101
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Cossell L, Iacaruso MF, Muir DR, Houlton R, Sader EN, Ko H, Hofer SB, Mrsic-Flogel TD. Functional organization of excitatory synaptic strength in primary visual cortex. Nature 2015; 518:399-403. [PMID: 25652823 PMCID: PMC4843963 DOI: 10.1038/nature14182] [Citation(s) in RCA: 321] [Impact Index Per Article: 35.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2014] [Accepted: 01/02/2015] [Indexed: 01/19/2023]
Abstract
The strength of synaptic connections fundamentally determines how neurons influence each other's firing. Excitatory connection amplitudes between pairs of cortical neurons vary over two orders of magnitude, comprising only very few strong connections among many weaker ones. Although this highly skewed distribution of connection strengths is observed in diverse cortical areas, its functional significance remains unknown: it is not clear how connection strength relates to neuronal response properties, nor how strong and weak inputs contribute to information processing in local microcircuits. Here we reveal that the strength of connections between layer 2/3 (L2/3) pyramidal neurons in mouse primary visual cortex (V1) obeys a simple rule--the few strong connections occur between neurons with most correlated responses, while only weak connections link neurons with uncorrelated responses. Moreover, we show that strong and reciprocal connections occur between cells with similar spatial receptive field structure. Although weak connections far outnumber strong connections, each neuron receives the majority of its local excitation from a small number of strong inputs provided by the few neurons with similar responses to visual features. By dominating recurrent excitation, these infrequent yet powerful inputs disproportionately contribute to feature preference and selectivity. Therefore, our results show that the apparently complex organization of excitatory connection strength reflects the similarity of neuronal responses, and suggest that rare, strong connections mediate stimulus-specific response amplification in cortical microcircuits.
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Affiliation(s)
- Lee Cossell
- Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH - 4056 Basel, Switzerland
| | - Maria Florencia Iacaruso
- Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH - 4056 Basel, Switzerland
| | - Dylan R Muir
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH - 4056 Basel, Switzerland
| | - Rachael Houlton
- Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK
| | - Elie N Sader
- Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK
| | - Ho Ko
- Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK
- Lui Che Woo Institute of Innovative Medicine and Chow Yuk Ho Technology Center for Innovative Medicine, Faculty of Medicine, the Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
| | - Sonja B Hofer
- Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH - 4056 Basel, Switzerland
| | - Thomas D Mrsic-Flogel
- Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH - 4056 Basel, Switzerland
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102
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Sadeh S, Rotter S. Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics. PLoS Comput Biol 2015; 11:e1004045. [PMID: 25569445 PMCID: PMC4287576 DOI: 10.1371/journal.pcbi.1004045] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2014] [Accepted: 11/14/2014] [Indexed: 02/02/2023] Open
Abstract
The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not depend on the state of network dynamics, and hold equally well for mean-driven and fluctuation-driven regimes of activity.
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Affiliation(s)
- Sadra Sadeh
- Bernstein Center Freiberg & Faculty of Biology, University of Freiberg, Freiberg, Germany
- * E-mail:
| | - Stefan Rotter
- Bernstein Center Freiberg & Faculty of Biology, University of Freiberg, Freiberg, Germany
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103
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Bauer R, Zubler F, Pfister S, Hauri A, Pfeiffer M, Muir DR, Douglas RJ. Developmental self-construction and -configuration of functional neocortical neuronal networks. PLoS Comput Biol 2014; 10:e1003994. [PMID: 25474693 PMCID: PMC4256067 DOI: 10.1371/journal.pcbi.1003994] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Accepted: 10/09/2014] [Indexed: 11/20/2022] Open
Abstract
The prenatal development of neural circuits must provide sufficient configuration to support at least a set of core postnatal behaviors. Although knowledge of various genetic and cellular aspects of development is accumulating rapidly, there is less systematic understanding of how these various processes play together in order to construct such functional networks. Here we make some steps toward such understanding by demonstrating through detailed simulations how a competitive co-operative (‘winner-take-all’, WTA) network architecture can arise by development from a single precursor cell. This precursor is granted a simplified gene regulatory network that directs cell mitosis, differentiation, migration, neurite outgrowth and synaptogenesis. Once initial axonal connection patterns are established, their synaptic weights undergo homeostatic unsupervised learning that is shaped by wave-like input patterns. We demonstrate how this autonomous genetically directed developmental sequence can give rise to self-calibrated WTA networks, and compare our simulation results with biological data. Models of learning in artificial neural networks generally assume that the neurons and approximate network are given, and then learning tunes the synaptic weights. By contrast, we address the question of how an entire functional neuronal network containing many differentiated neurons and connections can develop from only a single progenitor cell. We chose a winner-take-all network as the developmental target, because it is a computationally powerful circuit, and a candidate motif of neocortical networks. The key aspect of this challenge is that the developmental mechanisms must be locally autonomous as in Biology: They cannot depend on global knowledge or supervision. We have explored this developmental process by simulating in physical detail the fundamental biological behaviors, such as cell proliferation, neurite growth and synapse formation that give rise to the structural connectivity observed in the superficial layers of the neocortex. These differentiated, approximately connected neurons then adapt their synaptic weights homeostatically to obtain a uniform electrical signaling activity before going on to organize themselves according to the fundamental correlations embedded in a noisy wave-like input signal. In this way the precursor expands itself through development and unsupervised learning into winner-take-all functionality and orientation selectivity in a biologically plausible manner.
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Affiliation(s)
- Roman Bauer
- Institute of Neuroinformatics, University/ETH Zürich, Zürich, Switzerland
- School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
- * E-mail:
| | - Frédéric Zubler
- Institute of Neuroinformatics, University/ETH Zürich, Zürich, Switzerland
- Department of Neurology, Inselspital Bern, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Sabina Pfister
- Institute of Neuroinformatics, University/ETH Zürich, Zürich, Switzerland
| | - Andreas Hauri
- Institute of Neuroinformatics, University/ETH Zürich, Zürich, Switzerland
| | - Michael Pfeiffer
- Institute of Neuroinformatics, University/ETH Zürich, Zürich, Switzerland
| | - Dylan R. Muir
- Institute of Neuroinformatics, University/ETH Zürich, Zürich, Switzerland
- Biozentrum, University of Basel, Basel, Switzerland
| | - Rodney J. Douglas
- Institute of Neuroinformatics, University/ETH Zürich, Zürich, Switzerland
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104
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Sadeh S, Rotter S. Distribution of orientation selectivity in recurrent networks of spiking neurons with different random topologies. PLoS One 2014; 9:e114237. [PMID: 25469704 PMCID: PMC4254981 DOI: 10.1371/journal.pone.0114237] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2014] [Accepted: 11/04/2014] [Indexed: 11/18/2022] Open
Abstract
Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.
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Affiliation(s)
- Sadra Sadeh
- Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Stefan Rotter
- Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Freiburg, Germany
- * E-mail:
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105
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Litwin-Kumar A, Doiron B. Formation and maintenance of neuronal assemblies through synaptic plasticity. Nat Commun 2014; 5:5319. [PMID: 25395015 DOI: 10.1038/ncomms6319] [Citation(s) in RCA: 147] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Accepted: 09/18/2014] [Indexed: 01/12/2023] Open
Abstract
The architecture of cortex is flexible, permitting neuronal networks to store recent sensory experiences as specific synaptic connectivity patterns. However, it is unclear how these patterns are maintained in the face of the high spike time variability associated with cortex. Here we demonstrate, using a large-scale cortical network model, that realistic synaptic plasticity rules coupled with homeostatic mechanisms lead to the formation of neuronal assemblies that reflect previously experienced stimuli. Further, reverberation of past evoked states in spontaneous spiking activity stabilizes, rather than erases, this learned architecture. Spontaneous and evoked spiking activity contains a signature of learned assembly structures, leading to testable predictions about the effect of recent sensory experience on spike train statistics. Our work outlines requirements for synaptic plasticity rules capable of modifying spontaneous dynamics and shows that this modification is beneficial for stability of learned network architectures.
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Affiliation(s)
- Ashok Litwin-Kumar
- 1] Program for Neural Computation, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA [2] Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA [3] Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania 15213, USA
| | - Brent Doiron
- 1] Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA [2] Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania 15213, USA
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106
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Affiliation(s)
- Ho Ko
- Lui Che Woo Institute of Innovative Medicine and Chow Yuk Ho Technology Center for Innovative Medicine, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong
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107
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Kang JI, Huppé-Gourgues F, Vaucher E. Boosting visual cortex function and plasticity with acetylcholine to enhance visual perception. Front Syst Neurosci 2014; 8:172. [PMID: 25278848 PMCID: PMC4167004 DOI: 10.3389/fnsys.2014.00172] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2014] [Accepted: 08/31/2014] [Indexed: 11/29/2022] Open
Abstract
The cholinergic system is a potent neuromodulatory system that plays critical roles in cortical plasticity, attention and learning. In this review, we propose that the cellular effects of acetylcholine (ACh) in the primary visual cortex during the processing of visual inputs might induce perceptual learning; i.e., long-term changes in visual perception. Specifically, the pairing of cholinergic activation with visual stimulation increases the signal-to-noise ratio, cue detection ability and long-term facilitation in the primary visual cortex. This cholinergic enhancement would increase the strength of thalamocortical afferents to facilitate the treatment of a novel stimulus while decreasing the cortico-cortical signaling to reduce recurrent or top-down modulation. This balance would be mediated by different cholinergic receptor subtypes that are located on both glutamatergic and GABAergic neurons of the different cortical layers. The mechanisms of cholinergic enhancement are closely linked to attentional processes, long-term potentiation (LTP) and modulation of the excitatory/inhibitory balance. Recently, it was found that boosting the cholinergic system during visual training robustly enhances sensory perception in a long-term manner. Our hypothesis is that repetitive pairing of cholinergic and sensory stimulation over a long period of time induces long-term changes in the processing of trained stimuli that might improve perceptual ability. Various non-invasive approaches to the activation of the cholinergic neurons have strong potential to improve visual perception.
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Affiliation(s)
- Jun Il Kang
- École d'optométrie, Université de Montréal Montréal, QC, Canada ; Département de Neuroscience, Université de Montréal Montréal, QC, Canada
| | | | - Elvire Vaucher
- École d'optométrie, Université de Montréal Montréal, QC, Canada
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108
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Abstract
Layer 5 thick tufted pyramidal cells (TTCs) in the neocortex are particularly electrically complex, owing to their highly excitable dendrites. The interplay between dendritic nonlinearities and recurrent cortical microcircuit activity in shaping network response is largely unknown. We simulated detailed conductance-based models of TTCs forming recurrent microcircuits that were interconnected as found experimentally; the network was embedded in a realistic background synaptic activity. TTCs microcircuits significantly amplified brief thalamocortical inputs; this cortical gain was mediated by back-propagation activated N-methyl-d-aspartate depolarizations and dendritic back-propagation-activated Ca2+ spike firing, ignited by the coincidence of thalamic-activated somatic spike and local dendritic synaptic inputs, originating from the cortical microcircuit. Surprisingly, dendritic nonlinearities in TTCs microcircuits linearly multiplied thalamic inputs—amplifying them while maintaining input selectivity. Our findings indicate that dendritic nonlinearities are pivotal in controlling the gain and the computational functions of TTCs microcircuits, which serve as a dominant output source for the neocortex.
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Affiliation(s)
- Etay Hay
- Edmond and Lily Safra Center for Brain Sciences
| | - Idan Segev
- Edmond and Lily Safra Center for Brain Sciences Department of Neurobiology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
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109
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Xu HT, Han Z, Gao P, He S, Li Z, Shi W, Kodish O, Shao W, Brown KN, Huang K, Shi SH. Distinct lineage-dependent structural and functional organization of the hippocampus. Cell 2014; 157:1552-64. [PMID: 24949968 DOI: 10.1016/j.cell.2014.03.067] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2013] [Revised: 02/21/2014] [Accepted: 03/29/2014] [Indexed: 12/21/2022]
Abstract
The hippocampus, as part of the cerebral cortex, is essential for memory formation and spatial navigation. Although it has been extensively studied, especially as a model system for neurophysiology, the cellular processes involved in constructing and organizing the hippocampus remain largely unclear. Here, we show that clonally related excitatory neurons in the developing hippocampus are progressively organized into discrete horizontal, but not vertical, clusters in the stratum pyramidale, as revealed by both cell-type-specific retroviral labeling and mosaic analysis with double markers (MADM). Moreover, distinct from those in the neocortex, sister excitatory neurons in the cornu ammonis 1 region of the hippocampus rarely develop electrical or chemical synapses with each other. Instead, they preferentially receive common synaptic input from nearby fast-spiking (FS), but not non-FS, interneurons and exhibit synchronous synaptic activity. These results suggest that shared inhibitory input may specify horizontally clustered sister excitatory neurons as functional units in the hippocampus.
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Affiliation(s)
- Hua-Tai Xu
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Zhi Han
- College of Software, Nankai University, 94 Weijin Road, Tianjin 300071, China
| | - Peng Gao
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Graduate Program in Neuroscience, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
| | - Shuijin He
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Zhizhong Li
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Wei Shi
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Graduate Program in Neuroscience, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
| | - Oren Kodish
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Wei Shao
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Graduate Program in Biochemistry and Structural Biology, Cell and Developmental Biology, and Molecular Biology, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
| | - Keith N Brown
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Graduate Program in Neuroscience, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
| | - Kun Huang
- Department of Biomedical Informatics, The Ohio State University, 333 West 10(th) Avenue, Columbus, OH 43210, USA
| | - Song-Hai Shi
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Graduate Program in Neuroscience, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA; Graduate Program in Biochemistry and Structural Biology, Cell and Developmental Biology, and Molecular Biology, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA.
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110
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Cimenser A, Miller KD. The effects of short-term synaptic depression at thalamocortical synapses on orientation tuning in cat V1. PLoS One 2014; 9:e106046. [PMID: 25157879 PMCID: PMC4144965 DOI: 10.1371/journal.pone.0106046] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Accepted: 07/30/2014] [Indexed: 12/02/2022] Open
Abstract
We examine the effects of short-term synaptic depression on the orientation tuning of the LGN input to simple cells in cat primary visual cortex (V1). The total LGN input has an untuned component as well as a tuned component, both of which grow with stimulus contrast. The untuned component is not visible in the firing rate responses of the simple cells. The suppression of the contribution of the untuned input component to firing rate responses is key to establishing orientation selectivity and its invariance with stimulus contrast. It has been argued that synaptic depression of LGN inputs could contribute to the selective suppression of the untuned component and thus contribute to the tuning observed in simple cells. We examine this using a model fit to the depression observed at thalamocortical synapses in-vivo, and compare this to an earlier model fit based on in-vitro observations. We examine the tuning of both the conductance and the firing rate induced in simple cells by the net LGN input. We find that depression causes minimal suppression of the untuned component. The primary effect of depression is to cause the contrast response curve to saturate at lower contrasts without differentially affecting the tuned vs. untuned components. This effect is slightly weaker for in-vivo vs. in-vitro parameters. Thus, synaptic depression of LGN inputs does not appreciably contribute to the orientation tuning of V1 simple cells.
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Affiliation(s)
- Aylin Cimenser
- Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Physics, Boston University, Boston, Massachusetts, United States of America
- * E-mail:
| | - Kenneth D. Miller
- Center for Theoretical Neuroscience, College of Physicians and Surgeons, Columbia University, New York, New York, United States of America
- Department of Neuroscience, College of Physicians and Surgeons, Columbia University, New York, New York, United States of America
- Swartz Program in Theoretical Neuroscience, College of Physicians and Surgeons, Columbia University, New York, New York, United States of America
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111
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Scaling down of balanced excitation and inhibition by active behavioral states in auditory cortex. Nat Neurosci 2014; 17:841-50. [PMID: 24747575 PMCID: PMC4108079 DOI: 10.1038/nn.3701] [Citation(s) in RCA: 220] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2014] [Accepted: 03/24/2014] [Indexed: 12/12/2022]
Abstract
Cortical sensory processing is modulated by behavioral and cognitive states. How
the modulation is achieved through impacting synaptic circuits remains largely unknown. In
awake mouse auditory cortex, we reported that sensory-evoked spike responses of layer 2/3
(L2/3) excitatory cells were scaled down with preserved sensory tuning when animals
transitioned from quiescence to active behaviors, while L4 and thalamic responses were
unchanged. Whole-cell voltage-clamp recordings further revealed that tone-evoked synaptic
excitation and inhibition exhibited a robust functional balance. Changes of behavioral
state caused scaling down of excitation and inhibition at an approximately equal level in
L2/3 cells, but no synaptic changes in L4 cells. This laminar-specific gain control could
be attributed to an enhancement of L1–mediated inhibitory tone, with L2/3
parvalbumin inhibitory neurons suppressed as well. Thus, L2/3 circuits can adjust the
salience of output in accordance with momentary behavioral demands while maintaining the
sensitivity and quality of sensory processing.
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112
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Wolf F, Engelken R, Puelma-Touzel M, Weidinger JDF, Neef A. Dynamical models of cortical circuits. Curr Opin Neurobiol 2014; 25:228-36. [PMID: 24658059 DOI: 10.1016/j.conb.2014.01.017] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2013] [Revised: 01/21/2014] [Accepted: 01/22/2014] [Indexed: 11/27/2022]
Abstract
Cortical neurons operate within recurrent neuronal circuits. Dissecting their operation is key to understanding information processing in the cortex and requires transparent and adequate dynamical models of circuit function. Convergent evidence from experimental and theoretical studies indicates that strong feedback inhibition shapes the operating regime of cortical circuits. For circuits operating in inhibition-dominated regimes, mathematical and computational studies over the past several years achieved substantial advances in understanding response modulation and heterogeneity, emergent stimulus selectivity, inter-neuron correlations, and microstate dynamics. The latter indicate a surprisingly strong dependence of the collective circuit dynamics on the features of single neuron action potential generation. New approaches are needed to definitely characterize the cortical operating regime.
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Affiliation(s)
- Fred Wolf
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Bernstein Focus Neurotechnology, Göttingen, Germany; Faculty of Physics, Göttingen University, Göttingen, Germany.
| | - Rainer Engelken
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Bernstein Focus Neurotechnology, Göttingen, Germany; Faculty of Physics, Göttingen University, Göttingen, Germany
| | - Maximilian Puelma-Touzel
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Bernstein Focus Neurotechnology, Göttingen, Germany; Faculty of Physics, Göttingen University, Göttingen, Germany
| | - Juan Daniel Flórez Weidinger
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Bernstein Focus Neurotechnology, Göttingen, Germany; Faculty of Physics, Göttingen University, Göttingen, Germany
| | - Andreas Neef
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Bernstein Center for Computational Neuroscience, Göttingen, Germany; Bernstein Focus Neurotechnology, Göttingen, Germany; Faculty of Physics, Göttingen University, Göttingen, Germany
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113
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Li YT, Liu BH, Chou XL, Zhang LI, Tao HW. Strengthening of Direction Selectivity by Broadly Tuned and Spatiotemporally Slightly Offset Inhibition in Mouse Visual Cortex. Cereb Cortex 2014; 25:2466-77. [PMID: 24654259 DOI: 10.1093/cercor/bhu049] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Direction selectivity (DS) of neuronal responses is fundamental for motion detection. How the integration of synaptic excitation and inhibition contributes to DS however remains not well-understood. Here, in vivo whole-cell voltage-clamp recordings in mouse primary visual cortex (V1) revealed that layer 4 simple cells received direction-tuned excitatory inputs but barely tuned inhibitory inputs under drifting-bar stimulation. Excitation and inhibition exhibited differential temporal offsets under movements of opposite directions: excitation peaked earlier than inhibition at the preferred direction, and vice versa at the null direction. This could be attributed to a small spatial mismatch between overlapping excitatory and inhibitory receptive fields: the distribution of excitatory input strengths was skewed and the skewness was strongly correlated with the DS of excitatory input, whereas that of inhibitory input strengths was spatially symmetric. Neural modeling revealed that the relatively stronger inhibition under null directional movements, as well as the specific spatial-temporal offsets between excitation and inhibition, allowed inhibition to enhance the DS of output responses by suppressing the null response more effectively than the preferred response. Our data demonstrate that while tuned excitatory input provides the basis for DS in mouse V1, the largely untuned and spatiotemporally offset inhibition contributes importantly to sharpening of DS.
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Affiliation(s)
- Ya-Tang Li
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA Graduate Programs, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Bao-Hua Liu
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Xiao-Lin Chou
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA Graduate Programs, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Li I Zhang
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Huizhong Whit Tao
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA Department of Cell and Neurobiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
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114
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Cruz-Martín A, El-Danaf RN, Osakada F, Sriram B, Dhande OS, Nguyen PL, Callaway EM, Ghosh A, Huberman AD. A dedicated circuit links direction-selective retinal ganglion cells to the primary visual cortex. Nature 2014; 507:358-61. [PMID: 24572358 PMCID: PMC4143386 DOI: 10.1038/nature12989] [Citation(s) in RCA: 215] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2013] [Accepted: 12/31/2013] [Indexed: 12/27/2022]
Abstract
How specific features in the environment are represented within the brain is an important unanswered question in neuroscience. A subset of retinal neurons, called direction-selective ganglion cells (DSGCs), are specialized for detecting motion along specific axes of the visual field. Despite extensive study of the retinal circuitry that endows DSGCs with their unique tuning properties, their downstream circuitry in the brain and thus their contribution to visual processing has remained unclear. In mice, several different types of DSGCs connect to the dorsal lateral geniculate nucleus (dLGN), the visual thalamic structure that harbours cortical relay neurons. Whether direction-selective information computed at the level of the retina is routed to cortical circuits and integrated with other visual channels, however, is unknown. Here we show that there is a di-synaptic circuit linking DSGCs with the superficial layers of the primary visual cortex (V1) by using viral trans-synaptic circuit mapping and functional imaging of visually driven calcium signals in thalamocortical axons. This circuit pools information from several types of DSGCs, converges in a specialized subdivision of the dLGN, and delivers direction-tuned and orientation-tuned signals to superficial V1. Notably, this circuit is anatomically segregated from the retino-geniculo-cortical pathway carrying non-direction-tuned visual information to deeper layers of V1, such as layer 4. Thus, the mouse harbours several functionally specialized, parallel retino-geniculo-cortical pathways, one of which originates with retinal DSGCs and delivers direction- and orientation-tuned information specifically to the superficial layers of the primary visual cortex. These data provide evidence that direction and orientation selectivity of some V1 neurons may be influenced by the activation of DSGCs.
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Affiliation(s)
- Alberto Cruz-Martín
- 1] Department of Neurosciences, University of California, San Diego, California 92093, USA [2] Neurobiology Section in the Division of Biological Sciences, University of California, San Diego, California 92093, USA
| | - Rana N El-Danaf
- 1] Department of Neurosciences, University of California, San Diego, California 92093, USA [2] Neurobiology Section in the Division of Biological Sciences, University of California, San Diego, California 92093, USA
| | - Fumitaka Osakada
- Salk Institute for Biological Studies, La Jolla, California 92097, USA
| | - Balaji Sriram
- Neurobiology Section in the Division of Biological Sciences, University of California, San Diego, California 92093, USA
| | - Onkar S Dhande
- 1] Department of Neurosciences, University of California, San Diego, California 92093, USA [2] Neurobiology Section in the Division of Biological Sciences, University of California, San Diego, California 92093, USA
| | - Phong L Nguyen
- 1] Department of Neurosciences, University of California, San Diego, California 92093, USA [2] Neurobiology Section in the Division of Biological Sciences, University of California, San Diego, California 92093, USA
| | - Edward M Callaway
- Salk Institute for Biological Studies, La Jolla, California 92097, USA
| | - Anirvan Ghosh
- Neuroscience Discovery, F. Hoffman La Roche, 4070 Basel, Switzerland
| | - Andrew D Huberman
- 1] Department of Neurosciences, University of California, San Diego, California 92093, USA [2] Neurobiology Section in the Division of Biological Sciences, University of California, San Diego, California 92093, USA [3] Salk Institute for Biological Studies, La Jolla, California 92097, USA [4] Department of Ophthalmology, University of California, San Diego, California 92093, USA
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115
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Sensory-evoked synaptic integration in cerebellar and cerebral cortical neurons. Nat Rev Neurosci 2014; 15:71-83. [PMID: 24434910 DOI: 10.1038/nrn3648] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Neurons integrate synaptic inputs across time and space, a process that determines the transformation of input signals into action potential output. This article explores how synaptic integration contributes to the richness of sensory signalling in the cerebellar and cerebral cortices. Whether a neuron receives a few or a few thousand discrete inputs, most evoked synaptic activity generates only subthreshold membrane potential fluctuations. Sensory tuning of synaptic inputs is typically broad, but short-term dynamics and the interplay between excitation and inhibition restrict action potential firing to narrow windows of opportunity. We highlight the challenges and limitations of the use of somatic recordings in the study of synaptic integration and the importance of active dendritic mechanisms in sensory processing.
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116
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Abstract
The sensory cortex contains a wide array of neuronal types, which are connected together into complex but partially stereotyped circuits. Sensory stimuli trigger cascades of electrical activity through these circuits, causing specific features of sensory scenes to be encoded in the firing patterns of cortical populations. Recent research is beginning to reveal how the connectivity of individual neurons relates to the sensory features they encode, how differences in the connectivity patterns of different cortical cell classes enable them to encode information using different strategies, and how feedback connections from higher-order cortex allow sensory information to be integrated with behavioural context.
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117
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