Prior Knowledge of Target Direction and Intended Movement Selection Improves Indirect Reaching Movement Decoding
نویسندگان
چکیده
Objective. Previous studies have demonstrated that target direction information presented by the dorsal premotor cortex (PMd) during movement planning could be incorporated into neural decoder for achieving better decoding performance. It is still unknown whether the neural decoder combined with only target direction could work in more complex tasks where obstacles impeded direct reaching paths. Methods. In this study, spike activities were collected from the PMd of two monkeys when performing a delayed obstacle-avoidance task. We examined how target direction and intended movement selection were encoded in neuron population activities of the PMd during movement planning. The decoding performances of movement trajectory were compared for three neural decoders with no prior knowledge, or only target direction, or both target direction and intended movement selection integrated into a mixture of trajectory model (MTM). Results. We found that not only target direction but also intended movement selection was presented in neural activities of the PMd during movement planning. It was further confirmed by quantitative analysis. Combined with prior knowledge, the trajectory decoder achieved the best performance among three decoders. Conclusion. Recruiting prior knowledge about target direction and intended movement selection extracted from the PMd could enhance the decoding performance of hand trajectory in indirect reaching movement.
منابع مشابه
Dynamic encoding of movement direction in motor cortical neurons.
When we perform a skilled movement such as reaching for an object, we can make use of prior information, for example about the location of the object in space. This helps us to prepare the movement, and we gain improved accuracy and speed during movement execution. Here, we investigate how prior information affects the motor cortical representation of movements during preparation and execution....
متن کاملCoupling time decoding and trajectory decoding using a target-included model in the motor cortex
Significant progress has been made within the last decade in motor cortical decoding that predicts movement behaviors from population neuronal activity in the motor cortex. A majority of these decoding methods have focused on estimating a subject's hand trajectory in a continuous movement. We recently proposed a time identification decoding approach and showed that if a stereotyped movement is ...
متن کاملDissociating visual and motor directional selectivity using visuomotor adaptation.
Directional selectivity during visually guided hand movements is a fundamental characteristic of neural populations in multiple motor areas of the primate brain. In the current study, we assessed how directional selectivity changes when reaching movements are dissociated from their visual feedback by rotating the visual field. We recorded simultaneous movement kinematics and fMRI activity while...
متن کاملEarly visuomotor representations revealed from evoked local field potentials in motor and premotor cortical areas.
Local field potentials (LFPs) recorded from primary motor cortex (MI) have been shown to be tuned to the direction of visually guided reaching movements, but MI LFPs have not been shown to be tuned to the direction of an upcoming movement during the delay period that precedes movement in an instructed-delay reaching task. Also, LFPs in dorsal premotor cortex (PMd) have not been investigated in ...
متن کاملA Real-time Brain-machine Interface Combining Plan and Peri-movement Activities
Brain-machine interfaces (BMI) map relevant neural activities to the intended movement, known as ‘decoding’. Information about various states of a movement are encoded in the motor areas. These include the kinematic states such as velocity and higher level states such as the intended target. Realtime BMIs have mostly focused on decoding individually either the goal of a movement or its kinemati...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 2017 شماره
صفحات -
تاریخ انتشار 2017