Higher Visual Areas Research Articles

A hierarchical model of perceptual multistability involving interocular grouping.

Ambiguous visual images can generate dynamic and stochastic switches in perceptual interpretation known as perceptual rivalry. Such dynamics have primarily been studied in the context of rivalry between two percepts, but there is growing interest in the neural mechanisms that drive rivalry between more than two percepts. In recent experiments, we showed that split images presented to each eye lead to subjects perceiving four stochastically alternating percepts (Jacot-Guillarmod et al. Vision research, 133, 37-46, 2017): two single eye images and two interocularly grouped images. Here we propose a hierarchical neural network model that exhibits dynamics consistent with our experimental observations. The model consists of two levels, with the first representing monocular activity, and the second representing activity in higher visual areas. The model produces stochastically switching solutions, whose dependence on task parameters is consistent with four generalized Levelt Propositions, and with experiments. Moreover, dynamics restricted to invariant subspaces of the model demonstrate simpler forms of bistable rivalry. Thus, our hierarchical model generalizes past, validated models of binocular rivalry. This neuromechanistic model also allows us to probe the roles of interactions between populations at the network level. Generalized Levelt's Propositions hold as long as feedback from the higher to lower visual areas is weak, and the adaptation and mutual inhibition at the higher level is not too strong. Our results suggest constraints on the architecture of the visual system and show that complex visual stimuli can be used in perceptual rivalry experiments to develop more detailed mechanistic models of perceptual processing.

Visuocortical tuning to a threat-related feature persists after extinction and consolidation of conditioned fear

Neurons in the visual cortex sharpen their orientation tuning as humans learn aversive contingencies. A stimulus orientation (CS+) that reliably predicts an aversive noise (unconditioned stimulus: US) is selectively enhanced in lower-tier visual cortex, while similar unpaired orientations (CS−) are inhibited. Here, we examine in male volunteers how sharpened visual processing is affected by fear extinction learning (where no US is presented), and how fear and extinction memory undergo consolidation one day after the original learning episode. Using steady-state visually evoked potentials from electroencephalography in a fear generalization task, we found that extinction learning prompted rapid changes in orientation tuning: Both conditioned visuocortical and skin conductance responses to the CS+ were strongly reduced. Next-day re-testing (delayed recall) revealed a brief but precise return-of-tuning to the CS+ in visual cortex accompanied by a brief, more generalized return-of-fear in skin conductance. Explorative analyses also showed persistent tuning to the threat cue in higher visual areas, 24 h after successful extinction, outlasting peripheral responding. Together, experience-based changes in the sensitivity of visual neurons show response patterns consistent with memory consolidation and spontaneous recovery, the hallmarks of long-term neural plasticity.

A segregated cortical stream for retinal direction selectivity

Visual features extracted by retinal circuits are streamed into higher visual areas (HVAs) after being processed along the visual hierarchy. However, how specialized neuronal representations of HVAs are built, based on retinal output channels, remained unclear. Here, we addressed this question by determining the effects of genetically disrupting retinal direction selectivity on motion-evoked responses in visual stages from the retina to HVAs in mice. Direction-selective (DS) cells in the rostrolateral (RL) area that prefer higher temporal frequencies, and that change direction tuning bias as the temporal frequency of a stimulus increases, are selectively reduced upon retinal manipulation. DS cells in the primary visual cortex projecting to area RL, but not to the posteromedial area, were similarly affected. Therefore, the specific connectivity of cortico-cortical projection neurons routes feedforward signaling originating from retinal DS cells preferentially to area RL. We thus identify a cortical processing stream for motion computed in the retina.

Unique Spatial Integration in Mouse Primary Visual Cortex and Higher Visual Areas.

Neurons in the visual system integrate over a wide range of spatial scales. This diversity is thought to enable both local and global computations. To understand how spatial information is encoded across the mouse visual system, we use two-photon imaging to measure receptive fields (RFs) and size-tuning in primary visual cortex (V1) and three downstream higher visual areas (HVAs: LM (lateromedial), AL (anterolateral), and PM (posteromedial)) in mice of both sexes. Neurons in PM, compared with V1 or the other HVAs, have significantly larger RF sizes and less surround suppression, independent of stimulus eccentricity or contrast. To understand how this specialization of RFs arises in the HVAs, we measured the spatial properties of V1 inputs to each area. Spatial integration of V1 axons was remarkably similar across areas and significantly different from the tuning of neurons in their target HVAs. Thus, unlike other visual features studied in this system, specialization of spatial integration in PM cannot be explained by specific projections from V1 to the HVAs. Further, the differences in RF properties could not be explained by differences in convergence of V1 inputs to the HVAs. Instead, our data suggest that distinct inputs from other areas or connectivity within PM may support the area's unique ability to encode global features of the visual scene, whereas V1, LM, and AL may be more specialized for processing local features.SIGNIFICANCE STATEMENT Surround suppression is a common feature of visual processing whereby large stimuli are less effective at driving neuronal responses than smaller stimuli. This is thought to enhance efficiency in the population code and enable higher-order processing of visual information, such as figure-ground segregation. However, this comes at the expense of global computations. Here we find that surround suppression is not equally represented across mouse visual areas: primary visual cortex has substantially more surround suppression than higher visual areas, and one higher area has significantly less suppression than two others examined, suggesting that these areas have distinct functional roles. Thus, we have identified a novel dimension of specialization in the mouse visual cortex that may enable both local and global computations.

A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex.

SummaryTo understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes cortical activity from nearly 60,000 neurons from 6 visual areas, 4 layers, and 12 transgenic mouse lines from 243 adult mice, in response to a systematic set of visual stimuli. We classify neurons based on joint reliabilities to multiple stimuli and validate this functional classification with models of visual responses. While most classes are characterized by responses to specific subsets of the stimuli, the largest class is not reliably responsive to any of the stimuli and becomes progressively larger in higher visual areas. These classes reveal a functional organization wherein putative dorsal areas show specialization for visual motion signals.

Activity in Lateral Visual Areas Contributes to Surround Suppression in Awake Mouse V1.

Neuronal response to sensory stimuli depends on the context. The response in primary visual cortex (V1), for instance, is reduced when a stimulus is surrounded by a similar stimulus [1-3]. The source of this surround suppression is partially known. In mouse, local horizontal integration by somatostatin-expressing interneurons contributes to surround suppression [4]. In primates, however, surround suppression arises too quickly to come from local horizontal integration alone, and myelinated axons from higher visual areas, where cells have larger receptive fields, are thought to provide additional surround suppression [5, 6]. Silencing higher visual areas indeed decreased surround suppression in the awake primate by increasing responses to large stimuli [7, 8], although not under anesthesia [9, 10]. In smaller mammals, like mice, fast surround suppression could be possible without feedback. Recent studies revealed a small reduction in V1 responses when silencing higher areas [11, 12] but have not investigated surround suppression. To determine whether higher visual areas contribute to V1 surround suppression, even when this is not necessary for fast processing, we inhibited the areas lateral to V1, particularly the lateromedial area (LM), a possible homolog of primate V2 [13], while recording in V1 of awake and anesthetized mice. We found that part of the surround suppression depends on activity from lateral visual areas in the awake, but not anesthetized, mouse. Inhibiting the lateral visual areas specifically increased responses in V1 to large stimuli. We present a model explaining how excitatory feedback to V1 can have these suppressive effects for large stimuli.

Altered effective connectivity of primary visual cortex in primary angle closure glaucoma using Granger causality analysis

Background Previous neuroimaging studies demonstrated that primary angle closure glaucoma patients were associated with abnormal intrinsic brain activity in primary visual cortex (V1). Purpose The purpose of this study was to investigate the effective connectivity patterns of V1 in patients with primary angle closure glaucoma. Material and Methods Thirty-seven patients with primary angle closure glaucoma (20 men, 17 women) and 36 healthy controls (20 men, 16 women) closely matched for age, sex, and education, underwent resting-state MRI scans. A voxel-wise Granger causality analysis method was performed to explore different effective connectivity pattern of V1 between the two groups. Results Compared with healthy controls, patients with primary angle closure glaucoma showed decreased effective connectivity from the left V1 to left cuneus and increased effective connectivity from the left V1 to left precentral gyrus and right supplementary motor area. Meanwhile, patients with primary angle closure glaucoma showed decreased effective connectivity from left precentral gyrus to left V1 and right frontal middle gyrus to left V1. In addition, patients with primary angle closure glaucoma showed a decreased effective connectivity from the right V1 to left cuneus/calcarine and increased effective connectivity from the right V1 to left inferior frontal gyrus and right caudate. Meanwhile, patients with primary angle closure glaucoma showed decreased effective connectivity from right middle frontal gyrus/precentral gyrus to right V1 and left precentral gyrus to right V1. Conclusion Our results highlighted that patients with primary angle closure glaucoma had abnormal effective connectivity between V1 and higher visual area, motor cortices, somatosensory cortices, and frontal lobe, which indicated that they might present with abnormal top-down modulations, visual imagery, vision-motor function, and vision-related higher cognition function.

Rethinking primary visual cortex function

Neuroscience Understanding how color is coded in the brain is central to vision research. The presently dominant model suggests that color and orientation are separately extracted in the primate primary visual cortex. These characteristics are thought to be represented by neurons located in different cortical columns that project separately to higher visual areas for further processing. Working with macaques, Garg et al. recorded from thousands of neurons using two-photon calcium imaging with single-neuron resolution. Nearly half of sampled hue-selective neurons responded more strongly to equiluminant colored stimuli than to full-contrast achromatic stimuli. A majority of strongly color-preferring neurons were also orientation selective. Processing of orientation and color is thus combined at the earliest stages of visual processing, which challenges existing models. Science , this issue p. [1275][1] [1]: /lookup/doi/10.1126/science.aaw5868

Characterisation of nonlinear receptive fields of visual neurons by convolutional neural network

A comprehensive understanding of the stimulus-response properties of individual neurons is necessary to crack the neural code of sensory cortices. However, a barrier to achieving this goal is the difficulty of analysing the nonlinearity of neuronal responses. Here, by incorporating convolutional neural network (CNN) for encoding models of neurons in the visual cortex, we developed a new method of nonlinear response characterisation, especially nonlinear estimation of receptive fields (RFs), without assumptions regarding the type of nonlinearity. Briefly, after training CNN to predict the visual responses to natural images, we synthesised the RF image such that the image would predictively evoke a maximum response. We first demonstrated the proof-of-principle using a dataset of simulated cells with various types of nonlinearity. We could visualise RFs with various types of nonlinearity, such as shift-invariant RFs or rotation-invariant RFs, suggesting that the method may be applicable to neurons with complex nonlinearities in higher visual areas. Next, we applied the method to a dataset of neurons in mouse V1. We could visualise simple-cell-like or complex-cell-like (shift-invariant) RFs and quantify the degree of shift-invariance. These results suggest that CNN encoding model is useful in nonlinear response analyses of visual neurons and potentially of any sensory neurons.

A visual illusion that influences perception and action through the dorsal pathway

There are two main anatomically and physiologically defined visual pathways connecting the primary visual cortex with higher visual areas: the ventral and the dorsal pathway. The influential two-visual-systems hypothesis postulates that visual attributes are analyzed differently for different functions: in the dorsal pathway visual information is analyzed to guide actions, whereas in the ventral pathway visual information is analyzed for perceptual judgments. We here show that a person who cannot identify objects due to an extensive bilateral ventral brain lesion is able to judge the velocity at which an object moves. Moreover, both his velocity judgements and his interceptive actions are as susceptible to a motion illusion as those of people without brain lesions. These findings speak in favor of the idea that dorsal structures process information about attributes such as velocity, irrespective of whether such information is used for perceptual judgments or to guide actions.

Architecture and organization of mouse posterior parietal cortex relative to extrastriate areas.

The posterior parietal cortex (PPC) is a multifaceted region of cortex, contributing to several cognitive processes, including sensorimotor integration and spatial navigation. Although recent years have seen a considerable rise in the use of rodents, particularly mice, to investigate PPC and related networks, a coherent anatomical definition of PPC in the mouse is still lacking. To address this, we delineated the mouse PPC, using cyto- and chemoarchitectural markers from Nissl-, parvalbumin-and muscarinic acetylcholine receptor M2-staining. Additionally, we performed bilateral triple anterograde tracer injections in primary visual cortex (V1) and prepared flattened tangential sections from one hemisphere and coronal sections from the other, allowing us to co-register the cytoarchitectural features of PPC with V1 projections. This revealed that extrastriate area A was largely contained within lateral PPC, that medial PPC overlapped with the anterior portion of area AM, and that anterior RL overlapped partially with area PtP. Furthermore, triple anterograde tracer injections in PPC showed strong projections to associative thalamic nuclei as well as higher visual areas, orbitofrontal, cingulate and secondary motor cortices. Retrograde circuit mapping with rabies virus further showed that all cortical connections were reciprocal. These combined approaches provide a coherent definition of mouse PPC that incorporates laminar architecture, extrastriate projections, thalamic, and cortico-cortical connections.

Altered functional connectivity of primary visual cortex in late blindness.

BackgroundPrevious studies demonstrated that early blindness is associated with abnormal intrinsic functional connectivity (FC) between the primary visual cortex (V1) and other sensory areas. However, the V1 pattern of spontaneous neural activity occurring in late blindness (LB) remains unknown. The purpose of this study was to investigate the intrinsic FC patterns of V1 in LB.Materials and methodsThirty LB individuals (18 males and 12 females; mean age: 38.76±14.43 years) and 30 sighted controls (SCs) individuals (18 males and 12 females; mean age: 38.67±13.85 years) closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. Region of interest analysis was performed to extract the correlation coefficient matrix among each pair of Brodmann area (BA) 17 and FC between V1 and vision-related subcortical nuclei.ResultsCompared with SCs, LB individuals showed a decreased FC between the left V1 and the bilateral cuneus (CUN)/lingual gyrus (LGG)/calcarine (CAL) (BA 18/19/30) and left precentral gyrus (PreCG) and the postcentral gyrus (PostCG) (BA 2/3/4). Also, LB individuals showed a decreased FC between the right V1 and the bilateral CUN/LGG/CAL (BA 18/19/30) and the left PreCG and PostCG (BA 2/3/4/6) (voxel-level: P<0.01, cluster-level: P<0.05). Meanwhile, LB individuals showed a decreased FC between the left V1 and the right V1 and increased FC between the left V1 and the right superior colliculus, the right V1, and the left hippocampus (P<0.05). Moreover, a positive correlation was observed between the onset age of blindness and FC values in V1 to CUN/LGG/CAL in LB.ConclusionOur results highlighted that LB induces a decreased FC between V1 and higher visual areas, motor cortices, and somatosensory cortices at rest. This might indicate that LB humans could present with impaired top-down modulations, visual imagery, and vision-motor function.

Segregated Subnetworks of Intracortical Projection Neurons in Primary Visual Cortex

The rules by which neurons in neocortex choose their synaptic partners are not fully understood. In sensory cortex, intermingled neurons encode different attributes of sensory inputs and relay them to different long-range targets. While neurons with similar responses to sensory stimuli make connections preferentially, the relationship between synaptic connectivity within an area and long-range projection target remains unclear. We examined the local connectivity and visual responses of primary visual cortex neurons projecting to anterolateral (AL) and posteromedial (PM) higher visual areas in mice. Although the response properties of layer 2/3 neurons projecting to different targets were often similar, they avoided making connections with each other. Thus, projection target, in addition to response similarity, constrains local synaptic connectivity of AL and PM projection neurons. We propose that reduced crosstalk between different populations of projection neurons permits independent function of these output channels.

Early Visual Processing of Feature Saliency Tasks: A Review of Psychophysical Experiments.

The visual system is constantly bombarded with information originating from the outside world, but it is unable to process all the received information at any given time. In fact, the most salient parts of the visual scene are chosen to be processed involuntarily and immediately after the first glance along with endogenous signals in the brain. Vision scientists have shown that the early visual system, from retina to lateral geniculate nucleus (LGN) and then primary visual cortex, selectively processes the low-level features of the visual scene. Everything we perceive from the visual scene is based on these feature properties and their subsequent combination in higher visual areas. Different experiments have been designed to investigate the impact of these features on saliency and understand the relative visual mechanisms. In this paper, we review the psychophysical experiments which have been published in the last decades to indicate how the low-level salient features are processed in the early visual cortex and extract the most important and basic information of the visual scene. Important and open questions are discussed in this review as well and one might pursue these questions to investigate the impact of higher level features on saliency in complex scenes or natural images.

Evolution in Neuromodulation-The Differential Roles of Acetylcholine in Higher Order Association vs. Primary Visual Cortices.

This review contrasts the neuromodulatory influences of acetylcholine (ACh) on the relatively conserved primary visual cortex (V1), compared to the newly evolved dorsolateral prefrontal association cortex (dlPFC). ACh is critical both for proper circuit development and organization, and for optimal functioning of mature systems in both cortical regions. ACh acts through both nicotinic and muscarinic receptors, which show very different expression profiles in V1 vs. dlPFC, and differing effects on neuronal firing. Cholinergic effects mediate attentional influences in V1, enhancing representation of incoming sensory stimuli. In dlPFC ACh plays a permissive role for network communication. ACh receptor expression and ACh actions in higher visual areas have an intermediate profile between V1 and dlPFC. This changing role of ACh modulation across association cortices may help to illuminate the particular susceptibility of PFC in cognitive disorders, and provide therapeutic targets to strengthen cognition.

Higher visual responses in the temporal cortex of mice

The visual cortex of mice is a useful model for investigating the mammalian visual system. In primates, higher visual areas are classified into two parts, the dorsal stream (“where” pathway) and ventral stream (“what” pathway). The ventral stream is known to include a part of the temporal cortex. In mice, however, some cortical areas adjacent to the primary visual area (V1) in the occipital cortex are thought to be comparable to the ventral stream in primates, although the whole picture of the mouse ventral stream has never been elucidated. We performed wide-field Ca2+ imaging in awake mice to investigate visual responses in the mouse temporal cortex, and found that the postrhinal cortex (POR), posterior to the auditory cortex (AC), and the ectorhinal and temporal association cortices (ECT), ventral to the AC, showed clear visual responses to moving visual objects. The retinotopic maps in the POR and ECT were not clearly observed, and the amplitudes of the visual responses in the POR and ECT were less sensitive to the size of the objects, compared to visual responses in the V1. In the ECT, objects of different sizes activated different subareas. These findings strongly suggest that the mouse ventral stream extends to the ECT ventral to the AC, and that it has characteristic response properties that are markedly different from the response properties in the V1.

Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia)

Recognizing and categorizing visual stimuli are cognitive functions vital for survival, and an important feature of visual systems in primates as well as in birds. Visual stimuli are processed along the ventral visual pathway. At every stage in the hierarchy, neurons respond selectively to more complex features, transforming the population representation of the stimuli. It is therefore easier to read-out category information in higher visual areas. While explicit category representations have been observed in the primate brain, less is known on equivalent processes in the avian brain. Even though their brain anatomies are radically different, it has been hypothesized that visual object representations are comparable across mammals and birds. In the present study, we investigated category representations in the pigeon visual forebrain using recordings from single cells responding to photographs of real-world objects. Using a linear classifier, we found that the population activity in the visual associative area mesopallium ventrolaterale (MVL) distinguishes between animate and inanimate objects, although this distinction is not required by the task. By contrast, a population of cells in the entopallium, a region that is lower in the hierarchy of visual areas and that is related to the primate extrastriate cortex, lacked this information. A model that pools responses of simple cells, which function as edge detectors, can account for the animate vs. inanimate categorization in the MVL, but performance in the model is based on different features than in MVL. Therefore, processing in MVL cells is very likely more abstract than simple computations on the output of edge detectors.

Comparison of cortical responses to the activation of retina by visual stimulation and transcorneal electrical stimulation

BackgroundElectrical stimulation has been widely used in many ophthalmic diseases to modulate neuronal activities or restore partial visual function. Due to the different processing pathways and mechanisms, responses to visual and electrical stimulation in the primary visual cortex and higher visual areas might be different. This differences would shed some light on the properties of cortical responses evoked by electrical stimulation. ObjectiveThis study's goal was to directly compare the cortical responses evoked by visual and electrical stimulation and investigate the cortical processing of visual information and extrinsic electrical signal. MethodsOptical imaging of intrinsic signals (OIS) was used to probe the cortical hemodynamic responses in 11 cats. Transcorneal electrical stimulation (TES) through an ERG-jet contact lens electrode was used to activate visual cortices. Full-field and peripheral drifting gratings were used as the visual stimuli. ResultsThe response latency evoked by TES was shorter than that responding to visual stimulation (VS). Cortical responses evoked by VS were retinotopically organized, which was consistent with previous studies. On the other hand, the cortical region activated by TES was preferentially located in the secondary visual cortex (Area 18), while the primary visual cortex (Area 17) was activated by a higher current intensity. Compared with the full-field VS, the cortical response in Area 18 to TES with a current intensity above 1.2 mA was significantly stronger. ConclusionAccording to our results, we provided some evidence that the cortical processing of TES was influenced by the distribution of the electrical field in the retina and the activating threshold of different retinal ganglion cells.

Recurrent Processing of Contour Integration in the Human Visual Cortex as Revealed By fMRI-Guided TMS.

Contour integration is a critical step in visual perception because it groups discretely local elements into perceptually global contours. Previous investigations have suggested that striate and extrastriate visual areas are involved in this mid-level processing of visual perception. However, the temporal dynamics of these areas in the human brain during contour integration is less understood. The present study used functional magnetic resonance imaging-guided transcranial magnetic stimulation (TMS) to briefly disrupt 1 of 2 visual areas (V1/V2 and V3B) and examined the causal contributions of these areas to contour detection. The results demonstrated that the earliest critical time window at which behavioral detection performance was impaired by TMS pluses differed between V1/V2 and V3B. The first critical window of V3B (90-110 ms after stimulus onset) was earlier than that of V1/V2 (120-140 ms after stimulus onset), thus indicating that feedback connection from higher to lower area was necessary for complete contour integration. These results suggested that the fine processing of contour-related information in V1/V2 follows the generation of a coarse template in the higher visual areas, such as V3B. Our findings provide direct causal evidence that a recurrent mechanism is necessary for the integration of contours from cluttered background in the human brain.

The cognitive and neural mechanism of chunk decomposition: A particular form of insight

Chunk decomposition refers to decompose familiar patterns into their component elements so that they can be regrouped in a meaningful manner. It is a creative process that can lead to insight. According to the Representation Change Theory, chunk decomposition can help problem solvers to update their interpretation of the problem situation and then restructure the starting states of the problem′s representation. The concept chunk decomposition was put forward by theoretical psychologist Ohlsson S. in 1980s. Since then, studies about the cognitive and neural mechanisms of chunk decomposition have been going on for more than thirty years. Up to now, it has been largely explored. The main findings are as follows: Firstly, chunk decomposition has typical insight attribute, such as ″suddenly″ and ″directly″ finding right solution. Secondly, it is a particular form of insight that occurs at the perceptual level. The early visual cortex shows a tendency of negative activation, whereas the higher visual cortex shows a tendency of positive activation. It suggests that, in order to successfully decompose a chunk, the higher visual areas must at least partly be ′disconnected′ from the input provided by early visual processing. This allows simple features to be rearranged into a different perceptual chunk. Meanwhile, chunk decomposition activates both the dorsal visual pathway and the ventral visual pathway, suggesting that subjects need to perceive both where the chunks are and what the chunks are. Thirdly, there are multiple causes of difficulty to block chunk decomposition, which may exert a ″1+1>2″ enlarged effect. For example, the factors of chunk tightness and familiarity increase the effective connectivity not only between the ″what″ and the ″where″ pathways, but also the functional connection from LITG to LSPL, i.e., from the terminal of the ″what″ pathway to the terminal of the ″where″ pathway. Fourthly, chunk decomposition is a product produced by the co-operation of brain′s left and right cerebral hemisphere. The right hemispheric lateralization advantage is limited to the stage after the failure in insight problem solving. The Zeigarnik effect shows that, the right hemisphere might be more positive in preserve the unsolved problem in mind and also more responsive to the external hint for problem solving. Fifthly, chunk decomposition is the synthesis of consciousness and unconsciousness processing. Probably, the novel processing of insight problem solving is unconscious, while the appropriate processing is conscious; or maybe the incubation stage in Wallace′s four-stage model of problem solving is unconscious, whereas both the illumination and verification stages are conscious.