Activity In Visual Cortex Research Articles

Neural Changes in Children With Residual Speech Sound Disorder After Ultrasound Biofeedback Speech Therapy.

Children with residual speech sound disorders (RSSD) have shown differences in neural function for speech production, as compared to their typical peers; however, information about how these differences may change over time and relative to speech therapy is needed. To address this gap, we used functional magnetic resonance imaging (fMRI) to examine functional activation and connectivity on adaptations of the syllable repetition task (SRT-Early Sounds and SRT-Late Sounds) in children with RSSD before and after a speech therapy program. Sixteen children with RSSD completed an fMRI experiment before (Time 1) and after (Time 2) a speech therapy program with ultrasound visual feedback for /ɹ/ misarticulation. Progress in therapy was measured via perceptual ratings of productions of untreated /ɹ/ word probes. To control for practice effects and developmental change in patterns of activation and connectivity, 17 children with typical speech development (TD) completed the fMRI at Time 1 and Time 2. Functional activation was analyzed using a region-of-interest approach and functional connectivity was analyzed using a seed-to-voxel approach. Children with RSSD showed a range of responses to therapy. After correcting for multiple comparisons, we did not observe any statistically significant cross-sectional differences or longitudinal changes in functional activation. A negative relationship between therapy effect size and functional activation in the left visual association cortex was on the SRT-Late Sounds after therapy, but it did not survive correction for multiple comparisons. Significant longitudinal changes in functional connectivity were observed for the RSSD group on SRT-Early Sounds and SRT-Late Sounds, as well as for the TD group on the SRT-Early Sounds. RSSD and TD groups showed connectivity differences near the left insula on the SRT-Late Sounds at Time 2. RSSD and treatment with ultrasound visual feedback may thus be associated with neural differences in speech motor and visual association processes recruited for speech production.

Gabor and Non-Gabor Neural Representations Are Shared between Visual Perception and Mental Imagery.

Visual perception and mental imagery have been shown to share a hierarchical topological visual structure of neural representation, despite the existence of dissociation of neural substrate between them in function and structure. However, we have limited knowledge about how the visual hierarchical cortex is involved in visual perception and visual imagery in a unique and shared fashion. In this study, a data set including a visual perception and an imagery experiment with human participants was used to train 2 types of voxel-wise encoding models. These models were based on Gabor features and voxel activity patterns of high-level visual cortex (i.e., fusiform face area, parahippocampal place area, and lateral occipital complex) to predict activity in the early visual cortex (EVC, i.e., V1, V2, V3) during perception, and then tested with respect to the generalization of these models to mental imagery. Our results showed that during perception and imagery, activities in the EVC could be independently predicted by the Gabor features and activity of high-level visual cortex via voxel-wise encoding models, which suggested that perception and imagery might share neural representation in the EVC. We further found Gabor-specific and non-Gabor-specific patterns of neural response to stimuli in the EVC, which were shared by perception and imagery. These findings provide insight into the mechanisms of how visual perception and imagery share representation in the EVC.

Expectation violations produce error signals in mouse V1.

Repeated exposure to visual sequences changes the form of evoked activity in the primary visual cortex (V1). Predictive coding theory provides a potential explanation for this, namely that plasticity shapes cortical circuits to encode spatiotemporal predictions and that subsequent responses are modulated by the degree to which actual inputs match these expectations. Here we use a recently developed statistical modeling technique called Model-Based Targeted Dimensionality Reduction (MbTDR) to study visually evoked dynamics in mouse V1 in the context of an experimental paradigm called "sequence learning." We report that evoked spiking activity changed significantly with training, in a manner generally consistent with the predictive coding framework. Neural responses to expected stimuli were suppressed in a late window (100-150ms) after stimulus onset following training, whereas responses to novel stimuli were not. Substituting a novel stimulus for a familiar one led to increases in firing that persisted for at least 300ms. Omitting predictable stimuli in trained animals also led to increased firing at the expected time of stimulus onset. Finally, we show that spiking data can be used to accurately decode time within the sequence. Our findings are consistent with the idea that plasticity in early visual circuits is involved in coding spatiotemporal information.

Tuberculose pulmonaire sur maladie de Takayasu compliquée de dissection de l’artère carotide commune

Previous studies have observed lower visual cortex activation for visual processing in cochlear implant (CI) users compared to normal hearing controls, while others reported enhanced visual speechreading abilities in CI users. The present work investigated whether lower visual cortical activation for visual processing can be explained by a more efficient visual sensory encoding in CI users. Specifically, we investigated whether CI users show enhanced stimulus-specific adaptation for visual stimuli compared to controls. Auditory sensory adaptation was also investigated to explore the sensory specificity of the predicted effect. Twenty post-lingually deafened adult CI users and twenty age-matched controls were presented with repeated visual and auditory stimuli during simultaneous acquisition of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). By integrating EEG and fNIRS signals we found significantly enhanced visual adaptation and lower visual cortex activation in CI users compared to controls. That is, responses to repeated visual stimuli decreased more prominently in CI users than in controls. The results suggest that CI users process visual stimuli more efficiently than controls.

Vividness as the similarity between generated imagery and an internal model

Vividness in visual mental imagery has been relatively under-explored compared to imagery’s representational format and neural mechanisms. In this paper, we take a deeper look at vividness and suggest that in re-framing it, we can potentially reconcile disparate findings regarding visual cortex activation during imagery. Unlike traditional views of vividness that define the concept in terms of perception, we frame vividness in terms of imagery’s relation to an internal model; the closer the generated imagery is to this model, the more vivid it is. This view is considered alongside existing neuroscientific, psychological, and philosophical research, as well as directions for future research.

Amplified cortical neural responses as animals learn to use novel activity patterns

Cerebral cortex supports representations of the world in patterns of neural activity, used by the brain to make decisions and guide behavior. Past work has found diverse, or limited, changes in the primary sensory cortex in response to learning, suggesting that the key computations might occur in downstream regions. Alternatively, sensory cortical changes may be central to learning. We studied cortical learning by using controlled inputs we insert: we trained mice to recognize entirely novel, non-sensory patterns of cortical activity in the primary visual cortex (V1) created by optogenetic stimulation. As animals learned to use these novel patterns, we found that their detection abilities improved by an order of magnitude or more. The behavioral change was accompanied by large increases in V1 neural responses to fixed optogenetic input. Neural response amplification to novel optogenetic inputs had little effect on existing visual sensory responses. A recurrent cortical model shows that this amplification can be achieved by a small mean shift in recurrent network synaptic strength. Amplification would seem to be desirable to improve decision-making in a detection task; therefore, these results suggest that adult recurrent cortical plasticity plays a significant role in improving behavioral performance during learning.

Individual alpha frequency appears unrelated to the latency of early visual responses.

A large body of work has linked neural oscillations in the alpha-band (8-13 Hz) to visual perceptual outcomes. In particular, studies have found that alpha phase prior to stimulus onset predicts stimulus detection, and sensory responses and that the frequency of alpha can predict temporal properties of perception. These findings have bolstered the idea that alpha-band oscillations reflect rhythmic sampling of visual information, however the mechanisms of this are unclear. Recently two contrasting hypotheses have been proposed. According to the rhythmic perception account, alpha oscillations impose phasic inhibition on perceptual processing and primarily modulate the amplitude or strength of visual responses and thus the likelihood of stimulus detection. On the other hand, the discrete perception account proposes that alpha activity discretizes perceptual inputs thereby reorganizing the timing (not only the strength) of perceptual and neural processes. In this paper, we sought neural evidence for the discrete perception account by assessing the correlation between individual alpha frequencies (IAF) and the latency of early visual evoked event-related potential (ERP) components. If alpha cycles were responsible for shifting neural events in time, then we may expect higher alpha frequencies to be associated with earlier afferent visual ERPs. Participants viewed large checkerboard stimuli presented to either the upper or lower visual field that were designed to elicit a large C1 ERP response (thought to index feedforward primary visual cortex activation). We found no reliable correlation between IAF and the C1 latency, or subsequent ERP component latencies, suggesting that the timing of these visual-evoked potentials was not modulated by alpha frequency. Our results thus fail to find evidence for discrete perception at the level of early visual responses but leave open the possibility of rhythmic perception.

Decoding brain basis of laughter and crying in natural scenes

Laughter and crying are universal signals of prosociality and distress, respectively. Here we investigated the functional brain basis of perceiving laughter and crying using naturalistic functional magnetic resonance imaging (fMRI) approach. We measured haemodynamic brain activity evoked by laughter and crying in three experiments with 100 subjects in each. The subjects i) viewed a 20-minute medley of short video clips, and ii) 30 min of a full-length feature film, and iii) listened to 13.5 min of a radio play that all contained bursts of laughter and crying. Intensity of laughing and crying in the videos and radio play was annotated by independent observes, and the resulting time series were used to predict hemodynamic activity to laughter and crying episodes. Multivariate pattern analysis (MVPA) was used to test for regional selectivity in laughter and crying evoked activations. Laughter induced widespread activity in ventral visual cortex and superior and middle temporal and motor cortices. Crying activated thalamus, cingulate cortex along the anterior-posterior axis, insula and orbitofrontal cortex. Both laughter and crying could be decoded accurately (66–77% depending on the experiment) from the BOLD signal, and the voxels contributing most significantly to classification were in superior temporal cortex. These results suggest that perceiving laughter and crying engage distinct neural networks, whose activity suppresses each other to manage appropriate behavioral responses to others’ bonding and distress signals.

Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness.

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18Hz) and high-frequency (>80Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

Modulation of Visual Responses and Ocular Dominance by Contralateral Inhibitory Activation in the Mouse Visual Cortex.

Both hemispheres connect with each other by excitatory callosal projections, and whether inhibitory interneurons, usually believed to have local innervation, engage in transcallosal activity modulation is unknown. Here, we used optogenetics in combination with cell-type-specific channelrhodopsin-2 expression to activate different inhibitory neuron subpopulations in the visual cortex and recorded the response of the entire visual cortex using intrinsic signal optical imaging. We found that optogenetic stimulation of inhibitory neurons reduced spontaneous activity (increase in the reflection of illumination) in the binocular area of the contralateral hemisphere, although these stimulations had different local effects ipsilaterally. The activation of contralateral interneurons differentially affected both eye responses to visual stimuli and, thus, changed ocular dominance. Optogenetic silencing of excitatory neurons affects the ipsilateral eye response and ocular dominance in the contralateral cortex to a lesser extent. Our results revealed a transcallosal effect of interneuron activation in the mouse visual cortex.

A survey of neurophysiological differentiation across mouse visual brain areas and timescales.

Neurophysiological differentiation (ND), a measure of the number of distinct activity states that a neural population visits over a time interval, has been used as a correlate of meaningfulness or subjective perception of visual stimuli. ND has largely been studied in non-invasive human whole-brain recordings where spatial resolution is limited. However, it is likely that perception is supported by discrete neuronal populations rather than the whole brain. Therefore, here we use Neuropixels recordings from the mouse brain to characterize the ND metric across a wide range of temporal scales, within neural populations recorded at single-cell resolution in localized regions. Using the spiking activity of thousands of simultaneously recorded neurons spanning 6 visual cortical areas and the visual thalamus, we show that the ND of stimulus-evoked activity of the entire visual cortex is higher for naturalistic stimuli relative to artificial ones. This finding holds in most individual areas throughout the visual hierarchy. Moreover, for animals performing an image change detection task, ND of the entire visual cortex (though not individual areas) is higher for successful detection compared to failed trials, consistent with the assumed perception of the stimulus. Together, these results suggest that ND computed on cellular-level neural recordings is a useful tool highlighting cell populations that may be involved in subjective perception.

A cortical zoom-in operation underlies covert shifts of visual spatial attention

Shifting the focus of attention without moving the eyes poses challenges for signal coding in visual cortex in terms of spatial resolution, signal routing, and cross-talk. Little is known how these problems are solved during focus shifts. Here, we analyze the spatiotemporal dynamic of neuromagnetic activity in human visual cortex as a function of the size and number of focus shifts in visual search. We find that large shifts elicit activity modulations progressing from highest (IT) through mid-level (V4) to lowest hierarchical levels (V1). Smaller shifts cause those modulations to start at lower levels in the hierarchy. Successive shifts involve repeated backward progressions through the hierarchy. We conclude that covert focus shifts arise from a cortical coarse-to-fine process progressing from retinotopic areas with larger toward areas with smaller receptive fields. This process localizes the target and increases the spatial resolution of selection, which resolves the above issues of cortical coding.

High-resolution quantitative and functional MRI indicate lower myelination of thin and thick stripes in human secondary visual cortex.

The characterization of cortical myelination is essential for the study of structure-function relationships in the human brain. However, knowledge about cortical myelination is largely based on post-mortem histology, which generally renders direct comparison to function impossible. The repeating pattern of pale-thin-pale-thick stripes of cytochrome oxidase (CO) activity in the primate secondary visual cortex (V2) is a prominent columnar system, in which histology also indicates different myelination of thin/thick versus pale stripes. We used quantitative magnetic resonance imaging (qMRI) in conjunction with functional magnetic resonance imaging (fMRI) at ultra-high field strength (7 T) to localize and study myelination of stripes in four human participants at sub-millimeter resolution in vivo. Thin and thick stripes were functionally localized by exploiting their sensitivity to color and binocular disparity, respectively. Resulting functional activation maps showed robust stripe patterns in V2 which enabled further comparison of quantitative relaxation parameters between stripe types. Thereby, we found lower longitudinal relaxation rates (R1) of thin and thick stripes compared to surrounding gray matter in the order of 1-2%, indicating higher myelination of pale stripes. No consistent differences were found for effective transverse relaxation rates (R2*). The study demonstrates the feasibility to investigate structure-function relationships in living humans within one cortical area at the level of columnar systems using qMRI.

Neural correlates of emotional valence for faces and words.

Stimuli with negative emotional valence are especially apt to influence perception and action because of their crucial role in survival, a property that may not be precisely mirrored by positive emotional stimuli of equal intensity. The aim of this study was to identify the neural circuits differentially coding for positive and negative valence in the implicit processing of facial expressions and words, which are among the main ways human beings use to express emotions. Thirty-six healthy subjects took part in an event-related fMRI experiment. We used an implicit emotional processing task with the visual presentation of negative, positive, and neutral faces and words, as primary stimuli. Dynamic Causal Modeling (DCM) of the fMRI data was used to test effective brain connectivity within two different anatomo-functional models, for the processing of words and faces, respectively. In our models, the only areas showing a significant differential response to negative and positive valence across both face and word stimuli were early visual cortices, with faces eliciting stronger activations. For faces, DCM revealed that this effect was mediated by a facilitation of activity in the amygdala by positive faces and in the fusiform face area by negative faces; for words, the effect was mainly imputable to a facilitation of activity in the primary visual cortex by positive words. These findings support a role of early sensory cortices in discriminating the emotional valence of both faces and words, where the effect may be mediated chiefly by the subcortical/limbic visual route for faces, and rely more on the direct thalamic pathway to primary visual cortex for words.

Successor-like representation guides the prediction of future events in human visual cortex and hippocampus.

Human agents build models of their environment, which enable them to anticipate and plan upcoming events. However, little is known about the properties of such predictive models. Recently, it has been proposed that hippocampal representations take the form of a predictive map-like structure, the so-called successor representation (SR). Here, we used human functional magnetic resonance imaging to probe whether activity in the early visual cortex (V1) and hippocampus adhere to the postulated properties of the SR after visual sequence learning. Participants were exposed to an arbitrary spatiotemporal sequence consisting of four items (A-B-C-D). We found that after repeated exposure to the sequence, merely presenting single sequence items (e.g., - B - -) resulted in V1 activation at the successor locations of the full sequence (e.g., C-D), but not at the predecessor locations (e.g., A). This highlights that visual representations are skewed toward future states, in line with the SR. Similar results were also found in the hippocampus. Moreover, the hippocampus developed a coactivation profile that showed sensitivity to the temporal distance in sequence space, with fading representations for sequence events in the more distant past and future. V1, in contrast, showed a coactivation profile that was only sensitive to spatial distance in stimulus space. Taken together, these results provide empirical evidence for the proposition that both visual and hippocampal cortex represent a predictive map of the visual world akin to the SR.

Assessing dynamic brain activity during verbal associative learning using MEG/fMRI co-processing

BackgroundThe abilities of individual neuroimaging methods to resolve spatial and temporal contributions of brain regions during cognitive processes are limited. Co-processing of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) may overcome some of the limitations by utilizing Multiple Sparse Priors (MSP) in a Bayesian framework that takes advantage of the temporal resolution of MEG and spatial resolution of fMRI. Methods24 healthy participants were recruited to perform a paired-associate verbal learning task during fMRI and MEG scans. FMRI data were processed within Group ICA fMRI Toolbox. Independent components (ICs) were temporally sorted by task time series (|r|>0.30 threshold identified task-related ICs). Task-positive (“generate”) ICs were retained as spatial priors for MEG analyses. MEG data were processed by an event-related potential (ERP) approach and with a theta power approach. MEG source reconstructions were constrained within the task-positive ICs for both ERP and theta-power approaches. ResultsFor fMRI, five networks were identified as task-related. Four ICs underlying active generation spanned bilateral parietal, orbitofrontal, medial frontal and superior temporal regions, and occipital lobe. FMRI-constrained MEG source reconstructions using the ERP approach yielded early visual cortex activity followed by left inferior frontal gyrus (IFG) and orbito-frontal cortex (OFC) recruitment to coalesce in the left inferior temporal lobe. For the theta approach, MEG source reconstructions showed a progression of activity from bilateral temporal areas to left OFC and middle temporal gyrus, followed by right IFG. DiscussionMSP analyses informed by fMRI produced more focused regional activity than reconstructions without priors suggesting this approach may result in identifying more relevant semantic information during active generation. Constraining MEG source reconstruction to fMRI priors during active generation indicates fronto-temporal and fronto-parietal networks are interconnected across time and space.

Visual-cortical enhancement by acoustic distractors: The effects of endogenous spatial attention and visual working memory load

Past work has shown that when a peripheral sound captures our attention, it activates the contralateral visual cortex as revealed by an event-related potential component labelled the auditory-evoked contralateral occipital positivity (ACOP). This cross-modal activation of the visual cortex has been observed even when the sounds were not relevant to the ongoing task (visual or auditory), suggesting that peripheral sounds automatically activate the visual cortex. However, it is unclear whether top-down factors such as visual working memory (VWM) load and endogenous attention, which modulate the impact of task-irrelevant information, may modulate this spatially-specific component. Here, we asked participants to perform a lateralized VWM task (change detection), whose performance is supported by both endogenous spatial attention and VWM storage. A peripheral sound that was unrelated to the ongoing task was delivered during the retention interval. The amplitude of sound-elicited ACOP was analyzed as a function of the spatial correspondence with the cued hemifield, and of the memory array set-size. The typical ACOP modulation was observed over parieto-occipital sites in the 280–500 ms time window after sound onset. Its amplitude was not affected by VWM load but was modulated when the location of the sound did not correspond to the hemifield (right or left) that was cued for the change detection task. Our results suggest that sound-elicited activation of visual cortices, as reflected in the ACOP modulation, is unaffected by visual working memory load. However, endogenous spatial attention affects the ACOP, challenging the hypothesis that it reflects an automatic process.

Learned value modulates the access to visual awareness during continuous flash suppression

Monetary value enhances visual perception and attention and boosts activity in the primary visual cortex, however, it is still unclear whether monetary value can modulate the conscious access to rewarding stimuli. Here we investigate this issue by employing a breaking continuous flash suppression (b-CFS) paradigm. We measured suppression durations of sinusoidal gratings having orthogonal orientations under CFS in adult volunteers before and after a short session of Pavlovian associative learning in which each orientation was arbitrarily associated either with high or low monetary reward. We found that monetary value accelerated the access to visual awareness during CFS. Specifically, after the associative learning, suppression durations of the visual stimulus associated with high monetary value were shorter compared to the visual stimulus associated with low monetary value. Critically, the effect was replicated in a second experiment using a detection task for b-CFS that was orthogonal to the reward associative learning. These results indicate that monetary reward facilitates the access to awareness of visual stimuli associated with monetary value probably by boosting their representation at the early stages of visual processing in the brain.

Behavioral origin of sound-evoked activity in mouse visual cortex

Sensory cortices can be affected by stimuli of multiple modalities and are thus increasingly thought to be multisensory. For instance, primary visual cortex (V1) is influenced not only by images but also by sounds. Here we show that the activity evoked by sounds in V1, measured with Neuropixels probes, is stereotyped across neurons and even across mice. It is independent of projections from auditory cortex and resembles activity evoked in the hippocampal formation, which receives little direct auditory input. Its low-dimensional nature starkly contrasts the high-dimensional code that V1 uses to represent images. Furthermore, this sound-evoked activity can be precisely predicted by small body movements that are elicited by each sound and are stereotyped across trials and mice. Thus, neural activity that is apparently multisensory may simply arise from low-dimensional signals associated with internal state and behavior.

Functional MRI study of feedback-based reinforcement learning in depression.

Reinforcement learning depends upon the integrity of emotional circuitry to establish associations between environmental cues, decisions, and positive or negative outcomes in order to guide behavior through experience. The emotional dysregulation characteristic of major depressive disorder (MDD) may alter activity in frontal and limbic structures that are key to learning. Although reward and decision-making have been examined in MDD, the effects of depression on associative learning is less well studied. We investigated whether depressive symptoms would be related to abnormalities in learning-related brain activity as measured by functional magnetic resonance imaging (fMRI). Also, we explored whether melancholic and atypical features were associated with altered brain activity. We conducted MRI scans on a 4T Varian MRI system in 10 individuals with MDD and 10 healthy subjects. We examined event-related brain activation during feedback-based learning task using Analysis of Functional NeuroImages (AFNI) for image processing and statistical analysis. We observed that MDD patients exhibited reduced activation in visual cortex but increased activation in cingulate and insular regions compared to healthy participants. Also, in relation to features of depressive subtypes, we observed that levels of activation in striatal, thalamic, and precuneus regions were negatively correlated with atypical characteristics. These results suggest that the effects of MDD change the neural circuitry underlying associative learning, and these effects may depend upon subtype features of MDD.