Reward association affects neuronal responses to visual stimuli in macaque te and perirhinal cortices

Gaze differences in configural and elemental evaluation during multi-attribute decision-making

Introduction

While many everyday choices are between multi-attribute options, how attribute values are integrated to allow such choices remains unclear. Recent findings suggest a distinction between elemental (attribute-by-attribute) and configural (holistic) evaluation of multi-attribute options, with different neural substrates. Here, we asked if there are behavioral or gaze pattern differences between these putatively distinct modes of multi-attribute decision-making.

Methods

Thirty-nine healthy men and women learned the monetary values of novel multi-attribute pseudo-objects (fribbles) and then made choices between pairs of these objects while eye movements were tracked. Value was associated with individual attributes in the elemental condition, and with unique combinations of attributes in the configural condition. Choice, reaction time, gaze fixation time on options and individual attributes, and within- and between-option gaze transitions were recorded.

Results

There were systematic behavioral differences between elemental and configural conditions. Elemental trials had longer reaction times and more between-option transitions, while configural trials had more within-option transitions. The effect of last fixation on choice was more pronounced in the configural condition.

Discussion

We observed differences in gaze patterns and the influence of last fixation location on choice in multi-attribute value-based choices depending on how value is associated with those attributes. This adds support for the claim that multi-attribute option values may emerge either elementally or holistically, reminiscent of similar distinctions in multi-attribute object recognition. This may be important to consider in neuroeconomics research that involve visually-presented complex objects.

Sequential involvements of the perirhinal cortex and hippocampus in the recall of item-location associative memory in macaques

The standard consolidation theory suggests that the hippocampus (HPC) is critically involved in acquiring new memory, while storage and recall gradually become independent of it. Converging studies have shown separate involvements of the perirhinal cortex (PRC) and parahippocampal cortex (PHC) in item and spatial processes, whereas HPC relates the item to a spatial context. These 2 strands of literature raise the following question; which brain region is involved in the recall process of item-location associative memory? To solve this question, this study applied an item-location associative (ILA) paradigm in a single-unit study of nonhuman primates. We trained 2 macaques to associate 4 visual item pairs with 4 locations on a background map in an allocentric manner before the recording sessions. In each trial, 1 visual item and the map image at a tilt (-90° to 90°) were sequentially presented as the item-cue and the context-cue, respectively. The macaques chose the item-cue location relative to the context-cue by positioning their gaze. Neurons in the PRC, PHC, and HPC, but not area TE, exhibited item-cue responses which signaled retrieval of item-location associative memory. This retrieval signal first appeared in the PRC, followed by the HPC and PHC. We examined whether neural representations of the retrieved locations were related to the external space that the macaques viewed. A positive representation similarity was found in the HPC and PHC, but not in the PRC, thus suggesting a contribution of the HPC to relate the retrieved location from the PRC with a first-person perspective of the subjects and provide the self-referenced retrieved location to the PHC. These results imply distinct but complementary contributions of the PRC and HPC to recall of item-location associative memory that can be used across multiple spatial contexts.

A Preferential Role for Ventromedial Prefrontal Cortex in Assessing "the Value of the Whole" in Multiattribute Object Evaluation

Everyday decision-making commonly involves assigning values to complex objects with multiple value-relevant attributes. Drawing on object recognition theories, we hypothesized two routes to multiattribute evaluation: assessing the value of the whole object based on holistic attribute configuration or summing individual attribute values. In two samples of healthy human male and female participants undergoing eye tracking and functional magnetic resonance imaging (fMRI) while evaluating novel pseudo objects, we found evidence for both forms of evaluation. Fixations to and transitions between attributes differed systematically when the value of pseudo objects was associated with individual attributes or attribute configurations. Ventromedial prefrontal cortex (vmPFC) and perirhinal cortex were engaged when configural processing was required. These results converge with our recent findings that individuals with vmPFC lesions were impaired in decisions requiring configural evaluation but not when evaluating the sum of the parts. This suggests that multiattribute decision-making engages distinct evaluation mechanisms relying on partially dissociable neural substrates, depending on the relationship between attributes and value.SIGNIFICANCE STATEMENT Decision neuroscience has only recently begun to address how multiple choice-relevant attributes are brought together during evaluation and choice among complex options. Object recognition research makes a crucial distinction between individual attribute and holistic/configural object processing, but how the brain evaluates attributes and whole objects remains unclear. Using fMRI and eye tracking, we found that the vmPFC and the perirhinal cortex contribute to value estimation specifically when value was related to whole objects, that is, predicted by the unique configuration of attributes and not when value was predicted by the sum of individual attribute values. This perspective on the interactions between subjective value and object processing mechanisms provides a novel bridge between the study of object recognition and reward-guided decision-making.

Dynamic coordination of the perirhinal cortical neurons supports coherent representations between task epochs

Cortical neurons show distinct firing patterns across multiple task epochs characterized by different computations. Recent studies suggest that such distinct patterns underlie dynamic population code achieving computational flexibility, whereas neurons in some cortical areas often show coherent firing patterns across epochs. To understand how coherent single-neuron code contributes to dynamic population code, we analyzed neural responses in the rat perirhinal cortex (PRC) during cue and reward epochs of a two-alternative forced-choice task. We found that the PRC neurons often encoded the opposite choice directions between those epochs. By using principal component analysis as a population-level analysis, we identified neural subspaces associated with each epoch, which reflected coordination across the neurons. The cue and reward epochs shared neural dimensions where the choice directions were consistently discriminated. Interestingly, those dimensions were supported by dynamically changing contributions of the individual neurons. These results demonstrated heterogeneity of coherent single-neuron representations in their contributions to population code.

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.

Gustatory responses in macaque monkeys revealed with fMRI: Comments on taste, taste preference, and internal state

Studies of the neural mechanisms underlying value-based decision making typically employ food or fluid rewards to motivate subjects to perform cognitive tasks. Rewards are often treated as interchangeable, but it is well known that the specific tastes of foods and fluids and the values associated with their taste sensations influence choices and contribute to overall levels of food consumption. Accordingly, we characterized the gustatory system in three macaque monkeys (Macaca mulatta) and examined whether gustatory responses were modulated by preferences and hydration status. To identify taste-responsive cortex, we delivered small quantities (0.1 ml) of sucrose (sweet), citric acid (sour), or distilled water in random order without any predictive cues while scanning monkeys using event-related fMRI. Neural effects were evaluated by using each session in each monkey as a data point in a second-level analysis. By contrasting BOLD responses to sweet and sour tastes with those from distilled water in a group level analysis, we identified taste responses in primary gustatory cortex area G, an adjacent portion of the anterior insular cortex, and prefrontal cortex area 12o. Choice tests administered outside the scanner revealed that all three monkeys strongly preferred sucrose to citric acid or water. BOLD responses in the ventral striatum, ventral pallidum, and amygdala reflected monkeys' preferences, with greater BOLD responses to sucrose than citric acid. Finally, we examined the influence of hydration level by contrasting BOLD responses to receipt of fluids when monkeys were thirsty and after ad libitum water consumption. BOLD responses in area G and area 12o in the left hemisphere were greater following full hydration. By contrast, BOLD responses in portions of medial frontal cortex were reduced after ad libitum water consumption. These findings highlight brain regions involved in representing taste, taste preference and internal state.

Learned Value Shapes Responses to Objects in Frontal and Ventral Stream Networks in Macaque Monkeys

We have an incomplete picture of how the brain links object representations to reward value, and how this information is stored and later retrieved. The orbitofrontal cortex (OFC), medial frontal cortex (MFC), and ventrolateral prefrontal cortex (VLPFC), together with the amygdala, are thought to play key roles in these processes. There is an apparent discrepancy, however, regarding frontal areas thought to encode value in macaque monkeys versus humans. To address this issue, we used fMRI in macaque monkeys to localize brain areas encoding recently learned image values. Each week, monkeys learned to associate images of novel objects with a high or low probability of water reward. Areas responding to the value of recently learned reward-predictive images included MFC area 10 m/32, VLPFC area 12, and inferior temporal visual cortex (IT). The amygdala and OFC, each thought to be involved in value encoding, showed little such effect. Instead, these 2 areas primarily responded to visual stimulation and reward receipt, respectively. Strong image value encoding in monkey MFC compared with OFC is surprising, but agrees with results from human imaging studies. Our findings demonstrate the importance of VLPFC, MFC, and IT in representing the values of recently learned visual images.

First-Pass Processing of Value Cues in the Ventral Visual Pathway

Real-world value often depends on subtle, continuously variable visual cues specific to particular object categories, like the tailoring of a suit, the condition of an automobile, or the construction of a house. Here, we used microelectrode recording in behaving monkeys to test two possible mechanisms for category-specific value-cue processing: (1) previous findings suggest that prefrontal cortex (PFC) identifies object categories, and based on category identity, PFC could use top-down attentional modulation to enhance visual processing of category-specific value cues, providing signals to PFC for calculating value, and (2) a faster mechanism would be first-pass visual processing of category-specific value cues, immediately providing the necessary visual information to PFC. This, however, would require learned mechanisms for processing the appropriate cues in a given object category. To test these hypotheses, we trained monkeys to discriminate value in four letter-like stimulus categories. Each category had a different, continuously variable shape cue that signified value (liquid reward amount) as well as other cues that were irrelevant. Monkeys chose between stimuli of different reward values. Consistent with the first-pass hypothesis, we found early signals for category-specific value cues in area TE (the final stage in monkey ventral visual pathway) beginning 81 ms after stimulus onset-essentially at the start of TE responses. Task-related activity emerged in lateral PFC approximately 40 ms later and consisted mainly of category-invariant value tuning. Our results show that, for familiar, behaviorally relevant object categories, high-level ventral pathway cortex can implement rapid, first-pass processing of category-specific value cues.

Temporal-prefrontal cortical network for discrimination of valuable objects in long-term memory

Remembering and discriminating objects based on their previously learned values are essential for goal-directed behaviors. While the cerebral cortex is known to contribute to object recognition, surprisingly little is known about its role in retaining long-term object-value associations. To address this question, we trained macaques to arbitrarily associate small or large rewards with many random fractal objects (>100) and then used fMRI to study the long-term retention of value-based response selectivity across the brain. We found a pronounced long-term value memory in core subregions of temporal and prefrontal cortex where, several months after training, fractals previously associated with high reward ("good" stimuli) elicited elevated fMRI responses compared with those associated with low reward ("bad" stimuli). Similar long-term value-based modulation was also observed in subregions of the striatum, amygdala, and claustrum, but not in the hippocampus. The value-modulated temporal-prefrontal subregions showed strong resting-state functional connectivity to each other. Moreover, for areas outside this core, the magnitude of long-term value responses was predicted by the strength of resting-state functional connectivity to the core subregions. In separate testing, free-viewing gaze behavior indicated that the monkeys retained stable long-term memory of object value. These results suggest an implicit and high-capacity memory mechanism in the temporal-prefrontal circuitry and its associated subcortical regions for long-term retention of object-value memories that can guide value-oriented behavior.

Flexible and Stable Value Coding Areas in Caudate Head and Tail Receive Anatomically Distinct Cortical and Subcortical Inputs

Anatomically distinct areas within the basal ganglia encode flexible- and stable-value memories for visual objects (Hikosaka et al., 2014), but an important question remains: do they receive inputs from the same or different brain areas or neurons? To answer this question, we first located flexible and stable value-coding areas in the caudate head (CDh) and caudate tail (CDt) of two rhesus macaque monkeys, and then injected different retrograde tracers into these areas of each monkey. We found that CDh and CDt received different inputs from several cortical and subcortical areas including temporal cortex, prefrontal cortex, cingulate cortex, amygdala, claustrum and thalamus. Superior temporal cortex and inferior temporal cortex projected to both CDh and CDt, with more CDt-projecting than CDh-projecting neurons. In superior temporal cortex and dorsal inferior temporal cortex, layers 3 and 5 projected to CDh while layers 3 and 6 projected to CDt. Prefrontal and cingulate cortex projected mostly to CDh bilaterally, less to CDt unilaterally. A cluster of neurons in the basolateral amygdala projected to CDt. Rostral-dorsal claustrum projected to CDh while caudal-ventral claustrum projected to CDt. Within the thalamus, different nuclei projected to either CDh or CDt. The medial centromedian nucleus and lateral parafascicular nucleus projected to CDt while the medial parafascicular nucleus projected to CDh. The inferior pulvinar and lateral dorsal nuclei projected to CDt. The ventral anterior and medial dorsal nuclei projected to CDh. We found little evidence of neurons projecting to both CDh and CDt across the brain. These data suggest that CDh and CDt can control separate functions using anatomically separate circuits. Understanding the roles of these striatal projections will be important for understanding how value memories are created and stored.

Emergence of visually-evoked reward expectation signals in dopamine neurons via the superior colliculus in V1 lesioned monkeys

Responses of midbrain dopamine (DA) neurons reflecting expected reward from sensory cues are critical for reward-based associative learning. However, critical pathways by which reward-related visual information is relayed to DA neurons remain unclear. To address this question, we investigated Pavlovian conditioning in macaque monkeys with unilateral primary visual cortex (V1) lesions (an animal model of ‘blindsight’). Anticipatory licking responses to obtain juice drops were elicited in response to visual conditioned stimuli (CS) in the affected visual field. Subsequent pharmacological inactivation of the superior colliculus (SC) suppressed the anticipatory licking. Concurrent single unit recordings indicated that DA responses reflecting the reward expectation could be recorded in the absence of V1, and that these responses were also suppressed by SC inactivation. These results indicate that the subcortical visual circuit can relay reward-predicting visual information to DA neurons and integrity of the SC is necessary for visually-elicited classically conditioned responses after V1 lesion.

DOI:http://dx.doi.org/10.7554/eLife.24459.001

To survive and thrive, animals must learn to approach cues in their environment that are likely to lead to a desirable outcome and avoid those that might lead them to harm. A group of brain regions known as the midbrain dopamine system helps many animals to achieve this. Dopamine is the brain’s reward signal. Cues that predict rewards, such as the sight or smell of food, activate midbrain dopamine neurons. However, the details of this process remained unclear.

Takakuwa et al. have now examined how visual information that signals reward reaches the midbrain dopamine neurons. The anatomy of the visual system suggests two main possibilities. Information may travel directly from the eyes to an area of the midbrain called the superior colliculus, and then onto the dopamine neurons. Alternatively, information may travel to the midbrain indirectly via a pathway that includes additional processing in the brain’s outer layer, the visual cortex.

To distinguish between these routes, Takakuwa et al. studied monkeys in which the indirect pathway via the visual cortex had been damaged. Some people with damage to this pathway have a disorder called blindsight. They are able to detect the movement or location of stimuli, but they cannot consciously see those stimuli. The monkeys with damage to visual cortex were able to learn that an image on a screen predicted the delivery of fruit juice. After repeated trials, the monkeys began to lick the spout dispensing the juice whenever the image appeared, even if no juice was delivered. The monkeys’ midbrain dopamine neurons also sent more signals in response to the images, and showed greater activity when the images predicted large rewards than small ones. Takakuwa et al. next inactivated the superior colliculus with a drug and showed that this prevented both the licking behavior and the increased signaling.

Together the findings show that visual information about potential rewards can reach midbrain dopamine neurons via a direct route through the superior colliculus, without needing to pass via the visual cortex. The next step is to determine how and when the visual cortex may get involved in this process to help animals maximize rewards.

DOI:http://dx.doi.org/10.7554/eLife.24459.002

Representation of Functional Category in the Monkey Prefrontal Cortex and Its Rule-Dependent Use for Behavioral Selection

Humans, monkeys, and other animals are considered to have the cognitive ability to use functional categories--that is, stimulus groups based on functional equivalence independent of physical properties. To investigate the underlying neural mechanisms of the use of functional categories, we recorded single-unit activity in the prefrontal cortex of monkeys performing a behavioral task in which the rule-dependent usage of functional category was needed to select an appropriate response. We found a neural correlate of functional categories on the single-neuron level and found that category information is coded independently of other task-relevant information such as rule and contingency information. Analysis of the time course of the information activation suggested that contingency information used for action selection is derived by integrating incoming category information with rule information maintained throughout a session. Such neural computation can be considered as the neural background of flexible behavioral control based on category and rule.

Finding and Not Finding Rat Perirhinal Neuronal Responses to Novelty

There is much evidence that the perirhinal cortex of both rats and monkeys is important for judging the relative familiarity of visual stimuli. In monkeys many studies have found that a proportion of perirhinal neurons respond more to novel than familiar stimuli. There are fewer studies of perirhinal neuronal responses in rats, and those studies based on exploration of objects, have raised into question the encoding of stimulus familiarity by rat perirhinal neurons. For this reason, recordings of single neuronal activity were made from the perirhinal cortex of rats so as to compare responsiveness to novel and familiar stimuli in two different behavioral situations. The first situation was based upon that used in “paired viewing” experiments that have established rat perirhinal differences in immediate early gene expression for novel and familiar visual stimuli displayed on computer monitors. The second situation was similar to that used in the spontaneous object recognition test that has been widely used to establish the involvement of rat perirhinal cortex in familiarity discrimination. In the first condition 30 (25%) of 120 perirhinal neurons were visually responsive; of these responsive neurons 19 (63%) responded significantly differently to novel and familiar stimuli. In the second condition eight (53%) of 15 perirhinal neurons changed activity significantly in the vicinity of objects (had “object fields”); however, for none (0%) of these was there a significant activity change related to the familiarity of an object, an incidence significantly lower than for the first condition. Possible reasons for the difference are discussed. It is argued that the failure to find recognition‐related neuronal responses while exploring objects is related to its detectability by the measures used, rather than the absence of all such signals in perirhinal cortex. Indeed, as shown by the results, such signals are found when a different methodology is used. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.

Dopamine reward prediction-error signalling: a two-component response

Environmental stimuli and objects, including rewards, are often processed sequentially in the brain. Recent work suggests that the phasic dopamine reward prediction-error response follows a similar sequential pattern. An initial brief, unselective and highly sensitive increase in activity unspecifically detects a wide range of environmental stimuli, then quickly evolves into the main response component, which reflects subjective reward value and utility. This temporal evolution allows the dopamine reward prediction-error signal to optimally combine speed and accuracy.

Reward functions of the basal ganglia

Besides their fundamental movement function evidenced by Parkinsonian deficits, the basal ganglia are involved in processing closely linked non-motor, cognitive and reward information. This review describes the reward functions of three brain structures that are major components of the basal ganglia or are closely associated with the basal ganglia, namely midbrain dopamine neurons, pedunculopontine nucleus, and striatum (caudate nucleus, putamen, nucleus accumbens). Rewards are involved in learning (positive reinforcement), approach behavior, economic choices and positive emotions. The response of dopamine neurons to rewards consists of an early detection component and a subsequent reward component that reflects a prediction error in economic utility, but is unrelated to movement. Dopamine activations to non-rewarded or aversive stimuli reflect physical impact, but not punishment. Neurons in pedunculopontine nucleus project their axons to dopamine neurons and process sensory stimuli, movements and rewards and reward-predicting stimuli without coding outright reward prediction errors. Neurons in striatum, besides their pronounced movement relationships, process rewards irrespective of sensory and motor aspects, integrate reward information into movement activity, code the reward value of individual actions, change their reward-related activity during learning, and code own reward in social situations depending on whose action produces the reward. These data demonstrate a variety of well-characterized reward processes in specific basal ganglia nuclei consistent with an important function in non-motor aspects of motivated behavior.

Neural representation for object recognition in inferotemporal cortex

We suggest that population representation of objects in inferotemporal cortex lie on a continuum between a purely structural, parts-based description and a purely holistic description. The intrinsic dimensionality of object representation is estimated to be around 100, perhaps with lower dimensionalities for object representations more toward the holistic end of the spectrum. Cognitive knowledge in the form of semantic information and task information feed back to inferotemporal cortex from perirhinal and prefrontal cortex respectively, providing high-level multimodal-based expectations that assist in the interpretation of object stimuli. Integration of object information across eye movements may also contribute to object recognition through a process of active vision.

Components and characteristics of the dopamine reward utility signal

Rewards are defined by their behavioral functions in learning (positive reinforcement), approach behavior, economic choices, and emotions. Dopamine neurons respond to rewards with two components, similar to higher order sensory and cognitive neurons. The initial, rapid, unselective dopamine detection component reports all salient environmental events irrespective of their reward association. It is highly sensitive to factors related to reward and thus detects a maximal number of potential rewards. It also senses aversive stimuli but reports their physical impact rather than their aversiveness. The second response component processes reward value accurately and starts early enough to prevent confusion with unrewarded stimuli and objects. It codes reward value as a numeric, quantitative utility prediction error, consistent with formal concepts of economic decision theory. Thus, the dopamine reward signal is fast, highly sensitive and appropriate for driving and updating economic decisions.

Acute effects of the designer drugs benzylpiperazine (BZP) and trifluoromethylphenylpiperazine (TFMPP) using functional magnetic resonance imaging (fMRI) and the Stroop task--a pilot study

RATIONALE

A novel group of designer drugs containing benzylpiperazine (BZP) and/or trifluoromethylphenylpiperazine (TFMPP) have been available worldwide for more than a decade; however, their effects on human brain function have not been extensively described.

OBJECTIVES

In a double-blind, placebo-controlled crossover study, the acute effects of BZP and TFMPP (alone and in combination) on the neural networks involved in executive function were investigated using an event-related Stroop functional magnetic resonance imaging (fMRI) paradigm.

METHODS

Thirteen healthy participants aged 18-40 years undertook the Stroop task 90 min after taking an oral dose of either BZP (200 mg), TFMPP (either 50 or 60 mg), BZP + TFMPP (100 + 30 mg) or placebo. A change in activity in neural regions reflects an increase in local demand for oxygen, due to an increase in neuronal activity.

RESULTS

Relative to placebo, an increase in neural activation was observed in the dorsal striatum following BZP, and in the thalamus following TFMPP, when performing the Stroop task.

CONCLUSION

These data suggest that additional compensatory resources were recruited to maintain performance during the Stroop task. When BZP and TFMPP were administered together, both the dorsal striatum and thalamus were activated. However, the combination of BZP/TFMPP attenuated activation in the caudate, possibly due to TFMPP's indirect effects on dopamine release via 5HT2C receptors.

Neuronal Reward and Decision Signals: From Theories to Data

Rewards are crucial objects that induce learning, approach behavior, choices, and emotions. Whereas emotions are difficult to investigate in animals, the learning function is mediated by neuronal reward prediction error signals which implement basic constructs of reinforcement learning theory. These signals are found in dopamine neurons, which emit a global reward signal to striatum and frontal cortex, and in specific neurons in striatum, amygdala, and frontal cortex projecting to select neuronal populations. The approach and choice functions involve subjective value, which is objectively assessed by behavioral choices eliciting internal, subjective reward preferences. Utility is the formal mathematical characterization of subjective value and a prime decision variable in economic choice theory. It is coded as utility prediction error by phasic dopamine responses. Utility can incorporate various influences, including risk, delay, effort, and social interaction. Appropriate for formal decision mechanisms, rewards are coded as object value, action value, difference value, and chosen value by specific neurons. Although all reward, reinforcement, and decision variables are theoretical constructs, their neuronal signals constitute measurable physical implementations and as such confirm the validity of these concepts. The neuronal reward signals provide guidance for behavior while constraining the free will to act.

Time context of cue-outcome associations represented by neurons in perirhinal cortex

The perirhinal cortex (PRh), which has extensive connections with diverse brain sites, may contribute to semantic memory by associating various types of information about objects. However, the extent of the types of associations in which PRh participates is unknown. In the present study, we let monkeys experience a consistent contingency between visual cues and different types of outcomes (water reward and sound-only acknowledgment) in a particular time context for many days and then recorded neuronal activities from PRh and area TE, which is the major source of visual inputs to PRh. We found that PRh cells represented the outcome type in their responses to the visual cues only in the time context in which the monkeys had experienced the cue-outcome contingency. In contrast, TE cells represented the outcome information whenever the cue appeared (i.e., independently from the related time context). These results showed that PRh cells represented not only the cue-outcome contingency but also the time context in which the monkeys had experienced the contingency. We conclude that PRh is not specific to the representation of sensory and associative properties of objects themselves but may represent broader information about objects, including the time context in which the objects are associated with particular outcomes.

Neural correlates of object-associated choice behavior in the perirhinal cortex of rats

The perirhinal cortex (PRC) is reportedly important for object recognition memory, with supporting physiological evidence obtained largely from primate studies. Whether neurons in the rodent PRC also exhibit similar physiological correlates of object recognition, however, remains to be determined. We recorded single units from the PRC in a PRC-dependent, object-cued spatial choice task in which, when cued by an object image, the rat chose the associated spatial target from two identical discs appearing on a touchscreen monitor. The firing rates of PRC neurons were significantly modulated by critical events in the task, such as object sampling and choice response. Neuronal firing in the PRC was correlated primarily with the conjunctive relationships between an object and its associated choice response, although some neurons also responded to the choice response alone. However, we rarely observed a PRC neuron that represented a specific object exclusively regardless of spatial response in rats, although the neurons were influenced by the perceptual ambiguity of the object at the population level. Some PRC neurons fired maximally after a choice response, and this post-choice feedback signal significantly enhanced the neuronal specificity for the choice response in the subsequent trial. Our findings suggest that neurons in the rat PRC may not participate exclusively in object recognition memory but that their activity may be more dynamically modulated in conjunction with other variables, such as choice response and its outcomes.

Population coding of affect across stimuli, modalities and individuals

It remains unclear how the brain represents external objective sensory events alongside our internal subjective impressions of them--affect. Representational mapping of population activity evoked by complex scenes and basic tastes in humans revealed a neural code supporting a continuous axis of pleasant-to-unpleasant valence. This valence code was distinct from low-level physical and high-level object properties. Although ventral temporal and anterior insular cortices supported valence codes specific to vision and taste, both the medial and lateral orbitofrontal cortices (OFC) maintained a valence code independent of sensory origin. Furthermore, only the OFC code could classify experienced affect across participants. The entire valence spectrum was represented as a collective pattern in regional neural activity as sensory-specific and abstract codes, whereby the subjective quality of affect can be objectively quantified across stimuli, modalities and people.

Sensory regulation of dopaminergic cell activity: Phenomenology, circuitry and function

Dopaminergic neurons in a range of species are responsive to sensory stimuli. In the anesthetized preparation, responses to non-noxious and noxious sensory stimuli are usually tonic in nature, although long-duration changes in activity have been reported in the awake preparation as well. However, in the awake preparation, short-latency, phasic changes in activity are most common. These phasic responses can occur to unconditioned aversive and non-aversive stimuli, as well as to the stimuli which predict them. In both the anesthetized and awake preparations, not all dopaminergic neurons are responsive to sensory stimuli, however responsive neurons tend to respond to more than a single stimulus modality. Evidence suggests that short-latency sensory information is provided to dopaminergic neurons by relatively primitive subcortical structures - including the midbrain superior colliculus for vision and the mesopontine parabrachial nucleus for pain and possibly gustation. Although short-latency visual information is provided to dopaminergic neurons by the relatively primitive colliculus, dopaminergic neurons can discriminate between complex visual stimuli, an apparent paradox which can be resolved by the recently discovered route of information flow through to dopaminergic neurons from the cerebral cortex, via a relay in the colliculus. Given that projections from the cortex to the colliculus are extensive, such a relay potentially allows the activity of dopaminergic neurons to report the results of complex stimulus processing from widespread areas of the cortex. Furthermore, dopaminergic neurons could acquire their ability to reflect stimulus value by virtue of reward-related modification of sensory processing in the cortex. At the forebrain level, sensory-related changes in the tonic activity of dopaminergic neurons may regulate the impact of the cortex on forebrain structures such as the nucleus accumbens. In contrast, the short latency of the phasic responses to sensory stimuli in dopaminergic neurons, coupled with the activation of these neurons by non-rewarding stimuli, suggests that phasic responses of dopaminergic neurons may provide a signal to the forebrain which indicates that a salient event has occurred (and possibly an estimate of how salient that event is). A stimulus-related salience signal could be used by downstream systems to reinforce behavioral choices.

Cortical regulation of dopaminergic neurons: role of the midbrain superior colliculus

Dopaminergic (DA) neurons respond to stimuli in a wide range of modalities, although the origin of the afferent sensory signals has only recently begun to emerge. In the case of vision, an important source of short-latency sensory information seems to be the midbrain superior colliculus (SC). However, longer-latency responses have been identified that are less compatible with the primitive perceptual capacities of the colliculus. Rather, they seem more in keeping with the processing capabilities of the cortex. Given that there are robust projections from the cortex to the SC, we examined whether cortical information could reach DA neurons via a relay in the colliculus. The somatosensory barrel cortex was stimulated electrically in the anesthetized rat with either single pulses or pulse trains. Although single pulses produced small phasic activations in the colliculus, they did not elicit responses in the majority of DA neurons. However, after disinhibitory intracollicular injections of the GABA_A antagonist bicuculline, collicular responses were substantially enhanced and previously unresponsive DA neurons now exhibited phasic excitations or inhibitions. Pulse trains applied to the cortex led to phasic changes (excitations to inhibitions) in the activity of DA neurons at baseline. These were blocked or attenuated by intracollicular administration of the GABA_A agonist muscimol. Taken together, the results indicate that the cortex can communicate with DA neurons via a relay in the SC. As a consequence, DA neuronal activity reflecting the unexpected occurrence of salient events and that signaling more complex stimulus properties may have a common origin.

Recognition memory and synaptic plasticity in the perirhinal and prefrontal cortices

Work is reviewed that relates recognition memory to studies of synaptic plasticity mechanisms in perirhinal and prefrontal cortices. The aim is to consider evidence that perirhinal cortex and medial prefrontal cortex store rather than merely transmit information necessary for recognition memory and, if so, to consider what mechanisms are potentially available within these cortices for producing such storage through synaptic change. Interventions with known actions on plasticity mechanisms are reviewed in relation to their effects on recognition memory processes. These interventions importantly include those involving antagonism of glutamatergic and cholinergic receptors but also inhibition of plasticity consolidation and expression mechanisms. It is concluded that there is strong evidence that perirhinal cortex is involved in information storage necessary for object recognition memory and, moreover, that such storage involves synaptic weakening mechanisms including the removal of AMPA glutamate receptors from synapses. There is good evidence that medial prefrontal cortex is necessary for associative and temporal order recognition memory and that this cortex expresses plasticity mechanisms that potentially allow the storage of information. However, the case for medial prefrontal cortex acting as a store requires further support.

Reward value-contingent changes of visual responses in the primate caudate tail associated with a visuomotor skill

A goal-directed action aiming at an incentive outcome, if repeated, becomes a skill that may be initiated automatically. We now report that the tail of the caudate nucleus (CDt) may serve to control a visuomotor skill. Monkeys looked at many fractal objects, half of which were always associated with a large reward (high-valued objects) and the other half with a small reward (low-valued objects). After several daily sessions, they developed a gaze bias, looking at high-valued objects even when no reward was associated. CDt neurons developed a response bias, typically showing stronger responses to high-valued objects. In contrast, their responses showed no change when object values were reversed frequently, although monkeys showed a strong gaze bias, looking at high-valued objects in a goal-directed manner. The biased activity of CDt neurons may be transmitted to the oculomotor region so that animals can choose high-valued objects automatically based on stable reward experiences.

Multiphasic temporal dynamics in responses of midbrain dopamine neurons to appetitive and aversive stimuli

The transient response of dopamine neurons has been described as reward prediction error (RPE), with activation or suppression by events that are better or worse than expected, respectively. However, at least a minority of neurons are activated by aversive or high-intensity stimuli, casting doubt on the generality of RPE in describing the dopamine signal. To overcome limitations of previous studies, we studied neuronal responses to a wider variety of high-intensity and aversive stimuli, and we quantified and controlled aversiveness through a choice task in which macaques sacrificed juice to avoid aversive stimuli. Whereas most previous work has portrayed the RPE as a single impulse or "phase," here we demonstrate its multiphasic temporal dynamics. Aversive or high-intensity stimuli evoked a triphasic sequence of activation-suppression-activation extending over a period of 40-700 ms. The initial activation at short latencies (40-120 ms) reflected sensory intensity. The influence of motivational value became dominant between 150 and 250 ms, with activation in the case of appetitive stimuli, and suppression in the case of aversive and neutral stimuli. The previously unreported late activation appeared to be a modest "rebound" after strong suppression. Similarly, strong activation by reward was often followed by suppression. We suggest that these "rebounds" may result from overcompensation by homeostatic mechanisms in some cells. Our results are consistent with a realistic RPE, which evolves over time through a dynamic balance of excitation and inhibition.

Stimulus-related activity during conditional associations in monkey perirhinal cortex neurons depends on upcoming reward outcome

Acquiring the significance of events based on reward-related information is critical for animals to survive and to conduct social activities. The importance of the perirhinal cortex for reward-related information processing has been suggested. To examine whether or not neurons in this cortex represent reward information flexibly when a visual stimulus indicates either a rewarded or unrewarded outcome, neuronal activity in the macaque perirhinal cortex was examined using a conditional-association cued-reward task. The task design allowed us to study how the neuronal responses depended on the animal's prediction of whether it would or would not be rewarded. Two visual stimuli, a color stimulus as Cue1 followed by a pattern stimulus as Cue2, were sequentially presented. Each pattern stimulus was conditionally associated with both rewarded and unrewarded outcomes depending on the preceding color stimulus. We found an activity depending upon the two reward conditions during Cue2, i.e., pattern stimulus presentation. The response appeared after the response dependent upon the image identity of Cue2. The response delineating a specific cue sequence also appeared between the responses dependent upon the identity of Cue2 and reward conditions. Thus, when Cue1 sets the context for whether or not Cue2 indicates a reward, this region represents the meaning of Cue2, i.e., the reward conditions, independent of the identity of Cue2. These results suggest that neurons in the perirhinal cortex do more than associate a single stimulus with a reward to achieve flexible representations of reward information.

Robust representation of stable object values in the oculomotor Basal Ganglia

Our gaze tends to be directed to objects previously associated with rewards. Such object values change flexibly or remain stable. Here we present evidence that the monkey substantia nigra pars reticulata (SNr) in the basal ganglia represents stable, rather than flexible, object values. After across-day learning of object-reward association, SNr neurons gradually showed a response bias to surprisingly many visual objects: inhibition to high-valued objects and excitation to low-valued objects. Many of these neurons were shown to project to the ipsilateral superior colliculus. This neuronal bias remained intact even after >100 d without further learning. In parallel with the neuronal bias, the monkeys tended to look at high-valued objects. The neuronal and behavioral biases were present even if no value was associated during testing. These results suggest that SNr neurons bias the gaze toward objects that were consistently associated with high values in one's history.

Rewards teach visual selective attention

Visual selective attention is the brain function that modulates ongoing processing of retinal input in order for selected representations to gain privileged access to perceptual awareness and guide behavior. Enhanced analysis of currently relevant or otherwise salient information is often accompanied by suppressed processing of the less relevant or salient input. Recent findings indicate that rewards exert a powerful influence on the deployment of visual selective attention. Such influence takes different forms depending on the specific protocol adopted in the given study. In some cases, the prospect of earning a larger reward in relation to a specific stimulus or location biases attention accordingly in order to maximize overall gain. This is mediated by an effect of reward acting as a type of incentive motivation for the strategic control of attention. In contrast, reward delivery can directly alter the processing of specific stimuli by increasing their attentional priority, and this can be measured even when rewards are no longer involved, reflecting a form of reward-mediated attentional learning. As a further development, recent work demonstrates that rewards can affect attentional learning in dissociable ways depending on whether rewards are perceived as feedback on performance or instead are registered as random-like events occurring during task performance. Specifically, it appears that visual selective attention is shaped by two distinct reward-related learning mechanisms: one requiring active monitoring of performance and outcome, and a second one detecting the sheer association between objects in the environment (whether attended or ignored) and the more-or-less rewarding events that accompany them. Overall this emerging literature demonstrates unequivocally that rewards "teach" visual selective attention so that processing resources will be allocated to objects, features and locations which are likely to optimize the organism's interaction with the surrounding environment and maximize positive outcome.

How instructed knowledge modulates the neural systems of reward learning

Recent research in neuroeconomics has demonstrated that the reinforcement learning model of reward learning captures the patterns of both behavioral performance and neural responses during a range of economic decision-making tasks. However, this powerful theoretical model has its limits. Trial-and-error is only one of the means by which individuals can learn the value associated with different decision options. Humans have also developed efficient, symbolic means of communication for learning without the necessity for committing multiple errors across trials. In the present study, we observed that instructed knowledge of cue-reward probabilities improves behavioral performance and diminishes reinforcement learning-related blood-oxygen level-dependent (BOLD) responses to feedback in the nucleus accumbens, ventromedial prefrontal cortex, and hippocampal complex. The decrease in BOLD responses in these brain regions to reward-feedback signals was functionally correlated with activation of the dorsolateral prefrontal cortex (DLPFC). These results suggest that when learning action values, participants use the DLPFC to dynamically adjust outcome responses in valuation regions depending on the usefulness of action-outcome information.

Uncovering the visual "alphabet": advances in our understanding of object perception

The ability to rapidly and accurately recognize visual stimuli represents a significant computational challenge. Yet, despite such complexity, the primate brain manages this task effortlessly. How it does so remains largely a mystery. The study of visual perception and object recognition was once limited to investigations of brain-damaged individuals or lesion experiments in animals. However, in the last 25years, new methodologies, such as functional neuroimaging and advances in electrophysiological approaches, have provided scientists with the opportunity to examine this problem from new perspectives. This review highlights how some of these recent technological advances have contributed to the study of visual processing and where we now stand with respect to our understanding of neural mechanisms underlying object recognition.

Dissociable Neural Effects of Long-term Stimulus–Reward Pairing in Macaque Visual Cortex

It has been proposed that perceptual learning may occur through a reinforcement process, in which consistently pairing stimuli with reward is sufficient for learning. We tested whether stimulus–reward pairing is sufficient to increase the sensorial representation of a stimulus by recording local field potentials (LFPs) in macaque extrastriate area V4 with chronically implanted electrodes. Two oriented gratings were repeatedly presented; one was paired with a fluid reward, whereas no reward was given at any other time. During the course of conditioning the LFP increased for the rewarded compared to the unrewarded orientation. The time course of the effect of stimulus–reward pairing and its reversal differed between an early and late interval of the LFP response: a fast change in the later part of the neural response that was dissociated from a slower change in the early part of the response. The fast change of the late interval LFP suggests that this late LFP change is related to enhanced attention during the presentation of the rewarded stimulus. The slower time course of the early interval response suggests an effect of sensorial learning. Thus, simple stimulus–reward pairing is sufficient to strengthen stimulus representations in visual cortex and does this by means of two dissociable mechanisms.

A computational model of Basal Ganglia and its role in memory retrieval in rewarded visual memory tasks

Visual working memory (WM) tasks involve a network of cortical areas such as inferotemporal, medial temporal and prefrontal cortices. We suggest here to investigate the role of the basal ganglia (BG) in the learning of delayed rewarded tasks through the selective gating of thalamocortical loops. We designed a computational model of the visual loop linking the perirhinal cortex, the BG and the thalamus, biased by sustained representations in prefrontal cortex. This model learns concurrently different delayed rewarded tasks that require to maintain a visual cue and to associate it to itself or to another visual object to obtain reward. The retrieval of visual information is achieved through thalamic stimulation of the perirhinal cortex. The input structure of the BG, the striatum, learns to represent visual information based on its association to reward, while the output structure, the substantia nigra pars reticulata, learns to link striatal representations to the disinhibition of the correct thalamocortical loop. In parallel, a dopaminergic cell learns to associate striatal representations to reward and modulates learning of connections within the BG. The model provides testable predictions about the behavior of several areas during such tasks, while providing a new functional organization of learning within the BG, putting emphasis on the learning of the striatonigral connections as well as the lateral connections within the substantia nigra pars reticulata. It suggests that the learning of visual WM tasks is achieved rapidly in the BG and used as a teacher for feedback connections from prefrontal cortex to posterior cortices.

The encoding of cocaine vs. natural rewards in the striatum of nonhuman primates: categories with different activations

The behavioral and motivational changes that result from use of abused substances depend upon activation of neuronal populations in the reward centers of the brain, located primarily in the corpus striatum in primates. To gain insight into the cellular mechanisms through which abused drugs reinforce behavior in the primate brain, changes in firing of neurons in the ventral (VStr, nucleus accumbens) and dorsal (DStr, caudate-putamen) striatum to "natural" (juice) vs. drug (i.v. cocaine) rewards were examined in four rhesus monkeys performing a visual Go-Nogo decision task. Task-related striatal neurons increased firing to one or more of the specific events that occurred within a trial represented by (1) Target stimuli (Go trials) or (2) Nogotarget stimuli (Nogo trials), and (3) Reward delivery for correct performance. These three cell populations were further subdivided into categories that reflected firing exclusively on one or the other type of signaled reward (juice or cocaine) trial (20%-30% of all cells), or, a second subpopulation that fired on both (cocaine and juice) types of rewarded trial (50%). Results show that neurons in the primate striatum encoded cocaine-rewarded trials similar to juice-rewarded trials, except for (1) increased firing on cocaine-rewarded trials, (2) prolonged activation during delivery of i.v. cocaine infusion, and (3) differential firing in ventral (VStr cells) vs. dorsal (DStr cells) striatum cocaine-rewarded trials. Reciprocal activations of antithetic subpopulations of cells during different temporal intervals within the same trial suggest a functional interaction between processes that encode drug and natural rewards in the primate brain.

Trial outcome and associative learning signals in the monkey hippocampus

In tasks of associative learning, animals establish new links between unrelated items by using information about trial outcome to strengthen correct/rewarded associations and modify incorrect/unrewarded ones. To study how hippocampal neurons convey information about reward and trial outcome during new associative learning, we recorded hippocampal neurons as monkeys learned novel object-place associations. A large population of hippocampal neurons (50%) signaled trial outcome by differentiating between correct and error trials during the period after the behavioral response. About half these cells increased their activity following correct trials (correct up cells) while the remaining half fired more following error trials (error up cells). Moreover, correct up cells, but not error up cells, conveyed information about learning by increasing their stimulus-selective response properties with behavioral learning. These findings suggest that information about successful trial outcome conveyed by correct up cells may influence new associative learning through changes in the cell's stimulus-selective response properties.

Sustained activities and retrieval in a computational model of the perirhinal cortex

The perirhinal cortex is involved not only in object recognition and novelty detection but also in multimodal integration, reward association, and visual working memory. We propose a computational model that focuses on the role of the perirhinal cortex in working memory, particularly with respect to sustained activities and memory retrieval. This model describes how different partial informations are integrated into assemblies of neurons that represent the identity of an object. Through dopaminergic modulation, the resulting clusters can retrieve the global information with recurrent interactions between neurons. Dopamine leads to sustained activities after stimulus disappearance that form the basis of the involvement of the perirhinal cortex in visual working memory processes. The information carried by a cluster can also be retrieved by a partial thalamic or prefrontal stimulation. Thus, we suggest that areas involved in planning and memory coordination encode a pointer to access the detailed information encoded in the associative cortex such as the perirhinal cortex.

Dynamic population coding of category information in inferior temporal and prefrontal cortex

Most electrophysiology studies analyze the activity of each neuron separately. While such studies have given much insight into properties of the visual system, they have also potentially overlooked important aspects of information coded in changing patterns of activity that are distributed over larger populations of neurons. In this work, we apply a population decoding method to better estimate what information is available in neuronal ensembles and how this information is coded in dynamic patterns of neural activity in data recorded from inferior temporal cortex (ITC) and prefrontal cortex (PFC) as macaque monkeys engaged in a delayed match-to-category task. Analyses of activity patterns in ITC and PFC revealed that both areas contain "abstract" category information (i.e., category information that is not directly correlated with properties of the stimuli); however, in general, PFC has more task-relevant information, and ITC has more detailed visual information. Analyses examining how information coded in these areas show that almost all category information is available in a small fraction of the neurons in the population. Most remarkably, our results also show that category information is coded by a nonstationary pattern of activity that changes over the course of a trial with individual neurons containing information on much shorter time scales than the population as a whole.

Effects of category learning on the stimulus selectivity of macaque inferior temporal neurons

Primates can learn to categorize complex shapes, but as yet it is unclear how this categorization learning affects the representation of shape in visual cortex. Previous studies that have examined the effect of categorization learning on shape representation in the macaque inferior temporal (IT) cortex have produced diverse and conflicting results that are difficult to interpret owing to inadequacies in design. The present study overcomes these issues by recording IT responses before and after categorization learning. We used parameterized shapes that varied along two shape dimensions. Monkeys were extensively trained to categorize the shapes along one of the two dimensions. Unlike previous studies, our paradigm counterbalanced the relevant categorization dimension across animals. We found that categorization learning increased selectivity specifically for the category-relevant stimulus dimension (i.e., an expanded representation of the trained dimension), and that the ratio of within-category response similarities to between-category response similarities increased for the relevant dimension (i.e., category tuning). These small effects were only evident when the learned category-related effects were disentangled from the prelearned stimulus selectivity. These results suggest that shape-categorization learning can induce minor category-related changes in the shape tuning of IT neurons in adults, suggesting that learned, category-related changes in neuronal response mainly occur downstream from IT.

Computational modeling of analogy: Destined ever to only be metaphor?

The target article by Leech et al. presents a compelling computational theory of analogy-making. However, there is a key difficulty that persists in theoretical treatments of analogy-making, computational and otherwise: namely, the lack of a detailed account of the neurophysiological mechanisms that give rise to analogy behavior. My commentary explores this issue.

Dopaminergic and non-dopaminergic value systems in conditioning and outcome-specific revaluation

Animals are motivated to choose environmental options that can best satisfy current needs. To explain such choices, this paper introduces the MOTIVATOR (Matching Objects To Internal VAlues Triggers Option Revaluations) neural model. MOTIVATOR describes cognitive-emotional interactions between higher-order sensory cortices and an evaluative neuraxis composed of the hypothalamus, amygdala, and orbitofrontal cortex. Given a conditioned stimulus (CS), the model amygdala and lateral hypothalamus interact to calculate the expected current value of the subjective outcome that the CS predicts, constrained by the current state of deprivation or satiation. The amygdala relays the expected value information to orbitofrontal cells that receive inputs from anterior inferotemporal cells, and medial orbitofrontal cells that receive inputs from rhinal cortex. The activations of these orbitofrontal cells code the subjective values of objects. These values guide behavioral choices. The model basal ganglia detect errors in CS-specific predictions of the value and timing of rewards. Excitatory inputs from the pedunculopontine nucleus interact with timed inhibitory inputs from model striosomes in the ventral striatum to regulate dopamine burst and dip responses from cells in the substantia nigra pars compacta and ventral tegmental area. Learning in cortical and striatal regions is strongly modulated by dopamine. The model is used to address tasks that examine food-specific satiety, Pavlovian conditioning, reinforcer devaluation, and simultaneous visual discrimination. Model simulations successfully reproduce discharge dynamics of known cell types, including signals that predict saccadic reaction times and CS-dependent changes in systolic blood pressure.

Catechol-O-methyltransferase val158met genotype influences neural processing of reward anticipation

Reward processing depends critically on dopaminergic neurotransmission in the ventral striatum. The common polymorphism val(158)met of catechol-O-methyltransferase (COMT) accounts for significant interindividual variations in dopamine (DA) degradation, although the direct effect of COMT on striatal DA might be limited. Using fMRI we assessed the influence of COMT val(158)met genotype on brain activations elicited by the anticipation of monetary gains and losses in forty-four healthy volunteers. We found that the met(158) allele, which is presumably linked to higher synaptic DA levels, was associated with higher responses in ventral striatum to loss incentives. There was a linear relationship between the number of met(158) alleles and ventral striatal activity. Furthermore, we observed a similar gene-dose effect in the anterior temporal cortex, a region that has been linked to the coupling of sensory information with emotional contents. Temporal cortex also showed enhanced connectivity to the ventral striatum during the processing of incentive stimuli. Increased ventral striatal reactivity to loss incentives related to the met(158) allele might contribute to the observed association of the met(158) allele to higher loss aversion behaviour. Current evidence and our results are compatible with an interpretation that construes this effect of COMT genotype on striatal reactivity as a result of a cortico-striatal interaction.

Learning to recognize visual objects with microstimulation in inferior temporal cortex

The malleability of object representations by experience is essential for adaptive behavior. It has been hypothesized that neurons in inferior temporal cortex (IT) in monkeys are pivotal in visual association learning, evidenced by experiments revealing changes in neural selectivity following visual learning, as well as by lesion studies, wherein functional inactivation of IT impairs learning. A critical question remaining to be answered is whether IT neuronal activity is sufficient for learning. To address this question directly, we conducted experiments combining visual classification learning with microstimulation in IT. We assessed the effects of IT microstimulation during learning in cases where the stimulation was exclusively informative, conditionally informative, and informative but not necessary for the classification task. The results show that localized microstimulation in IT can be used to establish visual classification learning, and the same stimulation applied during learning can predictably bias judgments on subsequent recognition. The effect of induced activity can be explained neither by direct stimulation-motor association nor by simple detection of cortical stimulation. We also found that the learning effects are specific to IT stimulation as they are not observed by microstimulation in an adjacent auditory area. Our results add the evidence that the differential activity in IT during visual association learning is sufficient for establishing new associations. The results suggest that experimentally manipulated activity patterns within IT can be effectively combined with ongoing visually induced activity during the formation of new associations.

Role of anticipated reward in cognitive behavioral control

The lateral prefrontal cortex (LPFC), which is important for higher cognitive activity, is also concerned with motivational operations; this is exemplified by its activity in relation to expectancy of rewards. In the LPFC, motivational information is integrated with cognitive information, as demonstrated by the enhancement of working-memory-related activity by reward expectancy. Such activity would be expected to induce changes in attention and, subsequently, to modify behavioral performance. Recently, the effects of motivation and emotion on neural activities have been examined in several areas of the brain in relation to cognitive-task performance. Of these areas, the LPFC seems to have the most important role in adaptive goal-directed behavior, by sending top-down attention-control signals to other areas of the brain.