社会认知神经科学的取向与研究进展

社会认知神经科学是社会心理学和认知神经科学相结合的新兴多学科研究领域,其强调在社会、认知与脑神经等三个层面的交互作用上去理解心理现象。前几年主要是对刻板印象、态度与态度改变、他人知觉、自我认知以及情绪与认知交互作用等方面进行了深入研究,其主要范式是应用认知神经科学的方法来验证社会心理学在这些范围内上的各种不同的理论观点,当前的研究主要集中在知觉和再认的社会标记、社会判断和归因、评价调节知觉和经验以及社会交互作用等传统的社会心理学方面,并取得了突破性进展。展望未来的研究,其将在系统准则研究发展的基础上,把当今的社会认知研究与认知神经科学在理论和方法论上整合起来,为揭示人类高级社会心理现象的神经基础,开辟一条崭新的研究道路。     

Mental illness from the perspective of theoretical neuroscience

Theoretical neuroscience, which characterizes neural mechanisms using mathematical and computational models, is highly relevant to central problems in the philosophy of psychiatry. These models can help to solve the explanation problem of causally connecting neural processes with the behaviors and experiences found in mental illnesses. Such explanations will also be useful for generating better classifications and treatments of psychiatric disorders. The result should help to eliminate concerns that mental illnesses such as depression and schizophrenia are not objectively real. A philosophical approach to mental illness based on neuroscience need not neglect the inherently social and historical nature of mental phenomena.     

Quantum physics in neuroscience and psychology: a neurophysical model of mind-brain interaction

Neuropsychological research on the neural basis of behaviour generally posits that brain mechanisms will ultimately suffice to explain all psychologically described phenomena. This assumption stems from the idea that the brain is made up entirely of material particles and fields, and that all causal mechanisms relevant to neuroscience can therefore be formulated solely in terms of properties of these elements. Thus, terms having intrinsic mentalistic and/or experiential content (e.g. 'feeling', 'knowing' and 'effort') are not included as primary causal factors. This theoretical restriction is motivated primarily by ideas about the natural world that have been known to be fundamentally incorrect for more than three-quarters of a century. Contemporary basic physical theory differs profoundly from classic physics on the important matter of how the consciousness of human agents enters into the structure of empirical phenomena. The new principles contradict the older idea that local mechanical processes alone can account for the structure of all observed empirical data. Contemporary physical theory brings directly and irreducibly into the overall causal structure certain psychologically described choices made by human agents about how they will act. This key development in basic physical theory is applicable to neuroscience, and it provides neuroscientists and psychologists with an alternative conceptual framework for describing neural processes. Indeed, owing to certain structural features of ion channels critical to synaptic function, contemporary physical theory must in principle be used when analysing human brain dynamics. The new framework, unlike its classic-physics-based predecessor, is erected directly upon, and is compatible with, the prevailing principles of physics. It is able to represent more adequately than classic concepts the neuroplastic mechanisms relevant to the growing number of empirical studies of the capacity of directed attention and mental effort to systematically alter brain function.     

A unifying theory on the relationship between spike trains,EEG, and ERP based on the noise shaping/predictive neural coding hypothesis

Cracking the neural code has long been a central issue in neuroscience. However, it has been proved difficult because there logically exist an infinite number of other models and interpretations that could account for the same data and phenomena (i.e. the problem of underdetermination). Therefore, I suggest that applying biologically realistic multiple constraints from ion-channel level to system level (e.g. cognitive neuroscience and human brain disorders) can only solve the problem of underdetermination. Here I have explored whether the noise shaping/predictive neural coding hypothesis can provide a unified view on following realistic multiple constraints: (1) cortical gain control mechanisms in vivo; (2) the relationships between acetylcholine, nicotine, dopamine, calcium-activated potassium ion-channel, and cognitive functions; (3) oscillations and synchrony; (4) why should spontaneous activity be irregular; (5) whether the cortical neurons in vivo are coincidence detectors or integrators; and (6) the causal relationship between theta oscillation, gamma band fluctuation, and P3 (or P300) ERP responses. Finally, recent experimental results supporting the unified view shall be discussed.     

Multiple interactions networks: towards more realistic descriptions of the web of life

Ecological communities are defined by species interacting dynamically in a given location at a given time, and can be conveniently represented as networks of interactions. Pairwise interactions can be ascribed to one of five main types, depending on their outcome for the species involved: amensalism, antagonism (including predation, parasitism and disease), commensalism, competition or mutualism. While most studies have dealt so far with networks involving one single type of interaction at a time, often focusing on a specific clade and/or guild, recent studies are being developed that consider networks with more than one interaction type and across several levels of biological organisation. We review these developments and suggest that three main frameworks are in use to investigate the properties of multiple interactions networks: ‘expanded food‐webs’, ‘multilayer networks’ and ‘equal footing networks’. They differ on how interactions are classified and implemented in mathematical models, and on whether the effect of different interaction types is expressed in the same units. We analyse the mathematical and ecological assumptions of these three approaches, and identify some of the questions that can be addressed with each one of them. Since the overwhelming majority of studies on multiple interactions are theoretical and use artificially generated data, we also provide recommendations for the incorporation of field data in such studies.     

Dynamics of wrist rotations

Understanding the dynamics of wrist rotations is important for many fields, including biomechanics, rehabilitation and motor neuroscience. This paper provides an experimentally based mathematical model of wrist rotation dynamics in Flexion-Extension (FE) and Radial-Ulnar Deviation (RUD), and characterizes the torques required to overcome the passive mechanical impedance of wrist rotations. We modeled the wrist as a universal joint with non-intersecting axes. The equations of motion of the hand rotating about the wrist joint include inertial, damping, and stiffness terms, with parameter values based on direct measurements (stiffness) or measurements combined with data available in the literature (inertia, damping). We measured the wrist kinematics of six young, healthy subjects making comfortable and fast-paced wrist rotations (±15° in FE, RUD, and combinations) and inserted these kinematic data into the model of wrist rotation dynamics. With this we quantified the torques required to overcome the impedance of wrist rotations and evaluated the relative importance of individual impedance terms as well as interactions between the degrees of freedom. We found that the wrist's passive stiffness is the major impedance the neuromuscular system must overcome to rotate the wrist. Inertia and passive damping only become important for very fast movements. Unlike elbow and shoulder reaching movements, inertial interaction torques are negligible for wrist rotations. Interaction torques due to stiffness and damping, however, are significant. Finally, we found that some model terms (inertial interaction torques, axis offset, and, for moderately sized rotations, non-linearities) can be neglected with little loss of accuracy, resulting in a simple, linear model useful for studies in biomechanics, motor neuroscience, and rehabilitation.     

Dissipative structures and amplification of enantiomeric excess (an experimental point of view)

Various mathematical models have been proposed to account for the origin of chiral molecules in biological systems. Most of these models invoke non-linear phenomena, and are based on the general concept of dissipative structures. These theoretical models define the fundamental criteria which must be obeyed by the experimental systems that we have investigated. Our initial approach to this problem was an extensive search of the literature data in order to select a few systems or experimental situations which would satisfy the criteria defined by the theoretical models. For these reasons, we carried out a study of the possibility of stereospecific autocatalysis in the asymmetric polymerisation of benzofuran. Similarly, the formation of spatial dissipative structures by coupling of a transport process with an interfacial reaction was investigated as a simple experimental example of symmetry breaking.