Thalamocortical projection from the ventral posteromedial nucleus sends its collaterals to layer I of the primary somatosensory cortex in rat

Oda, Satoko; Kawakami, Kiyoshi; Yang, Jincheng; Chen, Shaoyun; Yokofujita, Junko; Igarashi, Hiroaki; Tanihata, Sachiko; Kuroda, Minpei

doi:10.1016/j.neulet.2004.06.042

Cited by 34 publications

(27 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…SSC L1 receives its thalamocortical input primarily from the posterior nucleus, whereas motor neocortical L1 receives from the ventromedial and ventrolateral nuclei of the thalamus (Oda et al, 2004; Rubio-Garrido et al, 2009). This input is seen to innervate both the primary and the neighboring cortical column (Oberlaender et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Synaptic and cellular organization of layer 1 of the developing rat somatosensory cortex

2014

View full text Add to dashboard Cite

Layer 1 of the neocortex is sparsely populated with neurons and heavily innervated by fibers from lower layers and proximal and distal brain regions. Understanding the potential functions of this layer requires a comprehensive understanding of its cellular and synaptic organization. We therefore performed a quantitative study of the microcircuitry of neocortical layer 1 (L1) in the somatosensory cortex in juvenile rats (P13–P16) using multi-neuron patch-clamp and 3D morphology reconstructions. Expert-based subjective classification of the morphologies of the recorded L1 neurons suggest 6 morphological classes: (1) the Neurogliaform cells with dense axonal arborizations (NGC-DA) and with sparse arborizations (NGC-SA), (2) the Horizontal Axon Cell (HAC), (3) those with descending axonal collaterals (DAC), (4) the large axon cell (LAC), and (5) the small axon cell (SAC). Objective, supervised and unsupervised cluster analyses confirmed DAC, HAC, LAC and NGC as distinct morphological classes. The neurons were also classified into 5 electrophysiological types based on the Petilla convention; classical non-adapting (cNAC), burst non-adapting (bNAC), classical adapting (cAC), classical stuttering (cSTUT), and classical irregular spiking (cIR). The most common electrophysiological type of neuron was the cNAC type (40%) and the most common morpho-electrical type was the NGC-DA—cNAC. Paired patch-clamp recordings revealed that the neurons were connected via GABAergic inhibitory synaptic connections with a 7.9% connection probability and via gap junctions with a 5.2% connection probability. Most synaptic connections were mediated by both GABAA and GABAB receptors (62.6%). A smaller fraction of synaptic connections were mediated exclusively by GABAA (15.4%) or GABAB (21.8%) receptors. Morphological 3D reconstruction of synaptic connected pairs of L1 neurons revealed multi-synapse connections with an average of 9 putative synapses per connection. These putative synapses were widely distributed with 39% on somata and 61% on dendrites. We also discuss the functional implications of this L1 cellular and synaptic organization in neocortical information processing.

show abstract

Section: Discussionmentioning

confidence: 99%

Synaptic and cellular organization of layer 1 of the developing rat somatosensory cortex

2014

View full text Add to dashboard Cite

show abstract

“…This mechanism allows a coincidence signalling to downstream neurons. Since inputs to the soma and the apical tree may originate from different cortical sources (Budd 1998;Oda et al 2004), burst-timing could provide a way to detect and signal the coincident occurrence of bottomup and top-down signals.…”

Section: Discussionmentioning

confidence: 99%

“…Point-neuron approximations may be a good description for small neurons with short and isotropic dendritic trees. However, the apical dendritic tree of layer 5 pyramidal neurons extends across all cortical layers with a length of roughly 1.5 mm, and integrates inputs from different cortical and subcortical sources (Budd 1998;Binzegger et al 2004;Oda et al 2004). Whether the extended geometry of pyramidal neurons offers real computational advantages, or whether it only solves the 'packing problem' of collecting a large amount of synapses for a single integration process, remains an open issue and it will not be discussed here.…”

Section: Response To Dendritic Inputs and Soma-dendritic Interactionsmentioning

confidence: 99%

The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs

et al. 2008

View full text Add to dashboard Cite

The response of a population of neurons to time-varying synaptic inputs can show a rich phenomenology, hardly predictable from the dynamical properties of the membrane's inherent time constants. For example, a network of neurons in a state of spontaneous activity can respond significantly more rapidly than each single neuron taken individually. Under the assumption that the statistics of the synaptic input is the same for a population of similarly behaving neurons (mean field approximation), it is possible to greatly simplify the study of neural circuits, both in the case in which the statistics of the input are stationary (reviewed in La Camera et al. in Biol Cybern, 2008) and in the case in which they are time varying and unevenly distributed over the dendritic tree. Here, we review theoretical and experimental results on the single-neuron properties that are relevant for the dynamical collective behavior of a population of neurons. We focus on the response of integrate-and-fire neurons and real cortical neurons to long-lasting, noisy, in vivo-like stationary inputs and show how the theory can predict the observed rhythmic activity of cultures of neurons. We then show how cortical neurons adapt on multiple time scales in response to input with stationary statistics in vitro. Next, we review how it is possible to study the general response properties of a neural circuit to time-varying inputs by estimating the response of single neurons to noisy sinusoidal currents. Finally, we address the dendrite-soma interactions in cortical neurons leading to gain modulation and spike bursts, and show how these effects can be captured by a two-compartment integrate-and-fire neuron. Most of the experimental results reviewed in this article have been successfully reproduced by simple integrate-and-fire model neurons.

show abstract

“…Our results point to a surprising dependence of the effect of recurrent inhibition by Martinotti cells on their oscillatory synchronization, which may control not only the local circuit activity, but also how it is transmitted to and decoded by downstream circuits. resonance; beta oscillation; NMDA receptor; I h NEOCORTICAL LAYER 5 PYRAMIDAL neurons are characterized by extensively branched apical tuft dendrites in cortical layer 1, which are known to receive top-down and feedback inputs from cortical and thalamic regions (Cauller 1995;Larkum et al 2009;Oda et al 2004; Thomson and Bannister 2003). Besides these excitatory inputs, recent studies (Kapfer et al 2007;Murayama et al 2009;Silberberg and Markram 2007) Whittington and Traub 2003).…”

mentioning

confidence: 99%

“…NEOCORTICAL LAYER 5 PYRAMIDAL neurons are characterized by extensively branched apical tuft dendrites in cortical layer 1, which are known to receive top-down and feedback inputs from cortical and thalamic regions (Cauller 1995;Larkum et al 2009;Oda et al 2004;Thomson and Bannister 2003). Besides these excitatory inputs, recent studies (Kapfer et al 2007;Murayama et al 2009;Silberberg and Markram 2007) have shown that the distal apical dendrites of pyramidal cells also receive prominent recurrent inhibitory inputs from a particular class of GABAergic interneurons, namely, somatostatin-positive, low-threshold spiking (LTS) Martinotti cells which preferentially synapse on these distal dendrites (Ascoli et al 2008;Kawaguchi and Kubota 1997;Thomson et al 1995;Wang et al 2004).…”

mentioning

confidence: 99%

Control of layer 5 pyramidal cell spiking by oscillatory inhibition in the distal apical dendrites: a computational modeling study

Morita

Robinson

et al. 2013

Journal of Neurophysiology

View full text Add to dashboard Cite

Li X, Morita K, Robinson HP, Small M. Control of layer 5 pyramidal cell spiking by oscillatory inhibition in the distal apical dendrites: a computational modeling study. J Neurophysiol 109: 2739-2756, 2013. First published March 13, 2013 doi:10.1152/jn.00397.2012.-The distal apical dendrites of layer 5 pyramidal neurons receive cortico-cortical and thalamocortical top-down and feedback inputs, as well as local recurrent inputs. A prominent source of recurrent inhibition in the neocortical circuit is somatostatin-positive Martinotti cells, which preferentially target distal apical dendrites of pyramidal cells. These electrically coupled cells can fire synchronously at various frequencies, including over a relatively slow range (5ϳ30 Hz), thereby imposing oscillatory inhibition on the pyramidal apical tuft dendrites. We examined how such distal oscillatory inhibition influences the firing of a biophysically detailed layer 5 pyramidal neuron model, which reproduced the spatiotemporal properties of sodium, calcium, and N-methyl-D-aspartate receptor spikes found experimentally. We found that oscillatory synchronization strongly influences the impact of distal inhibition on the pyramidal cell firing. Whereas asynchronous inhibition largely cancels out the facilitatory effects of distal excitatory inputs, inhibition oscillating synchronously at around 10ϳ20 Hz allows distal excitation to drive axosomatic firing, as if distal inhibition were absent. Underlying this is a switch from relatively infrequent burst firing to single spike firing at every period of the inhibitory oscillation. This phenomenon depends on hyperpolarization-activated cation current-dependent membrane potential resonance in the dendrite, but also, in a novel manner, on a cooperative amplification of this resonance by N-methyl-D-aspartate-receptor-driven dendritic action potentials. Our results point to a surprising dependence of the effect of recurrent inhibition by Martinotti cells on their oscillatory synchronization, which may control not only the local circuit activity, but also how it is transmitted to and decoded by downstream circuits. resonance; beta oscillation; NMDA receptor; I h NEOCORTICAL LAYER 5 PYRAMIDAL neurons are characterized by extensively branched apical tuft dendrites in cortical layer 1, which are known to receive top-down and feedback inputs from cortical and thalamic regions (Cauller 1995;Larkum et al. 2009;Oda et al. 2004; Thomson and Bannister 2003). Besides these excitatory inputs, recent studies (Kapfer et al. 2007;Murayama et al. 2009;Silberberg and Markram 2007) Whittington and Traub 2003). Cholinergic agonists induce beta oscillations in superficial layers of prefrontal cortical slices, which are independent of rhythms in the deeper layers (van Aerde et al. 2009). It is, therefore, quite likely that LTS cell-mediated recurrent inhibition onto the pyramidal apical tuft dendrites is modulated at frequencies in the -to ␤-range in certain conditions in vivo. To understand the operation of recurrent inhibition in the neoco...

show abstract

Thalamocortical projection from the ventral posteromedial nucleus sends its collaterals to layer I of the primary somatosensory cortex in rat

Cited by 34 publications

References 17 publications

Synaptic and cellular organization of layer 1 of the developing rat somatosensory cortex

Synaptic and cellular organization of layer 1 of the developing rat somatosensory cortex

The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs

Control of layer 5 pyramidal cell spiking by oscillatory inhibition in the distal apical dendrites: a computational modeling study

Contact Info

Product

Resources

About