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.

Neural assemblies coordinated by cortical waves are associated with waking and hallucinatory brain states.

The relationship between sensory stimuli and perceptions is brain-state dependent: in wakefulness, suprathreshold stimuli evoke perceptions; under anesthesia, perceptions are abolished; and during dreaming and in dissociated states, percepts are internally generated. Here, we exploit this state dependence to identify brain activity associated with internally generated or stimulus-evoked perceptions. In awake mice, visual stimuli phase reset spontaneous cortical waves to elicit 3-6 Hz feedback traveling waves. These stimulus-evoked waves traverse the cortex and entrain visual and parietal neurons. Under anesthesia as well as during ketamine-induced dissociation, visual stimuli do not disrupt spontaneous waves. Uniquely, in the dissociated state, spontaneous waves traverse the cortex caudally and entrain visual and parietal neurons, akin to stimulus-evoked waves in wakefulness. Thus, coordinated neuronal assemblies orchestrated by traveling cortical waves emerge in states in which perception can manifest. The awake state is privileged in that this coordination is reliably elicited by external visual stimuli.

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.

An analysis of information segregation in parallel streams of a multi-stream convolutional neural network.

Visual information is processed in hierarchically organized parallel streams in the primate brain. In the present study, information segregation in parallel streams was examined by constructing a convolutional neural network with parallel architecture in all of the convolutional layers. Although filter weights for convolution were initially set to random values, color information was segregated from shape information in most model instances after training. Deletion of the color-related stream decreased recognition accuracy of animate images, whereas deletion of the shape-related stream decreased recognition accuracy of both animate and inanimate images. The results suggest that properties of filters and functions of a stream are spontaneously segregated in parallel streams of neural networks.

Immunocytochemical localization of nitric oxide synthase-containing neurons in the visual cortex of the Mongolian gerbil.

INTRODUCTION: Nitric oxide (NO) is present in various cell types in the central nervous system and plays a crucial role in the control of various cellular functions. The diurnal Mongolian gerbil is a member of the rodent family Muridae that exhibits unique physiological, anatomical, and behavioral differences from the nocturnal rat and mouse, which render it a useful model for studying the visual system. The purpose of this study was to confirm the distribution and morphology of neurons that contain nitric oxide synthase (NOS) and their pattern of co-expressing NOS with neuropeptide Y (NPY), somatostatin (SST), and gamma-aminobutyric acid (GABA) in the visual cortex of Mongolian gerbils. MATERIALS AND METHODS: Mongolian gerbils were used in the study. We confirmed the localization of NOS in the visual cortex of Mongolian gerbils using horseradish peroxidase immunocytochemistry, fluorescent immunocytochemistry, and conventional confocal microscopy. RESULTS: NOS-immunoreactive (IR) neurons were present in all layers of the visual cortex of the Mongolian gerbil, with the exception of layer I, with the highest density observed in layer V (50.00%). The predominant type of NOS-IR neurons was multipolar round/oval cells (60.96%). Two-color immunofluorescence revealed that 100% NOS-IR neurons were co-labeled with NPY and SST and 34.55% were co-labeled with GABA. CONCLUSIONS: Our findings of the laminar distribution and morphological characteristics of NOS-IR neurons, as well as the colocalization patterns of NOS-IR neurons with NPY, SST, and GABA, indicated the presence of species-specific differences, suggesting the functional diversity of NO in the visual cortex. This study provides valuable data on the anatomical organization of NOS-IR neurons and, consequently, a better understanding of the functional aspects of NO and species diversity.

Encoding luminance surfaces in the visual cortex of mice and monkeys: difference in responses to edge and center.

Luminance and spatial contrast provide information on the surfaces and edges of objects. We investigated neural responses to black and white surfaces in the primary visual cortex (V1) of mice and monkeys. Unlike primates that use their fovea to inspect objects with high acuity, mice lack a fovea and have low visual acuity. It thus remains unclear whether monkeys and mice share similar neural mechanisms to process surfaces. The animals were presented with white or black surfaces and the population responses were measured at high spatial and temporal resolution using voltage-sensitive dye imaging. In mice, the population response to the surface was not edge-dominated with a tendency to center-dominance, whereas in monkeys the response was edge-dominated with a "hole" in the center of the surface. The population response to the surfaces in both species exhibited suppression relative to a grating stimulus. These results reveal the differences in spatial patterns to luminance surfaces in the V1 of mice and monkeys and provide evidence for a shared suppression process relative to grating.

Representing stimulus motion with waves in adaptive neural fields.

Traveling waves of neural activity emerge in cortical networks both spontaneously and in response to stimuli. The spatiotemporal structure of waves can indicate the information they encode and the physiological processes that sustain them. Here, we investigate the stimulus-response relationships of traveling waves emerging in adaptive neural fields as a model of visual motion processing. Neural field equations model the activity of cortical tissue as a continuum excitable medium, and adaptive processes provide negative feedback, generating localized activity patterns. Synaptic connectivity in our model is described by an integral kernel that weakens dynamically due to activity-dependent synaptic depression, leading to marginally stable traveling fronts (with attenuated backs) or pulses of a fixed speed. Our analysis quantifies how weak stimuli shift the relative position of these waves over time, characterized by a wave response function we obtain perturbatively. Persistent and continuously visible stimuli model moving visual objects. Intermittent flashes that hop across visual space can produce the experience of smooth apparent visual motion. Entrainment of waves to both kinds of moving stimuli are well characterized by our theory and numerical simulations, providing a mechanistic description of the perception of visual motion.

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.

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.

Brightness illusions drive a neuronal response in the primary visual cortex under top-down modulation.

Brightness illusions are a powerful tool in studying vision, yet their neural correlates are poorly understood. Based on a human paradigm, we presented illusory drifting gratings to mice. Primary visual cortex (V1) neurons responded to illusory gratings, matching their direction selectivity for real gratings, and they tracked the spatial phase offset between illusory and real gratings. Illusion responses were delayed compared to real gratings, in line with the theory that processing illusions requires feedback from higher visual areas (HVAs). We provide support for this theory by showing a reduced V1 response to illusions, but not real gratings, following HVAs optogenetic inhibition. Finally, we used the pupil response (PR) as an indirect perceptual report and showed that the mouse PR matches the human PR to perceived luminance changes. Our findings resolve debates over whether V1 neurons are involved in processing illusions and highlight the involvement of feedback from HVAs.

Frequency-dependent dynamics of steady-state visual evoked potentials under sustained flicker stimulation.

Steady-state visual evoked potentials (SSVEP) are electroencephalographic signals elicited when the brain is exposed to a visual stimulus with a steady frequency. We analyzed the temporal dynamics of SSVEP during sustained flicker stimulation at 5, 10, 15, 20 and 40 Hz. We found that the amplitudes of the responses were not stable over time. For a 5 Hz stimulus, the responses progressively increased, while, for higher flicker frequencies, the amplitude increased during the first few seconds and often showed a continuous decline afterward. We hypothesize that these two distinct sets of frequency-dependent SSVEP signal properties reflect the contribution of parvocellular and magnocellular visual pathways generating sustained and transient responses, respectively. These results may have important applications for SSVEP signals used in research and brain-computer interface technology and may contribute to a better understanding of the frequency-dependent temporal mechanisms involved in the processing of prolonged periodic visual stimuli.

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.

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.

Stimulus-dependent synaptic plasticity underlies neuronal circuitry refinement in the mouse primary visual cortex.

Perceptual learning improves our ability to interpret sensory stimuli present in our environment through experience. Despite its importance, the underlying mechanisms that enable perceptual learning in our sensory cortices are still not fully understood. In this study, we used in vivo two-photon imaging to investigate the functional and structural changes induced by visual stimulation in the mouse primary visual cortex (V1). Our results demonstrate that repeated stimulation leads to a refinement of V1 circuitry by decreasing the number of responsive neurons while potentiating their response. At the synaptic level, we observe a reduction in the number of dendritic spines and an overall increase in spine AMPA receptor levels in the same subset of neurons. In addition, visual stimulation induces synaptic potentiation in neighboring spines within individual dendrites. These findings provide insights into the mechanisms of synaptic plasticity underlying information processing in the neocortex.

A Unifying Model for Discordant and Concordant Results in Human Neuroimaging Studies of Facial Viewpoint Selectivity.

Recognizing faces regardless of their viewpoint is critical for social interactions. Traditional theories hold that view-selective early visual representations gradually become tolerant to viewpoint changes along the ventral visual hierarchy. Newer theories, based on single-neuron monkey electrophysiological recordings, suggest a three-stage architecture including an intermediate face-selective patch abruptly achieving invariance to mirror-symmetric face views. Human studies combining neuroimaging and multivariate pattern analysis (MVPA) have provided convergent evidence of view selectivity in early visual areas. However, contradictory conclusions have been reached concerning the existence in humans of a mirror-symmetric representation like that observed in macaques. We believe these contradictions arise from low-level stimulus confounds and data analysis choices. To probe for low-level confounds, we analyzed images from two face databases. Analyses of image luminance and contrast revealed biases across face views described by even polynomials-i.e., mirror-symmetric. To explain major trends across neuroimaging studies, we constructed a network model incorporating three constraints: cortical magnification, convergent feedforward projections, and interhemispheric connections. Given the identified low-level biases, we show that a gradual increase of interhemispheric connections across network-layers is sufficient to replicate view-tuning in early processing stages and mirror-symmetry in later stages. Data analysis decisions-pattern dissimilarity measure and data recentering-accounted for the inconsistent observation of mirror-symmetry across prior studies. Pattern analyses of human fMRI data (of either sex) revealed biases compatible with our model. The model provides a unifying explanation of MVPA studies of viewpoint selectivity and suggests observations of mirror-symmetry originate from ineffectively normalized signal imbalances across different face views.

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.

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.

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.