The lateral occipitotemporal cortex in action

Neurocognitive mechanisms underlying action tool knowledge tasks: specificity of tool-tool compared to hand-tool compatibility tasks

Action tool knowledge can be assessed mainly with two kinds of tasks: tool-tool and hand-tool compatibility tasks. While these tasks are used to assess action tool knowledge, recent data showed striking dissociations between these tasks in brain-damaged patients. In this study, we explored the neuropsychological dissociations (Experiment 1; 60 brain-damaged patients) and the potential cognitive mechanisms engaged during these two tasks (Experiment 2; 52 healthy participants). Finally, we also reanalyzed fMRI data to investigate the neural bases engaged in tool-tool and hand-tool compatibility tasks (Experiment 3; 34 healthy participants). The three experiments provide convergent arguments by showing that both tasks share common core computations supported by a left-lateralized brain network, but hand-tool compatibility task engages regions outside of this brain network and is explained by visual imagery while tool-tool task is rather explained by motor imagery. Our results shed a new light on action tool knowledge tasks.

The Bodily Appearance of a Virtual Partner Affects the Activity of the Action Observation and Action Monitoring Systems in a Minimally Interactive Task

One pending question in social neuroscience is whether interpersonal interactions are processed differently by the brain depending on the bodily characteristics of the interactor, i.e., their physical appearance. To address this issue, we engaged participants in a minimally interactive task with an avatar either showing bodily features or not while recording their brain activity using electroencephalography (EEG) in order to investigate indices of action observation and action monitoring processing. Multivariate results showed that bodily compared with nonbodily appearance modulated parieto-occipital neural patterns throughout the entire duration of the observed movement and that, importantly, such patterns differ from the ones related to initial shape processing. Furthermore, among the electrocortical indices of action monitoring, only the early observational positivity (oPe) was responsive to the bodily appearance of the observed agent under the specific task requirement to predict the partner movement. Taken together, these findings broaden the understanding of how bodily appearance shapes the spatiotemporal processing of an interactor's movements. This holds particular relevance in our modern society, where human-artificial (virtual or robotic) agent interactions are rapidly becoming ubiquitous.

Distinct neural correlates of morphosyntactic and thematic comprehension processes in aphasia

Functional neuroimaging studies in neurotypical subjects correlate sentence comprehension to a left fronto-temporo-parietal network. Recent voxel-based lesion-symptom mapping (VLSM) studies of aphasia confirm the link between sentence comprehension and a left posterior region including the angular gyrus, the supra-marginal gyrus and the postero-superior division of the temporal lobe but support left pre-frontal involvement inconsistently. However, these studies focus on thematic role assignment without considering morphosyntactic processes. Hence, available VLSM evidence could provide a partial view of the neurofunctional substrate of sentence comprehension. In the present VLSM study, both morphosyntactic and thematic processes were evaluated systematically and in the same sentence types in each participant, to provide a more detailed picture of the sentence comprehension network. Participants (33 patients with post-stroke aphasia and 90 healthy controls) completed a sentence-picture matching task in which active and passive, declarative reversible sentences were paired with morphosyntactic, thematic and lexical-semantic alternatives. Phonological short-term memory tasks were also administered. Aphasic participants were selected from an initial pool of 70 because they scored below norm on thematic foils (n = 18) or on thematic and morphological foils (n = 15), but within the norm on lexical-semantic foils. The neurofunctional correlates of morphosyntactic and thematic processes were starkly distinguishable. Pre-frontal areas including the inferior and middle frontal gyrus were involved directly in processing local morphosyntactic features and only indirectly in thematic processes. When these areas were damaged, morphosyntactic errors always co-occurred with thematic errors, probably because morphosyntactic damage disrupts the assignment of grammatical roles and ultimately that of thematic roles. Morphosyntactic errors were not influenced by word order canonicity. In contrast, selective thematic role reversals were linked to temporal and parietal damage and were significantly influenced by word order, occurring on passive more than on active sentences. An area including the angular and supra-marginal gyrus was critical for processing non-canonical word order. In sentence comprehension, pre-frontal regions are critical for processing local morphosyntactic features (at least in simple declarative sentences). Temporal and parietal regions are critical for thematic processes. Postero-superior temporal areas are involved in retrieving verb argument structure. Parietal areas are critical for assigning morphosyntactically analysed constituents to the appropriate thematic role, thus serving a crucial function in thematic re-analysis. Each area plays a prevailing but not exclusive role in these processes, interacting with other areas in the network and possibly providing both the language-specific and the domain-general resources needed at various stages of sentence comprehension.

Cortical representation of novel tool use: Understanding the neural basis of mechanical problem solving

INTRODUCTION

Using tools effectively is a fundamental human ability. Besides the proper recall of semantic knowledge, the application of mechanical problem solving strategies allows one to execute tool-related tasks properly. Past fMRI studies have shown a mainly left-lateralized network, including ventral, ventro-dorsal, and dorso-dorsal streams while using familiar tools with access to semantic information. However, to what degree the network is recruited when applying mechanical problem solving strategies to handle novel tools remains unclear.

METHODS

An event-related fMRI study including 22 participants was conducted. During scanning, participants had to manipulate novel tools, the function of which they could infer by mechanical problem solving. Brain activity was measured during actual novel tool use and selection, both during the planning and execution phase.

RESULTS

Similar brain activation during tool use and tool selection could be observed, ranging from left-hemispheric inferior parietal to frontal regions in the ventro-dorsal stream with lack of ventral activation. Task-specific activations were more pronounced during the planning phases.

DISCUSSION

During mechanical problem solving brain activation is more pronounced in the ventro-dorsal stream, where mechanical understanding and motor control need to be integrated. Similar networks recruited during tool selection compared to tool use trials reflect mental simulation strategies used to determine the appropriate tool-recipient fit. The ventral stream, linked to the recall of semantic knowledge, plays a subordinate role during this task and a stronger involvement of anterior regions reflect the relevance of the frontal lobe contributing to mechanical problem solving.

Resting-State Functional Interactions Between the Action Observation Network and the Mentalizing System

Human social functioning is thought to rely on the action observation network (AON) and the mentalizing system (MS). It is debated whether AON and MS are functionally separate or if they interact. To this end, we combined resting-state connectivity with task-based fMRI to characterize the functional connectome within and between these systems. In detail, we computed resting-state connectivity within and between the AON and MS using single subject-defined regions of interest (ROIs). Our results showed a positive coupling between ROIs within each system and negative coupling between the two systems, supporting the existence of two independent networks at rest. Still, two regions (pSTS, aIFG) showed hybrid coupling, connecting with regions of both systems, suggesting that they might mediate cross-network communication. This characterization of the interplay between MS and AON in the healthy brain might provide the starting point to further investigate aberrant "connectivity" fingerprints associated with neuropsychiatric disorders characterized by impairments in social cognition.

Tool Representations in Human Visual Cortex

Tools such as pens, forks, and scissors play an important role in many daily-life activities, an importance underscored by the presence in visual cortex of a set of tool-selective brain regions. This review synthesizes decades of neuroimaging research that investigated the representational spaces in the visual ventral stream for objects, such as tools, that are specifically characterized by action-related properties. Overall, results reveal a dissociation between representational spaces in ventral and lateral occipito-temporal cortex (OTC). While lateral OTC encodes both visual (shape) and action-related properties of objects, distinguishing between objects acting as end-effectors (e.g., tools, hands) versus similar noneffector manipulable objects (e.g., a glass), ventral OTC primarily represents objects' visual features such as their surface properties (e.g., material and texture). These areas act in concert with regions outside of OTC to support object interaction and tool use. The parallel investigation of the dimensions underlying object representations in artificial neural networks reveals both the possibilities and the difficulties in capturing the action-related dimensions that distinguish tools from other objects. Although artificial neural networks offer promise as models of visual cortex computations, challenges persist in replicating the action-related dimensions that go beyond mere visual features. Taken together, we propose that regions in OTC support the representation of tools based on a behaviorally relevant action code and suggest future paths to generate a computational model of this object space.

Decoding the physics of observed actions in the human brain

Recognizing goal-directed actions is a computationally challenging task, requiring not only the visual analysis of body movements, but also analysis of how these movements causally impact, and thereby induce a change in, those objects targeted by an action. We tested the hypothesis that the analysis of body movements and the effects they induce relies on distinct neural representations in superior and anterior inferior parietal lobe (SPL and aIPL). In four fMRI sessions, participants observed videos of actions (e.g. breaking stick, squashing plastic bottle) along with corresponding point-light-display (PLD) stick figures, pantomimes, and abstract animations of agent-object interactions (e.g. dividing or compressing a circle). Cross-decoding between actions and animations revealed that aIPL encodes abstract representations of action effect structures independent of motion and object identity. By contrast, cross-decoding between actions and PLDs revealed that SPL is disproportionally tuned to body movements independent of visible interactions with objects. Lateral occipitotemporal cortex (LOTC) was sensitive to both action effects and body movements. These results demonstrate that parietal cortex and LOTC are tuned to physical action features, such as how body parts move in space relative to each other and how body parts interact with objects to induce a change (e.g. in position or shape/configuration). The high level of abstraction revealed by cross-decoding suggests a general neural code supporting mechanical reasoning about how entities interact with, and have effects on, each other.

Cortical structural degeneration and functional network connectivity changes in patients with subcortical vascular cognitive impairment

PURPOSE

To explore the structural basis of functional network connectivity (FNC) changes and early cortical degenerative patterns in subcortical vascular cognitive impairment (SVCI).

METHODS

We prospectively included SVCI cases and healthy controls (HCs). FNC alterations were evaluated using group-independent component analysis of resting-state functional MRI data. Cortical microstructural and macrostructural alterations were assessed using gray matter-based spatial statistics analysis with neurite orientation dispersion and density imaging and cortical thickness analysis with FreeSurfer software on T1-weighted images, respectively. Spearman correlation analyses were performed to assess relationships between FNC alterations and cortical microstructural/macrostructural alterations and between FNC, cortical thickness, or neurite density index (NDI)/orientation dispersion index (ODI) alterations and cognitive performance.

RESULTS

Forty-six SVCI patients and 73 HCs were recruited. FNC analysis showed lower network connectivity between the visual network (VN) and sensorimotor network (SMN) in SVCI, positively correlated with information processing speed (p=0.008) and negatively with summary SVD score (p = 0.037). Cortical microstructural analyses exhibited a lower NDI, mainly in the VN and default mode network (DMN) areas (PFWE < 0.05, cluster > 100 voxels), and lower ODI, mainly in the SMN and DMN areas (PFWE < 0.05, cluster > 100 voxels) in SVCI, both of which were related to cognitive function (p < 0.05). However, cortical thickness did not differ between groups. Lower NDI in the lateral occipital cortex was linked to lower VN-SMN connectivity in SVCI (p = 0.002).

CONCLUSION

Cortical microstructural alterations may serve as the basis for FNC changes in SVCI.

Self-Awareness from Whole-Body Movements

Humans can recognize their whole-body movements even when displayed as dynamic dot patterns. The sparse depiction of whole-body movements, coupled with a lack of visual experience watching ourselves in the world, has long implicated nonvisual mechanisms to self-action recognition. Using general linear modeling and multivariate analyses on human brain imaging data from male and female participants, we aimed to identify the neural systems for this ability. First, we found that cortical areas linked to motor processes, including frontoparietal and primary somatomotor cortices, exhibit greater engagement and functional connectivity when recognizing self-generated versus other-generated actions. Next, we show that these regions encode self-identity based on motor familiarity, even after regressing out idiosyncratic visual cues using multiple regression representational similarity analysis. Last, we found the reverse pattern for unfamiliar individuals: encoding localized to occipitotemporal visual regions. These findings suggest that self-awareness from actions emerges from the interplay of motor and visual processes.

Functional Connectivity Alterations Associated with COVID-19-Related Sleep Problems: A Longitudinal Resting-State fMRI Study

Background

COVID-19 has led to reports of fatigue and sleep problems. Brain function changes underlying sleep problems (SP) post-COVID-19 are unclear.

Purpose

This study investigated SP-related brain functional connectivity (FC) alterations.

Patients and methods

Fifty-five COVID-19 survivors with SP (COVID_SP) and 33 without SP (COVID_NSP), matched for demographics, completed PSQI and underwent rs-fMRI at baseline and 2-month follow-up. Correlations between FC and clinical data were analyzed by Pearson correlation analysis with Gaussian random field (GRF) correction. The repeated-measures analysis of variance (R-M ANOVA) was completed to explore the interaction with time.

Results

At baseline, COVID_SP exhibited elevated FC: right precentral gyrus (PrG) with left lateral occipital cortex (LOcC)/right PrG, left inferior parietal lobule (IPL) with right superior frontal gyrus (SFG), left hippocampus with right inferior frontal gyrus (IFG). Higher FC between left hippocampus and right SFG correlated with PSQI scores. At 2-month follow-up, decreased FC implicated in emotion regulation, executive function, and memory; increased FC in semantics, attention, and auditory-visual processing. The changes in these regions are correlated with the scores of PSQI, GAD, and PHQ. The Repeated-Measures Analysis of Variance (R-M ANOVA) revealed a significant time interaction effect between sleep and various emotion scales. Moreover, the analysis of the functional connectivity between the right PrG and the right PrG as well as that between the left IPL and the right SFG also discovered a significant time interaction effect.

Conclusion

This study provides insight into the changes in brain function associated with SP after COVID-19. These changes may partially explain the development of SP, and they also changed over time.

Are there cortical somatotopic motor maps outside of the human precentral gyrus?

Human body movements are supported by a somatotopic map, primary motor cortex (M1), that is found along the precentral gyrus. Recent evidence has suggested two further motor maps that span the lateral occipitotemporal cortex (LOTC) and the precuneus. Confirmation of these maps is important, as they influence our understanding of the organization of motor behavior, for example by revealing how visual- and motor-related activity interact. However, evidence for these recently proposed maps is limited. We analyzed an open functional MRI (fMRI) dataset of 62 participants who performed 12 different body part movements. We analyzed the magnitude of responses evoked by movements with novel quantitative indices that test for maplike organization. We found strong evidence for bilateral somatotopic maps in precentral and postcentral gyri. In LOTC, we found much weaker responses to movement and little evidence of somatotopy. In the precuneus, we found only limited evidence for somatotopy. We also adopted a background connectivity approach to examine correlations between M1, LOTC, and the precuneus in the residual time series data. This revealed a ventral-posterior/dorsal-anterior distinction in the connectivity between precuneus and M1, favoring the head and arms, respectively. Posterior right hemisphere LOTC showed some evidence of preferential connectivity to arm-selective regions of M1. Overall, our results do not support the existence of a somatotopic motor map in LOTC but provide some support for a coarse map in the precuneus, especially as revealed in connectivity patterns. These findings help clarify the organization of human motor representations beyond the precentral gyrus.NEW & NOTEWORTHY We investigated previous claims about the existence of somatotopic motor maps in the human lateral occipitotemporal cortex (LOTC) and the precuneus, in comparison to known maps in the precentral and postcentral gyri. Consistent with previous findings, we identified clear somatotopic motor maps in the latter two regions. With multiple quantitative measures of activity and connectivity, however, we found no evidence for a map in the LOTC and limited evidence for a map in the precuneus.

Two distinct neural pathways for mechanical versus digital technology

Technology pervades every aspect of our lives, making it crucial to investigate how the human mind deals with it. Here we examine the cognitive and neural foundations of technological cognition. In the first fMRI experiment, participants viewed videos depicting the use of mechanical tools (e.g., a screwdriver) and digital tools (e.g., a smartphone) compared to simple object movements. Results revealed a key dissociation: mechanical tools extensively activated the dorsal and ventro-dorsal visual streams, which are motor- and action-oriented brain systems. Conversely, digital tools largely engaged the ventral visual stream, associated with conceptual and social cognition. A second behavioral experiment showed a pronounced tendency to anthropomorphize digital tools. A third experiment involving a priming task confirmed that digital tools activate the social brain. The discovery of two different neurocognitive systems for mechanical versus digital technology offers new insights into human-technology interaction and its implications for the evolution of the human mind.

Primary manipulation knowledge of objects is associated with the functional coupling of pMTG and aIPS

Correctly using hand-held tools and manipulable objects typically relies not only on sensory and motor-related processes, but also centrally on conceptual knowledge about how objects are typically used (e.g. grasping the handle of a kitchen knife rather than the blade avoids injury). A wealth of fMRI connectivity-related evidence demonstrates that contributions from both ventral and dorsal stream areas are important for accurate tool knowledge and use. Here, we investigate the combined role of ventral and dorsal stream areas in representing "primary" manipulation knowledge - that is, knowledge that is hypothesized to be of central importance for day-to-day object use. We operationalize primary manipulation knowledge by extracting the first dimension from a multi-dimensional scaling solution over a behavioral judgement task where subjects arranged a set of 80 manipulable objects based on their overall manipulation similarity. We then relate this dimension to representational and time-course correlations between ventral and dorsal stream areas. Our results show that functional coupling between posterior middle temporal gyrus (pMTG) and anterior intraparietal sulcus (aIPS) is uniquely related to primary manipulation knowledge about objects, and that this effect is more pronounced for objects that require precision grasping. We reason this is due to precision-grasp objects requiring more ventral/temporal information relating to object shape, material and function to allow correct finger placement and controlled manipulation. These results demonstrate the importance of functional coupling across these ventral and dorsal stream areas in service of manipulation knowledge and accurate grasp-related behavior.

Regular sleep habits in toddlers are associated with social development and brain coherence

OBJECTIVE

Although sleep habits are associated with the development of toddlers, factors affecting social development and brain function remain unclear. We aimed to elucidate the relationship between sleep habits and social development as well as brain coherence in toddlers.

METHODS

We used the data set at 1.5-2 years old, in the longitudinal study until 6 years old. We evaluated sleep parameters, such as average wake-up time, bedtime, nighttime sleep duration, total sleep duration, and the standard deviation (SD) of sleep habits. We also examined the development, including the social stimuli fixation percentage using Gazefinder® and electroencephalography (EEG) coherence between brain regions.

RESULTS

Seventy-two children (37 boys and 35 girls) were included. The fixation percentage for the human face was negatively correlated with the SD of the total sleep duration, nighttime sleep duration, nap duration, and bedtime (r = -0.516, p = 0.000; r = -0.331, p = 0.005; r = -0.330, p = 0.005; and r = -0.324, p = 0.005, respectively). The EEG analysis indicated that α-band coherence in the right centro-parietal area was negatively correlated with the total sleep duration (r = -0.283, p = 0.016). The path diagram demonstrated a direct significant effect of sleep duration irregularity on development including social communication and fixation percentage for human faces. Additionally, total sleep duration exhibited a direct effect on α cortical coherence in the right centro-parietal area.

CONCLUSIONS

In this study, we found an association between sleep irregularity and the development of social communication, preference for humans, and brain coherence in toddlers. We suggest that regular sleep plays an important role in promoting the development of social communication.

Behaviorally-relevant features of observed actions dominate cortical representational geometry in natural vision

We effortlessly extract behaviorally relevant information from dynamic visual input in order to understand the actions of others. In the current study, we develop and test a number of models to better understand the neural representational geometries supporting action understanding. Using fMRI, we measured brain activity as participants viewed a diverse set of 90 different video clips depicting social and nonsocial actions in real-world contexts. We developed five behavioral models using arrangement tasks: two models reflecting behavioral judgments of the purpose (transitivity) and the social content (sociality) of the actions depicted in the video stimuli; and three models reflecting behavioral judgments of the visual content (people, objects, and scene) depicted in still frames of the stimuli. We evaluated how well these models predict neural representational geometry and tested them against semantic models based on verb and nonverb embeddings and visual models based on gaze and motion energy. Our results revealed that behavioral judgments of similarity better reflect neural representational geometry than semantic or visual models throughout much of cortex. The sociality and transitivity models in particular captured a large portion of unique variance throughout the action observation network, extending into regions not typically associated with action perception, like ventral temporal cortex. Overall, our findings expand the action observation network and indicate that the social content and purpose of observed actions are predominant in cortical representation.

Aging modulates the impact of cognitive interference subtypes on dynamic connectivity across a distributed motor network

Research has shown age-related declines in cognitive control in the context of interference, but these studies have focused on frontoparietal networks and less is known about impacts on motor response-related dynamics in the face of distractors. Thus, we examined whether healthy aging affected connectivity between attention networks and motor circuitry using a multisource interference task and magnetoencephalography in 72 healthy-aging participants (28-63 years-old). Our results indicated stronger beta connectivity with increasing age between bilateral primary motor (M1) and occipital cortices, as well as stronger gamma fronto-motor connectivity during flanker-type interference. Regarding Simon-type interference, stronger beta interactions were observed between left M1 and right temporal and right M1 and left parietal with increasing age. Finally, the superadditivity effect (flanker + Simon presented simultaneously) indicated weaker beta connectivity between right M1 and left premotor with increasing age. These findings suggest exhaustion of age-related compensatory adaptations in the fronto-parieto-motor network with greater interference.

Motor task-to-task transfer learning for motor imagery brain-computer interfaces

Motor imagery (MI) is one of the popular control paradigms in the non-invasive brain-computer interface (BCI) field. MI-BCI generally requires users to conduct the imagination of movement (e.g., left or right hand) to collect training data for generating a classification model during the calibration phase. However, this calibration phase is generally time-consuming and tedious, as users conduct the imagination of hand movement several times without being given feedback for an extended period. This obstacle makes MI-BCI non user-friendly and hinders its use. On the other hand, motor execution (ME) and motor observation (MO) are relatively easier tasks, yield lower fatigue than MI, and share similar neural mechanisms to MI. However, few studies have integrated these three tasks into BCIs. In this study, we propose a new task-to-task transfer learning approach of 3-motor tasks (ME, MO, and MI) for building a better user-friendly MI-BCI. For this study, 28 subjects participated in 3-motor tasks experiment, and electroencephalography (EEG) was acquired. User opinions regarding the 3-motor tasks were also collected through questionnaire survey. The 3-motor tasks showed a power decrease in the alpha rhythm, known as event-related desynchronization, but with slight differences in the temporal patterns. In the classification analysis, the cross-validated accuracy (within-task) was 67.05 % for ME, 65.93 % for MI, and 73.16 % for MO on average. Consistently with the results, the subjects scored MI (3.16) as the most difficult task compared with MO (1.42) and ME (1.41), with p < 0.05. In the analysis of task-to-task transfer learning, where training and testing are performed using different task datasets, the ME-trained model yielded an accuracy of 65.93 % (MI test), which is statistically similar to the within-task accuracy (p > 0.05). The MO-trained model achieved an accuracy of 60.82 % (MI test). On the other hand, combining two datasets yielded interesting results. ME and 50 % of the MI-trained model (50-shot) classified MI with a 69.21 % accuracy, which outperformed the within-task accuracy (p < 0.05), and MO and 50 % of the MI-trained model showed an accuracy of 66.75 %. Of the low performers with a within-task accuracy of 70 % or less, 90 % (n = 21) of the subjects improved in training with ME, and 76.2 % (n = 16) improved in training with MO on the MI test at 50-shot. These results demonstrate that task-to-task transfer learning is possible and could be a promising approach to building a user-friendly training protocol in MI-BCI.

Potential effects of peripheral neuropathy on brain function in patients with type 2 diabetes mellitus

Background

The mechanisms associated between diabetic peripheral neuropathy (DPN) and various brain function abnormalities in patients remains unclear. This study attempted to indirectly evaluate the effect of DPN on brain function in patients with type 2 diabetes mellitus (T2DM) by characterizing the resting-state functional connectivity (FC) of the lower limb sensorimotor cortex (LSM).

Methods

Forty-four T2DM patients with diabetic peripheral neuropathy (DPN), 39 T2DM patients without diabetic peripheral neuropathy (ND), and 43 healthy controls (HCs) underwent a neuropsychological assessment and resting-state functional magnetic resonance imaging examinations to examine the differences in FC between the LSM and the whole brain. The relationships of FC with clinical/cognitive variables were examined.

Results

In comparison with the HCs group, the ND group showed reduced FC of the LSM with the right lateral occipitotemporal cortex (LOTC) and increased FC with the medial superior frontal gyrus (SFGmed), while the DPN group showed reduced FC of the LSM with the right cerebellar lobule VI, the right LOTC, the rostral prefrontal cortex (rPFC), and the anterior cingulate gyrus (ACC). Moreover, in comparison with the ND group, the DPN group showed reduced FC of the LSM with the ACC, SFGmed, and rPFC. In the DPN group, the FC between the LSM and right cerebellar lobule VI was significantly correlated with fasting blood glucose levels (r = -0.490, p = 0.001), and that between the LSM and ACC was significantly correlated with the Montreal Cognitive Assessment score (r = 0.479, p = 0.001).

Conclusions

Patients with T2DM may show abnormal motion-related visual perceptual function before the appearance of DPN. Importantly, DPN can influence the brain regions that maintain motion and motor control, and this effect is not limited to motor function, which may be the central neuropathological basis for diabetic peripheral neuropathy.

Human Visual Pathways for Action Recognition versus Deep Convolutional Neural Networks: Representation Correspondence in Late but Not Early Layers

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

Organization of conceptual tool knowledge following left and right brain lesions: Evidence from neuropsychological dissociations and multivariate disconnectome symptom mapping

The aim of this work was to better understand the organization of conceptual tool knowledge following stroke. We explored specifically the link between manipulation kinematics and manipulation hand posture; and the link between manipulation kinematics and function relations in left brain-damaged (n = 30) and right brain-damaged (n = 30) patients. We examined the performance of brain-damaged patients in conceptual tool tasks using neuropsychological dissociations and disconnectome symptom mapping. Our results suggest that manipulation kinematics is more impaired than function relations, following left or right brain lesions. We also observed that manipulation kinematics and manipulation hand posture are dissociable dimensions but are still highly interrelated, particularly in left brain-damaged patients. We also found that the corpus callosum and bilateral superior longitudinal fasciculus are involved in action and semantic tool knowledge following left brain lesions. Our results provide evidence that the right hemisphere contains conceptual tool representations. Further studies are needed to better understand the mechanisms supporting the cognitive recovery of conceptual tool knowledge. An emerging hypothesis is that the right hemisphere may support functional recovery through interhemispheric transfer following a left hemisphere stroke.

Shared representations of human actions across vision and language

Humans can recognize and communicate about many actions performed by others. How are actions organized in the mind, and is this organization shared across vision and language? We collected similarity judgments of human actions depicted through naturalistic videos and sentences, and tested four models of action categorization, defining actions at different levels of abstraction ranging from specific (action verb) to broad (action target: whether an action is directed towards an object, another person, or the self). The similarity judgments reflected a shared organization of action representations across videos and sentences, determined mainly by the target of actions, even after accounting for other semantic features. Furthermore, language model embeddings predicted the behavioral similarity of action videos and sentences, and captured information about the target of actions alongside unique semantic information. Together, our results show that action concepts are similarly organized in the mind across vision and language, and that this organization reflects socially relevant goals.

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

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

Modeling short visual events through the BOLD moments video fMRI dataset and metadata

Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1000 short (3 s) naturalistic video clips of visual events across ten human subjects. We use the videos' extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.

The neural correlates of limb apraxia: An anatomical likelihood estimation meta-analysis of lesion-symptom mapping studies in brain-damaged patients

Limb apraxia is a motor disorder frequently observed following a stroke. Apraxic deficits are classically assessed with four tasks: tool use, pantomime of tool use, imitation, and gesture understanding. These tasks are supported by several cognitive processes represented in a left-lateralized brain network including inferior frontal gyrus, inferior parietal lobe (IPL), and lateral occipito-temporal cortex (LOTC). For the past twenty years, voxel-wise lesion symptom mapping (VLSM) studies have been used to unravel the neural correlates associated with apraxia, but none of them has proposed a comprehensive view of the topic. In the present work, we proposed to fill this gap by performing a systematic Anatomic Likelihood Estimation meta-analysis of VLSM studies which included tasks traditionally used to assess apraxia. We found that the IPL was crucial for all the tasks. Moreover, lesions within the LOTC were more associated with imitation deficits than tool use or pantomime, confirming its important role in higher visual processing. Our results questioned traditional neurocognitive models on apraxia and may have important clinical implications.

Natural scenes reveal diverse representations of 2D and 3D body pose in the human brain

Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.

Reciprocal interactions among parietal and occipito-temporal representations support everyday object-directed actions

Everyday interactions with common manipulable objects require the integration of conceptual knowledge about objects and actions with real-time sensory information about the position, orientation and volumetric structure of the grasp target. The ability to successfully interact with everyday objects involves analysis of visual form and shape, surface texture, material properties, conceptual attributes such as identity, function and typical context, and visuomotor processing supporting hand transport, grasp form, and object manipulation. Functionally separable brain regions across the dorsal and ventral visual pathways support the processing of these different object properties and, in cohort, are necessary for functional object use. Object-directed grasps display end-state-comfort: they anticipate in form and force the shape and material properties of the grasp target, and how the object will be manipulated after it is grasped. End-state-comfort is the default for everyday interactions with manipulable objects and implies integration of information across the ventral and dorsal visual pathways. We propose a model of how visuomotor and action representations in parietal cortex interact with object representations in ventral and lateral occipito-temporal cortex. One pathway, from the supramarginal gyrus to the middle and inferior temporal gyrus, supports the integration of action-related information, including hand and limb position (supramarginal gyrus) with conceptual attributes and an appreciation of the action goal (middle temporal gyrus). A second pathway, from posterior IPS to the fusiform gyrus and collateral sulcus supports the integration of grasp parameters (IPS) with the surface texture and material properties (e.g., weight distribution) of the grasp target. Reciprocal interactions among these regions are part of a broader network of regions that support everyday functional object interactions.

The neural representation of body part concepts

Neuropsychological and neuroimaging studies provide evidence for a degree of category-related organization of conceptual knowledge in the brain. Some of this evidence indicates that body part concepts are distinctly represented from other categories; yet, the neural correlates and mechanisms underlying these dissociations are unclear. We expand on the limited prior data by measuring functional magnetic resonance imaging responses induced by body part words and performing a series of analyses investigating the cortical representation of this semantic category. Across voxel-level contrasts, pattern classification, representational similarity analysis, and vertex-wise encoding analyses, we find converging evidence that the posterior middle temporal gyrus, the supramarginal gyrus, and the ventral premotor cortex in the left hemisphere play important roles in the preferential representation of this category compared to other concrete objects.

Hemispheric asymmetry of hand and tool perception in left- and right-handers with known language dominance

Regions in the brain that are selective for images of hands and tools have been suggested to be lateralised to the left hemisphere of right-handed individuals. In left-handers, many functions related to tool use or tool pantomime may also depend more on the left hemisphere. This result seems surprising, given that the dominant hand of these individuals is controlled by the right hemisphere. One explanation is that the left hemisphere is dominant for speech and language in the majority of left-handers, suggesting a supraordinate control system for complex motor sequencing that is required for skilled tool use, as well as for speech. In the present study, we examine if this left-hemispheric specialisation extends to perception of hands and tools in left- and right-handed individuals. We, crucially, also include a group of left-handers with right-hemispheric language dominance to examine their asymmetry biases. The results suggest that tools lateralise to the left hemisphere in most right-handed individuals with left-hemispheric language dominance. Tools also lateralise to the language dominant hemisphere in right-hemispheric language dominant left-handers, but the result for left-hemispheric language dominant left-handers are more varied, and no clear bias towards one hemisphere is found. Hands did not show a group-level asymmetry pattern in any of the groups. These results suggest a more complex picture regarding hemispheric overlap of hand and tool representations, and that visual appearance of tools may be driven in part by both language dominance and the hemisphere which controls the motor-dominant hand.

Characterizing the discriminability of visual categorical information in strongly connected voxels

Functional brain responses are strongly influenced by connectivity. Recently, we demonstrated a major example of this: category discriminability within occipitotemporal cortex (OTC) is enhanced for voxel sets that share strong functional connectivity to distal brain areas, relative to those that share lesser connectivity. That is, within OTC regions, sets of 'most-connected' voxels show improved multivoxel pattern discriminability for tool-, face-, and place stimuli relative to voxels with weaker connectivity to the wider brain. However, understanding whether these effects generalize to other domains (e.g. body perception network), and across different levels of the visual processing streams (e.g. dorsal as well as ventral stream areas) is an important extension of this work. Here, we show that this so-called connectivity-guided decoding (CGD) effect broadly generalizes across a wide range of categories (tools, faces, bodies, hands, places). This effect is robust across dorsal stream areas, but less consistent in earlier ventral stream areas. In the latter regions, category discriminability is generally very high, suggesting that extraction of category-relevant visual properties is less reliant on connectivity to downstream areas. Further, CGD effects are primarily expressed in a category-specific manner: For example, within the network of tool regions, discriminability of tool information is greater than non-tool information. The connectivity-guided decoding approach shown here provides a novel demonstration of the crucial relationship between wider brain connectivity and complex local-level functional responses at different levels of the visual processing streams. Further, this approach generates testable new hypotheses about the relationships between connectivity and local selectivity.

Causal relationship between multiparameter brain MRI phenotypes and age: evidence from Mendelian randomization

To explore the causal relationship between age and brain health (cortical atrophy, white matter integrity, white matter hyperintensities and cerebral microbleeds in various brain regions) related multiparameter imaging features using two-sample Mendelian randomization. Age was determined as chronological age of the subject. Cortical volume, white matter micro-integrity, white matter hyperintensity volume and cerebral microbleeds of each brain region were included as phenotypes for brain health. Age and imaging of brain health related genetic data were analysed to determine the causal relationship using inverse-variance weighted model, validated by heterogeneity and horizontal pleiotropy variables. Age is causally related to increased volumes of white matter hyperintensities (β = 0.151). For white matter micro-integrity, fibres of the inferior cerebellar peduncle (axial diffusivity β = -0.128, orientation dispersion index β = 0.173), cerebral peduncle (axial diffusivity β = -0.136), superior fronto-occipital fasciculus (isotropic volume fraction β = 0.163) and fibres within the limbic system were causally deteriorated. We also detected decreased cortical thickness of multiple frontal and temporal regions (P < 0.05). Microbleeds were not related with aging (P > 0.05). Aging is a threat of brain health, leading to cortical atrophy mainly in the frontal lobes, as well as the white matter degeneration especially abnormal hyperintensity and deteriorated white matter integrity around the hippocampus.

Action-specific feature processing in the human cortex: An fMRI study

Sensorimotor integration involves feedforward and reentrant processing of sensory input. Grasp-related motor activity precedes and is thought to influence visual object processing. Yet, while the importance of reentrant feedback is well established in perception, the top-down modulations for action and the neural circuits involved in this process have received less attention. Do action-specific intentions influence the processing of visual information in the human cortex? Using a cue-separation fMRI paradigm, we found that action-specific instruction processing (manual alignment vs. grasp) became apparent only after the visual presentation of oriented stimuli, and occurred as early as in the primary visual cortex and extended to the dorsal visual stream, motor and premotor areas. Further, dorsal stream area aIPS, known to be involved in object manipulation, and the primary visual cortex showed task-related functional connectivity with frontal, parietal and temporal areas, consistent with the idea that reentrant feedback from dorsal and ventral visual stream areas modifies visual inputs to prepare for action. Importantly, both the task-dependent modulations and connections were linked specifically to the object presentation phase of the task, suggesting a role in processing the action goal. Our results show that intended manual actions have an early, pervasive, and differential influence on the cortical processing of vision.

Overlapping representations of observed actions and action-related features

The lateral occipitotemporal cortex (LOTC) has been shown to capture the representational structure of a smaller range of actions. In the current study, we carried out an fMRI experiment in which we presented human participants with images depicting 100 different actions and used representational similarity analysis (RSA) to determine which brain regions capture the semantic action space established using judgments of action similarity. Moreover, to determine the contribution of a wide range of action-related features to the neural representation of the semantic action space we constructed an action feature model on the basis of ratings of 44 different features. We found that the semantic action space model and the action feature model are best captured by overlapping activation patterns in bilateral LOTC and ventral occipitotemporal cortex (VOTC). An RSA on eight dimensions resulting from principal component analysis carried out on the action feature model revealed partly overlapping representations within bilateral LOTC, VOTC, and the parietal lobe. Our results suggest spatially overlapping representations of the semantic action space of a wide range of actions and the corresponding action-related features. Together, our results add to our understanding of the kind of representations along the LOTC that support action understanding.

Visual neuroscience: A brain area tuned for processing social interactions

Socialising with others is part of everyday life. A new study demonstrates that a brain area specialised for visual body perception is attuned to processing social interactions between two people. Intriguingly, this area is lateralised in the left hemisphere.

Converging evidence that left extrastriate body area supports visual sensitivity to social interactions

Navigating our complex social world requires processing the interactions we observe. Recent psychophysical and neuroimaging studies provide parallel evidence that the human visual system may be attuned to efficiently perceive dyadic interactions. This work implies, but has not yet demonstrated, that activity in body-selective cortical regions causally supports efficient visual perception of interactions. We adopt a multi-method approach to close this important gap. First, using a large fMRI dataset (n = 92), we found that the left hemisphere extrastriate body area (EBA) responds more to face-to-face than non-facing dyads. Second, we replicated a behavioral marker of visual sensitivity to interactions: categorization of facing dyads is more impaired by inversion than non-facing dyads. Third, in a pre-registered experiment, we used fMRI-guided transcranial magnetic stimulation to show that online stimulation of the left EBA, but not a nearby control region, abolishes this selective inversion effect. Activity in left EBA, thus, causally supports the efficient perception of social interactions.

In vivo tau is associated with change in memory and processing speed, but not reasoning, in cognitively unimpaired older adults

The relationship between tau deposition and cognitive decline in cognitively healthy older adults is still unclear. The tau PET tracer 18F-MK-6240 has shown favorable imaging characteristics to identify early tau deposition in aging. We evaluated the relationship between in vivo tau levels (18F-MK-6240) and retrospective cognitive change over 5 years in episodic memory, processing speed, and reasoning. For tau quantification, a set of regions of interest (ROIs) was selected a priori based on previous literature: (1) total-ROI comprising selected areas, (2) medial temporal lobe-ROI, and (3) lateral temporal lobe-ROI and cingulate/parietal lobe-ROI. Higher tau burden in most ROIs was associated with a steeper decline in memory and speed. There were no associations between tau and reasoning change. The novelty of this finding is that tau burden may affect not only episodic memory, a well-established finding but also processing speed. Our finding reinforces the notion that early tau deposition in areas related to Alzheimer's disease is associated with cognitive decline in cognitively unimpaired individuals, even in a sample with low amyloid-β pathology.

The functional organization of skilled actions in the adextral and atypical brain

When planning functional grasps of tools, right-handed individuals (dextrals) show mostly left-lateralized neural activity in the praxis representation network (PRN), regardless of the used hand. Here we studied whether or not similar cerebral asymmetries are evident in non-righthanded individuals (adextrals). Sixty two participants, 28 righthanders and 34 non-righthanders (21 lefthanders, 13 mixedhanders), planned functional grasps of tools vs. grasps of control objects, and subsequently performed their pantomimed executions, in an event-related functional magnetic resonance imaging (fMRI) project. Both hands were tested, separately in two different sessions, counterbalanced across participants. After accounting for non-functional components of the prospective grasp, planning functional grasps of tools was associated with greater engagement of the same, left-hemisphere occipito-temporal, parietal and frontal areas of PRN, regardless of hand and handedness. Only when the analyses involved signal changes referenced to resting baseline intervals, differences between adextrals and dextrals emerged. Whereas in the left hemisphere the neural activity was equivalent in both groups (except for the occipito-temporo-parietal junction), its increases in the right occipito-temporal cortex, medial intraparietal sulcus (area MIP), the supramarginal gyrus (area PFt/PF), and middle frontal gyrus (area p9-46v) were significantly greater in adextrals. The inverse contrast was empty. Notably, when individuals with atypical and typical hemispheric phenotypes were directly compared, planning functional (vs. control) grasps invoked, instead, significant clusters located nearly exclusively in the left hemisphere of the typical phenotype. Previous studies interpret similar right-sided vs. left-sided increases in neural activity for skilled actions as handedness dependent, i.e., located in the hemisphere dominant for manual skills. Yet, none of the effects observed here can be purely handedness dependent because there were mixed-handed individuals among adextrals, and numerous mixed-handed and left-handed individuals possess the typical phenotype. Thus, our results clearly show that hand dominance has limited power in driving the cerebral organization of motor cognitive functions.

Low frequency oscillations during hand laterality judgment task with and without personal perspectives: a preliminary study

Sense of personal perspective is crucial for understanding in attentional mechanisms of the perception in "self" or "other's" body. In a hand laterality judgment (HLJ) task, perception of perspective can be assessed by arranging angular orientations and depths of images. A total of 11 healthy, right-handed participants (8 females, mean age: 38.36 years, education: 14 years) were included in the study. The purpose of this study was to investigate behavioural and cortical responses in low-frequency cortical rhythms during a HLJ task. A total of 80-visual hand stimuli were presented through the experiment. Hand visuals were categorized in the way of side (right vs. left) and perspective (1st vs. 3rd personal perspective). Both behavioural outcomes and brain oscillatory characteristics (i.e., frequency and amplitude) of the Electroencephalography were analysed. All reaction time and incorrect answers for 3rd person perspective were higher than the ones for 1st person perspective. Location effect was statistically significant in event-related theta responses confirming the dominant activity of theta frequency in spatial memory tasks on parietal and occipital areas. In addition, we found there were increasing in delta power and phase in hand visuals with 1st person perspective and increasing theta phase in hand visuals with 3rd person perspective (p < 0.05). Accordingly, a clear dissociation in the perception of perspectives in low-frequency bands was revealed. These different cortical strategy in the perception of hand visual with and without perspectives may be interpreted as delta activity may be related in self-body perception, whereas theta activity may be related in allocentric perception.

The Representation of Observed Actions at the Subordinate, Basic, and Superordinate Level

Actions can be planned and recognized at different hierarchical levels, ranging from very specific (e.g., to swim backstroke) to very broad (e.g., locomotion). Understanding the corresponding neural representation is an important prerequisite to reveal how our brain flexibly assigns meaning to the world around us. To address this question, we conducted an event-related fMRI study in male and female human participants in which we examined distinct representations of observed actions at the subordinate, basic and superordinate level. Using multiple regression representational similarity analysis (RSA) in predefined regions of interest, we found that the three different taxonomic levels were best captured by patterns of activations in bilateral lateral occipitotemporal cortex (LOTC), showing the highest similarity with the basic level model. A whole-brain multiple regression RSA revealed that information unique to the basic level was captured by patterns of activation in dorsal and ventral portions of the LOTC and in parietal regions. By contrast, the unique information for the subordinate level was limited to bilateral occipitotemporal cortex, while no single cluster was obtained that captured unique information for the superordinate level. The behaviorally established action space was best captured by patterns of activation in the LOTC and superior parietal cortex, and the corresponding neural patterns of activation showed the highest similarity with patterns of activation corresponding to the basic level model. Together, our results suggest that occipitotemporal cortex shows a preference for the basic level model, with flexible access across the subordinate and the basic level.SIGNIFICANCE STATEMENT The human brain captures information at varying levels of abstraction. It is debated which brain regions host representations across different hierarchical levels, with some studies emphasizing parietal and premotor regions, while other studies highlight the role of the lateral occipitotemporal cortex (LOTC). To shed light on this debate, here we examined the representation of observed actions at the three taxonomic levels suggested by Rosch et al. (1976) Our results highlight the role of the LOTC, which hosts a shared representation across the subordinate and the basic level, with the highest similarity with the basic level model. These results shed new light on the hierarchical organization of observed actions and provide insights into the neural basis underlying the basic level advantage.

Minor Changes Change Memories: Functional Magnetic Resonance Imaging and Behavioral Reflections of Episodic Prediction Errors

Episodic memories can be modified, a process that is potentially driven by mnemonic prediction errors. In the present study, we used modified cues to induce prediction errors of different episodic relevance. Participants encoded episodes in the form of short toy stories and then returned for an fMRI session on the subsequent day. Here, participants were presented either original episodes or slightly modified versions thereof. Modifications consisted of replacing a single object within the episode and either challenged the gist of an episode (gist modifications) or left it intact (surface modifications). On the next day, participants completed a post-fMRI memory test that probed memories for originally encoded episodes. Both types of modifications triggered brain activation in regions we previously found to be involved in the processing of content-based mnemonic prediction errors (i.e., the exchange of an object). Specifically, these were ventrolateral pFC, intraparietal cortex, and lateral occipitotemporal cortex. In addition, gist modifications triggered pronounced brain responses, whereas those for surface modification were only significant in the right inferior frontal sulcus. Processing of gist modifications also involved the posterior temporal cortex and the precuneus. Interestingly, our findings confirmed the posterior hippocampal role of detail processing in episodic memory, as evidenced by increased posterior hippocampal activity for surface modifications compared with gist modifications. In the post-fMRI memory test, previous experience with surface modified, but not gist-modified episodes, increased erroneous acceptance of the same modified versions as originally encoded. Whereas surface-level prediction errors might increase uncertainty and facilitate confusion of alternative episode representations, gist-level prediction errors seem to trigger the clear distinction of independent episodes.

The impact of early adversity on the cerebral cortex - a Mendelian randomization study

Background

The early adversity is associated with a series of negative outcomes in adulthood, and the impact on the cerebral cortex may be one of the fundamental causes of these adverse consequences in adulthood. In this study, we aim to investigate the causal relationship between early adversity and changes in cerebral cortex structure using Mendelian randomization (MR) analysis.

Methods

The GWAS summary statistics of 6 early adversity traits were obtained from individuals of European ancestry in the UK Biobank. The GWAS summary statistics of 34 known functional cortical regions were obtained from the ENIGMA Consortium. Causal relationships between the adversity factors and brain cortical structure were assessed using the inverse-variance weighted (IVW), MR-Egger, and weighted median methods, with IVW being the primary evaluation method. Cochran's Q-test, MR-PRESSO, leave-one-out analysis, and funnel plot examination were employed to detect potential heterogeneity and pleiotropy, as well as to identify and exclude outliers.

Results

At a global level, no causal relationship was found between early adversity and cortical thickness (TH) or surface area (SA) of the brain. However, at the regional level, early adversity was found to potentially influence the TH of the caudal anterior cingulate, superior temporal, entorhinal, paracentral, lateral occipital, banks of the superior temporal sulcus, and supramarginal regions, as well as the SA of the pars triangularis, lateral occipital, parahippocampal, medial orbitofrontal, and isthmus cingulate regions. All findings were nominally significant and passed sensitivity analyses, with no significant heterogeneity or pleiotropy detected.

Discussion

Our study provides evidence for the association between early adversity and alterations in brain cortical structure, which may serve as a foundation for certain mental disorders. Furthermore, magnetic resonance imaging (MRI) might be considered as a promising tool to aid healthcare professionals in identifying individuals with a history of adverse experiences, allowing for early interventions.

Planet earth calling: unveiling the brain's response to awe and driving eco-friendly consumption

Eco-friendly consumption is important for solving climate crisis and moving humanity toward a better future. However, few consumers are willing to pay premiums for eco-friendly products. We investigated the psychological and neural factors that can increase eco-friendly consumption. We propose an experience of awe, in which the individual self is temporarily attenuated as the importance of beings other than oneself increases. Behavioral (Study 1) and functional magnetic resonance imaging (fMRI; Study 2) experiments were conducted to explore the awe mechanisms through which climate crisis messages lead to eco-friendly consumption. In Study 1, we found participants felt awe when exposed to climate crisis messages, and their choice of eco-friendly consumption increased. In Study 2, we found that when individuals were exposed to messages depicting the climate crisis (as opposed to a control stimulus), their brains exhibited a lower level of activation in the self-awareness processing and a higher level of activation in external attention processing areas. These results suggest that the awe experience plays an important role in promoting eco-friendly consumption. Marketing must evolve from satisfying basic individual needs to a high level for the well-being of humanity, the planet, and the biosphere. This study sheds light on our understanding of human perceptions of the climate crisis and suggests an effective communication strategy to increase individuals' eco-friendly actions.

Mechanisms and neuroanatomy of response selection in tool and non-tool action tasks: Evidence from left-hemisphere stroke

The ability to select between potential actions is central to the complex process of tool use. After left hemisphere stroke, individuals with limb apraxia make more hand action errors when gesturing the use of tools with conflicting hand actions for grasping-to-move and use (e.g., screwdriver) relative to tools that are grasped-to-move and used with the same hand action (e.g., hammer). Prior research indicates that this grasp-use interference effect is driven by abnormalities in the competitive action selection process. The goal of this project was to determine whether common mechanisms and neural substrates support the competitive selection of task-appropriate responses in both tool and non-tool domains. If so, the grasp-use interference effect in a tool use gesturing task should be correlated with response interference effects in the classic Eriksen flanker and Simon tasks, and at least partly overlapping neural regions should subserve the 3 tasks. Sixty-four left hemisphere stroke survivors (33 with apraxia) participated in the tool- and non-tool interference tasks and underwent T1 anatomical MRI. There were robust grasp-use interference effects (grasp-use conflict test) and response interference effects (Eriksen flanker and Simon tasks), but these effects were not correlated. Lesion-symptom mapping analyses showed that lesions to the left inferior parietal lobule, ventral premotor cortex, and insula were associated with grasp-use interference. Lesions to the left inferior parietal lobule, postcentral gyrus, insula, caudate, and putamen were associated with response interference in the Eriksen flanker task. Lesions to the left caudate and putamen were also associated with response interference in the Simon task. Our results suggest that the selection of hand posture for tool use is mediated by distinct cognitive mechanisms and partly distinct neuroanatomic substrates from those mapping a stimulus to an appropriate motor response in non-tool domains.

Concepts require flexible grounding

Research on semantic memory has a problem. On the one hand, a robust body of evidence implicates sensorimotor regions in conceptual processing. On the other hand, a different body of evidence implicates a modality independent semantic system. The standard solution to this tension is to posit a hub-and-spoke system with modality independent hubs and modality specific spokes. In this paper, I argue in support of an alternative view of grounding which remains committed to neural reenactment but emphasizes the multimodal and multilevel nature of the semantic system. This view is built upon the recognition that abstraction is a design feature of concepts. Semantic memory employs hierarchically structured representations to capture different degrees of abstraction. Grounding does not work the way that many embodied approaches have assumed.

Neural and behavioral signatures of the multidimensionality of manipulable object processing

Understanding how we recognize objects requires unravelling the variables that govern the way we think about objects and the neural organization of object representations. A tenable hypothesis is that the organization of object knowledge follows key object-related dimensions. Here, we explored, behaviorally and neurally, the multidimensionality of object processing. We focused on within-domain object information as a proxy for the decisions we typically engage in our daily lives - e.g., identifying a hammer in the context of other tools. We extracted object-related dimensions from subjective human judgments on a set of manipulable objects. We show that the extracted dimensions are cognitively interpretable and relevant - i.e., participants are able to consistently label them, and these dimensions can guide object categorization; and are important for the neural organization of knowledge - i.e., they predict neural signals elicited by manipulable objects. This shows that multidimensionality is a hallmark of the organization of manipulable object knowledge.

Early categorization of social affordances during the visual encoding of bodily stimuli

Interpersonal interactions rely on various communication channels, both verbal and non-verbal, through which information regarding one's intentions and emotions are perceived. Here, we investigated the neural correlates underlying the visual processing of hand postures conveying social affordances (i.e., hand-shaking), compared to control stimuli such as hands performing non-social actions (i.e., grasping) or showing no movement at all. Combining univariate and multivariate analysis on electroencephalography (EEG) data, our results indicate that occipito-temporal electrodes show early differential processing of stimuli conveying social information compared to non-social ones. First, the amplitude of the Early Posterior Negativity (EPN, an Event-Related Potential related to the perception of body parts) is modulated differently during the perception of social and non-social content carried by hands. Moreover, our multivariate classification analysis (MultiVariate Pattern Analysis - MVPA) expanded the univariate results by revealing early (<200 ms) categorization of social affordances over occipito-parietal sites. In conclusion, we provide new evidence suggesting that the encoding of socially relevant hand gestures is categorized in the early stages of visual processing.

A large-scale fMRI dataset for human action recognition

Human action recognition is a critical capability for our survival, allowing us to interact easily with the environment and others in everyday life. Although the neural basis of action recognition has been widely studied using a few action categories from simple contexts as stimuli, how the human brain recognizes diverse human actions in real-world environments still needs to be explored. Here, we present the Human Action Dataset (HAD), a large-scale functional magnetic resonance imaging (fMRI) dataset for human action recognition. HAD contains fMRI responses to 21,600 video clips from 30 participants. The video clips encompass 180 human action categories and offer a comprehensive coverage of complex activities in daily life. We demonstrate that the data are reliable within and across participants and, notably, capture rich representation information of the observed human actions. This extensive dataset, with its vast number of action categories and exemplars, has the potential to deepen our understanding of human action recognition in natural environments.

A shared neural code for the physics of actions and object events

Observing others' actions recruits frontoparietal and posterior temporal brain regions - also called the action observation network. It is typically assumed that these regions support recognizing actions of animate entities (e.g., person jumping over a box). However, objects can also participate in events with rich meaning and structure (e.g., ball bouncing over a box). So far, it has not been clarified which brain regions encode information specific to goal-directed actions or more general information that also defines object events. Here, we show a shared neural code for visually presented actions and object events throughout the action observation network. We argue that this neural representation captures the structure and physics of events regardless of animacy. We find that lateral occipitotemporal cortex encodes information about events that is also invariant to stimulus modality. Our results shed light onto the representational profiles of posterior temporal and frontoparietal cortices, and their roles in encoding event information.

Magnetoencephalogram-based brain-computer interface for hand-gesture decoding using deep learning

Advancements in deep learning algorithms over the past decade have led to extensive developments in brain-computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging technique. The present study developed a MEG sensor-based BCI neural network to decode Rock-Paper-scissors gestures (MEG-RPSnet). Unique preprocessing pipelines in tandem with convolutional neural network deep-learning models accurately classified gestures. On a single-trial basis, we found an average of 85.56% classification accuracy in 12 subjects. Our MEG-RPSnet model outperformed two state-of-the-art neural network architectures for electroencephalogram-based BCI as well as a traditional machine learning method, and demonstrated equivalent and/or better performance than machine learning methods that have employed invasive, electrocorticography-based BCI using the same task. In addition, MEG-RPSnet classification performance using an intra-subject approach outperformed a model that used a cross-subject approach. Remarkably, we also found that when using only central-parietal-occipital regional sensors or occipitotemporal regional sensors, the deep learning model achieved classification performances that were similar to the whole-brain sensor model. The MEG-RSPnet model also distinguished neuronal features of individual hand gestures with very good accuracy. Altogether, these results show that noninvasive MEG-based BCI applications hold promise for future BCI developments in hand-gesture decoding.

A data-driven investigation of human action representations

Understanding actions performed by others requires us to integrate different types of information about people, scenes, objects, and their interactions. What organizing dimensions does the mind use to make sense of this complex action space? To address this question, we collected intuitive similarity judgments across two large-scale sets of naturalistic videos depicting everyday actions. We used cross-validated sparse non-negative matrix factorization to identify the structure underlying action similarity judgments. A low-dimensional representation, consisting of nine to ten dimensions, was sufficient to accurately reconstruct human similarity judgments. The dimensions were robust to stimulus set perturbations and reproducible in a separate odd-one-out experiment. Human labels mapped these dimensions onto semantic axes relating to food, work, and home life; social axes relating to people and emotions; and one visual axis related to scene setting. While highly interpretable, these dimensions did not share a clear one-to-one correspondence with prior hypotheses of action-relevant dimensions. Together, our results reveal a low-dimensional set of robust and interpretable dimensions that organize intuitive action similarity judgments and highlight the importance of data-driven investigations of behavioral representations.

Functional organization of social perception in the human brain

Humans rapidly extract diverse and complex information from ongoing social interactions, but the perceptual and neural organization of the different aspects of social perception remains unresolved. We showed short movie clips with rich social content to 97 healthy participants while their haemodynamic brain activity was measured with fMRI. The clips were annotated moment-to-moment for a large set of social features and 45 of the features were evaluated reliably between annotators. Cluster analysis of the social features revealed that 13 dimensions were sufficient for describing the social perceptual space. Three different analysis methods were used to map the social perceptual processes in the human brain. Regression analysis mapped regional neural response profiles for different social dimensions. Multivariate pattern analysis then established the spatial specificity of the responses and intersubject correlation analysis connected social perceptual processing with neural synchronization. The results revealed a gradient in the processing of social information in the brain. Posterior temporal and occipital regions were broadly tuned to most social dimensions and the classifier revealed that these responses showed spatial specificity for social dimensions; in contrast Heschl gyri and parietal areas were also broadly associated with different social signals, yet the spatial patterns of responses did not differentiate social dimensions. Frontal and subcortical regions responded only to a limited number of social dimensions and the spatial response patterns did not differentiate social dimension. Altogether these results highlight the distributed nature of social processing in the brain.