Synesthesia as a neuronal palimpsest

Synesthetes, a small fraction of the population, experience systematic, additional associations. For example, they may arbitrarily associate a specific color to each letter or number. Synesthesia has offered for the last ten years to cognitive science a unique opportunity to study the neural bases of subjective experience, drawing on individual differences just like in neuropsychology, but with healthy people. Here we review the current knowledge and propose a new theory, the "palimpsest hypothesis", a variant of the recycling hypothesis for reading. The neural development of written language expertise (a recent cultural invention acquired without any genetic modification) requires indeed the recycling of brain regions predisposed to expertise acquisition into reading regions. The palimpsest hypothesis supposes that for synesthetes recycling involves neuronal networks that were already specialized for color perception. Synesthetic colors would be the remains of this former expertise.     

Neural Activity during Natural Viewing of Sesame Street Statistically Predicts Test Scores in Early Childhood

It is not currently possible to measure the real-world thought process that a child has while observing an actual school lesson. However, if it could be done, children''s neural processes would presumably be predictive of what they know. Such neural measures would shed new light on children''s real-world thought. Toward that goal, this study examines neural processes that are evoked naturalistically, during educational television viewing. Children and adults all watched the same Sesame Street video during functional magnetic resonance imaging (fMRI). Whole-brain intersubject correlations between the neural timeseries from each child and a group of adults were used to derive maps of “neural maturity” for children. Neural maturity in the intraparietal sulcus (IPS), a region with a known role in basic numerical cognition, predicted children''s formal mathematics abilities. In contrast, neural maturity in Broca''s area correlated with children''s verbal abilities, consistent with prior language research. Our data show that children''s neural responses while watching complex real-world stimuli predict their cognitive abilities in a content-specific manner. This more ecologically natural paradigm, combined with the novel measure of “neural maturity,” provides a new method for studying real-world mathematics development in the brain.     

Taxi Cab Syndrome: A Review of the Extensive Genitourinary Pathology Experienced by Taxi Cab Drivers and What We Can Do to Help

This review consolidates knowledge regarding the extensive genitourinary pathology experienced by taxi cab drivers. Taxi cab, livery, truck, and other drivers all objectively and subjectively may have more voiding dysfunction, infertility, urolithiasis, bladder cancer, and urinary infections as compared with nonprofessional drivers; this is called taxi cab syndrome. Together with governmental and medical assistance, simple interventions—such as education, the addition of taxi relief stations, and possibly the use of sanitary urinary collection devices—to curb the progression of genitourinary disease in taxi drivers should be prospectively studied. It is postulated that many of these interventions may also benefit other groups of occupationally related infrequent voiders.Key words: Taxi cab syndrome, Infrequent voiders syndrome, Occupational hazard, Voiding dysfunction, Prostodynia, Infertility, UrolithiasisIn New York City, where taxi cabs flow like erythrocytes in a vast net of arteries, the drivers, New York’s backbone, often do not have sufficient flow themselves. This article demonstrates how the lack of adequate and accessible bathroom facilities in New York likely accounts for most of the genitourinary pathology that taxi drivers have. In fact, drivers represent only one of many occupations that contribute to voiding dysfunction as a result of inadequate bathroom access or other factors that lead to the inability to void regularly throughout the workday. These drivers represent the ultimate case study on how, using simple interventions, those who move us through New York City at an often bewildering speed may be helped.In the aptly worded article by Gany and colleagues,¹ “Every disease…man can get can start in this cab,” the cardiovascular risk factors of New York City taxi cabs are described in great detail. Gany and colleagues followed a cohort of South Asian immigrant taxi drivers, holding focus groups and administering surveys about the drivers’ perceptions of their own cardiovascular health. Musculoskeletal pain, diabetes, hypertension, vision problems, stress, obesity, and constipation were pervasive throughout the group. Additionally, urinary tract issues such as kidney problems, bladder dysfunction, and prostatism were noted. One of the participants attributed his onset of kidney problems to intentional infrequent urination, and said this was mostly “because you don’t have facilities at most places where you can stand and urinate.” Two other drivers with diabetes-induced polyuria also attributed their severe problem with this issue.¹     

The neuroscience of primate intellectual evolution: natural selection and passive and intentional niche construction

We trained Japanese macaque monkeys to use tools, an advanced cognitive function monkeys do not exhibit in the wild, and then examined their brains for signs of modification. Following tool-use training, we observed neurophysiological, molecular genetic and morphological changes within the monkey brain. Despite being 'artificially' induced, these novel behaviours and neural connectivity patterns reveal overlap with those of humans. Thus, they may provide us with a novel experimental platform for studying the mechanisms of human intelligence, for revealing the evolutionary path that created these mechanisms from the 'raw material' of the non-human primate brain, and for deepening our understanding of what cognitive abilities are and of those that are not uniquely human. On these bases, we propose a theory of 'intentional niche construction' as an extension of natural selection in order to reveal the evolutionary mechanisms that forged the uniquely intelligent human brain.     

What aspects of autism predispose to talent?

In this paper, we explore the question, why are striking special skills so much more common in autism spectrum conditions (ASC) than in other groups? Current cognitive accounts of ASC are briefly reviewed in relation to special skills. Difficulties in ‘theory of mind’ may contribute to originality in ASC, since individuals who do not automatically ‘read other minds’ may be better able to think outside prevailing fashions and popular theories. However, originality alone does not confer talent. Executive dysfunction has been suggested as the ‘releasing’ mechanism for special skills in ASC, but other groups with executive difficulties do not show raised incidence of talents. Detail-focused processing bias (‘weak coherence’, ‘enhanced perceptual functioning’) appears to be the most promising predisposing characteristic, or ‘starting engine’, for talent development. In support of this notion, we summarize data from a population-based twin study in which parents reported on their 8-year-olds'' talents and their ASC-like traits. Across the whole sample, ASC-like traits, and specifically ‘restricted and repetitive behaviours and interests’ related to detail focus, were more pronounced in children reported to have talents outstripping older children. We suggest that detail-focused cognitive style predisposes to talent in savant domains in, and beyond, autism spectrum disorders.     

Early cognitive experience prevents adult deficits in a neurodevelopmental schizophrenia model

Brain abnormalities acquired early in life may cause schizophrenia, characterized by adulthood onset of psychosis, affective flattening, and cognitive impairments. Cognitive symptoms, like impaired cognitive control, are now recognized to be important treatment targets but cognition-promoting treatments are ineffective. We hypothesized that cognitive training during the adolescent period of neuroplastic development can tune compromised neural circuits to develop in the service of adult cognition and attenuate schizophrenia-related cognitive impairments that manifest in adulthood. We report, using neonatal ventral hippocampus lesion rats (NVHL), an established neurodevelopmental model of schizophrenia, that adolescent cognitive training prevented the adult cognitive control impairment in NVHL rats. The early intervention also normalized brain function, enhancing cognition-associated synchrony of neural oscillations between the hippocampi, a measure of brain function that indexed cognitive ability. Adolescence appears to be a critical window during which prophylactic cognitive therapy may benefit people at risk of schizophrenia.     

Brain enabled by next-generation neurotechnology: using multiscale and multimodal models

As many articles in this issue of IEEE Pulse demonstrate, interfacing directly with the brain presents several fundamental challenges. These challenges reside at multiple levels and span many disciplines, ranging from the need to understand brain states at the level of neural circuits to creating technological innovations to facilitate new therapeutic options. The goal of our multiuniversity research team, composed of researchers from Stanford University, Brown University, the University of California at San Francisco (UCSF), and the University College London (UCL), is to substantially elevate the fundamental understanding of brain information processing and its relationship with sensation, behavior, and injury. Our team was assembled to provide expertise ranging from neuroscience to neuroengineering and to neurological and psychiatric clinical guidance, all of which are critical to the overarching research goal. By employing a suite of innovative experimental, computational, and theoretical approaches, the Defense Advanced Research Projects Agency (DARPA) Reorganization and Plasticity to Accelerate Injury Recovery (REPAIR) team has set its sights on learning how the brain and its microcircuitry react (e.g., to sudden physiological changes) and what can be done to encourage recovery from such (reversible) injury. In this article, we summarize some of the team's technical goals, approaches, and early illustrative results.     

Inferring Passenger Denial Behavior of Taxi Drivers from Large-Scale Taxi Traces

How to understand individual human actions is a fundamental question to modern science, which drives and incurs many social, technological, racial, religious and economic phenomena. Human dynamics tries to reveal the temporal pattern and internal mechanism of human actions in letter or electronic communications, from the perspective of continuous interactions among friends or acquaintances. For interactions between stranger to stranger, taxi industry provide fruitful phenomina and evidence to investigate the action decisions. In fact, one striking disturbing events commonly reported in taxi industry is passenger refusing or denial, whose reasons vary, including skin color, blind passenger, being a foreigner or too close destination, religion reasons and anti specific nationality, so that complaints about taxi passenger refusing have to be concerned and processed carefully by local governments. But more universal factors for this phenomena are of great significance, which might be fulfilled by big data research to obtain novel insights in this question. In this paper, we demonstrate the big data analytics application in revealing novel insights from massive taxi trace data, which, for the first time, validates the passengers denial in taxi industry and estimates the denial ratio in Beijing city. We first quantify the income differentiation facts among taxi drivers. Then we find out that choosing the drop-off places also contributes to the high income for taxi drivers, compared to the previous explanation of mobility intelligence. Moreover, we propose the pick-up, drop-off and grid diversity concepts and related diversity analysis suggest that, high income taxi drivers will deny passengers in some situations, so as to choose the passengers’ destination they prefer. Finally we design an estimation method for denial ratio and infer that high income taxi drivers will deny passengers with 8.52% likelihood in Beijing. Our work exhibits the power of big data analysis in revealing some dark side investigation.     

Searching for preventive measures of cardiovascular events in aged Japanese taxi drivers--the daily rhythm of cardiovascular risk factors during a night duty day

Previous studies have shown that Japanese taxi drivers are exposed to more risk factors and have a higher mortality rate due to cardiovascular disease than other occupational groups. We investigated the effect of night taxi driving with a view to preventing acute events of cardiovascular disease among aged taxi drivers. Twenty-nine taxi drivers (41-67 years old) were examined for urine normetanephrine/creatinine, von Willebrand factor, anti-thrombin III, t-plasminogen activator-plasminogen activator inhibitor 1-complex, hematocrit, blood glucose and blood pressure in the morning and at midnight during a duty day and in the following morning. At the same time, the blood pressure and blood glucose of 46 taxi drivers (43-67 years old) in the morning after a night duty with little sleep and in the morning after daytime work and subsequent night sleep were compared. The results obtained indicate that the aggravation of sympathetic nervous system functions with disturbed circadian rhythms, increased blood coagulation and blood concentration, endothelial injury and the elevation of blood glucose at midnight or the next morning were induced by their night work. These conditions are supposed to favour acute vascular events in aged taxi drivers. Preventive measures considered include social support for anticoagulant food and water intake, short exercise and walking as well as taking a rest and a nap during night work.     

Normal and pathological oscillatory communication in the brain

The huge number of neurons in the human brain are connected to form functionally specialized assemblies. The brain's amazing processing capabilities rest on local communication within and long-range communication between these assemblies. Even simple sensory, motor and cognitive tasks depend on the precise coordination of many brain areas. Recent improvements in the methods of studying long-range communication have allowed us to address several important questions. What are the common mechanisms that govern local and long-range communication and how do they relate to the structure of the brain? How does oscillatory synchronization subserve neural communication? And what are the consequences of abnormal synchronization?     

认知地图的神经环路基础

空间记忆是人类认识世界和改造世界的基本认知能力,与我们的生活息息相关.无论是寻找常用的生活物件,如钥匙和手机,还是外出上班、购物和约会,都依赖我们对周围环境的记忆.截止到目前已有大量研究从不同水平探讨大脑如何表征其周围环境,但仍然有很多未解的问题.本文系统综述了基于脑成像和神经电生理技术开展的空间记忆研究进展.通过梳理以往研究中有关生物体在构建认知地图的神经结构和神经活动规律,提出了海马结构和新皮层对空间记忆的编码环路和表征机制,并在此基础上对未来研究进行了展望.     

Language development.

Recent research suggests that our ability to learn language is innate, but not necessarily domain-specific. That is, language development appears to be based on a relatively plastic mix of neural systems that also serve other cognitive and perceptual functions. Evidence in support of this conclusion includes neural network simulations of language learning, event-related brain potential studies of normal language development, and studies of language development in several clinical populations of subjects suffering focal brain injury, specific language impairment, and contrasting forms of mental retardation.     

Respiratory symptoms and lung function in taxi drivers and manual workers

The aim of this study, was to determine the prevalence of some respiratory symptoms and possible diseases among taxi drivers and manual workers. This prospective study was performed on 165 Pakistani male drivers, (mean age: 34.5±7.8 years) and 165 Pakistani male manual workers not exposed to dust or fumes, without occupational exposure to driving employed in the Water and Electricity Department and recruited as controls (mean age: 34.6±7.6 years and mean height and weight 169.8±6.0 cm and 71.9±10.9 kg). The data on chronic respiratory symptoms showed that taxi drivers had higher prevalence of symptoms than manual workers, being significantly greater for asthma (RR=1.72; 95% CI=1.00–2.88,P=0.037); allergic rhinitis (RR=2.41; 95% CI=1.46–3.94,P=0.0006); dyspnea (RR=2.13; 95% CI=1.22–3.71,P=0.009); and nasal catarrh (RR=2.19; 95% CI=1.22–3.91,P=0.0106). Thirty percent of taxi drivers and 27% of manual workers were smokers, there was no significant differences in the prevalence of chronic respiratory symptoms between smokers and non-smokers. Lung function parameters in the taxi drivers were significantly lower than in manual workers group (P<0.0001) except PEF parameter. When comparing the measured mean values of lung function parameters in the drivers among smokers and nonsmokers, there was no significant differences between smokers and nonsmokers. Also, a comparison of ventilatory capacity of paired predicted values with measured normal values showed statistically significant differences between predicted and measured values for taxi drivers and manual workers for FVC, FEV₁, FEF_25–75 and PEF parameters except for FEV₁/FVC test in manual workers. In conclusion, the results of the present study provide evidence regarding effects of such as carbon monoxide, nitrogen dioxide, sulfur dioxide and gases exposures on taxi drivers and long-term driving, which may be associated with the development of chronic respiratory symptoms and lung function impairment.     

Distributed representations accelerate evolution of adaptive behaviours

Animals with rudimentary innate abilities require substantial learning to transform those abilities into useful skills, where a skill can be considered as a set of sensory–motor associations. Using linear neural network models, it is proved that if skills are stored as distributed representations, then within-lifetime learning of part of a skill can induce automatic learning of the remaining parts of that skill. More importantly, it is shown that this “free-lunch” learning (FLL) is responsible for accelerated evolution of skills, when compared with networks which either 1) cannot benefit from FLL or 2) cannot learn. Specifically, it is shown that FLL accelerates the appearance of adaptive behaviour, both in its innate form and as FLL-induced behaviour, and that FLL can accelerate the rate at which learned behaviours become innate.     

Network modeling of dynamic brain interactions predicts emergence of neural information that supports human cognitive behavior

How cognitive task behavior is generated by brain network interactions is a central question in neuroscience. Answering this question calls for the development of novel analysis tools that can firstly capture neural signatures of task information with high spatial and temporal precision (the “where and when”) and then allow for empirical testing of alternative network models of brain function that link information to behavior (the “how”). We outline a novel network modeling approach suited to this purpose that is applied to noninvasive functional neuroimaging data in humans. We first dynamically decoded the spatiotemporal signatures of task information in the human brain by combining MRI-individualized source electroencephalography (EEG) with multivariate pattern analysis (MVPA). A newly developed network modeling approach—dynamic activity flow modeling—then simulated the flow of task-evoked activity over more causally interpretable (relative to standard functional connectivity [FC] approaches) resting-state functional connections (dynamic, lagged, direct, and directional). We demonstrate the utility of this modeling approach by applying it to elucidate network processes underlying sensory–motor information flow in the brain, revealing accurate predictions of empirical response information dynamics underlying behavior. Extending the model toward simulating network lesions suggested a role for the cognitive control networks (CCNs) as primary drivers of response information flow, transitioning from early dorsal attention network-dominated sensory-to-response transformation to later collaborative CCN engagement during response selection. These results demonstrate the utility of the dynamic activity flow modeling approach in identifying the generative network processes underlying neurocognitive phenomena.

How is cognitive task behavior generated by brain network interactions? This study describes a novel network modeling approach and applies it to source electroencephalography data. The model accurately predicts future information dynamics underlying behavior and (via simulated lesioning) suggests a role for cognitive control networks as key drivers of response information flow.     

White Matter Integrity Supports BOLD Signal Variability and Cognitive Performance in the Aging Human Brain

Decline in cognitive performance in old age is linked to both suboptimal neural processing in grey matter (GM) and reduced integrity of white matter (WM), but the whole-brain structure-function-cognition associations remain poorly understood. Here we apply a novel measure of GM processing–moment-to-moment variability in the blood oxygenation level-dependent signal (SD_BOLD)—to study the associations between GM function during resting state, performance on four main cognitive domains (i.e., fluid intelligence, perceptual speed, episodic memory, vocabulary), and WM microstructural integrity in 91 healthy older adults (aged 60-80 years). We modeled the relations between whole-GM SD_BOLD with cognitive performance using multivariate partial least squares analysis. We found that greater SD_BOLD was associated with better fluid abilities and memory. Most of regions showing behaviorally relevant SD_BOLD (e.g., precuneus and insula) were localized to inter- or intra-network “hubs” that connect and integrate segregated functional domains in the brain. Our results suggest that optimal dynamic range of neural processing in hub regions may support cognitive operations that specifically rely on the most flexible neural processing and complex cross-talk between different brain networks. Finally, we demonstrated that older adults with greater WM integrity in all major WM tracts had also greater SD_BOLD and better performance on tests of memory and fluid abilities. We conclude that SD_BOLD is a promising functional neural correlate of individual differences in cognition in healthy older adults and is supported by overall WM integrity.     

Behavioral and neural analysis of associative learning in the honeybee: a taste from the magic well

Equipped with a mini brain smaller than one cubic millimeter and containing only 950,000 neurons, honeybees could be indeed considered as having rather limited cognitive abilities. However, bees display a rich and interesting behavioral repertoire, in which learning and memory play a fundamental role in the framework of foraging activities. We focus on the question of whether adaptive behavior in honeybees exceeds simple forms of learning and whether the neural mechanisms of complex learning can be unraveled by studying the honeybee brain. Besides elemental forms of learning, in which bees learn specific and univocal links between events in their environment, bees also master different forms of non-elemental learning, including categorization, contextual learning and rule abstraction, both in the visual and in the olfactory domain. Different protocols allow accessing the neural substrates of some of these learning forms and understanding how complex problem solving can be achieved by a relatively simple neural architecture. These results underline the enormous richness of experience-dependent behavior in honeybees, its high flexibility, and the fact that it is possible to formalize and characterize in controlled laboratory protocols basic and higher-order cognitive processing using an insect as a model. This paper is dedicated to the memory of Guillermo ‘Willy’ Zaccardi (1972–2007), disciple and friend beyond time and distance, who will always be remembered with a smile.     

Respiration modulates oscillatory neural network activity at rest

Despite recent advances in understanding how respiration affects neural signalling to influence perception, cognition, and behaviour, it is yet unclear to what extent breathing modulates brain oscillations at rest. We acquired respiration and resting state magnetoencephalography (MEG) data from human participants to investigate if, where, and how respiration cyclically modulates oscillatory amplitudes (2 to 150 Hz). Using measures of phase–amplitude coupling, we show respiration-modulated brain oscillations (RMBOs) across all major frequency bands. Sources of these modulations spanned a widespread network of cortical and subcortical brain areas with distinct spectrotemporal modulation profiles. Globally, delta and gamma band modulations varied with distance to the head centre, with stronger modulations at distal (versus central) cortical sites. Overall, we provide the first comprehensive mapping of RMBOs across the entire brain, highlighting respiration–brain coupling as a fundamental mechanism to shape neural processing within canonical resting state and respiratory control networks (RCNs).

Despite recent advances, it remains unclear to what extent breathing modulates brain oscillations at rest. This magnetoencephalography study in human participants identifies a widespread brain network of neural oscillations that are coupled to the respiratory rhythm.     

Selective disorders of reading?

Over the past few decades, refined cognitive architectures with highly specific components have been proposed to explain apparently selective disorders of reading, resulting from brain disease or injury, in previously literate adults. Recent analysis of the more general linguistic and cognitive abilities supported by neural systems damaged in the various forms of alexia favours a rather different view of reading and the kinds of models sufficient to account for its acquisition, skilled performance and disruption.