The neuroconnectionist research programme.

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have been not only lauded as the current best models of information processing in the brain but also criticized for failing to account for basic cognitive functions. In this Perspective article, we propose that arguing about the successes and failures of a restricted set of current ANNs is the wrong approach to assess the promise of neuroconnectionism for brain science. Instead, we take inspiration from the philosophy of science, and in particular from Lakatos, who showed that the core of a scientific research programme is often not directly falsifiable but should be assessed by its capacity to generate novel insights. Following this view, we present neuroconnectionism as a general research programme centred around ANNs as a computational language for expressing falsifiable theories about brain computation. We describe the core of the programme, the underlying computational framework and its tools for testing specific neuroscientific hypotheses and deriving novel understanding. Taking a longitudinal view, we review past and present neuroconnectionist projects and their responses to challenges and argue that the research programme is highly progressive, generating new and otherwise unreachable insights into the workings of the brain.

Recent Advances at the Interface of Neuroscience and Artificial Neural Networks.

Biological neural networks adapt and learn in diverse behavioral contexts. Artificial neural networks (ANNs) have exploited biological properties to solve complex problems. However, despite their effectiveness for specific tasks, ANNs are yet to realize the flexibility and adaptability of biological cognition. This review highlights recent advances in computational and experimental research to advance our understanding of biological and artificial intelligence. In particular, we discuss critical mechanisms from the cellular, systems, and cognitive neuroscience fields that have contributed to refining the architecture and training algorithms of ANNs. Additionally, we discuss how recent work used ANNs to understand complex neuronal correlates of cognition and to process high throughput behavioral data.

Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses.

An ideal vision model accounts for behavior and neurophysiology in both naturalistic conditions and designed lab experiments. Unlike psychological theories, artificial neural networks (ANNs) actually perform visual tasks and generate testable predictions for arbitrary inputs. These advantages enable ANNs to engage the entire spectrum of the evidence. Failures of particular models drive progress in a vibrant ANN research program of human vision.

Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future.

Convolutional neural networks (CNNs) were inspired by early findings in the study of biological vision. They have since become successful tools in computer vision and state-of-the-art models of both neural activity and behavior on visual tasks. This review highlights what, in the context of CNNs, it means to be a good model in computational neuroscience and the various ways models can provide insight. Specifically, it covers the origins of CNNs and the methods by which we validate them as models of biological vision. It then goes on to elaborate on what we can learn about biological vision by understanding and experimenting on CNNs and discusses emerging opportunities for the use of CNNs in vision research beyond basic object recognition.

Sharp injuries and their relationship with stress among nurses working in acute care settings.

BACKGROUND: Sharp injuries are common reasons for the transmission of blood-borne diseases in acute care settings. Fear of sharp injuries and their consequences can expose nurses to high levels of stress (sharp injuries stress). AIM: To examine the occurrence of sharp injuries and to assess their relationship with stress among nurses working in acute care settings. DESIGN: This was a cross-sectional study. METHODS: A total of 150 nurses working in 10 acute care settings in two selected hospitals in Alexandria, Egypt, were selected as the population of this study. Data on the occurrence of sharp injuries were collected using a sharp injuries circumstances questionnaire (including questions regarding number, instrument and reasons/procedures that caused sharp injuries, etc.), and two scales were used to measure sharp injuries stress (the Impact of Event Scale-Revised and the Post-Traumatic Stress Syndrome Questions Inventory). RESULTS: More than 13% of nurses experienced sharp injuries, and 25% of injuries were caused by contaminated instruments. Sharp injuries stress scores were high in nurses, with 65% of nurses experiencing sharp injuries and 30.8% of nurses who did not experience sharp injuries having high Impact of Event Scale-Revised scores. In addition, 45% of nurses who experienced sharp injuries and 15.39% of nurses who did not experience sharp injuries had high Post-Traumatic Stress Syndrome Questions Inventory (PTSSQI) scores. There was a significant relationship between the occurrence of sharp injuries and stress scales at P < .05. CONCLUSIONS: Nurses are exposed to sharp injuries, leading to sharp injury stress pre- and post-occurrence of injuries. Sharp injuries stress can make nurses prone to Post-Traumatic Stress Syndrome (PTSS). RELEVANCE TO CLINICAL PRACTICE: Factors that lead to the occurrence of sharp injuries and sharp injuries stress should be investigated, and a psychological rehabilitation unit should be instituted to help nurses working in acute care settings deal with the sharp injuries-related stressors they are facing.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed" selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training.SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli-and in particular, to combinations of stimuli ("mixed selectivity")-is a topic of interest. Even though models with random feedforward connectivity are capable of creating computationally relevant mixed selectivity, such a model does not match the levels of mixed selectivity seen in the data analyzed in this study. Adding simple Hebbian learning to the model increases mixed selectivity to the correct level and makes the model match the data on several other relevant measures. This study thus offers predictions on how mixed selectivity and other properties evolve with training.

The Association Between Mild Cognitive Impairment and Self-care in Adults With Chronic Heart Failure: A Systematic Review and Narrative Synthesis.

BACKGROUND: Emerging evidence suggests that heart failure (HF) patients who have mild cognitive impairment (MCI) may experience greater difficulty with self-care. OBJECTIVE: This article reports a systematic review that addressed the objective "What is the evidence for an association between MCI and self-care, measured in 1 or more of the self-care domains related to HF, in adults who have a diagnosis of chronic HF?" METHOD: We adopted Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for the review and synthesis of quantitative research studies that formally measured both cognitive function and self-care in HF patients and sought to describe the relationship between these factors. RESULTS: Ninety-one potentially relevant studies were located; 10 studies (2006-2014) were included. Because of heterogeneity in the retrieved studies, meta-analysis was not possible. Narrative synthesis found growing evidence regarding the association between MCI and adverse effects on self-care in HF. Nine studies reported significant positive associations between MCI and self-care in HF, either specifically in relation to medication adherence or more generic measures of self-care activity. One study reported a significant, negative correlation between cognitive function and self-care, suggesting that worse cognitive function was associated with better self-care; however, this is partially explained by a small sample size and mixed methodology. CONCLUSIONS: These findings have implications for clinical practice. It is known that HF patients have difficulty with self-care, and the influence of cognitive function needs to be considered when providing professional support. Further research to determine the feasibility and acceptability of cognitive assessment in routine clinical care is recommended.

Inpatients' attitudes to a personalised drug service.

NHS Greater Glasgow and Clyde's Making the Most of Your Medicines service involves a more patient-centred approach to inpatient medication administration. A study explored patients' knowledge, experiences and views of the service.

Grounding neuroscience in behavioral changes using artificial neural networks.

Connecting neural activity to function is a common aim in neuroscience. How to define and conceptualize function, however, can vary. Here I focus on grounding this goal in the specific question of how a given change in behavior is produced by a change in neural circuits or activity. Artificial neural network models offer a particularly fruitful format for tackling such questions because they use neural mechanisms to perform complex transformations and produce appropriate behavior. Therefore, they can be a means of causally testing the extent to which a neural change can be responsible for an experimentally observed behavioral change. Furthermore, because the field of interpretability in artificial intelligence has similar aims, neuroscientists can look to interpretability methods for new ways of identifying neural features that drive performance and behaviors.

Extracellular ISG15 triggers ISGylation via a type-I interferon independent mechanism to regulate host response during virus infection.

Type-I interferons (IFN) are key antiviral factors that induce several cellular proteins with antiviral activity. One such protein is Interferon Stimulated Gene 15 (ISG15). ISG15 is conjugated to proteins during ISGylation to confer antiviral activity. Apart from ISGylation, unconjugated ISG15 is also released from cells during immuno-stimulation and virus infection. The role of extracellular ISG15 during virus infection was unknown. We now show that extracellular ISG15 acts as a soluble antiviral factor to restrict virus infection in human epithelial cells via an IFN-independent mechanism. Additionally, we demonstrated that extracellular ISG15 induces expression of intracellular ISG15 and ISGylation in the absence of IFN. Mechanistic studies revealed that extracellular ISG15 interacts with cell surface integrin (α5ß1 integrins) molecules via its RGD-like motif to activate the integrin-FAK (Focal Adhesion Kinase) pathway resulting in IFN-independent ISGylation. Thus, our studies have identified ISG15 protein as a new soluble factor that confers IFN-independent antiviral activity by inducing ISGylation. Additionally, we have unfolded an IFN-independent non-canonical ISGylation by extracellular ISG15 that operates via the integrin-FAK pathway.

Diet quality indices and odds of metabolic dysfunction-associated fatty liver disease: a case-control study.

Objectives: There are only limited studies investigating the impact of dietary quality indicators, such as dietary quality index (DQI), dietary diversity score (DDS), and alternative healthy eating index (AHEI), on metabolic dysfunction-associated fatty liver disease (MASLD). Furthermore, these indicators may have different components that could lead to varying results. Therefore, this study aims to assess the nutritional quality indicators and their potential association with MASLD. Methods: The study included 128 recently diagnosed MASLD patients and 256 controls aged between 20 and 60 years. The dietary intake of participants was evaluated using a validated semi-quantitative food frequency questionnaire that consisted of 168 items. In this study, the method used to evaluate dietary diversity was based on five main food groups, specifically bread and grains, vegetables, fruits, meat, and dairy. The AHEI-2010 was computed using data collected from the FFQ. Results: After adjusting for confounders in the fully adjusted model, a significant negative correlation was observed between DDS and the risk of MASLD (OR 0.41, 95% CI 0.20, 0.97). Participants in the top quartile of AHEI had a 76% lower risk of MASLD compared with those in the bottom quartile after controlling for all potential confounders in the fully adjusted model (OR 0.24, 95% CI 0.12, 0.56). Conclusion: The results of our study suggest that there is a significant association between adherence to a high-diversity diet and a reduced likelihood of developing MASLD. Similarly, we observed a similar association between adherence to the AHEI diet and a lower risk of MASLD.

Proinflammatory Responses in SARS-CoV-2 and Soluble Spike Glycoprotein S1 Subunit Activated Human Macrophages.

Critically ill COVID-19 patients display signs of generalized hyperinflammation. Macrophages trigger inflammation to eliminate pathogens and repair tissue, but this process can also lead to hyperinflammation and resulting exaggerated disease. The role of macrophages in dysregulated inflammation during SARS-CoV-2 infection is poorly understood. We inoculated and treated human macrophage cell line THP-1 with SARS-CoV-2 and purified, glycosylated, soluble SARS-CoV-2 spike protein S1 subunit (S1) to clarify the role of macrophages in pro-inflammatory responses. Soluble S1 upregulated TNF-α and CXCL10 mRNAs, and induced secretion of TNF-α from THP-1 macrophages. While THP-1 macrophages did not support productive SARS-CoV-2 replication or viral entry, virus exposure resulted in upregulation of both TNF-α and CXCL10 genes. Our study shows that extracellular soluble S1 protein is a key viral component inducing pro-inflammatory responses in macrophages, independent of virus replication. Thus, virus- or soluble S1-activated macrophages may become sources of pro-inflammatory mediators contributing to hyperinflammation in COVID-19 patients.

Patient mortality in the 12 years following enrolment into a pre-surgical cardiac rehabilitation programme.

OBJECTIVE: This study examined whether involvement in a pre-surgical cardiac rehabilitation programme conferred a long-term survival benefit. DESIGN: Patients randomly allocated to a pre-surgical cardiac rehabilitation programme intervention or a control group were tracked through national databases at a point approximately 12 years later, and all causes of mortality were identified from death records. Kaplan-Meier survival analyses based on involvement in a cardiac rehabilitation programme and known pre-surgical risk factors were carried out. SETTING: Two health boards in the west of Scotland, referring to a single cardiothoracic tertiary centre. SUBJECTS: Patients admitted to the waiting list for coronary artery bypass surgery. INTERVENTIONS: Patients were randomly allocated to a control group ('usual' care) or an intervention group (nurse-led cardiac rehabilitation) in the pre-operative phase. They were followed up at 12 years post surgery. MAIN MEASURES: The only outcome measure used for analysis was survival. Measures of anxiety and depression, and physiological and lifestyle risk factors were included as independent variables in analysis of death. RESULTS: The initial study included 110 patients--none were lost to follow-up. Relative risk of death associated with inclusion in the cardiac rehabilitation programme was 0.814; risk of death increased with increasing pre-surgical depression (RR 1.07) and anxiety (RR 1.09). CONCLUSIONS: Undertaking pre-surgical cardiac rehabilitation confers a long-term survival advantage over patients not offered this service. Increased anxiety and depression in the pre-surgical phase are additional risk factors for increased mortality.

Human Respiratory Syncytial Virus NS2 Protein Induces Autophagy by Modulating Beclin1 Protein Stabilization and ISGylation.

Paramyxoviruses such as respiratory syncytial virus (RSV) are the leading cause of pneumonia in infants, the elderly, and immunocompromised individuals. Understanding host-virus interactions is essential for the development of effective interventions. RSV induces autophagy to modulate the immune response. The viral factors and mechanisms underlying RSV-induced autophagy are unknown. Here, we identify the RSV nonstructural protein NS2 as the virus component mediating RSV-induced autophagy. We show that NS2 interacts and stabilizes the proautophagy mediator Beclin1 by preventing its degradation by the proteasome. NS2 further impairs interferon-stimulated gene 15 (ISG15)-mediated Beclin1 ISGylation and generates a pool of "hypo-ISGylated" active Beclin1 to engage in functional autophagy. Studies with NS2-deficient RSV revealed that NS2 contributes to RSV-mediated autophagy during infection. The present study is the first report to show direct activation of autophagy by a paramyxovirus nonstructural protein. We also report a new viral mechanism for autophagy induction wherein the viral protein NS2 promotes hypo-ISGylation of Beclin1 to ensure availability of active Beclin1 to engage in the autophagy process. IMPORTANCE Understanding host-virus interactions is essential for the development of effective interventions against respiratory syncytial virus (RSV), a paramyxovirus that is a leading cause of viral pneumonia in infants. RSV induces autophagy following infection, although the viral factors involved in this mechanism are unknown. Here, we identify the RSV nonstructural protein 2 (NS2) as the virus component involved in autophagy induction. NS2 promotes autophagy by interaction with and stabilization of the proautophagy mediator Beclin1 and by impairing its ISGylation to overcome autophagy inhibition. To the best of our knowledge, this is the first report of a viral protein regulating the autophagy pathway by modulating ISGylation of autophagy mediators. Our studies highlight a direct role of a paramyxovirus nonstructural protein in activating autophagy by interacting with the autophagy mediator Beclin1. NS2-mediated regulation of the autophagy and ISGylation processes is a novel function of viral nonstructural proteins to control the host response against RSV.

Promoting recruitment of minority ethnic groups into research: qualitative study exploring the views of South Asian people with asthma.

BACKGROUND: We sought to understand the barriers and facilitators to participation in research from the perspectives of South Asian people with asthma. METHODS: Eight focus groups were conducted in the preferred language of participants. Sampling was purposeful to ensure inclusion of males and females from differing ethnic, linguistic and religious backgrounds. RESULTS: The forming of trusting relationships was described as pivotal to the successful recruitment of minority ethnic groups into research; personalized approaches were likely to be better received than more impersonal written approaches. Notable barriers to participation included: the stigma of being labelled with asthma; concerns surrounding participation in pharmaceutical trials; major time or travel commitments and a failure to show respect by not making information available in minority ethnic languages. Flexibility, in terms of timing, location and respecting of cultural and religious sensitivities around gender segregation, together with the offer of incentives, were highlighted as key factors to promote participation. CONCLUSIONS: The barriers to recruitment are largely surmountable, but these will necessitate the use of resource intensive and more personalized approaches than are commonly employed for the White European origin population. Our proposed model to enhance recruitment is likely to have transferability beyond the field of asthma.

Corrigendum: Attention in Psychology, Neuroscience, and Machine Learning.

[This corrects the article DOI: 10.3389/fncom.2020.00029.].

Proinflammatory responses in SARS-CoV-2 infected and soluble spike glycoprotein S1 subunit activated human macrophages.

Critically ill COVID-19 patients infected with SARS-CoV-2 display signs of generalized hyperinflammation. Macrophages trigger inflammation to eliminate pathogens and repair tissue, but this process can also lead to hyperinflammation and resulting exaggerated disease. The role of macrophages in dysregulated inflammation during SARS-CoV-2 infection is poorly understood. We used SARS-CoV-2 infected and glycosylated soluble SARS-CoV-2 Spike S1 subunit (S1) treated THP-1 human-derived macrophage-like cell line to clarify the role of macrophages in pro-inflammatory responses. Soluble S1 upregulated TNF-α and CXCL10 mRNAs, and induced secretion of TNF-α from THP-1 macrophages. While THP-1 macrophages did not support productive SARS-CoV-2 replication, virus infection resulted in upregulation of both TNF-α and CXCL10 genes. Our study shows that S1 is a key viral component inducing inflammatory response in macrophages, independently of virus replication. Thus, virus-infected or soluble S1-activated macrophages may become sources of pro-inflammatory mediators contributing to hyperinflammation in COVID-19 patients.

Attention in Psychology, Neuroscience, and Machine Learning.

Attention is the important ability to flexibly control limited computational resources. It has been studied in conjunction with many other topics in neuroscience and psychology including awareness, vigilance, saliency, executive control, and learning. It has also recently been applied in several domains in machine learning. The relationship between the study of biological attention and its use as a tool to enhance artificial neural networks is not always clear. This review starts by providing an overview of how attention is conceptualized in the neuroscience and psychology literature. It then covers several use cases of attention in machine learning, indicating their biological counterparts where they exist. Finally, the ways in which artificial attention can be further inspired by biology for the production of complex and integrative systems is explored.

Perceptions of a service redesign by adults living with type 2 diabetes.

AIM: This article is a report of a study conducted to explore the perceptions of adults with type 2 diabetes towards the service redesign. BACKGROUND: Diabetes is reaching epidemic proportions and the management of this chronic illness is changing in response to this challenge. In the United Kingdom, there is ongoing restructuring of healthcare services for people with chronic illnesses to ensure that their general health and clinical needs are met predominantly in primary care. METHOD: An explorative qualitative approach was used. Eight focus groups were conducted with 35 people with type 2 diabetes in one urban location between 2003 and 2004. Five focus groups were conducted with people who had recently experienced the restructured service and three groups with people who had up to 2 years' experience of the new service. Concurrent data collection and thematic analysis were conducted by three researchers and credibility and verification sought by feedback to participants. FINDINGS: Five main themes were identified: impact of living with diabetes; understanding diabetes; drivers for organizational change; care in context and individual concerns. Participants identified issues for ongoing development of the service. CONCLUSION: People with type 2 diabetes appreciate their care management within the primary care setting where there has been investment in staff to deliver this care. Healthcare resources are required to support the development of staff and the necessary infrastructure to undertake management in primary care. Policy makers need to address the balance of resources between primary and secondary care.

Accuracy of patient recall of preoperative symptom severity (angina and breathlessness) at one year following aorta-coronary artery bypass grafting.

AIM AND OBJECTIVE: The accuracy with which patients recall their cardiac symptoms prior to aorta-coronary artery bypass grafting is assessed approximately one year after surgery together with patient-related factors potentially influencing accuracy of recall. BACKGROUND: This is a novel investigation of patient's rating of preoperative symptom severity before and approximately one year following aorta-coronary artery bypass grafting. DESIGN: Patients undergoing aorta-coronary artery bypass grafting (n = 208) were recruited preoperatively and 177 of these were successfully followed up at 16.4 (SD 2.1) months after surgery and asked to describe current and recalled preoperative symptoms using a 15-point numerical scale. METHOD: Accuracy of recall was measured and correlated (Pearson's correlation) with current and past symptoms, health-related quality of life and coronary artery disease risk factors. Hypothesis tests used Student's t-test and the chi-squared test. RESULTS: Respective angina and breathlessness scores were recalled accurately by 16.9% and 14.1% while 59% and 58% were inaccurate by more than one point. Although the mean preoperative and recalled scores for severity of both angina and breathlessness and were not statistically different, patients who recalled most accurately their preoperative scores had, on average, significantly higher preoperative scores than those with less accurate recall. Patients whose angina and breathlessness symptoms were relieved by operation had significantly better accuracy of recall than patients with greater levels of symptoms postoperatively. CONCLUSION: Patient's rating of preoperative symptom severity before and one year following aorta-coronary artery bypass grafting was completely accurate in approximately one sixth of patients with similar proportions of the remaining patients overestimating and underestimating symptoms. The extent to which angina and breathlessness was relieved by operation was a significant factor in improving accuracy of recall. RELEVANCE TO CLINICAL PRACTICE: Factors associated with accuracy of recall of symptoms provide useful insights for clinicians when interpreting patients' views of the effectiveness of aorta-coronary artery bypass grafting for the relief of symptoms associated with coronary heart disease.