Causal Role of Thalamic Interneurons in Brain State TransitionsCitation formats

  • Authors:
  • Basabdatta Sen Bhattacharya
  • Thomas P Bond
  • Louise O'Hare
  • Daniel Turner
  • Simon J Durrant

Standard

Causal Role of Thalamic Interneurons in Brain State Transitions : A Study Using a Neural Mass Model Implementing Synaptic Kinetics. / Bhattacharya, Basabdatta Sen; Bond, Thomas P; O'Hare, Louise; Turner, Daniel; Durrant, Simon J.

In: Frontiers in Computational Neuroscience, Vol. 10, 16.11.2016, p. 115.

Research output: Contribution to journalArticlepeer-review

Harvard

Bhattacharya, BS, Bond, TP, O'Hare, L, Turner, D & Durrant, SJ 2016, 'Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics', Frontiers in Computational Neuroscience, vol. 10, pp. 115. https://doi.org/10.3389/fncom.2016.00115

APA

Bhattacharya, B. S., Bond, T. P., O'Hare, L., Turner, D., & Durrant, S. J. (2016). Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics. Frontiers in Computational Neuroscience, 10, 115. https://doi.org/10.3389/fncom.2016.00115

Vancouver

Bhattacharya BS, Bond TP, O'Hare L, Turner D, Durrant SJ. Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics. Frontiers in Computational Neuroscience. 2016 Nov 16;10:115. https://doi.org/10.3389/fncom.2016.00115

Author

Bhattacharya, Basabdatta Sen ; Bond, Thomas P ; O'Hare, Louise ; Turner, Daniel ; Durrant, Simon J. / Causal Role of Thalamic Interneurons in Brain State Transitions : A Study Using a Neural Mass Model Implementing Synaptic Kinetics. In: Frontiers in Computational Neuroscience. 2016 ; Vol. 10. pp. 115.

Bibtex

@article{cda80a8ece574e8498bb89be5eaecc1d,
title = "Causal Role of Thalamic Interneurons in Brain State Transitions: A Study Using a Neural Mass Model Implementing Synaptic Kinetics",
abstract = "Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20-25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8-13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes.",
author = "Bhattacharya, {Basabdatta Sen} and Bond, {Thomas P} and Louise O'Hare and Daniel Turner and Durrant, {Simon J}",
year = "2016",
month = nov,
day = "16",
doi = "10.3389/fncom.2016.00115",
language = "English",
volume = "10",
pages = "115",
journal = "Frontiers in Computational Neuroscience",
issn = "1662-5188",
publisher = "Frontiers Media S. A.",

}

RIS

TY - JOUR

T1 - Causal Role of Thalamic Interneurons in Brain State Transitions

T2 - A Study Using a Neural Mass Model Implementing Synaptic Kinetics

AU - Bhattacharya, Basabdatta Sen

AU - Bond, Thomas P

AU - O'Hare, Louise

AU - Turner, Daniel

AU - Durrant, Simon J

PY - 2016/11/16

Y1 - 2016/11/16

N2 - Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20-25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8-13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes.

AB - Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20-25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8-13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes.

U2 - 10.3389/fncom.2016.00115

DO - 10.3389/fncom.2016.00115

M3 - Article

C2 - 27899890

VL - 10

SP - 115

JO - Frontiers in Computational Neuroscience

JF - Frontiers in Computational Neuroscience

SN - 1662-5188

ER -