Top-down effects on early visual processing in humans: a predictive coding framework

An increasing number of human electroencephalography (EEG) studies examining the earliest component of the visual evoked potential, the so-called C1, have cast doubts on the previously prevalent notion that this component is impermeable to top-down effects. This article reviews the original studies that (i) described the C1, (ii) linked it to primary visual cortex (V1) activity, and (iii) suggested that its electrophysiological characteristics are exclusively determined by low-level stimulus attributes, particularly the spatial position of the stimulus within the visual field. We then describe conflicting evidence from animal studies and human neuroimaging experiments and provide an overview of recent EEG and magnetoencephalography (MEG) work showing that initial V1 activity in humans may be strongly modulated by higher-level cognitive factors. Finally, we formulate a theoretical framework for understanding top-down effects on early visual processing in terms of predictive coding

The pain matrix reloaded: a salience detection system for the body

Neuroimaging and neurophysiological studies have shown that nociceptive stimuli elia salience detection system for the bodycit responses in an extensive cortical network including somatosensory, insular and cingulate areas, as well as frontal and parietal areas. This network, often referred to as the "pain matrix", is viewed as representing the activity by which the intensity and unpleasantness of the perception elicited by a nociceptive stimulus are represented. However, recent experiments have reported (i) that pain intensity can be dissociated from the magnitude of responses in the "pain matrix", (ii) that the responses in the "pain matrix" are strongly influenced by the context within which the nociceptive stimuli appear, and (iii) that non-nociceptive stimuli can elicit cortical responses with a spatial configuration similar to that of the "pain matrix". For these reasons, we propose an alternative view of the functional significance of this cortical network, in which it reflects a system involved in detecting, orienting attention towards, and reacting to the occurrence of salient sensory events. This cortical network might represent a basic mechanism through which significant events for the body's integrity are detected, regardless of the sensory channel through which these events are conveyed. This function would involve the construction of a multimodal cortical representation of the body and nearby space. Under the assumption that this network acts as a defensive system signaling potentially damaging threats for the body, emphasis is no longer on the quality of the sensation elicited by noxious stimuli but on the action prompted by the occurrence of potential threats

Facts, skills and intuition : A typology of personal knowledge

This paper introduces a knowledge model in which the types of knowledge are formed according to the nature of knowledge. First we use Ryle’s distinction of “that” and “how” knowledge, to which we add further three types. The five knowledge types are then synthesized using Polanyi’s distinction of focal and subsidiary awareness. The resulting model distinguishes three types of knowledge, the facts, the skills, and the intuition; all three having focal and subsidiary parts. We believe that this knowledge model is comprehensive in the sense that can classify any knowledge and it also has great explanatory power, as it is demonstrated through illustrative examples. Moreover, the model is elegant and easy to use, which facilitates our understanding of the domain of personal knowledge. Therefore we expect our findings to be useful for both researchers and educators in the field of knowledge and knowledge management

An overview of current approaches and future challenges in physiological monitoring

Sufficient evidence exists from laboratory studies to suggest that physiological measures can be useful as an adjunct to behavioral and subjective measures of human performance and capabilities. Thus it is reasonable to address the conceptual and engineering challenges that arise in applying this technology in operational settings. Issues reviewed include the advantages and disadvantages of constructs such as mental states, the need for physiological measures of performance, areas of application for physiological measures in operational settings, which measures appear to be most useful, problem areas that arise in the use of these measures in operational settings, and directions for future development

Neural population coding: combining insights from microscopic and mass signals

Behavior relies on the distributed and coordinated activity of neural populations. Population activity can be measured using multi-neuron recordings and neuroimaging. Neural recordings reveal how the heterogeneity, sparseness, timing, and correlation of population activity shape information processing in local networks, whereas neuroimaging shows how long-range coupling and brain states impact on local activity and perception. To obtain an integrated perspective on neural information processing we need to combine knowledge from both levels of investigation. We review recent progress of how neural recordings, neuroimaging, and computational approaches begin to elucidate how interactions between local neural population activity and large-scale dynamics shape the structure and coding capacity of local information representations, make them state-dependent, and control distributed populations that collectively shape behavior