Cerebral cortex最新文献

To make optimal decisions, intelligent agents must learn latent environmental states from discrete observations. Bayesian frameworks argue that integration of evidence over time allows us to refine our state belief by reducing uncertainty about alternate possibilities. How is this increasing belief precision during learning reflected in the brain? We propose that temporal neural variability should scale with the degree of reduction of uncertainty during learning. In a sample of 47 healthy adults, we found that BOLD signal variability (SDBOLD, as measured across independent learning trials) indeed compressed with successive exposure to decision-related evidence. Crucially, more accurate participants expressed greater SDBOLD compression primarily in default mode network regions, possibly reflecting the increasing precision of their latent state belief during more efficient learning. Further, computational modeling of behavior suggested that more accurate subjects held a more unbiased (flatter) prior belief over possible states that allowed for larger uncertainty reduction during learning, which was directly reflected in SDBOLD changes. Our results provide first evidence that neural variability compresses with increasing belief precision during effective learning, proposing a flexible mechanism for how we come to learn the probabilistic nature of the world around us.

Many of the environments that we navigate through every day are hierarchically organized-they consist of spaces nested within other spaces. How do our mind/brains represent such environments? To address this question, we familiarized participants with a virtual environment consisting of a building within a courtyard, with objects distributed throughout the courtyard and building interior. We then scanned them with functional MRI (fMRI) while they performed a memory task that required them to think about spatial relationships within and across the subspaces. Behavioral responses were less accurate and response times were longer on trials requiring integration across the subspaces compared to trials not requiring integration. FMRI response differences between integration and non-integration trials were observed in scene-responsive and medial temporal lobe brain regions, which were correlated the behavioral integration effects in retrosplenial complex, occipital place area, and hippocampus. Multivoxel pattern analyses provided additional evidence for representations in these brain regions that reflected the hierarchical organization of the environment. These results indicate that people form cognitive maps of nested spaces by dividing them into subspaces and using an active cognitive process to integrate the subspaces. Similar mechanisms might be used to support hierarchical coding in memory more broadly.

How choices are made between rewards is fundamental to understanding the behavior of humans and most other vertebrates. A key factor in the choices is reward-specific satiety, which is the sensory-specific decrease in the reward value of a particular reward when it is consumed to satiety. Another key factor is reward-specific motivation, the increase in the reward value of a reward when it is first provided. Here, we develop the theory based on experimental evidence in humans and other primates, that reward-specific satiety is implemented in orbitofrontal cortex reward value neurons by adaptation in the synapses from visual and taste cortical regions in which the neuronal firing is not influenced by reward-specific satiety. Correspondingly we develop the theory that reward-specific motivation (or incentive motivation) is implemented by shorter-term synaptic facilitation in the same synapses on to orbitofrontal cortex reward value neurons. We complement the theories with an integrate-and-fire neuronal network model of how these reward value computations are performed in the orbitofrontal cortex by synaptic adaptation and synaptic facilitation in the afferent connections to orbitofrontal cortex reward value neurons, to implement a profound influence on behavioral choice that has great adaptive value for humans and many other animals.

Orientation is one of the most fundamental stimulus features in visual perception. In the primary visual cortex (V1), while most neurons are orientation-selective, a small portion exhibits a lack of this selectivity. However, it remains unclear what roles the orientation-untuned V1 neurons play in population orientation discrimination. Here, we analyzed data from a 2-photon calcium imaging study that recorded the responses of thousands of V1 neurons to a grating stimulus at various orientations in awake macaques. Our population analysis reveals that orientation-untuned neurons can independently decode stimulus orientation with accuracy comparable to tuned neurons. Remarkably, we found that the more critical role of orientation-untuned neuronal populations in orientation encoding is to enhance coding robustness, specifically by reducing sensitivity to noise. Moreover, when using artificial neural networks to model the primate ventral visual pathway, we found that the V1-like layer also contains a proportion of orientation-untuned units. Removing these units leads to significant impairments in natural object recognition. Overall, these results indicate that orientation-untuned neurons encode orientation information and play a crucial role in primate visual perception. The study provides compelling evidence for a continuous distribution of visual features across neurons and challenges the notion of highly specialized units.

The present study aims to investigate the relationship between white matter alterations and functional impairment in attention-deficit/hyperactivity disorder (ADHD) children. Diffusion tensor imaging data were examined in a cross-sectional sample of 125 ADHD children and 73 typically developing controls. White matter integrity was analyzed using two complementary approaches: tract-based spatial statistics analysis (TBSS) and automated fiber quantification (AFQ). Our findings revealed both disrupted (the left inferior longitudinal fasciculus, ILF_L; the left inferior fronto-occipital fasciculus, IFOF_L) and enhanced (the left anterior thalamic radiation, ATR_L; the left cingulum cingulate, CHC_L; forceps major) white matter alterations in ADHD using complementary TBSS and AFQ methods. The multiple regression analyses showed that functional impairment was higher for higher mean fractional anisotropy (FA) (nodes 64-100) of the left anterior thalamic radiation (beta = 0.19, P = 0.04) and lower for higher mean FA value (nodes 50-55) of the left inferior fronto-occipital fasciculus (beta = -0.15, P = 0.02). Importantly, mediation analyses revealed that ADHD symptom severity partially mediated the relationship between white matter alterations and functional impairment. This study revealed bidirectional white matter alterations in ADHD, and emphasized the potential of the anterior thalamic radiation and inferior fronto-occipital fasciculus abnormality as biomarkers for assessing functional impairments and informing targeted therapeutic strategies to improve clinical outcomes.

Understanding someone else's attention lies at the heart of human interaction. When we perceive something to be in someone else's attention, we understand it to be in that person's mind in the moment, ready to affect that person's choices. It has been proposed that people construct predictive models of the attentional state of others. In that proposal, a working understanding of someone else's attention goes far beyond merely tracking the direction of someone's eyes. For example, in a recent study, participants watched a spotlight of attention moving around a picture and successfully judged whether the trace represented real, human attention or an artificially manipulated version, demonstrating implicit information about how patterns of attention behave over space and time. However, the neuronal underpinnings of attention modeling are almost entirely unstudied. Here we tested people in an fMRI scanner while they performed the attention judgment paradigm. When contrasting attention traces that participants judged to be artificial versus those judged to be real, activity was found bilaterally in the precuneus, dorsomedial prefrontal cortex, anterior cingulate, and anterior insula, as well as in a part of the right temporoparietal junction. These areas partially overlap the theory-of-mind network and the salience network. The activations differ from those known to be involved in processing low-level features of attention such as the sight of other people's eyes. The results provide an initial picture of the cortical networks involved in monitoring the attention patterns of others and recognizing when those patterns deviate from expectation.

Stroke is a major public health challenge worldwide; yet, the impact of habitual coffee and caffeine consumption on stroke risk remains unclear, with conflicting evidence suggesting both protective and harmful effects. In this study, genetic variants linked to coffee and caffeine consumption were identified from prior genome-wide meta-analyses and used as instrumental variables. Summary-level data for stroke, including ischemic and hemorrhagic subtypes, were obtained from genome-wide association meta-analyses involving 1,913,565, 1,020,314, and 567,056 participants, respectively. Bidirectional 2-sample Mendelian randomization analyses were performed to assess the causal relationships between coffee/caffeine intake and stroke. Novel genetic loci, key genes, and pathways identified in our genome-wide association studies meta-analysis validated the reliability of genome-wide association studies summary statistics as instrumental variables. Forward Mendelian randomization analyses revealed that genetically-predicted coffee and caffeine consumption was associated with a reduced risk of stroke, with pooled odds ratios for stroke-related traits of 0.927 (95% CI, 0.877-0.979; P = 0.007), 0.898 (95% CI, 0.794-1.015; P = 0.085), and 0.954 (95% CI, 0.646-1.408; P = 0.812) for coffee consumption, and 0.831 (95% CI, 0.711-0.972; P = 0.0202), 0.897 (95% CI, 0.799-1.007; P = 0.0656), and 0.924 (95% CI, 0.834-1.023; P = 0.1275) for caffeine consumption. Reverse Mendelian randomization analyses found no evidence of a causal effect of stroke on coffee or caffeine consumption, and no significant heterogeneity or pleiotropy was detected. These findings suggest a potential protective role of coffee and caffeine against stroke and highlight the importance of integrating dietary habits and genetic determinants into future stroke prevention strategies.

Persons with cerebral palsy (CP) exhibit diminished somatosensory cortical activity and this has been linked with the extent of their muscular performance and mobility impairments. However, the influence of physical therapy paradigms on such diminished cortical activity remains unclear. The current study evaluated the extent of mobility changes and somatosensory cortical activity in persons with CP (n = 28; Age = 21.57 ± 7.1 yr; Gross Motor Function Classification Score levels I-III) following 8 weeks of a gait training protocol that involved exploratory activities that were directed at enhancing the somatosensory experience through rich/novel movement. A paired-pulse somatosensory paradigm during magnetoencephalography was used to assess the cortical changes after undergoing the physical therapy protocol. Consistent with the literature, the group with CP had weaker somatosensory cortical responses compared to the neurotypical controls. While the participants with CP demonstrated clinically relevant mobility improvements, there were no changes in the somatosensory cortical activity. However, there was a prominent increase in neural activity within the anterior cingulate. This implies that the novel gait training protocol used here may drive beneficial improvements in the ability of persons with CP to monitor their motor errors, attend to the available sensory feedback, and discriminate different sensory intensities during gait.

Patriotism and nationalism as 2 types of attitudes have been used to interpret nation-related social behaviors, but whether they are mediated by distinct psychological and neural constructs remains unclear. We recorded rating scores and brain activities related to nationalism and patriotism statements that were dissected into affective (ie positive emotions pertaining to one's own country or negative emotions pertaining to other countries) and cognitive (ie beliefs of the excellence of one's own country or superiority of one's own country over other countries) dimensions. Principal component analyses of the rating scores showed that the affective and cognitive components of nationalism vs. patriotism are disjointed to a larger degree. Functional magnetic resonance imaging results revealed that, while the right middle temporal cortex responded differentially to the affective and cognitive components of patriotism, a more extensive neural network, including the medial prefrontal cortex, lateral/orbital frontal cortices, insula, and temporal-parietal junction, responded differentially to the 2 components of nationalism statements. Moreover, the left frontal response to the affective nationalism statements mediated the link between nationalism-related emotions and behavioral tendencies to help other countries. Our findings unravel distinct psychological and neural constructs of patriotism and nationalism that advance our understanding of nation-related decision-making and behaviors.

In the search for EEG markers of human consciousness, alpha power has long been considered a reliable marker which is fundamental for the assessment of unresponsive patients from all etiologies. However, recent evidence questioned the role of alpha power as a marker of consciousness and proposed the spectral exponent and spatial gradient as more robust and generalizable clinical indexes. In this study, we analyzed a large-scale dataset of 303 unresponsive patients and investigated etiology-specific differences in clinical markers of level of consciousness, responsiveness and capacity to recover. We compare a set of candidate EEG makers: i) absolute, relative and flattened alpha power; ii) spatial ratios; iii) the spectral exponent; and iv) signal complexity. Our results support the claim that alpha power has higher diagnostic value for anoxic patients. Meanwhile, the spectral slope showed diagnostic value for non-anoxic patients only. Changes in relative power and signal complexity occurred alongside changes in the spectral slope. Grouping unresponsive patients from different etiologies together can confound or obscure the diagnostic value of different EEG markers of consciousness. Our study highlights the importance of analyzing different etiologies independently and emphasizes the need to develop clinical markers which better account for inter-individual and etiology-dependent differences.