Search

The lateral hypothalamus (LH), which plays a role in homeostatic functions such as appetite regulation, is also linked to arousal and motivational behavior. However, little is known about how these components are encoded in the LH. Thus cynomolgus monkeys were conditioned with two distinct contexts, i.e., an appetitive context with available rewards and an aversive context with predicted air puffs. Different LH neuron groups encoded different degrees of expectation, predictability, and risks of rewards in a specific manner. A nearly equal number of one-third of the recorded LH neurons showed a positive or negative correlation between their response to visual conditioned stimuli (CS) that predicted the probabilistic delivery of rewards (0%, 50%, and 100%) and the associative values. For another one-third of recorded neurons, a nearly equal number showed a positive or negative correlation between their responses to rewards [appetitive unconditioned stimulus (US)] and reward predictability. Some neurons exhibited their highest or lowest trace-period responses in the 50% reward trials. These response modulations were represented independently and overlaid on a consistent excitatory or inhibitory response across the conditioning events. LH neurons also showed consistent responses in the aversive context. However, the responses to aversive conditioning events depending on the air puff value and predictability were less common. The multifaceted modulation of consistent activity related to outcome predictions may reflect motivational and arousal signals. Furthermore, it may underlie the role the LH plays in the integration and relay of signals to cortices for adaptive and goal-directed physiological and behavioral responses to environmental changes. NEW & NOTEWORTHY The lateral hypothalamus (LH) is implicated in motivational and arousal behavior; however, the detailed information carried by single LH neurons remains unclear. We demonstrate that primate LH neurons encode multiple combinations of signals concerning different degrees of expectation, appreciation, and uncertainty of rewards in consistent responses across conditioning events and between different contexts. This multifaceted modulation of activity may underlie the role of the LH as a critical node integrating motivational signals with arousal signals.

Expectation of reward motivates our behaviors and influences our decisions. Indeed, neuronal activity in many brain areas is modulated by expected reward. However, it is still unclear where and how the reward-dependent modulation of neuronal activity occurs and how the reward-modulated signal is transformed into motor outputs. Recent studies suggest an important role of the basal ganglia. Sensorimotor/cognitive activities of neurons in the basal ganglia are strongly modulated by expected reward. Through their abundant outputs to the brain stem motor areas and the thalamocortical circuits, the basal ganglia appear capable of producing body movements based on expected reward. A good behavioral measure to test this hypothesis is saccadic eye movement because its brain stem mechanism has been extensively studied. Studies from our laboratory suggest that the basal ganglia play a key role in guiding the gaze to the location where reward is available. Neurons in the caudate nucleus and the substantia nigra pars reticulata are extremely sensitive to the positional difference in expected reward, which leads to a bias in excitability between the superior colliculi such that the saccade to the to-be-rewarded position occurs more quickly. It is suggested that the reward modulation occurs in the caudate where cortical inputs carrying spatial signals and dopaminergic inputs carrying reward-related signals are integrated. These data support a specific form of reinforcement learning theories, but also suggest further refinement of the theory.

To examine the role of the medial frontal cortex, supplementary motor area (SMA), and pre-SMA in the acquisition and control of sequential movements, we locally injected muscimol into 43 sites in the medial frontal cortex while monkeys (n = 2) performed a sequential button-press task. In this task, the monkey had to press two of 16 (4 × 4 matrix) buttons illuminated simultaneously in a predetermined order. A total of five pairs were presented in a fixed order for completion of a trial. To clarify the differential contribution of the medial frontal cortex for new acquisition and control of sequential movements, we used novel and learned sequences (that had been learned after extensive practice). We found that the number of errors increased for novel sequences, but not for learned sequences, after pre-SMA inactivations. A similar, but insignificant, trend was observed after SMA injections. The reaction time of button presses for both novel and learned sequences was prolonged by inactivations of both SMA and pre-SMA, with a trend for the effect to be larger for SMA inactivations. These findings suggest that the medial frontal cortex, especially pre-SMA, is related to the acquisition, rather than the storage or execution, of the correct order of button presses.

It has been suggested on the basis of previous studies involving functional MRI (fMRI) and single-neuron recording that neurons of the supplementary eye field (SEF) and anterior cingulate cortex (ACC) monitor conflict. To test this idea, we carried out microelectrode recording in monkeys performing a color-conditional eye movement task in which red and green cues instructed leftward and rightward saccades, respectively. In a variant inducing conflict by spatial incompatibility, the cue was presented either at the location of the target (no conflict) or opposite the location of the target (conflict). In a variant inducing conflict by reversal, the foveal cue either remained one color (no conflict) or reversed color after 100 ms (conflict), with the monkey required to follow the instruction conveyed by the second color. In both tasks, conflict was evident in behavioral measures (reduced percent correct and slowed reaction time) and in physiological measures (reduced strength of directional activity among direction-selective neurons). In the SEF, there was a tendency for neurons to fire more strongly on trials involving conflict, but this effect took the form of modulation of task-related activity among direction-selective neurons, not of a pure conflict-monitoring signal. In the ACC, there was no conflict-related enhancement. These results are incompatible with the idea that the SEF and ACC contain populations of neurons specialized for monitoring conflict.

Area V3A is an extrastriate visual area that provides a major input to parietal cortex. To identify the sensory, saccade-related, and cognitive signals carried by V3A neurons, we recorded from single units in alert monkeys during performance of fixation and memory guided saccade tasks. We found that visual responses to stationary stimuli in area V3A were affected by the behavioral relevance of the stimulus. The amplitude of the visual response differed between the memory-guided saccade task, in which the monkey had to use the information provided by the stimulus to guide its behavior, and the fixation task. For 18% (29/163) of V3A neurons, the response was significantly enhanced in the memory-guided saccade task as compared with that in the fixation task. For 8% (13/163) of V3A neurons, the amplitude of response in the memory-guided saccade task was significantly suppressed. We also observed task-related modulation of activity prior to stimulus onset. Among the V3A neurons (37/163) that showed significant differences between tasks in prestimulus activity, the majority (89%; 33/37) showed greater prestimulus activity in the memory-guided saccade task. Task-related increases in prestimulus activity in the memory-guided saccade task were not always matched by increases in the sensory response, indicating that visual responses and prestimulus activity can be modulated independently. Activity in the memory period was suppressed compared with prestimulus activity for 83% (49/59) of the V3A neurons that showed a significant difference in activity (59/197) between these two epochs. For some neurons, memory-period activity dropped even below the baseline level in the fixation task, indicating that there may be an active suppression mechanism. Many V3A neurons (75%, 148/197) also had activity in the saccade epoch. This activity was most prominent immediately after the saccade. Postsaccadic activity was observed even when testing was carried out in total darkness, indicating that this activity reflects, at least in part, extraretinal signals and is not simply a response to visual reafference. These results indicate that several kinds of signals are carried by single neurons in extrastriate area V3A. Moreover, activity in V3A is subject to modulation by extraretinal factors, including attention, anticipation, memory, and saccadic eye movements.

Nakamura, Kae, Katsuyuki Sakai, and Okihide Hikosaka. Neuronal activity in medial frontal cortex during learning of sequential procedures. J. Neurophysiol. 80: 2671–2687, 1998. To study the role of medial frontal cortex in learning and memory of sequential procedures, we examined neuronal activity of the presupplementary motor area (pre-SMA) and supplementary motor area (SMA) while monkeys ( n = 2) performed a sequential button press task, “2 × 5 task.” In this paradigm, 2 of 16 (4 × 4 matrix) light-emitting diode buttons (called “set”) were illuminated simultaneously and the monkey had to press them in a predetermined order. A total of five sets (called “hyperset”) was presented in a fixed order for completion of a trial. We examined the neuronal activity of each cell using two kinds of hypersets: new hypersets that the monkey experienced for the first time for which he had to find the correct orders of button presses by trial-and-error and learned hypersets that the monkey had learned with extensive practice ( n = 16 and 10 for each monkey). To investigate whether cells in medial frontal cortex are involved in the acquisition of new sequences or execution of well-learned procedures, we examined three to five new hypersets and three to five learned hypersets for each cell. Among 345 task-related cells, we found 78 cells that were more active during performance of new hypersets than learned hypersets (new-preferring cells) and 18 cells that were more active for learned hypersets (learned-preferring cells). Among new-preferring cells, 33 cells showed a learning-dependent decrease of cell activity: their activity was highest at the beginning of learning and decreased as the animal acquired the correct response for each set with increasing reliability. In contrast, 11 learned-preferring cells showed a learning-dependent increase of neuronal activity. We found a difference in the anatomic distribution of new-preferring cells. The proportion of new-preferring cells was greater in the rostral part of the medial frontal cortex, corresponding to the pre-SMA, than the posterior part, the SMA. There was some trend that learned-preferring cells were more abundant in the SMA. These results suggest that the pre-SMA, rather than SMA, is more involved in the acquisition of new sequential procedures.