2022
DOI: 10.1101/2022.12.21.521407
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Laminar Neural Dynamics of Auditory Evoked Responses: Computational Modeling of Local Field Potentials in Auditory Cortex of Non-Human Primates

Abstract: Evoked neural responses to sensory stimuli have been extensively investigated in humans and animal models both to enhance our understanding of brain function and to aid in clinical diagnosis of neurological and neuropsychiatric conditions. Recording and imaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), local field potentials (LFPs), and calcium imaging provide complementary information about different aspects of brain activity at different spatial and temporal scales. Model… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 106 publications
(133 reference statements)
0
1
0
Order By: Relevance
“… Harrison et al (2020) presented a variable-order Markov model which can learn higher-order statistics that change over time and which can consider memory constraints in detecting recurring tonal patterns. Unlike the present Markovian perspective, some computational theories take into account the neuroanatomical underpinnings of predictive models ( Friston, 2005 ; Kiebel et al, 2009 ; Wacongne et al, 2012 ; Maheu et al, 2019 ; Tabas, 2021 ; Chien et al, 2022 ). In a very recent computational approach tailored to model predictability of sound sequences, Chien et al (2020) the simulated signals for predictable and unpredictable sound sequences resembled the observed MEG amplitude traces from a study by Barascud et al (2016) .…”
Section: Distinction From Previous Markovian Approaches To Mmn (And R...mentioning
confidence: 99%
“… Harrison et al (2020) presented a variable-order Markov model which can learn higher-order statistics that change over time and which can consider memory constraints in detecting recurring tonal patterns. Unlike the present Markovian perspective, some computational theories take into account the neuroanatomical underpinnings of predictive models ( Friston, 2005 ; Kiebel et al, 2009 ; Wacongne et al, 2012 ; Maheu et al, 2019 ; Tabas, 2021 ; Chien et al, 2022 ). In a very recent computational approach tailored to model predictability of sound sequences, Chien et al (2020) the simulated signals for predictable and unpredictable sound sequences resembled the observed MEG amplitude traces from a study by Barascud et al (2016) .…”
Section: Distinction From Previous Markovian Approaches To Mmn (And R...mentioning
confidence: 99%