Temporal multiplexing of perception and memory codes in IT cortex

A central assumption of neuroscience is that long-term memories are represented by the same brain areas that encode sensory stimuli1. Neurons in inferotemporal (IT) cortex represent the sensory percept of visual objects using a distributed axis code2-4. Whether and how the same IT neural population represents the long-term memory of visual objects remains unclear. Here we examined how familiar faces are encoded in the IT anterior medial face patch (AM), perirhinal face patch (PR) and temporal pole face patch (TP). In AM and PR we observed that the encoding axis for familiar faces is rotated relative to that for unfamiliar faces at long latency; in TP this memory-related rotation was much weaker. Contrary to previous claims, the relative response magnitude to familiar versus unfamiliar faces was not a stable indicator of familiarity in any patch5-11. The mechanism underlying the memory-related axis change is likely intrinsic to IT cortex, because inactivation of PR did not affect axis change dynamics in AM. Overall, our results suggest that memories of familiar faces are represented in AM and perirhinal cortex by a distinct long-latency code, explaining how the same cell population can encode both the percept and memory of faces.

Paying attention to natural scenes in area V1

Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. We hypothesized that attentional and contextual signals interact in V1 in a manner that primarily benefits the representation of natural stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes, but not by synthetic stimuli lacking higher-order statistical regularities. Population analysis revealed that neuronal responses converged to a low-dimensional subspace only for natural stimuli. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the natural-scene subspace, indicating an alignment between the attentional and natural stimulus variance. These results suggest that attentional and contextual signals interact in V1 in a manner optimized for natural vision.

Uncovering the fast, directional signal flow through the human temporal pole during semantic processing

The temporal pole (TP) plays a central role in semantic memory, yet its neural machinery is unknown. Intracerebral recordings in patients discriminating visually the gender or actions of an actor, yielded gender discrimination responses in the ventrolateral (VL) and tip (T) regions of right TP. Granger causality revealed task-specific signals travelling first forward from VL to T, under control of orbitofrontal cortex (OFC) and neighboring prefrontal cortex, and then, strongly, backwards from T to VL. Many other cortical regions provided inputs to or received outputs from both TP regions, often with longer delays, with ventral temporal afferents to VL signaling the actor's physical appearance. The TP response timing reflected more that of the connections to VL, controlled by OFC, than that of the input leads themselves. Thus, visual evidence for gender categories, collected by VL, activates category labels in T, and consequently, category features in VL, indicating a two-stage representation of semantic categories in TP.

Conversion of concept-specific decision confidence into integrative introspection in primates

Introspection based on the integration of uncertain evidence is critical for acting upon abstract thinking and imagining future scenarios. However, it is unknown how confidence read-outs from multiple sources of different concepts are integrated, especially considering the relationships among the concepts. In this study, monkeys performed wagering based on an estimation of their performance in a preceding mnemonic decision. We found that the longer the response times for post-decision wagering, the more relieved the impairments having been caused by frontal disruption. This suggests the existence of a time-consuming compensatory metacognitive process. We found posterior inferior parietal lobe (pIPL) as its candidate, which was not coding the wagering per se (i.e., just high bet or low bet), but became more active when monkeys successfully chose the optimal bet option based on mnemonic decision performance. Thereafter, the pIPL prompts dorsal anterior cingulate cortex to carry the chosen wagering option. Our findings suggest a role for the pIPL in metacognitive concept integration.

Operating principles of the cerebral cortex as a six-layered network in primates: beyond the classic canonical circuit model

The cerebral cortex performs its computations with many six-layered fundamental units, collectively spreading along the cortical sheet. What is the local network structure and the operating dynamics of such a fundamental unit? Previous investigations of primary sensory areas revealed a classic "canonical" circuit model, leading to an expectation of similar circuit organization and dynamics throughout the cortex. This review clarifies the different circuit dynamics at play in the higher association cortex of primates that implements computation for high-level cognition such as memory and attention. Instead of feedforward processing of response selectivity through Layers 4 to 2/3 that the classic canonical circuit stipulates, memory recall in primates occurs in Layer 5/6 with local backward projection to Layer 2/3, after which the retrieved information is sent back from Layer 6 to lower-level cortical areas for further retrieval of nested associations of target attributes. In this review, a novel "dynamic multimode module (D3M)" in the primate association cortex is proposed, as a new "canonical" circuit model performing this operation.

Memory retrieval dynamics and storage capacity of a modular network model of association cortex with featural decomposition

The primate heteromodal cortex presents an evident functional modularity at a mesoscopic level, with physiological and anatomical evidence pointing to it as likely substrate of long-term memory. In order to investigate some of its properties, a model of multimodular autoassociator is studied. Each of the many modules represents a neocortical functional ensemble of recurrently connected neurons and operates as a Hebbian autoassociator, storing a number of local features which it can recall upon cue. The global memory patterns are made of combinations of features sparsely distributed across the modules. Intermodular connections are modelled as a finite-connectivity random graph. Any pair of features in any respective pair of modules is allowed to be involved in several memory patterns; the coarse-grained modular network dynamics is defined in such a way as to overcome the consequent ambiguity of associations. Effects of long-range homeostatic synaptic scaling on network performance are also assessed. The dynamical process of cued retrieval almost saturates a natural upper bound while producing negligible spurious activation. The extent of finite-size effects on storage capacity is quantitatively evaluated. In the limit of infinite size, the functional relationship between storage capacity and number of features per module reduces to that which other authors found by methods from equilibrium statistical mechanics, which suggests that the origin of the functional form is of a combinatorial nature. In contrast with its apparent inevitability at intramodular level, long-range synaptic scaling results to be of minor relevance to both retrieval and storage capacity, casting doubt on its existence in the neocortex. A conjecture is also posited about how statistical fluctuation of connectivity across the network may underpin spontaneous emergence of semantic hierarchies through learning.

Recurrent dynamics in the cerebral cortex: Integration of sensory evidence with stored knowledge

Current concepts of sensory processing in the cerebral cortex emphasize serial extraction and recombination of features in hierarchically structured feed-forward networks in order to capture the relations among the components of perceptual objects. These concepts are implemented in convolutional deep learning networks and have been validated by the astounding similarities between the functional properties of artificial systems and their natural counterparts. However, cortical architectures also display an abundance of recurrent coupling within and between the layers of the processing hierarchy. This massive recurrence gives rise to highly complex dynamics whose putative function is poorly understood. Here a concept is proposed that assigns specific functions to the dynamics of cortical networks and combines, in a unifying approach, the respective advantages of recurrent and feed-forward processing. It is proposed that the priors about regularities of the world are stored in the weight distributions of feed-forward and recurrent connections and that the high-dimensional, dynamic space provided by recurrent interactions is exploited for computations. These comprise the ultrafast matching of sensory evidence with the priors covertly represented in the correlation structure of spontaneous activity and the context-dependent grouping of feature constellations characterizing natural objects. The concept posits that information is encoded not only in the discharge frequency of neurons but also in the precise timing relations among the discharges. Results of experiments designed to test the predictions derived from this concept support the hypothesis that cerebral cortex exploits the high-dimensional recurrent dynamics for computations serving predictive coding.

Perirhinal circuits for memory processing

The perirhinal cortex (PRC) serves as the gateway to the hippocampus for episodic memory formation and plays a part in retrieval through its backward connectivity to various neocortical areas. First, I present the evidence suggesting that PRC neurons encode both experientially acquired object features and their associative relations. Recent studies have revealed circuit mechanisms in the PRC for the retrieval of cue-associated information, and have demonstrated that, in monkeys, PRC neuron-encoded information can be behaviourally read out. These studies, among others, support the theory that the PRC converts visual representations of an object into those of its associated features and initiates backward-propagating, interareal signalling for retrieval of nested associations of object features that, combined, extensionally represent the object meaning. I propose that the PRC works as the ventromedial hub of a 'two-hub model' at an apex of the hierarchy of a distributed memory network and integrates signals encoded in other downstream cortical areas that support diverse aspects of knowledge about an object.

Recency memory effects in Macaques during sequential delayed match-to-sample task with visual noise

Visual object recognition requires both visual sensory information and memory, and its mechanisms are often studied using old-world monkeys. Wittig et al. (2014, 2016) reported that Rhesus monkeys and humans seem to adopt different strategies in a short-term visual memory task. The Rhesus monkeys seemed to rely on recency of stimulus repetition, whereas humans relied on specific memorization. We conducted experiments using a sequential delayed match-to-sample task with random dot visual noise using Rhesus and Japanese monkeys and found that recency effect was observed in both species. There were differences in the noise effect on behavioral performances across species.

Dorsolateral prefrontal neurons mediate subjective decisions and their variation in humans

Subjective decisions play a vital role in human behavior because, while often grounded in fact, they are inherently based on personal beliefs that can vary broadly within and between individuals. While these properties set subjective decisions apart from many other sensorimotor processes and are of wide sociological impact, their single-neuronal basis in humans is unknown. Here we find cells in the dorsolateral prefrontal cortex (dlPFC) that reflect variations in the subjective decisions of humans when performing opinion-based tasks. These neurons changed their activities gradually as the participants transitioned between choice options but also reflected their unique point of conversion at equipoise. Focal disruption of the dlPFC, by contrast, diminished gradation between opposing decisions but had little effect on sensory perceptual choices or their motor report. These findings suggest that the human dlPFC plays an important role in subjective decisions and propose a mechanism for mediating their variation during opinion formation.

Dynamic laminar rerouting of inter-areal mnemonic signal by cognitive operations in primate temporal cortex

Execution of cognitive functions is orchestrated by a brain-wide network comprising multiple regions. However, it remains elusive whether the cortical laminar pattern of inter-areal interactions exhibits dynamic routings, depending on cognitive operations. We address this issue by simultaneously recording neuronal activities from area 36 and area TE of the temporal cortex while monkeys performed a visual cued-recall task. We identify dynamic laminar routing of the inter-areal interaction: during visual processing of a presented cue, spiking activities of area 36 neurons are preferentially coherent with local field potentials at the supragranular layer of area TE, while the signal from the same neurons switches to target the infragranular layer of area TE during memory retrieval. This layer-dependent signal represents the to-be-recalled object, and has an impact on the local processing at the supragranular layer in both cognitive operations. Thus, cortical layers form a key structural basis for dynamic switching of cognitive operations.

Inter-areal interaction has been shown to support various cognitive functions. Here, the authors report that neurons in area 36 flexibly synchronize their activity with different layers of area TE within different epochs of a visually cued recall task suggesting dynamic rerouting of information.

Encoding of long-term associations through neural unitization in the human medial temporal lobe

Besides decades of research showing the role of the medial temporal lobe (MTL) in memory and the encoding of associations, the neural substrates underlying these functions remain unknown. We identified single neurons in the human MTL that responded to multiple and, in most cases, associated stimuli. We observed that most of these neurons exhibit no differences in their spike and local field potential (LFP) activity associated with the individual response-eliciting stimuli. In addition, LFP responses in the theta band preceded single neuron responses by ~70 ms, with the single trial phase providing fine tuning of the spike response onset. We postulate that the finding of similar neuronal responses to associated items provides a simple and flexible way of encoding memories in the human MTL, increasing the effective capacity for memory storage and successful retrieval.

In this work, the authors recorded single neurons and field potentials from the human medial temporal lobe (MTL) and show indistinguishable responses to associated stimuli. This coding mechanism provides a simple and flexible way of encoding memories in the human MTL.

Perceptual processing in the ventral visual stream requires area TE but not rhinal cortex

There is an on-going debate over whether area TE, or the anatomically adjacent rhinal cortex, is the final stage of visual object processing. Both regions have been implicated in visual perception, but their involvement in non-perceptual functions, such as short-term memory, hinders clear-cut interpretation. Here, using a two-interval forced choice task without a short-term memory demand, we find that after bilateral removal of area TE, monkeys trained to categorize images based on perceptual similarity (morphs between dogs and cats), are, on the initial viewing, badly impaired when given a new set of images. They improve markedly with a small amount of practice but nonetheless remain moderately impaired indefinitely. The monkeys with bilateral removal of rhinal cortex are, under all conditions, indistinguishable from unoperated controls. We conclude that the final stage of the integration of visual perceptual information into object percepts in the ventral visual stream occurs in area TE.

What Is the Evidence for Inter-laminar Integration in a Prefrontal Cortical Minicolumn?

The objective of this perspective article is to examine columnar inter-laminar integration during the executive control of behavior. The integration hypothesis posits that perceptual and behavioral signals are integrated within the prefrontal cortical inter-laminar microcircuits. Inter-laminar minicolumnar activity previously recorded from the dorsolateral prefrontal cortex (dlPFC) of nonhuman primates, trained in a visual delay match-to-sample (DMS) task, was re-assessed from an integrative perspective. Biomorphic multielectrode arrays (MEAs) played a unique role in the in vivo recording of columnar cell firing in the dlPFC layers 2/3 and 5/6. Several integrative aspects stem from these experiments: 1. Functional integration of perceptual and behavioral signals across cortical layers during executive control. The integrative effect of dlPFC minicolumns was shown by: (i) increased correlated firing on correct vs. error trials; (ii) decreased correlated firing when the number of non-matching images increased; and (iii) similar spatial firing preference across cortical-striatal cells during spatial-trials, and less on object-trials. 2. Causal relations to integration of cognitive signals by the minicolumnar turbo-engines. The inter-laminar integration between the perceptual and executive circuits was facilitated by stimulating the infra-granular layers with firing patterns obtained from supra-granular layers that enhanced spatial preference of percent correct performance on spatial trials. 3. Integration across hierarchical levels of the brain. The integration of intention signals (visual spatial, direction) with movement preparation (timing, velocity) in striatum and with the motor command and posture in midbrain is also discussed. These findings provide evidence for inter-laminar integration of executive control signals within brain's prefrontal cortical microcircuits.

Information Accumulation over Time in Monkey Inferior Temporal Cortex Neurons Explains Pattern Recognition Reaction Time under Visual Noise

We recognize objects even when they are partially degraded by visual noise. We studied the relation between the amount of visual noise (5, 10, 15, 20, or 25%) degrading 8 black-and-white stimuli and stimulus identification in 2 monkeys performing a sequential delayed match-to-sample task. We measured the accuracy and speed with which matching stimuli were identified. The performance decreased slightly (errors increased) as the amount of visual noise increased for both monkeys. The performance remained above 80% correct, even with 25% noise. However, the reaction times markedly increased as the noise increased, indicating that the monkeys took progressively longer to decide what the correct response would be as the amount of visual noise increased, showing that the monkeys trade time to maintain accuracy. Thus, as time unfolds the monkeys act as if they are accumulating the information and/or testing hypotheses about whether the test stimulus is likely to be a match for the sample being held in short-term memory. We recorded responses from 13 single neurons in area TE of the 2 monkeys. We found that stimulus-selective information in the neuronal responses began accumulating when the match stimulus appeared. We found that the greater the amount of noise obscuring the test stimulus, the more slowly stimulus-related information by the 13 neurons accumulated. The noise induced slowing was about the same for both behavior and information. These data are consistent with the hypothesis that area TE neuron population carries information about stimulus identity that accumulates over time in such a manner that it progressively overcomes the signal degradation imposed by adding visual noise.

Large-scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions

KEY POINTS

There have been few systematic population-wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions. In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single-unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task. The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony. Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions. The strength of spike synchrony between two neurons was statistically independent of the spike rate-based preferences of the pair for behavioural functions.

ABSTRACT

Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population-wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular-spiking (putatively excitatory) and fast-spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single-unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external-trigger trials) or spontaneously without any cue (internal-trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular-spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population-wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate-based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large-scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement.

Laminar Module Cascade from Layer 5 to 6 Implementing Cue-to-Target Conversion for Object Memory Retrieval in the Primate Temporal Cortex

The cerebral cortex computes through the canonical microcircuit that connects six stacked layers; however, how cortical processing streams operate in vivo, particularly in the higher association cortex, remains elusive. By developing a novel MRI-assisted procedure that reliably localizes recorded single neurons at resolution of six individual layers in monkey temporal cortex, we show that transformation of representations from a cued object to a to-be-recalled object occurs at the infragranular layer in a visual cued-recall task. This cue-to-target conversion started in layer 5 and was followed by layer 6. Finally, a subset of layer 6 neurons exclusively encoding the sought target became phase-locked to surrounding field potentials at theta frequency, suggesting that this coordinated cell assembly implements cortical long-distance outputs of the recalled target. Thus, this study proposes a link from local computation spanning laminar modules of the temporal cortex to the brain-wide network for memory retrieval in primates.

Associative-memory representations emerge as shared spatial patterns of theta activity spanning the primate temporal cortex

Highly localized neuronal spikes in primate temporal cortex can encode associative memory; however, whether memory formation involves area-wide reorganization of ensemble activity, which often accompanies rhythmicity, or just local microcircuit-level plasticity, remains elusive. Using high-density electrocorticography, we capture local-field potentials spanning the monkey temporal lobes, and show that the visual pair-association (PA) memory is encoded in spatial patterns of theta activity in areas TE, 36, and, partially, in the parahippocampal cortex, but not in the entorhinal cortex. The theta patterns elicited by learned paired associates are distinct between pairs, but similar within pairs. This pattern similarity, emerging through novel PA learning, allows a machine-learning decoder trained on theta patterns elicited by a particular visual item to correctly predict the identity of those elicited by its paired associate. Our results suggest that the formation and sharing of widespread cortical theta patterns via learning-induced reorganization are involved in the mechanisms of associative memory representation.

Correlations and Neuronal Population Information

Brain function involves the activity of neuronal populations. Much recent effort has been devoted to measuring the activity of neuronal populations in different parts of the brain under various experimental conditions. Population activity patterns contain rich structure, yet many studies have focused on measuring pairwise relationships between members of a larger population-termed noise correlations. Here we review recent progress in understanding how these correlations affect population information, how information should be quantified, and what mechanisms may give rise to correlations. As population coding theory has improved, it has made clear that some forms of correlation are more important for information than others. We argue that this is a critical lesson for those interested in neuronal population responses more generally: Descriptions of population responses should be motivated by and linked to well-specified function. Within this context, we offer suggestions of where current theoretical frameworks fall short.

Remapping of memory encoding and retrieval networks: insights from neuroimaging in primates

Advancements in neuroimaging techniques have allowed for the investigation of the neural correlates of memory functions in the whole human brain. Thus, the involvement of various cortical regions, including the medial temporal lobe (MTL) and posterior parietal cortex (PPC), has been repeatedly reported in the human memory processes of encoding and retrieval. However, the functional roles of these sites could be more fully characterized utilizing nonhuman primate models, which afford the potential for well-controlled, finer-scale experimental procedures that are inapplicable to humans, including electrophysiology, histology, genetics, and lesion approaches. Yet, the presence and localization of the functional counterparts of these human memory-related sites in the macaque monkey MTL or PPC were previously unknown. Therefore, to bridge the inter-species gap, experiments were required in monkeys using functional magnetic resonance imaging (fMRI), the same methodology adopted in human studies. Here, we briefly review the history of experimentation on memory systems using a nonhuman primate model and our recent fMRI studies examining memory processing in monkeys performing recognition memory tasks. We will discuss the memory systems common to monkeys and humans and future directions of finer cell-level characterization of memory-related processes using electrophysiological recording and genetic manipulation approaches.

The transition in the ventral stream from feature to real-world entity representations

We propose that the ventral visual pathway of human and non-human primates is organized into three levels: (1) ventral retinotopic cortex including what is known as TEO in the monkey but corresponds to V4A and PITd/v, and the phPIT cluster in humans, (2) area TE in the monkey and its homolog LOC and neighboring fusiform regions, and more speculatively, (3) TGv in the monkey and its possible human equivalent, the temporal pole. We attribute to these levels the visual representations of features, partial real-world entities (RWEs), and known, complete RWEs, respectively. Furthermore, we propose that the middle level, TE and its homolog, is organized into three parallel substreams, lower bank STS, dorsal convexity of TE, and ventral convexity of TE, as are their corresponding human regions. These presumably process shape in depth, 2D shape and material properties, respectively, to construct RWE representations.

Long-term recordings improve the detection of weak excitatory-excitatory connections in rat prefrontal cortex

Characterization of synaptic connectivity is essential to understanding neural circuit dynamics. For extracellularly recorded spike trains, indirect evidence for connectivity can be inferred from short-latency peaks in the correlogram between two neurons. Despite their predominance in cortex, however, significant interactions between excitatory neurons (E) have been hard to detect because of their intrinsic weakness. By taking advantage of long duration recordings, up to 25 h, from rat prefrontal cortex, we found that 7.6% of the recorded pyramidal neurons are connected. This corresponds to ∼70% of the local E-E connection probability that has been reported by paired intracellular recordings (11.6%). This value is significantly higher than previous reports from extracellular recordings, but still a substantial underestimate. Our analysis showed that long recording times and strict significance thresholds are necessary to detect weak connections while avoiding false-positive results, but will likely still leave many excitatory connections undetected. In addition, we found that hyper-reciprocity of connections in prefrontal cortex that was shown previously by paired intracellular recordings was only present in short-distance, but not in long distance (∼300 micrometers or more) interactions. As hyper-reciprocity is restricted to local clusters, it might be a minicolumnar effect. Given the current surge of interest in very high-density neural spike recording (e.g., NIH BRAIN Project) it is of paramount importance that we have statistically reliable methods for estimating connectivity from cross-correlation analysis available. We provide an important step in this direction.

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function.

Cortico-basal ganglia networks subserving goal-directed behavior mediated by conditional visuo-goal association

Action is often executed according to information provided by a visual signal. As this type of behavior integrates two distinct neural representations, perception and action, it has been thought that identification of the neural mechanisms underlying this process will yield deeper insights into the principles underpinning goal-directed behavior. Based on a framework derived from conditional visuomotor association, prior studies have identified neural mechanisms in the dorsal premotor cortex (PMd), dorsolateral prefrontal cortex (dlPFC), ventrolateral prefrontal cortex (vlPFC), and basal ganglia (BG). However, applications resting solely on this conceptualization encounter problems related to generalization and flexibility, essential processes in executive function, because the association mode involves a direct one-to-one mapping of each visual signal onto a particular action. To overcome this problem, we extend this conceptualization and postulate a more general framework, conditional visuo-goal association. According to this new framework, the visual signal identifies an abstract behavioral goal, and an action is subsequently selected and executed to meet this goal. Neuronal activity recorded from the four key areas of the brains of monkeys performing a task involving conditional visuo-goal association revealed three major mechanisms underlying this process. First, visual-object signals are represented primarily in the vlPFC and BG. Second, all four areas are involved in initially determining the goals based on the visual signals, with the PMd and dlPFC playing major roles in maintaining the salience of the goals. Third, the cortical areas play major roles in specifying action, whereas the role of the BG in this process is restrictive. These new lines of evidence reveal that the four areas involved in conditional visuomotor association contribute to goal-directed behavior mediated by conditional visuo-goal association in an area-dependent manner.