scholarly journals Target Interneuron Preference in Thalamocortical Pathways Determines the Temporal Structure of Cortical Responses

2018 ◽  
Vol 29 (7) ◽  
pp. 2815-2831 ◽  
Author(s):  
Y Audrey Hay ◽  
Jérémie Naudé ◽  
Philippe Faure ◽  
Bertrand Lambolez
Keyword(s):  
Temporal Structure ◽  
Sensory Information ◽  
Response Duration ◽  
Cortical Response ◽  
Inhibitory Neurons ◽  
Thalamic Nuclei ◽  
Response Dynamics ◽  
Mean Field Model ◽  
Local Circuits ◽  
Feedforward Inhibition

Abstract Sensory processing relies on fast detection of changes in environment, as well as integration of contextual cues over time. The mechanisms by which local circuits of the cerebral cortex simultaneously perform these opposite processes remain obscure. Thalamic “specific” nuclei relay sensory information, whereas “nonspecific” nuclei convey information on the environmental and behavioral contexts. We expressed channelrhodopsin in the ventrobasal specific (sensory) or the rhomboid nonspecific (contextual) thalamic nuclei. By selectively activating each thalamic pathway, we found that nonspecific inputs powerfully activate adapting (slow-responding) interneurons but weakly connect fast-spiking interneurons, whereas specific inputs exhibit opposite interneuron preference. Specific inputs thereby induce rapid feedforward inhibition that limits response duration, whereas, in the same cortical area, nonspecific inputs elicit delayed feedforward inhibition that enables lasting recurrent excitation. Using a mean field model, we confirm that cortical response dynamics depends on the type of interneuron targeted by thalamocortical inputs and show that efficient recruitment of adapting interneurons prolongs the cortical response and allows the summation of sensory and contextual inputs. Hence, target choice between slow- and fast-responding inhibitory neurons endows cortical networks with a simple computational solution to perform both sensory detection and integration.

scholarly journals Role of intraglomerular circuits in shaping temporally structured responses to naturalistic inhalation-driven sensory input to the olfactory bulb

2015 ◽  
Vol 113 (9) ◽  
pp. 3112-3129 ◽  
Author(s):  
Ryan M. Carey ◽  
William Erik Sherwood ◽  
Michael T. Shipley ◽  
Alla Borisyuk ◽  
Matt Wachowiak
Keyword(s):  
Olfactory Bulb ◽  
Sensory Neuron ◽  
Temporal Structure ◽  
Decay Kinetics ◽  
Response Dynamics ◽  
Output Neurons ◽  
Tufted Cells ◽  
Slow Onset ◽  
Feedforward Inhibition

Olfaction in mammals is a dynamic process driven by the inhalation of air through the nasal cavity. Inhalation determines the temporal structure of sensory neuron responses and shapes the neural dynamics underlying central olfactory processing. Inhalation-linked bursts of activity among olfactory bulb (OB) output neurons [mitral/tufted cells (MCs)] are temporally transformed relative to those of sensory neurons. We investigated how OB circuits shape inhalation-driven dynamics in MCs using a modeling approach that was highly constrained by experimental results. First, we constructed models of canonical OB circuits that included mono- and disynaptic feedforward excitation, recurrent inhibition and feedforward inhibition of the MC. We then used experimental data to drive inputs to the models and to tune parameters; inputs were derived from sensory neuron responses during natural odorant sampling (sniffing) in awake rats, and model output was compared with recordings of MC responses to odorants sampled with the same sniff waveforms. This approach allowed us to identify OB circuit features underlying the temporal transformation of sensory inputs into inhalation-linked patterns of MC spike output. We found that realistic input-output transformations can be achieved independently by multiple circuits, including feedforward inhibition with slow onset and decay kinetics and parallel feedforward MC excitation mediated by external tufted cells. We also found that recurrent and feedforward inhibition had differential impacts on MC firing rates and on inhalation-linked response dynamics. These results highlight the importance of investigating neural circuits in a naturalistic context and provide a framework for further explorations of signal processing by OB networks.

scholarly journals Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
B Semihcan Sermet ◽  
Pavel Truschow ◽  
Michael Feyerabend ◽  
Johannes M Mayrhofer ◽  
Tess B Oram ◽  
...  
Keyword(s):  
Thalamic Nucleus ◽  
Barrel Cortex ◽  
Sensory Information ◽  
Cell Types ◽  
Excitatory Input ◽  
Higher Order ◽  
Inhibitory Neurons ◽  
Thalamic Nuclei ◽  
Thalamic Input ◽  
Layer 4

Mouse primary somatosensory barrel cortex (wS1) processes whisker sensory information, receiving input from two distinct thalamic nuclei. The first-order ventral posterior medial (VPM) somatosensory thalamic nucleus most densely innervates layer 4 (L4) barrels, whereas the higher-order posterior thalamic nucleus (medial part, POm) most densely innervates L1 and L5A. We optogenetically stimulated VPM or POm axons, and recorded evoked excitatory postsynaptic potentials (EPSPs) in different cell-types across cortical layers in wS1. We found that excitatory neurons and parvalbumin-expressing inhibitory neurons received the largest EPSPs, dominated by VPM input to L4 and POm input to L5A. In contrast, somatostatin-expressing inhibitory neurons received very little input from either pathway in any layer. Vasoactive intestinal peptide-expressing inhibitory neurons received an intermediate level of excitatory input with less apparent layer-specificity. Our data help understand how wS1 neocortical microcircuits might process and integrate sensory and higher-order inputs.

scholarly journals Modulation of tactile feedback for the execution of dexterous movement

2021 ◽  
Author(s):  
James M Conner ◽  
Andrew Bohannon ◽  
Masakazu Igarashi ◽  
James Taniguchi ◽  
Nicholas Baltar ◽  
...  
Keyword(s):  
Cortical Neurons ◽  
Molecular Genetic ◽  
Sensory Information ◽  
Tactile Feedback ◽  
Inhibitory Neurons ◽  
Tactile Information ◽  
Inhibitory Circuits ◽  
Complementary Pattern ◽  
Local Circuits ◽  
The Brain

While dexterity relies on the constant transmission of sensory information, unchecked feedback can be disruptive to behavior. Yet how somatosensory feedback from the hands is regulated as it first enters the brain, and whether this modulation exerts any influence on movement, remain unclear. Leveraging molecular-genetic access in mice, we find that tactile afferents from the hand recruit neurons in the brainstem cuneate nucleus whose activity is modulated by distinct classes of local inhibitory neurons. Selective manipulation of these inhibitory circuits can suppress or enhance the transmission of tactile information, affecting behaviors that rely on movement of the hands. Investigating whether these local circuits are subject to top-down control, we identify distinct descending cortical pathways that innervate cuneate in a complementary pattern. Somatosensory cortical neurons target the core tactile region of cuneate, while a large rostral cortical population drives feed-forward inhibition of tactile transmission through an inhibitory shell. These findings identify a circuit basis for tactile feedback modulation, enabling the effective execution of dexterous movement.

Neuromuscular Control of Movement

2018 ◽  
Keyword(s):  
Nervous System ◽  
Sensory Information ◽  
Neuromuscular Control ◽  
Complex Environments ◽  
Locomotor Rhythm ◽  
Motor Responses ◽  
Reflex Pathways ◽  
Local Reflex ◽  
Local Circuits ◽  
And Control

The control of movement is essential for animals traversing complex environments and operating across a range of speeds and gaits. We consider how animals process sensory information and initiate motor responses, primarily focusing on simple motor responses that involve local reflex pathways of feedback and control, rather than the more complex, longer-term responses that require the broader integration of higher centers within the nervous system. We explore how local circuits facilitate decentralized coordination of locomotor rhythm and examine the fundamentals of sensory receptors located in the muscles, tendons, joints, and at the animal’s body surface. These sensors monitor the animal’s physical environment and the action of its muscles. The sensory information is then carried back to the animal’s nervous system by afferent neurons, providing feedback that is integrated at the level of the spinal cord of vertebrates and sensory-motor ganglia of invertebrates.

scholarly journals High-fidelity transmission of high-frequency burst stimuli from peripheral nerve to thalamic nuclei in children with dystonia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Estefanía Hernandez-Martin ◽  
Enrique Arguelles ◽  
Yifei Zheng ◽  
Ruta Deshpande ◽  
Terence D. Sanger
Keyword(s):  
Deep Brain Stimulation ◽  
Peripheral Nerve ◽  
Brain Stimulation ◽  
High Frequency ◽  
Sensory Information ◽  
Brain Structures ◽  
High Fidelity ◽  
Thalamic Nuclei ◽  
Frequency Burst ◽  
Deep Brain

AbstractHigh-frequency peripheral nerve stimulation has emerged as a noninvasive alternative to thalamic deep brain stimulation for some patients with essential tremor. It is not known whether such techniques might be effective for movement disorders in children, nor is the mechanism and transmission of the peripheral stimuli to central brain structures understood. This study was designed to investigate the fidelity of transmission from peripheral nerves to thalamic nuclei in children with dystonia undergoing deep brain stimulation surgery. The ventralis intermediate (VIM) thalamus nuclei showed a robust evoked response to peripheral high-frequency burst stimulation, with a greatest response magnitude to intra-burst frequencies between 50 and 100 Hz, and reliable but smaller responses up to 170 Hz. The earliest response occurred at 12–15 ms following stimulation onset, suggesting rapid high-fidelity transmission between peripheral nerve and thalamic nuclei. A high-bandwidth, low-latency transmission path from peripheral nerve to VIM thalamus is consistent with the importance of rapid and accurate sensory information for the control of coordination and movement via the cerebello-thalamo-cortical pathway. Our results suggest the possibility of non-invasive modulation of thalamic activity in children with dystonia, and therefore the possibility that a subset of children could have beneficial clinical response without the need for invasive deep brain stimulation.

scholarly journals Differential connectivity and response dynamics of excitatory and inhibitory neurons in visual cortex

2011 ◽  
Vol 14 (8) ◽  
pp. 1045-1052 ◽  
Author(s):  
Sonja B Hofer ◽  
Ho Ko ◽  
Bruno Pichler ◽  
Joshua Vogelstein ◽  
Hana Ros ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Inhibitory Neurons ◽  
Response Dynamics ◽  
Differential Connectivity

Mechanisms for generating temporal filters in the electrosensory system

1999 ◽  
Vol 202 (10) ◽  
pp. 1281-1289 ◽  
Author(s):  
G.J. Rose ◽  
E.S. Fortune
Keyword(s):  
Nervous System ◽  
Discharge Rate ◽  
Temporal Structure ◽  
Sensory Information ◽  
Gain Control ◽  
Membrane Properties ◽  
Control Mechanisms ◽  
Temporal Features ◽  
Level Of Activity ◽  
The Central Nervous System

Temporal patterns of sensory information are important cues in behaviors ranging from spatial analyses to communication. Neural representations of the temporal structure of sensory signals include fluctuations in the discharge rate of neurons over time (peripheral nervous system) and the differential level of activity in neurons tuned to particular temporal features (temporal filters in the central nervous system). This paper presents our current understanding of the mechanisms responsible for the transformations between these representations in electric fish of the genus Eigenmannia. The roles of passive and active membrane properties of neurons, and frequency-dependent gain-control mechanisms are discussed.

Neuronal Circuits in Barrel Cortex for Whisker Sensory Perception

2021 ◽  
Vol 101 (1) ◽  
pp. 353-415
Author(s):  
Jochen F. Staiger ◽  
Carl C. H. Petersen
Keyword(s):  
Barrel Cortex ◽  
Specific Activity ◽  
Sensory Information ◽  
Inhibitory Neurons ◽  
Future Research ◽  
Cell Type ◽  
Molecular Features ◽  
Somatotopic Map ◽  
Cell Type Specific ◽  
The Impact

The array of whiskers on the snout provides rodents with tactile sensory information relating to the size, shape and texture of objects in their immediate environment. Rodents can use their whiskers to detect stimuli, distinguish textures, locate objects and navigate. Important aspects of whisker sensation are thought to result from neuronal computations in the whisker somatosensory cortex (wS1). Each whisker is individually represented in the somatotopic map of wS1 by an anatomical unit named a ‘barrel’ (hence also called barrel cortex). This allows precise investigation of sensory processing in the context of a well-defined map. Here, we first review the signaling pathways from the whiskers to wS1, and then discuss current understanding of the various types of excitatory and inhibitory neurons present within wS1. Different classes of cells can be defined according to anatomical, electrophysiological and molecular features. The synaptic connectivity of neurons within local wS1 microcircuits, as well as their long-range interactions and the impact of neuromodulators, are beginning to be understood. Recent technological progress has allowed cell-type-specific connectivity to be related to cell-type-specific activity during whisker-related behaviors. An important goal for future research is to obtain a causal and mechanistic understanding of how selected aspects of tactile sensory information are processed by specific types of neurons in the synaptically connected neuronal networks of wS1 and signaled to downstream brain areas, thus contributing to sensory-guided decision-making.

scholarly journals Involvement of NMDA receptors containing the GluN2C subunit in the psychotomimetic and antidepressant-like effects of ketamine

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mireia Tarrés-Gatius ◽  
Lluís Miquel-Rio ◽  
Leticia Campa ◽  
Francesc Artigas ◽  
Anna Castañé
Keyword(s):  
Motor Coordination ◽  
Sensory Information ◽  
Wild Type ◽  
Thalamic Nuclei ◽  
Treatment Resistant ◽  
Cortical Networks ◽  
Male And Female ◽  
Female Mice ◽  
Antidepressant Effects ◽  
The Brain

AbstractAcute ketamine administration evokes rapid and sustained antidepressant effects in treatment-resistant patients. However, ketamine also produces transient perceptual disturbances similarly to those evoked by other non-competitive NMDA-R antagonists like phencyclidine (PCP). Although the brain networks involved in both ketamine actions are not fully understood, PCP and ketamine activate thalamo-cortical networks after NMDA-R blockade in GABAergic neurons of the reticular thalamic nucleus (RtN). Given the involvement of thalamo-cortical networks in processing sensory information, these networks may underlie psychotomimetic action. Since the GluN2C subunit is densely expressed in the thalamus, including the RtN, we examined the dependence of psychotomimetic and antidepressant-like actions of ketamine on the presence of GluN2C subunits, using wild-type and GluN2C knockout (GluN2CKO) mice. Likewise, since few studies have investigated ketamine’s effects in females, we used mice of both sexes. GluN2C deletion dramatically reduced stereotyped (circling) behavior induced by ketamine in male and female mice, while the antidepressant-like effect was fully preserved in both genotypes and sexes. Despite ketamine appeared to induce similar effects in both sexes, some neurobiological differences were observed between male and female mice regarding c-fos expression in thalamic nuclei and cerebellum, and glutamate surge in prefrontal cortex. In conclusion, the GluN2C subunit may discriminate between antidepressant-like and psychotomimetic actions of ketamine. Further, the abundant presence of GluN2C subunits in the cerebellum and the improved motor coordination of GluN2CKO mice after ketamine treatment suggest the involvement of cerebellar NMDA-Rs in some behavioral actions of ketamine.

scholarly journals A robust model of Stimulus-Specific Adaptation validated on neuromorphic hardware

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Natacha Vanattou-Saïfoudine ◽  
Chao Han ◽  
Renate Krause ◽  
Eleni Vasilaki ◽  
Wolfger von der Behrens ◽  
...  
Keyword(s):  
Novelty Detection ◽  
Mean Field ◽  
Sensory Information ◽  
Neuronal Firing ◽  
Equivalent Model ◽  
Mean Field Model ◽  
Neuromorphic Circuits ◽  
Complete Control ◽  
Specific Adaptation ◽  
Neuromorphic Hardware

AbstractStimulus-Specific Adaptation (SSA) to repetitive stimulation is a phenomenon that has been observed across many different species and in several brain sensory areas. It has been proposed as a computational mechanism, responsible for separating behaviorally relevant information from the continuous stream of sensory information. Although SSA can be induced and measured reliably in a wide variety of conditions, the network details and intracellular mechanisms giving rise to SSA still remain unclear. Recent computational studies proposed that SSA could be associated with a fast and synchronous neuronal firing phenomenon called Population Spikes (PS). Here, we test this hypothesis using a mean-field rate model and corroborate it using a neuromorphic hardware. As the neuromorphic circuits used in this study operate in real-time with biologically realistic time constants, they can reproduce the same dynamics observed in biological systems, together with the exploration of different connectivity schemes, with complete control of the system parameter settings. Besides, the hardware permits the iteration of multiple experiments over many trials, for extended amounts of time and without losing the networks and individual neural processes being studied. Following this “neuromorphic engineering” approach, we therefore study the PS hypothesis in a biophysically inspired recurrent networks of spiking neurons and evaluate the role of different linear and non-linear dynamic computational primitives such as spike-frequency adaptation or short-term depression (STD). We compare both the theoretical mean-field model of SSA and PS to previously obtained experimental results in the area of novelty detection and observe its behavior on its neuromorphic physical equivalent model. We show how the approach proposed can be extended to other computational neuroscience modelling efforts for understanding high-level phenomena in mechanistic models.

Sign in / Sign up

Export Citation Format

Share Document