Invasive brain-machine interfaces (BMIs) have the potential to restore lost motor function due to paralysis. However, successful operation of BMIs depends on the extent to which neural activity can be volitionally modulated. Operant conditioning of single cortical neurons induces the rapid acquisition of arbitrary associations between machines and neural activity. In this thesis, I aimed at exploring intrinsic and extrinsic factors that influence single neuron behavior in a BMI, guided by operant conditioning in a rat model. Extracellularly recorded single neuron activity, from layer V of the motor cortex, was conditioned in BMI tasks designed to up-regulate instantaneous or smoothed firing rates. In the first two studies (Chapters 3 4), the neuron type was investigated as an intrinsic factor. Differences were found in the neuron-type-specific utility (defined as the degree of activity up-regulation), and in the neuron-type-specific responses in the activity leading to a reward. Next, I investigated the type of BMI task as an extrinsic factor (Chapter 5). Two tasks were compared:​ (i) a threshold-based task, in which firing rates surpassed a threshold, and (ii) a graded-activation task, where firing rates were maintained within a narrow window of activation. Single neuron activity was selectively up-regulated in the threshold-based task, while the graded activation task involved activation of neurons in the local network. This thesis demonstrates that intrinsic and extrinsic factors have an influence in the behavior of single neurons, and that these factors might inform the design of BMIs.