Previous studies demonstrated that pairing a visual stimulus and electrical micro-stimulation of the ventral tegmental area (VTA-EM) for multiple days is sufficient to induce visual cortical plasticity and changes perception. However, a brief epoch of VTA-EM–stimulus pairing within a single day has been shown to result in a behavioral preference for the paired stimulus. Here, we investigated whether a brief single-day session of VTA-EM–stimulus pairings is sufficient to induce changes in visual cortical responses. We examined macaque posterior inferior temporal (PIT) cortex because previous studies demonstrated response changes after VTA-EM stimulus pairing in that area. Multi-unit recordings in PIT were interleaved with VTA-EM–stimulus pairing epochs. During the short VTA-EM–stimulus pairing epochs (60 pairings), one image (fractal) was paired with VTA-EM (STIM) whereas another, unpaired fractal was presented as control. Two other fractals (dummies) were presented only during the recordings. The difference in response between the STIM and control fractals already increased after the first VTA-EM–stimulus pairing epoch, reflecting a relative increase of the response to the STIM fractal. However, the response to the STIM fractal did not increase further with more VTA-EM–stimulus pairing epochs. The relative increase in firing rate for the paired fractal was present early in the response, in line with a local/ bottom–up origin. These effects were absent when comparing the responses to the dummies pre- and post-VTA-EM. This study shows that pairing a visual image and VTA-EM in a brief single-day session is sufficient to increase the response for the paired image in macaque PIT.

An unresolved question in cognitive neuroscience is how representations of object categories at different levels (basic and superordinate) develop during the course of the neural response within an area. To address this, we decoded categories of different levels from the spiking responses of populations of neurons recorded in two fMRI-defined body patches in the macaque STS. Recordings of the two patches were made in the same animals with the same stimuli. Support vector machine classifiers were trained at brief response epochs and tested at the same or different epochs, thus assessing whether category representations change during the course of the response. In agreement with hierarchical processing within the body patch network, the posterior body patch mid STS body (MSB) showed an earlier onset of categorization compared with the anterior body patch anterior STS body (ASB), irrespective of the categorization level. Decoding of the superordinate body versus nonbody categories was less dynamic in MSB than in ASB, with ASB showing a biphasic temporal pattern. Decoding of the ordinate-level category human versus monkey bodies showed similar temporal patterns in both patches. The decoding onset of superordinate categorizations involving bodies was as early as for basic-level categorization, suggesting that previously reported differences between the onset of basic and superordinate categorizations may depend on the area. The qualitative difference between areas in their dynamics of category representation may hinder the interpretation of decoding dynamics based on EEG or MEG, methods that may mix signals of different areas.

Animals and humans learn statistical regularities that are embedded in sequences of stimuli. The neural mechanisms of such statistical learning are still poorly understood. Previous work in macaque inferior temporal (IT) cortex demonstrated suppressed spiking activity to visual images of a sequence in which the stimulus order was defined by transitional probabilities (labeled as “standard” sequence), compared with a sequence in which the stimulus order was random (“random” sequence). Here, we asked whether IT neurons encode the images of the standard sequence more accurately compared with images of the random sequence. Previous human fMRI studies in different sensory modalities also found a suppressed response to expected relative to unexpected stimuli but obtained various results regarding the effect of expectation on encoding, with one study reporting an improved classification accuracy of expected stimuli despite the reduced activation level. We employed a linear classifier to decode image identity from the spiking responses of the recorded IT neurons. We found a greater decoding accuracy for images of the standard compared with the random sequence during the early part of the stimulus presentation, but further analyses suggested that this reflected the sustained, stimulus-selective activity from the previous stimulus of the sequence, which is typical for IT neurons. However, the peak decoding accuracy was lower for the standard compared with the random sequence, in line with the reduced response to the former compared with the latter images. These data suggest that macaque IT neurons represent less accurately predictable compared with unpredictable images.

The anterior intraparietal area (AIP) of macaques contains neurons that signal the depth structure of disparity-defined 3-D shapes. Previous studies have suggested that AIP's depth information is used for sensorimotor transformations related to the efficient grasping of 3-D objects. We trained monkeys to categorize disparity-defined 3-D shapes and examined whether neuronal activity in AIP may also underlie pure perceptual categorization behavior. We first show that neurons with a similar 3-D shape preference cluster in AIP. We then demonstrate that the monkeys' 3-D shape discrimination performance depends on the position in depth of the stimulus and that this performance difference is reflected in the activity of AIP neurons. We further reveal correlations between the neuronal activity in AIP and the subject's subsequent choices and RTs during 3-D shape categorization. Our findings propose AIP as an important processing stage for 3-D shape perception.

Functional imaging studies in human and nonhuman primates have demonstrated regions in the brain that show category selectivity for faces or (headless) bodies. Recent fMRI-guided single unit studies of the macaque face category-selective regions have increased our understanding of the response properties of single neurons in these face patches. However, much less is known about the response properties of neurons in the fMRI-defined body category-selective regions (“body patches”). Recently, we reported that the majority of single neurons in one fMRI-defined body patch, the mid-STS body patch, responded more strongly to bodies compared with other objects. Here we assessed the tolerance of these neurons' responses and stimulus preference for shape-preserving image transformations. After mapping the receptive field of the single neurons, we found that their stimulus preference showed a high degree of tolerance for changes in the position and size of the stimulus. However, their response strongly depended on the in-plane orientation of a body. The selectivity of most neurons was, to a large degree, preserved when silhouettes were presented instead of the original textured and shaded images, suggesting that mainly shape-based features are driving these neurons. In a human psychophysical study, we showed that the information present in silhouettes is largely sufficient for body versus nonbody categorization. These data suggest that mid-STS body patch neurons respond predominantly to oriented shape features that are prevalent in images of bodies. Their responses can inform position- and retinal size-invariant body categorization and discrimination based on shape.

Practicing simple visual detection and discrimination tasks improves performance, a signature of adult brain plasticity. The neural mechanisms that underlie these changes in performance are still unclear. Previously, we reported that practice in discriminating the orientation of noisy gratings (coarse orientation discrimination) increased the ability of single neurons in the early visual area V4 to discriminate the trained stimuli. Here, we ask whether practice in this task also changes the stimulus tuning properties of later visual cortical areas, despite the use of simple grating stimuli. To identify candidate areas, we used fMRI to map activations to noisy gratings in trained rhesus monkeys, revealing a region in the posterior inferior temporal (PIT) cortex. Subsequent single unit recordings in PIT showed that the degree of orientation selectivity was similar to that of area V4 and that the PIT neurons discriminated the trained orientations better than the untrained orientations. Unlike in previous single unit studies of perceptual learning in early visual cortex, more PIT neurons preferred trained compared with untrained orientations. The effects of training on the responses to the grating stimuli were also present when the animals were performing a difficult orthogonal task in which the grating stimuli were task-irrelevant, suggesting that the training effect does not need attention to be expressed. The PIT neurons could support orientation discrimination at low signal-to-noise levels. These findings suggest that extensive practice in discriminating simple grating stimuli not only affects early visual cortex but also changes the stimulus tuning of a late visual cortical area.

Stimulus repetition produces a decrease of the response in many cortical areas and different modalities. This adaptation is highly prominent in macaque inferior temporal (IT) neurons. Here we ask how these repetition-induced changes in IT responses affect the accuracy by which IT neurons encode objects. This question bears on the functional consequences of adaptation, which are still unclear. We recorded the responses of single IT neurons to sequences of familiar shapes, each shown for 300 msec with an ISI of the same duration. The difference in shape between the two successively presented stimuli,that is, adapter and test, varied parametrically. The discriminability of the test stimuli was reduced for repeated compared with nonrepeated stimuli. In some conditions for which adapter and test shapes differed, the cross-adaptation resulted in an enhanced discriminability. These single cell results were confirmed in a second experiment in which we recorded multiunit spiking activity using a laminar microelectrode in macaque IT. Two familiar stimuli were presented successively for 500 msec each and separated with an ISI of the same duration. Trials consisted either of a repetition of the same stimulus or of their alternation. Small neuronal populations showed decreased classification accuracy for repeated compared with nonrepeated test stimuli, but classification was enhanced for the test compared with adapter stimuli when the test stimulus differed from recently seen stimuli. These findings suggest that short-term, stimulus-specific adaptation in IT supports efficient coding of stimuli that differ from recently seen ones while impairing the coding of repeated stimuli.

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.

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.

It has long been known that macaque inferior temporal (IT) neurons tend to fire more strongly to some shapes than to others, and that different IT neurons can show markedly different shape preferences. Beyond the discovery that these preferences can be elicited by features of moderate complexity, no general principle of (nonface) object recognition had emerged by which this enormous variation in selectivity could be understood. Psychophysical, as well as computational work, suggests that one such principle is the difference between viewpoint-invariant, nonaccidental (NAP) and view-dependent, metric shape properties (MPs). We measured the responses of single IT neurons to objects differing in either a NAP (namely, a change in a geon) or an MP of a single part, shown at two orientations in depth. The cells were more sensitive to changes in NAPs than in MPs, even though the image variation (as assessed by wavelet-like measures) produced by the former were smaller than the latter. The magnitude of the response modulation from the rotation itself was, on average, similar to that produced by the NAP differences, although the image changes from the rotation were much greater than that produced by NAP differences. Multidimensional scaling of the neural responses indicated a NAP/MP dimension, independent of an orientation dimension. The present results thus demonstrate that a significant portion of the neural code of IT cells represents differences in NAPs rather than MPs. This code may enable immediate recognition of novel objects at new views.