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Dynamic predictions: Oscillations and synchrony in top–down processing

Nature Reviews Neuroscience volume 2, pages 704716 (2001) | Download Citation

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Abstract

Classical theories of sensory processing view the brain as a passive, stimulus-driven device. By contrast, more recent approaches emphasize the constructive nature of perception, viewing it as an active and highly selective process. Indeed, there is ample evidence that the processing of stimuli is controlled by top–down influences that strongly shape the intrinsic dynamics of thalamocortical networks and constantly create predictions about forthcoming sensory events. We discuss recent experiments indicating that such predictions might be embodied in the temporal structure of both stimulus-evoked and ongoing activity, and that synchronous oscillations are particularly important in this process. Coherence among subthreshold membrane potential fluctuations could be exploited to express selective functional relationships during states of expectancy or attention, and these dynamic patterns could allow the grouping and selection of distributed neuronal responses for further processing.

Key points

  • Classical theories of sensory processing view the brain as a passive, stimulus-driven device. Newer theories, by contrast, view perception as an active, selective process controlled by top–down influences that include expectations and predictions, derived from experience, attention and working memory.

  • The temporal binding model assumes that synchrony between distributed neurons is required for object representation, response selection, attention and sensorimotor integration. In a 'dynamicist' view of top–down influences on perception, synchrony generated intrinsically by interactions between higher and lower cortical areas could strongly influence perception, enhancing some representations and suppressing others.

  • The firing rate and temporal response properties of neurons can be altered by attentional processes, working memory and behavioural context. For example, attention can enhance synchrony and/or gamma-band oscillations in neurons representing the attended stimulus.

  • Spontaneous fluctuations in ongoing activity could represent not noise, but rather 'bias signals' that prime certain stimulus-evoked responses to allow rapid selection among inputs. Self-generated activity fluctuations during the preparatory period can also predict, for example, the direction, latency or speed of a movement.

  • Contextual modulation can arise from networks of frontal, parietal and limbic areas as well as from sensorimotor areas. These areas can represent information related to goal definition, action planning, working memory and selective attention. Assemblies of neuronal populations implementing these aspects of top–down modulation could then entrain assemblies involved in the representation of new stimuli.

  • A new concept of 'top–down' is proposed in which large-scale dynamics, expressing contextual influences and stored knowledge, can influence local processing. Rather than an anatomical hierarchy, this model proposes that any area could, in principle, modulate activity in any other area to which it is connected.

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Acknowledgements

We dedicate this article to the memory of Francisco Varela, whose work profoundly shaped our ideas about the dynamics of the embodied brain and continues to be a source of inspiration.

Author information

Author notes

    • Pascal Fries

    Present address:University of Nijmegen and F. C. Donders Centre for Cognitive Neuroimaging, Adelbertusplein 1, 6525EK Nijmegen, The Netherlands.

Affiliations

  1. Cellular Neurobiology Group, Institute for Medicine, Research Centre Jülich, 52425 Jülich, Germany.

    • Andreas K. Engel
  2. Laboratory of Neuropsychology, National Institute of Mental Health, 9000 Rockville Pike, Bethesda, Maryland 20892-4415, USA.

    • Pascal Fries
  3. Department of Neurophysiology, Max-Planck-Institute for Brain Research, Deutschordenstrasse 46, 60528 Frankfurt, Germany.

    • Wolf Singer

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Corresponding author

Correspondence to Andreas K. Engel.

Glossary

HIERARCHY

A system of interconnected modules, in which 'higher' centres are activated later and contain more abstract representations than 'lower' areas.

ASSEMBLY

A spatially distributed set of cells that are activated in a coherent fashion and are part of the same representation.

BAYESIAN OPERATION

The estimation of conditional probabilities that can be used to quantify inferences about hypotheses, given certain input data. When implemented in a neural network, this can mean, for instance, that a neuron responds to feedforward input signals only if it previously received lateral inputs that convey an expectational bias from other neurons in the network.

VISUOMOTOR GO/NO-GO TASK

A task involving the control of behaviour by two alternative visual stimuli, one allowing and the other preventing a trained motor response.

INDUCED RHYTHMS

Oscillatory signals that are not phase-locked to the stimulus that is presented to the subject.

OPTICAL IMAGING

Recording of neural activity by measuring the optical properties of brain tissue, using either voltage-sensitive dyes or intrinsic signals related to the oxygen saturation of haemoglobin.

CORRELOGRAM

A histogram describing the time relation between two signals, in which a centre peak indicates synchrony and side peaks reflect oscillations.

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https://doi.org/10.1038/35094565

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