Training-Dependent Gradients of Timescales of Neural Dynamics in the Primate Prefrontal Cortex and Their Contributions to Working Memory.

Cortical neurons exhibit multiple timescales related to dynamics of spontaneous fluctuations (intrinsic timescales) and response to task events (seasonal timescales) in addition to selectivity to task-relevant signals. These timescales increase systematically across the cortical hierarchy, for example, from parietal to prefrontal and cingulate cortex, pointing to their role in cortical computations. It is currently unknown whether these timescales are inherent properties of neurons and/or depend on training in a specific task and if the latter, how their modulations contribute to task performance. To address these questions, we analyzed single-cell recordings within five subregions of the prefrontal cortex (PFC) of male macaques before and after training on a working-memory task. We found fine-grained but opposite gradients of intrinsic and seasonal timescales that mainly appeared after training. Intrinsic timescales decreased whereas seasonal timescales increased from posterior to anterior subregions within both dorsal and ventral PFC. Moreover, training was accompanied by increases in proportions of neurons that exhibited intrinsic and seasonal timescales. These effects were comparable to the emergence of response selectivity due to training. Finally, task selectivity accompanied opposite neural dynamics such that neurons with task-relevant selectivity exhibited longer intrinsic and shorter seasonal timescales. Notably, neurons with longer intrinsic and shorter seasonal timescales exhibited superior population-level coding, but these advantages extended to the delay period mainly after training. Together, our results provide evidence for plastic, fine-grained gradients of timescales within PFC that can influence both single-cell and population coding, pointing to the importance of these timescales in understanding cognition.

Cholinergic Neuromodulation of Prefrontal Attractor Dynamics Controls Performance in Spatial Working Memory.

The behavioral and neural effects of the endogenous release of acetylcholine following stimulation of the nucleus basalis (NB) of Meynert have been recently examined in two male monkeys (Qi et al., 2021). Counterintuitively, NB stimulation enhanced behavioral performance while broadening neural tuning in the prefrontal cortex (PFC). The mechanism by which a weaker mnemonic neural code could lead to better performance remains unclear. Here, we show that increased neural excitability in a simple continuous bump attractor model can induce broader neural tuning and decrease bump diffusion, provided neural rates are saturated. Increased memory precision in the model overrides memory accuracy, improving overall task performance. Moreover, we show that bump attractor dynamics can account for the nonuniform impact of neuromodulation on distractibility, depending on distractor distance from the target. Finally, we delve into the conditions under which bump attractor tuning and diffusion balance in biologically plausible heterogeneous network models. In these discrete bump attractor networks, we show that reducing spatial correlations or enhancing excitatory transmission can improve memory precision. Altogether, we provide a mechanistic understanding of how cholinergic neuromodulation controls spatial working memory through perturbed attractor dynamics in the PFC.

Emergence of Nonlinear Mixed Selectivity in Prefrontal Cortex after Training.

Neurons in the PFC are typically activated by different cognitive tasks, and also by different stimuli and abstract variables within these tasks. A single neuron's selectivity for a given stimulus dimension often changes depending on its context, a phenomenon known as nonlinear mixed selectivity (NMS). It has previously been hypothesized that NMS emerges as a result of training to perform tasks in different contexts. We tested this hypothesis directly by examining the neuronal responses of different PFC areas before and after male monkeys were trained to perform different working memory tasks involving visual stimulus locations and/or shapes. We found that training induces a modest increase in the proportion of PFC neurons with NMS exclusively for spatial working memory, but not for shape working memory tasks, with area 9/46 undergoing the most significant increase in NMS cell proportion. We also found that increased working memory task complexity, in the form of simultaneously storing location and shape combinations, does not increase the degree of NMS for stimulus shape with other task variables. Lastly, in contrast to the previous studies, we did not find evidence that NMS is predictive of task performance. Our results thus provide critical insights on the representation of stimuli and task information in neuronal populations, in working memory.SIGNIFICANCE STATEMENT How multiple types of information are represented in working memory remains a complex computational problem. It has been hypothesized that nonlinear mixed selectivity allows neurons to efficiently encode multiple stimuli in different contexts, after subjects have been trained in complex tasks. Our analysis of prefrontal recordings obtained before and after training monkeys to perform working memory tasks only partially agreed with this prediction, in that nonlinear mixed selectivity emerged for spatial but not shape information, and mostly in mid-dorsal PFC. Nonlinear mixed selectivity also displayed little modulation across either task complexity or correct performance. These results point to other mechanisms, in addition to nonlinear mixed selectivity, representing complex information about stimulus and task context in neuronal activity.

Drifts in Prefrontal and Parietal Neuronal Activity Influence Working Memory Judgments.

The dorsolateral prefrontal cortex (dlPFC) plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here, we addressed if this predictive ability extends to other working memory tasks and if it is present in other brain areas. We trained monkeys to remember the location of a stimulus and determine whether a second stimulus appeared at the same location or not. Neurophysiological recordings were performed in the dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and toward the location of the second stimulus would result in categorical errors. Indeed, for both areas, in nonmatching trials, when the first stimulus appeared in a neuron's preferred location, the neuron showed significantly higher firing rates in correct than in error trials; and vice versa, when the first stimulus appeared at a nonpreferred location, activity in error trials was higher than in correct. The results indicate that the activity of both dlPFC and PPC neurons is predictive of categorical judgments of information maintained in working memory, and neuronal firing rate deviations are revealing of the contents of working memory.

Working memory capacity is enhanced by distributed prefrontal activation and invariant temporal dynamics.

The amount of information that can be stored in working memory is limited but may be improved with practice. The basis of improved efficiency at the level of neural activity is unknown. To investigate this question, we trained monkeys to perform a working memory task that required memory for multiple stimuli. Performance decreased as a function of number of stimuli to be remembered, but improved as the animals practiced the task. Neuronal recordings acquired during this training revealed two hitherto unknown mechanisms of working memory capacity improvement. First, more prefrontal neurons became active as working memory improved, but their baseline activity decreased. Second, improved working memory capacity was characterized by less variable temporal dynamics, resulting in a more consistent firing rate at each time point during the course of a trial. Our results reveal that improved performance of working memory tasks is achieved through more distributed activation and invariant neuronal dynamics.

Persistent Spiking Activity Underlies Working Memory.

Persistent activity generated in the PFC during the delay period of working memory tasks represents information about stimuli held in memory and determines working memory performance. Alternative models of working memory, depending on the rhythmicity of discharges or exclusively on short-term synaptic plasticity, are inconsistent with the neurophysiological data.Dual Perspectives Companion Paper:Working Memory: Delay Activity, Yes! Persistent Activity? Maybe Not, by Mikael Lundqvist, Pawel Herman, and Earl K. Miller.

Functional specialization of areas along the anterior-posterior axis of the primate prefrontal cortex.

Functional specialization of areas along the anterior-posterior axis of the lateral prefrontal cortex has been speculated but little evidence exists about distinct neurophysiological properties between prefrontal sub-regions. To address this issue we divided the lateral prefrontal cortex into a posterior-dorsal, a mid-dorsal, an anterior-dorsal, a posterior-ventral, and an anterior ventral region. Selectivity for spatial locations, shapes, and colors was evaluated in six monkeys never trained in working memory tasks, while they viewed the stimuli passively. Recordings from over two thousand neurons revealed systematic differences between anterior and posterior regions. In the dorsal prefrontal cortex, anterior regions exhibited the largest receptive fields, longest response latencies, and lowest amount of information for stimuli. In the ventral prefrontal cortex, posterior regions were characterized by a low percentage of responsive neurons to any stimuli we used, consistent with high specialization for stimulus features. Additionally, spatial information was more prominent in the dorsal and color in ventral regions. Our results provide neurophysiological evidence for a rostral-caudal gradient of stimulus selectivity through the prefrontal cortex, suggesting that posterior areas are selective for stimuli even when these are not releant for execution of a task, and that anterior areas are likely engaged in more abstract operations.

Age-dependent changes in prefrontal intrinsic connectivity.

The prefrontal cortex continues to mature after puberty and into early adulthood, mirroring the time course of maturation of cognitive abilities. However, the way in which prefrontal activity changes during peri- and postpubertal cortical maturation is largely unknown. To address this question, we evaluated the developmental stage of peripubertal rhesus monkeys with a series of morphometric, hormonal, and radiographic measures, and conducted behavioral and neurophysiological tests as the monkeys performed working memory tasks. We compared firing rate and the strength of intrinsic functional connectivity between neurons in peripubertal vs. adult monkeys. Notably, analyses of spike train cross-correlations demonstrated that the average magnitude of functional connections measured between neurons was lower overall in the prefrontal cortex of peripubertal monkeys compared with adults. The difference resulted because negative functional connections (indicative of inhibitory interactions) were stronger and more prevalent in peripubertal compared with adult monkeys, whereas the positive connections showed similar distributions in the two groups. Our results identify changes in the intrinsic connectivity of prefrontal neurons, particularly that mediated by inhibition, as a possible substrate for peri- and postpubertal advances in cognitive capacity.

Lower neuronal variability in the monkey dorsolateral prefrontal than posterior parietal cortex.

The dorsolateral prefrontal and posterior parietal cortex are two brain areas involved in cognitive functions such as spatial attention and working memory. When tested with identical tasks, only subtle differences in firing rate are present between neurons recorded in the two areas. In this article we report that major differences in neuronal variability characterize the two areas during working memory. The Fano factors of spike counts in dorsolateral prefrontal neurons were consistently lower than those of the posterior parietal cortex across a range of tasks, epochs, and conditions in the same monkeys. Variability differences were observed despite minor differences in firing rates between the two areas in the tasks tested and higher overall firing rate in the prefrontal than in the posterior parietal sample. Other measures of neuronal discharge variability, such as the coefficient of variation of the interspike interval, displayed the same pattern of lower prefrontal variability. Fano factor values were negatively correlated with performance in the working memory task, suggesting that higher neuronal variability was associated with diminished task performance. The results indicate that information involving remembered stimuli is more reliably represented in the prefrontal than the posterior parietal cortex based on the variability of neuronal responses, and suggest functional differentiation between the two areas beyond differences in firing rate.

Representation of remembered stimuli and task information in the monkey dorsolateral prefrontal and posterior parietal cortex.

Both dorsolateral prefrontal and posterior parietal cortex have been implicated in spatial working memory and representation of task information. Prior experiments training animals to recall the first of a sequence of stimuli and examining the effect of subsequent distractors have identified increased ability of the prefrontal cortex to represent remembered stimuli and filter distractors. It is unclear, however, if this prefrontal functional specialization extends to stimuli appearing earlier in a sequence, when subjects are cued to remember subsequent ones. It is also not known how task information interacts with persistent activity representing remembered stimuli and distractors in the two areas. To address these questions, we trained monkeys to remember either the first or second of two stimuli presented in sequence and recorded neuronal activity from the posterior parietal and dorsolateral prefrontal cortex. The prefrontal cortex was better able to represent the actively remembered stimulus, whereas the posterior parietal cortex was more modulated by distractors; however, task effects interfered with this representation. As a result, large proportions of neurons with persistent activity and task effects exhibited a preference for a stimulus when it appeared as a distractor in both areas. Additionally, prefrontal neurons were modulated to a greater extent by task factors during the delay period of the task. The results indicate that the prefrontal cortex is better able than the posterior parietal cortex to differentiate between distractors and actively remembered stimuli and is more modulated by the task; however, this relative preference is highly context dependent and depends on the specific requirements of the task.

Differences in intrinsic functional organization between dorsolateral prefrontal and posterior parietal cortex.

The dorsolateral prefrontal and posterior parietal cortex are 2 components of the cortical network controlling attention, working memory, and executive function. Little is known about how the anatomical organization of the 2 areas accounts for their functional specialization. In order to address this question, we examined the strength of intrinsic functional connectivity between neurons sampled in each area by means of cross-correlation analyses of simultaneous recordings from monkeys trained to perform working memory tasks. In both areas, effective connectivity declined as a function of distance between neurons. However, the strength of effective connectivity was higher overall and more localized over short distances in the posterior parietal than the prefrontal cortex. The difference in connectivity strength between the 2 areas could not be explained by differences in firing rate or selectivity for the stimuli and task events, it was present when the fixation period alone was analyzed, and according to simulation results, was consistent with a systematic difference either in the strength or in the relative numbers of shared inputs between neurons. Our results indicate that the 2 areas are characterized by unique intrinsic functional organization, consistent with known differences in their response patterns during working memory.

Incorporation of new information into prefrontal cortical activity after learning working memory tasks.

The ability to learn new tasks requires that new information is integrated into neural systems that already support other behaviors. To study how new information is incorporated into neural representations, we analyzed single-unit recordings from the prefrontal cortex (PFC), a brain region important for task acquisition and working memory, before and after monkeys learned to perform two behavioral tasks. A population-decoding analysis revealed a large increase in task-relevant information, and smaller changes in stimulus-related information, after training. This new information was contained in dynamic patterns of neural activity, with many individual neurons containing the new task-relevant information for only relatively short periods of time in the midst of other large firing rate modulations. Additionally, we found that stimulus information could be decoded with high accuracy only from dorsal PFC, whereas task-relevant information was distributed throughout both dorsal and ventral PFC. These findings help resolve a controversy about whether PFC is innately specialized to process particular types of information or whether its responses are completely determined by task demands by showing there is both regional specialization within PFC that was present before training, as well as more widespread task-relevant information that is a direct result of learning. The results also show that information is incorporated into PFC through the emergence of a small population of highly selective neurons that overlay new signals on top of patterns of activity that contain information about previously encoded variables, which gives insight into how information is coded in neural activity.

Prefrontal neuronal dynamics in the absence of task execution.

Prefrontal cortical activity represents stimuli in working memory tasks in a low-dimensional manifold that transforms over the course of a trial. Such transformations reflect specific cognitive operations, so that, for example, the rotation of stimulus representations is thought to reduce interference by distractor stimuli. Here we show that rotations occur in the low-dimensional activity space of prefrontal neurons in naïve male monkeys (Macaca mulatta), while passively viewing familiar stimuli. Moreover, some aspects of these rotations remain remarkably unchanged after training to perform working memory tasks. Significant training effects are still present in population dynamics, which further distinguish correct and error trials during task execution. Our results reveal automatic functions of prefrontal neural circuits allow transformations that may aid cognitive flexibility.

Cholinergic neuromodulation of prefrontal attractor dynamics controls performance in spatial working memory.

The behavioral and neural effects of the endogenous release of acetylcholine following stimulation of the Nucleus Basalis of Meynert (NB) have been recently examined (Qi et al. 2021). Counterintuitively, NB stimulation enhanced behavioral performance while broadening neural tuning in the prefrontal cortex (PFC). The mechanism by which a weaker mnemonic neural code could lead to better performance remains unclear. Here, we show that increased neural excitability in a simple continuous bump attractor model can induce broader neural tuning and decrease bump diffusion, provided neural rates are saturated. Increased memory precision in the model overrides memory accuracy, improving overall task performance. Moreover, we show that bump attractor dynamics can account for the nonuniform impact of neuromodulation on distractibility, depending on distractor distance from the target. Finally, we delve into the conditions under which bump attractor tuning and diffusion balance in biologically plausible heterogeneous network models. In these discrete bump attractor networks, we show that reducing spatial correlations or enhancing excitatory transmission can improve memory precision. Altogether, we provide a mechanistic understanding of how cholinergic neuromodulation controls spatial working memory through perturbed attractor dynamics in PFC.

Brain structure and activity predicting cognitive maturation in adolescence.

Cognitive abilities of primates, including humans, continue to improve through adolescence 1,2. While a range of changes in brain structure and connectivity have been documented 3,4, how they affect neuronal activity that ultimately determines performance of cognitive functions remains unknown. Here, we conducted a multilevel longitudinal study of monkey adolescent neurocognitive development. The developmental trajectory of neural activity in the prefrontal cortex accounted remarkably well for working memory improvements. While complex aspects of activity changed progressively during adolescence, such as the rotation of stimulus representation in multidimensional neuronal space, which has been implicated in cognitive flexibility, even simpler attributes, such as the baseline firing rate in the period preceding a stimulus appearance had predictive power over behavior. Unexpectedly, decreases in brain volume and thickness, which are widely thought to underlie cognitive changes in humans 5 did not predict well the trajectory of neural activity or cognitive performance changes. Whole brain cortical volume in particular, exhibited an increase and reached a local maximum in late adolescence, at a time of rapid behavioral improvement. Maturation of long-distance white matter tracts linking the frontal lobe with areas of the association cortex and subcortical regions best predicted changes in neuronal activity and behavior. Our results provide evidence that optimization of neural activity depending on widely distributed circuitry effects cognitive development in adolescence.

Neural correlates of a decision variable before learning to perform a match/non-match task.

The lateral prefrontal cortex plays an important role in working memory and decision-making, although little is known about how neural correlates of these functions are shaped by learning. To understand the effect of learning on the neuronal representation of decision-making, we recorded single neurons from the lateral prefrontal cortex of monkeys before and after they were trained to judge whether two stimuli appeared at matching spatial locations. After training, and in agreement with previous studies, a population of neurons exhibited activity that was modulated depending on whether the second stimulus constituted a match or not, which had predictive ability for the monkey's choice. However, even before training, prefrontal neurons displayed modulation depending on the match or non-match status of a stimulus, with approximately equal percentages of neurons preferring a match or a non-match. The difference in firing rate and discriminability for match and non-match stimuli before training was of comparable magnitude as that after training. Changes observed after training involved an increase in the percentage of neurons exhibiting this effect, a greater proportion of neurons preferring non-match stimuli, and a greater percentage of neurons representing information about the first stimulus during the presentation of the second stimulus. Our results suggest that the neuronal activity representing some match/non-match judgments is present in the lateral prefrontal cortex even when subjects are not required to perform a comparison and before any training.

Working memory performance and neural activity in prefrontal cortex of peripubertal monkeys.

The dorsolateral prefrontal cortex matures late into adolescence or early adulthood. This pattern of maturation mirrors working memory abilities, which continue to improve into adulthood. However, the nature of the changes that prefrontal neuronal activity undergoes during this process is poorly understood. We investigated behavioral performance and neural activity in working memory tasks around the time of puberty, a developmental event associated with the release of sex hormones and significant neurological change. The developmental stages of male rhesus monkeys were evaluated with a series of morphometric, hormonal, and radiographic measures. Peripubertal monkeys were trained to perform an oculomotor delayed response task and a variation of this task involving a distractor stimulus. We found that the peripubertal monkeys tended to abort a relatively large fraction of trials, and these were associated with low levels of task-related neuronal activity. However, for completed trials, accuracy in the delayed saccade task was high and the appearance of a distractor stimulus did not impact performance significantly. In correct trials delay period activity was robust and was not eliminated by the presentation of a distracting stimulus, whereas in trials that resulted in errors the sustained cue-related activity was significantly weaker. Our results show that in peripubertal monkeys the prefrontal cortex is capable of generating robust persistent activity in the delay periods of working memory tasks, although in general it may be more prone to stochastic failure than in adults.

Training-dependent gradients of timescales of neural dynamics in the primate prefrontal cortex and their contributions to working memory.

Cortical neurons exhibit multiple timescales related to dynamics of spontaneous fluctuations (intrinsic timescales) and response to task events (seasonal timescales) in addition to selectivity to task-relevant signals. These timescales increase systematically across the cortical hierarchy, e.g., from parietal to prefrontal and cingulate cortex, pointing to their role in cortical computations. It is currently unknown whether these timescales depend on training in a specific task and/or are an inherent property of neurons, and whether more fine-grained hierarchies of timescales exist within specific cortical regions. To address these questions, we analyzed single-cell recordings within five subregions of the prefrontal cortex (PFC) of male macaques before and after training on a working-memory task. We found fine-grained but opposite gradients of intrinsic and seasonal timescales that mainly appeared after training. Intrinsic timescales decreased whereas seasonal timescales increased from posterior to anterior subregions within both dorsal and ventral PFC. Moreover, training was accompanied by increases in proportions of neurons that exhibited intrinsic and seasonal timescales. These effects were comparable to the emergence of response selectivity due to training. Finally, task selectivity accompanied opposite neural dynamics such that neurons with task-relevant selectivity exhibited longer intrinsic and shorter seasonal timescales. Notably, neurons with longer intrinsic and shorter seasonal timescales exhibited superior population-level coding, but these advantages extended to the delay period mainly after training. Together, our results provide evidence for plastic, fine-grained gradients of timescales within PFC that can influence both single-cell and population coding, pointing to the importance of these timescales in understanding cognition. Significance statement: Recent studies have demonstrated that neural responses exhibit dynamics with different timescales that follow a certain order or hierarchy across cortical areas. While the hierarchy of timescales is consistent across different tasks, it is unknown if these timescales emerge only after training or if they represent inherent properties of neurons. To answer this question, we estimated multiple timescales in neural response across five subregions of the monkeys' lateral prefrontal cortex before and after training on a working-memory task. Our results provide evidence for fine-grained gradients related to certain neural dynamics. Moreover, we show that these timescales depend on and can be modulated by training in a cognitive task, and contribute to encoding of task-relevant information at single-cell and population levels.

Stimulus selectivity in dorsal and ventral prefrontal cortex after training in working memory tasks.

The prefrontal cortex is known to represent different types of information in working memory. Contrasting theories propose that the dorsal and ventral regions of the lateral prefrontal cortex are innately specialized for the representation of spatial and nonspatial information, respectively (Goldman-Rakic, 1996), or that the two regions are shaped by the demands of cognitive tasks imposed on them (Miller, 2000). To resolve this issue, we recorded from neurons in the two regions, before and at multiple stages of training monkeys on visual working memory tasks. Before training, substantial functional differences were present between the two regions. Dorsal prefrontal cortex exhibited higher overall responsiveness to visual stimuli and higher selectivity for spatial information. After training, stimulus selectivity generally decreased, although dorsal prefrontal cortex retained higher spatial selectivity regardless of task performed. Ventral prefrontal cortex appeared to be affected to a greater extent by the nature of the task. Our results indicate that regional specialization for stimulus selectivity is present in the primate prefrontal cortex regardless of training. Dorsal areas of the prefrontal cortex are inherently organized to represent spatial information, and training has little influence on this spatial bias. Ventral areas are biased toward nonspatial information, although they are more influenced by training both in terms of activation and changes in stimulus selectivity.

Neurons with inverted tuning during the delay periods of working memory tasks in the dorsal prefrontal and posterior parietal cortex.

The dorsolateral prefrontal and posterior parietal cortices are two interconnected brain areas that are coactivated in tasks involving functions such as spatial attention and working memory. The response properties of neurons in the two areas are in many respects indistinguishable, yet only prefrontal neurons are able to resist interference by distracting stimuli when subjects are required to remember an initial stimulus. Several mechanisms have been proposed that could account for this functional difference, including the existence of specialized interneuron types, specific to the prefrontal cortex. Although such neurons with inverted tuning during the delay period of a working memory task have been described in the prefrontal cortex, no comparative data exist from other cortical areas that would establish a unique prefrontal role. To test this hypothesis, we analyzed a large database of recordings obtained in the dorsolateral prefrontal and posterior parietal cortex of the same monkeys as they performed working memory tasks. We found that in the prefrontal cortex, neurons with inverted tuning were more numerous and manifested unique properties. Our results give credence to the idea that a division of labor exists between separate neuron types in the prefrontal cortex and that this represents a functional specialization that is not present in its cortical afferents.