “tuned” response components. The largest condition-invariant component was much larger than any of the tuned components; i.e., it explained more of the structure in individual-neuron responses. This condition-invariant response component underwent a rapid change before movement onset. The timing of that change predicted most of the trial-by-trial variance in reaction time. Thus, although individual M1 and PMd neurons essentially always reflected which movement was made, the largest component of the population response reflected movement timing rather than movement type.

Recent advances in multi-electrode array technology have made it possible to monitor large neuronal ensembles at cellular resolution. In humans, however, current approaches either restrict recordings to only a few neurons per penetrating electrode or combine the signals of thousands of neurons in local field potential (LFP) recordings. Here, we describe a new probe variant and set of techniques which enable simultaneous recording from over 200 well-isolated cortical single units in human participants during intraoperative neurosurgical procedures using silicon Neuropixels probes. We characterized a diversity of extracellular waveforms with eight separable single unit classes, with differing firing rates, positions along the length of the linear electrode array, spatial spread of the waveform, and modulation by LFP events such as interictal discharges and burst suppression. While some additional challenges remain in creating a turn-key recording system, high-density silicon arrays provide a path for studying humanspecific cognitive processes and their dysfunction at unprecedented spatiotemporal resolution.Major technological advances in the past decade have led to a revolution in the neurosciences.Many research programs now routinely rely on the analysis of single-neuron action potentials from hundreds and even thousands of neurons, which provide a rich understanding of the coordinated activity of large neuronal ensembles that underlie sensory, motor, and cognitive operations [1][2][3][4] . While these developments have been most pronounced in animal models, there have been parallel, albeit slower, advances in the ability to record from single neurons in humans. Single-unit recordings in humans have been performed since the mid-1950s 5-8 , and were foundational in understanding the role of neural circuits in neurologic disease. For example, such techniques helped to establish an understanding of the relationship between .