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It has remained unclear whether individuals with psychiatric disorders involving altered visual processing employ similar neuronal mechanisms during perceptual learning of a visual task. We investigated this question by training patients with body dysmorphic disorder, a psychiatric disorder characterized by distressing or impairing preoccupation with nonexistent or slight defects in one's physical appearance, and healthy controls on a visual detection task for human faces with low spatial frequency components. Brain activation during task performance was measured with functional magnetic resonance imaging before the beginning and after the end of behavioral training. Both groups of participants improved performance on the trained task to a similar extent. However, neuronal changes in the fusiform face area were substantially different between groups such that activation for low spatial frequency faces in the right fusiform face area increased after training in body dysmorphic disorder patients but decreased in controls. Moreover, functional connectivity between left and right fusiform face area decreased after training in patients but increased in controls. Our results indicate that neuronal mechanisms involved in perceptual learning of a face detection task differ fundamentally between body dysmorphic disorder patients and controls. Such different neuronal mechanisms in body dysmorphic disorder patients might reflect the brain's adaptations to altered functions imposed by the psychiatric disorder.

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Visual simulation - i.e., using internal reconstructions of the world to experience potential future versions of events that are not currently happening - is among the most sophisticated capacities of the human mind. But is this ability in fact uniquely human? To answer this question, we tested monkeys on a series of experiments involving the 'Planko' game, which we have previously used to evoke visual simulation in human participants. We found that monkeys were able to successfully play the game using a simulation strategy, predicting the trajectory of a ball through a field of planks while demonstrating a level of accuracy and behavioral signatures comparable to humans. Computational analyses further revealed that the monkeys' strategy while playing Planko aligned with a recurrent neural network (RNN) that approached the task using a spontaneously learned simulation strategy. Finally, we carried out awake functional magnetic resonance imaging while monkeys played Planko. We found activity in motion-sensitive regions of the monkey brain during hypothesized simulation periods, even without any perceived visual motion cues. This neural result closely mirrors previous findings from human research, suggesting a shared mechanism of visual simulation across species. In all, these findings challenge traditional views of animal cognition, proposing that nonhuman primates possess a complex cognitive landscape, capable of invoking imaginative and predictive mental experiences to solve complex everyday problems.

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The allocation of attention to objects raises several intriguing questions: What are objects, how does attention access them, what anatomical regions are involved? Here, we review recent progress in the field to determine the mechanisms underlying object-based attention. First, findings from unconscious priming and cueing suggest that the preattentive targets of object-based attention can be fully developed object representations that have reached the level of identity. Next, the control of object-based attention appears to come from ventral visual areas specialized in object analysis that project downward to early visual areas. How feedback from object areas can accurately target the object's specific locations and features is unknown but recent work in autoencoding has made this plausible. Finally, we suggest that the three classic modes of attention may not be as independent as is commonly considered, and instead could all rely on object-based attention. Specifically, studies show that attention can be allocated to the separated members of a group-without affecting the space between them-matching the defining property of feature-based attention. At the same time, object-based attention directed to a single small item has the properties of space-based attention. We outline the architecture of object-based attention, the novel predictions it brings, and discuss how it works in parallel with other attention pathways.

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It is generally believed that learning of a perceptual task involving low-level neuronal mechanisms is similar between individuals. However, it is unclear whether this assumption also applies to individuals with psychiatric disorders that are known to have altered brain activation during visual processing. We investigated this question in patients with body dysmorphic disorder (BDD), a psychiatric disorder characterized by distressing or impairing preoccupation with nonexistent or slight defects in one's physical appearance, and in healthy controls. Participants completed six training sessions on separate days on a visual detection task for human faces with low spatial frequency (LSF) components. Brain activation during task performance was measured with functional magnetic resonance imaging (fMRI) on separate days prior to and after training. The behavioral results showed that both groups of participants improved on the visual detection task to a similar extent through training. Despite this similarity in behavioral improvement, neuronal changes in the Fusiform Face Area (FFA), a core cortical region involved in face processing, with training were substantially different between groups. First, activation in the right FFA for LSF faces relative to High Spatial Frequency (HSF) faces that were used as an untrained control increased after training in BDD patients but decreased in controls. Second, resting state functional connectivity between left and right FFAs decreased after training in BDD patients but increased in controls. Contrary to the assumption that learning of a perceptual task is subserved by the same neuronal mechanisms across individuals, our results indicate that the neuronal mechanisms involved in learning of a face detection task differ fundamentally between patients with BDD and healthy individuals. The involvement of different neuronal mechanisms for learning of even simple perceptual tasks in patients with BDD might reflect the brain's adaptations to altered functions imposed by the psychiatric disorder.

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Our brains continuously acquire sensory information and make judgments even when visual information is limited. In some circumstances, an ambiguous object can be recognized from how it moves, such as an animal hopping or a plane flying overhead. Yet it remains unclear how movement is processed by brain areas involved in visual object recognition. Here we investigate whether inferior temporal (IT) cortex, an area known for its relevance in visual form processing, has access to motion information during recognition. We developed a matching task that required monkeys to recognize moving shapes with variable levels of shape degradation. Neural recordings in area IT showed that, surprisingly, some IT neurons responded stronger to degraded shapes than clear ones. Furthermore, neurons exhibited motion sensitivity at different times during the presentation of the blurry target. Population decoding analyses showed that motion patterns could be decoded from IT neuron pseudo-populations. Contrary to previous findings, these results suggest that neurons in IT can integrate visual motion and shape information, particularly when shape information is degraded, in a way that has been previously overlooked. Our results highlight the importance of using challenging multifeature recognition tasks to understand the role of area IT in naturalistic visual object recognition.

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Although visual object recognition is well studied and relatively well understood, much less is known about how shapes are recognized by touch and how such haptic stimuli might be compared with visual shapes. One might expect that the processes of visual and haptic object recognition engage similar brain structures given the advantages of avoiding redundant brain circuitry and indeed there is some evidence that this is the case. A potentially fruitful approach to understanding the differences in how shapes might be neurally represented is to find an algorithmic method of comparing shapes, which agrees with human behavior and determines whether that method differs between different modality conditions. If not, it would provide further evidence for a shared representation of shape. We recruited human participants to perform a one-back same-different visual and haptic shape comparison task both within (i.e., comparing two visual shapes or two haptic shapes) and across (i.e., comparing visual with haptic shapes) modalities. We then used various shape metrics to predict performance based on the shape, orientation, and modality of the two stimuli that were being compared on each trial. We found that the metrics that best predict shape comparison behavior heavily depended on the modality of the two shapes, suggesting differences in which features are used for comparing shapes depending on modality and that object recognition is not necessarily performed in a single, modality-agnostic region.

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To engage with the world, we must regularly make predictions about the outcomes of physical scenes. How do we make these predictions? Recent computational evidence points to simulation-the idea that we can introspectively manipulate rich, mental models of the world-as one explanation for how such predictions are accomplished. However, questions about the potential neural mechanisms of simulation remain. We hypothesized that the process of simulating physical events would evoke imagery-like representations in visual areas of those same events. Using functional magnetic resonance imaging, we find that when participants are asked to predict the likely trajectory of a falling ball, motion-sensitive brain regions are activated. We demonstrate that this activity, which occurs even though no motion is being sensed, resembles activity patterns that arise while participants perceive the ball's motion. This finding thus suggests that mental simulations recreate sensory depictions of how a physical scene is likely to unfold.

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We regularly interact with moving objects in our environment. Yet, little is known about how we extrapolate the future movements of visually perceived objects. One possibility is that movements are experienced by a mental visual simulation, allowing one to internally picture an object's upcoming motion trajectory, even as the object itself remains stationary. Here we examined this possibility by asking human participants to make judgments about the future position of a falling ball on an obstacle-filled display. We found that properties of the ball's trajectory were highly predictive of subjects' reaction times and accuracy on the task. We also found that the eye movements subjects made while attempting to ascertain where the ball might fall had significant spatiotemporal overlap with those made while actually perceiving the ball fall. These findings suggest that subjects simulated the ball's trajectory to inform their responses. Finally, we trained a convolutional neural network to see whether this problem could be solved by simple image analysis as opposed to the more intricate simulation strategy we propose. We found that while the network was able to solve our task, the model's output did not effectively or consistently predict human behavior. This implies that subjects employed a different strategy for solving our task, and bolsters the conclusion that they were engaging in visual simulation. The current study thus provides support for visual simulation of motion as a means of understanding complex visual scenes and paves the way for future investigations of this phenomenon at a neural level.

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There is substantial evidence for individual differences in personality and cognitive abilities, but we lack clear intuitions about individual differences in visual abilities. Previous work on this topic has typically compared performance with only 2 categories, each measured with only 1 task. This approach is insufficient for demonstration of domain-general effects. Most previous work has used familiar object categories, for which experience may vary between participants and categories, thereby reducing correlations that would stem from a common factor. In Study 1, we adopted a latent variable approach to test for the first time whether there is a domain-general object recognition ability, o. We assessed whether shared variance between latent factors representing performance for each of 5 novel object categories could be accounted for by a single higher-order factor. On average, 89% of the variance of lower-order factors denoting performance on novel object categories could be accounted for by a higher-order factor, providing strong evidence for o. Moreover, o also accounted for a moderate proportion of variance in tests of familiar object recognition. In Study 2, we assessed whether the strong association across categories in object recognition is due to third-variable influences. We find that o has weak to moderate associations with a host of cognitive, perceptual, and personality constructs and that a clear majority of the variance in and covariance between performance on different categories is independent of fluid intelligence. This work provides the first demonstration of a reliable, specific, and domain-general object recognition ability, and suggest a rich framework for future work in this area. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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Information about external stimuli is thought to be stored in cortical circuits through experience-dependent modifications of synaptic connectivity. These modifications of network connectivity should lead to changes in neuronal activity as a particular stimulus is repeatedly encountered. Here we ask what plasticity rules are consistent with the differences in the statistics of the visual response to novel and familiar stimuli in inferior temporal cortex, an area underlying visual object recognition. We introduce a method that allows one to infer the dependence of the presumptive learning rule on postsynaptic firing rate, and we show that the inferred learning rule exhibits depression for low postsynaptic rates and potentiation for high rates. The threshold separating depression from potentiation is strongly correlated with both mean and s.d. of the firing rate distribution. Finally, we show that network models implementing a rule extracted from data show stable learning dynamics and lead to sparser representations of stimuli.

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Attracted by the appealing advantages of optogenetics, many nonhuman primate labs are attempting to incorporate this technique in their experiments. Despite some reported successes by a few groups, many still find it difficult to develop a reliable way to transduce cells in the monkey brain and subsequently monitor light-induced neuronal activity. Here, we describe a methodology that we have developed and successfully deployed on a regular basis with multiple monkeys. All devices and accessories are easy to obtain and results using these have been proven to be highly replicable. We developed the "in-chair" viral injection system and used tapered and thinner fibers for optical stimulation, which significantly improved the efficacy and reduced tissue damage. With these methods, we have successfully transduced cells in multiple monkeys in both deep and shallow cortical areas. We could reliably obtain neural modulation for months after injection, and no light-induced artifacts were observed during recordings. Further experiments using these methods have shown that optogenetic stimulation can be used to bias spatial attention in a visual choice discrimination task in a way comparable to electrical microstimulation, which demonstrates the potential use of our methods in both fundamental research and clinical applications.

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The successful retrieval of learned visual associations requires coordination of multiple brain regions involved in the encoding and association of visual images. In this issue of Neuron, Takeda et al. (2015) use a combination of modern recording and analytical methods to eavesdrop on this process.

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The lateral intraparietal area (LIP) is thought to play an important role in the guidance of where to look and pay attention. LIP can also respond selectively to differently shaped objects. We sought to understand to what extent short-term and long-term experience with visual orienting determines the responses of LIP to objects of different shapes. We taught monkeys to arbitrarily associate centrally presented objects of various shapes with orienting either toward or away from a preferred spatial location of a neuron. The training could last for less than a single day or for several months. We found that neural responses to objects are affected by such experience, but that the length of the learning period determines how this neural plasticity manifests. Short-term learning affects neural responses to objects, but these effects are only seen relatively late after visual onset; at this time, the responses to newly learned objects resemble those of familiar objects that share their meaning or arbitrary association. Long-term learning affects the earliest bottom-up responses to visual objects. These responses tend to be greater for objects that have been associated with looking toward, rather than away from, LIP neurons' preferred spatial locations. Responses to objects can nonetheless be distinct, although they have been similarly acted on in the past and will lead to the same orienting behavior in the future. Our results therefore indicate that a complete experience-driven override of LIP object responses may be difficult or impossible. We relate these results to behavioral work on visual attention.

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Our ability to plan and execute a series of tasks leading to a desired goal requires remarkable coordination between sensory, motor, and decision-related systems. Prefrontal cortex (PFC) is thought to play a central role in this coordination, especially when actions must be assembled extemporaneously and cannot be programmed as a rote series of movements. A central component of this flexible behavior is the moment-by-moment allocation of working memory and attention. The ubiquity of sequence planning in our everyday lives belies the neural complexity that supports this capacity, and little is known about how frontal cortical regions orchestrate the monitoring and control of sequential behaviors. For example, it remains unclear if and how sensory cortical areas, which provide essential driving inputs for behavior, are modulated by the frontal cortex during these tasks. Here, we review what is known about moment-to-moment monitoring as it relates to visually guided, rule-driven behaviors that change over time. We highlight recent human work that shows how the rostrolateral prefrontal cortex (RLPFC) participates in monitoring during task sequences. Neurophysiological data from monkeys suggests that monitoring may be accomplished by neurons that respond to items within the sequence and may in turn influence the tuning properties of neurons in posterior sensory areas. Understanding the interplay between proceduralized or habitual acts and supervised control of sequences is key to our understanding of sequential task execution. A crucial bridge will be the use of experimental protocols that allow for the examination of the functional homology between monkeys and humans. We illustrate how task sequences may be parceled into components and examined experimentally, thereby opening future avenues of investigation into the neural basis of sequential monitoring and control.

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Neuroprosthesis research aims to enable communication between the brain and external assistive devices while restoring lost functionality such as occurs from stroke, spinal cord injury or neurodegenerative diseases. In future closed-loop sensorimotor prostheses, one approach is to use neuromodulation as direct stimulus to the brain to compensate for a lost sensory function and help the brain to integrate relevant information for commanding external devices via, e.g. movement intention. Current neuromodulation techniques rely mainly of electrical stimulation. Here we focus specifically on the question of eliciting a biomimetically relevant sense of touch by direct stimulus of the somatosensory cortex by introducing optogenetic techniques as an alternative to electrical stimulation. We demonstrate that light activated opsins can be introduced to target neurons in the somatosensory cortex of non-human primates and be optically activated to create a reliably detected sensation which the animal learns to interpret as a tactile sensation localized within the hand. The accomplishment highlighted here shows how optical stimulation of a relatively small group of mostly excitatory somatosensory neurons in the nonhuman primate brain is sufficient for eliciting a useful sensation from data acquired by simultaneous electrophysiology and from behavioral metrics. In this first report to date on optically neuromodulated behavior in the somatosensory cortex of nonhuman primates we do not yet dissect the details of the sensation the animals exerience or contrast it to those evoked by electrical stimulation, issues of considerable future interest.

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Optogenetics is a recently developed method in which neurons are genetically modified to express membrane proteins sensitive to light, enabling precisely targeted control of neural activity [1-3]. The temporal and spatial precision afforded by neural stimulation by light holds promise as a powerful alternative to current methods of neural control, which rely predominantly on electrical and pharmacological methods, in both research and clinical settings [4, 5]. Although the optogenetic approach has been widely used in rodent and other small animal models to study neural circuitry [6-8], its functional application in primate models has proven more difficult. In contrast to the relatively large literature on the effects of cortical electrical microstimulation in perceptual and decision-making tasks [9-13], previous studies of optogenetic stimulation in primates have not demonstrated its utility in similar paradigms [14-18]. In this study, we directly compare the effects of optogenetic activation and electrical microstimulation in the lateral intraparietal area during a visuospatial discrimination task. We observed significant and predictable biases in visual attention in response to both forms of stimulation that are consistent with the experimental modulation of a visual salience map. Our results demonstrate the power of optogenetics as a viable alternative to electrical microstimulation for the precise dissection of the cortical pathways of high-level processes in the primate brain.

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The shape of an object restricts its movements and therefore its future location. The rules governing selective sampling of the environment likely incorporate any available data, including shape, that provide information about where important things are going to be in the near future so that the object can be located, tracked, and sampled for information. We asked people to assess in which direction several novel objects pointed or directed them. With independent groups of people, we investigated whether their attention and sense of motion were systematically biased in this direction. Our work shows that nearly any novel object has intrinsic directionality derived from its shape. This shape information is swiftly and automatically incorporated into the allocation of overt and covert visual orienting and the detection of motion, processes that themselves are inherently directional. The observed connection between form and space suggests that shape processing goes beyond recognition alone and may help explain why shape is a relevant dimension throughout the visual brain.

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The cerebral cortex is composed of many distinct classes of neurons. Numerous studies have demonstrated corresponding differences in neuronal properties across cell types, but these comparisons have largely been limited to conditions outside of awake, behaving animals. Thus the functional role of the various cell types is not well understood. Here, we investigate differences in the functional properties of two widespread and broad classes of cells in inferior temporal cortex of macaque monkeys: inhibitory interneurons and excitatory projection cells. Cells were classified as putative inhibitory or putative excitatory neurons on the basis of their extracellular waveform characteristics (e.g., spike duration). Consistent with previous intracellular recordings in cortical slices, putative inhibitory neurons had higher spontaneous firing rates and higher stimulus-evoked firing rates than putative excitatory neurons. Additionally, putative excitatory neurons were more susceptible to spike waveform adaptation following very short interspike intervals. Finally, we compared two functional properties of each neuron's stimulus-evoked response: stimulus selectivity and response latency. First, putative excitatory neurons showed stronger stimulus selectivity compared with putative inhibitory neurons. Second, putative inhibitory neurons had shorter response latencies compared with putative excitatory neurons. Selectivity differences were maintained and latency differences were enhanced during a visual search task emulating more natural viewing conditions. Our results suggest that short-latency inhibitory responses are likely to sculpt visual processing in excitatory neurons, yielding a sparser visual representation.

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Primates can learn to recognize a virtually limitless number of visual objects. A candidate neural substrate for this adult plasticity is the inferior temporal cortex (ITC). Using a large stimulus set, we explored the impact that long-term experience has on the response properties of two classes of neurons in ITC: broad-spiking (putative excitatory) cells and narrow-spiking (putative inhibitory) cells. We found that experience increased maximum responses of putative excitatory neurons but had the opposite effect on maximum responses of putative inhibitory neurons, an observation that helps to reconcile contradictory reports regarding the presence and direction of this effect. In addition, we found that experience reduced the average stimulus-evoked response in both cell classes, but this decrease was much more pronounced in putative inhibitory units. This latter finding supports a potentially critical role of inhibitory neurons in detecting and initiating the cascade of events underlying adult neural plasticity in ITC.

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Inferotemporal cortex (IT) is believed to be directly involved in object processing and necessary for accurate and efficient object recognition. The frontal eye field (FEF) is an area in the primate prefrontal cortex that is involved in visual spatial selection and is thought to guide spatial attention and eye movements. We show that object-selective responses of IT neurons and behavioral performance are affected by changes in frontal eye field activity. This was found in monkeys performing a search classification task by temporarily inactivating subregions of FEF while simultaneously recording the activity from single neurons in IT. The effect on object selectivity and performance was specific, occurring in a predictable spatially dependent manner and was strongest when the IT neuron's preferred target was presented in the presence of distractors. FEF inactivation did not affect IT responses on trials in which the nonpreferred target was presented in the search array.

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