Working memory control dynamics follow principles of spatial computing

Unraveling the roles of spatial working memory sustained and selective neurons in prefrontal cortex

The heart of goal-directed behavior organization is working memory. Recent studies have emphasized the critical role of the prefrontal cortex (PFC) in working memory, highlighting elevated spiking levels in PFC neurons during working-memory delays. As a higher-order cortex, PFC contains various types of neurons with complex receptive fields, making it challenging to identify task-engaged neurons, particularly during the working memory periods when firing rates are lower compared to stimulus periods. While previous studies have primarily focused on neurons selective for sensory stimuli, there are also task-sustained neurons that are not selective for specific stimulus characteristics. In this study, we differentiate between working memory (WM)-sustained neurons, which show task-related activity without stimulus spatial selectivity, and working memory (WM)-selective neurons, which are selective for the location of the stimulus. To investigate their roles, we investigated the neural activities of the lateral PFC neurons in two macaque monkeys during a spatial working memory task. Fano factor analysis revealed that the neuronal variability of both WM-selective and WM-sustained neurons was similar and significantly higher than that of non-active neurons (neurons not modulated by the task). Moreover, the Fano factor of active neurons diminished during error trials compared to correct trials. The spike phase locking (SPL) value was measured to evaluate the coupling of local field potentials (LFPs) phases to spike times, considering neural network characteristics. SPL results indicated that both WM-selective neurons and WM-sustained neurons exhibited higher SPL in the alpha/beta-band compared to non-active neurons. Additionally, the alpha/beta-band SPL of working memory-active neurons decreased during error trials. In summary, despite the non-stimulus-specific activation of WM-sustained neurons, they may contribute to task performance alongside WM-selective neurons.

Orbitofrontal High-Gamma Reflects Spike-Dissociable Value and Decision Mechanisms

The orbitofrontal cortex (OFC) plays a crucial role in value-based decisions. While much is known about how OFC neurons represent values, far less is known about information encoded in OFC local field potentials (LFPs). LFPs are important because they can reflect subthreshold activity not directly coupled to spiking and because they are potential targets for less invasive forms of brain-machine interface (BMI). We recorded neural activity in the OFC of male macaques performing a two-option value-based decision task. We compared the value- and decision-coding properties of high-gamma LFPs (HG, 50-150 Hz) to the coding properties of spiking multiunit activity (MUA) recorded concurrently on the same electrodes. HG and MUA both represented the values of decision targets, but HG signals had value-coding features that were distinct from concurrently measured MUA. On average HG amplitude increased monotonically with value, whereas in MUA the value encoding was net neutral on average. HG encoded a signal consistent with a comparison between target values, a signal which was negligible in MUA. In individual channels, HG could predict choice outcomes more accurately than MUA; however, when channels were combined in a population-based decoder, MUA was more accurate than HG. In summary, HG signals reveal value-coding features in OFC that could not be observed from spiking activity, including representation of value comparisons and more accurate behavioral predictions. These results have implications for the role of OFC in value-based decisions and suggest that high-frequency LFPs may be a viable-or even preferable-target for BMIs to assist cognitive function.

Memory States From Almost Nothing: Representing and Computing in a Nonassociative Algebra

This letter presents a nonassociative algebraic framework for the representation and computation of information items in high-dimensional space. This framework is consistent with the principles of spatial computing and with the empirical findings in cognitive science about memory. Computations are performed through a process of multiplication-like binding and nonassociative interference-like bundling. Models that rely on associative bundling typically lose order information, which necessitates the use of auxiliary order structures, such as position markers, to represent sequential information that is important for cognitive tasks. In contrast, the nonassociative bundling proposed allows the construction of sparse representations of arbitrarily long sequences that maintain their temporal structure across arbitrary lengths. In this operation, noise is a constituent element of the representation of order information rather than a means of obscuring it. The nonassociative nature of the proposed framework results in the representation of a single sequence by two distinct states. The L-state, generated through left-associative bundling, continuously updates and emphasizes a recency effect, while the R-state, formed through right-associative bundling, encodes finite sequences or chunks, capturing a primacy effect. The construction of these states may be associated with activity in the prefrontal cortex in relation to short-term memory and hippocampal encoding in long-term memory, respectively. The accuracy of retrieval is contingent on a decision-making process that is based on the mutual information between the memory states and the cue. The model is able to replicate the serial position curve, which reflects the empirical recency and primacy effects observed in cognitive experiments.

Home-Cage Training for Non-Human Primates: An Opportunity to Reduce Stress and Study Natural Behavior in Neurophysiology Experiments

Research involving non-human primates remains a cornerstone in fields such as biomedical research and systems neuroscience. However, the daily routines of laboratory work can induce stress in these animals, potentially compromising their well-being and the reliability of experimental outcomes. To address this, many laboratories have adopted home-cage training protocols to mitigate stress caused by routine procedures such as transport and restraint-a factor that can impact both macaque physiology and experimental validity. This review explores the primary methods and experimental setups employed in home-cage training, highlighting their potential not only to address ethical concerns surrounding animal welfare but also to reduce training time and risks for the researchers. Furthermore, by combining home-cage training with wireless recordings, it becomes possible to expand research opportunities in behavioral neurophysiology with non-human primates. This approach enables the study of various cognitive processes in more naturalistic settings, thereby increasing the ecological validity of scientific findings through innovative experimental designs that thoroughly investigate the complexity of the animals' natural behavior.

Interictal network dysfunction and cognitive impairment in epilepsy

Epilepsy is diagnosed when neural networks become capable of generating excessive or hypersynchronous activity patterns that result in observable seizures. In many cases, epilepsy is associated with cognitive comorbidities that persist between seizures and negatively impact quality of life. Dysregulation of the coordinated physiological network interactions that are required for cognitive function has been implicated in mediating these enduring symptoms, but the causal mechanisms are often elusive. Here, we provide an overview of neural network abnormalities with the potential to contribute to cognitive dysfunction in epilepsy. We examine these pathological interactions across spatial and temporal scales, additionally highlighting the dynamics that arise in response to the brain's intrinsic capacity for plasticity. Understanding these processes will facilitate development of network-level interventions to address cognitive comorbidities that remain undertreated by currently available epilepsy therapeutics.

Oscillatory control over representational geometry of sequence working memory in macaque frontal cortex

To process sequential streams of information, e.g., language, the brain must encode multiple items in sequence working memory (SWM) according to their ordinal relationship. While the geometry of neural states could represent sequential events in the frontal cortex, the control mechanism over these neural states remains unclear. Using high-throughput electrophysiology recording in the macaque frontal cortex, we observed widespread theta responses after each stimulus entry. Crucially, by applying targeted dimensionality reduction to extract task-relevant neural subspaces from both local field potential (LFP) and spike data, we found that theta power transiently encoded each sequentially presented stimulus regardless of its order. At the same time, theta-spike interaction was rank-selectively associated with memory subspaces, thereby potentially supporting the binding of items to appropriate ranks. Furthermore, this putative theta control can generalize to length-variable and error sequences, predicting behavior. Thus, decomposed entry/rank-WM subspaces and theta-spike interactions may underlie the control of SWM.

Working memory needs pointers

Cognitive neuroscience has converged on a definition of working memory (WM) as a capacity-limited system that maintains highly accessible representations via stimulus-specific neural patterns. We argue that this standard definition may be incomplete. We highlight the fundamental need to recognize specific instances or tokens and to bind those tokens to the surrounding context. We propose that contextual binding is supported by spatiotemporal 'pointers' and that pointers are the source of neural signals that track the number of stored items, independent of their content. These content-independent pointers may provide a productive perspective for understanding item-based capacity limits in WM and the role of WM as a gateway for long-term storage.

Touch-evoked traveling waves establish a translaminar spacetime code

Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked traveling waves and underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a late wave that lasted hundreds of milliseconds poststimulus. Notably, late waves were modulated by perceived value and predicted behavioral choice in a two-whisker discrimination task. We found that the late wave feature was (i) modulated by motor feedback, (ii) differentially engaged a sparse ensemble reactivation pattern across layer 2/3, which a balanced-state network model reconciled via feedback-induced inhibitory stabilization, and (iii) aligned to regenerative layer 5 apical dendritic Ca2+ events. Our results reveal that translaminar spacetime patterns organized by cortical feedback support sparse touch-evoked traveling waves.

Effects of high-intensity interval training and moderate-intensity continuous training on neural dynamics and firing in the CA1-MEC region of mice

The aim of this study is to investigate the differential impacts of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on neural circuit dynamics and neuronal firing in the hippocampal CA1 subregion (CA1) region and medial entorhinal cortex (MEC) of mice. Forty-two male ICR mice were randomized into control, HIIT, and MICT groups. Electrophysiological recordings were performed pre- and postintervention to assess neural circuit dynamics and neuronal firing patterns in the CA1-MEC pathway. Both exercise protocols increased local field potential (LFP) coherence, with MICT showing a more pronounced effect on δ and γ coherences (P < 0.05). Both modalities reduced δ power spectral density (PSD) (HIIT, P < 0.05; MICT, P < 0.01) and elevated θ, β, and γ PSDs. Neuronal firing frequency improved in both CA1 and MEC following HIIT and MICT (P < 0.05). HIIT enhanced firing regularity in CA1 (P < 0.05), whereas MICT improved regularity in both regions (P < 0.05). Both protocols reduced firing latency (HIIT, P < 0.05; MICT, P < 0.01) and enhanced burst firing ratio, interburst interval (IBI), burst duration (BD), and LFP phase locking (P < 0.05 or P < 0.01). Notably, MICT significantly improved spatial working memory and novel recognition abilities, as evidenced by increased novel arm time, entries, and preference index (P < 0.01). This study reveals that both HIIT and MICT positively impact neural processing and information integration in the CA1-MEC network of mice. Notably, MICT exhibits a more pronounced impact on neural functional connectivity and cognitive function compared with HIIT. These findings, coupled with the similarities in hippocampal electrophysiological characteristics between rodents and humans, suggest potential exercise-mediated neural plasticity and cognitive benefits in humans.NEW & NOTEWORTHY This study is the first to investigate HIIT and MICT's effects on neural activity in the mouse CA1-MEC circuit, demonstrating that exercise modulates processing, enhances integration, and boosts cognitive performance. Due to similar hippocampal electrophysiology in rodents and humans during movement and navigation, our findings suggest implications for human brain neural changes, advancing the understanding of neurophysiological mechanisms underlying exercise-cognition interactions and informing exercise recommendations for cognitive health.

Prefrontal cortex contribution in transitive inference task through the interplay of beta and gamma oscillations

Transitive inference allows people to infer new relations between previously experienced premises. It has been hypothesized that this logical thinking relies on a mental schema that spatially organizes elements, facilitating inferential insights. However, recent evidence challenges the need for these complex cognitive processes. To dig into the neural substrate driving TI cognitive processes, we examine the role of beta and gamma local field potential bands in the prefrontal cortex of 2 monkeys. During the inferential problem-solving period, we discover a tight link between beta and gamma bands modulation and TI complexity. This correlation diminishes its strength before initiating the motor response, indicating the chosen item. Notably, while the beta band maintains a constant relationship with TI performance throughout the trial, the gamma band shows a flexible relationship. This research highlights the role of beta and gamma interplay in cognitive computations when solving TI problems.

Is working memory domain-general or domain-specific?

Given the fundamental role of working memory (WM) in all domains of cognition, a central question has been whether WM is domain-general. However, the term 'domain-general' has been used in different, and sometimes misleading, ways. By reviewing recent evidence and biologically plausible models of WM, we show that the level of domain-generality varies substantially between three facets of WM: in terms of computations, WM is largely domain-general. In terms of neural correlates, it contains both domain-general and domain-specific elements. Finally, in terms of application, it is mostly domain-specific. This variance encourages a shift of focus towards uncovering domain-general computational principles and away from domain-general approaches to the analysis of individual differences and WM training, favoring newer perspectives, such as training-as-skill-learning.

Multimodal neuroimaging of hierarchical cognitive control

Cognitive control enables us to translate our knowledge into actions, allowing us to flexibly adjust our behavior, according to environmental contexts, our internal goals, and future plans. Multimodal neuroimaging and neurostimulation techniques have proven essential for advancing our understanding of how cognitive control emerges from the coordination of distributed neuronal activities in the brain. In this review, we examine the literature on multimodal studies of cognitive control. We explore how these studies provide converging evidence for a novel, multiplexed model of cognitive control, in which neural oscillations support different levels of control processing along a functionally hierarchical organization of distinct frontoparietal networks.

Distinct functions for beta and alpha bursts in gating of human working memory

Multiple neural mechanisms underlying gating to working memory have been proposed with divergent results obtained in human and animal studies. Previous findings from non-human primates suggest prefrontal beta frequency bursts as a correlate of transient inhibition during selective encoding. Human studies instead suggest a similar role for sensory alpha power fluctuations. To cast light on these discrepancies we employed a sequential working memory task with distractors for human participants. In particular, we examined their whole-brain electrophysiological activity in both alpha and beta bands with the same single-trial burst analysis earlier performed on non-human primates. Our results reconcile earlier findings by demonstrating that both alpha and beta bursts in humans correlate with the filtering and control of memory items, but with region and task-specific differences between the two rhythms. Occipital beta burst patterns were selectively modulated during the transition from sensory processing to memory retention whereas prefrontal and parietal beta bursts tracked sequence order and were proactively upregulated prior to upcoming target encoding. Occipital alpha bursts instead increased during the actual presentation of unwanted sensory stimuli. Source reconstruction additionally suggested the involvement of striatal and thalamic alpha and beta. Thus, specific whole-brain burst patterns correlate with different aspects of working memory control.

Cell Type-Specific Profiles and Developmental Trajectories of Transcriptomes in Primate Prefrontal Layer 3 Pyramidal Neurons: Implications for Schizophrenia

OBJECTIVE

In schizophrenia, impaired working memory is associated with transcriptome alterations in layer 3 pyramidal neurons (L3PNs) in the dorsolateral prefrontal cortex (DLPFC). Distinct subtypes of L3PNs that send axonal projections to the DLPFC in the opposite hemisphere (callosal projection [CP] neurons) or the parietal cortex in the same hemisphere (ipsilateral projection [IP] neurons) play critical roles in working memory. However, how the transcriptomes of these L3PN subtypes might shift during late postnatal development when working memory impairments emerge in individuals later diagnosed with schizophrenia is not known. The aim of this study was to characterize and compare the transcriptome profiles of CP and IP L3PNs across developmental transitions from prepuberty to adulthood in macaque monkeys.

METHODS

The authors used retrograde labeling to identify CP and IP L3PNs in the DLPFC of prepubertal, postpubertal, and adult macaque monkeys, and used laser microdissection to capture these neurons for RNA sequencing.

RESULTS

At all three ages, CP and IP L3PNs had distinct transcriptomes, with the number of genes differentially expressed between neuronal subtypes increasing with age. For IP L3PNs, age-related shifts in gene expression were most prominent between prepubertal and postpubertal animals, whereas for CP L3PNs such shifts were most prominent between postpubertal and adult animals.

CONCLUSIONS

These findings demonstrate the presence of cell type-specific profiles and developmental trajectories of the transcriptomes of PPC-projecting IP and DLPFC-projecting CP L3PNs in monkey DLPFC. The evidence that IP L3PNs reach a mature transcriptome earlier than CP L3PNs suggests that these two subtypes differentially contribute to the maturation of working memory performance across late postnatal development and that they may be differentially vulnerable to the disease process of schizophrenia at specific stages of postnatal development.

Maintenance of delay-period activity in working memory task is modulated by local network structure

Revealing the relationship between neural network structure and function is one central theme of neuroscience. In the context of working memory (WM), anatomical data suggested that the topological structure of microcircuits within WM gradient network may differ, and the impact of such structural heterogeneity on WM activity remains unknown. Here, we proposed a spiking neural network model that can replicate the fundamental characteristics of WM: delay-period neural activity involves association cortex but not sensory cortex. First, experimentally observed receptor expression gradient along the WM gradient network is reproduced by our network model. Second, by analyzing the correlation between different local structures and duration of WM activity, we demonstrated that small-worldness, excitation-inhibition balance, and cycle structures play crucial roles in sustaining WM-related activity. To elucidate the relationship between the structure and functionality of neural networks, structural circuit gradients in brain should also be subject to further measurement. Finally, combining anatomical data, we simulated the duration of WM activity across different brain regions, its maintenance relies on the interaction between local and distributed networks. Overall, network structural gradient and interaction between local and distributed networks are of great significance for WM.

Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory

The computational resources of a neuromorphic network model introduced earlier were investigated in the first paper of this series. It was argued that a form of ubiquitous spontaneous local convolution enabled logical gate-like neural motifs to form into hierarchical feed-forward structures of the Hubel-Wiesel type. Here we investigate concomitant data-like structures and their dynamic rôle in memory formation, retrieval, and replay. The mechanisms give rise to the need for general inhibitory sculpting, and the simulation of the replay of episodic memories, well known in humans and recently observed in rats. Other consequences include explanations of such findings as the directional flows of neural waves in memory formation and retrieval, visual anomalies and memory deficits in schizophrenia, and the operation of GABA agonist drugs in suppressing episodic memories. We put forward the hypothesis that all neural logical operations and feature extractions are of the convolutional hierarchical type described here and in the earlier paper, and exemplified by the Hubel-Wiesel model of the visual cortex, but that in more general cases the precise geometric layering might be obscured and so far undetected.

Mixed selectivity: Cellular computations for complexity

The property of mixed selectivity has been discussed at a computational level and offers a strategy to maximize computational power by adding versatility to the functional role of each neuron. Here, we offer a biologically grounded implementational-level mechanistic explanation for mixed selectivity in neural circuits. We define pure, linear, and nonlinear mixed selectivity and discuss how these response properties can be obtained in simple neural circuits. Neurons that respond to multiple, statistically independent variables display mixed selectivity. If their activity can be expressed as a weighted sum, then they exhibit linear mixed selectivity; otherwise, they exhibit nonlinear mixed selectivity. Neural representations based on diverse nonlinear mixed selectivity are high dimensional; hence, they confer enormous flexibility to a simple downstream readout neural circuit. However, a simple neural circuit cannot possibly encode all possible mixtures of variables simultaneously, as this would require a combinatorially large number of mixed selectivity neurons. Gating mechanisms like oscillations and neuromodulation can solve this problem by dynamically selecting which variables are mixed and transmitted to the readout.

Beta: bursts of cognition

Beta oscillations are linked to the control of goal-directed processing of sensory information and the timing of motor output. Recent evidence demonstrates they are not sustained but organized into intermittent high-power bursts mediating timely functional inhibition. This implies there is a considerable moment-to-moment variation in the neural dynamics supporting cognition. Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions. Recent method advances reveal diversity in beta bursts that provide deeper insights into their function and the underlying neural circuit activity motifs. We propose that brain-wide, spatiotemporal patterns of beta bursting reflect various cognitive operations and that their dynamics reveal nonlinear aspects of cortical processing.

Cognition is an emergent property

Cognition relies on the flexible organization of neural activity. In this discussion, we explore how many aspects of this organization can be described as emergent properties, not reducible to their constituent parts. We discuss how electrical fields in the brain can serve as a medium for propagating activity nearly instantaneously, and how population-level patterns of neural activity can organize computations through subspace coding.

Simultaneous oscillatory encoding of "hot" and "cold" information during social interactions in the monkey medial prefrontal cortex

Social interactions in primates require social cognition abilities such as anticipating the partner's future choices as well as pure cognitive skills involving processing task-relevant information. The medial prefrontal cortex (mPFC) has been implicated in these cognitive processes. Here, we investigated the neural oscillations underlying the complex social behaviors involving the interplay of social roles (Actor vs. Observer) and interaction types (whether working with a "Good" or "Bad" partner). We found opposite power modulations of the beta and gamma bands by social roles, indicating dedicated processing for task-related information. Concurrently, the interaction type was conveyed by lower frequencies, which are commonly associated with neural circuits linked to performance and reward monitoring. Thus, the mPFC exhibits parallel coding of both "cold" processes (purely cognitive) and "hot" processes (reward and social-related). This allocation of neural resources gives the mPFC a key neural node, flexibly integrating multiple sources of information during social interactions.

An integrative view of the role of prefrontal cortex in consciousness

The involvement of the prefrontal cortex (PFC) in consciousness is an ongoing focus of intense investigation. An important question is whether representations of conscious contents and experiences in the PFC are confounded by post-perceptual processes related to cognitive functions. Here, I review recent findings suggesting that neuronal representations of consciously perceived contents-in the absence of post-perceptual processes-can indeed be observed in the PFC. Slower ongoing fluctuations in the electrophysiological state of the PFC seem to control the stability and updates of these prefrontal representations of conscious awareness. In addition to conscious perception, the PFC has been shown to play a critical role in controlling the levels of consciousness as observed during anesthesia, while prefrontal lesions can result in severe loss of perceptual awareness. Together, the convergence of these processes in the PFC suggests its integrative role in consciousness and highlights the complex nature of consciousness itself.

A Translaminar Spacetime Code Supports Touch-Evoked Traveling Waves

Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked cortical traveling waves and their underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a variable late wave that lasted hundreds of milliseconds post-stimulus. Strikingly, late-wave dynamics were modulated by stimulus value and correlated with task performance. Mechanistically, the late wave component was i) modulated by motor feedback, ii) complemented by a sparse ensemble pattern across layer 2/3, which a balanced-state network model reconciled via inhibitory stabilization, and iii) aligned to regenerative Layer-5 apical dendritic Ca 2+ events. Our results reveal a translaminar spacetime pattern organized by cortical feedback in the sensory cortex that supports touch-evoked traveling waves.

GRAPHICAL ABSTRACT AND HIGHLIGHTS

Whisker touch evokes both early- and late-traveling waves in the barrel cortex over 100's of millisecondsReward reinforcement modulates wave dynamics Late wave emergence coincides with network sparsity in L23 and time-locked L5 dendritic Ca 2+ spikes Experimental and computational results link motor feedback to distinct translaminar spacetime patterns.

Alpha phase-coding supports feature binding during working memory maintenance

The ability to successfully retain and manipulate information in working memory (WM) requires that objects' individual features are bound into cohesive representations; yet, the mechanisms supporting feature binding remain unclear. Binding (or swap) errors, where memorized features are erroneously associated with the wrong object, can provide a window into the intrinsic limits in capacity of WM that represent a key bottleneck in our cognitive ability. We tested the hypothesis that binding in WM is accomplished via neural phase synchrony and that swap errors result from perturbations in this synchrony. Using magnetoencephalography data collected from human subjects in a task designed to induce swap errors, we showed that swaps are characterized by reduced phase-locked oscillatory activity during memory retention, as predicted by an attractor model of spiking neural networks. Further, we found that this reduction arises from increased phase-coding variability in the alpha-band over a distributed network of sensorimotor areas. Our findings demonstrate that feature binding in WM is accomplished through phase-coding dynamics that emerge from the competition between different memories.

Multiplexed Levels of Cognitive Control through Delta and Theta Neural Oscillations

Cognitive control allows behavior to be guided according to environmental contexts and internal goals. During cognitive control tasks, fMRI analyses typically reveal increased activation in frontal and parietal networks, and EEG analyses reveal increased amplitude of neural oscillations in the delta/theta band (2-3, 4-7 Hz) in frontal electrodes. Previous studies proposed that theta-band activity reflects the maintenance of rules associating stimuli to appropriate actions (i.e., the rule set), whereas delta synchrony is specifically associated with the control over the context for when to apply a set of rules (i.e., the rule abstraction). We tested these predictions using EEG and fMRI data collected during the performance of a hierarchical cognitive control task that manipulated the level of abstraction of task rules and their set-size. Our results show a clear separation of delta and theta oscillations in the control of rule abstraction and of stimulus-action associations, respectively, in distinct frontoparietal association networks. These findings support a model by which frontoparietal networks operate through dynamic, multiplexed neural processes.

The prefrontal cortex: from monkey to man

The prefrontal cortex is so important to human beings that, if deprived of it, our behaviour is reduced to action-reactions and automatisms, with no ability to make deliberate decisions. Why does the prefrontal cortex hold such importance in humans? In answer, this review draws on the proximity between humans and other primates, which enables us, through comparative anatomical-functional analysis, to understand the cognitive functions we have in common and specify those that distinguish humans from their closest cousins. First, a focus on the lateral region of the prefrontal cortex illustrates the existence of a continuum between rhesus monkeys (the most studied primates in neuroscience) and humans for most of the major cognitive functions in which this region of the brain plays a central role. This continuum involves the presence of elementary mental operations in the rhesus monkey (e.g. working memory or response inhibition) that are constitutive of 'macro-functions' such as planning, problem-solving and even language production. Second, the human prefrontal cortex has developed dramatically compared to that of other primates. This increase seems to concern the most anterior part (the frontopolar cortex). In humans, the development of the most anterior prefrontal cortex is associated with three major and interrelated cognitive changes: (i) a greater working memory capacity, allowing for greater integration of past experiences and prospective futures; (ii) a greater capacity to link discontinuous or distant data, whether temporal or semantic; and (iii) a greater capacity for abstraction, allowing humans to classify knowledge in different ways, to engage in analogical reasoning or to acquire abstract values that give rise to our beliefs and morals. Together, these new skills enable us, among other things, to develop highly sophisticated social interactions based on language, enabling us to conceive beliefs and moral judgements and to conceptualize, create and extend our vision of our environment beyond what we can physically grasp. Finally, a model of the transition of prefrontal functions between humans and non-human primates concludes this review.