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Wollstadt P, Rathbun DL, Usrey WM, Bastos AM, Lindner M, Priesemann V, Wibral M. Information-theoretic analyses of neural data to minimize the effect of researchers' assumptions in predictive coding studies. PLoS Comput Biol 2023; 19:e1011567. [PMID: 37976328 PMCID: PMC10703417 DOI: 10.1371/journal.pcbi.1011567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 12/07/2023] [Accepted: 10/02/2023] [Indexed: 11/19/2023] Open
Abstract
Studies investigating neural information processing often implicitly ask both, which processing strategy out of several alternatives is used and how this strategy is implemented in neural dynamics. A prime example are studies on predictive coding. These often ask whether confirmed predictions about inputs or prediction errors between internal predictions and inputs are passed on in a hierarchical neural system-while at the same time looking for the neural correlates of coding for errors and predictions. If we do not know exactly what a neural system predicts at any given moment, this results in a circular analysis-as has been criticized correctly. To circumvent such circular analysis, we propose to express information processing strategies (such as predictive coding) by local information-theoretic quantities, such that they can be estimated directly from neural data. We demonstrate our approach by investigating two opposing accounts of predictive coding-like processing strategies, where we quantify the building blocks of predictive coding, namely predictability of inputs and transfer of information, by local active information storage and local transfer entropy. We define testable hypotheses on the relationship of both quantities, allowing us to identify which of the assumed strategies was used. We demonstrate our approach on spiking data collected from the retinogeniculate synapse of the cat (N = 16). Applying our local information dynamics framework, we are able to show that the synapse codes for predictable rather than surprising input. To support our findings, we estimate quantities applied in the partial information decomposition framework, which allow to differentiate whether the transferred information is primarily bottom-up sensory input or information transferred conditionally on the current state of the synapse. Supporting our local information-theoretic results, we find that the synapse preferentially transfers bottom-up information.
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Affiliation(s)
- Patricia Wollstadt
- MEG Unit, Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Daniel L. Rathbun
- Center for Neuroscience, University of California, Davis, California, United States of America
- Center for Ophthalmology, University of Tübingen, Tübingen, Germany
| | - W. Martin Usrey
- Center for Neuroscience, University of California, Davis, California, United States of America
- Department of Neurobiology, Physiology, and Behavior, University of California, Davis, California, United States of America
| | - André Moraes Bastos
- Department of Psychology and Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Michael Lindner
- Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen, Germany
| | - Viola Priesemann
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Michael Wibral
- Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen, Germany
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Zheng B, Liu DD, Theyel BB, Abdulrazeq H, Kimata AR, Lauro PM, Asaad WF. Thalamic neuromodulation in epilepsy: A primer for emerging circuit-based therapies. Expert Rev Neurother 2023; 23:123-140. [PMID: 36731858 DOI: 10.1080/14737175.2023.2176752] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
INTRODUCTION Epilepsy is a common, often debilitating disease of hyperexcitable neural networks. While medically intractable cases may benefit from surgery, there may be no single, well-localized focus for resection or ablation. In such cases, approaching the disease from a network-based perspective may be beneficial. AREAS COVERED Herein, the authors provide a narrative review of normal thalamic anatomy and physiology and propose general strategies for preventing and/or aborting seizures by modulating this structure. Additionally, they make specific recommendations for targeting the thalamus within different contexts, motivated by a more detailed discussion of its distinct nuclei and their respective connectivity. By describing important principles governing thalamic function and its involvement in seizure networks, the authors aim to provide a primer for those now entering this fast-growing field of thalamic neuromodulation for epilepsy. EXPERT OPINION The thalamus is critically involved with the function of many cortical and subcortical areas, suggesting it may serve as a compelling node for preventing or aborting seizures, and so it has increasingly been targeted for the surgical treatment of epilepsy. As various thalamic neuromodulation strategies for seizure control are developed, there is a need to ground such interventions in a mechanistic, circuit-based framework.
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Affiliation(s)
- Bryan Zheng
- The Warren Alpert Medical School of Brown University, Providence, RI, USA.,Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - David D Liu
- The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Brian B Theyel
- Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA.,Department of Neuroscience, Brown University, Providence, RI, USA
| | - Hael Abdulrazeq
- Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - Anna R Kimata
- The Warren Alpert Medical School of Brown University, Providence, RI, USA.,Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - Peter M Lauro
- The Warren Alpert Medical School of Brown University, Providence, RI, USA.,Department of Neuroscience, Brown University, Providence, RI, USA
| | - Wael F Asaad
- Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA.,Department of Neuroscience, Brown University, Providence, RI, USA.,The Carney Institute for Brain Science, Brown University, Providence, RI, USA.,The Norman Prince Neurosciences Institute, Rhode Island Hospital, Providence, RI, USA
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Brown JW, Taheri A, Kenyon RV, Berger-Wolf TY, Llano DA. Signal Propagation via Open-Loop Intrathalamic Architectures: A Computational Model. eNeuro 2020; 7:ENEURO.0441-19.2020. [PMID: 32005750 PMCID: PMC7053175 DOI: 10.1523/eneuro.0441-19.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 01/13/2020] [Accepted: 01/20/2020] [Indexed: 01/06/2023] Open
Abstract
Propagation of signals across the cerebral cortex is a core component of many cognitive processes and is generally thought to be mediated by direct intracortical connectivity. The thalamus, by contrast, is considered to be devoid of internal connections and organized as a collection of parallel inputs to the cortex. Here, we provide evidence that "open-loop" intrathalamic pathways involving the thalamic reticular nucleus (TRN) can support propagation of oscillatory activity across the cortex. Recent studies support the existence of open-loop thalamo-reticulo-thalamic (TC-TRN-TC) synaptic motifs in addition to traditional closed-loop architectures. We hypothesized that open-loop structural modules, when connected in series, might underlie thalamic and, therefore cortical, signal propagation. Using a supercomputing platform to simulate thousands of permutations of a thalamocortical network based on physiological data collected in mice, rats, ferrets, and cats and in which select synapses were allowed to vary both by class and individually, we evaluated the relative capacities of closed-loop and open-loop TC-TRN-TC synaptic configurations to support both propagation and oscillation. We observed that (1) signal propagation was best supported in networks possessing strong open-loop TC-TRN-TC connectivity; (2) intrareticular synapses were neither primary substrates of propagation nor oscillation; and (3) heterogeneous synaptic networks supported more robust propagation of oscillation than their homogeneous counterparts. These findings suggest that open-loop, heterogeneous intrathalamic architectures might complement direct intracortical connectivity to facilitate cortical signal propagation.
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Affiliation(s)
- Jeffrey W Brown
- College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Aynaz Taheri
- Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60607
| | - Robert V Kenyon
- Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60607
| | - Tanya Y Berger-Wolf
- Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60607
| | - Daniel A Llano
- College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
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Martínez-Cañada P, Mobarhan MH, Halnes G, Fyhn M, Morillas C, Pelayo F, Einevoll GT. Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells. PLoS Comput Biol 2018; 14:e1005930. [PMID: 29377888 PMCID: PMC5805346 DOI: 10.1371/journal.pcbi.1005930] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2017] [Revised: 02/08/2018] [Accepted: 12/17/2017] [Indexed: 11/19/2022] Open
Abstract
Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN) in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs) and interneurons (INs) not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (‘push-pull’) and phase-matched (‘push-push’), as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli when feedback is present. The functional role of the dorsal lateral geniculate nucleus (dLGN), placed on route from retina to primary visual cortex in the early visual pathway, is still poorly understood. A striking feature of the dLGN circuit is that dLGN cells not only receive feedforward input from the retina, but also a prominent feedback from cells in the visual cortex. It has been seen in experiments that cortical feedback modifies the spatial properties of dLGN cells in response to visual stimuli. In particular, it has been shown to increase the center-surround antagonism for flashing-spot and patch-grating visual stimuli, i.e., the suppression of responses to very large stimuli compared to smaller stimuli. Here we investigate the putative mechanisms behind this feature by means of a comprehensive network model of biophysically detailed neuron models for RCs and INs in the dLGN and orientation-selective cortical cells providing the feedback. Our results support that the experimentally observed feedback effects may be due to a phase-reversed (‘push-pull’) arrangement of the cortical feedback where ON-symmetry RCs receive (indirect) inhibitory feedback from ON-dominated cortical cell and excitation from OFF-dominated cortical cells, and vice versa for OFF-symmetry RCs.
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Affiliation(s)
- Pablo Martínez-Cañada
- Department of Computer Architecture and Technology, University of Granada, Granada, Spain
- Centro de Investigación en Tecnologías de la Información y de las Comunicaciones (CITIC), University of Granada, Granada, Spain
| | - Milad Hobbi Mobarhan
- Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Geir Halnes
- Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Marianne Fyhn
- Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Christian Morillas
- Department of Computer Architecture and Technology, University of Granada, Granada, Spain
- Centro de Investigación en Tecnologías de la Información y de las Comunicaciones (CITIC), University of Granada, Granada, Spain
| | - Francisco Pelayo
- Department of Computer Architecture and Technology, University of Granada, Granada, Spain
- Centro de Investigación en Tecnologías de la Información y de las Comunicaciones (CITIC), University of Granada, Granada, Spain
| | - Gaute T. Einevoll
- Center for Integrative Neuroplasticity (CINPLA), University of Oslo, Oslo, Norway
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
- Department of Physics, University of Oslo, Oslo, Norway
- * E-mail:
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Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role. Prog Neurobiol 2017. [DOI: 10.1016/j.pneurobio.2017.06.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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