Neurons In Lateral Prefrontal Cortex Research Articles

Prefrontal cortex neuronal ensembles dynamically encode task features during associative memory and virtual navigation.

Neuronal populations expand their information-encoding capacity using mixed selective neurons. This is particularly prominent in association areas such as the lateral prefrontal cortex (LPFC), which integrate information from multiple sensory systems. However, during conditions that approximate natural behaviors, it is unclear how LPFC neuronal ensembles process space- and time-varying information about task features. Here, we show that, during a virtual reality task with naturalistic elements that requires associative memory, individual neurons and neuronal ensembles in the primate LPFC dynamically mix unconstrained features of the task, such as eye movements, with task-related visual features. Neurons in dorsal regions show more selectivity for space and eye movements, while ventral regions show more selectivity for visual features, representing them in a separate subspace. In summary, LPFC neurons exhibit dynamic and mixed selectivity for unconstrained and constrained task elements, and neural ensembles can separate task features in different subspaces.

P.133 Neurons in the lateral prefrontal cortex encode task features during virtual navigation

Background: The lateral prefrontal cortex (LPFC) is uniquely found in primates and has been associated with contextual learning. This function is thought to be subserved by neurons that are tuned to abstract concepts and the combination of those concepts. LPFC neuron tuning remains to be fully investigated in naturalistic conditions. Methods: Two macaques were trained to perform a context-colour association task while using a joystick to navigate in an X-shaped maze. They were implanted with two 96-channel microelectrode arrays, targeting the LPFC. Mean firing rates were computed and multivariate linear regressions were used to determine tuning. Results: LPFC neurons were tuned to context (12.4%), color position (6.2%), target side (17.2%), and were selective to more than one feature (21.2%). LPFC neurons acquired tuning to task features in an ordered manner, starting with context (130.1±27.4ms), followed by the colour position (296.2±21.4ms) and then target side (493.3±19.3ms). Furthermore, most neurons (54%) changed their tuning over time. Conclusions: We demonstrate that single neurons can encode relevant features embedded in a naturalistic virtual environment. Our results support previous observations that LPFC neurons combine individual features and suggest that these features are also combined temporally. These findings contribute towards understanding the LPFC and have potential practical implications.

Dopamine receptor activation regulates reward expectancy signals during cognitive control in primate prefrontal neurons

Dopamine neurons respond to reward-predicting cues but also modulate information processing in the prefrontal cortex essential for cognitive control. Whether dopamine controls reward expectation signals in prefrontal cortex that motivate cognitive control is unknown. We trained two male macaques on a working memory task while varying the reward size earned for successful task completion. We recorded neurons in lateral prefrontal cortex while simultaneously stimulating dopamine D1 receptor (D1R) or D2 receptor (D2R) families using micro-iontophoresis. We show that many neurons predict reward size throughout the trial. D1R stimulation showed mixed effects following reward cues but decreased reward expectancy coding during the memory delay. By contrast, D2R stimulation increased reward expectancy coding in multiple task periods, including cueing and memory periods. Stimulation of either dopamine receptors increased the neurons’ selective responses to reward size upon reward delivery. The differential modulation of reward expectancy by dopamine receptors suggests that dopamine regulates reward expectancy necessary for successful cognitive control.

Ensembles code for associative learning in the primate lateral prefrontal cortex

The lateral prefrontal cortex (LPFC) of primates is thought to play a role in associative learning. However, it remains unclear how LPFC neuronal ensembles dynamically encode and store memories for arbitrary stimulus-response associations. We recorded the activity of neurons in LPFC of two macaques during an associative learning task using multielectrode arrays. During task trials, the color of a symbolic cue indicated the location of one of two possible targets for a saccade. During a trial block, multiple randomly chosen associations were learned by the subjects. A state-space analysis indicated that LPFC neuronal ensembles rapidly learn new stimulus-response associations mirroring the animals' learning. Multiple associations acquired during training are stored in a neuronal subspace and can be retrieved hours after learning. Finally,knowledge of old associations facilitates learning new, similar associations. These results indicate that neuronal ensembles in the primate LPFC provide a flexible and dynamic substrate for associative learning.

Stable Working Memory and Perceptual Representations in Macaque Lateral Prefrontal Cortex during Naturalistic Vision.

Primates use perceptual and mnemonic visuospatial representations to perform everyday functions. Neurons in the lateral prefrontal cortex (LPFC) have been shown to encode both of these representations during tasks where eye movements are strictly controlled and visual stimuli are reduced in complexity. This raises the question of whether perceptual and mnemonic representations encoded by LPFC neurons remain robust during naturalistic vision-in the presence of a rich visual scenery and during eye movements. Here we investigate this issue by training macaque monkeys to perform working memory and perception tasks in a visually complex virtual environment that requires navigation using a joystick and allows for free visual exploration of the scene. We recorded the activity of 3950 neurons in the LPFC (areas 8a and 9/46) of two male rhesus macaques using multielectrode arrays, and measured eye movements using video tracking. We found that navigation trajectories to target locations and eye movement behavior differed between the perception and working memory tasks, suggesting that animals used different behavioral strategies. Single neurons were tuned to target location during cue encoding and working memory delay, and neural ensemble activity was predictive of the behavior of the animals. Neural decoding of the target location was stable throughout the working memory delay epoch. However, neural representations of similar target locations differed between the working memory and perception tasks. These findings indicate that during naturalistic vision, LPFC neurons maintain robust and distinct neural codes for mnemonic and perceptual visuospatial representations.SIGNIFICANCE STATEMENT We show that lateral prefrontal cortex neurons encode working memory and perceptual representations during a naturalistic task set in a virtual environment. We show that despite eye movement and complex visual input, neurons maintain robust working memory representations of space, which are distinct from neuronal representations for perception. We further provide novel insight into the use of virtual environments to construct behavioral tasks for electrophysiological experiments.

Chemogenetic inactivation reveals the inhibitory control function of the prefronto-striatal pathway in the macaque brain

The lateral prefrontal cortex (LPFC) has a strong monosynaptic connection with the caudate nucleus (CdN) of the striatum. Previous human MRI studies have suggested that this LPFC-CdN pathway plays an important role in inhibitory control and working memory. We aimed to validate the function of this pathway at a causal level by pathway-selective manipulation of neural activity in non-human primates. To this end, we trained macaque monkeys on a delayed oculomotor response task with reward asymmetry and expressed an inhibitory type of chemogenetic receptors selectively to LPFC neurons that project to the CdN. Ligand administration reduced the inhibitory control of impulsive behavior, as well as the task-related neuronal responses observed in the local field potentials from the LPFC and CdN. These results show that we successfully suppressed pathway-selective neural activity in the macaque brain, and the resulting behavioral changes suggest that the LPFC-CdN pathway is involved in inhibitory control.

Neurons in primate prefrontal cortex signal valuable social information during natural viewing.

Information about social partners is innately valuable to primates. Decisions about which sources of information to consume are highly naturalistic but also complex and place unusually strong demands on the brain's decision network. In particular, both the orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) play key roles in decision making and social behaviour, suggesting a likely role in social information-seeking as well. To test this idea, we developed a ‘channel surfing' task in which monkeys were shown a series of 5 s video clips of conspecifics engaged in natural behaviours at a field site. Videos were annotated frame-by-frame using an ethogram of species-typical behaviours, an important source of social information. Between each clip, monkeys were presented with a choice between targets that determined which clip would be seen next. Monkeys' gaze during playback indicated differential engagement depending on what behaviours were presented. Neurons in both OFC and LPFC responded to choice targets and to video, and discriminated a subset of the behaviours in the ethogram during video viewing. These findings suggest that both OFC and LPFC are engaged in processing social information that is used to guide dynamic information-seeking decisions.This article is part of the theme issue ‘Existence and prevalence of economic behaviours among non-human primates’.

The Effects of Methylphenidate (Ritalin) on the Neurophysiology of the Monkey Caudal Prefrontal Cortex

Methylphenidate (MPH), commonly known as Ritalin, is the most widely prescribed drug worldwide to treat patients with attention deficit disorders. Although MPH is thought to modulate catecholamine neurotransmission in the brain, it remains unclear how these neurochemical effects influence neuronal activity and lead to attentional enhancements. Studies in rodents overwhelmingly point to the lateral prefrontal cortex (LPFC) as a main site of action of MPH. To understand the mechanism of action of MPH in a primate brain, we recorded the responses of neuronal populations using chronic multielectrode arrays implanted in the caudal LPFC of two macaque monkeys while the animals performed an attention task (N = 2811 neuronal recordings). Over different recording sessions (N = 55), we orally administered either various doses of MPH or a placebo to the animals. Behavioral analyses revealed positive effects of MPH on task performance at specific doses. However, analyses of individual neurons activity, noise correlations, and neuronal ensemble activity using machine learning algorithms revealed no effects of MPH. Our results suggest that the positive behavioral effects of MPH observed in primates (including humans) may not be mediated by changes in the activity of caudal LPFC neurons. MPH may enhance cognitive performance by modulating neuronal activity in other regions of the attentional network in the primate brain.

Parallel and functionally segregated processing of task phase and conscious content in the prefrontal cortex

The role of lateral prefrontal cortex (LPFC) in mediating conscious perception has been recently questioned due to potential confounds resulting from the parallel operation of task related processes. We have previously demonstrated encoding of contents of visual consciousness in LPFC neurons during a no-report task involving perceptual suppression. Here, we report a separate LPFC population that exhibits task-phase related activity during the same task. The activity profile of these neurons could be captured as canonical response patterns (CRPs), with their peak amplitudes sequentially distributed across different task phases. Perceptually suppressed visual input had a negligible impact on sequential firing and functional connectivity structure. Importantly, task-phase related neurons were functionally segregated from the neuronal population, which encoded conscious perception. These results suggest that neurons exhibiting task-phase related activity operate in the LPFC concurrently with, but segregated from neurons representing conscious content during a no-report task involving perceptual suppression.

Intrinsic neuronal dynamics predict distinct functional roles during working memory

Working memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF), and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We find that cells with short timescales carry memory information relatively early during memory encoding in lPFC; whereas long-timescale cells play a greater role later during processing, dominating coding in the delay period. We also observe a link between functional connectivity at rest and the intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predict complex neuronal dynamics during WM, ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.

Neuronal Encoding in Prefrontal Cortex during Hierarchical Reinforcement Learning.

Reinforcement learning models have proven highly effective for understanding learning in both artificial and biological systems. However, these models have difficulty in scaling up to the complexity of real-life environments. One solution is to incorporate the hierarchical structure of behavior. In hierarchical reinforcement learning, primitive actions are chunked together into more temporally abstract actions, called "options," that are reinforced by attaining a subgoal. These subgoals are capable of generating pseudoreward prediction errors, which are distinct from reward prediction errors that are associated with the final goal of the behavior. Studies in humans have shown that pseudoreward prediction errors positively correlate with activation of ACC. To determine how pseudoreward prediction errors are encoded at the single neuron level, we trained two animals to perform a primate version of the task used to generate these errors in humans. We recorded the electrical activity of neurons in ACC during performance of this task, as well as neurons in lateral prefrontal cortex and OFC. We found that the firing rate of a small population of neurons encoded pseudoreward prediction errors, and these neurons were restricted to ACC. Our results provide support for the idea that ACC may play an important role in encoding subgoals and pseudoreward prediction errors to support hierarchical reinforcement learning. One caveat is that neurons encoding pseudoreward prediction errors were relatively few in number, especially in comparison to neurons that encoded information about the main goal of the task.

Spatiotemporal encoding of search strategies by prefrontal neurons

Working memory is capacity-limited. In everyday life we rarely notice this limitation, in part because we develop behavioral strategies that help mitigate the capacity limitation. How behavioral strategies are mediated at the neural level is unclear, but a likely locus is lateral prefrontal cortex (LPFC). Neurons in LPFC play a prominent role in working memory and have been shown to encode behavioral strategies. To examine the role of LPFC in overcoming working-memory limitations, we recorded the activity of LPFC neurons in animals trained to perform a serial self-ordered search task. This task measured the ability to prospectively plan the selection of unchosen spatial search targets while retrospectively tracking which targets were previously visited. We found that individual LPFC neurons encoded the spatial location of the current search target but also encoded the spatial location of targets up to several steps away in the search sequence. Neurons were more likely to encode prospective than retrospective targets. When subjects used a behavioral strategy of stereotyped target selection, mitigating the working-memory requirements of the task, not only did the number of selection errors decrease but there was a significant reduction in the strength of spatial encoding in LFPC. These results show that LPFC neurons have spatiotemporal mnemonic fields, in that their firing rates are modulated both by the spatial location of future selection behaviors and the temporal organization of that behavior. Furthermore, the strength of this tuning can be dynamically modulated by the demands of the task.

Attentional Changes in Either Criterion or Sensitivity Are Associated with Robust Modulations in Lateral Prefrontal Cortex

Visual attention is associated with neuronal changes across the brain, and these widespread signals are generally assumed to underlie a unitary mechanism of attention. However, using signal detection theory, attention-related effects on performance can be partitioned into changes in either the subject's criterion or sensitivity. Neuronal modulations associated with only sensitivity changes were previously observed in visual cortex, raising questions about which structures mediate attention-related changes in criterion and whether individual neurons are involved in multiple components of attention. Here, we recorded from monkey lateral prefrontal cortex (LPFC) and found that, in contrast to visual cortex, neurons in LPFC changed their firing rates, pairwise correlation, and Fano factor when subjects changed either their criterion or their sensitivity. These results indicate that attention-related neuronal modulations in separate brain regions are not a monolithic signal and instead can be linked to distinct behavioral changes.

Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex

The primate lateral prefrontal cortex (LPFC) encodes visual stimulus features while they are perceived and while they are maintained in working memory. However, it remains unclear whether perceived and memorized features are encoded by the same or different neurons and population activity patterns. Here we record LPFC neuronal activity while monkeys perceive the motion direction of a stimulus that remains visually available, or memorize the direction if the stimulus disappears. We find neurons with a wide variety of combinations of coding strength for perceived and memorized directions: some neurons encode both to similar degrees while others preferentially or exclusively encode either one. Reading out the combined activity of all neurons, a machine-learning algorithm reliably decode the motion direction and determine whether it is perceived or memorized. Our results indicate that a functionally diverse population of LPFC neurons provides a substrate for discriminating between perceptual and mnemonic representations of visual features.

Strength and Diversity of Inhibitory Signaling Differentiates Primate Anterior Cingulate from Lateral Prefrontal Cortex.

The lateral prefrontal cortex (LPFC) and anterior cingulate cortex (ACC) of the primate play distinctive roles in the mediation of complex cognitive tasks. Compared with the LPFC, integration of information by the ACC can span longer timescales and requires stronger engagement of inhibitory processes. Here, we reveal the synaptic mechanism likely to underlie these differences using in vitro patch-clamp recordings of synaptic events and multiscale imaging of synaptic markers in rhesus monkeys. Although excitatory synaptic signaling does not differ, the level of synaptic inhibition is much higher in ACC than LPFC layer 3 pyramidal neurons, with a significantly higher frequency (∼6×) and longer duration of inhibitory synaptic currents. The number of inhibitory synapses and the ratio of cholecystokinin to parvalbumin-positive inhibitory inputs are also significantly higher in ACC compared with LPFC neurons. Therefore, inhibition is functionally and structurally more robust and diverse in ACC than in LPFC, resulting in a lower excitatory: inhibitory ratio and a greater dynamic range for signal integration and network oscillation by the ACC. These differences in inhibitory circuitry likely underlie the distinctive network dynamics in ACC and LPC during normal and pathological brain states.SIGNIFICANCE STATEMENT The lateral prefrontal cortex (LPFC) and anterior cingulate cortex (ACC) play temporally distinct roles during the execution of cognitive tasks (rapid working memory during ongoing tasks and long-term memory to guide future action, respectively). Compared with LPFC-mediated tasks, ACC-mediated tasks can span longer timescales and require stronger engagement of inhibition. This study shows that inhibitory signaling is much more robust and diverse in the ACC than in the LPFC. Therefore, there is a lower excitatory: inhibitory synaptic ratio and a greater dynamic range for signal integration and oscillatory behavior in the ACC. These significant differences in inhibitory synaptic transmission form an important basis for the differential timing of cognitive processing by the LPFC and ACC in normal and pathological brain states.

Correlated variability modifies working memory fidelity in primate prefrontal neuronal ensembles

Neurons in the primate lateral prefrontal cortex (LPFC) encode working memory (WM) representations via sustained firing, a phenomenon hypothesized to arise from recurrent dynamics within ensembles of interconnected neurons. Here, we tested this hypothesis by using microelectrode arrays to examine spike count correlations (rsc ) in LPFC neuronal ensembles during a spatial WM task. We found a pattern of pairwise rsc during WM maintenance indicative of stronger coupling between similarly tuned neurons and increased inhibition between dissimilarly tuned neurons. We then used a linear decoder to quantify the effects of the high-dimensional rsc structure on information coding in the neuronal ensembles. We found that the rsc structure could facilitate or impair coding, depending on the size of the ensemble and tuning properties of its constituent neurons. A simple optimization procedure demonstrated that near-maximum decoding performance could be achieved using a relatively small number of neurons. These WM-optimized subensembles were more signal correlation (rsignal )-diverse and anatomically dispersed than predicted by the statistics of the full recorded population of neurons, and they often contained neurons that were poorly WM-selective, yet enhanced coding fidelity by shaping the ensemble's rsc structure. We observed a pattern of rsc between LPFC neurons indicative of recurrent dynamics as a mechanism for WM-related activity and that the rsc structure can increase the fidelity of WM representations. Thus, WM coding in LPFC neuronal ensembles arises from a complex synergy between single neuron coding properties and multidimensional, ensemble-level phenomena.

Cognitive Functions in the Prefrontal Association Cortex; Transitive Inference and the Lateral Prefrontal Cortex

To behave appropriately in a complex and uncertain world, the brain makes use of several distinct learning systems. One such system is called the "model-free process", via which conditioning allows the association between a stimulus or response and a given reward to be learned. Another system is called the "model-based process". Via this process, the state transition between a stimulus and a response is learned so that the brain is able to plan actions prior to their execution. Several studies have tried to relate the difference between model-based and model-free processes to the difference in functions of the lateral prefrontal cortex (LPFC) and the striatum. Here, we describe a series of studies that demonstrate the ability of LPFC neurons to categorize visual stimuli by their associated behavioral responses and to generate abstract information. If LPFC neurons utilize abstract code to associate a stimulus with a reward, they should be able to infer similar relationships between other stimuli of the same category and their rewards without direct experience of these stimulus-reward contingencies. We propose that this ability of LPFC neurons to utilize abstract information can contribute to the model-based learning process.

Prefrontal Neurons Represent Motion Signals from Across the Visual Field But for Memory-Guided Comparisons Depend on Neurons Providing These Signals.

Visual decisions often involve comparisons of sequential stimuli that can appear at any location in the visual field. The lateral prefrontal cortex (LPFC) in nonhuman primates, shown to play an important role in such comparisons, receives information about contralateral stimuli directly from sensory neurons in the same hemisphere, and about ipsilateral stimuli indirectly from neurons in the opposite hemisphere. This asymmetry of sensory inputs into the LPFC poses the question of whether and how its neurons incorporate sensory information arriving from the two hemispheres during memory-guided comparisons of visual motion. We found that, although responses of individual LPFC neurons to contralateral stimuli were stronger and emerged 40 ms earlier, they carried remarkably similar signals about motion direction in the two hemifields, with comparable direction selectivity and similar direction preferences. This similarity was also apparent around the time of the comparison between the current and remembered stimulus because both ipsilateral and contralateral responses showed similar signals reflecting the remembered direction. However, despite availability in the LPFC of motion information from across the visual field, these "comparison effects" required for the comparison stimuli to appear at the same retinal location. This strict dependence on spatial overlap of the comparison stimuli suggests participation of neurons with localized receptive fields in the comparison process. These results suggest that while LPFC incorporates many key aspects of the information arriving from sensory neurons residing in opposite hemispheres, it continues relying on the interactions with these neurons at the time of generating signals leading to successful perceptual decisions. Visual decisions often involve comparisons of sequential visual motion that can appear at any location in the visual field. We show that during such comparisons, the lateral prefrontal cortex (LPFC) contains accurate representation of visual motion from across the visual field, supplied by motion processing neurons. However, at the time of comparison, LPFC neurons can only use this information to compute the differences between the stimuli, if stimuli appear at the same retinal location, implicating neurons with localized receptive fields in the comparison process. These findings show that sensory comparisons rely on the interactions between LPFC and sensory neurons that not only supply sensory signals but also actively participate in the comparison of these signals at the time of the decision.

Dissociable functions of reward inference in the lateral prefrontal cortex and the striatum.

In a complex and uncertain world, how do we select appropriate behavior? One possibility is that we choose actions that are highly reinforced by their probabilistic consequences (model-free processing). However, we may instead plan actions prior to their actual execution by predicting their consequences (model-based processing). It has been suggested that the brain contains multiple yet distinct systems involved in reward prediction. Several studies have tried to allocate model-free and model-based systems to the striatum and the lateral prefrontal cortex (LPFC), respectively. Although there is much support for this hypothesis, recent research has revealed discrepancies. To understand the nature of the reward prediction systems in the LPFC and the striatum, a series of single-unit recording experiments were conducted. LPFC neurons were found to infer the reward associated with the stimuli even when the monkeys had not yet learned the stimulus-reward (SR) associations directly. Striatal neurons seemed to predict the reward for each stimulus only after directly experiencing the SR contingency. However, the one exception was “Exclusive Or” situations in which striatal neurons could predict the reward without direct experience. Previous single-unit studies in monkeys have reported that neurons in the LPFC encode category information, and represent reward information specific to a group of stimuli. Here, as an extension of these, we review recent evidence that a group of LPFC neurons can predict reward specific to a category of visual stimuli defined by relevant behavioral responses. We suggest that the functional difference in reward prediction between the LPFC and the striatum is that while LPFC neurons can utilize abstract code, striatal neurons can code individual associations between stimuli and reward but cannot utilize abstract code.

Egalitarian reward contingency in competitive games and primate prefrontal neuronal activity.

How people work to obtain a reward depends on the context of the reward delivery, such as the presence/absence of competition and the contingency of reward delivery. Since resources are limited, winning a competition is critically important for organisms' obtaining a reward. People usually expect ordinary performance-reward contingency, with better performers obtaining better rewards. Unordinary reward contingency, such as egalitarianism (equal rewards/no-rewards to both good and poor performers), dampens people's motivation. We previously reported that monkeys were more motivated, and neurons in the lateral prefrontal cortex (LPFC) showed higher outcome-related activity in a competitive than in a noncompetitive game (Hosokawa and Watanabe, 2012). However, monkey's behavior and LPFC neuronal activity have not been examined in a competitive situation with an unordinary performance-reward contingency. Also, the fixed performance-reward contingency in the previous study did not allow us to examine effects of win/loss separately from those of reward/no-reward on prefrontal neuronal activity. Here, we employed the egalitarian competitive situation in which both the winner and loser, or neither of them, got a reward as well as the normal competitive situation in which only the winner got a reward. Monkey's behavioral performance greatly deteriorated in trials with the egalitarian outcome conditions. LPFC neurons showed activities that reflected the normal or egalitarian outcome condition while very few neurons coded win/loss independent of reward/no-reward. Importantly, we found neurons that showed reward-related activity in the normal, but not in the egalitarian outcome conditions, even though the same reward was given to the animal. These results indicate that LPFC may play an important role in monitoring the current reward contingency and integrating it with the performance outcome (win-loss) for better performing the competitive game, and thus for better survival.