9
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Attention Configures Synchronization Within Local Neuronal Networks for Processing of the Behaviorally Relevant Stimulus

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The need for fast and dynamic processing of relevant information imposes high demands onto the flexibility and efficiency of the nervous system. A good example for such flexibility is the attention-dependent selection of relevant sensory information. Studies investigating attentional modulations of neuronal responses to simultaneously arriving input showed that neurons respond, as if only the attended stimulus would be present within their receptive fields (RF). However, attention also improves neuronal representation and behavioral performance, when only one stimulus is present. Thus, attention serves for selecting relevant input and changes the neuronal processing of signals representing selected stimuli, ultimately leading to a more efficient behavioral performance. Here, we tested the hypothesis that attention configures the strength of functional coupling between a local neuronal network's neurons specifically for effective processing of signals representing attended stimuli. This coupling is measured as the strength of γ-synchronization between these neurons. The hypothesis predicts that the pattern of synchronization in local networks should depend on which stimulus is attended. Furthermore, we expect this pattern to be similar for the attended stimulus presented alone or together with irrelevant stimuli in the RF. To test these predictions, we recorded spiking-activity and local field potentials (LFP) with closely spaced electrodes in area V4 of monkeys performing a demanding attention task. Our results show that the γ-band phase coherence (γ-PhC) between spiking-activity and the LFP, as well as the spiking-activity of two groups of neurons, strongly depended on which of the two stimuli in the RF was attended. The γ-PhC was almost identical for the attended stimulus presented either alone or together with a distractor. The functional relevance of dynamic γ-band synchronization is further supported by the observation of strongly degraded γ-PhC before behavioral errors, while firing rates were barely affected. These qualitatively different results point toward a failure of attention-dependent top-down mechanisms to correctly synchronize the local neuronal network in V4, even though this network receives the correctly selected input. These findings support the idea of a flexible, demand-dependent dynamic configuration of local neuronal networks, for performing different functions, even on the same sensory input.

          Related collections

          Most cited references59

          • Record: found
          • Abstract: found
          • Article: not found

          Structural and functional brain networks: from connections to cognition.

          How rich functionality emerges from the invariant structural architecture of the brain remains a major mystery in neuroscience. Recent applications of network theory and theoretical neuroscience to large-scale brain networks have started to dissolve this mystery. Network analyses suggest that hierarchical modular brain networks are particularly suited to facilitate local (segregated) neuronal operations and the global integration of segregated functions. Although functional networks are constrained by structural connections, context-sensitive integration during cognition tasks necessarily entails a divergence between structural and functional networks. This degenerate (many-to-one) function-structure mapping is crucial for understanding the nature of brain networks. The emergence of dynamic functional networks from static structural connections calls for a formal (computational) approach to neuronal information processing that may resolve this dialectic between structure and function.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Measuring phase synchrony in brain signals

            This article presents, for the first time, a practical method for the direct quantification of frequency‐specific synchronization (i.e., transient phase‐locking) between two neuroelectric signals. The motivation for its development is to be able to examine the role of neural synchronies as a putative mechanism for long‐range neural integration during cognitive tasks. The method, called phase‐locking statistics (PLS), measures the significance of the phase covariance between two signals with a reasonable time‐resolution (<100 ms). Unlike the more traditional method of spectral coherence, PLS separates the phase and amplitude components and can be directly interpreted in the framework of neural integration. To validate synchrony values against background fluctuations, PLS uses surrogate data and thus makes no a priori assumptions on the nature of the experimental data. We also apply PLS to investigate intracortical recordings from an epileptic patient performing a visual discrimination task. We find large‐scale synchronies in the gamma band (45 Hz), e.g., between hippocampus and frontal gyrus, and local synchronies, within a limbic region, a few cm apart. We argue that whereas long‐scale effects do reflect cognitive processing, short‐scale synchronies are likely to be due to volume conduction. We discuss ways to separate such conduction effects from true signal synchrony. Hum Brain Mapping 8:194–208, 1999. © 1999 Wiley‐Liss, Inc.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Normalization as a canonical neural computation.

              There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Neural Circuits
                Front Neural Circuits
                Front. Neural Circuits
                Frontiers in Neural Circuits
                Frontiers Media S.A.
                1662-5110
                29 August 2018
                2018
                : 12
                : 71
                Affiliations
                Center for Cognitive Science, Brain Research Institute, University of Bremen , Bremen, Germany
                Author notes

                Edited by: Fu-Ming Zhou, University of Tennessee Health Science Center, United States

                Reviewed by: Ernst Niebur, Johns Hopkins University, United States; Ekaterina Levichkina, The University of Melbourne, Australia

                *Correspondence: Eric Drebitz drebitz@ 123456brain.uni-bremen.de

                †Present Address: Marcus Haag, Institute of Neuroscience, Newcastle University, Newcastle-upon-Tyne, United Kingdom

                Iris Grothe, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany

                Article
                10.3389/fncir.2018.00071
                6123385
                30210309
                e5a9a866-1f06-45d8-a624-625ac5651339
                Copyright © 2018 Drebitz, Haag, Grothe, Mandon and Kreiter.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 March 2018
                : 09 August 2018
                Page count
                Figures: 4, Tables: 1, Equations: 6, References: 69, Pages: 16, Words: 12779
                Funding
                Funded by: FAZIT Stiftung 10.13039/501100003099
                Categories
                Neuroscience
                Original Research

                Neurosciences
                visual cortex,macaque monkey,gamma-band,area v4,neuronal network configuration,spatial selective attention,functional coupling,dynamic assembly formation

                Comments

                Comment on this article