Cognitive Control Signals for Neural Prosthetics
Recent development of neural prosthetics for assisting paralyzed patients has focused on decoding intended hand trajectories from motor cortical neurons and using this signal to control external devices. In this study, higher level signals related to the goals of movements were decoded from three monkeys and used to position cursors on a computer screen without the animals emitting any behavior. Their performance in this task improved over a period of weeks. Expected value signals related to
... id preference, the expected magnitude, or probability of reward were decoded simultaneously with the intended goal. For neural prosthetic applications, the goal signals can be used to operate computers, robots, and vehicles, whereas the expected value signals can be used to continuously monitor a paralyzed patient's preferences and motivation. Neural prosthetics are being designed to record brain activity related to intended movements from the sensorimotor pathway of paralyzed patients and to use these signals to control external devices. It would be valuable to determine what parameters can be decoded and used for prosthetic applications. Previous research has concentrated on extracting the online (real-time) intended trajectories of the hand by recording signals primarily, but not exclusively, from the motor cortex (1-5). This study explores whether a higher level signal of the goal of a movement can be decoded for prosthetic control. For example, a goal signal indicates the intention to reach for an apple, whereas a trajectory signal would indicate the intended direction of the hand movement during the reach. Another high-level signal of interest is expected value, which is used for making decisions. For instance, if an individual has two potential reach goals, an apple and an orange, and the subject prefers apples over oranges, there are signals in his or her brain that indicate this preference and will influence the decision to reach for the apple instead of the orange. We refer to this approach of extracting high-level signals as cognitive based; intended trajectories can also be considered among this group of signals, although at a lower level. Recordings were made at points along a major pathway for visually guided movement which begins in the extrastriate visual cortex (6) and passes through the parietal reach region (PRR) and area 5 to the dorsal premotor cortex (PMd) and then to the primary motor cortex (7, 8). Although PRR is specialized for reaching movements (9, 10), it represents the goals of the reach in visual coordinates (11). This visual representation indicates that the planned movement is at an abstract level and codes the intended goal rather than how to move the hand. Further emphasizing its cognitive nature, this goal signal is present when Fig. 5. Recovery of behavior. (Top) The escape bend of a fish before regeneration, after regeneration, and in an unlesioned fish. Images are shown every 2 msec after the start of the turn until the maximum of the bend. Bottom panels quantify the escape performance before and after cAMP-induced regeneration (mean ϩ SEM). Performance measures included (A) response latency, (B) peak angular velocity, (C) duration, and (D) maximum angle of the bend. These performance measures are shown for a group of five fish (five trials each) studied before (black bar, 3 days post-lesion) and after (black bar, 5 days post-lesion) cAMP treatment and for a control, untreated group (white bars) over the same time course (P Ͻ .0001 in every case for treated versus control). White bars on the right show performance measures from wild-type (w.t.) fish at 9 days.