Swiftly halting ongoing motor actions is essential to react to unforeseen and potentially perilous circumstances. However, the neural bases subtending the complex interplay between emotions and motor ...control have been scarcely investigated. Here, we used an emotional stop signal task (SST) to investigate whether specific neural circuits engaged by action suppression are differently modulated by emotional signals with respect to neutral ones. Participants performed an SST before and after the administration of one session of repetitive transcranial magnetic stimulation (rTMS) over the pre‐supplementary motor cortex (pre‐SMA), the right inferior frontal gyrus (rIFG), and the left primary motor cortex (lM1). Results show that rTMS over the pre‐SMA improved the ability to inhibit prepotent action (i.e., better action control) when emotional stimuli were presented. In contrast, action control in a neutral context was fostered by rTMS over the rIFG. No changes were observed after lM1 stimulation. Intriguingly, individuals with higher impulsivity traits exhibited enhanced motor control when facing neutral stimuli following rIFG stimulation. These results further our understanding of the interplay between emotions and motor functions, shedding light on the selective modulation of neural pathways underpinning these processes.
The ability to interrupt ongoing actions is crucial to face unexpected circumstances. However, the neural underpinnings of the interplay between inhibitory action control and emotions have only been marginally studied. Here, we investigated the involvement of key neural circuits in action control in different emotional contexts using the stop signal task. The results show that specific brain areas are selectively involved in stopping performance in either emotional or neutral settings.
Learning to recognize and respond to potential threats is crucial for survival. Pavlovian threat conditioning represents a key paradigm for investigating the neurobiological mechanisms of fear ...learning. In this review, we address the role of specific neuropharmacological adjuvants that act on neurochemical synaptic transmission, as well as on brain plasticity processes implicated in fear memory. We focus on novel neuropharmacological manipulations targeting glutamatergic, noradrenergic, and endocannabinoid systems, and address how the modulation of these neurobiological systems affects fear extinction learning in humans. We show that the administration of N-methyl-D-aspartate (NMDA) agonists and modulation of the endocannabinoid system by fatty acid amide hydrolase (FAAH) inhibition can boost extinction learning through the stabilization and regulation of the receptor concentration. On the other hand, elevated noradrenaline levels dynamically modulate fear learning, hindering long-term extinction processes. These pharmacological interventions could provide novel targeted treatments and prevention strategies for fear-based and anxiety-related disorders.
Emotions are able to impact our ability to control our behaviors. However, it is not clear whether emotions play a detrimental or an advantageous effect on action control and whether the valence of ...the emotional stimuli differently affects such motor abilities. One way to measure reactive inhibitory control is the stop-signal task (SST), which estimates the ability to cancel outright a response to the presentation of a stop signal by means of the stop signal reaction times (SSRT). Impaired as well as facilitated action control has been found when faced with emotional stimuli such as stop signals in SSTs and mixed results were observed for positive versus negative stimuli. Here, we aimed to investigate these unresolved issues more deeply. Action control capabilities were tested in 60 participants by means of a SST, in which the stop signals were represented by a fearful and a happy body posture together with their neutral counterpart. Results showed that both positive and negative body postures enhanced the ability to suppress an ongoing action compared to neutral body postures. These results demonstrate that emotional valence-independent emotional stimuli facilitate action control and suggest that emotional stimuli may trigger increased sensory representation and/or attentional processing that may have promote stop-signal processing and hence improved inhibitory performance.
Fear extinction is a phenomenon that involves a gradual reduction in conditioned fear responses through repeated exposure to fear-inducing cues. Functional brain connectivity assessments, such as ...functional magnetic resonance imaging (fMRI), provide valuable insights into how brain regions communicate during these processes. Stress, a ubiquitous aspect of life, influences fear learning and extinction by changing the activity of the amygdala, prefrontal cortex, and hippocampus, leading to enhanced fear responses and/or impaired extinction. Glucocorticoid receptors (GRs) are key to the stress response and show a dual function in fear regulation: while they enhance the consolidation of fear memories, they also facilitate extinction. Accordingly, GR dysregulation is associated with anxiety and mood disorders. Recent advancements in cognitive neuroscience underscore the need for a comprehensive understanding that integrates perspectives from the molecular, cellular, and systems levels. In particular, neuropharmacology provides valuable insights into neurotransmitter and receptor systems, aiding the investigation of mechanisms underlying fear regulation and potential therapeutic targets. A notable player in this context is cortisol, a key stress hormone, which significantly influences both fear memory reconsolidation and extinction processes. Gaining a thorough understanding of these intricate interactions has implications in terms of addressing psychiatric disorders related to stress. This review sheds light on the complex interactions between cognitive processes, emotions, and their neural bases. In this endeavor, our aim is to reshape the comprehension of fear, stress, and their implications for emotional well-being, ultimately aiding in the development of therapeutic interventions.
Since the dawn of cognitive neuroscience, emotions have been recognized to impact on several executive processes, such as action inhibition. However, the complex interplay between emotional stimuli ...and action control is not yet fully understood. One way to measure inhibitory control is the stop-signal task (SST), which estimates the ability to cancel outright an action to the presentation of a stop signal by means of the stop-signal reaction times (SSRTs). Impaired as well as facilitated action control has been found when faced with intrinsic emotional stimuli as stop signals in SSTs. Here, we aimed at investigating more deeply the power of negative stimuli to influence our action control, testing the hypothesis that a previously neutral stimulus i.e., the image of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has been conditioned through vicarious fear learning, has the same impact on reactive action inhibition performance as an intrinsically negative stimulus (i.e., a fearful face or body). Action control capabilities were tested in 90 participants by means of a SST, in which the stop signals were represented by different negative stimuli. Results showed that the SARS-CoV-2 image enhanced the ability to suppress an ongoing action similarly to observing fearful facial expressions or fearful body postures. Interestingly, we found that this effect was predicted by impulsivity traits: for example, the less self-control the participants had, the less they showed emotional facilitation for inhibitory performance. These results demonstrated that vicarious fear learning has a critical impact on cognitive abilities, making a neutral image as threatening as phylogenetically innate negative stimuli and able to impact on our behavioral control.
Modern Machine Learning (ML) has significantly advanced various research fields, but the opaque nature of ML models hinders their adoption in several domains. Explainable AI (XAI) addresses this ...challenge by providing additional information to help users understand the internal decision-making process of ML models. In the field of neuroscience, enriching a ML model for brain decoding with attribution-based XAI techniques means being able to highlight which brain areas correlate with the task at hand, thus offering valuable insights to domain experts. In this paper, we analyze human and Computer Vision (CV) systems in parallel, training and explaining two ML models based respectively on functional Magnetic Resonance Imaging (fMRI) and movie frames. We do so by leveraging the "StudyForrest" dataset, which includes functional Magnetic Resonance Imaging (fMRI) scans of subjects watching the "Forrest Gump" movie, emotion annotations, and eye-tracking data. For human vision the ML task is to link fMRI data with emotional annotations, and the explanations highlight the brain regions strongly correlated with the label. On the other hand, for computer vision, the input data is movie frames, and the explanations are pixel-level heatmaps. We cross-analyzed our results, linking human attention (obtained through eye-tracking) with XAI saliency on CV models and brain region activations. We show how a parallel analysis of human and computer vision can provide useful information for both the neuroscience community (allocation theory) and the ML community (biological plausibility of convolutional models).
No data are available on the quality of targeted temperature management (TTM) provided to out-of-hospital cardiac arrest (OHCA) patients and its association with outcome.
Post hoc analysis of the ...TTH48 study (NCT01689077), which compared the effects of prolonged TTM at 33 °C for 48 h to standard 24-h TTM on neurologic outcome. Admission temperature, speed of cooling, rewarming rates, precision (i.e. temperature variability), overcooling and overshooting as post-cooling fever (i.e. >38.0 °C) were collected. A specific score, ranging from 1 to 9, was computed to define the “quality of TTM”.
On a total of 352 patients, most had a moderate quality of TTM (n = 217; 62% — score 4–6), while 80 (23%) patients had a low quality of TTM (score 1–3) and only 52 (16%) a high quality of TTM (score 7–9). The proportion of patients with unfavorable neurological outcome (UO; Cerebral Performance Category of 3–5 at 6 months) was similar between the different quality of TTM groups (p = 0.90). Although a shorter time from arrest to target temperature and a lower proportion of time outside the target ranges in the TTM 48-h than in the TTM 24-h group, quality of TTM was similar between groups. Also, the proportion of patients with UO was similar between the different quality of TTM groups when TTM 48-h and TTM 24-h were compared.
In this study, high quality of TTM was provided to a small proportion of patients. However, quality of TTM was not associated with patients’ outcome.
Current guidelines suggest high-dose steroids as first-line treatment for dysthyroid optic neuropathy (DON). When steroids fail, decompressive surgery is mandatory.
We conducted a single-center, ...retrospective cohort study in a tertiary care combined Thyroid-Eye clinic in Milan, Italy. We studied 88 orbits of 56 patients that were submitted to surgical orbital decompression to treat DON from 2005 to 2020. Of these, 33 orbits (37.5%) underwent surgery as first-line treatment for DON whereas the other 55 (62.5%) were decompressed after being unresponsive to very high-dose steroids. Previous orbital surgery, concurrent neurological or ophthalmologic diseases, or incomplete follow-up were considered as exclusion criteria from this study. Surgery was considered successful if no further decompression was needed to preserve vision. Pinhole best corrected visual acuity (p-BCVA), color sensitivity, automated visual field, pupil reflexes, optic disk and fundus appearance, exophtalmometry, and ocular motility were studied before and after surgery (1 week, 1, 3, 6, and 12 months). Activity of Graves' Orbitopathy (GO) was graded using a clinical activity score (CAS).
Surgery was successful in 77 orbits (87.5%). The remaining 11 orbits (12.5%) needed further surgery to treat DON definitively. All parameters of visual function improved significantly at follow-up and GO inactivated (CAS <3) within 1 month. At 3 months, all 77 responding orbits had p-BCVA >0.63 whereas all of the 11 non-responding orbits had p-BCVA ≤0.63. Visual field parameters and color sensitivity were not associated with response to surgery. High-dose steroid treatment before surgery was associated with a better response rate (96% vs. 73%;
= 0.004). Balanced decompression was associated with a higher response rate compared with medial wall decompression (96% vs. 80%;
= 0.04). A significant inverse correlation was observed between final p-BCVA and the patient's age (
= -0.42;
= 0.0003).
Surgical decompression was found to be a very effective treatment for DON. In this study, all clinical parameters improved after surgery and further intervention was rarely needed.
This article addresses the problem of optimizing voltage profiles in distribution networks. The voltage optimization is split into two stages; the former is performed offline and the latter online. ...First, the network is partitioned into several weakly coupled voltage control zones (VCZs) with pilot nodes (PNs). Then, the partitioning is used to optimize the voltage profiles of the distribution systems on the frame of a two time-scale-based coordinated approach. At the first level, a centralized voltage optimization problem (VOP), minimizing the distance of bus voltages at the PNs from their reference values and subject to linearized power flow equations, is solved to fix the positions of the on-load tap changer and of step-voltage regulators, and the reactive powers provided by capacitor banks. At the second level, the VOP is implemented according to a decentralized approach, in which the solution is obtained by applying a distributed algorithm based on the alternating direction method of multipliers. It optimizes in each VCZ the voltage at the PN by acting on the active and reactive powers provided by the distributed energy resources present in the VCZ; the VCZ solutions are driven to the global optimum of the whole distribution system by a limited data exchange between the PNs. The proposed approach reduces the complexity and computational burden typical when solving the VOP on a large scale system. The proposed strategy is tested on the modified IEEE 123-bus system; various load and generation scenarios are analyzed proving the effectiveness of the proposed approach in achieving the objective of voltage regulation.
