A real-time marker of object-based attention in the human brain. A possible component of a "gate-keeping mechanism" performing late attentional selection in the Ventro-Lateral Prefrontal Cortex

Enhancing ventrolateral prefrontal cortex activation mitigates social pain and modifies subsequent social attitudes: Insights from TMS and fMRI

Social pain, a multifaceted emotional response triggered by interpersonal rejection or criticism, profoundly impacts mental well-being and social interactions. While prior research has implicated the right ventrolateral prefrontal cortex (rVLPFC) in mitigating social pain, the precise neural mechanisms and downstream effects on subsequent social attitudes remain elusive. This study employed transcranial magnetic stimulation (TMS) integrated with fMRI recordings during a social pain task to elucidate these aspects. Eighty participants underwent either active TMS targeting the rVLPFC (n = 41) or control stimulation at the vertex (n = 39). Our results revealed that TMS-induced rVLPFC facilitation significantly reduced self-reported social pain, confirming the causal role of the rVLPFC in social pain relief. Functional connectivity analyses demonstrated enhanced interactions between the rVLPFC and the dorsolateral prefrontal cortex, emphasizing the collaborative engagement of prefrontal regions in emotion regulation. Significantly, we observed that negative social feedback led to negative social attitudes, whereas rVLPFC activation countered this detrimental effect, showcasing the potential of the rVLPFC as a protective buffer against adverse social interactions. Moreover, our study uncovered the impact role of the hippocampus in subsequent social attitudes, a relationship particularly pronounced during excitatory TMS over the rVLPFC. These findings offer promising avenues for improving mental health within the intricate dynamics of social interactions. By advancing our comprehension of the neural mechanisms underlying social pain relief, this research introduces novel intervention strategies for individuals grappling with social distress. Empowering individuals to modulate rVLPFC activation may facilitate reshaping social attitudes and successful reintegration into communal life.

Event-related potential patterns of selective attention modulated by perceptual load

INTRODUCTION

A high perceptual load can effectively prevent attention from being drawn to irrelevant stimuli; however, the neural pattern underlying this process remains unclear.

METHODS

This study adopted a perceptual load paradigm to examine the temporal processes of attentional modulation by incorporating conditions of perceptual load, distractor-target compatibility, and eccentricity.

RESULTS

The behavioral results showed that a high perceptual load significantly reduced attentional distraction caused by peripheral distractors. The event-related potential results further revealed that shorter P2 latencies were observed for peripheral distractors than for central distractors under a high perceptual load and that a suppressed compatibility effect with increasing load was reflected by the P3 component.

CONCLUSION

These findings suggested that (1) P2 and P3 components effectively captured different sides of attentional processing modulated by load (i.e., the filter processing of the object and the overall attentional resource allocation) and (2) response patterns of selective attention modulated by perceptual load were influenced by eccentricity. Our electrophysiological evidence confirmed the behavioral findings, indicating the neural mechanisms of attentional modulation.

Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability

Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions.

Spiking Neural Network Based on Multi-Scale Saliency Fusion for Breast Cancer Detection

Deep neural networks have been successfully applied in the field of image recognition and object detection, and the recognition results are close to or even superior to those from human beings. A deep neural network takes the activation function as the basic unit. It is inferior to the spiking neural network, which takes the spiking neuron model as the basic unit in the aspect of biological interpretability. The spiking neural network is considered as the third-generation artificial neural network, which is event-driven and has low power consumption. It modulates the process of nerve cells from receiving a stimulus to firing spikes. However, it is difficult to train spiking neural network directly due to the non-differentiable spiking neurons. In particular, it is impossible to train a spiking neural network using the back-propagation algorithm directly. Therefore, the application scenarios of spiking neural network are not as extensive as deep neural network, and a spiking neural network is mostly used in simple image classification tasks. This paper proposed a spiking neural network method for the field of object detection based on medical images using the method of converting a deep neural network to spiking neural network. The detection framework relies on the YOLO structure and uses the feature pyramid structure to obtain the multi-scale features of the image. By fusing the high resolution of low-level features and the strong semantic information of high-level features, the detection precision of the network is improved. The proposed method is applied to detect the location and classification of breast lesions with ultrasound and X-ray datasets, and the results are 90.67% and 92.81%, respectively.

The diachronic account of attentional selectivity

Many models of attention assume that attentional selection takes place at a specific moment in time that demarcates the critical transition from pre-attentive to attentive processing of sensory input. We argue that this intuitively appealing standard account of attentional selectivity is not only inaccurate, but has led to substantial conceptual confusion. As an alternative, we offer a 'diachronic' framework that describes attentional selectivity as a process that unfolds over time. Key to this view is the concept of attentional episodes, brief periods of intense attentional amplification of sensory representations that regulate access to working memory and response-related processes. We describe how attentional episodes are linked to earlier attentional mechanisms and to recurrent processing at the neural level. We review studies that establish the existence of attentional episodes, delineate the factors that determine if and when they are triggered, and discuss the costs associated with processing multiple events within a single episode. Finally, we argue that this framework offers new solutions to old problems in attention research that have never been resolved. It can provide a unified and conceptually coherent account of the network of cognitive and neural processes that produce the goal-directed selectivity in perceptual processing that is commonly referred to as 'attention'.

Mind-wandering Is Accompanied by Both Local Sleep and Enhanced Processes of Spatial Attention Allocation

Mind-wandering (MW) is a subjective, cognitive phenomenon, in which thoughts move away from the task toward an internal train of thoughts, possibly during phases of neuronal sleep-like activity (local sleep, LS). MW decreases cortical processing of external stimuli and is assumed to decouple attention from the external world. Here, we directly tested how indicators of LS, cortical processing, and attentional selection change in a pop-out visual search task during phases of MW. Participants’ brain activity was recorded using magnetoencephalography, MW was assessed via self-report using randomly interspersed probes. As expected, the performance decreased under MW. Consistent with the occurrence of LS, MW was accompanied by a decrease in high-frequency activity (HFA, 80–150 Hz) and an increase in slow wave activity (SWA, 1–6 Hz). In contrast, visual attentional selection as indexed by the N2pc component was enhanced during MW with the N2pc amplitude being directly linked to participants’ performance. This observation clearly contradicts accounts of attentional decoupling that would predict a decrease in attention-related responses to external stimuli during MW. Together, our results suggest that MW occurs during phases of LS with processes of attentional target selection being upregulated, potentially to compensate for the mental distraction during MW.

Influence of homophone processing during auditory language comprehension on executive control processes: A dual-task paradigm

In the present preregistered study, we evaluated the possibility of a shared cognitive mechanism during verbal and non-verbal tasks and therefore the implication of domain-general cognitive control during language comprehension. We hypothesized that a behavioral cost will be observed during a dual-task including both verbal and non-verbal difficult processing. Specifically, to test this claim, we designed a dual-task paradigm involving: an auditory language comprehension task (sentence comprehension) and a non-verbal Flanker task (including congruent and incongruent trials). We manipulated sentence ambiguity and evaluated if the ambiguity effect modified behavioral performances in the non-verbal Flanker task. Under the assumption that ambiguous sentences induce a more difficult process than unambiguous sentences, we expected non-verbal flanker task performances to be impaired only when a simultaneous difficult language processing is performed. This would be specifically reflected by a performance cost during incongruent Flanker items only during ambiguous sentence presentation. Conversely, we observed a facilitatory effect for the incongruent Flanker items during ambiguous sentence suggesting better non-verbal inhibitory performances when an ambiguous sentence was simultaneously processed. Exploratory data analysis suggests that this effect is not only related to a more difficult language processing but also to the previous (n-1) Flanker item. Indeed, results showed that incongruent n-1 Flanker items led to a facilitation of the incongruent synchronized Flanker items only when ambiguous sentences were conjointly presented. This result, even if it needs to be corroborated in future studies, suggests that the recruitment of executive control mechanisms facilitates subsequent executive control implication during difficult language processing. The present study suggests a common executive control mechanism during difficult verbal and non-verbal tasks.

Probabilistic mapping of language networks from high frequency activity induced by direct electrical stimulation

Direct electrical stimulation (DES) at 50 Hz is used as a gold standard to map cognitive functions but little is known about its ability to map large‐scale networks and specific subnetwork. In the present study, we aim to propose a new methodological approach to evaluate the specific hypothesis suggesting that language errors/dysfunction induced by DES are the result of large‐scale network modification rather than of a single cortical region, which explains that similar language symptoms may be observed after stimulation of different cortical regions belonging to this network. We retrospectively examined 29 patients suffering from focal drug‐resistant epilepsy who benefitted from stereo‐electroencephalographic (SEEG) exploration and exhibited language symptoms during a naming task following 50 Hz DES. We assessed the large‐scale language network correlated with behavioral DES‐induced responses (naming errors) by quantifying DES‐induced changes in high frequency activity (HFA, 70–150 Hz) outside the stimulated cortical region. We developed a probabilistic approach to report the spatial pattern of HFA modulations during DES‐induced language errors. Similarly, we mapped the pattern of after‐discharges (3–35 Hz) occurring after DES. HFA modulations concurrent to language symptoms revealed a brain network similar to our current knowledge of language gathered from standard brain mapping. In addition, specific subnetworks could be identified within the global language network, related to different language processes, generally described in relation to the classical language regions. Spatial patterns of after‐discharges were similar to HFA induced during DES. Our results suggest that this new methodological DES‐HFA mapping is a relevant approach to map functional networks during SEEG explorations, which would allow to shift from “local” to “network” perspectives.