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While classic views proposed that working memory (WM) is mediated by sustained firing, recent evidence suggests a contribution of activity-silent states. Within WM, human neuroimaging studies suggest a switch between attentional foreground and background, with only the foregrounded item represented in active neural firing. To address this process at the cellular level, we recorded prefrontal (PFC) and posterior parietal (PPC) neurons in a complex problem-solving task, with monkeys searching for one or two target locations in a first cycle of trials, and retaining them for memory-guided revisits on subsequent cycles. When target locations were discovered, neither frontal nor parietal neurons showed sustained goal-location codes continuing into subsequent trials and cycles. Instead there were sequences of timely goal silencing and reactivation, and following reactivation, sustained states until behavioral response. With two target locations, goal representations in both regions showed evidence of transitions between foreground and background, but the PFC representation was more complete, extending beyond the current trial to include both past and future selections. In the absence of unbroken sustained codes, different neuronal states interact to support maintenance and retrieval of WM representations across successive trials.

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Ventrolateral prefrontal cortex (vlPFC), dorsolateral prefrontal cortex (dlPFC), and temporal cortex (TE) all contribute to visual decision-making. Accumulating evidence suggests that vlPFC may play a central role in multiple cognitive operations, perhaps resembling domain-general regions of the human frontal lobe. We trained monkeys in a task calling for learning, retrieval, and spatial selection of rewarded target objects. Recordings of neural activity covered large areas of vlPFC, dlPFC, and TE. Results suggested a central role for vlPFC in each cognitive operation with strong coding of each task feature, while only location was strongly coded in dlPFC and current object identity in TE. During target selection, target location was communicated first from vlPFC to dlPFC, followed by extensive mutual support. In vlPFC, stimulus identities were independently coded in different task operations. The results suggest a central role for the inferior frontal convexity in controlling successive operations of a complex, multi-step task.

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In the behaving monkey, complex neural dynamics in the prefrontal cortex contribute to context-dependent decisions and attentional competition. We used demixed principal component analysis to track prefrontal activity dynamics in a cued target detection task. In this task, the animal combined identity of a visual object with a prior instruction cue to determine a target/nontarget decision. From population activity, we extracted principal components for each task feature and examined their time course and sensitivity to stimulus and task variations. For displays containing a single choice object in left or right hemifield, object identity, cue identity and decision were all encoded in population activity, with different dynamics and lateralisation. Object information peaked at 100-200 ms from display onset and was largely confined to the contralateral hemisphere. Cue information was weaker and present even prior to display onset. Integrating information from cue and object, decision information arose more slowly and was bilateral. Individual neurons contributed independently to coding of the three task features. The analysis was then extended to displays with a target in one hemifield and a competing distractor in the other. In this case, the data suggest that each hemisphere initially encoded the identity of the contralateral object. The distractor representation was then rapidly suppressed, with the final target decision again encoded bilaterally. The results show how information is coded along task-related dimensions while competition is resolved and suggest how information flows within and across frontal lobes to implement a learned behavioural decision.

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Much animal learning is slow, with cumulative changes in behavior driven by reward prediction errors. When the abstract structure of a problem is known, however, both animals and formal learning models can rapidly attach new items to their roles within this structure, sometimes in a single trial. Frontal cortex is likely to play a key role in this process. To examine information seeking and use in a known problem structure, we trained monkeys in an explore/exploit task, requiring the animal first to test objects for their association with reward, then, once rewarded objects were found, to reselect them on further trials for further rewards. Many cells in the frontal cortex showed an explore/exploit preference aligned with one-shot learning in the monkeys' behavior: the population switched from an explore state to an exploit state after a single trial of learning but partially maintained the explore state if an error indicated that learning had failed. Binary switch from explore to exploit was not explained by continuous changes linked to expectancy or prediction error. Explore/exploit preferences were independent for two stages of the trial: object selection and receipt of feedback. Within an established task structure, frontal activity may control the separate processes of explore and exploit, switching in one trial between the two.SIGNIFICANCE STATEMENT Much animal learning is slow, with cumulative changes in behavior driven by reward prediction errors. When the abstract structure a problem is known, however, both animals and formal learning models can rapidly attach new items to their roles within this structure. To address transitions in neural activity during one-shot learning, we trained monkeys in an explore/exploit task using familiar objects and a highly familiar task structure. When learning was rapid, many frontal neurons showed a binary, one-shot switch between explore and exploit. Within an established task structure, frontal activity may control the separate operations of exploring alternative objects to establish their current role, then exploiting this knowledge for further reward.

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Serial and parallel processing in visual search have been long debated in psychology, but the processing mechanism remains an open issue. Serial processing allows only one object at a time to be processed, whereas parallel processing assumes that various objects are processed simultaneously. Here, we present novel neural models for the two types of processing mechanisms based on analysis of simultaneously recorded spike trains using electrophysiological data from prefrontal cortex of rhesus monkeys while processing task-relevant visual displays. We combine mathematical models describing neuronal attention and point process models for spike trains. The same model can explain both serial and parallel processing by adopting different parameter regimes. We present statistical methods to distinguish between serial and parallel processing based on both maximum likelihood estimates and decoding the momentary focus of attention when two stimuli are presented simultaneously. Results show that both processing mechanisms are in play for the simultaneously recorded neurons, but neurons tend to follow parallel processing in the beginning after the onset of the stimulus pair, whereas they tend to serial processing later on.

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Complex cognition is dynamic, with each stage of a task requiring new cognitive processes appropriately linked to stimulus or other content. To investigate control over successive task stages, we recorded neural activity in lateral frontal and parietal cortex as monkeys carried out a complex object selection task, with each trial separated into phases of visual selection and learning from feedback. To study capacity limitation, complexity was manipulated by varying the number of object targets to be learned in each problem. Different task phases were associated with quasi-independent patterns of activity and information coding, with no suggestion of sustained activity linked to a current target. Object and location coding were largely parallel in frontal and inferior parietal cortex, though frontal cortex showed somewhat stronger object representation at feedback, and more sustained location coding at choice. At both feedback and choice, coding precision diminished as task complexity increased, matching a decline in performance. We suggest that, across successive task steps, there is radical but capacity-limited reorganization of frontoparietal activity, selecting different cognitive operations linked to their current targets.

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Prefrontal neurons code many kinds of behaviourally relevant visual information. In behaving monkeys, we used a cued target detection task to address coding of objects, behavioural categories and spatial locations, examining the temporal evolution of neural activity across dorsal and ventral regions of the lateral prefrontal cortex (encompassing parts of areas 9, 46, 45A and 8A), and across the two cerebral hemispheres. Within each hemisphere there was little evidence for regional specialisation, with neurons in dorsal and ventral regions showing closely similar patterns of selectivity for objects, categories and locations. For a stimulus in either visual field, however, there was a strong and temporally specific difference in response in the two cerebral hemispheres. In the first part of the visual response (50-250 ms from stimulus onset), processing in each hemisphere was largely restricted to contralateral stimuli, with strong responses to such stimuli, and selectivity for both object and category. Later (300-500 ms), responses to ipsilateral stimuli also appeared, many cells now responding more strongly to ipsilateral than to contralateral stimuli, and many showing selectivity for category. Activity on error trials showed that late activity in both hemispheres reflected the animal's final decision. As information is processed towards a behavioural decision, its encoding spreads to encompass large, bilateral regions of prefrontal cortex.

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The sense of smell is found widely in the animal kingdom. Human and animal studies show that odor perception is modulated by experience and/or physiological state (such as hunger), and that some odors can arouse emotion, and can lead to the recall of emotional memories. Further, odors can influence psychological and physiological states. Individual odorants are mapped via gene-specified receptors to corresponding glomeruli in the olfactory bulb, which directly projects to the piriform cortex and the amygdala without a thalamic relay. The odors to which a glomerulus responds reflect the chemical structure of the odorant. The piriform cortex and the amygdala both project to the orbitofrontal cortex (OFC) which with the amygdala is involved in emotion and associative learning, and to the entorhinal/hippocampal system which is involved in long-term memory including episodic memory. Evidence that some odors can modulate emotion and cognition is described, and the possible implications for the treatment of psychological problems, for example in reducing the effects of stress, are considered.

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Prefrontal cortex has been proposed to show highly adaptive information coding, with neurons dynamically allocated to processing task-relevant information. To track this dynamic allocation in monkey prefrontal cortex, we used time-resolved measures of neural population activity in a simple case of competition between target (behaviorally critical) and nontarget objects in opposite visual hemifields. Early in processing, there were parallel responses to competing inputs, with neurons in each hemisphere dominated by the contralateral stimulus. Later, the nontarget lost control of neural activity, with emerging global control by the behaviorally critical target. The speed of transition reflected the competitive weights of different display elements, occurring most rapidly when relative behavioral significance was well established by training history. In line with adaptive coding, the results show widespread reallocation of prefrontal processing resources as an attentional focus is established.

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Habituation is a form of non-associative memory that plays an important role in filtering stable or redundant inputs. The present study examines the contribution of habituation and cortical adaptation to odor-background segmentation. Segmentation of target odorants from background odorants is a fundamental computational requirement for the olfactory system. Recent electrophysiological data have shown that odor specific adaptation in piriform cortex neurons, mediated at least partially by synaptic adaptation between the olfactory bulb outputs and piriform cortex pyramidal cells, may provide an ideal mechanism for odor-background segmentation. This rapid synaptic adaptation acts as a filter to enhance cortical responsiveness to changing stimuli, while reducing responsiveness to static, potentially background stimuli. Using previously developed computational models of the olfactory system, we here show how synaptic adaptation at the olfactory bulb input to the piriform cortex, as demonstrated electrophysiologically, creates odor specific adaptation. We show how this known feature of olfactory cortical processing can contribute to adaptation to a background odor and to odor-background segmentation. We then show in a behavioral experiment that the odor-background segmentation is perceptually important and functions at the same time-scale as the synaptic adaptation observed between the olfactory bulb and cortex.

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Piriform cortical circuits are hypothesized to form perceptions from responses to specific odorant features, but the anterior piriform cortex (aPCX) and posterior piriform cortex (pPCX) differ markedly in their anatomical organization, differences that could lead to distinct roles in odor encoding. Here, we tested whether experience with a complex odorant mixture would modify encoding of the mixture and its components in aPCX and pPCX. Rats were exposed to an odorant mixture and its components in a go/no-go rewarded odor discrimination task. After reaching behavioral performance criterion, single-unit recordings were made from the aPCX and pPCX in these rats and in odor-naïve, control, urethane-anesthetized rats. After odor experience, aPCX neurons were more narrowly tuned to the test odorants, and there was a decorrelation in aPCX population responses to the mixture and its components, suggesting a more distinct encoding of the familiar mixture from its components. In contrast, pPCX neurons were more broadly tuned to the familiar odorants, and pPCX population responses to the mixture and its components became more highly correlated, suggesting a pPCX encoding of similarity between familiar stimuli. The results suggest aPCX and pPCX play different roles in the processing of familiar odors and are consistent with an experience-dependent encoding (perceptual learning) of synthetic odorant identity in aPCX and an experience-dependent encoding of odor similarity or odor quality in pPCX.

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In most sensory systems, the sensory cortex is the place where sensation approaches perception. As described in this review, olfaction is no different. The olfactory system includes both primary and higher order cortical regions. These cortical structures perform computations that take highly analytical afferent input and synthesize it into configural odor objects. Cortical plasticity plays an important role in this synthesis and may underlie olfactory perceptual learning. Olfactory cortex is also involved in odor memory and association of odors with multimodal input and contexts. Finally, the olfactory cortex serves as an important sensory gate, modulating information throughput based on recent experience and behavioral state.

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Detection and discrimination of odors generally, if not always, occurs against an odorous background. On any given inhalation, olfactory receptor neurons will be activated by features of both the target odorant and features of background stimuli. To identify a target odorant against a background therefore, the olfactory system must be capable of grouping a subset of features into an odor object distinct from the background. Our previous work has suggested that rapid homosynaptic depression of afferents to the anterior piriform cortex (aPCX) contributes to both cortical odor adaptation to prolonged stimulation and habituation of simple odor-evoked behaviors. We hypothesize here that this process may also contribute to figure-ground separation of a target odorant from background stimulation. Single-unit recordings were made from both mitral/tufted cells and aPCX neurons in urethan-anesthetized rats and mice. Single-unit responses to odorant stimuli and their binary mixtures were determined. One of the odorants was randomly selected as the background and presented for 50 s. Forty seconds after the onset of the background stimulus, the second target odorant was presented, producing a binary mixture. The results suggest that mitral/tufted cells continue to respond to the background odorant and, when the target odorant is presented, had response magnitudes similar to that evoked by the binary mixture. In contrast, aPCX neurons filter out the background stimulus while maintaining responses to the target stimulus. Thus the aPCX acts as a filter driven most strongly by changing stimuli, providing a potential mechanism for olfactory figure-ground separation and selective reading of olfactory bulb output.

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The responses of 3687 neurons in the macaque primary taste cortex in the insula/frontal operculum, orbitofrontal cortex (OFC) and amygdala to oral sensory stimuli reveals principles of representation in these areas. Information about the taste, texture of what is in the mouth (viscosity, fat texture and grittiness, which reflect somatosensory inputs), temperature and capsaicin is represented in all three areas. In the primary taste cortex, taste and viscosity are more likely to activate different neurons, with more convergence onto single neurons particularly in the OFC and amygdala. The different responses of different OFC neurons to different combinations of these oral sensory stimuli potentially provides a basis for different behavioral responses. Consistently, the mean correlations between the representations of the different stimuli provided by the population of OFC neurons were lower (0.71) than for the insula (0.81) and amygdala (0.89). Further, the encoding was more sparse in the OFC (0.67) than in the insula (0.74) and amygdala (0.79). The insular neurons did not respond to olfactory and visual stimuli, with convergence occurring in the OFC and amygdala. Human psychophysics showed that the sensory spaces revealed by multidimensional scaling were similar to those provided by the neurons.

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It is shown that the primate primary taste cortex represents not only taste but also information about many nontaste properties of oral stimuli. Of 1,122 macaque anterior insular/frontal opercular neurons recorded, 62 (5.5%) responded to oral stimuli. Of the orally responsive neurons, some (53%) represented the viscosity, tested using carboxymethyl-cellulose in the range 1-10,000 cP. Other neurons (8%) responded to fat in the mouth by encoding its texture (as shown similar responses to nonfat oils), and 8% responded to gritty texture. Some neurons (35%) responded to the temperature of the liquid in the mouth. Some neurons responded to capsaicin, and others to fatty acids. Some neurons (56%) had taste responses. Some (50%) of these neurons were unimodal, responding to one of these types of stimulus, and the majority combined responsiveness to these types of stimulus, with 23% responding for example to both taste and temperature. Some neurons respond to taste, texture, and temperature unimodally, but others combine these inputs. None of these orally responsive neurons responded to odor or to the sight of food. These results provide fundamental evidence about the information channels used to represent the taste, texture, and temperature of food in the first cortical area involved in taste in the primate brain. The results are relevant to understanding the physiological and pathophysiological processes related to how the properties of oral stimuli are represented in the brain and thus to the control of food intake and food selection.

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The primate orbitofrontal cortex (OFC) is a site of convergence from taste, olfactory, and somatosensory cortical areas. We describe a population of single neurons in the macaque OFC that responds to the texture of food in the mouth. Use of oral viscosity stimuli consisting of carboxymethylcellulose (CMC) in the range 1-10,000 centipoise showed that the responses of one subset of these neurons were related to stimulus viscosity. Some of the neurons had increasing responses to increasing viscosity, some had decreasing responses, and some neurons were tuned to a range of viscosities. These neurons are a different population to oral fat-sensitive neurons, in that their responses to fats (e.g., safflower oil), to silicone oil [(Si(CH3)2O)n], and to mineral oil (hydrocarbon) depended on the viscosity of these oils. Thus there is a dissociation between texture channels used to sense viscosity and fat. Some of these viscosity-sensitive single neurons were unimodal (somatosensory; 25%) and some received convergent taste inputs (75%). A second subpopulation of neurons responded to gritty texture (produced by microspheres suspended in CMC). A third subpopulation of neurons responded to capsaicin. These results provide evidence about the information channels used to represent the texture and flavor of food in a part of the brain important in appetitive responses to food and are relevant to understanding the physiological and pathophysiological processes related to food intake, food selection, and the effects of variety of food texture in combination with taste and other inputs that affect food intake.

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The primate orbitofrontal cortex (OFC) is a site of convergence from primary taste, olfactory, and somatosensory cortical areas. We describe the responses of a population of single neurons in the OFC that respond to orally applied fat (e.g., safflower oil) and to substances with a similar texture but different chemical composition, such as mineral oil (hydrocarbon) and silicone oil [(Si(CH3)2O)n]. These findings provide evidence that the neurons respond to the oral texture of fat, sensed by the somatosensory system. Use of an oral viscosity stimulus consisting of carboxymethyl-cellulose in the range 1-10,000 centipoise (cP) showed that the responses of these fat-sensitive neurons are not related to stimulus viscosity. Thus a textural component independent of viscosity and related to the slick or oily property is being used to activate these oral fat-sensitive neurons. Moreover, a separate population of neurons responds to viscosity (produced, e.g., by the carboxymethyl-cellulose series), but not to fat with the same viscosity. Thus there is a dissociation between texture channels used to sense fat viscosity and non-fat-produced viscosity. Further, free fatty acids such as linoleic acid do not activate these neurons, providing further evidence that the oral fat-sensing mechanism through which these OFC neurons are activated is not gustatory but textural. Most of this population of fat-sensitive neurons receive convergent taste inputs. These results provide evidence about how oral fat is sensed and are relevant to understanding the physiological and pathophysiological processes related to fat intake.

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