Convolutional neural network models applied to neuronal responses in macaque V1 reveal limited nonlinear processing.

Computational models of the primary visual cortex (V1) have suggested that V1 neurons behave like Gabor filters followed by simple nonlinearities. However, recent work employing convolutional neural network (CNN) models has suggested that V1 relies on far more nonlinear computations than previously thought. Specifically, unit responses in an intermediate layer of VGG-19 were found to best predict macaque V1 responses to thousands of natural and synthetic images. Here, we evaluated the hypothesis that the poor performance of lower layer units in VGG-19 might be attributable to their small receptive field size rather than to their lack of complexity per se. We compared VGG-19 with AlexNet, which has much larger receptive fields in its lower layers. Whereas the best-performing layer of VGG-19 occurred after seven nonlinear steps, the first convolutional layer of AlexNet best predicted V1 responses. Although the predictive accuracy of VGG-19 was somewhat better than that of standard AlexNet, we found that a modified version of AlexNet could match the performance of VGG-19 after only a few nonlinear computations. Control analyses revealed that decreasing the size of the input images caused the best-performing layer of VGG-19 to shift to a lower layer, consistent with the hypothesis that the relationship between image size and receptive field size can strongly affect model performance. We conducted additional analyses using a Gabor pyramid model to test for nonlinear contributions of normalization and contrast saturation. Overall, our findings suggest that the feedforward responses of V1 neurons can be well explained by assuming only a few nonlinear processing stages.

The influence of electrode types to the visually induced gamma oscillations in mouse primary visual cortex.

The local field potential (LFP) is an extracellular electrical signal associated with neural ensemble input and dendritic signaling. Previous studies have linked gamma band oscillations of the LFP in cortical circuits to sensory stimuli encoding, attention, memory, and perception. Inconsistent results regarding gamma tuning for visual features were reported, but it remains unclear whether these discrepancies are due to variations in electrode properties. Specifically, the surface area and impedance of the electrode are important characteristics in LFP recording. To comprehensively address these issues, we conducted an electrophysiological study in the V1 region of lightly anesthetized mice using two types of electrodes: one with higher impedance (1 MΩ) and a sharp tip (10 µm), while the other had lower impedance (100 KΩ) but a thicker tip (200 µm). Our findings demonstrate that gamma oscillations acquired by sharp-tip electrodes were significantly stronger than those obtained from thick-tip electrodes. Regarding size tuning, most gamma power exhibited surround suppression at larger gratings when recorded from sharp-tip electrodes. However, the majority showed enhanced gamma power at larger gratings when recorded from thick-tip electrodes. Therefore, our study suggests that microelectrode parameters play a significant role in accurately recording gamma oscillations and responsive tuning to sensory stimuli.

Nonuniform and pathway-specific laminar processing of spatial frequencies in the primary visual cortex of primates.

The neocortex comprises six cortical layers that play a crucial role in information processing; however, it remains unclear whether laminar processing is consistent across all regions within a single cortex. In this study, we demonstrate diverse laminar response patterns in the primary visual cortex (V1) of three male macaque monkeys when exposed to visual stimuli at different spatial frequencies (SFs). These response patterns can be categorized into two groups. One group exhibit suppressed responses in the output layers for all SFs, while the other type shows amplified responses specifically at high SFs. Further analysis suggests that both magnocellular (M) and parvocellular (P) pathways contribute to the suppressive effect through feedforward mechanisms, whereas amplification is specific to local recurrent mechanisms within the parvocellular pathway. These findings highlight the non-uniform distribution of neural mechanisms involved in laminar processing and emphasize how pathway-specific amplification selectively enhances representations of high-SF information in primate V1.

Organization of corticocortical and thalamocortical top-down inputs in the primary visual cortex.

Unified visual perception requires integration of bottom-up and top-down inputs in the primary visual cortex (V1), yet the organization of top-down inputs in V1 remains unclear. Here, we used optogenetics-assisted circuit mapping to identify how multiple top-down inputs from higher-order cortical and thalamic areas engage V1 excitatory and inhibitory neurons. Top-down inputs overlap in superficial layers yet segregate in deep layers. Inputs from the medial secondary visual cortex (V2M) and anterior cingulate cortex (ACA) converge on L6 Pyrs, whereas ventrolateral orbitofrontal cortex (ORBvl) and lateral posterior thalamic nucleus (LP) inputs are processed in parallel in Pyr-type-specific subnetworks (Pyr←ORBvl and Pyr←LP) and drive mutual inhibition between them via local interneurons. Our study deepens understanding of the top-down modulation mechanisms of visual processing and establishes that V2M and ACA inputs in L6 employ integrated processing distinct from the parallel processing of LP and ORBvl inputs in L5.

Predictions and errors are distinctly represented across V1 layers.

Popular accounts of mind and brain propose that the brain continuously forms predictions about future sensory inputs and combines predictions with inputs to determine what we perceive.1,2,3,4,5,6 Under "predictive processing" schemes, such integration is supported by the hierarchical organization of the cortex, whereby feedback connections communicate predictions from higher-level deep layers to agranular (superficial and deep) lower-level layers.7,8,9,10 Predictions are compared with input to compute the "prediction error," which is transmitted up the hierarchy from superficial layers of lower cortical regions to the middle layers of higher areas, to update higher-level predictions until errors are reconciled.11,12,13,14,15 In the primary visual cortex (V1), predictions have thereby been proposed to influence representations in deep layers while error signals may be computed in superficial layers. Despite the framework's popularity, there is little evidence for these functional distinctions because, to our knowledge, unexpected sensory events have not previously been presented in human laminar paradigms to contrast against expected events. To this end, this 7T fMRI study contrasted V1 responses to expected (75% likely) and unexpected (25%) Gabor orientations. Multivariate decoding analyses revealed an interaction between expectation and layer, such that expected events could be decoded with comparable accuracy across layers, while unexpected events could only be decoded in superficial laminae. Although these results are in line with these accounts that have been popular for decades, such distinctions have not previously been demonstrated in humans. We discuss how both prediction and error processes may operate together to shape our unitary perceptual experiences.

A non-image-forming visual circuit mediates the innate fear of heights in male mice.

The neural basis of fear of heights remains largely unknown. In this study, we investigated the fear response to heights in male mice and observed characteristic aversive behaviors resembling human height vertigo. We identified visual input as a critical factor in mouse reactions to heights, while peripheral vestibular input was found to be nonessential for fear of heights. Unexpectedly, we found that fear of heights in naïve mice does not rely on image-forming visual processing by the primary visual cortex. Instead, a subset of neurons in the ventral lateral geniculate nucleus (vLGN), which connects to the lateral/ventrolateral periaqueductal gray (l/vlPAG), drives the expression of fear associated with heights. Additionally, we observed that a subcortical visual pathway linking the superior colliculus to the lateral posterior thalamic nucleus inhibits the defensive response to height threats. These findings highlight a rapid fear response to height threats through a subcortical visual and defensive pathway from the vLGN to the l/vlPAG.

Neuronal functional connectivity is impaired in a layer dependent manner near chronically implanted intracortical microelectrodes in C57BL6 wildtype mice.

Objective.This study aims to reveal longitudinal changes in functional network connectivity within and across different brain structures near chronically implanted microelectrodes. While it is well established that the foreign-body response (FBR) contributes to the gradual decline of the signals recorded from brain implants over time, how the FBR affects the functional stability of neural circuits near implanted brain-computer interfaces (BCIs) remains unknown. This research aims to illuminate how the chronic FBR can alter local neural circuit function and the implications for BCI decoders.Approach.This study utilized single-shank, 16-channel,100µm site-spacing Michigan-style microelectrodes (3 mm length, 703µm2 site area) that span all cortical layers and the hippocampal CA1 region. Sex balanced C57BL6 wildtype mice (11-13 weeks old) received perpendicularly implanted microelectrode in left primary visual cortex. Electrophysiological recordings were performed during both spontaneous activity and visual sensory stimulation. Alterations in neuronal activity near the microelectrode were tested assessing cross-frequency synchronization of local field potential (LFP) and spike entrainment to LFP oscillatory activity throughout 16 weeks after microelectrode implantation.Main results. The study found that cortical layer 4, the input-receiving layer, maintained activity over the implantation time. However, layers 2/3 rapidly experienced severe impairment, leading to a loss of proper intralaminar connectivity in the downstream output layers 5/6. Furthermore, the impairment of interlaminar connectivity near the microelectrode was unidirectional, showing decreased connectivity from Layers 2/3 to Layers 5/6 but not the reverse direction. In the hippocampus, CA1 neurons gradually became unable to properly entrain to the surrounding LFP oscillations.Significance. This study provides a detailed characterization of network connectivity dysfunction over long-term microelectrode implantation periods. This new knowledge could contribute to the development of targeted therapeutic strategies aimed at improving the health of the tissue surrounding brain implants and potentially inform engineering of adaptive decoders as the FBR progresses. Our study's understanding of the dynamic changes in the functional network over time opens the door to developing interventions for improving the long-term stability and performance of intracortical microelectrodes.

Binocular receptive-field construction in the primary visual cortex.

ON and OFF thalamic afferents from the two eyes converge in the primary visual cortex to form binocular receptive fields. The receptive fields need to be diverse to sample our visual world but also similar across eyes to achieve binocular fusion. It is currently unknown how the cortex balances these competing needs between receptive-field diversity and similarity. Our results demonstrate that receptive fields in the cat visual cortex are binocularly matched with exquisite precision for retinotopy, orientation/direction preference, orientation/direction selectivity, response latency, and ON-OFF polarity/structure. Specifically, the average binocular mismatches in retinotopy and ON-OFF structure are tightly restricted to 1/20 and 1/5 of the average receptive-field size but are still large enough to generate all types of binocular disparity tuning. Based on these results, we conclude that cortical receptive fields are binocularly matched with the high precision needed to facilitate binocular fusion while allowing restricted mismatches to process visual depth.

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.

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.

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.

Altered functional connectivity strength of primary visual cortex in subjects with thyroid-associated ophthalmopathy.

Our objective was to explore the disparities in the intrinsic functional connectivity (FC) patterns of primary visual cortex (V1) between patients with thyroid-associated ophthalmopathy (TAO) and healthy controls (HCs) utilizing resting-state functional MRI. Twenty-one patients with TAO (14 males and 7 females; mean age: 54.17 ±â€…4.83 years) and 21 well-matched HCs (14 males and 7 females; mean age: 55.17 ±â€…5.37 years) underwent functional MRI scans in the resting-state. We assessed modifications in the intrinsic FC patterns of the V1 in TAO patients using the FC method. Subsequently, the identified alterations in FC regions in the analysis were selected as classification features to distinguish TAO patients from HCs through the support vector machine (SVM) method. The results indicated that, in comparison to HCs, patients with TAO exhibited notably reduced FC values between the left V1 and the bilateral calcarine (CAL), lingual gyrus (LING) and superior occipital gyrus, as well as between the right V1 and the bilateral CAL/LING and the right cerebellum. Furthermore, the SVM classification model based on FC maps demonstrated effective performance in distinguishing TAO patients from HCs, achieving an accuracy of 61.9% using the FC of the left V1 and 64.29% using the FC of the right V1. Our study revealed that patients with TAO manifested disruptions in FC between the V1 and higher visual regions during rest. This might indicate that TAO patients could present with impaired top-down modulations, visual imagery and vision-motor function. These insights could be valuable in understanding the underlying neurobiological mechanisms of vision impairment in individuals with TAO.

Resting-State Functional Connectivity of the Primary Visual Cortex in Children with Anisometropia Amblyopia.

INTRODUCTION: This study aimed to explore the functional connectivity of the primary visual cortex (V1) in children with anisometropic amblyopia by using the resting-state functional connectivity analysis method and determine whether anisometropic amblyopia is associated with changes in brain function. METHODS: Functional magnetic resonance imaging (fMRI) data were obtained from 16 children with anisometropia amblyopia (CAA group) and 12 healthy children (HC group) during the resting state. The Brodmann area 17 (BA17) was used as the region of interest, and the functional connection (FC) of V1 was analyzed in both groups. A two-sample t test was used to analyze the FC value between the two groups. Pearson's correlation was used to analyze the correlation between the mean FC value in the brain function change area of the CAA group and the best corrected visual acuity (BCVA) of amblyopia. p < 0.05 was considered statistically significant. RESULTS: There were no significant differences in age and sex between the CAA and HC groups (p > 0.05). Compared to the HC group, the CAA group showed lower FC values in BA17 and the left medial frontal gyrus, as well as BA17 and the left triangle inferior frontal gyrus. Conversely, the CAA group showed higher FC values in BA17 and the left central posterior gyrus. Notably, BCVA in amblyopia did not correlate with the area of change in mean FC in the brain function of the CAA group. CONCLUSION: Resting-state fMRI-based functional connectivity analysis indicates a significant alteration in V1 of children with anisometropic amblyopia. These findings contribute additional insights into the neuropathological mechanisms underlying visual impairment in anisometropic amblyopia.

Stimulus-dependent differences in cortical versus subcortical contributions to visual detection in mice.

The primary visual cortex (V1) and the superior colliculus (SC) both occupy stations early in the processing of visual information. They have long been thought to perform distinct functions, with the V1 supporting the perception of visual features and the SC regulating orienting to visual inputs. However, growing evidence suggests that the SC supports the perception of many of the same visual features traditionally associated with the V1. To distinguish V1 and SC contributions to visual processing, it is critical to determine whether both areas causally contribute to the detection of specific visual stimuli. Here, mice reported changes in visual contrast or luminance near their perceptual threshold while white noise patterns of optogenetic stimulation were delivered to V1 or SC inhibitory neurons. We then performed a reverse correlation analysis on the optogenetic stimuli to estimate a neuronal-behavioral kernel (NBK), a moment-to-moment estimate of the impact of V1 or SC inhibition on stimulus detection. We show that the earliest moments of stimulus-evoked activity in the SC are critical for the detection of both luminance and contrast changes. Strikingly, there was a robust stimulus-aligned modulation in the V1 contrast-detection NBK but no sign of a comparable modulation for luminance detection. The data suggest that behavioral detection of visual contrast depends on both V1 and SC spiking, whereas mice preferentially use SC activity to detect changes in luminance. Electrophysiological recordings showed that neurons in both the SC and V1 responded strongly to both visual stimulus types, while the reverse correlation analysis reveals when these neuronal signals actually contribute to visually guided behaviors.

M2 receptors are required for spatiotemporal sequence learning in mouse primary visual cortex.

Acetylcholine is a neurotransmitter that plays a variety of roles in the central nervous system. It was previously shown that blocking muscarinic receptors with a nonselective antagonist prevents a form of experience-dependent plasticity termed "spatiotemporal sequence learning" in the mouse primary visual cortex (V1). Muscarinic signaling is a complex process involving the combined activities of five different G protein-coupled receptors, M1-M5, all of which are expressed in the murine brain but differ from each other functionally and in anatomical localization. Here we present electrophysiological evidence that M2, but not M1, receptors are required for spatiotemporal sequence learning in mouse V1. We show in male mice that M2 is highly expressed in the neuropil in V1, especially in thalamorecipient layer 4, and colocalizes with the soma in a subset of somatostatin-expressing neurons in deep layers. We also show that expression of M2 receptors is higher in the monocular region of V1 than it is in the binocular region but that the amount of experience-dependent sequence potentiation is similar in both regions and that blocking muscarinic signaling after visual stimulation does not prevent plasticity. This work establishes a new functional role for M2-type receptors in processing temporal information and demonstrates that monocular circuits are modified by experience in a manner similar to binocular circuits.NEW & NOTEWORTHY Muscarinic acetylcholine receptors are required for multiple forms of plasticity in the brain and support perceptual functions, but the precise role of the five subtypes (M1-M5) are unclear. Here we show that the M2 receptor is specifically required to encode experience-dependent representations of spatiotemporal relationships in both monocular and binocular regions of mouse V1. This work identifies a novel functional role for M2 receptors in coding temporal information into cortical circuits.

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.

Are we aware of neural activity in primary visual cortex? A neuropsychological case study.

OBJECTIVE: According to a seminal hypothesis stated by Crick and Koch in 1995, one is not aware of neural activity in primary visual cortex (V1) because this region lacks reciprocal connections with prefrontal cortex (PFC). METHODS: We provide here a neuropsychological illustration of this hypothesis in a patient with a very rare form of cortical blindness: ventral and dorsal cortical pathways were lesioned bilaterally while V1 areas were partially preserved. RESULTS: Visual stimuli escaped conscious perception but still activated V1 regions that were functionally disconnected from PFC. INTERPRETATION: These results are consistent with the hypothesis of a causal role of PFC in visual awareness.

In primary visual cortex fMRI responses to chromatic and achromatic stimuli are interdependent and predict contrast detection thresholds.

Chromatic and achromatic signals in primary visual cortex have historically been considered independent of each other but have since shown evidence of interdependence. Here, we investigated the combination of two components of a stimulus; an achromatic dynamically changing check background and a chromatic (L-M or S cone) target grating. We found that combinations of chromatic and achromatic signals in primary visual cortex were interdependent, with the dynamic range of responses to chromatic contrast decreasing as achromatic contrast increased. A contrast detection threshold study also revealed interdependence of background and target, with increasing chromatic contrast detection thresholds as achromatic background contrast increased. A model that incorporated a normalising effect of achromatic contrast on chromatic responses, but not vice versa, best predicted our V1 data as well as behavioural thresholds. Further along the visual hierarchy, the dynamic range of chromatic responses was maintained when compared to achromatic responses, which became increasingly compressive.

Dynamic fading memory and expectancy effects in the monkey primary visual cortex.

In order to investigate the involvement of the primary visual cortex (V1) in working memory (WM), parallel, multisite recordings of multi-unit activity were obtained from monkey V1 while the animals performed a delayed match-to-sample (DMS) task. During the delay period, V1 population firing rate vectors maintained a lingering trace of the sample stimulus that could be reactivated by intervening impulse stimuli that enhanced neuronal firing. This fading trace of the sample did not require active engagement of the monkeys in the DMS task and likely reflects the intrinsic dynamics of recurrent cortical networks in lower visual areas. This renders an active, attention-dependent involvement of V1 in the maintenance of WM contents unlikely. By contrast, population responses to the test stimulus depended on the probabilistic contingencies between sample and test stimuli. Responses to tests that matched expectations were reduced which agrees with concepts of predictive coding.

Predicting Single Neuron Responses of the Primary Visual Cortex with Deep Learning Model.

Modeling neuron responses to stimuli can shed light on next-generation technologies such as brain-chip interfaces. Furthermore, high-performing models can serve to help formulate hypotheses and reveal the mechanisms underlying neural responses. Here the state-of-the-art computational model is presented for predicting single neuron responses to natural stimuli in the primary visual cortex (V1) of mice. The algorithm incorporates object positions and assembles multiple models with different train-validation data, resulting in a 15%-30% improvement over the existing models in cross-subject predictions and ranking first in the SENSORIUM 2022 Challenge, which benchmarks methods for neuron-specific prediction based on thousands of images. Importantly, The model reveals evidence that the spatial organizations of V1 are conserved across mice. This model will serve as an important noninvasive tool for understanding and utilizing the response patterns of primary visual cortex neurons.