The temporal dynamics of visual object priming

Priming reflects an important means of learning that is mediated by implicit memory. Importantly, priming occurs for previously viewed objects (item-specific priming) and their category relatives (category-wide priming). Two distinct neural mechanisms are known to mediate priming, including the sharpening of a neural object representation and the retrieval of stimulus–response mappings. Here, we investigated whether the relationship between these neural mechanisms could help explain why item-specific priming generates faster responses than category-wide priming. Participants studied pictures of everyday objects, and then performed a difficult picture identification task while we recorded event-related potentials (ERP). The identification task gradually revealed random line segments of previously viewed items (Studied), category exemplars of previously viewed items (Exemplar), and items that were not previously viewed (Unstudied). Studied items were identified sooner than Unstudied items, showing evidence of item-specific priming, and importantly Exemplar items were also identified sooner than Unstudied items, showing evidence of category-wide priming. Early activity showed sustained neural suppression of parietal activity for both types of priming. However, these neural suppression effects may have stemmed from distinct processes because while category-wide neural suppression was correlated with priming behavior, item-specific neural suppression was not. Late activity, examined with response-locked ERPs, showed additional processes related to item-specific priming including neural suppression in occipital areas and parietal activity that was correlated with behavior. Together, we conclude that item-specific and category-wide priming are mediated by separate, parallel neural mechanisms in the context of the current paradigm. Temporal differences in behavior are determined by the timecourses of these distinct processes.     

Neuronal correlates of decisions to speak and act: Spontaneous emergence and dynamic topographies in a computational model of frontal and temporal areas

The neural mechanisms underlying the spontaneous, stimulus-independent emergence of intentions and decisions to act are poorly understood. Using a neurobiologically realistic model of frontal and temporal areas of the brain, we simulated the learning of perception–action circuits for speech and hand-related actions and subsequently observed their spontaneous behaviour. Noise-driven accumulation of reverberant activity in these circuits leads to their spontaneous ignition and partial-to-full activation, which we interpret, respectively, as model correlates of action intention emergence and action decision-and-execution. Importantly, activity emerged first in higher-association prefrontal and temporal cortices, subsequently spreading to secondary and finally primary sensorimotor model-areas, hence reproducing the dynamics of cortical correlates of voluntary action revealed by readiness-potential and verb-generation experiments. This model for the first time explains the cortical origins and topography of endogenous action decisions, and the natural emergence of functional specialisation in the cortex, as mechanistic consequences of neurobiological principles, anatomical structure and sensorimotor experience.     

Individual differences in ERPs during mental rotation of characters: Lateralization,and performance level

The cognitive process of imaging an object turning around is called mental rotation. Many studies have been put forward analyzing mental rotation by means of event-related potentials (ERPs). Event-related potentials (ERPs) were measured during mental rotation of characters in a sample (N = 82) with a sufficient size to obtain even small effects. A bilateral ERP amplitude modulation as a function of angular displacement was observed at parietal leads without any lateralization. Sex had no effect on mental rotation of characters, neither with respect to performance nor with respect to brain potentials. When the sample was split into groups of high- and low-performers, however, the results indicated (a) in line with the idea of neural efficiency substantially larger amplitudes for low-performers; (b) that the smaller amplitudes of the high-performers involved larger parietal networks; and (c) a left-parietal disengagement of neural activity for high-performers but a right-parietal disengagement for low-performers. The latter finding became evident through an analysis of internal consistencies of ERP amplitudes across conditions and performance levels, showing that internal consistencies were reduced at all three leads in the high-performance group for the biggest rotation angle, relative the other conditions and the low-performing group.     

Dispositional implementation solves the superfluous structure problem

Consciousness supervenes on activity; computation supervenes on structure. Because of this, some argue, conscious states cannot supervene on computational ones. If true, this would present serious difficulties for computationalist analyses of consciousness (or, indeed, of any domain with properties that supervene on actual activity). I argue that the computationalist can avoid the Superfluous Structure Problem (SSP) by moving to a dispositional theory of implementation. On a dispositional theory, the activity of computation depends entirely on changes in the intrinsic properties of implementing material. As extraneous structure is not required for computation, a system can implement a program running on some but not all possible inputs. Dispositional computationalism thus permits episodes of computational activity that correspond to potential episodes of conscious awareness. The SSP cannot be motivated against this account, and so computationalism may be preserved.     

Investigation of psycho-physiological interactions between patient and therapist during a psychodynamic therapy and their relation to speech using in terms of entropy analysis using a neural network approach

In the present contribution we investigate in an exemplary single-case study the behavior of psycho-physiological variables in psychotherapy sessions. The values are measured continously during a single session at the same time for both patient and therapist. The analysis of the data is done using an artificial neural network approach for non-linear principal component analysis and faithful data representation/visualization and compression required for subsequent process analysis. The used network (growing self-organizing map, GSOM) thereby uses a kernel smoothing for improved data density estimation. In this way, we are able to generate an entropy model of psycho-physiological variability detecting emotionally instable phases during the therapy process. We relate our finding to results obtained by speech analysis of the therapy sessions according to the cycle model invented by Mergenthaler. Thus, we get preliminary suggestions how psycho-physiological reactions are related to the therapeutic process.     

The frozen cyborg: A reply to Selinger and Engström

Selinger and Engstrom, A moratorium on cyborgs: Computation, cognition and commerce, 2008 (this issue) urge upon us a moratorium on ‘cyborg discourse’. But the argument underestimates the richness and complexity of our ongoing communal explorations. It leans on a somewhat outdated version of the machine metaphor (exemplified perhaps by a frozen 1970’s Cyborg). The modern cyborg, informed by an evolving computational model of mind, can play a positive role in the critical discussions that Selinger and Engstrom seek.     

情绪识别研究中被“冷落”的线索:躯体表情加工的特点、神经基础及加工机制

躯体和面孔是个体情绪表达与识别的重要线索。与面部表情相比,躯体表情加工的显著特点是补偿情绪信息,感知运动与行为信息,及产生适应性行为。情绪躯体与面孔加工的神经基础可能相邻或部分重合,但也存在分离;EBA、FBA、SPL、IPL等是与躯体表情加工相关的特异性脑区。今后应系统研究面孔、躯体及语音情绪线索加工潜在的神经基础,探讨躯体情绪加工的跨文化差异,考察情绪障碍患者的躯体表情加工特点。     

为什么会出现“舌尖现象”?——TOT现象发生机制之争

舌尖现象(tip-of-the-tongue,TOT)是一种普遍发生的现象,但是发生TOT的对象、情景、机制等却是特殊和复杂的。因此,它引起了研究者的关注,尤其是在其产生机制上更是存在着很多争论。国外研究者提出了部分激活理论、传递缺陷理论、障碍物假说、神经网络模型、元认知理论等。但研究者大多都基于单一条件或情景来探讨TOT的产生,因此提出的理论的使用范围,解释广度等均有局限。关于TOT依然有许多疑惑,同时也存在值得探讨的课题。     

Criteria for the design and evaluation of cognitive architectures

Cognitive architectures are unified theories of cognition that take the form of computational formalisms. They support computational models that collectively account for large numbers of empirical regularities using small numbers of computational mechanisms. Empirical coverage and parsimony are the most prominent criteria by which architectures are designed and evaluated, but they are not the only ones. This paper considers three additional criteria that have been comparatively undertheorized. (a) Successful architectures possess subjective and intersubjective meaning, making cognition comprehensible to individual cognitive scientists and organizing groups of like-minded cognitive scientists into genuine communities. (b) Successful architectures provide idioms that structure the design and interpretation of computational models. (c) Successful architectures are strange: They make provocative, often disturbing, and ultimately compelling claims about human information processing that demand evaluation.