Optical imaging of the intrinsic signal as a tool to characterize orientation sensitivity in the primary visual cortex of the young mouse.

We employed intrinsic signal optical imaging (ISOI) to investigate orientation sensitivity bias in the visual cortex of young mice. Optical signals were recorded in response to the moving light gratings stimulating ipsi­, contra­ and binocular eye inputs. ISOI allowed visualization of cortical areas activated by gratings of specific orientation and temporal changes of light scatter during visual stimulation. These results confirmed ISOI as a reliable technique for imaging the activity of large populations of neurons in the mouse visual cortex. Our results revealed that the contralateral ocular input activated a larger area of the primary visual cortex than the ipsilateral input, and caused the highest response amplitudes of light scatter signals to all ocular inputs. Horizontal gratings moved in vertical orientation induced the most significant changes in light scatter when presented contralaterally and binocularly, surpassing stimulations by vertical or oblique gratings. These observations suggest dedicated integration mechanisms for the combined inputs from both eyes. We also explored the relationship between point luminance change (PLC) of grating stimuli and ISOI time courses under various orientations of movements of the gratings and ocular inputs, finding higher cross-correlation values for cardinal orientations and ipsilateral inputs. These findings suggested specific activation of different neuronal assemblies within the mouse's primary visual cortex by grating stimuli of the corresponding orientation. However, further investigations are needed to examine this summation hypothesis. Our study highlights the potential of optical imaging as a valuable tool for exploring functional­anatomical relationships in the mouse visual system.

Two what, two where, visual cortical streams in humans.

ROLLS, E. T. Two What, Two Where, Visual Cortical Streams in Humans. NEUROSCI BIOBEHAV REV 2024. Recent cortical connectivity investigations lead to new concepts about 'What' and 'Where' visual cortical streams in humans, and how they connect to other cortical systems. A ventrolateral 'What' visual stream leads to the inferior temporal visual cortex for object and face identity, and provides 'What' information to the hippocampal episodic memory system, the anterior temporal lobe semantic system, and the orbitofrontal cortex emotion system. A superior temporal sulcus (STS) 'What' visual stream utilising connectivity from the temporal and parietal visual cortex responds to moving objects and faces, and face expression, and connects to the orbitofrontal cortex for emotion and social behaviour. A ventromedial 'Where' visual stream builds feature combinations for scenes, and provides 'Where' inputs via the parahippocampal scene area to the hippocampal episodic memory system that are also useful for landmark-based navigation. The dorsal 'Where' visual pathway to the parietal cortex provides for actions in space, but also provides coordinate transforms to provide inputs to the parahippocampal scene area for self-motion update of locations in scenes in the dark or when the view is obscured.

Auditory cortex conveys non-topographic sound localization signals to visual cortex.

Spatiotemporally congruent sensory stimuli are fused into a unified percept. The auditory cortex (AC) sends projections to the primary visual cortex (V1), which could provide signals for binding spatially corresponding audio-visual stimuli. However, whether AC inputs in V1 encode sound location remains unknown. Using two-photon axonal calcium imaging and a speaker array, we measured the auditory spatial information transmitted from AC to layer 1 of V1. AC conveys information about the location of ipsilateral and contralateral sound sources to V1. Sound location could be accurately decoded by sampling AC axons in V1, providing a substrate for making location-specific audiovisual associations. However, AC inputs were not retinotopically arranged in V1, and audio-visual modulations of V1 neurons did not depend on the spatial congruency of the sound and light stimuli. The non-topographic sound localization signals provided by AC might allow the association of specific audiovisual spatial patterns in V1 neurons.

Impact of light-emitting diodes on visual cortex layer 5 pyramidal neurons (V1-L5PNs)-A rodent study.

Purpose: Light-induced neural retinal insult leads to alterations in the visual cortex neurons. We examined light-induced neuronal alterations in the visual cortex layer 5 pyramidal neurons (V1-L5PNs) of adult male Wistar rats. Methods: A total of 24 rats were divided into the following groups (n=6 each): control (NC), blue (BL), white (WL), and yellow (YL). The exposure groups were subjected to light-emitting diodes (LED) exposure (450-500 lx) of differing wavelengths for 90 days (12:12 16 light-dark cycle). After LED exposure, the animals were sacrificed, and the brain tissues were removed and impregnated in freshly prepared Golgi-Cox stain for 21 days. Sholl's grading analysis was used to quantify the apical and basal dendritic branching points and intersections of the V1-L5PNs. Results: There was a significant difference in the number of apical branching points among all groups (p<0.001), with a particularly notable difference between the BL and WL groups (p<0.001). A post hoc test revealed that all exposure groups (BL, WL, and YL) had fewer apical branching points (p<0.001) on an average of 3.6 µm and a significant reduction in the dendritic intersections (p<0.001) compared to the number of branching points extending from layer Va (V1) neurons. Conclusions: Chronic and cumulative exposure to blue and white LEDs led to the pruning of V1-L5PNs, which might impair visual processing.

Modeling circuit mechanisms of opposing cortical responses to visual flow perturbations.

In an ever-changing visual world, animals' survival depends on their ability to perceive and respond to rapidly changing motion cues. The primary visual cortex (V1) is at the forefront of this sensory processing, orchestrating neural responses to perturbations in visual flow. However, the underlying neural mechanisms that lead to distinct cortical responses to such perturbations remain enigmatic. In this study, our objective was to uncover the neural dynamics that govern V1 neurons' responses to visual flow perturbations using a biologically realistic computational model. By subjecting the model to sudden changes in visual input, we observed opposing cortical responses in excitatory layer 2/3 (L2/3) neurons, namely, depolarizing and hyperpolarizing responses. We found that this segregation was primarily driven by the competition between external visual input and recurrent inhibition, particularly within L2/3 and L4. This division was not observed in excitatory L5/6 neurons, suggesting a more prominent role for inhibitory mechanisms in the visual processing of the upper cortical layers. Our findings share similarities with recent experimental studies focusing on the opposing influence of top-down and bottom-up inputs in the mouse primary visual cortex during visual flow perturbations.

Enhancement of low gamma oscillations by volitional conditioning of local field potential in the primary motor and visual cortex of mice.

Volitional control of local field potential oscillations in low gamma band via brain machine interface can not only uncover the relationship between low gamma oscillation and neural synchrony but also suggest a therapeutic potential to reverse abnormal local field potential oscillation in neurocognitive disorders. In nonhuman primates, the volitional control of low gamma oscillations has been demonstrated by brain machine interface techniques in the primary motor and visual cortex. However, it is not clear whether this holds in other brain regions and other species, for which gamma rhythms might involve in highly different neural processes. Here, we established a closed-loop brain-machine interface and succeeded in training mice to volitionally elevate low gamma power of local field potential in the primary motor and visual cortex. We found that the mice accomplished the task in a goal-directed manner and spiking activity exhibited phase-locking to the oscillation in local field potential in both areas. Moreover, long-term training made the power enhancement specific to direct and adjacent channel, and increased the transcriptional levels of NMDA receptors as well as that of hypoxia-inducible factor relevant to metabolism. Our results suggest that volitionally generated low gamma rhythms in different brain regions share similar mechanisms and pave the way for employing brain machine interface in therapy of neurocognitive disorders.

Efficient coding of natural images in the mouse visual cortex.

How the activity of neurons gives rise to natural vision remains a matter of intense investigation. The mid-level visual areas along the ventral stream are selective to a common class of natural images-textures-but a circuit-level understanding of this selectivity and its link to perception remains unclear. We addressed these questions in mice, first showing that they can perceptually discriminate between textures and statistically simpler spectrally matched stimuli, and between texture types. Then, at the neural level, we found that the secondary visual area (LM) exhibited a higher degree of selectivity for textures compared to the primary visual area (V1). Furthermore, textures were represented in distinct neural activity subspaces whose relative distances were found to correlate with the statistical similarity of the images and the mice's ability to discriminate between them. Notably, these dependencies were more pronounced in LM, where the texture-related subspaces were smaller than in V1, resulting in superior stimulus decoding capabilities. Together, our results demonstrate texture vision in mice, finding a linking framework between stimulus statistics, neural representations, and perceptual sensitivity-a distinct hallmark of efficient coding computations.

The influence of cortical activity on perception depends on behavioral state and sensory context.

The mechanistic link between neural circuit activity and behavior remains unclear. While manipulating cortical activity can bias certain behaviors and elicit artificial percepts, some tasks can still be solved when cortex is silenced or removed. Here, mice were trained to perform a visual detection task during which we selectively targeted groups of visually responsive and co-tuned neurons in L2/3 of primary visual cortex (V1) for two-photon photostimulation. The influence of photostimulation was conditional on two key factors: the behavioral state of the animal and the contrast of the visual stimulus. The detection of low-contrast stimuli was enhanced by photostimulation, while the detection of high-contrast stimuli was suppressed, but crucially, only when mice were highly engaged in the task. When mice were less engaged, our manipulations of cortical activity had no effect on behavior. The behavioral changes were linked to specific changes in neuronal activity. The responses of non-photostimulated neurons in the local network were also conditional on two factors: their functional similarity to the photostimulated neurons and the contrast of the visual stimulus. Functionally similar neurons were increasingly suppressed by photostimulation with increasing visual stimulus contrast, correlating with the change in behavior. Our results show that the influence of cortical activity on perception is not fixed, but dynamically and contextually modulated by behavioral state, ongoing activity and the routing of information through specific circuits.

Mirrored might: A vision for inhibition.

In this issue of Neuron, Znamenskiy et al.1 unveil functional connection specificity between PV+ inhibitory interneurons and excitatory pyramidal neurons in mouse visual cortex, providing a circuit mechanism for stable amplification of cortical subpopulations.

Multiple objects evoke fluctuating responses in several regions of the visual pathway.

How neural representations preserve information about multiple stimuli is mysterious. Because tuning of individual neurons is coarse (e.g., visual receptive field diameters can exceed perceptual resolution), the populations of neurons potentially responsive to each individual stimulus can overlap, raising the question of how information about each item might be segregated and preserved in the population. We recently reported evidence for a potential solution to this problem: when two stimuli were present, some neurons in the macaque visual cortical areas V1 and V4 exhibited fluctuating firing patterns, as if they responded to only one individual stimulus at a time (Jun et al., 2022). However, whether such an information encoding strategy is ubiquitous in the visual pathway and thus could constitute a general phenomenon remains unknown. Here, we provide new evidence that such fluctuating activity is also evoked by multiple stimuli in visual areas responsible for processing visual motion (middle temporal visual area, MT), and faces (middle fundus and anterolateral face patches in inferotemporal cortex - areas MF and AL), thus extending the scope of circumstances in which fluctuating activity is observed. Furthermore, consistent with our previous results in the early visual area V1, MT exhibits fluctuations between the representations of two stimuli when these form distinguishable objects but not when they fuse into one perceived object, suggesting that fluctuating activity patterns may underlie visual object formation. Taken together, these findings point toward an updated model of how the brain preserves sensory information about multiple stimuli for subsequent processing and behavioral action.

A clinico-anatomical dissection of the magnocellular and parvocellular pathways in a patient with the Riddoch syndrome.

KEY MESSAGE: The Riddoch syndrome is thought to be caused by damage to the primary visual cortex (V1), usually following a vascular event. This study shows that damage to the anatomical input to V1, i.e., the optic radiations, can result in selective visual deficits that mimic the Riddoch syndrome. The results also highlight the differential susceptibility of the magnocellular and parvocellular visual systems to injury. Overall, this study offers new insights that will improve our understanding of the impact of brain injury and neurosurgery on the visual pathways. The Riddoch syndrome, characterised by the ability to perceive, consciously, moving visual stimuli but not static ones, has been associated with lesions of primary visual cortex (V1). We present here the case of patient YL who, after a tumour resection surgery that spared his V1, nevertheless showed symptoms of the Riddoch syndrome. Based on our testing, we postulated that the magnocellular (M) and parvocellular (P) inputs to his V1 may be differentially affected. In a first experiment, YL was presented with static and moving checkerboards in his blind field while undergoing multimodal magnetic resonance imaging (MRI), including structural, functional, and diffusion, acquired at 3 T. In a second experiment, we assessed YL's neural responses to M and P visual stimuli using psychophysics and high-resolution fMRI acquired at 7 T. YL's optic radiations were partially damaged but not severed. We found extensive activity in his visual cortex for moving, but not static, visual stimuli, while our psychophysical tests revealed that only low-spatial frequency moving checkerboards were perceived. High-resolution fMRI revealed strong responses in YL's V1 to M stimuli and very weak ones to P stimuli, indicating a functional P lesion affecting V1. In addition, YL frequently reported seeing moving stimuli and discriminating their direction of motion in the absence of visual stimulation, suggesting that he was experiencing visual hallucinations. Overall, this study highlights the possibility of a selective loss of P inputs to V1 resulting in the Riddoch syndrome and in hallucinations of visual motion.

Activation and depression of neural and hemodynamic responses induced by the intracortical microstimulation and visual stimulation in the mouse visual cortex.

Objective. Intracortical microstimulation (ICMS) can be an effective method for restoring sensory perception in contemporary brain-machine interfaces. However, the mechanisms underlying better control of neuronal responses remain poorly understood, as well as the relationship between neuronal activity and other concomitant phenomena occurring around the stimulation site.Approach. Different microstimulation frequencies were investigatedin vivoon Thy1-GCaMP6s mice using widefield and two-photon imaging to evaluate the evoked excitatory neural responses across multiple spatial scales as well as the induced hemodynamic responses. Specifically, we quantified stimulation-induced neuronal activation and depression in the mouse visual cortex and measured hemodynamic oxyhemoglobin and deoxyhemoglobin signals using mesoscopic-scale widefield imaging.Main results. Our calcium imaging findings revealed a preference for lower-frequency stimulation in driving stronger neuronal activation. A depressive response following the neural activation preferred a slightly higher frequency stimulation compared to the activation. Hemodynamic signals exhibited a comparable spatial spread to neural calcium signals. Oxyhemoglobin concentration around the stimulation site remained elevated during the post-activation (depression) period. Somatic and neuropil calcium responses measured by two-photon microscopy showed similar dependence on stimulation parameters, although the magnitudes measured in soma was greater than in neuropil. Furthermore, higher-frequency stimulation induced a more pronounced activation in soma compared to neuropil, while depression was predominantly induced in soma irrespective of stimulation frequencies.Significance. These results suggest that the mechanism underlying depression differs from activation, requiring ample oxygen supply, and affecting neurons. Our findings provide a novel understanding of evoked excitatory neuronal activity induced by ICMS and offer insights into neuro-devices that utilize both activation and depression phenomena to achieve desired neural responses.

Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects.

Recent neuroimaging studies have shown that the visual cortex plays an important role in representing the affective significance of visual input. The origin of these affect-specific visual representations is debated: they are intrinsic to the visual system versus they arise through reentry from frontal emotion processing structures such as the amygdala. We examined this problem by combining convolutional neural network (CNN) models of the human ventral visual cortex pre-trained on ImageNet with two datasets of affective images. Our results show that in all layers of the CNN models, there were artificial neurons that responded consistently and selectively to neutral, pleasant, or unpleasant images and lesioning these neurons by setting their output to zero or enhancing these neurons by increasing their gain led to decreased or increased emotion recognition performance respectively. These results support the idea that the visual system may have the intrinsic ability to represent the affective significance of visual input and suggest that CNNs offer a fruitful platform for testing neuroscientific theories.

Integrative processing in artificial and biological vision predicts the perceived beauty of natural images.

Previous research shows that the beauty of natural images is already determined during perceptual analysis. However, it is unclear which perceptual computations give rise to the perception of beauty. Here, we tested whether perceived beauty is predicted by spatial integration across an image, a perceptual computation that reduces processing demands by aggregating image parts into more efficient representations of the whole. We quantified integrative processing in an artificial deep neural network model, where the degree of integration was determined by the amount of deviation between activations for the whole image and its constituent parts. This quantification of integration predicted beauty ratings for natural images across four studies with different stimuli and designs. In a complementary functional magnetic resonance imaging study, we show that integrative processing in human visual cortex similarly predicts perceived beauty. Together, our results establish integration as a computational principle that facilitates perceptual analysis and thereby mediates the perception of beauty.

Decision-making processes in perceptual learning depend on effectors.

Visual perceptual learning is traditionally thought to arise in visual cortex. However, typical perceptual learning tasks also involve systematic mapping of visual information onto motor actions. Because the motor system contains both effector-specific and effector-unspecific representations, the question arises whether visual perceptual learning is effector-specific itself, or not. Here, we study this question in an orientation discrimination task. Subjects learn to indicate their choices either with joystick movements or with manual reaches. After training, we challenge them to perform the same task with eye movements. We dissect the decision-making process using the drift diffusion model. We find that learning effects on the rate of evidence accumulation depend on effectors, albeit not fully. This suggests that during perceptual learning, visual information is mapped onto effector-specific integrators. Overlap of the populations of neurons encoding motor plans for these effectors may explain partial generalization. Taken together, visual perceptual learning is not limited to visual cortex, but also affects sensorimotor mapping at the interface of visual processing and decision making.

Parallel Streams of Direct Corticogeniculate Feedback from Mid-level Extrastriate Cortex in the Macaque Monkey.

First-order thalamic nuclei receive feedforward signals from peripheral receptors and relay these signals to primary sensory cortex. Primary sensory cortex, in turn, provides reciprocal feedback to first-order thalamus. Because the vast majority of sensory thalamocortical inputs target primary sensory cortex, their complementary corticothalamic neurons are assumed to be similarly restricted to primary sensory cortex. We upend this assumption by characterizing morphologically diverse neurons in multiple mid-level visual cortical areas of the primate (Macaca mulatta) brain that provide direct feedback to the primary visual thalamus, the dorsal lateral geniculate nucleus (LGN). Although the majority of geniculocortical neurons project to primary visual cortex (V1), a minority, located mainly in the koniocellular LGN layers, provide direct input to extrastriate visual cortex. These "V1-bypassing" projections may be implicated in blindsight. We hypothesized that geniculocortical inputs directly targeting extrastriate cortex should be complemented by reciprocal corticogeniculate circuits. Using virus-mediated circuit tracing, we discovered corticogeniculate neurons throughout three mid-level extrastriate areas: MT, MST, and V4. Quantitative morphological analyses revealed nonuniform distributions of unique cell types across areas. Many extrastriate corticogeniculate neurons had spiny stellate morphology, suggesting possible targeting of koniocellular LGN layers. Importantly though, multiple morphological types were observed across areas. Such morphological diversity could suggest parallel streams of V1-bypassing corticogeniculate feedback at multiple stages of the visual processing hierarchy. Furthermore, the presence of corticogeniculate neurons across visual cortex necessitates a reevaluation of the LGN as a hub for visual information rather than a simple relay.

Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks.

Computational neuroscience studies have shown that the structure of neural variability to an unchanged stimulus affects the amount of information encoded. Some artificial deep neural networks, such as those with Monte Carlo dropout layers, also have variable responses when the input is fixed. However, the structure of the trial-by-trial neural covariance in neural networks with dropout has not been studied, and its role in decoding accuracy is unknown. We studied the above questions in a convolutional neural network model with dropout in both the training and testing phases. We found that trial-by-trial correlation between neurons (i.e., noise correlation) is positive and low dimensional. Neurons that are close in a feature map have larger noise correlation. These properties are surprisingly similar to the findings in the visual cortex. We further analyzed the alignment of the main axes of the covariance matrix. We found that different images share a common trial-by-trial noise covariance subspace, and they are aligned with the global signal covariance. This evidence that the noise covariance is aligned with signal covariance suggests that noise covariance in dropout neural networks reduces network accuracy, which we further verified directly with a trial-shuffling procedure commonly used in neuroscience. These findings highlight a previously overlooked aspect of dropout layers that can affect network performance. Such dropout networks could also potentially be a computational model of neural variability.

Study of vision-related resting-state activity in suprasellar tumor patients with postoperative visual damage.

INTRODUCTION: The objective of this study was to investigate changes in vision-related resting-state activity in patients with suprasellar tumors (ST) who experienced vision deterioration after surgery. METHODS: Twelve patients with ST and vision deterioration after surgery were included in the study. Resting-state functional connectivity (FC) was compared before and after surgery using a seed-based analysis with a priori specified regions of interest (ROIs) within the visual areas. The differences between the two groups were identified using a paired t-test. RESULTS: The data showed a decrease in FC within and between the dorsal and ventral pathways, as well as in the third pathway in ST patients. The middle temporal visual cortex (MT+) showed a decreased FC with more regions than other visual ROIs. The data also revealed an increase in FC between the visual ROIs and higher-order cortex. The superior frontal gyrus/BA8 showed an increased FC with more ROIs than other high-order regions, and the hOC4d was involved in an increased FC with more high-order regions than other ROIs. CONCLUSIONS: The study results indicate significant neural reorganization in the vision-related cortex of ST patients with postoperative vision damage. Most subareas within the visual cortex showed remarkable neural dysfunction, and some highe-order cortex may be primarily involved in top-down control of the subareas within the visual cortex. The hot zones may arise in the processing of "top-down" influence.

Dissociable components of attention exhibit distinct neuronal signatures in primate visual cortex.

Attention can be deployed in multiple forms and facilitates behavior by influencing perceptual sensitivity and choice bias. Attention is also associated with a myriad of changes in sensory neural activity. Yet, the relationship between the behavioral components of attention and the accompanying changes in neural activity remains largely unresolved. We examined this relationship by quantifying sensitivity and bias in monkeys performing a task that dissociated eye movement responses from the focus of covert attention. Unexpectedly, bias, not sensitivity, increased at the focus of covert attention, whereas sensitivity increased at the location of planned eye movements. Furthermore, neuronal activity within visual area V4 varied robustly with bias, but not sensitivity, at the focus of covert attention. In contrast, correlated variability between neuronal pairs was lowest at the location of planned eye movements, and varied with sensitivity, but not bias. Thus, dissociable behavioral components of attention exhibit distinct neuronal signatures within the visual cortex.

Parafoveal vision reveals qualitative differences between fusiform face area and parahippocampal place area.

The center-periphery visual field axis guides early visual system organization with enhanced resources devoted to central vision leading to reduced peripheral performance relative to that of central vision (i.e., behavioral eccentricity effect) for many visual functions. The center-periphery organization extends to high-order visual cortex where, for example, the well-studied face-sensitive fusiform face area (FFA) shows sensitivity to central vision and the place-sensitive parahippocampal place area (PPA) shows sensitivity to peripheral vision. As we have recently found that face perception is more sensitive to eccentricity than place perception, here we examined whether these behavioral findings reflect differences in FFA's and PPA's sensitivities to eccentricity. We assumed FFA would show higher sensitivity to eccentricity than PPA would, but that both regions' modulation by eccentricity would be invariant to the viewed category. We parametrically investigated (fMRI, n = 32) how FFA's and PPA's activations are modulated by eccentricity (≤8°) and category (upright/inverted faces/houses) while keeping stimulus size constant. As expected, FFA showed an overall higher sensitivity to eccentricity than PPA. However, both regions' activation modulations by eccentricity were dependent on the viewed category. In FFA, a reduction of activation with growing eccentricity ("BOLD eccentricity effect") was found (with different amplitudes) for all categories. In PPA however, qualitatively different BOLD eccentricity effect modulations were found (e.g., at 8° mild BOLD eccentricity effect for houses but a reverse BOLD eccentricity effect for faces and no modulation for inverted faces). Our results emphasize that peripheral vision investigations are critical to further our understanding of visual processing.