THE HUMAN VISUAL CORTEX

On the Geometry of Somatosensory Representations in the Cortex

The processing of somatosensory information in the cortex is often described using body maps, where adjacent cortical regions correspond to adjacent body parts. Additionally, the somatosensory cortex follows a hierarchical structure, which extends from the primary somatosensory cortex (S1) to higher cortical regions. While previous studies have identified multiple body maps and various hierarchy relations, the large-scale organization of these maps and their interactions have been less explored. Using functional MRI with full-body light touch stimulation, we discovered that in S1, body and hierarchy maps are orthogonal, but this orthogonality does not extend to other regions. On a larger scale, both body representation and hierarchy exhibit a radial organization, with a few central extrema governing numerous cortical regions. Similar patterns of radial organization in the visual and auditory systems suggest that radial topography may be a general organizational feature across sensory systems.

The striatal compartments, striosome and matrix, are embedded in largely distinct resting-state functional networks

The striatum is divided into two interdigitated tissue compartments, the striosome and matrix. These compartments exhibit distinct anatomical, neurochemical, and pharmacological characteristics and have separable roles in motor and mood functions. Little is known about the functions of these compartments in humans. While compartment-specific roles in neuropsychiatric diseases have been hypothesized, they have yet to be directly tested. Investigating compartment-specific functions is crucial for understanding the symptoms produced by striatal injury, and to elucidating the roles of each compartment in healthy human skills and behaviors. We mapped the functional networks of striosome-like and matrix-like voxels in humans in-vivo. We utilized a diverse cohort of 674 healthy adults, derived from the Human Connectome Project, including all subjects with complete diffusion and functional MRI data and excluding subjects with substance use disorders. We identified striatal voxels with striosome-like and matrix-like structural connectivity using probabilistic diffusion tractography. We then investigated resting-state functional connectivity (rsFC) using these compartment-like voxels as seeds. We found widespread differences in rsFC between striosome-like and matrix-like seeds (p < 0.05, family wise error corrected for multiple comparisons), suggesting that striosome and matrix occupy distinct functional networks. Slightly shifting seed voxel locations (<4 mm) eliminated these rsFC differences, underscoring the anatomic precision of these networks. Striosome-seeded networks exhibited ipsilateral dominance; matrix-seeded networks had contralateral dominance. Next, we assessed compartment-specific engagement with the triple-network model (default mode, salience, and frontoparietal networks). Striosome-like voxels dominated rsFC with the default mode network bilaterally. The anterior insula (a primary node in the salience network) had higher rsFC with striosome-like voxels. The inferior and middle frontal cortices (primary nodes, frontoparietal network) had stronger rsFC with matrix-like voxels on the left, and striosome-like voxels on the right. Since striosome-like and matrix-like voxels occupy highly segregated rsFC networks, striosome-selective injury may produce different motor, cognitive, and behavioral symptoms than matrix-selective injury. Moreover, compartment-specific rsFC abnormalities may be identifiable before disease-related structural injuries are evident. Localizing rsFC differences provides an anatomic substrate for understanding how the tissue-level organization of the striatum underpins complex brain networks, and how compartment-specific injury may contribute to the symptoms of specific neuropsychiatric disorders.

Layer-specific spatiotemporal dynamics of feedforward and feedback in human visual object perception

Visual object perception is mediated by information flow between regions of the ventral visual stream along feedforward and feedback anatomical connections. However, feedforward and feedback signals during naturalistic vision are rapid and overlapping, complicating their identification and precise functional specification. Here we recorded human layer-specific fMRI responses to naturalistic object images in early visual cortex (EVC) and lateral occipital complex (LOC) to isolate feedforward and feedback information signals spatially by their cortical layer specific termination pattern. We combined these layer-specific fMRI responses with electroencephalography (EEG) responses for the same images to segregate feedforward and feedback signals in both time and space. Feedforward signals emerge early in the middle layers of EVC and LOC, followed by feedback signals in the superficial layer of both regions, and the deep layer of EVC. Comparing the identified dynamics in LOC to a visual deep neural network (DNN), revealed that early feedforward signals in LOC encode medium complexity features, whereas later feedback signals increase the representational format to high complexity features. Together this specifies the spatiotemporal dynamics and functional role of feedforward and feedback information flow mediating visual object perception.

Object representations drive emotion schemas across a large and diverse set of daily-life scenes

The rapid emotional evaluation of objects and events is essential in daily life. While visual scenes reliably evoke emotions, it remains unclear whether emotion schemas evoked by daily-life scenes depend on object processing systems or are extracted independently. To explore this, we collected emotion ratings for 4913 daily-life scenes from 300 participants, and predicted these ratings from representations in deep neural networks and functional magnetic resonance imaging (fMRI) activity patterns in visual cortex. AlexNet, an object-based model, outperformed EmoNet, an emotion-based model, in predicting emotion ratings for daily-life scenes, while EmoNet excelled for explicitly evocative scenes. Emotion information was processed hierarchically within the object recognition system, consistent with the visual cortex's organization. Activity patterns in the lateral occipital complex (LOC), an object-selective region, reliably predicted emotion ratings and outperformed other visual regions. These findings suggest that the emotional evaluation of daily-life scenes is mediated by visual object processing, with additional mechanisms engaged when object content is uninformative.

Assessing brain neuroplasticity: Surface morphometric analysis of cortical changes induced by Quadrato motor training

Morphological markers for brain plasticity are still lacking and their findings are challenged by the extreme variability of cortical brain surface. Trying to overcome the "correspondence problem," we applied a landmark-free method (the generalized procrustes surface analysis (GPSA)) for investigating the shape variation of cortical surface in a group of 40 healthy volunteers (i.e., the practice group) subjected to daily motor training known as Quadrato motor training (QMT). QMT is a sensorimotor walking meditation that aims at balancing body, cognition, and emotion. More specifically, QMT requires coordination and attention and consists of moving in one of three possible directions on corners of a 50 × 50 cm2. Brain magnetic resonance images (MRIs) of practice group (acquired at baseline, as well as after 6 and 12 weeks of QMT), were 3D reconstructed and here compared with brain MRIs of six more volunteers never practicing the QMT (naïve group). Cortical regions mostly affected by morphological variations were visualized on a 3D average color-scaled brain surface indicating from higher (red) to lower (blue) levels of variation. Cortical regions interested in most of the shape variations were as follows: (1) the supplementary motor cortex; (2) the inferior frontal gyrus (pars opercolaris) and the anterior insula; (3) the visual cortex; (4) the inferior parietal lobule (supramarginal gyrus and angular gyrus). Our results show that surface morphometric analysis (i.e., GPSA) can be applied to assess brain neuroplasticity processes, such as those stimulated by QMT.

The impact of dwell time on the contextual effect of visual and passive lead-in movements

Contextual cues arising from distinct movements are crucial in shaping control strategies for human movement. Here, we examine the impact of visual and passive lead-in movement cues on unimanual motor learning, focusing on the influence of "dwell time," where two-part movements are separated by the interval between the end of the first movement and the start of the second. We used a robotic manipulandum to implement a point-to-point interference task with switching opposing viscous curl fields in male and female human participants. Consistent with prior research, in both visual and passive lead-in conditions, participants showed significant adaptation to opposing dynamics with short dwell times. As dwell time increased for both visual and passive signals, past movement information had less contextual influence. However, the efficacy of visual movement cues declined more rapidly as dwell times increased. At dwell times greater than 800 ms, the contextual influence of prior visual movement was small, whereas the effectiveness of passive lead-in movement was found to be significantly greater. This indicates that the effectiveness of sensory movement cues in motor learning is modality dependent. We hypothesize that such differences may arise because proprioceptive signals directly relate to arm movements, whereas visual inputs exhibit longer latency and, in addition, can relate to many aspects of movement in the environment and not just to our own arm movements. Therefore, the motor system may not always find visual movement cues as relevant for predictive control of dynamics.NEW & NOTEWORTHY This research uncovers, for the first time, how visual and proprioceptive sensory cues affect motor learning as a function of the pause or "dwell time" in two-part movements. The study has shown that visual lead-in movement cues lose their effectiveness sooner than passive lead-in movement cues as dwell time increases. By revealing the modality-dependent nature of sensory information, this study enhances our understanding of motor control and opens new possibilities for improving therapeutic interventions.

A multi-subject and multi-session EEG dataset for modelling human visual object recognition

We share a multi-subject and multi-session (MSS) dataset with 122-channel electroencephalographic (EEG) signals collected from 32 human participants. The data was obtained during serial visual presentation experiments in two paradigms. Dataset of first paradigm consists of around 800,000 trials presenting stimulus sequences at 5 Hz. Dataset of second paradigm comprises around 40,000 trials displaying each image for 1 second. Each participant completed between 1 to 5 sessions on different days, and each session lasted for approximately 1.5 hours of EEG recording. The stimulus set used in the experiments included 10,000 images, with 500 images per class, manually selected from PASCAL and ImageNet image databases. The MSS dataset can be useful for various studies, including but not limited to (1) exploring the characteristics of EEG visual response, (2) comparing the differences in EEG response of different visual paradigms, and (3) designing machine learning algorithms for cross-subject and cross-session brain-computer interfaces (BCIs) using EEG data from multiple subjects and sessions.

Enhanced individual difference of functional brain network induced by volitional eyes closing

Volitional eyes closing (EC) can promote the interoceptive thoughts that vary considerably among individuals. Although this behavior is known to recruit a large-scale brain network as its neural underpinning, individual variability in such network recruitment remains unexplored. Here, we compared the intersubject variability in functional connectivity (IVFC) between the EC and eyes opening conditions. It was found that the IVFC significantly increased during the EC condition, which could be replicated in different public datasets and multi-resolution parcellations. Moreover, the EC-enhanced IVFC focused on selective subsets of FCs, with predominant impact on the default-mode, dorsal attention, and visual networks. Finally, a positive relationship was discovered between EC-enhanced IVFC and deep involvement in the task-unrelated thoughts that was measured with an additional dataset. Collectively, these results suggested that enhanced individual difference characterize the functional network of volitional EC, with widespread impact on cognitive systems and potential connection to task-unrelated thoughts.

Disorders of Higher-order Visual Function

OBJECTIVE

This article provides an overview of disorders of higher-order visual function, encompassing key clinical features, methods for clinical assessment, anatomic localization, and etiologies associated with these disorders. A review of the organization and properties of the brain's visual system is introduced to enhance understanding and facilitate clinical recognition of higher-order visual dysfunction.

LATEST DEVELOPMENTS

Advances in the visual neurosciences have increased our understanding of the underlying properties of visual neurons. New therapies are available to treat diseases that impact cortical neurons and their white matter connections. Thus, recognizing the signs and symptoms of these disorders and using the proper assessment tools to measure dysfunction are essential for preventing disability.

ESSENTIAL POINTS

Functional specialization for distinct visual features defines higher-order visual regions and their corresponding networks. Damage to specialized regions along the occipitoparietal pathway leads to impaired motion processing and visuospatial perception, whereas damage to the occipitotemporal regions results in visual agnosia, including impaired color, object, and facial recognition. Patients experiencing higher-order visual dysfunction do not express symptoms significantly different from those with ocular disorders. Identifying higher-order visual dysfunction requires knowledge of the anatomy and visual properties of neurons in these regions. Assessment of higher-order visual functions can be incorporated into the neurologic mental status examination and prevent delays in diagnosis.

The leftmost digit change induces a decrease in brain activity related to visuospatial processing: An fMRI study of the price ending effect

Consumers perceive prices that have been slightly reduced from round price as irrationally cheap. This price ending effect is thought to be driven primarily by two factors: the left-digit effect which occurs when a small price drop changes the leftmost digit, and the image effect which stems from the symbolic association of a particular price ending with low prices or sales. Our study aimed to investigate the neural basis of these irrational effects on perceived cheapness using functional magnetic resonance imaging (fMRI). We used five price values in Yen (197, 198, 201, 202, 206; Japanese consumers tend to perceive prices ending in the number 8 as cheap) for fMRI experiment. Participants were asked to rate the price value of a product. The "left-digit effect" was observed based on the deactivation in brain regions associated with visuospatial processing including the left lingual gyrus and posterior middle temporal gyrus, and the right dorsal posterior precuneus and anterior precuneus. From these regions, the degree of deactivation in the right dorsal posterior precuneus was negatively correlated with the irrational perception of cheapness. Furthermore, this region showed negative functional connectivity with the dorsal striatal regions. No regions were found with "the image effect". Our results suggested that a decrease in activity in the regions associated with visuospatial processing suggests that changes in the leftmost digits alter the level of visuospatial attention towards the price, leading to an underestimation of the payment amount. This reduced attention might activate the dorsal striatum driving unconscious purchasing.

Large-scale functional network connectivity alterations in adolescents with major depression and non-suicidal self-injury

Non-suicidal self-injury (NSSI) is prevalent among adolescent populations worldwide, yet its neuropathological mechanisms remain unclear. This study aimed to investigate brain functional differences in NSSI patients by utilizing large-scale functional networks and examining their correlation with clinical outcomes. Cross-sectional clinical and functional magnetic resonance imaging (fMRI) data were collected from 42 patients and 47 healthy controls. Independent component analysis (ICA) was utilized to investigate changes in both intra-network and inter-network functional connectivity. We then investigated the potential association between functional network connectivity and clinical self-injurious behavior. The results revealed significant abnormalities in intra-network functional connectivity within the left middle cingulum gyrus, right angular gyrus, and middle frontal gyrus in patients with NSSI. Additionally, we found altered inter-network connectivity patterns, particularly between higher-order cognitive networks and primary sensory networks, suggesting potential disruptions in multisensory integration and emotional regulation in these patients. This study revealed significant alterations in large-scale functional network connectivity in adolescents with depression and NSSI, particularly in networks related to emotion regulation and cognitive control. These findings provide novel perspectives on the neurobiological mechanisms of NSSI and suggest possible avenues for early intervention and treatment.

A bioinspired in-materia analog photoelectronic reservoir computing for human action processing

Current computer vision is data-intensive and faces bottlenecks in shrinking computational costs. Incorporating physics into a bioinspired visual system is promising to offer unprecedented energy efficiency, while the mismatch between physical dynamics and bioinspired algorithms makes the processing of real-world samples rather challenging. Here, we report a bioinspired in-materia analogue photoelectronic reservoir computing for dynamic vision processing. Such system is built based on InGaZnO photoelectronic synaptic transistors as the reservoir and a TaOX-based memristor array as the output layer. A receptive field inspired encoding scheme is implemented, simplifying the feature extraction process. High recognition accuracies (>90%) on four motion recognition datasets are achieved based on such system. Furthermore, falling behaviors recognition is also verified by our system with low energy consumption for processing per action (~45.78 μJ) which outperforms most previous reports on human action processing. Our results are of profound potential for advancing computer vision based on neuromorphic electronics.

Long-term consumption of green tea protects the mental health of middle-aged and older adult men by improving inflammation levels

Background

Middle-aged and older adult men are at a heightened risk of depression. Green tea, as a popular beverage, has drawn widespread attention for its health benefits. However, there remains controversy over the effects of green tea on combating depression and regulating hormones.

Objective

This study aimed to investigate the effects of long-term green tea consumption on depression levels, hormones, and brain structure in, middle-aged and older adult men.

Methods

A total of 280 volunteers participated in the study, divided into a tea-drinking group and a control group. Basic demographic information and biological marker data, as well as MRI data from some of the volunteers, were collected. A controlled study was conducted to explore the effects of long-term tea drinking on them.

Results

BMI (p = 0.002), depression level (p = 0.003), insomnia severity (p = 0.008), and systemic inflammation index (p = 0.009) were significantly lower in the tea drinking group, and their testosterone levels were significantly higher than those in the control group (p = 0.001). Moreover, GM volume in the right precuneus in the control group was significantly reduced compared with that in the tea drinking group.

Conclusion

Long-term tea consumption helps reduce BMI and increase testosterone levels in middle-aged and older adult men, and it can also reduce their risk of depression by lowering inflammation and improving sleep quality. Additionally, long-term tea consumption may have the potential to delay brain aging in middle-aged and older adult men.

Dynamic Evolution of EEG Complexity in Schizophrenia Across Cognitive Tasks

Schizophrenia is characterized by widespread disruptions in neural connectivity and dynamic modulation. Traditional EEG analyses often rely on static or averaged measures, which may overlook the temporal evolution of neural complexity across cognitive demands. This study employed Higuchi Fractal Dimension, a non-linear measure of signal complexity, to examine the temporal dynamics of EEG activity across five cortical regions (central, frontal, occipital, parietal, and temporal lobes) during an attentional and a memory-based task in individuals diagnosed with schizophrenia and healthy controls. A permutation-based topographic analysis of variance revealed significant differences in neural complexity between tasks and groups. In the control group, results showed a consistent pattern of higher neural complexity during the attentional task across the different brain regions (except during a few moments in the temporal and occipital regions). This pattern of differentiation in complexity between the attentional and memory tasks reflects healthy individuals' ability to dynamically modulate neural activity based on task-specific requirements. In contrast, the group of patients with schizophrenia exhibited inconsistent patterns of differences in complexity between tasks over time across all neural regions. That is, differences in complexity between tasks varies across time intervals, being sometimes higher in the attentional task and other times higher in the memory task (especially in the central, frontal, and temporal regions). This inconsistent pattern in patients can explain reduced task-specific modulation of EEG complexity in schizophrenia, and suggests a disruption in the modulation of neural activity on function of task demands. These findings underscore the importance of analyzing the temporal dynamics of EEG complexity to capture task-specific neural modulation.

Vision of objects happens faster and earlier for location than for identity

Visual perception of objects requires the integration of separate independent stimulus features, such as object identity and location. We ask whether the location and the identity of an object are processed with different efficiency for being consciously recognized and reported. Participants viewed a target letter at one out of several locations that were terminated by pattern masks at all possible locations. Participants reported the location of the target and/or its letter identity. Report performance as a function of the target duration before the mask is enabled to estimate the speed of visual processing and the minimum duration for processing to start. Visual processing was faster and started earlier for spatial location than for object identity, even though the processing of the features was (stochastically) independent. Together, these findings reveal an intrinsic preference of the human visual system for the perceptual processing of space as opposed to visual features such as categorical identity.

Functional MRI for stereoscopic vision analysis: an experimental design

PURPOSE

The aim was to establish a functional MRI protocol for analyzing human stereoscopic vision in clinical practice. The feasibility was established in a cohort of 9 healthy subjects to determine the functional cortical areas responsible for virtually relief vision.

METHODS

Nine healthy right-handed subjects underwent orthoptic examination and functional MRI. The activation paradigms used were based on a block sequence with the projection of static and dynamic 2D and 3D test patterns during three experiments. The test patterns were projected through two separate eyepieces to create stereoscopic vision. SPM software was used for post-processing and data analysis.

RESULTS

Among the three different test patterns used, the second, which corresponded to a static high-relief image of a billiard, appeared to be significant for identifying cortical area activation during stereoscopy. In the group analysis, only areas V3A and V6 showed statistically significant activation. Individual analysis revealed activation of the rostral IPS and V5/MT+.

CONCLUSION

More data is needed to determine the precise cortical area of activation for stereoscopy. This study proposes a useful and accessible method for functional MRI analysis of stereoscopy.

Neural processing of naturalistic audiovisual events in space and time

Our brain seamlessly integrates distinct sensory information to form a coherent percept. However, when real-world audiovisual events are perceived, the specific brain regions and timings for processing different levels of information remain less investigated. To address that, we curated naturalistic videos and recorded functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data when participants viewed videos with accompanying sounds. Our findings reveal early asymmetrical cross-modal interaction, with acoustic information represented in both early visual and auditory regions, while visual information only identified in visual cortices. The visual and auditory features were processed with similar onset but different temporal dynamics. High-level categorical and semantic information emerged in multisensory association areas later in time, indicating late cross-modal integration and its distinct role in converging conceptual information. Comparing neural representations to a two-branch deep neural network model highlighted the necessity of early cross-modal connections to build a biologically plausible model of audiovisual perception. With EEG-fMRI fusion, we provided a spatiotemporally resolved account of neural activity during the processing of naturalistic audiovisual stimuli.

Explaining cognitive function in multiple sclerosis through networks of grey and white matter features: a joint independent component analysis

Cognitive impairment (CI) in multiple sclerosis (MS) is only partially explained by whole-brain volume measures, but independent component analysis (ICA) can extract regional patterns of damage in grey matter (GM) or white matter (WM) that have proven more closely associated with CI. Pathology in GM and WM occurs in parallel, and so patterns can span both. This study assessed whether joint-ICA of GM and WM features better explained cognitive function compared to single-tissue ICA. 89 people with MS underwent cognitive testing and magnetic resonance imaging. Structural T1 and diffusion-weighted images were used to measure GM volumes and WM connectomes (based on fractional anisotropy weighted by the number of streamlines). ICA was performed for each tissue type separately and as joint-ICA. For each tissue type and joint-ICA, 20 components were extracted. In stepwise linear regression models, joint-ICA components were significantly associated with all cognitive domains. Joint-ICA showed the highest variance explained for executive function (Adjusted R2 = 0.35) and visual memory (Adjusted R2 = 0.30), while WM-ICA explained the highest variance for working memory (Adjusted R2 = 0.23). No significant differences were found between joint-ICA and single-tissue ICA in information processing speed or verbal memory. This is the first MS study to explore GM and WM features in a joint-ICA approach and shows that joint-ICA outperforms single-tissue analysis in some, but not all cognitive domains. This highlights that cognitive domains are differentially affected by tissue-specific features in MS and that processes spanning GM and WM should be considered when explaining cognition.

Spatial and temporal patterns of brain neural activity mediating human thermal sensations

This study aimed to elucidate the spatial and temporal patterns of brain neural activity that are associated with cold and hot sensations. Participants (n = 20) sat in a controlled room with their eyes closed and received local thermal stimuli to the right fingers using a Peltier apparatus. The thermal stimuli were repeated 40 times using a paired-thermal stimulus paradigm, comprising a 15 s-reference stimulus (32 °C), followed by 10 s-conditioned stimuli (24 °C and 40 °C, cold and hot conditions, respectively), for which 15-channel electroencephalography (EEG) signals were continuously monitored. To identify the patterns of brain neural activity, an independent component (IC) analysis was applied to the preprocessed EEG data. The equivalent current dipole locations were estimated, followed by clustering of the ICs with a dipole residual variance of <15 %. Subsequently, event-related spectral perturbations were analyzed in each identified cluster to calculate the power changes across specific frequency ranges. The right precentral gyrus, precuneus, medial frontal gyrus, middle frontal gyrus, superior frontal gyrus, cuneus, cingulate gyrus, left precentral gyrus, middle occipital gyrus, and cingulate gyrus were activated in both cold and hot conditions. In most activated regions, EEG power temporal changes were observed across the frequency ranges and were different between the two conditions. These results may suggest that cold and hot sensations are processed through different temporal brain neural activity patterns in overlapping brain regions.

The association between rapid antiretroviral therapy initiation and brain structure and function based on multimodal magnetic resonance imaging in HIV-positive men who have sex with men

An increasing number of treatment guidelines recommend rapid initiation of antiretroviral therapy (ART) after the diagnosis of human immunodeficiency virus (HIV) infection. However, data on the association between rapid ART initiation and alterations in brain structure and function remain limited in people with HIV (PWH). A cross-sectional analysis was conducted on HIV-positive men who have sex with men (MSM) undergoing ART. Fifty-four participants who started ART within 30 days of confirmed HIV diagnosis (rapid ART group) and 20 participants who started ART more than 6 months of confirmed HIV diagnosis (non-rapid ART group) completed clinical assessments and multimodal magnetic resonance imaging scans to obtain both anatomical and resting-state functional images. Compared to PWH in the non-rapid ART group, those in the rapid ART group exhibited a greater total gray matter volume (P = 0.001) and functional changes, including a lower amplitude of low-frequency fluctuations in the left angular gyrus (P < 0.001). Moreover, the results of the main effects and interactions indicated that rapid ART initiation had main effects on major imaging outcomes. The validation analysis results in participants who started ART within 7 days of confirmed HIV diagnosis generally corroborated and complemented the aforementioned findings. Our study demonstrated brain gray matter volume atrophy and functional alterations in PWH of the non-rapid ART group compared to those in the rapid ART group, suggesting that rapid ART initiation may be associated with better brain structure and function changes in HIV-positive MSM.

Artificial Visual System for Stereo-Orientation Recognition Based on Hubel-Wiesel Model

Stereo-orientation selectivity is a fundamental neural mechanism in the brain that plays a crucial role in perception. However, due to the recognition process of high-dimensional spatial information commonly occurring in high-order cortex, we still know little about the mechanisms underlying stereo-orientation selectivity and lack a modeling strategy. A classical explanation for the mechanism of two-dimensional orientation selectivity within the primary visual cortex is based on the Hubel-Wiesel model, a cascading neural connection structure. The local-to-global information aggregation thought within the Hubel-Wiesel model not only contributed to neurophysiology but also inspired the development of computer vision fields. In this paper, we provide a clear and efficient conceptual understanding of stereo-orientation selectivity and propose a quantitative explanation for its generation based on the thought of local-to-global information aggregation within the Hubel-Wiesel model and develop an artificial visual system (AVS) for stereo-orientation recognition. Our approach involves modeling depth selective cells to receive depth information, simple stereo-orientation selective cells for combining distinct depth information inputs to generate various local stereo-orientation selectivity, and complex stereo-orientation selective cells responsible for integrating the same local information to generate global stereo-orientation selectivity. Simulation results demonstrate that our AVS is effective in stereo-orientation recognition and robust against spatial noise jitters. AVS achieved an overall over 90% accuracy on noise data in orientation recognition tasks, significantly outperforming deep models. In addition, the AVS contributes to enhancing deep models' performance, robustness, and stability in 3D object recognition tasks. Notably, AVS enhanced the TransNeXt model in improving its overall performance from 73.1% to 97.2% on the 3D-MNIST dataset and from 56.1% to 86.4% on the 3D-Fashion-MNIST dataset. Our explanation for the generation of stereo-orientation selectivity offers a reliable, explainable, and robust approach for extracting spatial features and provides a straightforward modeling method for neural computation research.

Understanding gender differences in reasoning and specific paradigm using meta-analysis of neuroimaging

Reasoning is a fundamental cognitive process that allows individuals to make inferences, decisions, and solve problems. Understanding the neural mechanisms of reasoning and the gender differences in these mechanisms is crucial for comprehending the neural foundations of reasoning and promoting gender equality in cognitive processing. This study conducted an Activation Likelihood Estimation (ALE) meta-analysis of 275 studies, revealing that reasoning involves multiple brain regions, including the parts of frontal, parietal, occipital, temporal lobes, limbic system, and subcortical areas. These findings indicate that reasoning is a complex cognitive process requiring the coordinated activity of multiple brain regions. Additionally, 25 studies focusing on the Wisconsin Card Sorting Test (WCST) paradigm confirmed the importance of these regions in reasoning processes. The gender-specific activation results indicate that males and females utilize different neural networks during reasoning and WCST tasks. While significant differences exist in specific regions, the overall activation patterns do not show marked gender differences. Notably, females exhibit greater activation in the limbic system compared to males, suggesting that emotional states may play a more prominent role for females when engaging in reasoning tasks.

Seeing and visualizing across the hemispheres

Despite our subjective experience of a largely symmetric visual world, the human brain exhibits varying patterns and degrees of hemispheric asymmetry in distinct processes of visual cognition. This chapter reviews behavioral and neuroimaging evidence from neurotypical individuals and neurological patients, concerning functional asymmetries between the right hemisphere (RH) and the left hemisphere (LH) in visual object processing and mental imagery. Hierarchical perception shows RH preference for global processing and LH preference for local processing. At later stages of visual object processing, RH-based circuits exhibit a relative advantage in terms of perceptual integration, with a subsequent shift toward LH-based circuits for processing at higher conceptual and semantic levels. In voluntary visual mental imagery, circuits in the LH ventral temporal cortex play a pivotal role in transitioning from object meaning to simulated visualization. These hemispheric asymmetries in visual object processing might, in part, be influenced by the overall need to minimize wiring, coupled with the presence of distinct specialized networks within each hemisphere, such as the RH attention networks and the LH language networks. From a broader viewpoint, the evidence examined in this chapter indicates that visual object processing involves the interactions of large-scale cortical circuits within and between the hemispheres.

Functional resilience of the neural visual recognition system post-pediatric occipitotemporal resection

Neural representations for visual stimuli typically emerge with a bilateral distribution across occipitotemporal cortex (OTC)? Pediatric patients undergoing unilateral OTC resection offer an opportunity to evaluate whether representations for visual stimulus individuation can sufficiently develop in a single OTC. Here, we assessed the non-resected hemisphere of patients with pediatric resection within (n = 9) and outside (n = 12) OTC, as well as healthy controls' two hemispheres (n = 21). Using functional magnetic resonance imaging, we mapped category selectivity (CS), and representations for visual stimulus individuation (for faces, objects, and words) with repetition suppression (RS). There were no group differences in CS or RS. However, OTC resection patients' accuracy on face and object (but not word) recognition was lower than controls'. The neuroimaging results highlight neural resilience following damage to the contralateral homologue. Critically, however, a single OTC does not suffice for typical behavior, and, thereby, implicates the necessary contributions of bilateral OTC for visual recognition.

Development of Spatial Memory: A Behavioral Study

Although spatial memory has been widely studied in rodents, developmental studies involving humans are limited in number and sample size. We designed and studied the validity of two simple experimental setups for the evaluation of spatial memory and navigation development. The dataset of this study was composed of 496 schoolchildren, from 4 to 15 years old. Participants were tested blindfolded on their ability to navigate in a square area between three stool stations while performing an item-collecting task, having observed the experimental space and procedure (Test 1) or having, in addition, executed the task open-eyed (Test 2). The performance times were analyzed to identify age-specific differences. Parametric methods, including the one-way ANOVA and independent samples t-test, were employed. Statistically significant differences were observed in the mean performance time among age groups, as well as within the same age groups when comparing Test 1 and Test 2. Our results revealed a performance improvement with aging for both functions and showed that spatial memory and spatial navigation develop throughout childhood and puberty and interact during development. When children integrate visual stimuli with other sensory inputs, they can form stronger spatial memories, thereby enhancing their navigation skills. The proposed experimental setup is considered feasible and can be used for behavioral studies of navigation-related memory in children and beyond with appropriate adaptations, allowing for large-scale assessment.

Zero-shot counting with a dual-stream neural network model

To understand a visual scene, observers need to both recognize objects and encode relational structure. For example, a scene comprising three apples requires the observer to encode concepts of "apple" and "three." In the primate brain, these functions rely on dual (ventral and dorsal) processing streams. Object recognition in primates has been successfully modeled with deep neural networks, but how scene structure (including numerosity) is encoded remains poorly understood. Here, we built a deep learning model, based on the dual-stream architecture of the primate brain, which is able to count items "zero-shot"-even if the objects themselves are unfamiliar. Our dual-stream network forms spatial response fields and lognormal number codes that resemble those observed in the macaque posterior parietal cortex. The dual-stream network also makes successful predictions about human counting behavior. Our results provide evidence for an enactive theory of the role of the posterior parietal cortex in visual scene understanding.

The striatal compartments, striosome and matrix, are embedded in largely distinct resting state functional networks

The striatum is divided into two interdigitated tissue compartments, the striosome and matrix. These compartments exhibit distinct anatomical, neurochemical, and pharmacological characteristics and have separable roles in motor and mood functions. Little is known about the functions of these compartments in humans. While compartment-specific roles in neuropsychiatric diseases have been hypothesized, they have yet to be directly tested. Investigating compartment-specific functions is crucial for understanding the symptoms produced by striatal injury, and to elucidating the roles of each compartment in healthy human skills and behaviors. We mapped the functional networks of striosome and matrix in humans in vivo. We utilized a diverse cohort of 674 healthy adults, derived from the Human Connectome Project, including all subjects with complete diffusion and functional MRI data and excluding subjects with substance use disorders. We identified striatal voxels with striosome-like and matrix-like structural connectivity using probabilistic diffusion tractography. We then investigated resting state functional connectivity (rsFC) using these compartment-like voxels as seeds. We found widespread differences in rsFC between striosome-like and matrix-like seeds (p < 0.05, FWE corrected for multiple comparisons), suggesting that striosome and matrix occupy distinct functional networks. Slightly shifting seed voxel locations (<4 mm) eliminated these rsFC differences, underscoring the anatomic precision of these networks. Striosome-seeded networks exhibited ipsilateral dominance; matrix-seeded networks had contralateral dominance. Next, we assessed compartment-specific engagement with the triple-network model (default mode, salience, and frontoparietal networks). Striosome-like voxels dominated rsFC with the default mode network bilaterally. The anterior insula (a primary node in the salience network) had higher rsFC with striosome-like voxels. The inferior and middle frontal cortices (primary nodes, frontoparietal network) had stronger rsFC with matrix-like voxels on the left, and striosome-like voxels on the right. Since striosome-like and matrix-like voxels occupy highly segregated rsFC networks, striosome-selective injury may produce different motor, cognitive, and behavioral symptoms than matrix-selective injury. Moreover, compartment-specific rsFC abnormalities may be identifiable before disease-related structural injuries are evident. Localizing rsFC differences provides an anatomic substrate for understanding how the tissue-level organization of the striatum underpins complex brain networks, and how compartment-specific injury may contribute to the symptoms of specific neuropsychiatric disorders.

Cross-sectional and longitudinal changes in category-selectivity in visual cortex following pediatric cortical resection

The topographic organization of category-selective responses in human ventral occipitotemporal cortex (VOTC) and its relationship to regions subserving language functions is remarkably uniform across individuals. This arrangement is thought to result from the clustering of neurons responding to similar inputs, constrained by intrinsic architecture and tuned by experience. We examined the malleability of this organization in individuals with unilateral resection of VOTC during childhood for the management of drug-resistant epilepsy. In cross-sectional and longitudinal functional imaging studies, we compared the topography and neural representations of 17 category-selective regions in individuals with a VOTC resection, a 'control patient' with resection outside VOTC, and typically developing matched controls. We demonstrated both adherence to and deviation from the standard topography and uncovered fine-grained competitive dynamics between word- and face-selectivity over time in the single, preserved VOTC. The findings elucidate the nature and extent of cortical plasticity and highlight the potential for remodeling of extrastriate architecture and function.

Encoding models for developmental cognitive computational neuroscience: Promise, challenges, and potential

Cognitive computational neuroscience has received broad attention in recent years as an emerging area integrating cognitive science, neuroscience, and artificial intelligence. At the heart of this field, approaches using encoding models allow for explaining brain activity from latent and high-dimensional features, including artificial neural networks. With the notable exception of temporal response function models that are applied to electroencephalography, most prior studies have focused on adult subjects, making it difficult to capture how brain representations change with learning and development. Here, we argue that future developmental cognitive neuroscience studies would benefit from approaches relying on encoding models. We provide an overview of encoding models used in adult functional magnetic resonance imaging research. This research has notably used data with a small number of subjects, but with a large number of samples per subject. Studies using encoding models also generally require task-based neuroimaging data. Though these represent challenges for developmental studies, we argue that these challenges may be overcome by using functional alignment techniques and naturalistic paradigms. These methods would facilitate encoding model analysis in developmental neuroimaging research, which may lead to important theoretical advances.

Moving and Static Faces, Bodies, Objects, and Scenes Are Differentially Represented across the Three Visual Pathways

Models of human cortex propose the existence of neuroanatomical pathways specialized for different behavioral functions. These pathways include a ventral pathway for object recognition, a dorsal pathway for performing visually guided physical actions, and a recently proposed third pathway for social perception. In the current study, we tested the hypothesis that different categories of moving stimuli are differentially processed across the dorsal and third pathways according to their behavioral implications. Human participants (n = 30) were scanned with fMRI while viewing moving and static stimuli from four categories (faces, bodies, scenes, and objects). A whole-brain group analysis showed that moving bodies and moving objects increased neural responses in the bilateral posterior parietal cortex, parts of the dorsal pathway. By contrast, moving faces and moving bodies increased neural responses, the superior temporal sulcus, part of the third pathway. This pattern of results was also supported by a separate ROI analysis showing that moving stimuli produced more robust neural responses for all visual object categories, particularly in lateral and dorsal brain areas. Our results suggest that dynamic naturalistic stimuli from different categories are routed in specific visual pathways that process dissociable behavioral functions.

Orthographic and phonological processing in the left ventral occipitotemporal cortex during Chinese word reading

The left ventral occipitotemporal cortex (lvOT) has been consistently identified as a crucial structure in word reading, and its function varies across subregions. Nevertheless, the specific function of the lvOT and its subregions remains controversial because the obvious grapheme-to-phoneme correspondence rules of alphabetic languages make it difficult to disentangle the contributions of orthography and phonology to neural activations. To explore information processing in lvOT subregions, the present study manipulated the orthography and phonology in a factorial design and used the fMRI rapid adaptation paradigm. The results revealed a posterior-to-anterior functional gradient in lvOT in Chinese word reading and specified that the functional transition from sublexical to lexical processing occurred in the middle subregion close to the classic VWFA. More importantly, we found that the middle and posterior subregions of lvOT are responsible for processing both orthographic and phonological information during Chinese word reading. These results elaborated the function of the lvOT in Chinese word reading.

Correlates of implicit semantic processing as revealed by representational similarity analysis applied to EEG

Most researchers agree that some stages of object recognition can proceed implicitly. Implicit recognition occurs when an object is automatically and unintentionally encoded and represented in the brain even though the object is irrelevant to the current task. No consensus has been reached as to what level of semantic abstraction processing can go implicitly. An informative method to explore the level of abstraction and the time courses of informational content in neural representations is representational similarity analysis (RSA). Here, we apply RSA to EEG data recorded while participants processed semantics of visually presented objects. Explicit focus on semantics was given when participants classified images of objects as manmade or natural. For implicit processing of semantics, participants judged the location of images on the screen. The category animate/inanimate as well as more concrete categories (e.g., birds, fruit, musical instruments, etc.) are processed implicitly whereas the category manmade/natural is not processed implicitly.

The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder

Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression, defined in this context by a state of persistently low valence, may arise from various factors-including inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. Integrating algorithmic, dynamical systems, and neurobiological concepts, we map the agent model to brain circuits and functional networks, framing potential etiological routes and linking with depression biotypes. Finally, we explore how brain stimulation, psychotherapy, and plasticity-enhancing compounds such as psychedelics can synergistically repair neural circuits and optimize therapies using personalized computational models.

Convolutional neural networks uncover the dynamics of human visual memory representations over time

The ability to accurately retrieve visual details of past events is a fundamental cognitive function relevant for daily life. While a visual stimulus contains an abundance of information, only some of it is later encoded into long-term memory representations. However, an ongoing challenge has been to isolate memory representations that integrate various visual features and uncover their dynamics over time. To address this question, we leveraged a novel combination of empirical and computational frameworks based on the hierarchal structure of convolutional neural networks and their correspondence to human visual processing. This enabled to reveal the contribution of different levels of visual representations to memory strength and their dynamics over time. Visual memory strength was measured with distractors selected based on their shared similarity to the target memory along low or high layers of the convolutional neural network hierarchy. The results show that visual working memory relies similarly on low and high-level visual representations. However, already after a few minutes and on to the next day, visual memory relies more strongly on high-level visual representations. These findings suggest that visual representations transform from a distributed to a stronger high-level conceptual representation, providing novel insights into the dynamics of visual memory over time.

Magnetoencephalographic brain activity evoked by the optic-flow task is correlated with β-amyloid burden and parahippocampal atrophy

Visuospatial perception is often impaired in people with Alzheimer's disease (AD). Because visuospatial information is thought to be processed in the visual dorsal stream, it is believed that brain activities in the dorsal stream will be altered in AD patients. In this study, we investigated whether regional brain activity related to visuospatial perception were associated with AD progression markers. An optic-flow task, which activates the dorsal stream associated with visuospatial perception, was performed, and the brain activities evoked by the task were evaluated using magnetoencephalography (MEG). First, we evaluated the responses to optic-flow stimuli in 21 cognitively unimpaired participants and determined the regions of interest (ROIs) where optic-flow activities were activated. Task-related activations were observed in 14 cortical regions including the dorsal stream: the right and left medial ventral occipital cortex (MVOcC), lateral occipital cortex (LOcC), precuneus (Pcun), inferior parietal lobule (IPL), superior parietal lobule (SPL), posterior superior temporal sulcus (pSTS), and fusiform gyri (FuG). Next, we performed correlation analyses between task-related activity in each ROI and two AD progression markers, global amyloid burden and parahippocampal gyrus (PHG) volume, for 25 participants who underwent amyloid positron emission tomography (PET) scans. We found that the global amyloid burden was negatively correlated with task-related activity in the left MVOcC and right SPL [r = -0.488 (p = 0.013) and r = -0.421 (p = 0.038), respectively]. Furthermore, significant positive correlations were observed between PHG volume and task-related activity in both the left and right SPL [r = 0.500 (p = 0.011) and r = 0.549 (p = 0.005), respectively]. Since the SPL is known to be responsible for visuospatial perception, these results suggest that MEG neuronal activity of patients performing the optic-flow activity can detect changes in brain activity associated with visuospatial impairment related to AD.

Registered Report Stage II: Decoding the category information from evoked potentials to visible and invisible visual objects

Previous studies that use decoding methods and EEG to investigate the neural representation of the category information of visual objects focused mainly on consciously processed visual objects. It remains unclear whether the category information of unconsciously processed visual objects can be decoded and whether the decoding performance is different for consciously and unconsciously processed visual objects. The present study compared the neural decoding of the animacy category of visible and invisible visual objects via EEG and decoding methods. The results revealed that the animacy of visible visual objects could be decoded above the chance level by the P200, N300, and N400, but not by the early N/P100. However, the animacy of invisible visual objects could not be decoded above the chance level by neither early nor late ERP components. The decoding accuracy was greater for visible visual objects than that for invisible visual objects for the P200, N300 and N400. These results suggested that access to animacy category information for visual objects requires conscious processing.

Understanding contrast perception in amblyopia: a psychophysical analysis of the ON and OFF visual pathways

Purpose

The study aimed to explore potential discrepancies in contrast sensitivity in the ON and OFF visual pathways among individuals with amblyopia compared to controls.

Methods

Eleven adult amblyopes (26.2 ± 4.4 [SD] years old) and 10 controls (24.6 ± 0.8 years old) with normal or corrected to normal visual acuity (logMAR VA ≤ 0) participated in this study. Using the quick contrast sensitivity function (qCSF) algorithm, we measured balanced CSF which would stimulate the ON and OFF pathways unselectively, and CSFs for increments and decrements that would selectively stimulate the ON and OFF visual pathways. Contrast sensitivity and area under log contrast sensitivity function were extracted for statistical analysis.

Results

For the balanced CSF, we found significant interocular differences in sensitivity and area under log contrast sensitivity function in both amblyopes [F(1,10) = 74.992, p < 0.001] and controls [F(1,9) = 35.6, p < 0.001], while such differences were more pronounced in amblyopes than in controls. For increment and decrement CSFs, we found that the increment sensitivity (p = 0.038) and area under log contrast sensitivity function (p = 0.001) were significantly lower than the decrement in the amblyopic eye. Such differences between increment and decrement CSFs were not observed in the fellow eye of the amblyopes or in the controls.

Conclusion

There is a subtle difference in the contrast sensitivity of the amblyopic eye when exposed to stimulation in the ON and OFF pathways.

Minimal exposure durations reveal visual processing priorities for different stimulus attributes

Human vision can detect a single photon, but the minimal exposure required to extract meaning from stimulation remains unknown. This requirement cannot be characterised by stimulus energy, because the system is differentially sensitive to attributes defined by configuration rather than physical amplitude. Determining minimal exposure durations required for processing various stimulus attributes can thus reveal the system's priorities. Using a tachistoscope enabling arbitrarily brief displays, we establish minimal durations for processing human faces, a stimulus category whose perception is associated with several well-characterised behavioural and neural markers. Neural and psychophysical measures show a sequence of distinct minimal exposures for stimulation detection, object-level detection, face-specific processing, and emotion-specific processing. Resolving ongoing debates, face orientation affects minimal exposure but emotional expression does not. Awareness emerges with detection, showing no evidence of subliminal perception. These findings inform theories of visual processing and awareness, elucidating the information to which the visual system is attuned.

A biologically inspired computational model of human ventral temporal cortex

Our minds represent miscellaneous objects in the physical world metaphorically in an abstract and complex high-dimensional object space, which is implemented in a two-dimensional surface of the ventral temporal cortex (VTC) with topologically organized object selectivity. Here we investigated principles guiding the topographical organization of object selectivities in the VTC by constructing a hybrid Self-Organizing Map (SOM) model that harnesses a biologically inspired algorithm of wiring cost minimization and adheres to the constraints of the lateral wiring span of human VTC neurons. In a series of in silico experiments with functional brain neuroimaging and neurophysiological single-unit data from humans and non-human primates, the VTC-SOM predicted the topographical structure of fine-scale category-selective regions (face-, tool-, body-, and place-selective regions) and the boundary in large-scale abstract functional maps (animate vs. inanimate, real-word small-size vs. big-size, central vs. peripheral), with no significant loss in functionality (e.g., categorical selectivity and view-invariant representations). In addition, when the same principle was applied to V1 orientation preferences, a pinwheel-like topology emerged, suggesting the model's broad applicability. In summary, our study illustrates that the simple principle of wiring cost minimization, coupled with the appropriate biological constraint of lateral wiring span, is able to implement the high-dimensional object space in a two-dimensional cortical surface.

Cortical Thickness Correlates of Go/No-go and Motor Sequencing in Mild Cognitive Impairment and Suspected Alzheimer Disease Dementia

BACKGROUND

While the cognitive hallmark of typical Alzheimer disease (AD) is impaired memory consolidation, increasing evidence suggests that the frontal lobes and associated executive functions are also impacted.

OBJECTIVE

We examined two neurobehavioral executive function tasks and associations with cortical thickness in patients diagnosed with mild cognitive impairment (MCI), suspected AD dementia, and a healthy control group.

METHODS

First, we compared group performances on a go/no-go (GNG) task and on Luria's Fist-Edge-Palm (FEP) motor sequencing task. We then examined correlations between neurobehavioral task performance and the thickness of frontal cortical regions, AD signature regions, broader unbiased brain regions, and white matter hyperintensities (WMH).

RESULTS

Participants with MCI performed worse than healthy controls, but better than participants with suspected AD dementia on both tasks. Both GNG and FEP (to a slightly greater extent) tasks showed diffuse associations with most AD signature regions and multiple additional regions within the temporal, parietal, and occipital cortices. Similarly, both tasks showed significant associations with all other cognitive tasks examined. Of the frontal regions examined, only the middle frontal gyrus and pars opercularis were associated with performance on these tasks. Interactions between the precuneus and transtemporal gyri were most predictive of GNG task performance, while the interaction between superior temporal and lingual gyri was most predictive of FEP task performance.

CONCLUSION

This study replicates difficulties with both GNG and FEP tasks in participants with MCI and AD dementia. Both tasks showed widespread associations with the cortical thickness of various brain structures rather than localizing to frontal regions, consistent with the diffuse nature of AD.

Neural Representations of Sensory Uncertainty and Confidence Are Associated with Perceptual Curiosity

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.

Learning, Fast and Slow: Single- and Many-Shot Learning in the Hippocampus

The hippocampus is critical for memory and spatial navigation. The ability to map novel environments, as well as more abstract conceptual relationships, is fundamental to the cognitive flexibility that humans and other animals require to survive in a dynamic world. In this review, we survey recent advances in our understanding of how this flexibility is implemented anatomically and functionally by hippocampal circuitry, during both active exploration (online) and rest (offline). We discuss the advantages and limitations of spike timing-dependent plasticity and the more recently discovered behavioral timescale synaptic plasticity in supporting distinct learning modes in the hippocampus. Finally, we suggest complementary roles for these plasticity types in explaining many-shot and single-shot learning in the hippocampus and discuss how these rules could work together to support the learning of cognitive maps.

Daily Cannabidiol Administration for 10 Weeks Modulates Hippocampal and Amygdalar Resting-State Functional Connectivity in Cannabis Users: A Functional Magnetic Resonance Imaging Open-Label Clinical Trial

Introduction: Cannabis use is associated with brain functional changes in regions implicated in prominent neuroscientific theories of addiction. Emerging evidence suggests that cannabidiol (CBD) is neuroprotective and may reverse structural brain changes associated with prolonged heavy cannabis use. In this study, we examine how an ∼10-week exposure of CBD in cannabis users affected resting-state functional connectivity in brain regions functionally altered by cannabis use. Materials and Methods: Eighteen people who use cannabis took part in a ∼10 weeks open-label pragmatic trial of self-administered daily 200 mg CBD in capsules. They were not required to change their cannabis exposure patterns. Participants were assessed at baseline and post-CBD exposure with structural magnetic resonance imaging (MRI) and a functional MRI resting-state task (eyes closed). Seed-based connectivity analyses were run to examine changes in the functional connectivity of a priori regions-the hippocampus and the amygdala. We explored if connectivity changes were associated with cannabinoid exposure (i.e., cumulative cannabis dosage over trial, and plasma CBD concentrations and Δ9-tetrahydrocannabinol (THC) plasma metabolites postexposure), and mental health (i.e., severity of anxiety, depression, and positive psychotic symptom scores), accounting for cigarette exposure in the past month, alcohol standard drinks in the past month and cumulative CBD dose during the trial. Results: Functional connectivity significantly decreased pre-to-post the CBD trial between the anterior hippocampus and precentral gyrus, with a strong effect size (d=1.73). Functional connectivity increased between the amygdala and the lingual gyrus pre-to-post the CBD trial, with a strong effect size (d=1.19). There were no correlations with cannabinoids or mental health symptom scores. Discussion: Prolonged CBD exposure may restore/reduce functional connectivity differences reported in cannabis users. These new findings warrant replication in a larger sample, using robust methodologies-double-blind and placebo-controlled-and in the most vulnerable people who use cannabis, including those with more severe forms of Cannabis Use Disorder and experiencing worse mental health outcomes (e.g., psychosis, depression).

Polygenic Score for Conscientiousness Is a Protective Factor for Reversion from Mild Cognitive Impairment to Normal Cognition

Spontaneous reversion from mild cognitive impairment (MCI) to normal cognition (NC) is little known. Based on the data of the Genetics of Personality Consortium and MCI participants from Alzheimer's Disease Neuroimaging Initiative, the authors investigate the effect of polygenic scores (PGS) for personality traits on the reversion of MCI to NC and its underlying neurobiology. PGS analysis reveals that PGS for conscientiousness (PGS-C) is a protective factor that supports the reversion from MCI to NC. Gene ontology enrichment analysis and tissue-specific enrichment analysis indicate that the protective effect of PGS-C may be attributed to affecting the glutamatergic synapses of subcortical structures, such as hippocampus, amygdala, nucleus accumbens, and caudate nucleus. The structural covariance network (SCN) analysis suggests that the left whole hippocampus and its subfields, and the left whole amygdala and its subnuclei show significantly stronger covariance with several high-cognition relevant brain regions in the MCI reverters compared to the stable MCI participants, which may help illustrate the underlying neural mechanism of the protective effect of PGS-C.

Immediate and long-term brain activation of acupuncture on ischemic stroke patients: an ALE meta-analysis of fMRI studies

Background

Acupuncture, as an alternative and complementary therapy recommended by the World Health Organization for stroke treatment, holds potential in ameliorating neurofunctional deficits induced by ischemic stroke (IS). Understanding the immediate and long-term effects of acupuncture and their interrelation would contribute to a better comprehension of the mechanisms underlying acupuncture efficacy.

Methods

Activation likelihood estimation (ALE) meta-analysis was used to analyze the brain activation patterns reported in 21 relevant functional neuroimaging studies. Among these studies, 12 focused on the immediate brain activation and 9 on the long-term activation. Single dataset analysis were employed to identify both immediate and long-term brain activation of acupuncture treatment in IS patients, while contrast and conjunction analysis were utilized to explore distinctions and connections between the two.

Results

According to the ALE analysis, immediately after acupuncture treatment, IS patients exhibited an enhanced cluster centered around the right precuneus (PCUN) and a reduced cluster centered on the left middle frontal gyrus (MFG). After long-term acupuncture treatment, IS patients showed an enhanced cluster in the left PCUN, along with two reduced clusters in the right insula (INS) and hippocampus (HIP), respectively. Additionally, in comparison to long-term acupuncture treatment, the right angular gyrus (ANG) demonstrated higher ALE scores immediately after acupuncture, whereas long-term acupuncture resulted in higher scores in the left superior parietal gyrus (SPG). The intersecting cluster activated by both of them was located in the left cuneus (CUN).

Conclusion

The findings provide initial insights into both the immediate and long-term brain activation patterns of acupuncture treatment for IS, as well as the intricate interplay between them. Both immediate and long-term acupuncture treatments showed distinct patterns of brain activation, with the left CUN emerging as a crucial regulatory region in their association.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, CRD42023480834.

Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets

In computer vision research, convolutional neural networks (CNNs) have demonstrated remarkable capabilities at extracting patterns from raw pixel data, achieving state-of-the-art recognition accuracy. However, they significantly differ from human visual perception, prioritizing pixel-level correlations and statistical patterns, often overlooking object semantics. To explore this difference, we propose an approach that isolates core visual features crucial for human perception and object recognition: color, texture, and shape. In experiments on three benchmarks-Fruits 360, CIFAR-10, and Fashion MNIST-each visual feature is individually input into a neural network. Results reveal data set-dependent variations in classification accuracy, highlighting that deep learning models tend to learn pixel-level correlations instead of fundamental visual features. To validate this observation, we used various combinations of concatenated visual features as input for a neural network on the CIFAR-10 data set. CNNs excel at learning statistical patterns in images, achieving exceptional performance when training and test data share similar distributions. To substantiate this point, we trained a CNN on CIFAR-10 data set and evaluated its performance on the "dog" class from CIFAR-10 and on an equivalent number of examples from the Stanford Dogs data set. The CNN poor performance on Stanford Dogs images underlines the disparity between deep learning and human visual perception, highlighting the need for models that learn object semantics. Specialized benchmark data sets with controlled variations hold promise for aligning learned representations with human cognition in computer vision research.

Intrinsic functional connectivity mediates the effect of personality traits on depressive symptoms

BACKGROUND

Personality traits have been proposed as risk factors for depressive symptoms. However, the neural mechanism behind these relationships is unclear. This study examined the possible mediating effect of resting-state functional connectivity networks on these relationships.

METHODS

Data from 153 healthy Germans were obtained from the MPI-Leipzig Mind-Brain-Body: Neuroanatomy & Connectivity Protocol database. Network-based statistics were used to identify significant functional connectivity networks that were positively and negatively associated with the personality traits of neuroticism, conscientiousness, and extraversion, with and without demographical covariates. Mediation analyses were performed for each personality trait and depressive symptoms with the significant positive and negative network strengths of the respective personality traits as mediators.

RESULTS

Neuroticism, conscientiousness, and extraversion were significantly correlated with depressive symptoms. Network-based statistics identified patterns of functional connectivity that were significantly associated with neuroticism and conscientiousness. After controlling for demographical covariates, significant conscientiousness-associated and extraversion-associated networks emerged. Mediation analysis concluded that only the neuroticism-positive network mediated the effect of neuroticism on depressive symptoms. When age and sex were controlled, the extraversion-positive network completely mediated the effect of extraversion on depressive symptoms.

CONCLUSIONS

These findings revealed that patterns of intrinsic functional networks predict personality traits and suggest that the relationship between personality traits and depressive symptoms may in part be due to their common patterns of intrinsic functional networks.

Higher-contrast images are better remembered during naturalistic encoding

It is unclear whether memory for images of poorer visibility (as low contrast or small size) will be lower due to weak signals elicited in early visual processing stages, or perhaps better since their processing may entail top-down processes (as effort and attention) associated with deeper encoding. We have recently shown that during naturalistic encoding (free viewing without task-related modulations), for image sizes between 3°-24°, bigger images stimulating more visual system processing resources at early processing stages are better remembered. Similar to size, higher contrast leads to higher activity in early visual processing. Therefore, here we hypothesized that during naturalistic encoding, at critical visibility ranges, higher contrast images will lead to higher signal-to-noise ratio and better signal quality flowing downstream and will thus be better remembered. Indeed, we found that during naturalistic encoding higher contrast images were remembered better than lower contrast ones (~ 15% higher accuracy, ~ 1.58 times better) for images at 7.5-60 RMS contrast range. Although image contrast and size modulate early visual processing very differently, our results further substantiate that at poor visibility ranges, during naturalistic non-instructed visual behavior, physical image dimensions (contributing to image visibility) impact image memory.