Identification and discrimination of bilingual talkers across languages

This study investigated the extent to which language familiarity affects the perception of the indexical properties of speech by testing listeners' identification and discrimination of bilingual talkers across two different languages. In one experiment, listeners were trained to identify bilingual talkers speaking in only one language and were then tested on their ability to identify the same talkers speaking in another language. In the second experiment, listeners discriminated between bilingual talkers across languages in an AX discrimination paradigm. The results of these experiments indicate that there is sufficient language-independent indexical information in speech for listeners to generalize knowledge of talkers' voices across languages and to successfully discriminate between bilingual talkers regardless of the language they are speaking. However, the results of these studies also revealed that listeners do not solely rely on language-independent information when performing these tasks. Listeners use language-dependent indexical cues to identify talkers who are speaking a familiar language. Moreover, the tendency to perceive two talkers as the "same" or "different" depends on whether the talkers are speaking in the same language. The combined results of these experiments thus suggest that indexical processing relies on both language-dependent and language-independent information in the speech signal.     

Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition

Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity “dendrophilia”, and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology.     

Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders

Recent findings of neurological functioning in autism spectrum disorder (ASD) point to altered brain connectivity as a key feature of its pathophysiology. The cortical underconnectivity theory of ASD (Just et al., 2004) provides an integrated framework for addressing these new findings. This theory suggests that weaker functional connections among brain areas in those with ASD hamper their ability to accomplish complex cognitive and social tasks successfully. We will discuss this theory, but will modify the term underconnectivity to ‘disrupted cortical connectivity’ to capture patterns of both under- and over-connectivity in the brain. In this paper, we will review the existing literature on ASD to marshal supporting evidence for hypotheses formulated on the disrupted cortical connectivity theory. These hypotheses are: 1) underconnectivity in ASD is manifested mainly in long-distance cortical as well as subcortical connections rather than in short-distance cortical connections; 2) underconnectivity in ASD is manifested only in complex cognitive and social functions and not in low-level sensory and perceptual tasks; 3) functional underconnectivity in ASD may be the result of underlying anatomical abnormalities, such as problems in the integrity of white matter; 4) the ASD brain adapts to underconnectivity through compensatory strategies such as overconnectivity mainly in frontal and in posterior brain areas. This may be manifested as deficits in tasks that require frontal–parietal integration. While overconnectivity can be tested by examining the cortical minicolumn organization, long-distance underconnectivity can be tested by cognitively demanding tasks; and 5) functional underconnectivity in brain areas in ASD will be seen not only during complex tasks but also during task-free resting states. We will also discuss some empirical predictions that can be tested in future studies, such as: 1) how disrupted connectivity relates to cognitive impairments in skills such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD.     

Neural coding: computational and biophysical perspectives

While recognizing a face or kicking a ball may seem to be easy tasks for us, they still constitute challenging problems for even the most sophisticated computer algorithms available nowadays. The brain has evolved complex mechanisms to encode behaviorally relevant information. Here we review the types of codes used by the brain, what their constraints are and how they map the sensory environment or the motor output. We start by defining neural codes and briefly describing some of the current tools available to record activity from the brain. We give several examples of coding strategies used by different systems and multiple organisms and discuss how spiking patterns can be read out. Going beyond correlations between physiology and stimuli, we show what is currently known about the direct causal link between neuronal responses and behavioral output or sensory input. Finally, we identify what we consider to be some of the pressing questions in the field.     

Behavioral and computational aspects of language and its acquisition

One of the greatest challenges facing the cognitive sciences is to explain what it means to know a language, and how the knowledge of language is acquired. The dominant approach to this challenge within linguistics has been to seek an efficient characterization of the wealth of documented structural properties of language in terms of a compact generative grammar—ideally, the minimal necessary set of innate, universal, exception-less, highly abstract rules that jointly generate all and only the observed phenomena and are common to all human languages. We review developmental, behavioral, and computational evidence that seems to favor an alternative view of language, according to which linguistic structures are generated by a large, open set of constructions of varying degrees of abstraction and complexity, which embody both form and meaning and are acquired through socially situated experience in a given language community, by probabilistic learning algorithms that resemble those at work in other cognitive modalities.     

Superconductivity,diamagnetism, and the mean inner potential of solids

The mean inner potential of a solid is known to be proportional to its diamagnetic susceptibility. Superconductors exhibit giant diamagnetism. What does this say about the connection between superconductivity and mean inner potential? Nothing, according to the conventional theory of superconductivity. Instead, it is proposed that a deep connection exists between the mean inner potential, diamagnetism, and superconductivity: that they are all intimately linked to the fundamental charge asymmetry of matter. It is discussed how this physics can be probed experimentally and what the implications of different experimental findings would be for the understanding of superconductivity.     

Characterizing the Typical Information Curves of Diverse Languages

Optimal coding theories of language predict that speakers will keep the amount of information in their utterances relatively uniform under the constraints imposed by their language, but how much do these constraints influence information structure, and how does this influence vary across languages? We present a novel method for characterizing the information structure of sentences across a diverse set of languages. While the structure of English is broadly consistent with the shape predicted by optimal coding, many languages are not consistent with this prediction. We proceed to show that the characteristic information curves of languages are partly related to a variety of typological features from phonology to word order. These results present an important step in the direction of exploring upper bounds for the extent to which linguistic codes can be optimal for communication.     

Can we really ‘read’ art to see the changing brain? A review and empirical assessment of clinical case reports and published artworks for systematic evidence of quality and style changes linked to damage or neurodegenerative disease

The past three decades have seen multiple reports of people with neurodegenerative disorders, or other forms of changes in their brains, who also show putative changes in how they approach and produce visual art. Authors argue that these cases may provide a unique body of evidence, so-called ‘artistic signatures’ of neurodegenerative diseases, that might be used to understand disorders, provide diagnoses, be employed in treatment, create patterns of testable hypotheses for causative study, and also provide unique insight into the neurobiological linkages between the mind, brain, body, and the human penchant for art-making itself. However—before we can begin to meaningfully build from such emerging findings, much less formulate applications—not only is such evidence currently quite disparate and in need of systematic review, almost all case reports and artwork ratings are entirely subjective, based on authors' personal observations or a sparse collection of methods that may not best fit underlying research aims. This leads to the very real question of whether we might actually find patterns of systematic change if fit to a rigorous review—Can we really ‘read’ art to illuminate possible changes in the brain? How might we best approach this topic in future neuroscientific, clinical, and art-related research? This paper presents a review of this field and answer to these questions. We consider the current case reports for seven main disorders—Alzheimer's and Parkinson's disease, frontotemporal and Lewy body dementia, corticobasal degeneration, aphasia, as well as stroke—consolidating arguments for factors and changes related to art-making and critiquing past methods. Taking the published artworks from these papers, we then conduct our own assessment, employing computerized and human-rater-based approaches, which we argue represent best practice to identify stylistic or creativity/quality changes. We suggest, indeed, some evidence for systematic patterns in art-making for specific disorders and also find that case authors showed rather high agreement with our own assessments. More important, through opening this topic and past evidence to a systematic review, we hope to open a discussion and provide a theoretical and empirical foundation for future application and research on the intersection of art-making and the neurotypical, the changed, and the artistic brain.     

Making sense of policy choices: understanding the roles of value predispositions, mass media, and cognitive processing in public attitudes toward nanotechnology

Using a nationally representative telephone survey of 1,015 adults in the United States, this study examines how value predispositions, communication variables, and perceptions of risks and benefits are associated with public support for federal funding of nanotechnology. Our findings show that highly religious individuals were less supportive of funding of nanotech than less religious individuals, whereas individuals who held a high deference for scientific authority were more supportive of funding of the emerging technology than those low in deference. Mass media use and elaborative processing of scientific news were positively associated with public support for funding, whereas factual scientific knowledge had no significant association with policy choices. The findings suggest that thinking about and reflecting upon scientific news promote better understanding of the scientific world and may provide a more sophisticated cognitive structure for the public to form opinions about nanotech than factual scientific knowledge. Finally, heuristic cues including trust in scientists and perceived risks and benefits of nanotech were found to be associated with public support for nanotech funding. We conclude with policy implications that will be useful for policymakers and science communication practitioners.     

Functional connectivity between task-positive and task-negative brain areas and its relation to working memory performance

Functional brain imaging studies have identified a set of brain areas typically activated during cognitive tasks (task-positive brain areas) and another set of brain areas typically deactivated during cognitive tasks (task-negative brain areas). Negative correlations, or anticorrelations, between task-positive and task-negative brain areas have been reported at rest. Furthermore, the strength of these anticorrelations appears to be related to cognitive function. However, studies examining anticorrelations have typically employed global regression or similar analysis steps that force anticorrelated relationships to exist between brain areas. Therefore the validity of these findings has been questioned. Here we examine anticorrelations between a task-negative region in the medial frontal gyrus/anterior cingulate cortex and dorsolateral prefrontal cortex, a classic task-positive area, using an analysis that does not include global regression. Instead, we control for whole-brain correlations in the group-level analysis. Using this approach, we demonstrate that the strength of the functional connection between the medial frontal cortex and the dorsolateral prefrontal cortex is related to cognitive function and that this relationship is not an artifact of global regression.     

Corticothalamic projections control synchronization in locally coupled bistable thalamic oscillators

Thalamic circuits are able to generate state-dependent oscillations of different frequencies and degrees of synchronization. However, little is known about how synchronous oscillations, such as spindle oscillations in the thalamus, are organized in the intact brain. Experimental findings suggest that the simultaneous occurrence of spindle oscillations over widespread territories of the thalamus is due to the corticothalamic projections, as the synchrony is lost in the decorticated thalamus. In this Letter we study the influence of corticothalamic projections on the synchrony in a thalamic network, and uncover the underlying control mechanism, leading to a control method which is applicable for several types of oscillations in the central nervous system.     

The Public and Nanotechnology: How Citizens Make Sense of Emerging Technologies

We report findings from a national telephone survey on levels of knowledge about and attitudes toward nanotechnology that demonstrate how people make decisions about emerging technologies. Our findings confirm previous research that suggests that people form opinions and attitudes even in the absence of relevant scientific or policy-related information. In fact, our data show that cognitive shortcuts or heuristics – often provided by mass media – are currently a key factor in influencing how the public thinks about nanotechnology and about its risks and benefits, and in determining the level of support among the public for further funding for research in this area.     

Processing speech signal using auditory-like filterbank provides least uncertainty about articulatory gestures

Understanding how the human speech production system is related to the human auditory system has been a perennial subject of inquiry. To investigate the production-perception link, in this paper, a computational analysis has been performed using the articulatory movement data obtained during speech production with concurrently recorded acoustic speech signals from multiple subjects in three different languages: English, Cantonese, and Georgian. The form of articulatory gestures during speech production varies across languages, and this variation is considered to be reflected in the articulatory position and kinematics. The auditory processing of the acoustic speech signal is modeled by a parametric representation of the cochlear filterbank which allows for realizing various candidate filterbank structures by changing the parameter value. Using mathematical communication theory, it is found that the uncertainty about the articulatory gestures in each language is maximally reduced when the acoustic speech signal is represented using the output of a filterbank similar to the empirically established cochlear filterbank in the human auditory system. Possible interpretations of this finding are discussed.     

The neural processing of taste

Although there have been many recent advances in the field of gustatory neurobiology, our knowledge of how the nervous system is organized to process information about taste is still far from complete. Many studies on this topic have focused on understanding how gustatory neural circuits are spatially organized to represent information about taste quality (e.g., "sweet", "salty", "bitter", etc.). Arguments pertaining to this issue have largely centered on whether taste is carried by dedicated neural channels or a pattern of activity across a neural population. But there is now mounting evidence that the timing of neural events may also importantly contribute to the representation of taste. In this review, we attempt to summarize recent findings in the field that pertain to these issues. Both space and time are variables likely related to the mechanism of the gustatory neural code: information about taste appears to reside in spatial and temporal patterns of activation in gustatory neurons. What is more, the organization of the taste network in the brain would suggest that the parameters of space and time extend to the neural processing of gustatory information on a much grander scale.     

Decreased Resting-State Functional Complexity in Elderly with Subjective Cognitive Decline

Individuals with subjective cognitive decline (SCD) are at high risk of developing preclinical or clinical state of Alzheimer’s disease (AD). Resting state functional magnetic resonance imaging, which can indirectly reflect neuron activities by measuring the blood-oxygen-level-dependent (BOLD) signals, is promising in the early detection of SCD. This study aimed to explore whether the nonlinear complexity of BOLD signals can describe the subtle differences between SCD and normal aging, and uncover the underlying neuropsychological implications of these differences. In particular, we introduce amplitude-aware permutation entropy (AAPE) as the novel measure of brain entropy to characterize the complexity in BOLD signals in each brain region of the Brainnetome atlas. Our results demonstrate that AAPE can reflect the subtle differences between both groups, and the SCD group presented significantly decreased complexities in subregions of the superior temporal gyrus, the inferior parietal lobule, the postcentral gyrus, and the insular gyrus. Moreover, the results further reveal that lower complexity in SCD may correspond to poorer cognitive performance or even subtle cognitive impairment. Our findings demonstrated the effectiveness and sensitiveness of the novel brain entropy measured by AAPE, which may serve as the potential neuroimaging marker for exploring the subtle changes in SCD.     

Alzheimer's disease: biological aspects, therapeutic perspectives and diagnostic tools

Alzheimer's disease (AD) is the most common form of dementia among older people. Dementia is an irreversible brain disorder that seriously affects a person's ability to carry out daily activities. It is characterized by loss of cognitive functioning and behavioral abilities, to such an extent that it interferes with the daily life and activities of the affected patients. Although it is still unknown how the disease process begins, it seems that brain damage starts a decade or more before problems become evident. Scientific data seem to indicate that changes in the generation or the degradation of the amyloid-b peptide (Aβ) lead to the formation of aggregated structures that are the triggering molecular events in the pathogenic cascade of AD. This review summarizes some characteristic features of Aβ misfolding and aggregation and how cell damage and death mechanisms are induced by these supramolecular and toxic structures. Further, some interventions for the early diagnosis of AD are described and in the last part the potential therapeutic strategies adoptable to slow down, or better block, the progression of the pathology are reported.     

Computational models of music perception and cognition I: The perceptual and cognitive processing chain

We present a review on perception and cognition models designed for or applicable to music. An emphasis is put on computational implementations. We include findings from different disciplines: neuroscience, psychology, cognitive science, artificial intelligence, and musicology. The article summarizes the methodology that these disciplines use to approach the phenomena of music understanding, the localization of musical processes in the brain, and the flow of cognitive operations involved in turning physical signals into musical symbols, going from the transducers to the memory systems of the brain. We discuss formal models developed to emulate, explain and predict phenomena involved in early auditory processing, pitch processing, grouping, source separation, and music structure computation. We cover generic computational architectures of attention, memory, and expectation that can be instantiated and tuned to deal with specific musical phenomena. Criteria for the evaluation of such models are presented and discussed. Thereby, we lay out the general framework that provides the basis for the discussion of domain-specific music models in Part II.     

Effets des radiofréquences sur le système nerveux central chez lʼhomme : EEG,sommeil, cognition,vascularisation

Most of clinical studies on radiofrequency electromagnetic fields (RF) were directed at mobile phone-related exposures, usually at the level of the head, at their effect on some physiological functions including sleep, brain electrical activity (EEG), cognitive processes, brain vascularisation, and more generally on the cardiovascular and endocrine systems. They were frequently carried out on healthy adults. Effects on the amplitude of EEG alpha waves, mainly during sleep, look reproducible. It would however be important to define more precisely whether and how the absence of electromagnetic disturbance between RF exposure and the recording systems is checked. No consensus arises about cognitive effects. Some effects on cerebral vascularisation need complementary work.