ArticlePLoS computational biology2018
Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- A Framework Integrating Spiking Cortical Circuit Modeling and Simulation-Based Inference to Probe Biomarkers of Cortical Dysfunction in Alzheimer's Disease.Interdisciplinary sciences, computational life sciences · 2026Article
- A novel mechanism for short-term post-tetanic plasticity in thalamocortical neurons.Brain research · 2025Article
- Determination of the Time-frequency Features for Impulse Components in EEG Signals.Neuroinformatics · 2025Article
- Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Firing-rate based network modeling of the dLGN circuit: Effects of cortical feedback on spatiotemporal response properties of relay cells.PLoS computational biology · 2018Article
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7 authors.
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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.
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