Archivio della ricerca della Scuola Superiore Sant'Anna
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Kernel-based LFP estimation in detailed large-scale spiking network model of mouse visual cortex
Get PDFSimulations of large-scale neural activity are an increasingly important tool for investigating neural network activity. Calculating measurable brain signals, like the local field potential (LFP) from such simulations is crucial because it bridges the gap between model predictions and experimental observations and helps us better understand the information content of such signals. Accurately simulating LFPs from large-scale neural network models has, however, required highly biologically detailed models, which pose significant computational challenges, and have limited their practical application.
In this study, we demonstrate that a kernel-based method can accurately and efficiently estimate the LFPs simulated in a highly detailed multicompartmental network model of the mouse primary visual cortex (V1), in response to both drifting gratings and full-field flashes of light.
Beyond enabling computationally efficient and accurate LFP estimation, the kernel method also aids analysis by disentangling the contributions of individual neuronal populations to the LFP. Leveraging this capability, we found that the LFP in the mouse V1 model was dominated by external synaptic inputs: feedback from lateromedial visual areas in the upper visual layers, and thalamic afferents in layer 4. In contrast, local synaptic activity from V1 neuronal families contributed only marginally to the LFP. We further demonstrated how correlations between external and local neural activity could mask this insight in experimental data.
Our findings demonstrate the kernel method as an accurate tool for LFP estimation in state-of-the-art large-scale network models. Moreover, we highlight its potential to reveal novel insights into the neural mechanisms that shape measurable brain signals
Promoting MENA tourism thought public diplomacy: the case of Ningxia autonomous region and its Hui minority
No full textEtiological Treatment of Cardiac Amyloidosis: Standard of Care and Future Directions
No full textPurpose of Review: Cardiac amyloidosis (CA) is a condition caused by interstitial infiltration of misfolded proteins structured into amyloid fibrils. Transthyretin (ATTR) and immunoglobulin light chain (AL) amyloidosis represent the most common forms of CA. CA was traditionally perceived as a rare and incurable disease, but diagnostic and therapeutic advances have undermined the conventional paradigm. Recent Findings: The standard of care for ATTR-CA include agents capable of selectively stabilizing the precursor protein (e.g., tafamidis), whereas the plasma cell clone is the main target of chemotherapy for AL-CA. For long, tafamidis represented the only drug approved for patients with ATTR-CA. Recent data from ATTRibute-CM led to the approval of acoramidis, whereas patisiran received refusal based on the APOLLO-B trial. Novel CRISPR-Cas9-based drugs (i.e., NTLA-2001) hold great potential in the setting of ATTR-CA. Several hematological regimens are available to treat AL-CA. The main limit of current therapies is their inability to trigger removal of amyloid from tissues. However, the investigation of monoclonal antibodies targeting misfolded ATTR (e.g., PRX004, NI301A) or AL (e.g., birtamimab, anselamimab) has led to encouraging results. Summary: Various cutting-edge strategies are being tested for treatment of CA and may change the prognostic landscape of this condition in the next years
Navigating Transnational Innovation. Best Practices in Academic Cooperation between Italy and China
No full textCostituzionalismo “off-shore” e insularità: la sovranità “limitata” delle Dipendenze della Corona Britannica
Get PDFWars, Depression, and Fascism: Income Inequality in Italy, 1901-1950
Get PDFThis paper presents yearly estimates of income inequality in Italy from 1901 to 1950. By constructing dynamic social tables, we comprehensively assess inequality across all elements of Italian society and compare Italy with other countries over the same period. In a context of declining inequality across Europe, interwar Italy reveals a trajectory at odds with consolidated narratives: a sharp increase of inequality during World War I, a reversal during 1918–1922, a renewed rise after the Fascist takeover, and new peaks during World War II. Our results allow us to identify sizeable short-term distributive shocks and discuss the political economy of fascist Italy, reinforcing a reinterpretation of interwar inequality trends in Europe and the regressive nature of fascist regimes
Integrating optimization and LCA models in the steelmaking process: Insights from the ALCHIMIA project
Get PDFImproving the sustainability of the steelmaking sector is a challenging task because steelmakers are expected to meet environmental targets and strict quality requirements that depend on the final application of the product. Recycling steel in electric arc furnaces (EAFs) is a well-established
circular practice that helps reducing the environmental impact of steelmaking. However, an optimal combination of different scrap types and additions, along with minimum electricity and gas consumption during the melting phase, is necessary to ensure high quality and environmental
performance of final products. The process input mix can be improved by exploiting optimization tools and Life Cycle Assessment (LCA) to minimize a multi-objective function including environmental impacts, constrained by technical requirements of steel and process operating conditions. The paper presents a methodology to transform “traditional” LCA into an “optimized LCA approach”, focusing on how Life Cycle Inventories and Life Cycle Impact Assessment can be associated to optimization variables or inputs, depending on steelmakers’ ability to affect EAF-based steelmaking operational parameters. The discussion highlights opportunities and limitations of integrating LCA and optimization methodologies within the framework of a real-world case study carried out in the European project ALCHIMIA
Heart failure with improved ejection fraction: A dynamic journey of recovery and possible relapse
No full textRehabilitation robotics and allied digital technologies: opportunities, barriers and solutions for improving their clinical implementation. A position paper from the Fit for Medical Robotics Initiative
Get PDFRobotics has been proposed as a promising solution for treating individuals with motor, sensory, and/or cognitive disabilities. Despite the great technological effort put into this field, the translation of robots from the laboratory to
the clinical environment is not a seamless and smooth process, and their real-world adoption remains limited. Several barriers to the introduction of robotics in clinical practice have been identified, including a lack of sufficient scientific evidence about its actual cost/effectiveness, resistance to adopting these technologies, and economic, ethical, and regulatory restraints. Fit for Medical Robotics (Fit4MedRob) is an ambitious Initiative designed to bridge the gap between technological innovation and clinical application. One of the main goals of the Initiative is to conduct large-scale pragmatic trials to evaluate the effectiveness and the sustainability of commercially available robotic solutions. To guide the design of these trials, different online surveys have been implemented and delivered to identify the needs of healthcare practitioners and patients at different phases of the disease (acute to chronic) and therapeutic settings (hospital to home care). The results of the Initiative will suggest new organizational models to effectively introduce robotics-assisted rehabilitation into clinical practice. The paper will report on the opportunities of robotics for rehabilitation, the barriers to their clinical implementation, and the proposal of Fit4MedRob to overcome such limitations and facilitate the effective clinical implementation of robotic solutions