Structured Synaptic Connectivity between Hippocampal Regions

Druckmann, Shaul; Feng, Linqing; Lee, Bokyoung; Yook, Chaehyun; Zhao, Ting; Magee, Jeffrey C.; Kim, Jinhyun

doi:10.1016/j.neuron.2013.11.026

Cited by 180 publications

(184 citation statements)

References 41 publications

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“…The size and location of these dendritic compartments are not fixed and can dynamically change according to the activation and input pattern Behabadi et al, 2012;Jadi et al, 2012;Major et al, 2013). Recent studies support the notion of anatomical and functional clustering of synapses to dendritic compartments both during development and learning (Fu et al, 2012;Takahashi et al, 2012;DeBello et al, 2014;Druckmann et al, 2014;Cichon and Gan, 2015), in line with the possibility that dendritic branchlets may serve as key plasticity and storage elements during learning (Mel, 1992;Poirazi and Mel, 2001;Chklovskii et al, 2004).…”

Section: Compartmentalized Plasticity Mechanismsmentioning

confidence: 74%

A Novel Form of Local Plasticity in Tuft Dendrites of Neocortical Somatosensory Layer 5 Pyramidal Neurons

Sandler

Shulman

Schiller

2016

Neuron

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Tuft dendrites of layer 5 pyramidal neurons form a separate biophysical and processing compartment. Presently, little is known about plasticity mechanisms in this isolated compartment. Here, we describe a novel form of plasticity in which unpaired low-frequency (0.1 Hz) stimulation of tuft inputs resulted in prolonged transient (86.3 ± 7.3 min) potentiation of EPSPs (286.1% ± 30.5%) and enhanced local excitability that enabled more-efficient back-propagation of axo-somatic action potentials and dendritic calcium spikes selectively into the activated dendritic segments. This plasticity was exclusive to tuft dendrites and did not occur in basal dendrites. Induction of this plasticity depended on activation of Kv4.2 potassium and NMDAR channels, internalization of membrane proteins, and insertion of AMPAR. This unique form of tuft plasticity increases proximal-distal electrical coupling of activated tuft dendrites and opens a prolonged time window for binding and storing feedforward and feedback information in a branch-specific manner.

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Section: Compartmentalized Plasticity Mechanismsmentioning

confidence: 74%

A Novel Form of Local Plasticity in Tuft Dendrites of Neocortical Somatosensory Layer 5 Pyramidal Neurons

Sandler

Shulman

Schiller

2016

Neuron

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“…In a different piece of work from the same serial dataset the directional selectivity of individual amacrine dendrites looked to be arranged in a way that was incompatible with random contacts . In hippocampus, support for the idea that connectivity was not explicable simply by proximity has also been obtained (Mishchenko et al, 2010;Druckmann et al, 2014). The previous results do not explicitly test the degree to which actual proximity of each individual axon to all the postsynaptic sites in a volume explains the connectivity patterns observed.…”

Section: Discussionmentioning

confidence: 91%

Saturated Reconstruction of a Volume of Neocortex

Kasthuri

Hayworth

Berger

et al. 2015

Cell

972

974

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We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters' rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.

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“…24, 2015; findings and demonstrated that dendrites extend the computational capacity of a single neuron (Cazé et al, 2012(Cazé et al, , 2013. Recent experimental evidence has shown that excitatory synapses distribute non-randomly on dendrites and can form synaptic clusters (Takahashi et al, 2012;Druckmann et al, 2014;Kleindienst et al, 2011). We examine here whether we can employ the spatial distribution of excitatory synapses to implement stimulus selectivity.…”

Section: Introductionmentioning

confidence: 92%

Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity

et al. 2017

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Hearing, vision, touch -underlying all of these senses is stimulus selectivity, a robust information processing operation in which cortical neurons respond more to some stimuli than to others. Previous models assume that these neurons receive the highest weighted input from an ensemble encoding the preferred stimulus, but dendrites enable other possibilities. Non-linear dendritic processing can produce stimulus selectivity based on the spatial distribution of synapses, even if the total preferred stimulus weight does . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/023200 doi: bioRxiv preprint first posted online Jul. 24, 2015; not exceed that of non-preferred stimuli. Using a multi-subunit non-linear model, we demonstrate that stimulus selectivity can arise from the spatial distribution of synapses.We propose this as a general mechanism for information processing by neurons possessing dendritic trees. Moreover, we show that this implementation of stimulus selectivity increases the neuron's robustness to synaptic and dendritic failure. Importantly, our model can maintain stimulus selectivity for a larger range of synapses or dendrites loss than an equivalent linear model. We then use a layer 2/3 biophysical neuron model to show that our implementation is consistent with two recent experimental observations: (1) one can observe a mixture of selectivities in dendrites, that can differ from the somatic selectivity, and (2) hyperpolarization can broaden somatic tuning without affecting dendritic tuning. Our model predicts that an initially non-selective neuron can become selective when depolarized. In addition to motivating new experiments, the model's increased robustness to synapses and dendrites loss provides a starting point for fault-resistant neuromorphic chip development.

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Structured Synaptic Connectivity between Hippocampal Regions

Cited by 180 publications

References 41 publications

A Novel Form of Local Plasticity in Tuft Dendrites of Neocortical Somatosensory Layer 5 Pyramidal Neurons

A Novel Form of Local Plasticity in Tuft Dendrites of Neocortical Somatosensory Layer 5 Pyramidal Neurons

Saturated Reconstruction of a Volume of Neocortex

Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity

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