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The cortical network that processes visual cues to self-motion was characterized with functional magnetic resonance imaging in 3 awake behaving macaques. The experimental protocol was similar to previous human studies in which the responses to a single large optic flow patch were contrasted with responses to an array of 9 similar flow patches. This distinguishes cortical regions where neurons respond to flow in their receptive fields regardless of surrounding motion from those that are sensitive to whether the overall image arises from self-motion. In all 3 animals, significant selectivity for egomotion-consistent flow was found in several areas previously associated with optic flow processing, and notably dorsal middle superior temporal area, ventral intra-parietal area, and VPS. It was also seen in areas 7a (Opt), STPm, FEFsem, FEFsac and in a region of the cingulate sulcus that may be homologous with human area CSv. Selectivity for egomotion-compatible flow was never total but was particularly strong in VPS and putative macaque CSv. Direct comparison of results with the equivalent human studies reveals several commonalities but also some differences., (© The Author 2017. Published by Oxford University Press.)

Primates can recognize objects embedded in complex natural scenes in a glimpse. Rapid categorization paradigms have been extensively used to study our core perceptual abilities when the visual system is forced to operate under strong time constraints. However, the neural underpinning of rapid categorization remains to be understood, and the incredible speed of sight has yet to be reconciled with modern ventral stream cortical theories of object recognition. Here we recorded multichannel subdural electrocorticogram (ECoG) signals from intermediate areas (V4/PIT) of the ventral stream of the visual cortex while monkeys were actively engaged in a rapid animal/non-animal categorization task. A traditional event-related potential (ERP) analysis revealed short visual latencies (<50-70ms) followed by a rapidly developing visual selectivity (within ~20-30ms) for most electrodes. A multi-variate pattern analysis (MVPA) technique further confirmed that reliable animal/non-animal category information was possible from this initial ventral stream neural activity (within ~90-100ms). Furthermore, this early category-selective neural activity was (a) unaffected by the presentation of a backward (pattern) mask, (b) generalized to novel (unfamiliar) stimuli and (c) co-varied with behavioral responses (both accuracy and reaction times). Despite the strong prevalence of task-related information on the neural signal, task-irrelevant visual information could still be decoded independently of monkey behavior. Monkey behavioral responses were also found to correlate significantly with human behavioral responses for the same set of stimuli. Together, the present study establishes that rapid ventral stream neural activity induces a visually selective signal subsequently used to drive rapid visual categorization and that this visual strategy may be shared between human and non-human primates., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Rapid visual categorization is a crucial ability for survival of many animal species, including monkeys and humans. In real conditions, objects (either animate or inanimate) are never isolated but embedded in a complex background made of multiple elements. It has been shown in humans and monkeys that the contextual background can either enhance or impair object categorization, depending on context/object congruency (for example, an animal in a natural vs. man-made environment). Moreover, a scene is not only a collection of objects; it also has global physical features (i.e phase and amplitude of Fourier spatial frequencies) which help define its gist. In our experiment, we aimed to explore and compare the contribution of the amplitude spectrum of scenes in the context-object congruency effect in monkeys and humans. We designed a rapid visual categorization task, Animal versus Non-Animal, using as contexts both real scenes photographs and noisy backgrounds built from the amplitude spectrum of real scenes but with randomized phase spectrum. We showed that even if the contextual congruency effect was comparable in both species when the context was a real scene, it differed when the foreground object was surrounded by a noisy background: in monkeys we found a similar congruency effect in both conditions, but in humans the congruency effect was absent (or even reversed) when the context was a noisy background.

Conceptual abilities in animals have been shown at several levels of abstraction, but it is unclear whether the analogy with humans results from convergent evolution or from shared brain mechanisms inherited from a common origin. Macaque monkeys can access "non-similarity-based concepts," such as when sorting pictures containing a superordinate target category (animal, tree, etc.) among other scenes. However, such performances could result from low-level visual processing based on learned regularities of the photographs, such as for scene categorization by artificial systems. By using pictures of man-made objects or animals embedded in man-made or natural contexts, the present study clearly establishes that macaque monkeys based their categorical decision on the presence of the animal targets regardless of the scene backgrounds. However, as is found with humans, monkeys performed better with categorically congruent object/context associations, especially when small object sizes favored background information. The accuracy improvements and the response-speed gains attributable to superordinate category congruency in monkeys were strikingly similar to those of human subjects tested with the same task and stimuli. These results suggest analogous processing of visual information during the activation of abstract representations in both humans and monkeys; they imply a large overlap between superordinate visual representations in humans and macaques as well as the implicit use of experienced associations between object and context.

The extent to which object identification is influenced by the background of the scene is still controversial. On the one hand, the global context of a scene might be considered as an ultimate representation, suggesting that object processing is performed almost systematically before scene context analysis. Alternatively, the gist of a scene could be extracted sufficiently early to be able to influence object categorization. It is thus essential to assess the processing time of scene context. In the present study, we used a go/no-go rapid visual categorization task in which subjects had to respond as fast as possible when they saw a "man-made environment", or a "natural environment", that was flashed for only 26 ms. "Man-made" and "natural" scenes were categorized with very high accuracy (both around 96%) and very short reaction times (median RT both around 390 ms). Compared with previous results from our group, these data demonstrate that global context categorization is remarkably fast: (1) it is as fast as object categorization [Fabre-Thorpe, M., Delorme, A., Marlot, C., & Thorpe, S. (2001). A limit to the speed of processing in ultra-rapid visual categorization of novel natural scenes. Journal of Cognitive Neuroscience, 13(2), 171-180]; (2) it is faster than contextual categorization at more detailed levels such as sea, mountain, indoor or urban contexts [Rousselet, G. A., Joubert, O. R., & Fabre-Thorpe, M. (2005). How long to get to the "gist" of real-world natural scenes? Visual Cognition, 12(6), 852-877]. Further analysis showed that the efficiency of contextual categorization was impaired by the presence of a salient object in the scene especially when the object was incongruent with the context. Processing of natural scenes might thus involve in parallel the extraction of the global gist of the scene and the concurrent object processing leading to categorization. These data also suggest early interactions between scene and object representations compatible with contextual influences on object categorization in a parallel network.

Humans are fast and accurate at performing an animal categorization task with natural photographs briefly flashed centrally. Here, this central categorization task is compared to a three position task in which photographs could appear randomly either centrally, or at 3.6 degrees eccentricity (right or left) of the fixation point. A mild behavioral impairment was found with peripheral stimuli with no evidence in support of hemispheric superiority; but enlarging the window of spatial attention to three possible stimuli locations had no behavioral cost on the processing of central images. Performance in the central categorization task has been associated with a large difference between the potentials evoked to target and non-target correct trials, starting about 150 ms after stimulus onset on frontal sites. Present results show that this activity originates within extrastriate visual cortices and probably reflects perceptual stimuli differences processed within areas involved in object recognition. Latencies, slopes, and peak amplitudes of this differential activity were invariant to stimulus position and attentional load. Stimulus location uncertainty and lateralization did not affect speed of visual processing.

The prefrontal cortex supports many cognitive abilities, which humans share to some degree with monkeys. The specialized functions of the prefrontal cortex depend both on the nature of its inputs from other brain regions and on distinctive aspects of local processing. We used functional MRI to compare prefrontal activity between monkey and human subjects when they viewed identical images of objects, either intact or scrambled. Visual object-related activation of the lateral prefrontal cortex was observed in both species, but was stronger in monkeys than in humans, both in magnitude (factors 2-3) and in spatial extent (fivefold or more as a percentage of prefrontal volume). This difference was observed for two different stimulus sets, at two field strengths, and over a range of tasks. These results suggest that there may be more volitional control over visual processing in humans than in monkeys.

We compared neural substrates of two-dimensional shape processing in human and nonhuman primates using functional magnetic resonance (MR) imaging in awake subjects. The comparison of MR activity evoked by viewing intact and scrambled images of objects revealed shape-sensitive regions in occipital, temporal, and parietal cortex of both humans and macaques. Intraparietal cortex in monkeys was relatively more two-dimensional shape sensitive than that of humans. In both species, there was an interaction between scrambling and type of stimuli (grayscale images and drawings), but the effect of stimulus type was much stronger in monkeys than in humans. Shape- and motion-sensitive regions overlapped to some degree. However, this overlap was much more marked in humans than in monkeys. The shape-sensitive regions can be used to constrain the warping of monkey to human cortex and suggest a large expansion of lateral parietal and superior temporal cortex in humans compared with monkeys.

Using functional magnetic resonance imaging (fMRI), we mapped the retinotopic organization throughout the visual cortex of fixating monkeys. The retinotopy observed in areas V1, V2, and V3 was completely consistent with the classical view. V1 and V3 were bordered rostrally by a vertical meridian representation, and V2 was bordered by a horizontal meridian. More anterior in occipital cortex, both areas V3A and MT-V5 had lower and upper visual field representations split by a horizontal meridian. The rostral border of dorsal V4 was characterized by the gradual transition of a representation of the vertical meridian (dorsally) to a representation of the horizontal meridian (more ventrally). Central and ventral V4, on the other hand, were rostrally bordered by a representation of the horizontal meridian. The eccentricity lines ran perpendicular to the ventral V3-V4 border but were parallel to the dorsal V3-V4 border. These results indicate different retinotopic organizations within dorsal and ventral V4, suggesting that the latter regions may not be merely the lower and upper visual field representations of a single area. Moreover, because the present fMRI data are in agreement with previously published electrophysiological results, reported distinctions in the retinotopic organization of human and monkey dorsal V4 reflect genuine species differences that cannot be attributed to technical confounds. Finally, aside from dorsal V4, the retinotopic organization of macaque early visual cortex (V1, V2, V3, V3A, and ventral V4) is remarkably similar to that observed in human fMRI studies. This finding indicates that early visual cortex is mostly conserved throughout hominid evolution.

Stereopsis, the perception of depth from small differences between the images in the two eyes, provides a rich model for investigating the cortical construction of surfaces and space. Although disparity-tuned cells have been found in a large number of areas in macaque visual cortex, stereoscopic processing in these areas has never been systematically compared using the same stimuli and analysis methods. In order to examine the global architecture of stereoscopic processing in primate visual cortex, we studied fMRI activity in alert, fixating human and macaque subjects. In macaques, we found strongest activation to near/far compared to zero disparity in areas V3, V3A, and CIPS. In humans, we found strongest activation to the same stimuli in areas V3A, V7, the V4d topolog (V4d-topo), and a caudal parietal disparity region (CPDR). Thus, in both primate species a small cluster of areas at the parieto-occipital junction appears to be specialized for stereopsis.

The present report reviews a series of functional magnetic resonance imaging (fMRI) activation studies conducted in parallel in awake monkeys and humans using the same motion stimuli in both species. These studies reveal that motion stimuli engage largely similar cortical regions in the two species. These common regions include MT/V5 and its satellites, of which FST contributes more to the human motion complex than is generally assumed in human imaging. These results also establish a direct link between selectivity of MT/V5 neurons for speed gradients and functional activation of human MT/V5 by three-dimensional (3D) structure from motion stimuli. On the other hand, striking functional differences also emerged: in humans V3A and several regions in the intraparietal sulcus (IPS) are much more motion sensitive than their simian counterparts.

Iron oxide contrast agents have been employed extensively in anesthetized rodents to enhance fMRI sensitivity and to study the physiology of cerebral blood volume (CBV) in relation to blood oxygen level-dependent (BOLD) signal following neuronal activation. This study quantified the advantages of exogenous agent for repeated neuroimaging in awake, nonhuman primates using a clinical 3 Tesla scanner. A monocrystalline iron oxide nanoparticle (MION) solution was injected at iron doses of 8 to 10 mg/kg in two macaque monkeys. Adverse behavioral effects due to contrast agent were not observed in either monkey using cumulative doses in excess of 60 mg/kg. Relative to BOLD imaging at 3 Tesla, MION increased functional sensitivity by an average factor of 3 across the brain for a stimulus of long duration. Rapid stimulus presentation attenuated MION signal changes more than BOLD signal changes, due to the slower time constant of the blood volume response relative to BOLD signal. Overall, the contrast agent produced a dramatic improvement in functional brain imaging results in the awake, behaving primate at this field strength. (c) 2002 Elsevier Science (USA).

To reduce the information gap between human neuroimaging and macaque physiology and anatomy, we mapped fMRI signals produced by moving and stationary stimuli (random dots or lines) in fixating monkeys. Functional sensitivity was increased by a factor of approximately 5 relative to the BOLD technique by injecting a contrast agent (monocrystalline iron oxide nanoparticle [MION]). Areas identified as motion sensitive included V2, V3, MT/V5, vMST, FST, VIP, and FEF (with moving dots), as well as V4, TE, LIP, and PIP (with random lines). These regions sensitive for moving dots are largely in agreement with monkey single unit data and (except for V3A) with human fMRI results. Moving lines activate some regions that have not been previously implicated in motion processing. Overall, the results clarify the relationship between the motion pathway and the dorsal stream in primates.

Event-related fMRI was used to investigate brain activation during a visual go/no-go categorization task based on colored photographs of natural scenes, similar to a previous ERP study by Thorpe et al. (1996, Nature 381: 520-522). Subjects had to press a key when an animal was present in the display. Stimuli were flashed for 33 ms using an intertrial interval of 5 s and a design that carefully balanced targets and distractors in a pseudo-random sequence. Activation produced by targets and distractors was compared with two different techniques, one based on correlations with the stimulation pattern, the other using simple t score statistics to compare selected scans. The contralateral primary motor cortex and the ipsilateral cerebellum were both more active following target trials than following distractors, thus confirming the sensitivity of the method. Differential activity was also seen in the posterior cingulate cortex, the fusiform, and the parahippocampic gyri. Activity in such structures could underlie the differential evoked-potentials reported previously in the same task. Surprisingly, in these visual structures, the signal was stronger following distractor trials than target ones. This result could be due to more prolonged processing on distractor trials. Alternatively, it could be that target detection induces strong activation of a small proportion of neurons, which, because of competitive inhibitory mechanisms, could result in a decrease in activity for the population as a whole. We suggest that this kind of mechanism could also account for the decreases in signal observed in perceptual priming experiments., (Copyright 2000 Academic Press.)

How long does it take for the human visual system to process a complex natural image? Subjectively, recognition of familiar objects and scenes appears to be virtually instantaneous, but measuring this processing time experimentally has proved difficult. Behavioural measures such as reaction times can be used, but these include not only visual processing but also the time required for response execution. However, event-related potentials (ERPs) can sometimes reveal signs of neural processing well before the motor output. Here we use a go/no-go categorization task in which subjects have to decide whether a previously unseen photograph, flashed on for just 20 ms, contains an animal. ERP analysis revealed a frontal negativity specific to no-go trials that develops roughly 150 ms after stimulus onset. We conclude that the visual processing needed to perform this highly demanding task can be achieved in under 150 ms.