Biology subjects

Constantinidis, C.

Publications and source records attributed to Constantinidis, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Intermittent stimulation of the basal forebrain improves working memory in aged nonhuman primates.

Brain aging contributes to cognitive decline and risk of dementia. Degeneration of the basal forebrain cholinergic system parallels these changes in aging, Alzheimers dementia, Parkinsons dementia, and Lewy body dementia, and thus is a common element linked to executive function across the lifespan and in disease states. Here, we tested the potential of one-hour daily intermittent basal forebrain stimulation to improve cognition in senescent monkeys, and its mechanisms of action. Stimulation in five animals improved working memory duration in 8-12 weeks across all animals, with peak improvements observed in the first four weeks. In an ensuing three month period without stimulation, improvements were retained. With additional stimulation, performance remained above baseline throughout the 15 months of the study. Studies with a cholinesterase inhibitor produced inconsistent improvements in behavior. One of five animals improved significantly. Manipulating the stimulation pattern demonstrated selectivity for both stimulation and recovery period duration. Brain stimulation led to acute increases in cerebrospinal levels of tissue plasminogen activator, which is an activating element for two brain neurotrophins, Nerve Growth Factor (NGF) and Brain-Derived Growth Factor (BDNF). Stimulation also led to improved glucose utilization in stimulated hemispheres relative to contralateral. Glucose utilization also consistently declines with aging and some dementias. Together, these findings suggest that intermittent stimulation of the nucleus basalis of Meynert improves executive function and reverses some aspects of brain aging. HighlightsO_LIThe basal forebrain and its cholinergic projections are the sole source of acetylcholine for the cortical mantle in primates and humans. C_LIO_LIForebrain function tracks cognitive loss throughout the adult lifespan. C_LIO_LIOne hour per day intermittent stimulation of this region improves executive function behaviors and plausibly reverses some aspects of brain aging, a large risk factor in dementias. C_LIO_LIThis stimulation exceeds impacts of standard pharmacotherapies, is enduring, recruits brain neurotrophic pathways and improves cortical glucose utilization. C_LI

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bioRxiv2024

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. Significance statementAcetylcholine has been thought to improve cognitive performance by sharpening neuronal tuning in prefrontal cortex. Recent work has shown that electrical stimulation of the cholinergic forebrain in awake-behaving monkeys induces a reduction in prefrontal neural tuning under stimulation conditions that improve performance. To reconcile these divergent observations, we provide network simulations showing that these derive consistently from specific conditions in prefrontal attractor dynamics: firing rate saturation leads to increased storage precision and reduced neural tuning upon cholinergic activation via an increase in neural excitability, a reduction in neural correlations, and an increase in excitatory transmission. Our study integrates previously reported data into a consistent mechanistic view of how acetylcholine controls spatial working memory via attractor network dynamics in prefrontal cortex.

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bioRxiv2023

Recurrent activity within microcircuits of macaque dorsolateral prefrontal cortex tracks cognitive flexibility

Human and non-human primate data clearly implicate the dorsolateral prefrontal cortex (dlPFC) as critical for advanced cognitive functions1,2. It is thought that intracortical synaptic architectures within dlPFC are the integral neurobiological substrate that gives rise to these processes, including working memory, inferential reasoning, and decision-making3-7. In the prevailing model, each cortical column makes up one fundamental processing unit composed of dense intrinsic connectivity, conceptualized as the canonical cortical microcircuit3,8. Each cortical microcircuit receives sensory and cognitive information from a variety of sources which are represented by sustained activity within the microcircuit, referred to as persistent or recurrent activity4,9. Via recurrent connections within the microcircuit, activity can propagate for a variable length of time, thereby allowing temporary storage and computations to occur locally before ultimately passing a transformed representation to a downstream output4,5,10. Competing theories regarding how microcircuit activity is coordinated have proven difficult to reconcile in vivo where intercortical and intracortical computations cannot be fully dissociated5,9,11,12. Here, we interrogated the intrinsic features of isolated microcircuit networks using high-density calcium imaging of macaque dlPFC ex vivo. We found that spontaneous activity is intrinsically maintained by microcircuit architecture, persisting at a high rate in the absence of extrinsic connections. Further, using perisulcal stimulation to evoke persistent activity in deep layers, we found that activity propagates through stochastically assembled intracortical networks, creating predictable population-level events from largely non-overlapping ensembles. Microcircuit excitability covaried with individual cognitive performance, thus anchoring heuristic models of abstract cortical functions within quantifiable constraints imposed by the underlying synaptic architecture.

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bioRxiv2023

Brain-wide human oscillatory LFP activity during visual working memory

Oscillatory activity is thought to be a marker of cognitive processes, although its role and distribution across the brain during working memory has been a matter of debate. To understand how oscillatory activity differentiates tasks and brain areas in humans, we recorded local field potentials (LFPs) in 12 adults as they performed visual-spatial and shape-matching memory tasks. Tasks were designed to engage working memory processes at a range of delay intervals between stimulus delivery and response initiation. LFPs were recorded using intracranial depth electrodes implanted to localize seizures for management of intractable epilepsy. Task-related LFP power analyses revealed an extensive network of cortical regions that were activated during the presentation of visual stimuli and during their maintenance in working memory, including occipital, parietal, temporal, insular, and prefrontal cortical areas, and subcortical structures including the amygdala and hippocampus. Across most brain areas, the appearance of a stimulus produced broadband power increase, while gamma power was evident during the delay interval of the working memory task. Notable differences between areas included that occipital cortex was characterized by elevated power in the high gamma (100-150 Hz) range during the 500 ms of visual stimulus presentation, which was less pronounced or absent in other areas. A decrease in power centered in beta frequency (16-40 Hz) was also observed after the stimulus presentation, whose magnitude differed across areas. These results reveal the interplay of oscillatory activity across a broad network, and region-specific signatures of oscillatory processes associated with visual working memory.

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bioRxiv2023

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 statementRecent 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.

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bioRxiv2023

Local organization of spatial and shape information during working memory in the primate prefrontal cortex

The current understanding of sensory and motor cortical areas has been defined by the existence of topographical maps across the brain surface, however, higher cortical areas, such as the prefrontal cortex, seem to lack an equivalent organization, and only limited evidence of functional clustering of neurons with similar stimulus properties is evident in them. We thus sought to examine whether neurons that represent similar spatial and object information are clustered in the monkey prefrontal cortex and whether such an organization only emerges as a result of training. To this end, we analyzed neurophysiological recordings from male macaque monkeys before and after training in spatial and shape working memory tasks. Neurons with similar spatial or shape selectivity were more likely than chance to be encountered at short distances from each other. Some aspects of organization were present even in naive animals, however other changes appeared after cognitive training. Our results reveal that prefrontal microstructure automatically supports orderly representations of spatial and object information.

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bioRxiv2023

Laminar pattern of adolescent development changes in working memory neuronal activity

Adolescent development is characterized by an improvement in cognitive abilities, such as working memory. Neurophysiological recordings in a non-human primate model of adolescence have revealed changes in neural activity that mirror improvement in behavior, including higher firing rate during the delay intervals of working memory tasks. The laminar distribution of these changes is unknown. By some accounts, persistent activity is more pronounced in superficial layers, so we sought to determine whether changes are most pronounced there. We therefore analyzed neurophysiological recordings from neurons recorded in the young and adult stage, at different cortical depths. Superficial layers exhibited increased baseline firing rate in the adult stage. Unexpectedly, changes in persistent activity were most pronounced in the middle layers. Finally, improved discriminability of stimulus location was most evident in the deeper layers. These results reveal the laminar pattern of neural activity maturation that is associated with cognitive improvement. NEW AND NOTEWORTHYStructural brain changes are evident during adolescent development particularly in the cortical thickness of the prefrontal cortex, at a time when working memory ability increases markedly. The depth distribution of neurophysiological changes during adolescence is not known. Here we show that neurophysiological changes are not confined to superficial layers, which have most often been implicated in the maintenance of working memory. Contrary to expectations, greatest changes were evident in intermediate layers of the prefrontal cortex.

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bioRxiv2023

Decoding working memory information from persistent and activity-silent neurons in the primate prefrontal cortex

Persistent activity of neurons in the prefrontal cortex has been thought to represent the information maintained in working memory, though alternative models have recently challenged this idea. Activity-silent theories posit that stimulus information may be maintained by the activity pattern of neurons that do not produce firing rate significantly elevated about their baseline during the delay period of working memory tasks. We thus tested the ability of neurons that do and do not generate persistent activity in the prefrontal cortex of monkeys to represent spatial and object information in working memory. Neurons that generated persistent activity represented more information about the stimuli in both spatial and object working memory tasks. The amount of information that could be decoded from neural activity depended on the choice of decoder and parameters used but neurons with persistent activity outperformed non-persistent neurons consistently. Although averaged across all neurons and stimuli, firing rate did not appear clearly elevated above baseline during the maintenance of neural activity particularly for object working memory, this grant average masked neurons that generated persistent activity selective for their preferred stimuli, which carried the majority of information about the stimulus identity. These results reveal that prefrontal neurons with generate persistent activity constitute the primary mechanism of working memory maintenance in the cortex. NEW AND NOTEWORTHYCompeting theories suggest that neurons that generate persistent activity or do not are primarily responsible for the maintenance of information, particularly regarding object working memory. While the two models have been debated on theoretical terms, direct comparison of empirical results have been lacking. Analysis of neural activity in a large database of prefrontal recordings revealed that neurons that generate persistent activity were primarily responsible for the maintenance of both spatial and object working memory.

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bioRxiv2023

Single-neuron and population measures of neuronal activity in working memory tasks

Information represented in working memory is reflected in the firing rate of neurons in the prefrontal cortex and brain areas connected to it. In recent years, there has been an increased realization that population measures capture more accurately neural correlates of cognitive functions. We examined how single neuron firing in the prefrontal and posterior parietal cortex of two male monkeys compared with population measures in spatial working memory tasks. Persistent activity was observed in the dorsolateral prefrontal and posterior parietal cortex and firing rate predicted working memory behavior, particularly in the prefrontal cortex. These findings had equivalents in population measures, including trajectories in state space that became less separated in error trials. We additionally observed rotations of the stimulus space for different task conditions, which was not obvious in firing rate measures. These results suggest that population measures provide a richer view of how neuronal activity is associated with behavior, however, largely confirm that persistent activity is the core phenomenon that maintains visual-spatial information in working memory. NEW & NOTEWORTHYRecordings from large numbers of neurons led to a re-evaluation of neural correlates of cognitive functions, which traditionally were defined based on responses of single neurons, or averages of firing rates. Analysis of neuronal recordings from the dorsolateral prefrontal and posterior parietal cortex revealed that properties of neuronal firing captured in classical studies of persistent activity can account for population representations, though some population characteristics did not have clear correlates in single neuron activity.

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bioRxiv2023

Influence of Fast-Spiking Prefrontal Neurons on Working Memory Behavior

Working memory is a limited-capacity system for maintaining and manipulating information for recall. Neurons that generate persistent activity in the primate dorsolateral prefrontal and posterior parietal cortex have been shown to be predictive of behavior in working memory tasks, though subtle differences between them have been observed in how information was represented, in some tasks. The role of different neuron types in each of these areas has not been investigated at depth. We thus compared the activity of neurons classified as fast-spiking, putative interneurons, and regular-spiking, putative pyramidal neurons, recorded from the prefrontal and posterior parietal cortex of male monkeys, to analyze their role in the maintenance of working memory. Our results demonstrate that fast-spiking neurons are active during a range of tasks and generate persistent activity during the delay period over which stimuli need to be maintained in memory. Furthermore, the activity of fast spiking neurons, particularly in the prefrontal cortex, is predictive of the subjects recall no less than that of regular-spiking neurons, which are exclusively projection neurons in the cortex and thus capable of transmitting signals from the prefrontal cortex into other areas. Our results shed light onto the fundamental neural circuits that determine subjects memories and judgments.

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bioRxiv2022

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 naive monkeys, 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.

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bioRxiv2022

Deep learning segmentation of the nucleus basalis of Meynert on 3T MRI

The nucleus basalis of Meynert (NBM) is a key subcortical structure that is important in arousal, cognition, brain network modulation, and has been explored as a deep brain stimulation target. It has also been implicated in several disease states, including Alzheimers disease, Parkinsons disease, and temporal lobe epilepsy (TLE). Given the small size of NBM and variability between patients, NBM is difficult to study; thus, accurate, patient-specific segmentation is needed. We investigated whether a deep learning network could produce accurate, patient-specific segmentations of NBM on commonly utilized 3T MRI. It is difficult to accurately segment NBM on 3T MRI, with 7T being preferred. Paired 3T and 7T MRI datasets of 21 healthy subjects were obtained, with 6 completely withheld for testing. NBM was expertly segmented on 7T MRI, providing accurate labels for the paired 3T MRI. An external dataset of 14 patients with TLE was used to test the model on brains with neurological disorders. A 3D-Unet convolutional neural network was constructed, and a 5-fold cross-validation was performed. The model was evaluated on healthy subjects using the held-out test dataset and the external dataset of TLE patients. The model demonstrated significantly improved dice coefficient over the standard probabilistic atlas for both healthy subjects (0.68MEAN{+/-}0.08SD vs. 0.47{+/-}0.06, p=0.0089, t-test) and TLE patients (0.63{+/-}0.08 vs. 0.38{+/-}0.19, p=0.0001). Additionally, the centroid distance was significantly decreased when using the model in patients with TLE (1.22{+/-}0.33mm, 3.25{+/-}2.57mm, p=0.0110). We developed the first model, to our knowledge, for automatic and accurate patient-specific segmentation of the NBM.

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bioRxiv2021

Strong gamma frequency oscillations in the adolescent prefrontal cortex

Working memory ability continues to mature into adulthood in both humans and non-human primates. At the single neuron level, adolescent development is characterized by increased prefrontal firing rate in the delay period, but less is known about how coordinated activity between neurons is altered. Local field potentials (LFP) provide a window into the computation carried out by the local network. To address the effects of adolescent development on LFP activity, three male rhesus monkeys were trained to perform an oculomotor delayed response task and tested at both the adolescent and adult stage. Simultaneous single-unit and LFP signals were recorded from areas 8a and 46 of the dorsolateral prefrontal cortex (dlPFC). In both the cue and delay period, power relative to baseline increased in the gamma frequency range (32 - 128 Hz). In the adult stage, high-firing neurons were also more likely to reside at sites with strong gamma power increase from baseline. For both stages, the gamma power increase in the delay was selective for sites with neuron encoding stimulus information in their spiking. Gamma power and neuronal firing did not show stronger temporal correlations. Our results establish gamma power decrease to be a feature of prefrontal cortical maturation. Significance StatementGamma-frequency oscillations in extracellular field recordings (such as LFP or EEG) are a marker of normal interactions between excitatory and inhibitory neurons in neural circuits. Abnormally low gamma power during working memory is seen in conditions such as schizophrenia. We sought to examine whether the immature prefrontal cortex similarly exhibits lower power in the gamma frequency range during working memory, in a non-human primate model of adolescence. Contrary to this expectation, the adolescent PFC exhibited stronger gamma power during the maintenance of working memory. Our findings reveal an unknown developmental maturation trajectory of gamma band oscillations and raise the possibility that schizophrenia represent an excessive state of prefrontal maturation.

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bioRxiv2021

Trial-to-trial variability of spiking delay activity in prefrontal cortex constrains burst-coding models of working memory

A hallmark neuronal correlate of working memory (WM) is stimulus-selective spiking activity of neurons in prefrontal cortex (PFC) during mnemonic delays. These observations have motivated an influential computational modeling framework in which WM is supported by persistent activity. Recently this framework has been challenged by arguments that observed persistent activity may be an artifact of trial-averaging, which potentially masks high variability of delay activity at the single-trial level. In an alternative scenario, WM delay activity could be encoded in bursts of selective neuronal firing which occur intermittently across trials. However, this alternative proposal has not been tested on single-neuron spike-train data. Here, we developed a framework for addressing this issue by characterizing the trial-to-trial variability of neuronal spiking quantified by Fano factor (FF). By building a doubly stochastic Poisson spiking model, we first demonstrated that the burst-coding proposal implies a significant increase in FF positively correlated with firing rate, and thus loss of stability across trials during the delay. Simulation of spiking cortical circuit WM models further confirmed that FF is a sensitive measure that can well dissociate distinct WM mechanisms. We then tested these predictions on datasets of single-neuron recordings from macaque prefrontal cortex during three WM tasks. In sharp contrast to the burst-coding model predictions, we only found a small fraction of neurons showing increased WM-dependent burstiness, and stability across trials during delay was strengthened in empirical data. Therefore, reduced trial-to-trial variability during delay provides strong constraints on the contribution of single-neuron intermittent bursting to WM maintenance. Significance StatementThere are diverging classes of theoretical models explaining how information is maintained in working memory by cortical circuits. In an influential model class, neurons fire exhibit persistent elevated memorandum-selective firing, whereas a recently developed class of burst-coding models suggests that persistent activity is an artifact of trial-averaging, and spiking is sparse in each single trial, subserved by brief intermittent bursts. However, this alternative picture has not been characterized or tested on empirical spike-train data. Here we combine mathematical analysis, computational model simulation and experimental data analysis to test empirically theses two classes of models and show that the trial-to-trial variability of empirical spike trains is not consistent with burst coding. These findings provide constraints for theoretical models of working memory.

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bioRxiv2020

Training-induced prefrontal neuronal changes transfer between tasks

Training to improve working memory is associated with changes in prefrontal activation and confers lasting benefits, some of which generalize to untrained tasks, though the issue remains contentious and the neural substrate underlying such transfer are unknown. To assess how neural activity changes induced by training transfer across tasks, we recorded single units, multi-unit activity (MUA) and local field potentials (LFP) with chronic electrode arrays implanted in the prefrontal cortex of two monkeys, as they were trained to perform cognitive tasks. Mastering different tasks was associated with distinct changes in neural activity, which included redistribution of power across frequency bands in the LFP, recruitment of larger numbers of MUA sites, and increase or decrease of mean neural activity across single units. In every training phase, changes induced by the actively learned task transferred to an untrained control task, which remained the same across the training period. The results explicate the neural basis through which training can transfer across cognitive tasks.

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bioRxiv2020

Emergence of prefrontal neuron maturation properties by training recurrent neural networks in cognitive tasks

Working memory and response inhibition are functions that mature relatively late in life, after adolescence, paralleling the maturation of the prefrontal cortex. The link between behavioral and neural maturation is not obvious, however, making it challenging to understand how neural activity underlies the maturation of cognitive function. To gain insights into the nature of observed changes in prefrontal activity between adolescence and adulthood, we investigated the progressive changes in unit activity of Recurrent Neural Networks (RNNs) as they were trained to perform working memory and response inhibition tasks. These included increased delay period activity during working memory tasks, and increased activation in antisaccade tasks. These findings reveal universal properties underlying the neuronal computations behind cognitive tasks and explicate the nature of changes that occur as the result of developmental maturation.

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bioRxiv2020

Emergence of Non-Linear Mixed Selectivity in Prefrontal Cortex after Training

Neurons in the prefrontal cortex (PFC) are typically activated by different cognitive tasks, and also by different stimuli and abstract variables within these tasks. A single neurons 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 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 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, which may pave the way to a greater understanding of neural selectivity in working memory. SIGNIFICANCE STATEMENTHow 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, to represent complex information about stimulus and context in neuronal activity.

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bioRxiv2020

Prefrontal and Parietal Attractor Networks Mediate Working Memory Judgments

The dorsolateral prefrontal cortex plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here we addressed whether this predictive ability extends to categorical judgments based on information retained in working memory, and is present in other brain areas. We trained monkeys in a novel, Match-Stay, Nonmatch-Go task, which required them to observe two stimuli presented in sequence with an intervening delay period between them. If the two stimuli were different, the monkeys had to saccade to the location of the second stimulus; if they were the same, they held fixation. Neurophysiological recordings were performed in areas 8a and 46 of the dlPFC and 7a and lateral intraparietal cortex (LIP) of the PPC. We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and towards the location of the second stimulus would result in categorical errors. Indeed, for both areas, when the first stimulus appeared in a neurons preferred location, the neuron showed significantly higher firing rates in correct than in error trials. When the first stimulus appeared at a nonpreferred location and the second stimulus at a preferred, 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 the magnitude of neuronal firing rate deviations is revealing of the contents of working memory as it determines performance. SIGNIFICANCE STATEMENTThe neural basis of working memory and the areas mediating this function is a topic of controversy. Persistent activity in the prefrontal cortex has traditionally been thought to be the neural correlate of working memory, however recent studies have proposed alternative mechanisms and brain areas. Here we show that persistent activity in both the dorsolateral prefrontal cortex and posterior parietal cortex predicts behavior in a working memory task that requires a categorical judgement. Our results offer support to the idea that a network of neurons in both areas act as an attractor network that maintains information in working memory, which informs behavior.

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