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Developmental myelination is a protracted process in the mammalian brain1. One theory for why oligodendrocytes mature so slowly posits that myelination may stabilize neuronal circuits and temper neuronal plasticity as animals age2-4. We tested this theory in the visual cortex, which has a well-defined critical period for experience-dependent neuronal plasticity5. During adolescence, visual experience modulated the rate of oligodendrocyte maturation in visual cortex. To determine whether oligodendrocyte maturation in turn regulates neuronal plasticity, we genetically blocked oligodendrocyte differentiation and myelination in adolescent mice. In adult mice lacking adolescent oligodendrogenesis, a brief period of monocular deprivation led to a significant decrease in visual cortex responses to the deprived eye, reminiscent of the plasticity normally restricted to adolescence. This enhanced functional plasticity was accompanied by a greater turnover of dendritic spines and coordinated reductions in spine size following deprivation. Furthermore, inhibitory synaptic transmission, which gates experience-dependent plasticity at the circuit level, was diminished in the absence of adolescent oligodendrogenesis. These results establish a critical role for oligodendrocytes in shaping the maturation and stabilization of cortical circuits and support the concept of developmental myelination acting as a functional brake on neuronal plasticity.

Humans are immensely curious and motivated to reduce uncertainty, but little is known about the neural mechanisms that generate curiosity. Curiosity is inversely associated with confidence, suggesting that it is triggered by states of low confidence (subjective uncertainty), but the neural mechanisms of this link, have been little investigated. Inspired by studies of sensory uncertainty, we hypothesized that visual areas provide multivariate representations of uncertainty, which are read out by higher-order structures to generate signals of confidence and, ultimately, curiosity. We scanned participants (17 female, 15 male) using fMRI while they performed a new task in which they rated their confidence in identifying distorted images of animals and objects and their curiosity to see the clear image. We measured the activity evoked by each image in the occipitotemporal cortex (OTC) and devised a new metric of "OTC Certainty" indicating the strength of evidence this activity conveys about the animal versus object categories. We show that, perceptual curiosity peaked at low confidence and OTC Certainty negatively correlated with curiosity, establishing a link between curiosity and a multivariate representation of sensory uncertainty. Moreover, univariate (average) activity in two frontal areas-vmPFC and ACC-correlated positively with confidence and negatively with curiosity, and the vmPFC mediated the relationship between OTC Certainty and curiosity. The results reveal novel mechanisms through which uncertainty about an event generates curiosity about that event.

Attention supports decision making by selecting the features that are relevant for decisions. Selective enhancement of the relevant features and inhibition of distractors has been proposed as potential neural mechanisms driving this selection process. Yet, how attention operates when relevance cannot be directly determined, and the attention signal needs to be internally constructed is less understood. Here we recorded from populations of neurons in the anterior cingulate cortex (ACC) of mice in an attention-shifting task where relevance of stimulus modalities changed across blocks of trials. In contrast with V1 recordings, decoding of the irrelevant modality gradually declined in ACC after an initial transient. Our analytical proof and a recurrent neural network model of the task revealed mutually inhibiting connections that produced context-gated suppression as observed in mice. Using this RNN model we predicted a correlation between contextual modulation of individual neurons and their stimulus drive, which we confirmed in ACC but not in V1.

This study aimed to investigate the impact of eccentric-vision training on population receptive field (pRF) estimates to provide insights into brain plasticity processes driven by practice. Fifteen participants underwent functional magnetic resonance imaging (fMRI) measurements before and after behavioral training on a visual crowding task, where the relative orientation of the opening (gap position: up/down, left/right) in a Landolt C optotype had to be discriminated in the presence of flanking ring stimuli. Drifting checkerboard bar stimuli were used for pRF size estimation in multiple regions of interest (ROIs): dorsal-V1 (dV1), dorsal-V2 (dV2), ventral-V1 (vV1), and ventral-V2 (vV2), including the visual cortex region corresponding to the trained retinal location. pRF estimates in V1 and V2 were obtained along eccentricities from 0.5° to 9°. Statistical analyses revealed a significant decrease of the crowding anisotropy index (p = 0.009) after training, indicating improvement on crowding task performance following training. Notably, pRF sizes at and near the trained location decreased significantly (p = 0.005). Dorsal and ventral V2 exhibited significant pRF size reductions, especially at eccentricities where the training stimuli were presented (p < 0.001). In contrast, no significant changes in pRF estimates were found in either vV1 (p = 0.181) or dV1 (p = 0.055) voxels. These findings suggest that practice on a crowding task can lead to a reduction of pRF sizes in trained visual cortex, particularly in V2, highlighting the plasticity and adaptability of the adult visual system induced by prolonged training.

First-order thalamic nuclei receive feedforward signals from peripheral receptors and relay these signals to primary sensory cortex. Primary sensory cortex, in turn, provides reciprocal feedback to first-order thalamus. Because the vast majority of sensory thalamocortical inputs target primary sensory cortex, their complementary corticothalamic neurons are assumed to be similarly restricted to primary sensory cortex. We upend this assumption by characterizing morphologically diverse neurons in multiple mid-level visual cortical areas of the primate (Macaca mulatta) brain that provide direct feedback to the primary visual thalamus, the dorsal lateral geniculate nucleus (LGN). Although the majority of geniculocortical neurons project to primary visual cortex (V1), a minority, located mainly in the koniocellular LGN layers, provide direct input to extrastriate visual cortex. These "V1-bypassing" projections may be implicated in blindsight. We hypothesized that geniculocortical inputs directly targeting extrastriate cortex should be complemented by reciprocal corticogeniculate circuits. Using virus-mediated circuit tracing, we discovered corticogeniculate neurons throughout three mid-level extrastriate areas: MT, MST, and V4. Quantitative morphological analyses revealed nonuniform distributions of unique cell types across areas. Many extrastriate corticogeniculate neurons had spiny stellate morphology, suggesting possible targeting of koniocellular LGN layers. Importantly though, multiple morphological types were observed across areas. Such morphological diversity could suggest parallel streams of V1-bypassing corticogeniculate feedback at multiple stages of the visual processing hierarchy. Furthermore, the presence of corticogeniculate neurons across visual cortex necessitates a reevaluation of the LGN as a hub for visual information rather than a simple relay.

The retina and primary visual cortex (V1) both exhibit diverse neural populations sensitive to diverse visual features. Yet it remains unclear how neural populations in each area partition stimulus space to span these features. One possibility is that neural populations are organized into discrete groups of neurons, with each group signaling a particular constellation of features. Alternatively, neurons could be continuously distributed across feature-encoding space. To distinguish these possibilities, we presented a battery of visual stimuli to the mouse retina and V1 while measuring neural responses with multi-electrode arrays. Using machine learning approaches, we developed a manifold embedding technique that captures how neural populations partition feature space and how visual responses correlate with physiological and anatomical properties of individual neurons. We show that retinal populations discretely encode features, while V1 populations provide a more continuous representation. Applying the same analysis approach to convolutional neural networks that model visual processing, we demonstrate that they partition features much more similarly to the retina, indicating they are more like big retinas than little brains.

Primary visual cortex (V1) has been the focus of extensive neurophysiological investigations, with its laminar organization serving as a crucial model for understanding the functional logic of neocortical microcircuits. Utilizing newly developed high-density, Neuropixels probes, we measured visual responses from large populations of simultaneously recorded neurons distributed across layers of macaque V1. Within single recordings, myriad differences in the functional properties of neuronal subpopulations could be observed. Notably, while standard measurements of orientation selectivity showed only minor differences between laminar compartments, decoding stimulus orientation from layer 4C responses outperformed both superficial and deep layers within the same cortical column. The superior orientation discrimination within layer 4C was associated with greater response reliability of individual neurons rather than lower correlated activity within neuronal populations. Our results underscore the efficacy of high-density electrophysiology in revealing the functional organization and network properties of neocortical microcircuits within single experiments.

Our previous studies find that subcutaneously administered (s.c.) subanesthetic ketamine promotes sustained cortical disinhibition and plasticity in adult mouse binocular visual cortex (bV1). We hypothesized that intranasal delivery (i.n.) of subanesthetic ketamine may have similar actions. To test this, we delivered ketamine (10 mg/kg, i.n.) to adult mice and then recorded excitatory pyramidal neurons or PV+ interneurons in L2/3 of bV1 slices. In pyramidal neurons the baseline IPSC amplitudes from mice treated with ketamine are significantly weaker than those in control mice. Acute bath application of neuregulin-1 (NRG1) to cortical slices increases these IPSC amplitudes in mice treated with ketamine but not in controls. In PV+ interneurons, the baseline EPSC amplitudes from mice treated with ketamine are significantly weaker than those in control mice. Acute bath application of NRG1 to cortical slices increases these EPSC amplitudes in mice treated with ketamine but not in controls. We also found that mice treated with ketamine exhibit increased pCREB staining in L2/3 of bV1. Together, our results show that a single intranasal delivery of ketamine reduces PV+ interneuron excitation and reduces pyramidal neuron inhibition and that these effects are acutely reversed by NRG1. These results are significant as they show that intranasal delivery of ketamine induces cortical disinhibition, which has implications for the treatment of psychiatric, neurologic, and ophthalmic disorders.

BackgroundMethodResultsConclusionHigher levels of brain-derived neurotrophic factor (BDNF) have been associated with better neurocognitive outcomes. BDNF is present in cardiovascular tissue, and some evidence suggests it may benefit cardiovascular function. The current study assessed whether there is a mediating and/or moderating role of cardiovascular health in the relationship between BDNF and brain and cognitive outcomes.We examined longitudinal data from 397 older adults (aged 54–89;164 females, 233 males) enrolled in the Alzheimer’s Disease Neuroimaging Initiative with available plasma BDNF, medical, neuroimaging, and cognitive assessments. We used path analysis and linear regression to estimate the mediating and moderating roles of two measures of cardiovascular health, the Framingham Risk Score (FRS) and pulse pressure, in the relationships between BDNF and longitudinal changes in brain structure (white matter hyperintensity volume, hippocampal volume, and primary visual cortex volume) and cognitive function (executive function, episodic memory, and language).There was no significant association of plasma BDNF with FRS or pulse pressure (ps > 0.31), precluding mediation. There were no robust associations between BDNF and longitudinal change in any brain structural or cognitive measures (ps > .12). Higher FRS was significantly associated with greater increases in WMH volume (ps < .01). FRS and pulse pressure were not associated with any other brain structural or cognitive outcomes (ps > .07).These results suggest that cardiovascular health may not play an important role in the influence of BDNF on neurocognitive health in older adults. [ABSTRACT FROM AUTHOR]

Functional maturation of the visual cortex is induced by visual experiences during critical periods. Blind animals and humans exhibit improved auditory abilities after losing their vision. Here we investigated the response of the visual cortex to white noise stimuli during the progression of photoreceptor degeneration in a rat model of blindness (Royal College of Surgeons [RCS] (rdy/rdy) rats). Optical coherence tomography of RCS (+/+) rats with normal visual function revealed normal photoreceptor cells, whereas 3-month-old RCS (rdy/rdy) rats demonstrated photoreceptor cell degeneration. Visual cortex responses (VCRs) to a single flash stimulus were negligible in 3-month-old photoreceptor-degenerated rats. However, VCRs with white noise stimuli were significantly increased in blind versus RCS rats (+/+). Slight changes in the intrinsic optical signals of the control rats were observed on the ventral side of the visual cortex. In contrast, responses were markedly increased throughout the visual cortex of RCS (rdy/rdy) rats. These results indicate that the visual cortex rapidly acquires auditory system function over the first 3 months of life and that the entire visual cortex, rather than just the portion close to the auditory cortex, responds to white noise. [ABSTRACT FROM AUTHOR]

Selective attention relies on neural mechanisms that facilitate processing of behaviorally relevant sensory information while suppressing irrelevant information, consistently linked to alpha-band oscillations in human M/EEG studies. We analyzed cortical alpha responses from intracranial electrodes implanted in eight epilepsy patients, who performed a visual spatial attention task. Electrocorticographic data revealed a spatiotemporal dissociation between attention-modulated alpha desynchronization, associated with the enhancement of sensory processing, and alpha synchronization, associated with the suppression of sensory processing, during the cue-target interval. Dorsal intraparietal areas contralateral to the attended hemifield primarily exhibited a delayed and sustained alpha desynchronization, while ventrolateral extrastriatal areas ipsilateral to the attended hemifield primarily exhibited an earlier and sustained alpha synchronization. Analyses of cross-frequency coupling between alpha phase and broadband high-frequency activity (HFA) further revealed cross-frequency interactions along the visual hierarchy contralateral to the attended locations. Directionality analyses indicate that alpha phase in early and extrastriatal visual areas modulated HFA power in downstream visual areas, thus potentially facilitating the feedforward processing of an upcoming, spatially predictable target. In contrast, in areas ipsilateral to the attended locations, HFA power modulated local alpha phase in early and extrastriatal visual areas, with suppressed interareal interactions, potentially attenuating the processing of distractors. Our findings reveal divergent alpha-mediated neural mechanisms underlying target enhancement and distractor suppression during the deployment of spatial attention, reflecting enhanced functional connectivity at attended locations, while suppressed functional connectivity at unattended locations. The collective dynamics of these alpha-mediated neural mechanisms play complementary roles in the efficient gating of sensory information. [ABSTRACT FROM AUTHOR]

The contemporary definition of mental imagery is characterized by two aspects: a sensory representation that resembles, but does not result from, perception, and an associated subjective experience. Neuroimaging demonstrated imagery-related sensory representations in primary visual cortex (V1) that show striking parallels to perception. However, it remains unclear whether these representations always reflect subjective experience or if they can be dissociated from it. We addressed this question by comparing sensory representations and subjective imagery among visualizers and aphantasics, the latter with an impaired ability to experience imagery. Importantly, to test for the presence of sensory representations independently of the ability to generate imagery on demand , we examined both spontaneous and voluntary imagery forms. Using multivariate fMRI, we tested for decodable sensory representations in V1 and subjective visual imagery reports that occurred either spontaneously (during passive listening of evocative sounds) or in response to the instruction to voluntarily generate imagery of the sound content (always while blindfolded inside the scanner). Among aphantasics, V1 decoding of sound content was at chance during voluntary imagery, and lower than in visualizers, but it succeeded during passive listening, despite them reporting no imagery. In contrast, in visualizers, decoding accuracy in V1 was greater in voluntary than spontaneous imagery (while being positively associated with the reported vividness of both imagery types). Finally, for both conditions, decoding in precuneus was successful in visualizers but at chance for aphantasics. Together, our findings show that V1 representations can be dissociated from subjective imagery, while implicating a key role of precuneus in the latter. • A novel paradigm was used to elicit spontaneous and voluntary imagery using sounds • V1 representations of sounds were found in aphantasics despite subjective imagery absence • Aphantasics and visualizers differed in V1 for voluntary but not for spontaneous imagery • Precuneus emerged as higher-level correlate of subjective imagery presence Cabbai et al. test whether sensory representations in primary visual cortex (V1) can be dissociated from subjective mental imagery. They find that V1 representations can occur without subjective experience in aphantasics during a task designed to elicit spontaneous imagery. Their findings also implicate precuneus in conscious imagery experience. [ABSTRACT FROM AUTHOR]

For the brain to compute object motion in the world during self-motion, it must discount the global patterns of image motion (optic flow) caused by self-motion. Optic flow parsing is a proposed visual mechanism for computing object motion in the world, and studies in both humans and monkeys have demonstrated perceptual biases consistent with the operation of a flow-parsing mechanism. However, the neural basis of flow parsing remains unknown. We demonstrate, at both the individual unit and population levels, that neural activity in macaque middle temporal (MT) area is biased by peripheral optic flow in a manner that can at least partially account for perceptual biases induced by flow parsing. These effects cannot be explained by conventional surround suppression mechanisms or choice-related activity and have substantial neural latency. Together, our findings establish the first neural basis for the computation of scene-relative object motion based on flow parsing. [Display omitted] • Perception of the direction of visual motion is biased by background optic flow • Neural responses in area MT are modulated, with a delay, by background optic flow • Decoding population responses from area MT partially accounts for behavioral biases • Neural correlates of flow parsing cannot be explained by choice-related activity Peltier et al. demonstrate a neural basis for optic flow parsing in macaque middle temporal (MT) area. Flow parsing is a mechanism by which the brain discounts self-motion to compute object motion in the world. The responses of MT neurons are modulated by optic flow in a manner that at least partially accounts for behavioral biases associated with flow parsing. [ABSTRACT FROM AUTHOR]

Schemas allow us to make assumptions about the world based upon previous experiences and aid in memory organisation and retrieval. However, a reliance on schemas may also result in increased false memories to schematically related lures. Prior neuroimaging work has linked schematic processing in memory tasks to activity in prefrontal, visual, and temporal regions. Yet, it is unclear what type of processing in these regions underlies memory errors. The current study examined where schematic lures exhibit greater neural similarity to schematic targets, leading to this memory error, as compared to neural overlap with non-schematic lures, which, like schematic lures, are novel items at retrieval. Results showed that patterns of neural activity in ventromedial prefrontal cortex, medial frontal gyrus, middle temporal gyrus, hippocampus, and occipital cortices exhibited greater neural pattern similarity for schematic targets and schematic lures than between schematic lures and non-schematic lures. As such, results suggest that schematic membership, and not object history, may be more critical to the neural processes underlying memory retrieval in the context of a strong schema. [ABSTRACT FROM AUTHOR]

Endogenous shifts of spatial attention toward an upcoming stimulus are associated with improvements in behavioral responses to the stimulus, preparatory retinotopic shifts in alpha power, and changes in ERPs. Although attentional modulation of several early sensory ERPs is well established, there is still debate about under what circumstances attention affects the earliest cortical visual evoked response—the C1 ERP component—which is putatively generated from afferent input into primary visual cortex. Moreover, the effects of spatial attention on the recently discovered ERP signature of evidence accumulation—the central parietal positivity (CPP)—have not been fully characterized. The present study assessed the effect of spatial attention on the C1 and CPP components through a spatially cued contrast discrimination task using stimuli that were specifically designed to produce large-amplitude C1 responses and that varied in sensory evidence strength to characterize the CPP. Participants responded according to which of two checkerboard stimuli had greater contrast following an 80% valid cue toward the upper or lower visual field. Prestimulus alpha power changed topographically based on the cue, suggesting participants shifted attention to prepare for the upcoming stimuli. Despite these attentional shifts in alpha power and the fact that the stimuli reliably elicited C1 responses several times greater than many prior studies, there was no evidence of an attention effect on the C1. The CPP, however, showed a clear increase in build-up rate on valid trials. Our findings suggest that endogenous attention may not affect the early C1 ERP component but may improve behavior at a decision stage, as reflected in brain signals related to evidence accumulation (the CPP). [ABSTRACT FROM AUTHOR]

Deep convolutional neural networks (DCNNs) have attained human-level performance for object categorization and exhibited representation alignment between network layers and brain regions. Does such representation alignment naturally extend to other visual tasks beyond recognizing objects in static images? In this study, we expanded the exploration to the recognition of human actions from videos and assessed the representation capabilities and alignment of two-stream DCNNs in comparison with brain regions situated along ventral and dorsal pathways. Using decoding analysis and representational similarity analysis, we show that DCNN models do not show hierarchical representation alignment to human brain across visual regions when processing action videos. Instead, later layers of DCNN models demonstrate greater representation similarities to the human visual cortex. These findings were revealed for two display formats: photorealistic avatars with full-body information and simplified stimuli in the point-light display. The discrepancies in representation alignment suggest fundamental differences in how DCNNs and the human brain represent dynamic visual information related to actions. [ABSTRACT FROM AUTHOR]

Background: In this study, we used electroencephalogram (EEG) to investigate the activity pattern of the cerebral cortex related to visual pursuit and saccade strategies to predict the arrival position of a visual target. In addition, we clarified the differences in the EEG of those who could predict the arrival position well using the saccade strategy compared to those who were not proficient. Methods: Sixteen participants performed two tasks: the "Pursuit Strategy Task (PST)" and the "Saccade Strategy Task (SST)" while undergoing EEG. For the PST, the participants were instructed to follow the target with their eyes throughout its trajectory and indicate when it reached the final point. For the SST, the participants were instructed to shift their gaze to the end point of arrival once they had predicted it. Results: Low beta EEG activity at the Oz, Cz, and CP2 electrodes was significantly higher during the SST than during the PST. In addition, low beta EEG activity at P7 electrode was significantly higher in the group showing a small position error (PE) than in the group showing a large PE at response. Conclusions: EEG activity at the Oz, Cz, and CP2 electrodes during the SST may reflect visuospatial attention to the moving target, the tracking of moving targets, and the focus on the final destination position. In addition, EEG activity at P7 electrode may more accurately detect the speed and direction of the moving target by the small PE group at response. [ABSTRACT FROM AUTHOR]

Improving the efficiency of current neural networks and modeling them on biological neural systems have become prominent research directions in recent years. The pulse-coupled neural network (PCNN) is widely used to mimic the computational characteristics of the human brain in computer vision and neural network fields. However, PCNN faces limitations such as limited neural connections, high computational costs, and a lack of stochastic properties. This study proposes a random-coupled neural network (RCNN) to address these limitations. RCNN employs a stochastic inactivation process, selectively inactivating neural connections using a random inactivation weight matrix. This method reduces the computational burden and allows for extensive neural connections. RCNN encodes constant stimuli as periodic spike trains and periodic stimuli as chaotic spike trains, reflecting the information encoding characteristics of biological neural systems. Our experiments applied RCNN to image segmentation and fusion tasks, demonstrating its robustness, efficiency, and high noise resistance. Results indicate that RCNN surpasses traditional methods in performance across these applications. [ABSTRACT FROM AUTHOR]

Purpose: To develop and demonstrate a fast 3D fMRI acquisition technique with high spatial resolution over a reduced FOV, named k‐t 3D reduced FOV imaging (3D‐rFOVI). Methods: Based on 3D gradient‐echo EPI, k‐t 3D‐rFOVI used a 2D RF pulse to reduce the FOV in the in‐plane phase‐encoding direction, boosting spatial resolution without increasing echo train length. For image acceleration, full sampling was applied in the central k‐space region along the through‐slab direction (kz) for all time frames, while randomized undersampling was used in outer kz regions at different time frames. Images were acquired at 3T and reconstructed using a method based on partial separability. fMRI detection sensitivity of k‐t 3D‐rFOVI was quantitively analyzed with simulation data. Human visual fMRI experiments were performed to evaluate k‐t 3D‐rFOVI and compare it with a commercial multiband EPI sequence. Results: The simulation data showed that k‐t 3D‐rFOVI can detect 100% of fMRI activations with an acceleration factor (R) of 2 and ˜80% with R = 6. In the human fMRI data acquired with 1.5‐mm spatial resolution and 800‐ms volume TR (TRvol), k‐t 3D‐rFOVI with R = 4 detected 46% more activated voxels in the visual cortex than the multiband EPI. Additional fMRI experiments showed that k‐t 3D‐rFOVI can achieve TRvol of 480 ms with R = 6, while reliably detecting visual activation. Conclusions: k‐t 3D‐rFOVI can simultaneously achieve a high spatial resolution (1.5‐mm isotropically) and short TRvol (480‐ms) at 3T. It offers a robust acquisition technique for fast fMRI studies over a focused brain volume. [ABSTRACT FROM AUTHOR]

The human primary visual cortex (V1) development is pivotal to understanding cortical maturation and neuroplasticity. Theories on V1 development range from early maturation models, which emphasize the early peak of synapses in infancy, to those suggesting an extended developmental timeline where key plasticity mechanisms continue to mature well into adulthood. Classic histological approaches have supported early development, while recent molecular studies highlight prolonged or multiple windows of plasticity, indicating that V1 remains susceptible to experience-dependent modifications beyond childhood. This review consolidates findings from both anatomical and molecular studies, tracing the development of V1 from prenatal stages through aging. The evidence reveals that human V1 develops across multiple timescales, with some aspects maturing early and others gradually changing across the lifespan. Reflecting on Cajal’s early work, this review underscores the importance of methodological advancements in revealing the intricate details of V1’s development. [ABSTRACT FROM AUTHOR]

GABAergic inhibitory interneurons comprise many subtypes that differ in their molecular, anatomical, and functional properties. In mouse visual cortex, they also differ in their modulation with an animal’s behavioral state, and this state modulation can be predicted from the first principal component (PC) of the gene expression matrix. Here, we ask whether this link between transcriptome and state- dependent processing generalizes across species. To this end, we analysed seven single-cell and single-nucleus RNA sequencing datasets from mouse, human, songbird, and turtle forebrains. Despite homology at the level of cell types, we found clear differences between transcriptomic PCs, with greater dissimilarities between evolutionarily distant species. These dissimilarities arise from two factors: divergence in gene expression within homologous cell types and divergence in cell-type abundance. We also compare the expression of cholinergic receptors, which are thought to causally link transcriptome and state modulation. Several cholinergic receptors predictive of state modulation in mouse interneurons are differentially expressed between species. Circuit modelling and mathematical analyses suggest conditions under which these expression differences could translate into functional differences. [ABSTRACT FROM AUTHOR]

Even though the oral cavity is not visible, food chewing can be performed without damaging the tongue, oral mucosa, or other intraoral parts, with cross-modal perception of chewing possibly critical for appropriate recognition of its performance. This study was conducted to clarify the relationship of chewing food cross-modal perception with cortex activities based on examinations of the posterior parietal cortex (PPC) and visual cortex during chewing in comparison with sham chewing without food, imaginary chewing, and rest using functional near-infrared spectroscopy. Additionally, the effects of a deafferent tongue dorsum on PPC/visual cortex activities during chewing performance were examined. The results showed that chewing food increased activity in the PPC/visual cortex as compared with imaginary chewing, sham chewing without food, and rest. Nevertheless, those activities were not significantly different during imaginary chewing or sham chewing without food as compared with rest. Moreover, subjects with a deafferent tongue dorsum showed reduced PPC/visual cortex activities during chewing food performance. These findings suggest that chewing of food involves cross-modal recognition, while an oral somatosensory deficit may modulate such cross-modal activities. [ABSTRACT FROM AUTHOR]

A central goal of neuroscience is to understand how function-relevant brain activations are generated. Here we test the hypothesis that function-relevant brain activations are generated primarily by distributed network flows. We focused on visual processing in human cortex, given the long-standing literature supporting the functional relevance of brain activations in visual cortex regions exhibiting visual category selectivity. We began by using fMRI data from N = 352 human participants to identify category-specific responses in visual cortex for images of faces, places, body parts, and tools. We then systematically tested the hypothesis that distributed network flows can generate these localized visual category selective responses. This was accomplished using a recently developed approach for simulating – in a highly empirically constrained manner – the generation of task-evoked brain activations by modeling activity flowing over intrinsic brain connections. We next tested refinements to our hypothesis, focusing on how stimulus-driven network interactions initialized in V1 generate downstream visual category selectivity. We found evidence that network flows directly from V1 were sufficient for generating visual category selectivity, but that additional, globally distributed (whole-cortex) network flows increased category selectivity further. Using null network architectures we also found that each region's unique intrinsic "connectivity fingerprint" was key to the generation of category selectivity. These results generalized across regions associated with all four visual categories tested (bodies, faces, places, and tools), and provide evidence that the human brain's intrinsic network organization plays a prominent role in the generation of functionally relevant, localized responses. Author summary: A fundamental question in neuroscience has persisted for over a century: to what extent do distributed processes drive brain function? The existence of category-selective regions within visual cortex provides long-standing evidence supporting localized computations, wherein specialized functions (e.g., selective responsiveness to face images) are thought to be primarily generated by within-region processes. This account was recently updated to include category selectivity dispersed across visual cortex, in the absence of category-selective regions. Here we provide groundwork evidence demonstrating that locally-exhibited visual-category-selective responses can be accurately generated via distributed activity flowing over globally connected systems. These processes were simulated via empirically-based computational models initialized by stimulus-evoked activity patterns and empirical connectivity matching each category-selective region's unique intrinsic functional connectivity fingerprint. Results demonstrate that activity flowing over the human brain's distributed network architecture can account for the generation of category selectivity in visual cortex regions. [ABSTRACT FROM AUTHOR]

Representational drift—the gradual continuous change of neuronal representations—has been observed across many brain areas. It is unclear whether drift is caused by synaptic plasticity elicited by sensory experience, or by the intrinsic volatility of synapses. Here, using chronic two-photon calcium imaging in primary visual cortex of female mice, we find that the preferred stimulus orientation of individual neurons slowly drifts over the course of weeks. By using cylinder lens goggles to limit visual experience to a narrow range of orientations, we show that the direction of drift, but not its magnitude, is biased by the statistics of visual input. A network model suggests that drift of preferred orientation largely results from synaptic volatility, which under normal visual conditions is counteracted by experience-driven Hebbian mechanisms, stabilizing preferred orientation. Under deprivation conditions these Hebbian mechanisms enable adaptation. Thus, Hebbian synaptic plasticity steers drift to match the statistics of the environment. Neural mechanisms underlying representational drift are not fully understood. Here authors report that the preferred orientation of mouse visual cortex neurons drifts over time. Altering visual experience does not change drift magnitude, but rather its direction, such that neurons' tuning matches the statistics of the environment. [ABSTRACT FROM AUTHOR]

Neural activity cannot be directly observed using fMRI; rather it must be inferred from the hemodynamic responses that neural activity causes. Solving this inverse problem is made possible through the use of forward models, which generate predicted hemodynamic responses given hypothesised underlying neural activity. Commonly‐used hemodynamic models were developed to explain data from healthy young participants; however, studies of ageing and dementia are increasingly shifting the focus toward elderly populations. We evaluated the validity of a range of hemodynamic models across the healthy adult lifespan: from basis sets for the linear convolution models commonly used to analyse fMRI studies, to more advanced models including nonlinear fitting of a parameterised hemodynamic response function (HRF) and nonlinear fitting of a biophysical generative model (hemodynamic modelling, HDM). Using an exceptionally large sample of participants, and a sensorimotor task optimized for detecting the shape of the BOLD response to brief stimulation, we first characterised the effects of age on descriptive features of the response (e.g., peak amplitude and latency). We then compared these to features from more complex nonlinear models, fit to four regions of interest engaged by the task, namely left auditory cortex, bilateral visual cortex, left (contralateral) motor cortex and right (ipsilateral) motor cortex. Finally, we validated the extent to which parameter estimates from these models have predictive validity, in terms of how well they predict age in cross‐validated multiple regression. We conclude that age‐related differences in the BOLD response can be captured effectively by models with three free parameters. Furthermore, we show that biophysical models like the HDM have predictive validity comparable to more common models, while additionally providing insights into underlying mechanisms, which go beyond descriptive features like peak amplitude or latency, and include estimation of nonlinear effects. Here, the HDM revealed that most of the effects of age on the BOLD response could be explained by an increased rate of vasoactive signal decay and decreased transit rate of blood, rather than changes in neural activity per se. However, in the absence of other types of neural/hemodynamic data, unique interpretation of HDM parameters is difficult from fMRI data alone, and some brain regions in some tasks (e.g., ipsilateral motor cortex) can show responses that are more difficult to capture using current models. [ABSTRACT FROM AUTHOR]

Background/Objectives: Habituation and sensitization are opposite phenomena that play a role in the pathophysiology of episodic migraine and its progression to chronic migraine (CM). There have been just a few studies that have investigated these phenomena in patients with medication overuse headache (MOH) in comparison to those with chronic migraine (CM) and healthy controls (HCs), and the findings have been inconsistent. Methods: We measured and examined visual evoked potentials (VEPs) in 81 patients with MOH and 24 patients with CM, as well as 24 HCs. The VEPs were used to assess sensitization by analysing the amplitude of the first block (100 sweeps) and to evaluate habituation by measuring the amplitude response decrement after six blocks. We further examined patients diagnosed with MOH based on their acute medication type and after a 3-week acute medication withdrawal program. Results: There were no significant differences between groups in terms of the first N1-P1 VEP amplitude block and its habituation. It was found that patients with MOH had a greater drop in the amplitude of the VEP P1-N2 complex after repeated stimulation than patients with CM or HC. The VEP parameters showed no significant differences based on the specific overused drug and after a 3-week acute medication withdrawal. Conclusions: We propose that the results obtained in patients with MOH indicate an abnormal activation of inhibitory circuits in the parieto-occipital region in response to repeated modulatory stimuli. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The ability to modulate specific neural circuits and simultaneously visualize and measure brain activity with MRI would greatly impact our understanding of brain function in health and disease. The combination of neurostimulation methods and functional MRI in animal models have already shown promise in elucidating fundamental mechanisms associated with brain activity. We developed an innovativemagnetogenetics neurostimulation technology that can trigger neural activity through magnetic fields. Similar to other genetic-based neuromodulation methods, magnetogenetics offers cell-, area-, and temporal- specific control of neural activity. Themagnetogenetic protein--Electromagnetic Perceptive Gene (EPG)--is activated by non-invasive magnetic fields, providing a unique way to target neural circuits by the MRI static and gradient fields while simultaneously measuring their effect on brain activity. EPG was expressed in rat's visual cortex and the amplitude of low-frequency fluctuation, resting-state functional connectivity (FC), and sensory activation was measured using a 7T MRI. The results demonstrate that EPG-expressing rats had significantly higher signal fluctuations in the visual areas and stronger FC in sensory areas consistent with known anatomical visuosensory and visuomotor connections. This new technology complements the existing neurostimulation toolbox and provides a means to study brain function in a minimally-invasive way which was not possible previously. [ABSTRACT FROM AUTHOR]

Recent visual experience heavily influences our visual perception, but how neuronal activity is reshaped to alter and improve perceptual discrimination remains unknown. We recorded from populations of neurons in visual cortical area V4 while two male rhesus macaque monkeys performed a natural image change detection task under different experience conditions. We found that maximizing the recent experience with a particular image led to an improvement in the ability to detect a change in that image. This improvement was associated with decreased neural responses to the image, consistent with neuronal changes previously seen in studies of adaptation and expectation. We found that the magnitude of behavioral improvement was correlated with the magnitude of response suppression. Furthermore, this suppression of activity led to an increase in signal separation, providing evidence that a reduction in activity can improve stimulus encoding. Within populations of neurons, greater recent experience was associated with decreased trial-to-trial shared variability, indicating that a reduction in variability is a key means by which experience influences perception. Taken together, the results of our study contribute to an understanding of how recent visual experience can shape our perception and behavior through modulating activity patterns in the mid-level visual cortex. [ABSTRACT FROM AUTHOR]

The role of experience in the organization of cortical feedback (FB) remains unknown. We measured the effects of manipulating visual experience on the retinotopic specificity of supragranular and infragranular projections from the lateromedial (LM) visual area to layer (L)1 of the mouse primary visual cortex (V1). LM inputs were, on average, retinotopically matched with V1 neurons in normally and dark-reared mice, but visual exposure reduced the fraction of spatially overlapping inputs to V1. FB inputs from L5 conveyed more surround information to V1 than those from L2/3. The organization of LM inputs from L5 depended on their orientation preference and was disrupted by dark rearing. These observations were recapitulated by a model where visual experience minimizes receptive field overlap between LM inputs and V1 neurons. Our results provide a mechanism for the dependency of surround modulations on visual experience and suggest how expected interarea coactivation patterns are learned in cortical circuits. • Visual experience reduces the receptive field overlap between LM inputs and V1 neurons • LM inputs from L5 convey more surround information to V1 neurons than those from L2/3 • The tuning-dependent organization of LM inputs from L5 requires visual experience • Spatial redundancy minimization explains visual experience effects on LM inputs Dias and Rajan et al. compared the functional organization of cortical feedback inputs in the primary visual cortex of normally and dark-reared mice. They found that visual experience reduces the representational redundancy between feedback inputs and primary visual cortex neurons. [ABSTRACT FROM AUTHOR]

Introduction: Altered subjective visual sensitivity manifests as feelings of discomfort or overload elicited by intense and irritative visual stimuli. This can result in a host of visual aberrations including visual distortions, elementary visual hallucinations and visceral responses like dizziness and nausea, collectively referred to as "pattern glare." Current knowledge of the underlying neural mechanisms has focused on overall excitability of the visual cortex, but the individual contribution of excitatory and inhibitory systems has not yet been quantified. Methods: In this study, we focus on the role of glutamate and ?-aminobutyric acid (GABA) as potential mediators of individual differences in subjective visual sensitivity, measured by a computerized Pattern Glare Test--a series of monochromatic square-wave gratings with three different spatial frequencies, while controlling for psychological variables related to sensory sensitivity with multiple questionnaires. Resting neurotransmitter concentrations in primary visual cortex (V1) and right anterior insula were studied in 160 healthy participants using magnetic resonance spectroscopy. Results: Data showed significant differences in the perception of visual distortions (VD) and comfort scores between men and women, with women generally reporting more VD, and therefore the modulatory effect of sex was considered in a further examination. A general linear model analysis showed a negative effect of occipital glutamate on a number of reported visual distortions, but also a significant role of several background psychological traits. When assessing comfort scores in women, an important intervening variable was the menstrual cycle. Discussion: Our findings do not support that baseline neurotransmitter levels have a significant role in overreactivity to aversive stimuli in neurotypical population. However, we demonstrated that biological sex can have a significant impact on subjective responses. Based on this additional finding, we suggest that future studies investigate aversive visual stimuli while examining the role of biological sex. [ABSTRACT FROM AUTHOR]

Primary visual cortex (V1) has been the focus of extensive neurophysiological investigations, with its laminar organization serving as a crucial model for understanding the functional logic of neocortical microcircuits. Utilizing newly developed highdensity, Neuropixels probes, we measured visual responses from large populations of simultaneously recorded neurons distributed across layers of macaque V1. Within single recordings, myriad differences in the functional properties of neuronal subpopulations could be observed. Notably, while standard measurements of orientation selectivity showed only minor differences between laminar compartments, decoding stimulus orientation from layer 4C responses outperformed both superficial and deep layers within the same cortical column. The superior orientation discrimination within layer 4C was associated with greater response reliability of individual neurons rather than lower correlated activity within neuronal populations. Our results underscore the efficacy of high-density electrophysiology in revealing the functional organization and network properties of neocortical microcircuits within single experiments. [ABSTRACT FROM AUTHOR]

Artificial visual system empowered by 2D materials-based hardware simulates the functionalities of the human visual system, leading the forefront of artificial intelligence vision. However, retina-mimicked hardware that has not yet fully emulated the neural circuits of visual pathways is restricted from realizing more complex and special functions. In this work, we proposed a human visual pathway-replicated hardware that consists of crossbar arrays with split floating gate 2D tungsten diselenide (WSe2) unit devices that simulate the retina and visual cortex, and related connective peripheral circuits that replicate connectomics between the retina and visual cortex. This hardware experimentally displays advanced multi-functions of red–green color-blindness processing, low-power shape recognition, and self-driven motion tracking, promoting the development of machine vision, driverless technology, brain–computer interfaces, and intelligent robotics. Realizing complex functions in artificial visual systems is challenging. Here, the authors report a human visual pathway-replicated hardware with a split floating gate crossbar arrays and related peripheral circuits, achieving colour-blindness processing, shape recognition, and self-driven motion tracking. [ABSTRACT FROM AUTHOR]

Background/Objectives: Neural decoding methods are often limited by the performance of brain encoders, which map complex brain signals into a latent representation space of perception information. These brain encoders are constrained by the limited amount of paired brain and stimuli data available for training, making it challenging to learn rich neural representations. Methods: To address this limitation, we present a novel multimodal training approach using paired image and functional magnetic resonance imaging (fMRI) data to establish a brain masked autoencoder that learns the interactions between images and brain activities. Subsequently, we employ a diffusion model conditioned on brain data to decode realistic images. Results: Our method achieves high-quality decoding results in semantic contents and low-level visual attributes, outperforming previous methods both qualitatively and quantitatively, while maintaining computational efficiency. Additionally, our method is applied to decode artificial patterns across region of interests (ROIs) to explore their functional properties. We not only validate existing knowledge concerning ROIs but also unveil new insights, such as the synergy between early visual cortex and higher-level scene ROIs, as well as the competition within the higher-level scene ROIs. Conclusions: These findings provide valuable insights for future directions in the field of neural decoding. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to analyze the features of resting‐state functional magnetic resonance imaging (rs‐fMRI) and clinical relevance in patients with benign paroxysmal positional vertigo (BPPV) that have undergone repositioning maneuvers. Methods: A total of 38 patients with BPPV who have received repositioning maneuvers and 38 matched healthy controls (HCs) were enrolled in the present study from March 2018 to August 2021. Imaging analysis software was employed for functional image preprocessing and indicator calculation, mainly including the amplitude of low‐frequency fluctuation (ALFF), fractional ALFF (fALFF), percent amplitude of fluctuation (PerAF), and seed‐based functional connectivity (FC). Statistical analysis of the various functional indicators in patients with BPPV and HCs was also conducted, and correlation analysis with clinical data was performed. Results: Patients with BPPV displayed decrease in ALFF, fALFF, and PerAF values, mainly in the bilateral occipital lobes in comparison with HCs. Additionally, their ALFF and fALFF values in the proximal vermis region of the cerebellum increased relative to HCs. The PerAF values in the bilateral paracentral lobules, the right supplementary motor area (SMA), and the left precuneus decreased in patients with BPPV and were negatively correlated with dizziness visual analog scale (VAS) scores 1 week after repositioning (W1). In addition, in the left fusiform gyrus and lingual gyrus, the PerAF values show a negative correlation with dizziness handicap inventory (DHI) scores at initial visit (W0). Seed‐based FC analysis using the seeds from differential clusters of fALFF, ALFF, and PerAF showed reductions between the left precuneus and bilateral occipital lobe, the left precuneus and left paracentral lobule, and within the occipital lobes among patients with BPPV. Conclusion: The spontaneous activity of certain brain regions in the bilateral occipital and frontoparietal lobes of patients with BPPV was reduced, whereas the activity in the cerebellar vermis was increased. Additionally, there were reductions in FC between the precuneus and occipital cortex or paracentral lobule, as well as within the occipital cortex. The functional alterations in these brain regions may be associated with the inhibitory interaction and functional integration of visual, vestibular, and sensorimotor systems. The functional alterations observed in the visual cortex and precuneus may represent adaptive responses associated with residual dizziness. [ABSTRACT FROM AUTHOR]

The fate of deprived sensory cortices (visual regions in the blind and auditory regions in the deaf) exemplifies the extent to which experience can change brain regions. These regions are frequently seen to activate during tasks involving other sensory modalities, leading many authors to infer that these regions have started to process sensory information of other modalities. However, such observations can also imply that these regions are now activating in response to any task event, regardless of the sensory modality. Activating in response to task events, irrespective of the sensory modality involved, is a feature of the multiple-demands (MD) network. This is a set of regions within the frontal and parietal cortices that activate in response to any kind of control demand. Thus, demands as diverse as attention, perceptual difficulty, rule-switching, updating working memory, inhibiting responses, decision-making and difficult arithmetic all activate the same set of regions that are thought to instantiate domain-general cognitive control and underpin fluid intelligence. We investigated whether deprived sensory cortices, or foci within them, become part of the MD network. We tested whether the same foci within the visual regions of the blind and auditory regions of the deaf activated in response to different control demands. We found that control demands related to updating auditory working memory, difficult tactile decisions, time-duration judgments and sensorimotor speed all activated the entire bilateral occipital regions in the blind but not in the sighted. These occipital regions in the blind were the only regions outside the canonical frontoparietal MD regions to show such activation in response to multiple control demands. Furthermore, compared with the sighted, these occipital regions in the blind had higher functional connectivity with frontoparietal MD regions. Early deaf, in contrast, did not activate their auditory regions in response to different control demands, showing that auditory regions do not become MD regions in the deaf. We suggest that visual regions in the blind do not take a new sensory role but become part of the MD network, and this is not a response of all deprived sensory cortices but a feature unique to the visual regions. [ABSTRACT FROM AUTHOR]

Hearing difficulty (HD) is a major health burden in older adults. While ageing-related changes in the peripheral auditory system play an important role, genetic variation associated with brain structure and function could also be involved in HD predisposition. We analysed a large-scale HD genome-wide association study (GWAS; n total = 501 825, 56% females) and GWAS data related to 3935 brain imaging-derived phenotypes (IDPs) assessed in up to 33 224 individuals (52% females) using multiple MRI modalities. To investigate HD pleiotropy with brain structure and function, we conducted genetic correlation, latent causal variable, Mendelian randomization and multivariable generalized linear regression analyses. Additionally, we performed local genetic correlation and multi-trait co-localization analyses to identify genomic regions and loci implicated in the pleiotropic mechanisms shared between HD and brain IDPs. We observed a widespread genetic correlation of HD with 120 IDPs in females, 89 in males and 171 in the sex-combined analysis. The latent causal variable analysis showed that some of these genetic correlations could be due to cause-effect relationships. For seven of them, the causal effects were also confirmed by the Mendelian randomization approach: vessel volume→HD in the sex-combined analysis; hippocampus volume→HD, cerebellum grey matter volume→HD, primary visual cortex volume→HD and HD→fluctuation amplitudes of node 46 in resting-state functional MRI dimensionality 100 in females; global mean thickness→HD and HD→mean orientation dispersion index in superior corona radiata in males. The local genetic correlation analysis identified 13 pleiotropic regions between HD and these seven IDPs. We also observed a co-localization signal for the rs13026575 variant between HD, primary visual cortex volume and SPTBN1 transcriptomic regulation in females. Brain structure and function may have a role in the sex differences in HD predisposition via possible cause-effect relationships and shared regulatory mechanisms. [ABSTRACT FROM AUTHOR]

Music is a powerful medium that influences our emotions and memories. Neuroscience research has demonstrated music's ability to engage brain regions associated with emotion, reward, motivation, and autobiographical memory. While music's role in modulating emotions has been explored extensively, our study investigates whether music can alter the emotional content of memories. Building on the theory that memories can be updated upon retrieval, we tested whether introducing emotional music during memory recollection might introduce false emotional elements into the original memory trace. We developed a 3-day episodic memory task with separate encoding, recollection, and retrieval phases. Our primary hypothesis was that emotional music played during memory recollection would increase the likelihood of introducing novel emotional components into the original memory. Behavioral findings revealed two key outcomes: 1) participants exposed to music during memory recollection were more likely to incorporate novel emotional components congruent with the paired music valence, and 2) memories retrieved 1 day later exhibited a stronger emotional tone than the original memory, congruent with the valence of the music paired during the previous day's recollection. Furthermore, fMRI results revealed altered neural engagement during story recollection with music, including the amygdala, anterior hippocampus, and inferior parietal lobule. Enhanced connectivity between the amygdala and other brain regions, including the frontal and visual cortex, was observed during recollection with music, potentially contributing to more emotionally charged story reconstructions. These findings illuminate the interplay between music, emotion, and memory, offering insights into the consequences of infusing emotional music into memory recollection processes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Modular and distributed coding theories of category selectivity along the human ventral visual stream have long existed in tension. Here, we present a reconciling framework--contrastive coding--based on a series of analyses relating category selectivity within biological and artificial neural networks. We discover that, in models trained with contrastive self-supervised objectives over a rich natural image diet, category-selective tuning naturally emerges for faces, bodies, scenes, and words. Further, lesions of these model units lead to selective, dissociable recognition deficits, highlighting their distinct functional roles in information processing. Finally, these pre-identified units can predict neural responses in all corresponding face-, scene-, body-, and word-selective regions of human visual cortex, under a highly constrained sparse positive encoding procedure. The success of this single model indicates that brain-like functional specialization can emerge without category-specific learning pressures, as the system learns to untangle rich image content. Contrastive coding, therefore, provides a unifying account of object category emergence and representation in the human brain. [ABSTRACT FROM AUTHOR]

Aphantasia refers to reduced or absent visual imagery. While most of us can readily recall decade-old personal experiences (autobiographical memories, AM) with vivid mental images, there is a dearth of information about whether the loss of visual imagery in aphantasics affects their AM retrieval. The hippocampus is thought to be a crucial hub in a brain-wide network underlying AM. One important question is whether this network, especially the connectivity of the hippocampus, is altered in aphantasia. In the current study, we tested 14 congenital aphantasics and 16 demographically matched controls in an AM fMRI task to investigate how key brain regions (i.e. hippocampus and visual-perceptual cortices) interact with each other during AM re-experiencing. All participants were interviewed regarding their autobiographical memory to examine their episodic and semantic recall of specific events. Aphantasics reported more difficulties in recalling AM, were less confident about their memories, and described less internal and emotional details than controls. Neurally, aphantasics displayed decreased hippocampal and increased visual-perceptual cortex activation during AM retrieval compared to controls. In addition, controls showed strong negative functional connectivity between the hippocampus and the visual cortex during AM and resting-state functional connectivity between these two brain structures predicted better visualization skills. Our results indicate that visual mental imagery plays an important role in detail-rich vivid AM, and that this type of cognitive function is supported by the functional connection between the hippocampus and the visual-perceptual cortex. [ABSTRACT FROM AUTHOR]

In the mammalian neocortex, inhibition is important for dynamically balancing excitation and shaping the response properties of cells and circuits. The various computational functions of inhibition are thought to be mediated by different inhibitory neuron types, of which a large diversity exists in several species. Current understanding of the function and connectivity of distinct inhibitory neuron types has mainly derived from studies in transgenic mice. However, it is unknown whether knowledge gained from mouse studies applies to the non-human primate, the model system closest to humans. The lack of viral tools to selectively access inhibitory neuron types has been a major impediment to studying their function in the primate. Here, we have thoroughly validated and characterized several recently developed viral vectors designed to restrict transgene expression to GABAergic cells or their parvalbumin (PV) subtype, and identified two types that show high specificity and efficiency in marmoset V1. We show that in marmoset V1, AAV-h56D induces transgene expression in GABAergic cells with up to 91–94% specificity and 79% efficiency, but this depends on viral serotype and cortical layer. AAV-PHP.eB-S5E2 induces transgene expression in PV cells across all cortical layers with up to 98% specificity and 86–90% efficiency, depending on layer. Thus, these viral vectors are promising tools for studying GABA and PV cell function and connectivity in the primate cortex. [ABSTRACT FROM AUTHOR]

Exploring the relationship between neuronal loss in adult visual cortex and its consequential changes in synaptic connection provides experimental evidence to elucidate impaired visual function upon traumatic brain injury. The primary visual cortex (V1) of 8-week-old C57BL/6 mice was sparsely infected with adeno-associated viruses (AAVs) encoding diphtheria toxin A (DTA) to induce neuronal apoptosis. Neuronal number and dendritic spine morphology of surviving pyramidal neurons in layers 2-4 of visual cortex were analyzed using immunofluorescence staining, Golgi staining and confocal microscopy after four weeks post-injection. Through stereotactic injection of different titers (E+11-13) of DTA-expressing viruses, mouse models were generated with various levels of neuronal loss (by 14~85%) in the adult visual cortex. The results revealed that low-titer (E+11) DTA-expressing AAV led to moderate reduction of neuronal number (by~18%, P＜0.01), mimicking the level of neuronal loss in patients with mild traumatic brain injury (16.5~2.9%). In this DTA group, while dendritic spine density of pyramidal neurons did not change in comparison to the control group, the proportion of mature spines reduced by ~19% (P＜0.0001). Neuronal loss in adult visual cortex impaired synaptic connection and probably compromised visual function in the brain. [ABSTRACT FROM AUTHOR]

Background Toxoplasma gondii infection of Alzheimer's disease model mice decreases amyloid β plaques. We aimed to determine if there is a brain regional difference in amyloid β reduction in the brains of T. gondii- infected compared to control mice. Method Three-month-old 5xFAD (AD model) mice were injected with T. gondii or with phosphate-buffered saline as a control. Intact brains were harvested at 6 weeks postinfection, optically cleared using iDISCO+, and brain-wide amyloid burden was visualized using volumetric light-sheet imaging. Amyloid signal was quantified across each brain and computationally mapped to the Allen Institute Brain Reference Atlas to determine amyloid density in each region. Results A brain-wide analysis of amyloid in control and T. gondii- infected 5xFAD mice revealed that T. gondii infection decreased amyloid burden in the brain globally as well as in the cortex and hippocampus, and many daughter regions. Daughter regions that showed reduced amyloid burden included the prelimbic cortex, visual cortex, and retrosplenial cortex. The olfactory tubercle, a region known to have increased monocytes following T. gondii infection, also showed reduced amyloid after infection. Conclusions T. gondii infection of AD mice reduces amyloid burden in a brain region-specific manner that overlaps with known regions of T. gondii infection and peripheral immune cell infiltration. [ABSTRACT FROM AUTHOR]

The field of computer vision has long drawn inspiration from neuroscientific studies of the human and non-human primate visual system. The development of convolutional neural networks (CNNs), for example, was informed by the properties of simple and complex cells in early visual cortex. However, the computational relevance of oscillatory dynamics experimentally observed in the visual system are typically not considered in artificial neural networks (ANNs). Computational models of neocortical dynamics, on the other hand, rarely take inspiration from computer vision. Here, we combine methods from computational neuroscience and machine learning to implement multiplexing in a simple ANN using oscillatory dynamics. We first trained the network to classify individually presented letters. Post-training, we added temporal dynamics to the hidden layer, introducing refraction in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, indicating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activate sequentially, ordered along the phase of the inhibitory oscillations. Our model implements the idea that inhibitory oscillations segregate competing inputs in time. The results of our simulations pave the way for applications in deeper network architectures and more complicated machine learning problems. Author summary: Computer vision is a subfield of artificial intelligence focused on developing artificial neural networks (ANNs) that classify and generate images. Neuronal responses to visual features and the anatomical structure of the human visual system have traditionally inspired the development of computer vision models. The visual cortex also produces rhythmic activity that has long been suggested to support visual processes. However, there are only a few examples of ANNs embracing the temporal dynamics of the human brain. Here, we present a prototype of an ANN with biologically inspired dynamics—a dynamical ANN. We show that the dynamics enable the network to process two inputs simultaneously and read them out as a sequence, a task it has not been explicitly trained on. A crucial component of generating this dynamic output is a rhythm at about 10Hz, akin to the so-called alpha oscillations dominating human visual cortex. The oscillations rhythmically suppress activations in the network and stabilise its dynamics. The presented algorithm paves the way for applications in more complex machine learning problems. Moreover, we present several predictions that can be tested using established neuroscientific approaches. As such, the presented work contributes to both artificial intelligence and neuroscience. [ABSTRACT FROM AUTHOR]

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. Examination of how visual feedback mediates visuomotor interaction reveals insights into motor learning processes, highlighting distinct roles of sensory and motor areas, as well as early and late visual areas. [ABSTRACT FROM AUTHOR]

To survive in nature, it is crucial for animals to promptly and appropriately respond to visual information, specifically to animacy cues that pose a threat. The subcortical visual pathway is thought to be implicated in the processing of visual information necessary for these responses. In primates, this pathway consists of retina-superior colliculus-pulvinar-amygdala, functioning as a visual pathway that bypasses the geniculo-striate system (retina-lateral geniculate nucleus-primary visual cortex). In this mini review, we summarize recent neurophysiological studies that have revealed neural responses to threatening animacy cues, namely snake images, in different parts of the subcortical visual pathway and closely related brain regions in primates. The results of these studies provide new insights on (1) the role of the subcortical visual pathway in innate cognitivemechanisms for predator recognition that are evolutionarily conserved, and (2) the possible role of the medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) in the development of fear conditioning to cues that should be instinctively avoided based on signals from the subcortical visual pathway, as well as their function in excessive aversive responses to animacy cues observed in conditions such as ophidiophobia (snake phobia). [ABSTRACT FROM AUTHOR]

Objective: Previous studies have found that patients with Major Depressive Disorder (MDD) exhibit impaired visual motion perception capabilities, and multi-level abnormalities in the human middle temporal complex (MT+), a key brain area for processing visual motion information. However, the brain activity pattern of MDD patients during the perception of visual motion information is currently unclear. In order to study the effect of depression on the activity and functional connectivity (FC) of MT+ during the perception of visual motion information, we conducted a study combining task-state fMRI and psychophysical paradigm to compare MDD patients and healthy control (HC). Methods: Duration threshold was examined through a visual motion perception psychophysical experiment. In addition, a classic block-design grating motion task was utilized for fMRI scanning of 24 MDD patients and 25 HC. The grating moved randomly in one of eight directions. We examined the neural activation under visual stimulation conditions compared to the baseline and FC. Results: Compared to HC group, MDD patients exhibited increased duration threshold. During the task, MDD patients showed decreased beta value and percent signal change in left and right MT+. In the sample comprising MDD and HC, there was a significant negative correlation between beta value in right MT+ and duration threshold. And in MDD group, activation in MT+ were significantly correlated with retardation score. Notably, no such differences in activation were observed in primary visual cortex (V1). Furthermore, when left MT+ served as the seed region, compared to the HC, MDD group showed increased FC with right calcarine fissure and surrounding cortex and decreased FC with left precuneus. Conclusion: Overall, the findings of this study highlight that the visual motion perception function impairment in MDD patients relates to abnormal activation patterns in MT+, and task-related activity are significantly connected to the retardation symptoms of the disease. This not only provides insights into the potential neurobiological mechanisms behind visual motion perception disorder in MDD patients from the aspect of task-related brain activity, but also supports the importance of MT+ as a candidate biomarker region for MDD. [ABSTRACT FROM AUTHOR]

Monocular deprivation (MD) causes an initial decrease in synaptic responses to the deprived eye in juvenile mouse primary visual cortex (V1) through Hebbian long-term depression (LTD). This is followed by a homeostatic increase, which has been attributed either to synaptic scaling or to a slide threshold for Hebbian long-term potentiation (LTP) rather than scaling. We therefore asked in mice of all sexes whether the homeostatic increase during MD requires GluN2B-containing NMDA receptor activity, which is required to slide the plasticity threshold but not for synaptic scaling. Selective GluN2B blockade from 2–6 d after monocular lid suture prevented the homeostatic increase in miniature excitatory postsynaptic current (mEPSC) amplitude in monocular V1 of acute slices and prevented the increase in visually evoked responses in binocular V1 in vivo. The decrease in mEPSC amplitude and visually evoked responses during the first 2 d of MD also required GluN2B activity. Together, these results support the idea that GluN2B-containing NMDA receptors first play a role in LTD immediately following eye closure and then promote homeostasis during prolonged MD by sliding the plasticity threshold in favor of LTP. [ABSTRACT FROM AUTHOR]

Objective: The aim of this is to explore changes in cross-modal reorganization within the auditory–visual cortex after cochlear implantation, examining their influence on auditory and speech functions along with their underlying mechanisms. Methods: Twenty prelingually deaf children who received cochlear implantation and rehabilitation training at our hospital between February 2022 and February 2023 comprised the prelingual deaf group. Simultaneously, 20 healthy children served as the control group. The prelingual deaf group underwent brain cortical activity assessment and evaluation of auditory-speech recovery pre-surgery, at postoperative weeks 1 and 2, and at months 1, 3, 6, 9, and 12. The control group underwent parallel assessments and evaluations. We analyzed the correlation between cortical activity in the auditory–visual cortex of patients and their auditory-speech functional recovery. Results: The group with prelingual deafness displayed elevated levels of auditory and visual cortical electromagnetic intensity compared to the control group, both prior to and 9  months after surgery. However, by the 12-month mark postsurgery, there was no discernible distinction between the two groups. Following surgery, the prelingually deaf group exhibited a progressive improvement in both Categories of Auditory Performance (CAP) and Speech Intelligibility Rate (SIR), initially lagging behind the control group. Notably, a negative correlation emerged between auditory and visual cortical electromagnetic intensity values and CAP/SIR scores at the 12-month post-surgery assessment. Conclusion: Cochlear implantation in prelingually deaf children results in elevated activity within the auditory and visual cortices, demonstrated by heightened electromagnetic intensity readings. Cross-modal reorganization is observed temporarily at 3  months post-surgery, which resolves to baseline levels by 12  months post-surgery. This phenomenon of reversal correlates with the restoration of auditory and speech functions in these children. [ABSTRACT FROM AUTHOR]