The frontal eye field (FEF) is a key brain region to study visuomotor transformations because the primary input to FEF is visual in nature, whereas its output reflects the planning of behaviorally relevant saccadic eye movements. In this study, we used a memory-guided saccade task to temporally dissociate the visual epoch from the saccadic epoch through a delay epoch, and used the local field potential (LFP) along with simultaneously recorded spike data to study the visuomotor transformation process. We showed that visual latency of the LFP preceded spiking activity in the visual epoch, whereas spiking activity preceded LFP activity in the saccade epoch. We also found a spatially tuned elevation in gamma band activity (30-70 Hz), but not in the corresponding spiking activity, only during the delay epoch, whose activity predicted saccade reaction times and the cells' saccade tuning. In contrast, beta band activity (13-30 Hz) showed a nonspatially selective suppression during the saccade epoch. Taken together, these results suggest that motor plans leading to saccades may be generated internally within the FEF from local activity represented by gamma activity.T he process of generating a motor plan from visual information entails a visuomotor transformation. The frontal eye field (FEF) is one of the cortical regions that contributes to the visuomotor transformation process by participating in critical events such as target selection (1-3) and saccade preparation (4-6). In addition to FEF, other oculomotor areas such as the lateral intraparietal cortex (7), the supplementary eye fields (8), the superior colliculus (9), and the dorsolateral prefrontal cortex (10) also possess neurons with similar properties as FEF neurons. Thus, a central question that remains unresolved is to what extent do the response properties of FEF neurons represent a cause versus a consequence of computations occurring elsewhere.One approach to resolve this question of causation versus consequence, in the context of target selection, was the use of simultaneously recorded local field potentials (LFP) and spikesmaking use of the idea that the LFP represents synchronized input coming into a brain area, as opposed to spiking activity, which is thought to represent output (11)(12)(13)(14)(15). Using this approach, Monosov et al. showed that FEF received spatially nonselective input through LFP earlier than spikes in the early visual epoch; however, in the consequent target selection epoch, spiking activity of FEF neurons evolved spatial selectivity and actively discriminated between the behaviorally relevant and the irrelevant stimuli earlier than the LFP (1). Such a temporal relationship between LFP and spikes during target selection in FEF has also been studied by others using simultaneously recorded LFP and spikes, converging to the same evidence (5, 16). However, whereas these studies suggest a causal role for FEF in visual selection, the causal role of FEF in saccade preparation has not yet been reported. In this study, we asked whether sac...
Although the cerebellum has been implicated in simple reward-based learning recently, the role of complex spikes (CS) and simple spikes (SS), their interaction and their relationship to complex reinforcement learning and decision making is still unclear. Here we show that in a context where a non-human primate learned to make novel visuomotor associations, classifying CS responses based on their SS properties revealed distinct cell-type specific encoding of the probability of failure after the stimulus onset and the non-human primate’s decision. In a different context, CS from the same cerebellar area also responded in a cell-type and learning independent manner to the stimulus that signaled the beginning of the trial. Both types of CS signals were independent of changes in any motor kinematics and were unlikely to instruct the concurrent SS activity through an error based mechanism, suggesting the presence of context dependent, flexible, multiple independent channels of neural encoding by CS and SS. This diversity in neural information encoding in the mid-lateral cerebellum, depending on the context and learning state, is well suited to promote exploration and acquisition of wide range of cognitive behaviors that entail flexible stimulus-action-reward relationships but not necessarily motor learning.
What are the neural correlates that distinguish goal-directed (G) from non-goal-1 directed movements (nG)? We investigated this question in the monkey frontal eye field, 2 which is implicated in voluntary control of saccades. We found that only for G-saccades, the 3 variability in spike rate across trials decreased, the regularity of spike timings within trials 4 increased, the neural activity increased earlier from baseline and had a concurrent reduction 5 of LFP beta band power. 6 7 Most movements are goal directed while others, such as fidgets, may not be. However, the 8 neural mechanism that entail these different movements is poorly studied. The macaque frontal 9 eye fields (FEF) in particular has neurons that discharge before visually guided saccades, saccades 10 made in total darkness such as learned saccades or memory-guided saccades, but not before 11 spontaneous saccades in total darkness 1 . Here we discovered that when monkeys make saccades 12 that have no obvious goal in a lit environment, FEF movement and vis-mov neurons do, in fact, 13 discharge. We asked if these seeming non-goal-directed saccades made in the light were actually 14 made to a goal that we did not discern, or if there were differences in neural activities that 15 distinguished between non-goal-directed (nG) and goal directed (G) saccades. We studied two 16 characteristics of neural response not directly visible in the firing rate but which precede 17 movements: a decrease in neural response variability 2 and a decrease in local field potential beta 18 oscillatory activity 3,4 . Previous studies have shown that decreases in response variability are 19 correlated with attention 5 , preparation of visually guided saccades 2 , the onset of a visual stimulus 6 , 20 etc; and decreases in beta power have been correlated with motor preparation, and inhibitory 21 control 7,8 among other processes 9 . Nevertheless, despite these efforts, their roles in goal-directed 22We performed all our analyses on previously published datasets of frontal eye field neurons 3,10 . 130Please refer to that study for full details. We briefly describe the experimental procedures and methods here. 132Subjects: Two adult monkeys, J (male, Macaca radiata) and G (female, Macaca mulatta) were used for 133 the experiments and were cared for in accordance with the Committee for the Purpose of Control and
A hallmark of intelligent behavior is that we can separate intention from action. To understand the mechanism that gates the flow of information between motor planning and execution, we compared the activity of frontal eye field neurons with motor unit activity from neck muscles in the presence of an intervening delay period in which spatial information regarding the target was available to plan a response. Whereas spatially-specific delay period activity was present in the activity of frontal eye field neurons, it was absent in motor unit activity. Nonetheless, motor unit activity was correlated with the time it took to initiate saccades. Interestingly, we observed a heterogeneity of responses amongst motor units, such that only units with smaller amplitudes showed a clear modulation during the delay period. These small amplitude motor units also had higher spontaneous activity compared to the units which showed modulation only during the movement epoch. Taken together, our results suggest the activity of smaller motor units convey temporal information and explains how the delay period primes muscle activity leading to faster reaction times.
The conventional approach to understanding neural responses underlying complex computations is to study across‐trial averages of repeatedly performed computations from single neurons. When neurons perform complex computations, such as processing stimulus‐related information or movement planning, it has been repeatedly shown, through measures such as the Fano factor (FF), that neural variability across trials decreases. However, multiple neurons contribute to a common computation on a single trial, rather than a single neuron contributing to a computation across multiple trials. Therefore, at the level of a single trial, the concept of FF loses significance. Here, using a combination of simulations and empirical data, we show that changes in the spiking regularity on single trials produce changes in FF. Further, at the behavioural level, the reaction time of the animal was faster when the neural spiking regularity both within and across trials was lower. Taken together, our results provide further constraints on how changes in spiking statistics help neurons optimally encode visual and saccade‐related information across multiple timescales and its implication on behaviour.
The cerebellum has long been considered crucial for supervised motor learning 1 and its optimization 1-3 . However, new evidence has also implicated the cerebellum in reward 2 based learning 4-8 , executive function 9-12 , and frontal-like clinical deficits 13 . We recently 3 showed that the simple spikes of Purkinje cells (P-cells) in the mid-lateral cerebellar 4 hemisphere (Crus I and II) encode a reinforcement error signal when monkeys learn to 5 associate arbitrary symbols with hand movements 4 . However, it is unclear if the cerebellum 6 is necessary for any process beyond motor learning. To investigate if the mid-lateral 7 cerebellum is actually necessary for learning visuomotor associations, we reversibly 8 inactivated the mid-lateral cerebellum of two primates with muscimol while they learned to 9 associate arbitrary symbols with hand movements. Here we show that cerebellar inactivation 10 impaired the monkey's ability to learn new associations, although it had no effect on the 11 monkeys' performance on a task with overtrained symbols. A computational model 12 corroborates our results. Cerebellar inactivation increased the reaction time, but there were 13 no deficits in any motor kinematics such as the hand movement, licking or eye movement. 14 There was no loss of function when we inactivated a more anterior region of the cerebellum 15 that is implicated in motor control. We suggest that the mid-lateral cerebellum, which 16 provides a reinforcement learning error signal 4 , is necessary for visuomotor association 17 learning. Our results have implications for the involvement of cerebellum in cognitive 18 control, and add critical constraints to brain models of non-motor learning 14,15 . 19 20We trained two monkeys to associate arbitrary visual symbols with left and right hand 21 movements to earn an immediate liquid reward. On each recording session, the monkeys first 22
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