Early Visual Cortex Research Articles

Comparing Neural Correlates of Memory Encoding and Maintenance for Foveal and Peripheral Stimuli.

Visual working memory is believed to rely on top-down attentional mechanisms that sustain active sensory representations in early visual cortex, a mechanism referred to as sensory recruitment. However, both bottom-up sensory input and top-down attentional modulations thereof appear to prioritize the fovea over the periphery, such that initially peripheral percepts may even be assimilated by foveal processes. This raises the question whether and how visual working memory differs for central and peripheral input. To address this, we conducted a delayed orientation recall task in which an orientation was presented either at the center of the screen or at 15° eccentricity to the left or right. Response accuracy, EEG activity, and gaze position were recorded from 30 participants. Accuracy was slightly but significantly higher for foveal versus peripheral memories. Decoding of EEG recordings revealed a clear dissociation between early sensory and later maintenance signals. Although sensory signals were clearly decodable for foveal stimuli, they were not for peripheral input. In contrast, maintenance signals were equally decodable for both foveal and peripheral memories, suggesting comparable top-down components regardless of eccentricity. Moreover, although memory representations were initially spatially specific and reflected in voltage fluctuations, later during the maintenance period, they generalized across locations, as emerged in alpha oscillations, thus revealing a dynamic transformation within memory from separate sensory traces to what we propose are common output-related codes. Furthermore, the combined absence of reliable decoding of sensory signals and robust presence of maintenance decoding indicates that storage activity patterns as measured by EEG reflect signals beyond primary visual cortex. We discuss the implications for the sensory recruitment hypothesis.

The blushing brain: neural substrates of cheek temperature increase in response to self-observation.

Darwin proposed that blushing-the reddening of the face owing to heightened self-awareness-is 'the most human of all expressions'. Yet, relatively little is known about the underlying mechanisms of blushing. Theories diverge on whether it is a rapid, spontaneous emotional response that does not involve reflection upon the self or whether it results from higher-order socio-cognitive processes. Investigating the neural substrates of blushing can shed light on the mental processes underlying blushing and the mechanisms involved in self-awareness. To reveal neural activity associated with blushing, 16-20 year-old participants (n = 40) watched pre-recorded videos of themselves (versus other people as a control condition) singing karaoke in a magnetic resonance imaging scanner. We measured participants' cheek temperature increase-an indicator of blushing-and their brain activity. The results showed that blushing is higher when watching oneself versus others sing. Those who blushed more while watching themselves sing had, on average, higher activation in the cerebellum (lobule V) and the left paracentral lobe and exhibited more time-locked processing of the videos in early visual cortices. These findings show that blushing is associated with the activation of brain areas involved in emotional arousal, suggesting that it may occur independently of higher-order socio-cognitive processes. Our results provide new avenues for future research on self-awareness in infants and non-human animals.

Dissonant music engages early visual processing

The neuroscientific examination of music processing in audio-visual contexts offers a valuable framework to assess how auditory information influences the emotional encoding of visual information. Using fMRI during naturalistic film viewing, we investigated the neural mechanisms underlying the effect of music on valence inferences during mental state attribution. Thirty-eight participants watched the same short-film accompanied by systematically controlled consonant or dissonant music. Subjects were instructed to think about the main character's intentions. The results revealed that increasing levels of dissonance led to more negatively valenced inferences, displaying the profound emotional impact of musical dissonance. Crucially, at the neuroscientific level and despite music being the sole manipulation, dissonance evoked the response of the primary visual cortex (V1). Functional/effective connectivity analysis showed a stronger coupling between the auditory ventral stream (AVS) and V1 in response to tonal dissonance and demonstrated the modulation of early visual processing via top-down feedback inputs from the AVS to V1. These V1 signal changes indicate the influence of high-level contextual representations associated with tonal dissonance on early visual cortices, serving to facilitate the emotional interpretation of visual information. Our results highlight the significance of employing systematically controlled music, which can isolate emotional valence from the arousal dimension, to elucidate the brain's sound-to-meaning interface and its distributive crossmodal effects on early visual encoding during naturalistic film viewing.

Expression perceptive fields explain individual differences in the recognition of facial emotions

Humans can use the facial expressions of another to infer their emotional state, although it remains unknown how this process occurs. Here we suppose the presence of perceptive fields within expression space, analogous to feature-tuned receptive-fields of early visual cortex. We developed genetic algorithms to explore a multidimensional space of possible expressions and identify those that individuals associated with different emotions. We next defined perceptive fields as probabilistic maps within expression space, and found that they could predict the emotions that individuals infer from expressions presented in a separate task. We found profound individual variability in their size, location, and specificity, and that individuals with more similar perceptive fields had similar interpretations of the emotion communicated by an expression, providing possible channels for social communication. Modelling perceptive fields therefore provides a predictive framework in which to understand how individuals infer emotions from facial expressions.

Short-latency preference for faces in primate superior colliculus depends on visual cortex

Face processing is fundamental to primates and has been extensively studied in higher-order visual cortex. Here, we report that visual neurons in the midbrain superior colliculus (SC) of macaque monkeys display a preference for images of faces. This preference emerges within 40ms of stimulus onset-well before "face patches" in visual cortex-and, at the population level, can be used to distinguish faces from other visual objects with accuracies of ∼80%. This short-latency face preference in SC depends on signals routed through early visual cortex because inactivating the lateral geniculate nucleus, the key relay from retina to cortex, virtually eliminates visual responses in SC, including face-related activity. These results reveal an unexpected circuit in the primate visual system for rapidly detecting faces in the periphery, complementing the higher-order areas needed for recognizing individual faces.

Amodal completion across the brain: The impact of structure and knowledge.

This study investigates the phenomenon of amodal completion within the context of naturalistic objects, employing a repetition suppression paradigm to disentangle the influence of structure and knowledge cues on how objects are completed. The research focuses on early visual cortex (EVC) and lateral occipital complex (LOC), shedding light on how these brain regions respond to different completion scenarios. In LOC, we observed suppressed responses to structure and knowledge-compatible stimuli, providing evidence that both cues influence neural processing in higher-level visual areas. However, in EVC, we did not find evidence for differential responses to completions compatible or incompatible with either structural or knowledge-based expectations. Together, our findings suggest that the interplay between structure and knowledge cues in amodal completion predominantly impacts higher-level visual processing, with less pronounced effects on the early visual cortex. This study contributes to our understanding of the complex mechanisms underlying visual perception and highlights the distinct roles played by different brain regions in amodal completion.

Meta-analysis of experimental factors influencing single-pulse TMS effects on the early visual cortex.

Single-pulse transcranial magnetic stimulation (spTMS) applied to the Early Visual Cortex (EVC) has demonstrated the ability to suppress the perception on visual targets, akin to the effect of visual masking. However, the reported spTMS suppression effects across various studies have displayed inconsistency. We aim to test if the heterogeneity of the spTMS effects can be attributable to variations in experimental factors. We conducted a meta-analysis using data collected from the PubMed and Web of Science databases spanning from 1995 to March 2024. The meta-analysis encompassed a total of 40 independent experiments drawn from 33 original articles. The findings unveiled an overall significant spTMS suppression effect on visual perception. Nevertheless, there existed substantial heterogeneity among the experiments. Univariate analysis elucidated that the spTMS effects could be significantly influenced by TMS intensity, visual angle of the stimulus, coil type, and TMS stimulators from different manufacturers. Reliable spTMS suppression effects were observed within the time windows of -80 to 0 ms and 50 to 150 ms. Multivariate linear regression analyses, which included SOA, TMS intensity, visual angle of the stimulus, and coil type, identified SOA as the key factor influencing the spTMS effects. Within the 50 to 150 ms time window, optimal SOAs were identified as 112 ms and 98 ms for objective and subjective performance, respectively. Collectively, multiple experimental factors accounted for 22.9% (r = 0.3353) and 39.9% (r = 0.3724) of the variance in objective and subjective performance, respectively. Comparing univariate and multivariate analyses, it was evident that experimental factors had different impacts on objective performance and subjective performance. The present study provided quantitative recommendations for future experiments involving the spTMS effects on visual targets, offering guidance on how to configure experimental factors to achieve the optimal masking effect.

The execution of saccadic eye movements suppresses visual processing of both color and luminance in the early visual cortex of humans.

Our eyes execute rapid, directional movements known as saccades, occurring several times per second, to focus on objects of interest in our environment. During these movements, visual sensitivity is temporarily reduced. Despite numerous studies on this topic, the underlying mechanism remains elusive, including a lingering debate on whether saccadic suppression affects the parvocellular visual pathway. To address this issue, we conducted a study employing steady-state visual evoked potentials (SSVEPs) elicited by chromatic and luminance stimuli while observers performed saccadic eye movements. We also employed an innovative analysis pipeline to enhance the signal-to-noise ratio, yielding superior results compared to the previous method. Our findings revealed a clear suppression effect on SSVEP signals during saccades compared to fixation periods. Notably, this suppression effect was comparable for both chromatic and luminance stimuli. We went further to measure the suppression effect across various contrast levels, which enabled us to model SSVEP responses with contrast response functions. The results suggest that saccades primarily reduce response gain without significantly affecting contrast gain and that this reduction applies uniformly to both chromatic and luminance pathways. In summary, our study provides robust evidence that saccades similarly suppress visual processing in both the parvocellular and magnocellular pathways within the human early visual cortex, as indicated by SSVEP responses. The observation that saccadic eye movements impact response gain rather than contrast gain implies that they influence visual processing through a multiplicative mechanism.NEW & NOTEWORTHY The present study demonstrates that saccadic eye movements reduce the processing of both luminance and chromatic stimuli in the early visual cortex of humans. By modeling the contrast response function, the study further shows that saccades affect visual processing by reducing the response gain rather than altering the contrast gain, suggesting that a multiplicative mechanism of visual attenuation affects both parvocellular and magnocellular pathways.

The causal involvement of the visual cortex in visual working memory remains uncertain.

The role of the early visual cortex in visual working memory (VWM) is a matter of current debate. Neuroimaging studies have consistently shown that visual areas encode the content of working memory, while transcranial magnetic stimulation (TMS) studies have presented incongruent results. Thus, we lack conclusive evidence supporting the causal role of early visual areas in VWM. In a recent registered report, Phylactou et al. (Phylactou P, Shimi A, Konstantinou N 2023 R. Soc. Open Sci. 10, 230321 (doi:10.1098/rsos.230321)) sought to tackle this controversy via two well-powered TMS experiments, designed to correct possible methodological issues of previous attempts identified in a preceding systematic review and meta-analysis (Phylactou P, Traikapi A, Papadatou-Pastou M, Konstantinou N 2022 Psychon. Bull. Rev. 29, 1594-1624 (doi:10.3758/s13423-022-02107-y)). However, a key part of their critique and experimental design was based on a misunderstanding of the visual system. They disregarded two important anatomical facts, namely that early visual areas of each hemisphere represent the contralateral visual hemifield, and that each hemisphere receives equally strong input from each eye-both leading to confounded conditions and artefactual effects in their studies. Here, we explain the correct anatomy, describe why their experiments failed to address current issues in the literature and perform a thorough reanalysis of their TMS data revealing important null results. We conclude that the causal role of the visual cortex in VWM remains uncertain.

Finding Pattern in the Noise: Persistent Implicit Statistical Knowledge Impacts the Processing of Unpredictable Stimuli.

Humans can extract statistical regularities of the environment to predict upcoming events. Previous research recognized that implicitly acquired statistical knowledge remained persistent and continued to influence behavior even when the regularities were no longer present in the environment. Here, in an fMRI experiment, we investigated how the persistence of statistical knowledge is represented in the brain. Participants (n = 32) completed a visual, four-choice, RT task consisting of statistical regularities. Two types of blocks constantly alternated with one another throughout the task: predictable statistical regularities in one block type and unpredictable ones in the other. Participants were unaware of the statistical regularities and their changing distribution across the blocks. Yet, they acquired the statistical regularities and showed significant statistical knowledge at the behavioral level not only in the predictable blocks but also in the unpredictable ones, albeit to a smaller extent. Brain activity in a range of cortical and subcortical areas, including early visual cortex, the insula, the right inferior frontal gyrus, and the right globus pallidus/putamen contributed to the acquisition of statistical regularities. The right insula, inferior frontal gyrus, and hippocampus as well as the bilateral angular gyrus seemed to play a role in maintaining this statistical knowledge. The results altogether suggest that statistical knowledge could be exploited in a relevant, predictable context as well as transmitted to and retrieved in an irrelevant context without a predictable structure.

Estimating receptive fields of simple and complex cells in early visual cortex: A convolutional neural network model with parameterized rectification.

Neurons in the primary visual cortex respond selectively to simple features of visual stimuli, such as orientation and spatial frequency. Simple cells, which have phase-sensitive responses, can be modeled by a single receptive field filter in a linear-nonlinear model. However, it is challenging to analyze phase-invariant complex cells, which require more elaborate models having a combination of nonlinear subunits. Estimating parameters of these models is made additionally more difficult by cortical neurons' trial-to-trial response variability. We develop a simple convolutional neural network method to estimate receptive field models for both simple and complex visual cortex cells from their responses to natural images. The model consists of a spatiotemporal filter, a parameterized rectifier unit (PReLU), and a two-dimensional Gaussian "map" of the receptive field envelope. A single model parameter determines the simple vs. complex nature of the receptive field, capturing complex cell responses as a summation of homogeneous subunits, and collapsing to a linear-nonlinear model for simple type cells. The convolutional method predicts simple and complex cell responses to natural image stimuli as well as grating tuning curves. The fitted models yield a continuum of values for the PReLU parameter across the sampled neurons, showing that the simple/complex nature of cells can vary in a continuous manner. We demonstrate that complex-like cells respond less reliably than simple-like cells. However, compensation for this unreliability with noise ceiling analysis reveals predictive performance for complex cells proportionately closer to that for simple cells. Most spatial receptive field structures are well fit by Gabor functions, whose parameters confirm well-known properties of cat A17/18 receptive fields.

Computation on Demand: Action-Specific Representations of Visual Task Features Arise during Distinct Movement Phases.

The intention to act influences the computations of various task-relevant features. However, little is known about the time course of these computations. Furthermore, it is commonly held that these computations are governed by conjunctive neural representations of the features. But, support for this view comes from paradigms arbitrarily combining task features and affordances, thus requiring representations in working memory. Therefore, the present study used electroencephalography and a well-rehearsed task with features that afford minimal working memory representations to investigate the temporal evolution of feature representations and their potential integration in the brain. Female and male human participants grasped objects or touched them with a knuckle. Objects had different shapes and were made of heavy or light materials with shape and weight being relevant for grasping, not for "knuckling." Using multivariate analysis showed that representations of object shape were similar for grasping and knuckling. However, only for grasping did early shape representations reactivate at later phases of grasp planning, suggesting that sensorimotor control signals feed back to the early visual cortex. Grasp-specific representations of material/weight only arose during grasp execution after object contact during the load phase. A trend for integrated representations of shape and material also became grasp-specific but only briefly during the movement onset. These results suggest that the brain generates action-specific representations of relevant features as required for the different subcomponents of its action computations. Our results argue against the view that goal-directed actions inevitably join all features of a task into a sustained and unified neural representation.

A unifying framework for functional organization in early and higher ventral visual cortex

A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly understood. Here, we develop the topographic deep artificial neural network (TDANN), the first model to predict several aspects of the functional organization of multiple cortical areas in the primate visual system. We analyze the factors driving the TDANN's success and find that it balances two objectives: learning a task-general sensory representation and maximizing the spatial smoothness of responses according to a metric that scales with cortical surface area. In turn, the representations learned by the TDANN are more brain-like than in spatially unconstrained models. Finally, we provide evidence that the TDANN's functional organization balances performance with between-area connection length. Our results offer a unified principle for understanding the functional organization of the primate ventral visual system.

Uncovering the Role of the Early Visual Cortex in Visual Mental Imagery.

The question of whether the early visual cortex (EVC) is involved in visual mental imagery remains a topic of debate. In this paper, I propose that the inconsistency in findings can be explained by the unique challenges associated with investigating EVC activity during imagery. During perception, the EVC processes low-level features, which means that activity is highly sensitive to variation in visual details. If the EVC has the same role during visual mental imagery, any change in the visual details of the mental image would lead to corresponding changes in EVC activity. Within this context, the question should not be whether the EVC is 'active' during imagery but how its activity relates to specific imagery properties. Studies using methods that are sensitive to variation in low-level features reveal that imagery can recruit the EVC in similar ways as perception. However, not all mental images contain a high level of visual details. Therefore, I end by considering a more nuanced view, which states that imagery can recruit the EVC, but that does not mean that it always does so.

Visuospatial processing in early brain-based visual impairment is associated with differential recruitment of dorsal and ventral visual streams.

Visuospatial processing impairments are prevalent in individuals with cerebral visual impairment (CVI) and are typically ascribed to "dorsal stream dysfunction" (DSD). However, the contribution of other cortical regions, including early visual cortex (EVC), frontal cortex, or the ventral visual stream, to such impairments remains unknown. Thus, here, we examined fMRI activity in these regions, while individuals with CVI (and neurotypicals) performed a visual search task within a dynamic naturalistic scene. First, behavioral performance was measured with eye tracking. Participants were instructed to search and follow a walking human target. CVI participants took significantly longer to find the target, and their eye gaze patterns were less accurate and less precise. Second, we used the same task in the MRI scanner. Along the dorsal stream, activation was reduced in CVI participants, consistent with the proposed DSD in CVI. Intriguingly, however, visual areas along the ventral stream showed the complete opposite pattern, with greater activation in CVI participants. In contrast, we found no differences in either EVC or frontal cortex between groups. These results suggest that the impaired visuospatial processing abilities in CVI are associated with differential recruitment of the dorsal and ventral visual streams, likely resulting from impaired selective attention.

Divergent roles of early visual cortex and inferior frontal junction in visual working memory

BackgroundRecent studies indicate that both prefrontal and visual regions play critical roles in visual working memory (VWM), with prefrontal regions mainly associated with executive functions, and visual cortices linked to representations of memory contents. VWM involves the selective filtering of irrelevant information, yet the specific contributions of the prefrontal regions and visual cortex in this process remain unclear. ObjectiveTo understand the dynamic causal roles of prefrontal and visual regions in VWM. MethodsThe differentiation of VWM components was achieved using a computational model that incorporated a swap rate for non-target stimuli. Single-pulse magnetic transcranial stimulation (spTMS) was delivered to the early visual cortex (EVC) and the inferior frontal junction (IFJ) across different phases of an orientation recall task that with or without distractors. ResultsOur results indicate that spTMS over the EVC and IFJ influences VWM particularly when distractors are present. VWM precision can be impacted by spTMS applied to either region during the early retention, while spTMS effect is especially prominent when EVC is stimulated during the late retention phase and when directed at the ipsilateral EVC. Conversely, the probability of accurately recalling the target exhibited comparable patterns when spTMS was administered to either the EVC or IFJ. ConclusionsWe highlight the “sensory recruitment” of VWM characterized by critical involvement of EVC particularly in the information-filtering process within VWM. The maintenance of memory content representations necessitates ongoing communication between the EVC and IFJ throughout the entirety of the VWM process in a dynamic pattern.

Altered functional-structural coupling may predict Parkinson's patient's depression.

We aimed to elucidate the neurobiological basis of depression in Parkinson's disease and identify potential imaging markers for depression in patients with Parkinson's disease. We recruited 43 normal controls (NC), 46 depressed Parkinson's disease patients (DPD) and 56 non-depressed Parkinson's disease (NDPD). All participants underwent routine T2-weighted, T2Flair, and resting-state scans on the same 3.0T magnetic resonance imaging (MRI) scanner at our hospital. Pre-processing includes calculating surface-based Regional Homogeneity (2DReHo) and cortical thickness. Then we defined the correlation coefficient between 2DReHo and cortical thickness as the functional-structural coupling index. Between-group comparisons were conducted on the Fisher's Z-transformed correlation coefficients. To identify specific regions of decoupling, the 2DReHo for each participant were divided by cortical thickness at each vertex, followed by threshold-free cluster enhancement (TFCE) multiple comparison correction. Binary logistic regression analysis was performed with DPD as the dependent variable, and significantly altered indicators as the independent variables. Receiver operating characteristic curves were constructed to compare the diagnostic performance of individual predictors and combinations using R and MedCalc software. DPD patients exhibited a significantly lower whole-brain functional-structural coupling index than NDPD patients and NC. Abnormal functional-structural coupling was primarily observed in the left inferior parietal lobule and right primary and early visual cortices in DPD patients. Receiver operating characteristic analysis revealed that the combination of cortical functional-structural coupling, surface-based ReHo, and thickness had the best diagnostic performance, achieving a sensitivity of 65% and specificity of 77.7%. This is the first study to explore the relationship between functional and structural changes in DPD patients and evaluate the diagnostic performance of these altered correlations to predict depression in Parkinson's disease patients. We posit that these changes in functional-structural relationships may serve as imaging biomarkers for depression in Parkinson's disease patients, potentially aiding in the classification and diagnosis of Parkinson's disease. Additionally, our findings provide functional and structural imaging evidence for exploring the neurobiological basis of depression in Parkinson's disease.

Convolutional neural networks develop major organizational principles of early visual cortex when enhanced with retinal sampling.

Primate visual cortex exhibits key organizational principles: cortical magnification, eccentricity-dependent receptive field size and spatial frequency tuning as well as radial bias. We provide compelling evidence that these principles arise from the interplay of the non-uniform distribution of retinal ganglion cells, and a quasi-uniform convergence rate from the retina to the cortex. We show that convolutional neural networks outfitted with a retinal sampling layer, which resamples images according to retinal ganglion cell density, develop these organizational principles. Surprisingly, our results indicate that radial bias is spatial-frequency dependent and only manifests for high spatial frequencies. For low spatial frequencies, the bias shifts towards orthogonal orientations. These findings introduce a novel hypothesis about the origin of radial bias. Quasi-uniform convergence limits the range of spatial frequencies (in retinal space) that can be resolved, while retinal sampling determines the spatial frequency content throughout the retina.

Visual omitted stimulus potentials are not retinotopic

Omitted stimulus potentials (OSPs) are elicited in response to the omission of expected stimuli and are thought to reflect prediction errors. If prediction errors are signaled in the sensory cortex, OSPs are expected to be generated in the sensory cortex. The present study investigated the involvement of the early visual cortex in the generation of OSPs by testing whether omitted visual stimuli elicit brain responses in a spatially specific manner. Checkerboard pattern stimuli were presented alternately in the upper and lower visual fields, and the stimuli were omitted in 10 % of the trials. Event-related potentials were recorded from 33 participants. While a retinotopic C1 component was evoked by real visual stimuli, omitted stimuli did not produce any response reflecting retinotopy but did elicit a visual mismatch negativity, which was larger for omitted stimuli expected in the lower visual field than for those in the upper visual field. These results suggest that omitted visual stimuli are processed in a different pathway than actual stimuli.

Visual perception of highly memorable images is mediated by a distributed network of ventral visual regions that enable a late memorability response.

Behavioral and neuroscience studies in humans and primates have shown that memorability is an intrinsic property of an image that predicts its strength of encoding into and retrieval from memory. While previous work has independently probed when or where this memorability effect may occur in the human brain, a description of its spatiotemporal dynamics is missing. Here, we used representational similarity analysis (RSA) to combine functional magnetic resonance imaging (fMRI) with source-estimated magnetoencephalography (MEG) to simultaneously measure when and where the human cortex is sensitive to differences in image memorability. Results reveal that visual perception of High Memorable images, compared to Low Memorable images, recruits a set of regions of interest (ROIs) distributed throughout the ventral visual cortex: a late memorability response (from around 300 ms) in early visual cortex (EVC), inferior temporal cortex, lateral occipital cortex, fusiform gyrus, and banks of the superior temporal sulcus. Image memorability magnitude results are represented after high-level feature processing in visual regions and reflected in classical memory regions in the medial temporal lobe (MTL). Our results present, to our knowledge, the first unified spatiotemporal account of visual memorability effect across the human cortex, further supporting the levels-of-processing theory of perception and memory.