scholarly journals Influence of spiking activity on cortical local field potentials

2013 ◽  
Vol 591 (21) ◽  
pp. 5291-5303 ◽  
Author(s):  
Stephan Waldert ◽  
Roger N. Lemon ◽  
Alexander Kraskov
eNeuro ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. ENEURO.0178-19.2019 ◽  
Author(s):  
Junmo An ◽  
Taruna Yadav ◽  
John P. Hessburg ◽  
Joseph T. Francis

2019 ◽  
Author(s):  
Lorena Casado-Román ◽  
Guillermo V. Carbajal ◽  
David Pérez-González ◽  
Manuel S. Malmierca

AbstractThe mismatch negativity (MMN) is a key biomarker of automatic deviance detection thought to emerge from two cortical sources. First, the auditory cortex (AC) encodes spectral regularities and reports frequency-specific deviances. Then, more abstract representations in the prefrontal cortex (PFC) allow to detect contextual changes of potential behavioral relevance. However, the precise location and time asynchronies between neuronal correlates underlying this fronto-temporal network remain unclear and elusive. Our study presented auditory oddball paradigms along with ‘no-repetition’ controls to record mismatch responses in neuronal spiking activity and local field potentials at the rat medial PFC. Whereas mismatch responses in the auditory system are mainly induced by stimulus-dependent effects, we found that auditory responsiveness in the PFC was driven by unpredictability, yielding context-dependent, comparatively delayed, more robust and longer-lasting mismatch responses mostly comprised of prediction error signaling activity. This characteristically different composition discarded that mismatch responses in the PFC could be simply inherited or amplified downstream from the auditory system. Conversely, it is more plausible for the PFC to exert top-down influences on the AC, since the PFC exhibited flexible and potent predictive processing, capable of suppressing redundant input more efficiently than the AC. Remarkably, the time course of the mismatch responses we observed in the spiking activity and local field potentials of the AC and the PFC combined coincided with the time course of the large-scale MMN-like signals reported in the rat brain, thereby linking the microscopic, mesoscopic and macroscopic levels of automatic deviance detection.


2020 ◽  
Vol 32 (10) ◽  
pp. 2024-2035 ◽  
Author(s):  
Mikael Lundqvist ◽  
André M. Bastos ◽  
Earl K. Miller

Theta (2–8 Hz), alpha (8–12 Hz), beta (12–35 Hz), and gamma (>35 Hz) rhythms are ubiquitous in the cortex. However, there is little understanding of whether they have similar properties and functions in different cortical areas because they have rarely been compared across them. We record neuronal spikes and local field potentials simultaneously at several levels of the cortical hierarchy in monkeys. Theta, alpha, beta, and gamma oscillations had similar relationships to spiking activity in visual, parietal, and prefrontal cortices. However, the frequencies in all bands increased up the cortical hierarchy. These results suggest that these rhythms have similar inhibitory and excitatory functions across the cortex. We discuss how the increase in frequencies up the cortical hierarchy may help sculpt cortical flow and processing.


2013 ◽  
Vol 25 (1) ◽  
pp. 157-185 ◽  
Author(s):  
Jung Hoon Lee ◽  
Joji Tsunada ◽  
Yale E. Cohen

Local field potentials (LFPs) and spiking activity reflect different types of information procssing. For example, neurophysiological studies indicate that signal novelty in the ventrolateral prefrontal cortex is differentially represented by LFPs and spiking activity: LFPs habituate to repeated stimulus presentations, whereas spiking activity does not. The neural mechanisms that allow for this differential representation between LFPs and spiking activity are not clear. Here, we model and simulate LFPs and spiking activity of neurons in the ventrolateral prefrontal cortex in order to elucidate potential mechanisms underlying this differential representation. We demonstrate that dynamic negative-feedback loops cause LFPs to habituate in response to repeated presentations of the same stimulus while spiking activity is maintained. This disassociation between LFPs and spiking activity may be a mechanism by which LFPs code stimulus novelty, whereas spiking activity carries abstract information, such as category membership and decision-related activity.


PLoS Biology ◽  
2020 ◽  
Vol 18 (12) ◽  
pp. e3001019
Author(s):  
Lorena Casado-Román ◽  
Guillermo V. Carbajal ◽  
David Pérez-González ◽  
Manuel S. Malmierca

The mismatch negativity (MMN) is a key biomarker of automatic deviance detection thought to emerge from 2 cortical sources. First, the auditory cortex (AC) encodes spectral regularities and reports frequency-specific deviances. Then, more abstract representations in the prefrontal cortex (PFC) allow to detect contextual changes of potential behavioral relevance. However, the precise location and time asynchronies between neuronal correlates underlying this frontotemporal network remain unclear and elusive. Our study presented auditory oddball paradigms along with “no-repetition” controls to record mismatch responses in neuronal spiking activity and local field potentials at the rat medial PFC. Whereas mismatch responses in the auditory system are mainly induced by stimulus-dependent effects, we found that auditory responsiveness in the PFC was driven by unpredictability, yielding context-dependent, comparatively delayed, more robust and longer-lasting mismatch responses mostly comprised of prediction error signaling activity. This characteristically different composition discarded that mismatch responses in the PFC could be simply inherited or amplified downstream from the auditory system. Conversely, it is more plausible for the PFC to exert top-down influences on the AC, since the PFC exhibited flexible and potent predictive processing, capable of suppressing redundant input more efficiently than the AC. Remarkably, the time course of the mismatch responses we observed in the spiking activity and local field potentials of the AC and the PFC combined coincided with the time course of the large-scale MMN-like signals reported in the rat brain, thereby linking the microscopic, mesoscopic, and macroscopic levels of automatic deviance detection.


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