Single cell and multiunit signals were recorded by a multichannel recording system (Plexon Inc, Texas) from 96 paralyne coated tungsten or platinum/iridium electrodes (impedance ≈ 300 kΩ) (Microprobe Inc. Maryland) implanted in the medial intraparietal area (MIP), a subdivision of the parietal reach region (PRR), and area 5 (1) of three rhesus monkeys trained to perform a memory reach task. One monkey (monkey S) also had 64 electrodes implanted in the dorsal premotor area (PMd) in a separate surgery. Each session consisted of a reach segment and a brain control segment. Trials in both segments were initiated in the same way: after the monkeys acquired a central red fixation point with the eyes and touched a central green target, a peripheral cue was flashed indicating the location of one out of four, five, six, or eight reach targets ( Figure 1a) (cue epoch). Reach targets were uniformly distributed around the central fixation point. As soon as the fixation point and central green target were acquired, hand and eye movements were restricted by a real time behavioural controller (LabVIEW, National Instruments). Eye position was monitored using a scleral search coil (CNC Engineering, monkeys S and O), or an infrared reflection system (ISCAN, monkey C) while hand position was monitored using an acoustic touch screen (ELO Touch). In order to successfully complete a trial, the monkeys were not allowed to move their eyes. In addition, the reaching hand had to be in contact with the centrally located green target at all times except after the GO signal which appeared during the reach segment of the session. After the offset of the cue, a delay of 1.5 ± 0.3 seconds ensued. During the reach segment, the green central target was extinguished after the memory period

The cortical local field potential (LFP) is a summation signal of excitatory and inhibitory dendritic potentials that has recently become of increasing interest. We report that LFP signals in the parietal reach region (PRR) of the posterior parietal cortex of macaque monkeys have temporal structure that varies with the type of planned or executed motor behavior. LFP signals from PRR provide better decode performance for reaches compared to saccades and have stronger coherency with simultaneously recorded spiking activity during the planning of reach movements than during saccade planning. LFP signals predict the animal's behavioral state (e.g., planning a reach or saccade) and the direction of the currently planned movement from single-trial information. This new evidence provides further support for a role of the parietal cortex in movement planning and the potential application of LFP signals for a brain-machine interface.

To perform grasping movements, the hand is shaped according to the form of the target object and the intended manipulation, which in turn depends on the context of the action. The anterior intraparietal cortex (AIP) is strongly involved in the sensorimotor transformation of grasping movements, but the extent to which it encodes context-specific information for hand grasping is unclear. To explore this issue, we recorded 571 single-units in AIP of two macaques during a delayed grasping task, in which animals were instructed by an external context cue (LED) to perform power or precision grips on a handle that was presented in various orientations. While 55% of the recorded neurons encoded the object orientation from the cue epoch on, the number of cells encoding the grip type increased from 25% during the cue epoch to 58% during movement execution. Furthermore, a classification of cells according to the time of their tuning onset revealed differences in the function and anatomical location of early-versus late-tuned cells. In a cue separation task, when the object was presented first, neurons representing power or precision grips were activated simultaneously until the actual grip type was instructed. In contrast, when the grasp type instruction was presented before the object, type information was only weakly represented in AIP, but was strongly encoded after the grasp target was revealed. We conclude that AIP encodes context specific hand grasping movements to perceived objects, but in the absence of a grasp target, the encoding of context information is weak.

Eye muscle fibers can be divided into two categories: nontwitch, multiply innervated muscle fibers (MIFs), and twitch, singly innervated muscle fibers (SIFs). We investigated the location of motoneurons supplying SIFs and MIFs in the six extraocular muscles of monkeys. Injections of retrograde tracers into eye muscles were placed either centrally, within the central SIF endplate zone; in an intermediate zone, outside the SIF endplate zone, targeting MIF endplates along the length of muscle fiber; or distally, into the myotendinous junction containing palisade endings. Central injections labeled large motoneurons within the abducens, trochlear or oculomotor nucleus, and smaller motoneurons lying mainly around the periphery of the motor nuclei. Intermediate injections labeled some large motoneurons within the motor nuclei but also labeled many peripheral motoneurons. Distal injections labeled small and medium-large peripheral neurons strongly and almost exclusively. The peripheral neurons labeled from the lateral rectus muscle surround the medial half of the abducens nucleus: from superior oblique, they form a cap over the dorsal trochlear nucleus; from inferior oblique and superior rectus, they are scattered bilaterally around the midline, between the oculomotor nucleus; from both medial and inferior rectus, they lie mainly in the C-group, on the dorsomedial border of oculomotor nucleus. In the medial rectus distal injections, a "C-group extension" extended up to the Edinger-Westphal nucleus and labeled dendrites within the supraoculomotor area. We conclude that large motoneurons within the motor nuclei innervate twitch fibers, whereas smaller motoneurons around the periphery innervate nontwitch, MIF fibers. The peripheral subgroups also contain medium-large neurons which may be associated with the palisade endings of global MIFs. The role of MIFs in eye movements is unclear, but the concept of a final common pathway must now be reconsidered.

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity.