Networks In Visual Cortex Research Articles

Stimulus type shapes the topology of cellular functional networks in mouse visual cortex

On the timescale of sensory processing, neuronal networks have relatively fixed anatomical connectivity, while functional interactions between neurons can vary depending on the ongoing activity of the neurons within the network. We thus hypothesized that different types of stimuli could lead those networks to display stimulus-dependent functional connectivity patterns. To test this hypothesis, we analyzed single-cell resolution electrophysiological data from the Allen Institute, with simultaneous recordings of stimulus-evoked activity from neurons across 6 different regions of mouse visual cortex. Comparing the functional connectivity patterns during different stimulus types, we made several nontrivial observations: (1) while the frequencies of different functional motifs were preserved across stimuli, the identities of the neurons within those motifs changed; (2) the degree to which functional modules are contained within a single brain region increases with stimulus complexity. Altogether, our work reveals unexpected stimulus-dependence to the way groups of neurons interact to process incoming sensory information.

Human Visual Cortex and Deep Convolutional Neural Network Care Deeply about Object Background.

Deep convolutional neural networks (DCNNs) are able to partially predict brain activity during object categorization tasks, but factors contributing to this predictive power are not fully understood. Our study aimed to investigate the factors contributing to the predictive power of DCNNs in object categorization tasks. We compared the activity of four DCNN architectures with EEG recordings obtained from 62 human participants during an object categorization task. Previous physiological studies on object categorization have highlighted the importance of figure-ground segregation-the ability to distinguish objects from their backgrounds. Therefore, we investigated whether figure-ground segregation could explain the predictive power of DCNNs. Using a stimulus set consisting of identical target objects embedded in different backgrounds, we examined the influence of object background versus object category within both EEG and DCNN activity. Crucially, the recombination of naturalistic objects and experimentally controlled backgrounds creates a challenging and naturalistic task, while retaining experimental control. Our results showed that early EEG activity (< 100 msec) and early DCNN layers represent object background rather than object category. We also found that the ability of DCNNs to predict EEG activity is primarily influenced by how both systems process object backgrounds, rather than object categories. We demonstrated the role of figure-ground segregation as a potential prerequisite for recognition of object features, by contrasting the activations of trained and untrained (i.e., random weights) DCNNs. These findings suggest that both human visual cortex and DCNNs prioritize the segregation of object backgrounds and target objects to perform object categorization. Altogether, our study provides new insights into the mechanisms underlying object categorization as we demonstrated that both human visual cortex and DCNNs care deeply about object background.

Association between clinical features and decreased degree centrality and variability in dynamic functional connectivity in the obsessive–compulsive disorder

Neuroimaging studies have indicated widespread brain structural and functional disruptions in patients with obsessive–compulsive disorder (OCD). However, the underlying mechanism of these changes remains unclear. A total of 45 patients with OCD and 42 healthy controls (HC) were enrolled. The study investigated local degree centrality (DC) abnormalities and employed abnormal regions of DC as seeds to investigate variability in dynamic functional connectivity (dFC) in the whole brain using a sliding window approach to analyze resting-state functional magnetic resonance imaging. The relationship between abnormal DC and dFC as well as the clinical features of OCD were examined using correlation analysis. Our findings suggested decreased DC in the bilateral thalamus, bilateral precuneus, and bilateral cuneus in OCD patients and a nominally negative correlation between the DC value in the thalamus and illness severity measured using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). In addition, seed-based dFC analysis showed that compared to measurements in the HC, the patients had decreased dFC variability between the left thalamus and the left cuneus and right lingual gyrus, and between the bilateral cuneus and bilateral postcentral gyrus, and a nominally positive correlation between the duration of illness and dFC variability between the left cuneus and left postcentral gyrus. These results indicated that OCD patients had decreased hub importance in the bilateral thalamus and cuneus throughout the entire brain. This reduction was associated with impaired coupling with dynamic function in the visual cortex and sensorimotor network and provided novel insights into the neurophysiological mechanisms underlying OCD.

Visual cortex: How mice learn to detect entirely novel inputs

A new study has revealed that neural amplification in mouse primary visual cortex substantially increases between training sessions as mice learn to detect novel optogenetic input directly into visual cortex, suggesting consolidation and recurrent network plasticity contribute to learning the behavior.

Dynamic Feedback Between Antidepressant Placebo Expectancies and Mood

Despite high antidepressant placebo response rates, the mechanisms underlying the persistence of antidepressant placebo effects are still poorly understood. To investigate the neurobehavioral mechanisms underlying the evolution of antidepressant placebo effects using a reinforcement learning (RL) framework. In this acute within-patient cross-sectional study of antidepressant placebos, patients aged 18 to 55 years not receiving medication for major depressive disorder (MDD) were recruited at the University of Pittsburgh between February 21, 2017, to March 1, 2021. The antidepressant placebo functional magnetic resonance imaging task manipulates placebo-associated expectancies using visually cued fast-acting antidepressant infusions and controls their reinforcement with sham visual neurofeedback while assessing expected and experienced mood improvement. The trial-by-trial evolution of expectancies and mood was examined using multilevel modeling and RL, relating model-predicted signals to spatiotemporal dynamics of blood oxygenation level-dependent (BOLD) response. A bayesian RL model comparison in 60 individuals (mean [SE] age, 24.5 [0.8] years; 51 females [85%]) with MDD revealed that antidepressant placebo trial-wise expectancies were updated by composite learning signals multiplexing sensory evidence (neurofeedback) and trial-wise mood (bayesian omnibus risk <0.001; exceedance probability = 97%). Placebo expectancy, neurofeedback manipulations, and composite learning signals modulated the visual cortex and dorsal attention network (threshold-free cluster enhancement [TFCE] = 1 - P >.95). As participants anticipated antidepressant infusions, learned placebo expectancies modulated the salience network (SN, TFCE = 1 - P >.95), positively scaling with depression severity. Results of this cross-sectional study suggest that on a timescale of minutes, antidepressant placebo effects were maintained by positive feedback loops between expectancies and mood improvement. During learning, representations of placebos and their perceived effects were enhanced in primary and secondary sensory cortices. Latent learned placebo expectancies were encoded in the SN.

Functional topography of pulvinar-visual cortex networks in macaques revealed by INS-fMRI.

The pulvinar in the macaque monkey contains three divisions: the medial pulvinar (PM), the lateral pulvinar (PL), and the inferior pulvinar (PI). Anatomical studies have shown that connections of PM are preferentially distributed to higher association areas, those of PL are biased toward the ventral visual pathway, and those of PI are biased with the dorsal visual pathway. To study functional connections of the pulvinar at mesoscale, we used a novel method called INS-fMRI (infrared neural stimulation and functional magnetic resonance imaging). This method permits studies and comparisons of multiple pulvinar networks within single animals. As previously revealed, stimulations of different sites in PL and PI produced topographically organized focal activations in visual areas V1, V2, and V3. In contrast, PM stimulation elicited little or diffuse response. The relative activations of areas V1, V2, V3A, V3d, V3v, V4, MT, and MST revealed that connections of PL are biased to ventral pathway areas, and those of PI are biased to dorsal areas. Different statistical values of activated blood-oxygen-level-dependent responses produced the same center of activation, indicating stability of connectivity; it also suggests possible dynamics of broad to focal responses from single stimulation sites. These results demonstrate that infrared neural stimulation-induced connectivity is largely consistent with previous anatomical connectivity studies, thereby demonstrating validity of our novel method. In addition, it suggests additional interpretations of functional connectivity to complement anatomical studies.

Persistent Brain Connectivity Changes in Healthy Volunteers Following Nitrous Oxide Inhalation

BackgroundNitrous oxide holds promise in the treatment of major depressive disorder. Its psychotropic effects and NMDA receptor antagonism have led to comparisons with ketamine. Despite longstanding use, persistent effects of nitrous oxide on the brain have not been characterized. MethodsSixteen healthy volunteers were recruited in a double-blind crossover study. In randomized order, individuals underwent a 1-hour inhalation of either 50% nitrous oxide/oxygen or air/oxygen mixtures. At least two 7.5-minute echo-planar resting-state functional magnetic resonance imaging scans were obtained before and at 2 and 24 hours after each inhalation (average 130 min/participant). Using the time series of preprocessed, motion artifact–scrubbed, and nuisance covariate–regressed imaging data, interregional signal correlations were measured and converted to T scores. Hierarchical clustering and linear mixed-effects models were employed. ResultsNitrous oxide inhalation produced changes in global brain connectivity that persisted in the occipital cortex at 2 and 24 hours postinhalation (p < .05, false discovery rate–corrected). Analysis of resting-state networks demonstrated robust strengthening of connectivity between regions of the visual network and those of the dorsal attention network, across 2 and 24 hours after inhalation (p < .05, false discovery rate–corrected). Weaker changes in connectivity were found between the visual cortex and regions of the frontoparietal and default mode networks. Parallel analyses following air/oxygen inhalation yielded no significant changes in functional connectivity. ConclusionsNitrous oxide inhalation in healthy volunteers revealed persistent increases in global connectivity between regions of primary visual cortex and dorsal attention network. These findings suggest that nitrous oxide inhalation induces neurophysiological cortical changes that persist for at least 24 hours.

Task modulates the orthographic and phonological representations in the bilateral ventral Occipitotemporal cortex.

As a key area in word reading, the left ventral occipitotemporal cortex is proposed for abstract orthographic processing, and its middle part has even been labeled as the visual word form area. Because the definition of the VWFA largely varies and the reading task differs across studies, the function of the left ventral occipitotemporal cortex in word reading is continuingly debated on whether this region is specific for orthographic processing or be involved in an interactive framework. By using representational similarity analysis (RSA), this study examined information representation in the VWFA at the individual level and the modulatory effect of reading task. Twenty-four subjects were scanned while performing the explicit (i.e., the naming task) and implicit (i.e., the perceptual task) reading tasks. Activation analysis showed that the naming task elicited greater activation in regions related to phonological processing (e.g., the bilateral prefrontal cortex and temporoparietal cortex), while the perceptual task recruited greater activation in visual cortex and default mode network (e.g., the bilateral middle frontal gyrus, angular gyrus, and the right middle temporal gyrus). More importantly, RSA also showed that task modulated information representation in the bilateral anterior occipitotemporal cortex and VWFA. Specifically, ROI-based RSA revealed enhanced orthographic and phonological representations in the bilateral anterior fusiform cortex and VWFA in the naming task relative to the perceptual task. These results suggest that lexical representation in the VWFA is influenced by the demand of phonological processing, which supports the interactive account of the VWFA.

Emergence of probabilistic representation in the neural network of primary visual cortex

SummaryDuring the early development of the mammalian visual system, the distribution of neuronal preferred orientations in the primary visual cortex (V1) gradually shifts to match major orientation features of the environment, achieving its optimal representation. By combining computational modeling and electrophysiological recording, we provide a circuit plasticity mechanism that underlies the developmental emergence of such matched representation in the visual cortical network. Specifically, in a canonical circuit of densely-interconnected pyramidal cells and inhibitory parvalbumin-expressing (PV+) fast-spiking interneurons in V1 layer 2/3, our model successfully simulates the experimental observations and further reveals that the nonuniform inhibition plays a key role in shaping the network representation through spike timing-dependent plasticity. The experimental results suggest that PV + interneurons in V1 are capable of providing nonuniform inhibition shortly after vision onset. Our study elucidates a circuit mechanism for acquisition of prior knowledge of environment for optimal inference in sensory neural systems

Within and beyond the visual cortex: brain tumors induce highly sensitive plasticity of visual processing in whole-brain neural functional networks.

Vision is a key source of information input for humans, which involves various cognitive functions and a great range of neural networks inside and beyond the visual cortex. There has been increasing observation that the cognitive outcomes after a brain lesion cannot be well predicted by the attributes of the lesion itself but are influenced by the functional network plasticity. However, the mechanisms of impaired or preserved visual cognition have not been probed from direct function-execution conditions and few works have observed it on whole-brain dynamic networks. We used high-resolution electroencephalogram recordings from 25 patients with brain tumors to track the dynamical patterns of functional reorganization in visual processing tasks with multilevel complexity. By comparing with 24 healthy controls, increased cortical responsiveness as functional compensation was identified in the early phase of processing, which was highly localized to the visual cortex and functional networks and less relevant to the tumor position. Besides, a spreading wide enhancement in whole-brain functional connectivity was elicited by the visual word-recognition task. Enhanced early rapid-onset cortical compensation in the local functional networks may contribute to largely preserved basic vision functions, and higher-cognitive tasks are vulnerable to impairment but with high sensitivity of functional plasticity being elicited.

Functional and volumetric cortico-cerebellar alterations in congenital blind children associated with language processing

IntroductionVisual deprivation affects learning and cognition, and maybe associated with structural and functional changes in the cerebral and cerebellar areas. We explored the role of the cerebellum in sensory-motor integration with the visual cortex and their correlation with education duration and age of onset. MethodologyT1W MRI and two functional tasks (Braille reading and auditory semantics (synonyms and antonyms)) were acquired using a 3T MR scanner in twenty congenital blind (CB) subjects and twenty sighted controls (SC), and analysis was done with the SUIT and CONN tools respectively. ResultsVolumetric changes were observed in the vermis, crus I, II, cerebellum 45,6,3,7b,8b, and posterior cerebral areas of CB compared to SC. ROI analysis for auditory tasks revealed increased functional connectivity (FC) between the posterior cerebellar network, salience network, and language network, and reduced FC between the posterior cerebellar network and default mode network. For both the functional tasks, FC was increased between language regions and bilateral Cerebellum regions (crus I, crus II, cerebellum 45). DiscussionIncreased BOLD activity in cerebellum, visual cortex, and language areas; intact connectivity between the visual and language networks; a positive correlation between the duration of education and functional cluster coefficient and changes in volume suggest integrated semantic language processing by the cerebellum, visual cortex, and language networks indicating functional and structural plasticity of cerebellum. ConclusionThe cerebellum exhibits neural plasticity for processing auditory perception and Braille reading and supports the visual cortex after visual deprivation. Education enhances sensory-motor coordination in congenital blind participants.

Saliency Map Using Features Derived from Spiking Neural Networks of Primate Visual Cortex

Saliency Map Using Features Derived from Spiking Neural Networks of Primate Visual Cortex

Saliency Map Using Features Derived from Spiking Neural Networks of Primate Visual Cortex

Saliency Map Using Features Derived from Spiking Neural Networks of Primate Visual Cortex

Visual Recognition Is Heralded by Shifts in Local Field Potential Oscillations and Inhibitory Networks in Primary Visual Cortex.

Learning to recognize and filter familiar, irrelevant sensory stimuli eases the computational burden on the cerebral cortex. Inhibition is a candidate mechanism in this filtration process, and oscillations in the cortical local field potential (LFP) serve as markers of the engagement of different inhibitory neurons. We show here that LFP oscillatory activity in visual cortex is profoundly altered as male and female mice learn to recognize an oriented grating stimulus—low-frequency (∼15 Hz peak) power sharply increases, whereas high-frequency (∼65 Hz peak) power decreases. These changes report recognition of the familiar pattern as they disappear when the stimulus is rotated to a novel orientation. Two-photon imaging of neuronal activity reveals that parvalbumin-expressing inhibitory neurons disengage with familiar stimuli and reactivate to novelty, whereas somatostatin-expressing inhibitory neurons show opposing activity patterns. We propose a model in which the balance of two interacting interneuron circuits shifts as novel stimuli become familiar.SIGNIFICANCE STATEMENT Habituation, familiarity, and novelty detection are fundamental cognitive processes that enable organisms to adaptively filter meaningless stimuli and focus attention on potentially important elements of their environment. We have shown that this process can be studied fruitfully in the mouse primary visual cortex by using simple grating stimuli for which novelty and familiarity are defined by orientation and by measuring stimulus-evoked and continuous local field potentials. Altered event-related and spontaneous potentials, and deficient habituation, are well-documented features of several neurodevelopmental psychiatric disorders. The paradigm described here will be valuable to interrogate the origins of these signals and the meaning of their disruption more deeply.

Neuroimaging studies in persistent postural-perceptual dizziness and related disease: a systematic review.

Persistent Postural-Perceptual Dizziness (PPPD) is one of the most common types of chronic dizziness. The pathogenesis remains unclear. This study aimed to systematically review neuroimaging literature for investigating the central mechanism of PPPD and related disorders. PubMed, EMBASE, Medline, Cochrane,and Web of Science were searched by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The articles analyzing structural and functional neuroimaging features of PPPD and related disorders were selected according to eligibility criteria. Fifteen articles, including 4 structural, 10 functional, and 1 multimodal imaging, were eligible for inclusion in this review. The whiter matter alterations in PPPD are not entirely consistent. The changes of grey matter mainly in multisensory vestibular cortices, visual cortex, cerebellum, as well as anxiety-related network. Consistent with structural imaging, functional imaging conducted during the specific tasks or in the resting state has both found abnormal functional activation and connectivity in the vestibular cortex, especially in the parieto-insular vestibular cortex (PIVC), visual cortex, cerebellum, and anxiety-related network in PPPD and related disorder. The current review provides up-to-date knowledge and summarizes the possible central mechanism for PPPD and related disorders, and it is helpful to understanding the mechanism of PPPD.

Reduced Functional Connectivity in Children With Congenital Cataracts Using Resting-State Electroencephalography Measurement.

ObjectivesNumerous task-based functional magnetic resonance imaging studies indicate the presence of compensatory functional improvement in patients with congenital cataracts. However, there is neuroimaging evidence that shows decreased sensory perception or cognition information processing related to visual dysfunction, which favors a general loss hypothesis. This study explored the functional connectivity between visual and other networks in children with congenital cataracts using resting state electroencephalography.MethodsTwenty-one children with congenital cataracts (age: 8.02 ± 2.03 years) and thirty-five sex- and age-matched normal sighted controls were enrolled to investigate functional connectivity between the visual cortex and the default mode network, the salience network, and the cerebellum network during resting state electroencephalography (eyes closed) recordings.ResultThe congenital cataract group was less active, than the control group, in the occipital, temporal, frontal and limbic lobes in the theta, alpha, beta1 and beta2 frequency bands. Additionally, there was reduced alpha-band connectivity between the visual and somatosensory cortices and between regions of the frontal and parietal cortices associated with cognitive and attentive control.ConclusionThe results indicate abnormalities in sensory, cognition, motion and execution functional connectivity across the developing brains of children with congenital cataracts when compared with normal controls. Reduced frontal alpha activity and alpha-band connectivity between the visual cortex and salience network might reflect attenuated inhibitory information flow, leading to higher attentional states, which could contribute to adaptation of environmental change in this group of patients.

To err is (not only) human: Mechanisms of post-error attentional regulation illuminated in mice

Errors yield unfavorable outcomes but also elicit adaptive mechanisms optimizing future behavior. Norman etal. demonstrate a previously unknown direct projection from medial frontal performance-monitoring areas in mice that modulate visual cortex network activity and enable post-error attentional adaptation.

Flexible Frequency Switching in Adult Mouse Visual Cortex Is Mediated by Competition Between Parvalbumin and Somatostatin Expressing Interneurons.

Neuronal networks in rodent primary visual cortex (V1) can generate oscillations in different frequency bands depending on the network state and the level of visual stimulation. High-frequency gamma rhythms, for example, dominate the network's spontaneous activity in adult mice but are attenuated upon visual stimulation, during which the network switches to the beta band instead. The spontaneous local field potential (LFP) of juvenile mouse V1, however, mainly contains beta rhythms and presenting a stimulus does not elicit drastic changes in network oscillations. We study, in a spiking neuron network model, the mechanism in adult mice allowing for flexible switches between multiple frequency bands and contrast this to the network structure in juvenile mice that lack this flexibility. The model comprises excitatory pyramidal cells (PCs) and two types of interneurons: the parvalbumin-expressing (PV) and the somatostatinexpressing (SOM) interneuron. In accordance with experimental findings, the pyramidal-PV and pyramidal-SOM cell subnetworks are associated with gamma and beta oscillations, respectively. In our model, they are both generated via a pyramidal-interneuron gamma (PING) mechanism, wherein the PCs drive the oscillations. Furthermore, we demonstrate that large but not small visual stimulation activates SOM cells, which shift the frequency of resting-state gamma oscillations produced by the pyramidal-PV cell subnetwork so that beta rhythms emerge. Finally, we show that this behavior is obtained for only a subset of PV and SOM interneuron projection strengths, indicating that their influence on the PCs should be balanced so that they can compete for oscillatory control of the PCs. In sum, we propose a mechanism by which visual beta rhythms can emerge from spontaneous gamma oscillations in a network model of the mouse V1; for this mechanism to reproduce V1 dynamics in adult mice, balance between the effective strengths of PV and SOM cells is required.

Adaptive Orthogonal Characteristics of Bio-Inspired Neural Networks

Abstract In recent years, neural networks have attracted much attention in the machine learning and the deep learning technologies. Bio-inspired functions and intelligence are also expected to process efficiently and improve existing technologies. In the visual pathway, the prominent features consist of nonlinear characteristics of squaring and rectification functions observed in the retinal and visual cortex networks, respectively. Further, adaptation is an important feature to activate the biological systems, efficiently. Recently, to overcome short-comings of the deep learning techniques, orthogonality for the weights in the networks has been developed for the signal propagation and the efficient optimization of the learning. In this paper, bio-inspired asymmetric networks with nonlinear characteristics are proposed, which are derived from the retinal networks in the biological visual pathway. The asymmetric network proposed here was verified to detect the movement of the object, efficiently in our previous studies. This paper shows a new characteristic of the adaptive orthogonality in the asymmetric networks. First, it is shown that the asymmetric network with nonlinear characteristics is effective for generating orthogonality. Second, the proposed asymmetric network with Gabor filters is compared with the conventional energy model from the point of the orthogonality characteristics. Finally, the asymmetric networks with nonlinear characteristics can generate the extended orthogonal bases in independent subspaces, which are useful for classification and efficient learning.

Emergence of Probabilistic Representation in the Neural Network of Primary Visual Cortex

Emergence of Probabilistic Representation in the Neural Network of Primary Visual Cortex