cognitive neuroscience: perception, attention, and memory

Editorial Cognitive Neuroscience: Perception, attention, and memory Cognitive Neuroscience represents a synthesis of traditional approaches, which include cognitive and experi- mental psychology, neuropsychology, psychophysiology, developmental psychology, and to a lesser extent, clinical psychology. Such a broad spectrum requires interdisciplinary work, which no longer allows researchers to remain focused within classical ®elds. Cognitive Neuroscience also has close links to other natural sciences such as bio- physics, neurology, neurobiology and neural computation, just to mention a few. The legend says that the name Cogni- tive Neuroscience was born during a conversation between Michael S. Gazzaniga and George A. Miller in a New York taxi cab in the late 1970s [1]. However, it took several years before the term `Cognitive Neuroscience' was fully estab- lished in the scienti®c community, and there are still some western countries in which Cognitive Neuroscience is not used as the name of a university research and teaching ®eld. Retaining traditional sub-disciplines at the organisational level, however, has not prevented more and more scientists seeing themselves as cognitive neuroscientists or the very rapid growth of the ®eld. For example, the ®rst meeting in 1994 of the Cognitive Neuroscience Society was visited by 400 scientists. The last meeting held in spring 2001 had more than 1400 participants. The development and use of neuroimaging techniques like PET and fMRI produced a major boost to the ®eld during the last decade and has been a powerful trigger of interdisciplinary work, but, it is not just imaging which allows new insights into the neural mechanisms of cognitive function, the ®eld also bene®ts from other highly developed technical devices, such as high density electrode array EEG, whole head MEG and TMS. It is the challenge of the new century that the respec- tive techniques are used together in one experiment in order to obtain complementary information, which one would not get by using a single technique. The ®rst steps in recording EEG while the subject is in the fMRI scanner are already being undertaken. Here again, interdisciplinary work is the key to the success. In the present Special Issue, we aimed to give the reader an overview of the most commonly used non-invasive techniques in the ®eld. However, it is quite obvious that it is impossible to present a comprehensive overview within the few pages of one issue of the journal. Therefore, we restricted ourselves to the areas of our research, which are attention, perception, and memory in the broadest sense. Even the restriction to the main topics of our research will not, however, allow coverage of all aspects of research performed in these areas. The ®rst section of the special issue is devoted to neural mechanisms of attention in the human brain. Event-related potentials ERPs) in healthy subjects and in patients with focal lesions provided an important insight into neural mechanisms of attention and the brain areas required for selective processing. This is complemented and extended by imaging studies. Here, the intact brain can be investigated to give us a better understanding of what areas in the brain are related to attentional information processing. Most of the research on attention was restricted to a single modality, and within this modality even to a particular require- ment of attentional orienting, like visual spatial attention or selective feature processing. However, our everyday life is not restricted to processing within a single modality. For example, when we hear a sound we tend to orient to the source of that sound. Recently, more and more work has been done to investigate cross-modal links in attention, which are investigated by means of behavioural as well as ERP data. This is an exciting new area of research about which there is still very little known. Macroscopic recordings give us only very limited information about how neuro- nal networks interact and the nature of the neural mechanisms, which comprise such networks. Computa- tional modelling makes it possible to build and test circuits that simulate the neural interaction required for attentional information processing. Single cell or multi-unit activity recordings in animal cortex make it possible to test the predictions of these theoretical models, which enables such arti®cial networks to be developed further so as to incorporate unexpected ®ndings. A further clear example of the productive interactions that can occur between computational modelling and intra- cortical recordings in animals has arisen in connection with the temporal binding hypothesis, which is discussed in the second section. Here, the animal recording work has stimu- lated research in humans involving the temporal binding hypothesis, which proposes that synchronised neural activity is the key neural mechanism mediating the brain's ability to `bind' different features of an perceived object together to form an integrated percept [2,3]. This relatively new approach of investigating high frequency responses, which Neuroscience and Biobehavioral Reviews 25 2001) 463±464 PERGAMON NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 0149-7634/01/$ - see front matter q 2001 Elsevier Science Ltd. All rights reserved. PII: S0149-763401)00026-4 www.elsevier.com/locate/neubiorev

cognitive neuroscience: perception, attention, and memory

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