Identifying Brain Network Structure for an fMRI Effective Connectivity Study Using the Least Absolute Shrinkage and Selection Operator (LASSO) Method.

Background: Studying causality relationships between different brain regions using the fMRI method has attracted great attention. To investigate causality relationships between different brain regions, we need to identify both the brain network structure and the influence magnitude. Most current methods concentrate on magnitude estimation, but not on identifying the connection or structure of the network. To address this problem, we proposed a nonlinear system identification method, in which a polynomial kernel was adopted to approximate the relation between the system inputs and outputs. However, this method has an overfitting problem for modelling the input-output relation if we apply the method to model the brain network directly. Methods: To overcome this limitation, this study applied the least absolute shrinkage and selection operator (LASSO) model selection method to identify both brain region networks and the connection strength (system coefficients). From these coefficients, the causality influence is derived from the identified structure. The method was verified based on the human visual cortex with phase-encoded designs. The functional data were pre-processed with motion correction. The visual cortex brain regions were defined based on a retinotopic mapping method. An eight-connection visual system network was adopted to validate the method. The proposed method was able to identify both the connected visual networks and associated coefficients from the LASSO model selection. Results: The result showed that this method can be applied to identify both network structures and associated causalities between different brain regions. Conclusions: System identification with LASSO model selection algorithm is a powerful approach for fMRI effective connectivity study.

Protecting vision with intraoperative visual evoked potentials and tractography in transcortical brain tumor surgery.

Objective: Intraoperative neuromonitoring (IONM) is nowadays a gold standard during brain tumor resections, but visual function mapping is less frequently performed in clinical practice. This article aims to report two transcortical brain tumor surgery cases affecting optic radiation, where the application of intraoperative visual evoked potentials (VEP) combined with tractography was beneficial to protect the patients' vision. Methods: Two patients with brain tumors compressing the left posterior visual pathways underwent surgery under general anesthesia using IONM and VEP with neurologic improvement and preservation of vision. Results: VEP is beneficial in the surgery of intra-axial lesions affecting the posterior visual pathways (optic radiation, visual cortex) and parasellar lesions involving the anterior visual pathways (chiasm). They can also be effectively combined with other mapping methods such as tractography. Conclusions: According to our experience, IONM with VEPs and neuronavigation with tractography protect visual function in transcortical approaches to resecting tumors near the optic radiation and should be considered a standard monitoring method for such operations.

Reduced neurovascular coupling of the visual network in migraine patients with aura as revealed with arterial spin labeling MRI: is there a demand-supply mismatch behind the scenes?

BACKGROUND: Although neuroimaging investigations have consistently demonstrated that "hyperresponsive" and "hyperconnected" visual cortices may represent the functional substrate of cortical spreading depolarization in patients with migraine with aura, the mechanisms which underpin the brain "tendency" to ignite the cortical spreading depolarization and, consequently, aura phenomenon are still matter of debate. Considering that triggers able to induce aura phenomenon constrain brain to increase global (such as physical activity, stressors and sleep abnormalities) or local (such as bright light visual stimulations) energy demand, a vascular supply unable to satisfy the increased energy requirement could be hypothesized in these patients. METHODS: Twenty-three patients with migraine with aura, 25 patients with migraine without aura and 20 healthy controls underwent a 3-Tesla MRI study. Cerebral blood flow and local functional connectivity (regional homogeneity) maps were obtained and registered to the MNI space where 100 cortical regions were derived using a functional local-global normative parcellation. A surrogate estimate of the regional neurovascular coupling for each subject was obtained at each parcel from the correlation coefficient between the z-scored ReHo map and the z-scored cerebral blood flow maps. RESULTS: A significantly higher regional cerebral blood flow across the visual cortex of both hemispheres (i.e. fusiform and lingual gyri) was detected in migraine with aura patients when compared to patients with migraine without aura (p < 0.05, corrected for multiple comparisons). Concomitantly, a significantly reduced neurovascular coupling (p < 0.05, false discovery rate corrected) in the primary visual cortex parcel (VIS-4) of the large-scale visual network was observed in the left hemisphere of patients with migraine with aura (0.23±0.03), compared to both patients with migraine without aura (0.32±0.05) and healthy controls (0.29±0.05). CONCLUSIONS: Visual cortex neurovascular "decoupling" might represent the "link" between the exposure to trigger factors and aura phenomenon ignition. While physiological vascular oversupply may compensate neurovascular demand-supply at rest, it becomes inadequate in case of increased energy demand (e.g. when patients face with trigger factors) paving the way to the aura phenomenon ignition in patients with migraine with aura. Whether preventive treatments may exert their therapeutic activity on migraine with aura restoring the energy demands and cerebral blood flow trade-off within the visual network should be further investigated.

Age and visual cortex inhibition: a TMS-MRS study.

Paired-pulse transcranial magnetic stimulation is a valuable tool for investigating inhibitory mechanisms in motor cortex. We recently demonstrated its use in measuring cortical inhibition in visual cortex, using an approach in which participants trace the size of phosphenes elicited by stimulation to occipital cortex. Here, we investigate age-related differences in primary visual cortical inhibition and the relationship between primary visual cortical inhibition and local GABA+ in the same region, estimated using magnetic resonance spectroscopy. GABA+ was estimated in 28 young (18 to 28 years) and 47 older adults (65 to 84 years); a subset (19 young, 18 older) also completed a paired-pulse transcranial magnetic stimulation session, which assessed visual cortical inhibition. The paired-pulse transcranial magnetic stimulation measure of inhibition was significantly lower in older adults. Uncorrected GABA+ in primary visual cortex was also significantly lower in older adults, while measures of GABA+ that were corrected for the tissue composition of the magnetic resonance spectroscopy voxel were unchanged with age. Furthermore, paired-pulse transcranial magnetic stimulation-measured inhibition and magnetic resonance spectroscopy-measured tissue-corrected GABA+ were significantly positively correlated. These findings are consistent with an age-related decline in cortical inhibition in visual cortex and suggest paired-pulse transcranial magnetic stimulation effects in visual cortex are driven by GABAergic mechanisms, as has been demonstrated in motor cortex.

Graph-based cell pattern recognition for merging the multi-modal optical microscopic image of neurons.

A deep understanding of neuron structure and function is crucial for elucidating brain mechanisms, diagnosing and treating diseases. Optical microscopy, pivotal in neuroscience, illuminates neuronal shapes, projections, and electrical activities. To explore the projection of specific functional neurons, scientists have been developing optical-based multimodal imaging strategies to simultaneously capture dynamic in vivo signals and static ex vivo structures from the same neuron. However, the original position of neurons is highly susceptible to displacement during ex vivo imaging, presenting a significant challenge for integrating multimodal information at the single-neuron level. This study introduces a graph-model-based approach for cell image matching, facilitating precise and automated pairing of sparsely labeled neurons across different optical microscopic images. It has been shown that utilizing neuron distribution as a matching feature can mitigate modal differences, the high-order graph model can address scale inconsistency, and the nonlinear iteration can resolve discrepancies in neuron density. This strategy was applied to the connectivity study of the mouse visual cortex, performing cell matching between the two-photon calcium image and the HD-fMOST brain-wide anatomical image sets. Experimental results demonstrate 96.67% precision, 85.29% recall rate, and 90.63% F1 Score, comparable to expert technicians. This study builds a bridge between functional and structural imaging, offering crucial technical support for neuron classification and circuitry analysis.

Distinct neural pathway and its information flow for blind individual's Braille reading.

Natural Braille reading presents significant challenges to the brain networks of late blind individuals, yet its underlying neural mechanisms remain largely unexplored. Using natural Braille texts in behavioral assessments and functional MRI, we sought to pinpoint the neural pathway and information flow crucial for Braille reading performance in late blind individuals. In the resting state, we discovered a unique neural connection between the higher-order 'visual' cortex, the lateral occipital cortex (LOC), and the inferior frontal cortex (IFC) in late blind individuals, but not in sighted controls. The left-lateralized LOC-IFC connectivity was correlated with individual Braille reading proficiency. Prolonged Braille reading practice led to increased strength of this connectivity. During a natural Braille reading task, bidirectional information flow between the LOC and the IFC was positively modulated, with a predominantly stronger top-down modulation from the IFC to the LOC. This stronger top-down modulation contributed to higher Braille reading proficiency. We thus proposed a two-predictor multiple regression model to predict individual Braille reading proficiency, incorporating both static connectivity and dynamic top-down communication between the LOC-IFC link. This work highlights the dual contributions of the occipito-frontal neural pathway and top-down cognitive strategy to superior natural Braille reading performance, offering guidance for training late blind individuals.

Functional magnetic resonance imaging signal has sub-second temporal accuracy.

Neuronal activation sequence information is essential for understanding brain functions. Extracting such timing information from blood-oxygenation-level-dependent functional magnetic resonance imaging (fMRI) signals is confounded by local cerebral vascular reactivity (CVR), which varies across brain locations. Thus, detecting neuronal synchrony as well as inferring inter-regional causal modulation using fMRI signals can be biased. Here we used fast fMRI measurements sampled at 10 Hz to measure the fMRI latency difference between visual and sensorimotor areas when participants engaged in a visuomotor task. The regional fMRI timing was calibrated by subtracting the CVR latency measured by a breath-holding task. After CVR calibration, the fMRI signal at the lateral geniculate nucleus (LGN) preceded that at the visual cortex by 496 ms, followed by the fMRI signal at the sensorimotor cortex with a latency of 464 ms. Sequential LGN, visual, and sensorimotor cortex activations were found in each participant after the CVR calibration. These inter-regional fMRI timing differences across and within participants were more closely related to the reaction time after the CVR calibration. Our results suggested the feasibility of mapping brain activity using fMRI with accuracy in hundreds of milliseconds.

Double dissociation of visuomotor interaction mediated by visual feedback during continuous de novo motor learning.

While the sensorimotor cortices are central neural substrates for motor control and learning, how the interaction between their subregions with visual cortices contributes to acquiring de novo visuomotor skills is poorly understood. We design a continuous visuomotor task in fMRI where participants control a cursor using their fingers while learning an arbitrary finger-to-cursor mapping. To investigate visuomotor interaction in the de novo motor task, we manipulate visual feedback of a cursor such that they learn to control using fingers under two alternating conditions: online cursor feedback is available or unavailable except when a target is reached. As a result, we find double dissociation of fMRI activity in subregions of the sensorimotor and visual cortices. Specifically, motor and late visual cortices are more active with online cursor feedback, and somatosensory and early visual cortices are more active without online cursor feedback. We also find a significant reduction in functional connectivity between somatosensory cortices and early visual cortices, which is highly correlated with performance improvement. These findings support the distinct interaction between subregions of sensorimotor cortices and visual cortices, while the connectivity analysis highlights the critical role of somatosensory cortices during de novo motor learning.

A visual representation of the hand in the resting somatomotor regions of the human brain.

Hand visibility affects motor control, perception, and attention, as visual information is integrated into an internal model of somatomotor control. Spontaneous brain activity, i.e., at rest, in the absence of an active task, is correlated among somatomotor regions that are jointly activated during motor tasks. Recent studies suggest that spontaneous activity patterns not only replay task activation patterns but also maintain a model of the body's and environment's statistical regularities (priors), which may be used to predict upcoming behavior. Here, we test whether spontaneous activity in the human somatomotor cortex as measured using fMRI is modulated by visual stimuli that display hands vs. non-hand stimuli and by the use/action they represent. A multivariate pattern analysis was performed to examine the similarity between spontaneous activity patterns and task-evoked patterns to the presentation of natural hands, robot hands, gloves, or control stimuli (food). In the left somatomotor cortex, we observed a stronger (multivoxel) spatial correlation between resting state activity and natural hand picture patterns compared to other stimuli. No task-rest similarity was found in the visual cortex. Spontaneous activity patterns in somatomotor brain regions code for the visual representation of human hands and their use.

Evaluation of potential alterations related to ADHD in the effective connectivity between the default mode network and cerebellum, hippocampus, thalamus, and primary visual cortex.

Hyperactivity in children with attention-deficit/hyperactivity disorder (ADHD) leads to restlessness and impulse-control impairments. Nevertheless, the relation between ADHD symptoms and brain regions interactions remains unclear. We focused on dynamic causal modeling to study the effective connectivity in a fully connected network comprised of four regions of the default mode network (DMN) (linked to response control behaviors) and four other regions with previously-reported structural alterations due to ADHD. Then, via the parametric empirical Bayes analysis, the most significant connections, with the highest correlation to the covariates ADHD/control, age, and sex were extracted. Our results demonstrated a positive correlation between ADHD and effective connectivity between the right cerebellum and three DMN nodes (intrinsically inhibitory connections). Therefore, an increase in the effective connectivity leads to more inhibition imposition from the right cerebellum to DMN that reduces this network activation. The lower DMN activity makes leaving the resting-state easier, which may be involved in the restlessness symptom. Furthermore, our results indicated a negative correlation between age and these connections. We showed that the difference between the average of effective connectivities of ADHD and control groups in the age-range of 7-11 years disappeared after 14 years-old. Therefore, aging tends to alleviate ADHD-specific symptoms.

Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields.

When multiple visual stimuli are presented simultaneously in the receptive field, the neural response is suppressed compared to presenting the same stimuli sequentially. The prevailing hypothesis suggests that this suppression is due to competition among multiple stimuli for limited resources within receptive fields, governed by task demands. However, it is unknown how stimulus-driven computations may give rise to simultaneous suppression. Using fMRI, we find simultaneous suppression in single voxels, which varies with both stimulus size and timing, and progressively increases up the visual hierarchy. Using population receptive field (pRF) models, we find that compressive spatiotemporal summation rather than compressive spatial summation predicts simultaneous suppression, and that increased simultaneous suppression is linked to larger pRF sizes and stronger compressive nonlinearities. These results necessitate a rethinking of simultaneous suppression as the outcome of stimulus-driven compressive spatiotemporal computations within pRFs, and open new opportunities to study visual processing capacity across space and time.

A concentration of visual cortex-like neurons in prefrontal cortex.

Visual recognition is largely realized through neurons in the ventral stream, though recently, studies have suggested that ventrolateral prefrontal cortex (vlPFC) is also important for visual processing. While it is hypothesized that sensory and cognitive processes are integrated in vlPFC neurons, it is not clear how this mechanism benefits vision, or even if vlPFC neurons have properties essential for computations in visual cortex implemented via recurrence. Here, we investigated if vlPFC neurons in two male monkeys had functions comparable to visual cortex, including receptive fields, image selectivity, and the capacity to synthesize highly activating stimuli using generative networks. We found a subset of vlPFC sites show all properties, suggesting subpopulations of vlPFC neurons encode statistics about the world. Further, these vlPFC sites may be anatomically clustered, consistent with fMRI-identified functional organization. Our findings suggest that stable visual encoding in vlPFC may be a necessary condition for local and brain-wide computations.

Sub-bundle based analysis reveals the role of human optic radiation in visual working memory.

White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function.

A ventromedial visual cortical 'Where' stream to the human hippocampus for spatial scenes revealed with magnetoencephalography.

The primate including the human hippocampus implicated in episodic memory and navigation represents a spatial view, very different from the place representations in rodents. To understand this system in humans, and the computations performed, the pathway for this spatial view information to reach the hippocampus was analysed in humans. Whole-brain effective connectivity was measured with magnetoencephalography between 30 visual cortical regions and 150 other cortical regions using the HCP-MMP1 atlas in 21 participants while performing a 0-back scene memory task. In a ventromedial visual stream, V1-V4 connect to the ProStriate region where the retrosplenial scene area is located. The ProStriate region has connectivity to ventromedial visual regions VMV1-3 and VVC. These ventromedial regions connect to the medial parahippocampal region PHA1-3, which, with the VMV regions, include the parahippocampal scene area. The medial parahippocampal regions have effective connectivity to the entorhinal cortex, perirhinal cortex, and hippocampus. In contrast, when viewing faces, the effective connectivity was more through a ventrolateral visual cortical stream via the fusiform face cortex to the inferior temporal visual cortex regions TE2p and TE2a. A ventromedial visual cortical 'Where' stream to the hippocampus for spatial scenes was supported by diffusion topography in 171 HCP participants at 7 T.

Predictions enable top-down pattern separation in the macaque face-processing hierarchy.

Distinguishing faces requires well distinguishable neural activity patterns. Contextual information may separate neural representations, leading to enhanced identity recognition. Here, we use functional magnetic resonance imaging to investigate how predictions derived from contextual information affect the separability of neural activity patterns in the macaque face-processing system, a 3-level processing hierarchy in ventral visual cortex. We find that in the presence of predictions, early stages of this hierarchy exhibit well separable and high-dimensional neural geometries resembling those at the top of the hierarchy. This is accompanied by a systematic shift of tuning properties from higher to lower areas, endowing lower areas with higher-order, invariant representations instead of their feedforward tuning properties. Thus, top-down signals dynamically transform neural representations of faces into separable and high-dimensional neural geometries. Our results provide evidence how predictive context transforms flexible representational spaces to optimally use the computational resources provided by cortical processing hierarchies for better and faster distinction of facial identities.

Retinal Damage and Visual Network Reconfiguration Defines Visual Function Recovery in Optic Neuritis.

BACKGROUND AND OBJECTIVES: Recovery of vision after acute optic neuritis (AON) is critical to improving the quality of life of people with demyelinating diseases. The objective of the study was to prospectively assess the changes in visual acuity, retinal layer thickness, and cortical visual network in patients with AON to identify the predictors of permanent visual disability. METHODS: We studied a prospective cohort of 88 consecutive patients with AON with 6-month follow-up using high and low-contrast (2.5%) visual acuity, color vision, retinal thickness from optical coherence tomography, latencies and amplitudes of multifocal visual evoked potentials, mean deviation of visual fields, and diffusion-based structural (n = 53) and functional (n = 19) brain MRI to analyze the cortical visual network. The primary outcome was 2.5% low-contrast vision, and data were analyzed with mixed-effects and multivariate regression models. RESULTS: We found that after 6 months, low-contrast vision and quality of vision remained moderately impaired. The thickness of the ganglion cell layer at baseline was a predictor of low-contrast vision 6 months later (ß = 0.49 [CI 0.11-0.88], p = 0.012). The structural cortical visual network at baseline predicted low-contrast vision, the best predictors being the betweenness of the right parahippocampal cortex (ß = -036 [CI -0.66 to 0.06], p = 0.021), the node strength of the right V3 (ß = 1.72 [CI 0.29-3.15], p = 0.02), and the clustering coefficient of the left intraparietal sulcus (ß = 57.8 [CI 12.3-103.4], p = 0.015). The functional cortical visual network at baseline also predicted low-contrast vision, the best predictors being the betweenness of the left ventral occipital cortex (ß = 8.6 [CI: 4.03-13.3], p = 0.009), the node strength of the right intraparietal sulcus (ß = -2.79 [CI: -5.1-0.4], p = 0.03), and the clustering coefficient of the left superior parietal lobule (ß = 501.5 [CI 50.8-952.2], p = 0.03). DISCUSSION: The assessment of the visual pathway at baseline predicts permanent vision disability after AON, indicating that damage is produced early after disease onset and that it can be used for defining vision impairment and guiding therapy.

Beyond primary visual cortex: The leading role of lateral occipital complex in early conscious visual processing.

The study of the neural substrates that serve conscious vision is one of the unsolved questions of cognitive neuroscience. So far, consciousness literature has endeavoured to disentangle which brain areas and in what order are involved in giving rise to visual awareness, but the problem of consciousness still remains unsolved. Availing of two different but complementary sources of data (i.e., Fast Optical Imaging and EEG), we sought to unravel the neural dynamics responsible for the emergence of a conscious visual experience. Our results revealed that conscious vision is characterized by a significant increase of activation in extra-striate visual areas, specifically in the Lateral Occipital Complex (LOC), and that, more interestingly, such activity occurred in the temporal window of the ERP component commonly thought to represent the electrophysiological signature of visual awareness, i.e., the Visual Awareness Negativity (VAN). Furthermore, Granger causality analysis, performed to further investigate the flow of activity occurring in the investigated areas, unveiled that neural processes relating to conscious perception mainly originated in LOC and subsequently spread towards visual and motor areas. In general, the results of the present study seem to advocate for an early contribution of LOC in conscious vision, thus suggesting that it could represent a reliable neural correlate of visual awareness. Conversely, striate visual areas, showing awareness-related activity only in later stages of stimulus processing, could be part of the cascade of neural events following awareness emergence.

Pupil-Linked Arousal Modulates Precision of Stimulus Representation in Cortex.

Neural responses are naturally variable from one moment to the next, even when the stimulus is held constant. What factors might underlie this variability in neural population activity? We hypothesized that spontaneous fluctuations in cortical stimulus representations are created by changes in arousal state. We tested the hypothesis using a combination of fMRI, probabilistic decoding methods, and pupillometry. Human participants (20 female, 12 male) were presented with gratings of random orientation. Shortly after viewing the grating, participants reported its orientation and gave their level of confidence in this judgment. Using a probabilistic fMRI decoding technique, we quantified the precision of the stimulus representation in the visual cortex on a trial-by-trial basis. Pupil size was recorded and analyzed to index the observer's arousal state. We found that the precision of the cortical stimulus representation, reported confidence, and variability in the behavioral orientation judgments varied from trial to trial. Interestingly, these trial-by-trial changes in cortical and behavioral precision and confidence were linked to pupil size and its temporal rate of change. Specifically, when the cortical stimulus representation was more precise, the pupil dilated more strongly prior to stimulus onset and remained larger during stimulus presentation. Similarly, stronger pupil dilation during stimulus presentation was associated with higher levels of subjective confidence, a secondary measure of sensory precision, as well as improved behavioral performance. Taken together, our findings support the hypothesis that spontaneous fluctuations in arousal state modulate the fidelity of the stimulus representation in the human visual cortex, with clear consequences for behavior.

Orientation selectivity mapping in the visual cortex.

The orientation map is one of the most well-studied functional maps of the visual cortex. However, results from the literature are of different qualities. Clear boundaries among different orientation domains and blurred uncertain distinctions were shown in different studies. These unclear imaging results will lead to an inaccuracy in depicting cortical structures, and the lack of consideration in experimental design will also lead to biased depictions of the cortical features. How we accurately define orientation domains will impact the entire field of research. In this study, we test how spatial frequency (SF), stimulus size, location, chromatic, and data processing methods affect the orientation functional maps (including a large area of dorsal V4, and parts of dorsal V1) acquired by intrinsic signal optical imaging. Our results indicate that, for large imaging fields, large grating stimuli with mixed SF components should be considered to acquire the orientation map. A diffusion model image enhancement based on the difference map could further improve the map quality. In addition, the similar outcomes of achromatic and chromatic gratings indicate two alternative types of afferents from LGN, pooling in V1 to generate cue-invariant orientation selectivity.

Mixing novel and familiar cues modifies representations of familiar visual images and affects behavior.

While visual responses to familiar and novel stimuli have been extensively studied, it is unknown how neuronal representations of familiar stimuli are affected when they are interleaved with novel images. We examined a large-scale dataset from mice performing a visual go/no-go change detection task. After training with eight images, six novel images were interleaved with two familiar ones. Unexpectedly, we found that the behavioral performance in response to familiar images was impaired when they were mixed with novel images. When familiar images were interleaved with novel ones, the dimensionality of their representation increased, indicating a perturbation of their neuronal responses. Furthermore, responses to familiar images in the primary visual cortex were less predictive of responses in higher-order areas, indicating less efficient communication. Spontaneous correlations between neurons were predictive of responses to novel images, but less so to familiar ones. Our study demonstrates the modification of representations of familiar images by novelty.