Balancing subject learning and decoder adaptation is central to increasing brain machine interface (BMI) performance. We addressed these complementary aspects in two studies: (1) a learning study, in which mice modulated “beta” band activity to control a 1D auditory cursor, and (2) an adaptive decoding study, in which a simple recurrent artificial neural network (RNN) decoded intended saccade targets of monkeys. In the learning study, three mice successfully increased beta band power following trial initiations, and specifically increased beta burst durations from 157 ms to 182 ms, likely contributing to performance. Though the task did not explicitly require specific movements, all three mice appeared to modulate beta activity via active motor control and had consistent vibrissal motor cortex multiunit activity and local field potential relationships with contralateral whisker pad electromyograms. The increased burst durations may therefore by a direct result of increased motor activity. These findings suggest that only a subset of beta rhythm phenomenology can be volitionally modulated (e.g. the tonic “hold” beta), therefore limiting the possible set of successful beta neuromodulation strategies. In the adaptive decoding study, RNNs decoded delay period activity in oculomotor and working memory regions while monkeys performed a delayed saccade task. Adaptive decoding sessions began with brain-controlled trials using pre-trained RNN models, in contrast to static decoding sessions in which 300-500 initial eye-controlled training trials were performed. Closed loop RNN decoding performance was lower than predicted by offline simulations. More consistent delay period activity and saccade paths across trials were associated with higher decoding performance. Despite the advantage of consistency, one monkey’s delay period activity patterns changed over the first week of adaptive decoding, and the other monkey’s saccades were more erratic during adaptive decoding than during static decoding sessions. It is possible that the altered session paradigm eliminating eye-controlled training trials led to either frustration or exploratory learning, causing the neural and behavioral changes. Considering neural control and decoder adaptation of BMIs in these studies, future work should improve the “two-learner” subject-decoder system by better modeling the interaction between underlying brain states (and possibly their modulation) and the neural signatures representing desired outcomes.

<p dir="ltr">Localizing movements in the external space is crucial for animals to navigate safely, find food, avoid predators, and interact with their surroundings. Efficient localization during body movements requires the brain to distinguish between externally generated movements and self-generated ones. This involves integrating external stimulation with a continuous estimate of one's body position, to isolate external motion by suppressing sensations arising from self-motion.</p><p dir="ltr">To explore the neural mechanisms underlying object localization during active touch, we focused on the mouse superior colliculus (SC), which harbors multiple egocentric maps of sensorimotor space. Our studies revealed that SC neurons exhibit a rapidly adapting tactile response during externally generated touch. The response is significantly attenuated during self-generated touch, thus enhancing the ability to distinguish between external and self-induced tactile stimuli. Additionally, the direction of external motion is precisely encoded in the firing rates of these tactile-responsive neurons, indicating a specialized localization mechanism within the SC.</p><p dir="ltr">In scenarios devoid of external stimuli, SC neural activity accurately reflects the kinematics of self-motion, such as whisker position and locomotion speed, capturing past, present, and future body positions. Half of the neurons that encode self-motion also respond to external tactile stimuli. This dual functionality suggests that these neurons not only track self-motion but also engage in the processing of external tactile information. The magnitude of the external tactile response in these neurons is modulated by the state of self-motion upon touch. These results suggest that SC neurons integrate internal estimates of body movements with external tactile inputs to compute the egocentric distance of objects.</p>