Receptor architecture of macaque and human early visual areas: not equal, but comparable

Existing cytoarchitectonic maps of the human and macaque posterior occipital cortex differ in the number of areas they display, thus hampering identification of homolog structures. We applied quantitative in vitro receptor autoradiography to characterize the receptor architecture of the primary visual and early extrastriate cortex in macaque and human brains, using previously published cytoarchitectonic criteria as starting point of our analysis. We identified 8 receptor architectonically distinct areas in the macaque brain (mV1d, mV1v, mV2d, mV2v, mV3d, mV3v, mV3A, mV4v), and their respective counterpart areas in the human brain (hV1d, hV1v, hV2d, hV2v, hV3d, hV3v, hV3A, hV4v). Mean densities of 14 neurotransmitter receptors were quantified in each area, and ensuing receptor fingerprints used for multivariate analyses. The 1st principal component segregated macaque and human early visual areas differ. However, the 2nd principal component showed that within each species, area-specific differences in receptor fingerprints were associated with the hierarchical processing level of each area. Subdivisions of V2 and V3 were found to cluster together in both species and were segregated from subdivisions of V1 and from V4v. Thus, comparative studies like this provide valuable architectonic insights into how differences in underlying microstructure impact evolutionary changes in functional processing of the primate brain and, at the same time, provide strong arguments for use of macaque monkey brain as a suitable animal model for translational studies.

Highly accurate retinotopic maps of the physiological blind spot in human visual cortex

The physiological blind spot is a naturally occurring scotoma corresponding with the optic disc in the retina of each eye. Even during monocular viewing, observers are usually oblivious to the scotoma, in part because the visual system extrapolates information from the surrounding area. Unfortunately, studying this visual field region with neuroimaging has proven difficult, as it occupies only a small part of retinotopic cortex. Here we used functional magnetic resonance imaging and a novel data-driven method for mapping the retinotopic organization in and around the blind spot representation in V1. Our approach allowed for highly accurate reconstructions of the extent of an observer's blind spot, and out-performed conventional model-based analyses. This method opens exciting opportunities to study the plasticity of receptive fields after visual field loss, and our data add to evidence suggesting that the neural circuitry responsible for impressions of perceptual completion across the physiological blind spot most likely involves regions of extrastriate cortex - beyond V1.

Normalization by orientation anisotropy in human V1-V3

An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a two-stage computation. The first stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of linear filters in quadrature phase. The second stage is normalization, in which a local population of complex cells mutually inhibit one another. Because the population includes cells tuned to a range of orientations and spatial frequencies, the result is that the responses are effectively normalized by the local stimulus contrast. Here, using evidence from human functional MRI, we show that the classical model fails to account for the relative responses to two classes of stimuli: straight, parallel, band-passed contours (gratings), and curved, band-passed contours (snakes). The snakes elicit fMRI responses that are about twice as large as the gratings, yet traditional energy models, including normalized energy models, predict responses that are about the same. Here, we propose a computational model, in which responses are normalized not by the sum of the contrast energy, but by the orientation anisotropy, computed as the variance in contrast energy across orientation channels. We first show that this model accounts for differential responses to these two classes of stimuli. We then show that the model successfully generalizes to other band-pass textures, both in V1 and in extrastriate cortex (V2 and V3). We speculate that high anisotropy in the orientation responses leads to larger outputs in downstream areas, which in turn normalizes responses in these later visual areas, as well as in V1 via feedback.

Robot faces elicit responses intermediate to human faces and objects at face-sensitive ERP components

Face recognition is supported by selective neural mechanisms that are sensitive to various aspects of facial appearance. These include event-related potential (ERP) components like the P100 and the N170 which exhibit different patterns of selectivity for various aspects of facial appearance. Examining the boundary between faces and non-faces using these responses is one way to develop a more robust understanding of the representation of faces in extrastriate cortex and determine what critical properties an image must possess to be considered face-like. Robot faces are a particularly interesting stimulus class to examine because they can differ markedly from human faces in terms of shape, surface properties, and the configuration of facial features, but are also interpreted as social agents in a range of settings. In the current study, we thus chose to investigate how ERP responses to robot faces may differ from the response to human faces and non-face objects. In two experiments, we examined how the P100 and N170 responded to human faces, robot faces, and non-face objects (clocks). In Experiment 1, we found that robot faces elicit intermediate responses from face-sensitive components relative to non-face objects (clocks) and both real human faces and artificial human faces (computer-generated faces and dolls). These results suggest that while human-like inanimate faces (CG faces and dolls) are processed much like real faces, robot faces are dissimilar enough to human faces to be processed differently. In Experiment 2 we found that the face inversion effect was only partly evident in robot faces. We conclude that robot faces are an intermediate stimulus class that offers insight into the perceptual and cognitive factors that affect how social agents are identified and categorized.

Electrophysiological priming effects demonstrate independence and overlap of visual regularity representations in the extrastriate cortex

An Event Related Potential (ERP) component called the Sustained Posterior Negativity (SPN) is generated by regular visual patterns (e.g. vertical reflectional symmetry, horizontal reflectional symmetry or rotational symmetry). Behavioural studies suggest symmetry becomes increasingly salient when the exemplars update rapidly. In line with this, Experiment 1 (N = 48) found that SPN amplitude increased when three different reflectional symmetry patterns were presented sequentially. We call this effect ‘SPN priming’. We then exploited SPN priming to investigate independence of different symmetry representations. SPN priming did not survive changes in retinal location (Experiment 2, N = 48) or non-orthogonal changes in axis orientation (Experiment 3, N = 48). However, SPN priming transferred between vertical and horizontal axis orientations (Experiment 4, N = 48) and between reflectional and rotational symmetry (Experiment 5, N = 48). SPN priming is interesting in itself, and a useful new method for identifying functional boundaries of the symmetry response. We conclude that visual regularities at different retinal locations are coded independently. However, there is some overlap between different regularities presented at the same retinal location.

Differentiating Real-World Autobiographical Experiences without Recourse to Behaviour

Investigating human consciousness based on brain activity alone is a key challenge in cognitive neuroscience. One of its central facets, the ability to form autobiographical memories, has been investigated through several fMRI studies that have revealed a pattern of activity across a network of frontal, parietal, and medial temporal lobe regions when participants view personal photographs, as opposed to when they view photographs from someone else’s life. Here, our goal was to attempt to decode when participants were re-experiencing an entire event, captured on video from a first-person perspective, relative to a very similar event experienced by someone else. Participants were asked to sit passively in a wheelchair while a researcher pushed them around a local mall. A small wearable camera was mounted on each participant, in order to capture autobiographical videos of the visit from a first-person perspective. One week later, participants were scanned while they passively viewed different categories of videos; some were autobiographical, while others were not. A machine-learning model was able to successfully classify the video categories above chance, both within and across participants, suggesting that there is a shared mechanism differentiating autobiographical experiences from non-autobiographical ones. Moreover, the classifier brain maps revealed that the fronto-parietal network, mid-temporal regions and extrastriate cortex were critical for differentiating between autobiographical and non-autobiographical memories. We argue that this novel paradigm captures the true nature of autobiographical memories, and is well suited to patients (e.g., with brain injuries) who may be unable to respond reliably to traditional experimental stimuli.

Transformation from local image contrast to location-independent numerosity tuning in human extrastriate cortex

Many animals use visual numerosity, the number of items in a group, to guide behavior. Neurons in human association cortices show numerosity-tuned responses, decreasing amplitude with distance from a specific numerosity. How are such responses derived from early visual responses? Recent studies show aggregate response amplitudes in human early visual cortex monotonically increase with numerosity, regardless of object size and spacing. This is surprising because numerosity is typically considered a high-level visual or cognitive feature. Here we first use computational modelling of 7T fMRI data to show these monotonic responses originate at the stimulus's retinotopic location in primary visual cortex (V1). Given this location, we then ask whether these monotonic responses can be better described by V1's established response properties. We characterize the Fourier decomposition (into contrast at specific orientations and spatial frequencies) of laboratory numerosity stimuli. This demonstrates that aggregate Fourier power (at all orientations and spatial frequencies) nonlinearly follows numerosity with little effect of item size, spacing or shape: it is proportional to numerosity at a fixed contrast. This nonlinear relationship lets us distinguish predictions of responses to Fourier power and numerosity. Monotonic responses are better predicted by Fourier power, later tuned responses are better predicted by numerosity. Tuned responses emerge after lateral occipital cortex and are independent of retinotopic location. We propose that numerosity's straightforward perception and neural responses reflect its straightforward estimation from early visual spatial frequency domain image representations. Our numerical vision may have built on behaviorally beneficial analysis of spatial frequency in simpler animals.

The Neural Bases of Drawing. A Meta-analysis and a Systematic Literature Review of Neurofunctional Studies in Healthy Individuals

Drawing is a multi-component process requiring a wide range of cognitive abilities. Several studies on patients with focal brain lesions and functional neuroimaging studies on healthy individuals demonstrated that drawing is associated with a wide brain network. However, the neural structures specifically related to drawing remain to be better comprehended. We conducted a systematic review complemented by a meta-analytic approach to identify the core neural underpinnings related to drawing in healthy individuals. In analysing the selected studies, we took into account the type of the control task employed (i.e. motor or non-motor) and the type of drawn stimulus (i.e. geometric, figurative, or nonsense). The results showed that a fronto-parietal network, particularly on the left side of the brain, was involved in drawing when compared with other motor activities. Drawing figurative images additionally activated the inferior frontal gyrus and the inferior temporal cortex, brain areas involved in selection of semantic features of objects and in visual semantic processing. Moreover, copying more than drawing from memory was associated with the activation of extrastriate cortex (BA 18, 19). The activation likelihood estimation coordinate-based meta-analysis revealed a core neural network specifically associated with drawing which included the premotor area (BA 6) and the inferior parietal lobe (BA 40) bilaterally, and the left precuneus (BA 7).These results showed that a fronto-parietal network is specifically involved in drawing and suggested that a crucial role is played by the (left) inferior parietal lobe, consistent with classical literature on constructional apraxia.

Cholinergic manipulations affect sensory responses but not attentional enhancement in macaque MT

Background Attentional modulation in the visual cortex of primates is characterized by multiplicative changes of sensory responses with changes in the attentional state of the animal. The cholinergic system has been linked to such gain changes in V1. Here, we aim to determine if a similar link exists in macaque area MT. While rhesus monkeys performed a top-down spatial attention task, we locally injected a cholinergic agonist or antagonist and recorded single-cell activity. Results Although we confirmed cholinergic influences on sensory responses, there was no additional cholinergic effect on the attentional gain changes. Neither a muscarinic blockage nor a local increase in acetylcholine led to a significant change in the magnitude of spatial attention effects on firing rates. Conclusions This suggests that the cellular mechanisms of attentional modulation in the extrastriate cortex cannot be directly inferred from those in the primary visual cortex.

Retinotopic organization of visual cortex in human infants

Vision develops rapidly during infancy, yet how visual cortex is organized during this period is unclear. One possibility is that the retinotopic organization of visual cortex emerges gradually as perceptual abilities improve. This may result in a hierarchical maturation of visual areas from striate to extrastriate cortex. Another possibility is that retinotopic organization is present from early infancy. This early maturation of area boundaries and tuning could scaffold further developmental changes. Here we test the functional maturity of infant visual cortex by performing retinotopic mapping with fMRI. Infants aged 5–23 months had retinotopic maps, with alternating preferences for vertical and horizontal meridians indicative of area boundaries from V1 to V4, and an orthogonal gradient of preferences from high to low spatial frequencies indicative of growing receptive field sizes. Although present in the youngest infants, these retinotopic maps showed subtle agerelated changes, suggesting that early maturation undergoes continued refinement.