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Fitting in to school and social life can be the single most challenging task when you have Aspergers syndrome. Aspergers Rules! can help. Packed full of information, this book covers common school situations and the uncommon challenges that they can present to a child with Aspergers. Kids will find the how-to for understanding and communicating with peers and teachers, standing up for and taking care of themselves, setting realistic goals, and making friends.

Biological neural network models whereby brains make minds help to understand autonomous adaptive intelligence. This article summarizes why the dynamics and emergent properties of such models for perception, cognition, emotion, and action are explainable, and thus amenable to being confidently implemented in large-scale applications. Key to their explainability is how these models combine fast activations, or short-term memory (STM) traces, and learned weights, or long-term memory (LTM) traces. Visual and auditory perceptual models have explainable conscious STM representations of visual surfaces and auditory streams in surface-shroud resonances and stream-shroud resonances, respectively. Deep Learning is often used to classify data. However, Deep Learning can experience catastrophic forgetting: At any stage of learning, an unpredictable part of its memory can collapse. Even if it makes some accurate classifications, they are not explainable and thus cannot be used with confidence. Deep Learning shares these problems with the back propagation algorithm, whose computational problems due to non-local weight transport during mismatch learning were described in the 1980s. Deep Learning became popular after very fast computers and huge online databases became available that enabled new applications despite these problems. Adaptive Resonance Theory, or ART, algorithms overcome the computational problems of back propagation and Deep Learning. ART is a self-organizing production system that incrementally learns, using arbitrary combinations of unsupervised and supervised learning and only locally computable quantities, to rapidly classify large non-stationary databases without experiencing catastrophic forgetting. ART classifications and predictions are explainable using the attended critical feature patterns in STM on which they build. The LTM adaptive weights of the fuzzy ARTMAP algorithm induce fuzzy IF-THEN rules that explain what feature combinations predict successful outcomes. ART has been successfully used in multiple large-scale real world applications, including remote sensing, medical database prediction, and social media data clustering. Also explainable are the MOTIVATOR model of reinforcement learning and cognitive-emotional interactions, and the VITE, DIRECT, DIVA, and SOVEREIGN models for reaching, speech production, spatial navigation, and autonomous adaptive intelligence. These biological models exemplify complementary computing, and use local laws for match learning and mismatch learning that avoid the problems of Deep Learning.

This article describes mechanistic links that exist in advanced brains between processes that regulate conscious attention, seeing, and knowing, and those that regulate looking and reaching. These mechanistic links arise from basic properties of brain design principles such as complementary computing, hierarchical resolution of uncertainty, and adaptive resonance. These principles require conscious states to mark perceptual and cognitive representations that are complete, context sensitive, and stable enough to control effective actions. Surface–shroud resonances support conscious seeing and action, whereas feature–category resonances support learning, recognition, and prediction of invariant object categories. Feedback interactions between cortical areas such as peristriate visual cortical areas V2, V3A, and V4, and the lateral intraparietal area (LIP) and inferior parietal sulcus (IPS) of the posterior parietal cortex (PPC) control sequences of saccadic eye movements that foveate salient features of attended objects and thereby drive invariant object category learning. Learned categories can, in turn, prime the objects and features that are attended and searched. These interactions coordinate processes of spatial and object attention, figure–ground separation, predictive remapping, invariant object category learning, and visual search. They create a foundation for learning to control motor-equivalent arm movement sequences, and for storing these sequences in cognitive working memories that can trigger the learning of cognitive plans with which to read out skilled movement sequences. Cognitive–emotional interactions that are regulated by reinforcement learning can then help to select the plans that control actions most likely to acquire valued goal objects in different situations. Many interdisciplinary psychological and neurobiological data about conscious and unconscious behaviors in normal individuals and clinical patients have been explained in terms of these concepts and mechanisms.

نشر وليامز كتابه مفاتيح اصطلاحية عام 1976، ثم جدده ونشره في طبعة ثانية عام 1983، وكان هاجسه الأكبر في الطبعتين ألا يقتصر عمله على مجرد مسرد للمصطلحات في معجم، بل أن يجعل من المصطلح كيانا ثقافيا وتاريخيا يصنع ويصنع ويكون، ويفتح الحقول المعرفية بعضها على بعض، مشرعة الأبواب. أما محررو هذا الكتاب فقد أرادوا أن يعيدوا النظر في مشروع وليامز ضمن خطة عالمية طموحة ساهم فيها عدد من الباحثين من مختلف أرجاء العالم، لإعادة تمحيص ما تغير من مصطلحات الثقافة والمجتمع، فكانت النتيجة هذه الخزانة الموسوعية التي أسموها : مفاتيح اصطلاحية جديدة.

Adaptive Resonance Theory, or ART, is a neural model that explains how normal and abnormal brains may learn to categorize and recognize objects and events in a changing world, and how these learned categories may be remembered for a long time. This article uses ART to propose and unify the explanation of diverse data about normal and abnormal modulation of learning and memory by acetylcholine (ACh). In ART, determines whether learned categories will be general and abstract, or specific and concrete. ART models how vigilance may be regulated by ACh release in layer 5 neocortical cells by influencing after-hyperpolarization (AHP) currents. This ACh release is mediated by cells in the nucleus basalis (NB) of Meynert that are activated by unexpected events. The article additionally discusses data about ACh-mediated control of vigilance. ART proposes that there are often dynamic breakdowns of tonic control in mental disorders such as autism, where vigilance remains high, and medial temporal amnesia, where vigilance remains low. Tonic control also occurs during sleep-wake cycles. Properties of Up and Down states during slow wave sleep arise in ACh-modulated laminar cortical ART circuits that carry out processes in awake individuals of contrast normalization, attentional modulation, decision-making, activity-dependent habituation, and mismatch-mediated reset. These slow wave sleep circuits interact with circuits that control circadian rhythms and memory consolidation. Tonic control properties also clarify how Alzheimer's disease symptoms follow from a massive structural degeneration that includes undermining vigilance control by ACh in cortical layers 3 and 5. Sleep disruptions before and during Alzheimer's disease, and how they contribute to a vicious cycle of plaque formation in layers 3 and 5, are also clarified from this perspective.

Currently available therapies for the treatment of Alzheimer's disease (AD) consist of cholinesterase inhibitors (ChEIs), such as donepezil, and the -methyl-D-aspartate receptor antagonist memantine. In December 2014, the US Food and Drug Administration approved Namzaric™, a once-daily, fixed-dose combination (FDC) of memantine extended-release (ER) and donepezil for patients with moderate-to-severe AD. The FDC capsule is bioequivalent to the coadministered individual drugs, and its bioavailability is similar when taken fasting, with food, or sprinkled onto applesauce. The combination of memantine and ChEIs in moderate-to-severe AD provides additional benefits to ChEI monotherapy across multiple domains and may delay the time to nursing home admission. A dedicated study of memantine ER compared to placebo in patients on a stable dose of a ChEI found statistically significant benefits on cognition and global status but not functioning. Treatment with memantine ER and donepezil is generally well tolerated, although higher doses of ChEIs are associated with more serious adverse events such as vomiting, syncope, and weight loss. Potential advantages of the FDC include a simpler treatment regimen, reduction in pill burden, and the ability to sprinkle the capsule onto soft foods. Patients who may benefit from the FDC include those with significant dysphagia, a history of poor compliance, or limited caregiver interaction. However, available evidence that these advantages would increase treatment adherence and persistence is conflicting, meaning that the added cost of switching patients from generic options to an FDC may not always be justified.

This article reviews and synthesizes highlights of the history of neural models of rate-based and spiking neural networks. It explains that theoretical and experimental results about how all rate-based neural network models, whose cells obey the membrane equations of neurophysiology, also called shunting laws, can be converted into spiking neural network models without any loss of explanatory power, and often with gains in explanatory power. These results are relevant to all the main brain processes, including individual neurons and networks for perception, learning, cognition, and navigation. The results build upon the hypothesis that the functional units of brain processes are spatial patterns of cell activities, or short-term-memory (STM) traces, and spatial patterns of learned adaptive weights, or long-term-memory (LTM) patterns. It is also shown how spatial patterns that are learned by spiking neurons during childhood can be preserved even as the child’s brain grows and deforms while it develops towards adulthood. Indeed, this property of spatiotemporal self-similarity may be one of the most powerful properties that individual spiking neurons contribute to the development of large-scale neural networks and architectures throughout life.

Despite tremendous gains in the molecular understanding of exocrine pancreatic cancer, the prognosis for this disease remains very poor, largely because of delayed disease detection and limited effectiveness of systemic therapies. Both incidence rates and mortality rates for pancreatic cancer have increased during the past decade, in contrast to most other solid tumor types. Recent improvements in multimodality care have substantially improved overall survival, local control, and metastasis‐free survival for patients who have localized tumors that are amenable to surgical resection. The widening gap in prognosis between patients with resectable and unresectable or metastatic disease reinforces the importance of detecting pancreatic cancer sooner to improve outcomes. Furthermore, the developing use of therapies that target tumor‐specific molecular vulnerabilities may offer improved disease control for patients with advanced disease. Finally, the substantial morbidity associated with pancreatic cancer, including wasting, fatigue, and pain, remains an under‐addressed component of this disease, which powerfully affects quality of life and limits tolerance to aggressive therapies. In this article, the authors review the current multidisciplinary standards of care in pancreatic cancer with a focus on emerging concepts in pancreatic cancer detection, precision therapy, and survivorship.

Alzheimer's disease (AD) is a progressive neurodegenerative disease that is the most common form of dementia. There are currently FDA-approved symptomatic therapies for AD and a recently approved, potentially disease-modifying drug, Aducanumab; however, there are no curative or preventative therapies. Research suggests that diet may play a role in AD, but it is inconclusive relative to which dietary approach provides the most neuroprotective effects. There are other life-style approaches that have been found to possibly play a role in AD prevention/treatment. These include exercise, brain training, and social interaction. A combined approach may be more effective than any one modality alone. The ketogenic diet (KD) is one specific diet that has been studied vis a vis neurodegenerative diseases. Similar benefits to those of a KD can also be achieved through consuming a normal diet and supplementing with ketogenic agents. The purpose of this review is to compare the methods of inducing hyperketonemia and their impact on AD prevention/treatment, as well as to explore the possible benefits of a combined approach. The PubMed database was searched for clinical trials and randomized, controlled trials involving the KD or exogenous ketone administration and AD. Key search terms used included “ketogenic diet and Alzheimer's disease,” “ketosis and Alzheimer's disease,” “MCT and Alzheimer's disease,” and “exercise and diet and Alzheimer's disease.” Only studies involving patients diagnosed with AD were included in this paper, but for the combined approach section, studies included patients diagnosed with MCI due to a paucity of combined approach studies involving AD patients alone. There is evidence that the KD and exogenous ketone supplementation may provide treatment benefits in AD patients. It is unclear whether one method is better than the other. The specific food composition of the KD should be considered, because certain types of fat sources are healthier than others. Many forms of the KD require strict monitoring of carbohydrate intake, which would often fall under the responsibility of the caregiver. Future studies may be more feasible in an institutional setting, where it would be easier to administer and to monitor a dietary protocol. Exogenous supplementation may be more likely to be adhered to as a long-term treatment, because the dietary changes are not as drastic. A multidomain approach may be the most effective in possibly preventing/delaying AD and in improving/stabilizing and possibly slowing disease progression in those with AD. Most current studies are small, often uncontrolled, and only look at the short-term effects of ketosis on cognition. Large, long-term, randomized, controlled trials relative to the impact of the KD in patients with cognitive impairment and AD are lacking and thus needed. Combined approaches may prove to be more beneficial in possibly preventing/delaying AD and in improving/stabilizing and possibly slowing disease progression in those with MCI or AD. Future research should investigate the effect of additional combined approaches relative to neurocognitive decline in AD patients.