ArticleJournal of neural engineering2013
System identification of the nonlinear dynamics in the thalamocortical circuit in response to patterned thalamic microstimulation in vivo.
Article in Journal of neural engineering, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 32 citations in OpenAlex.
- Brain-computer interfaces for neuropsychiatric disorders.Nature reviews bioengineering · 2024Article
- Optimization of Temporal Coding of Tactile Information in Rat Thalamus by Locus Coeruleus Activation.Biology · 2024Article
- Nonlinear dynamical modeling of neural activity using volterra series with GA-enhanced particle swarm optimization algorithm.Cognitive neurodynamics · 2023Article
- Review
- Modeling multiscale causal interactions between spiking and field potential signals during behavior.Journal of neural engineering · 2022Article
- Rapid Effects of Vagus Nerve Stimulation on Sensory Processing Through Activation of Neuromodulatory Systems.Frontiers in neuroscience · 2022Review
- Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation.Nature biomedical engineering · 2021Article
- Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior.Nature communications · 2021Article
- Rapid and transient enhancement of thalamic information transmission induced by vagus nerve stimulation.Journal of neural engineering · 2020Article
- Pupil-linked arousal modulates behavior in rats performing a whisker deflection direction discrimination task.Journal of neurophysiology · 2018Article
- Genetically expressed voltage sensor ArcLight for imaging large scale cortical activity in the anesthetized and awake mouse.Neurophotonics · 2017Article
- Combined Effects of Feedforward Inhibition and Excitation in Thalamocortical Circuit on the Transitions of Epileptic Seizures.Frontiers in computational neuroscience · 2017Article
- Thalamic state control of cortical paired-pulse dynamics.Journal of neurophysiology · 2017Article
- Response reliability observed with voltage-sensitive dye imaging of cortical layer 2/3: the probability of activation hypothesis.Journal of neurophysiology · 2016Article
- Abnormal Population Responses in the Somatosensory Cortex of Alzheimer's Disease Model Mice.Scientific reports · 2016Article
- Electrical and Optical Activation of Mesoscale Neural Circuits with Implications for Coding.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015Article
- Optogenetic feedback control of neural activity.eLife · 2015Article
- Adaptive shaping of cortical response selectivity in the vibrissa pathway.Journal of neurophysiology · 2015Article
- Sensory percepts induced by microwire array and DBS microstimulation in human sensory thalamus.Brain stimulationArticle
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
objectiveNonlinear system identification approaches were used to develop a dynamical model of the network level response to patterns of microstimulation in vivo. APPROACH: The thalamocortical circuit of the rodent vibrissa pathway was the model system, with voltage sensitive dye imaging capturing the cortical response to patterns of stimulation delivered from a single electrode in the ventral posteromedial thalamus. The results of simple paired stimulus experiments formed the basis for the development of a phenomenological model explicitly containing nonlinear elements observed experimentally. The phenomenological model was fit using datasets obtained with impulse train inputs, Poisson-distributed in time and uniformly varying in amplitude. MAIN
resultsThe phenomenological model explained 58% of the variance in the cortical response to out of sample patterns of thalamic microstimulation. Furthermore, while fit on trial-averaged data, the phenomenological model reproduced single trial response properties when simulated with noise added into the system during stimulus presentation. The simulations indicate that the single trial response properties were dependent on the relative sensitivity of the static nonlinearities in the two stages of the model, and ultimately suggest that electrical stimulation activates local circuitry through linear recruitment, but that this activity propagates in a highly nonlinear fashion to downstream targets. SIGNIFICANCE: The development of nonlinear dynamical models of neural circuitry will guide information delivery for sensory prosthesis applications, and more generally reveal properties of population coding within neural circuits.
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