Cortical oscillations and temporal interactions in a computer simulation of piriform cortex

1992 ◽  
Vol 67 (4) ◽  
pp. 981-995 ◽  
Author(s):  
M. Wilson ◽  
J. M. Bower
Keyword(s):  
Large Scale ◽  
Activity Patterns ◽  
Piriform Cortex ◽  
Afferent Fiber ◽  
Field Potential ◽  
Afferent Input ◽  
Fiber System ◽  
Eeg Activity ◽  
Electrical Shocks ◽  
40 Hz

1. A large-scale computer model of the piriform cortex was constructed on the basis of the known anatomic and physiological organization of this region. 2. The oscillatory field potential and electroencephalographic (EEG) activity generated by the model was compared with actual physiological results. The model was able to produce patterns of activity similar to those recorded physiologically in response to both weak and strong electrical shocks to the afferent input. The model also generated activity patterns similar to EEGs recorded in behaving animals. 3. In addition to replicating known physiological responses, it has been possible to use the simulations to explore the interactions of network components that might underlie these responses. This analysis suggests that the physiological properties of the cortex are dependent on the complex interaction of both network and cellular properties. In particular, we have found that the relationship between conduction velocities in intrinsic cortical fiber systems and the time constants of excitatory and inhibitory effects are critical for replicating physiological results. 4. Analysis of the model also suggests a correspondence between the 40-Hz oscillatory patterns of activity induced by low levels of odor-like stimulation and oscillatory patterns seen in lightly anesthetized cortex in response to weak electrical shocks to the afferent fiber system. 5. The specific relationships we have found between the different components of the model also support several speculations on their functional significance. The simulations suggest that during each 40-Hz cycle of EEG activity there is a convergence in rostral cortex of afferent information from the olfactory bulb and recurrent association fiber information from caudal cortex. This convergence could underlie an iterative process central to the recognition of complex olfactory stimuli.

scholarly journals Revealing Spatiotemporal Circuit Information of Olfactory Bulb in Large-scale Neural Recordings

2021 ◽  
Author(s):  
Xin Hu ◽  
Shahrukh Khanzada ◽  
Diana Klütsch ◽  
Federico Calegari ◽  
Hayder Amin
Keyword(s):  
Olfactory Bulb ◽  
Large Scale ◽  
Ex Vivo ◽  
Activity Patterns ◽  
Field Potential ◽  
Multidimensional Analysis ◽  
Label Free ◽  
Drug Induced ◽  
Neural Recordings ◽  
Neuronal Coding

ABSTRACTLarge-scale multi-site biosensors are essential to probe the olfactory bulb (OB) circuitry for understanding the spatiotemporal dynamics of simultaneous discharge patterns. Current ex-vivo electrophysiological techniques are limited to recording a small set of neurons and cannot provide an inadequate resolution, which hinders revealing the fast dynamic underlying the information coding mechanisms in the OB circuit. Here, we demonstrate a novel biohybrid OB-CMOS platform to decipher the cross-scale dynamics of OB electrogenesis and quantify the distinct neuronal coding properties. The approach with 4096-microelectrodes offers a non-invasive, label-free, bioelectrical imaging to decode simultaneous firing patterns from thousands of connected neuronal ensembles in acute OB slices. The platform can measure spontaneous and drug-induced extracellular field potential activity. We employ our OB-CMOS recordings to perform multidimensional analysis to instantiate specific neurophysiological metrics underlying the olfactory spatiotemporal coding that emerged from the OB interconnected layers. Our results delineate the computational implications of large-scale activity patterns in functional olfactory processing. The high-content characterization of the olfactory circuit could benefit better functional interrogations of the olfactory spatiotemporal coding, connectivity mapping, and, further, the designing of reliable and advanced olfactory cell-based biosensors for diagnostic biomarkers and drug discovery.

scholarly journals Dynamics of neural microstates in the VTA-striatal-prefrontal loop during novelty exploration in the rat

2020 ◽  
Author(s):  
A. Mishra ◽  
N. Marzban ◽  
M. X Cohen ◽  
B. Englitz
Keyword(s):  
Spatial Patterns ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Activity Patterns ◽  
Field Potential ◽  
Brain Regions ◽  
Brain Areas ◽  
Neural Recordings ◽  
Temporal Correlations

AbstractEEG microstates refer to quasi-stable spatial patterns of scalp potentials, and their dynamics have been linked to cognitive and behavioral states. Neural activity at single and multiunit levels also exhibit spatiotemporal coordination, but this spatial scale is difficult to relate to EEG. Here, we translated EEG microstate analysis to triple-area local field potential (LFP) recordings from up to 192 electrodes in rats to investigate the mesoscopic dynamics of neural microstates within and across brain regions.We performed simultaneous recordings from the prefrontal cortex (PFC), striatum (STR), and ventral tegmental area (VTA) during awake behavior (object novelty and exploration). We found that the LFP data can be accounted for by multiple, recurring, quasi-stable spatial activity patterns with an average period of stability of ~60-100 ms. The top four maps accounted for 60-80% of the total variance, compared to ~25% for shuffled data. Cross-correlation of the microstate time-series across brain regions revealed rhythmic patterns of microstate activations, which we interpret as a novel indicator of inter-regional, mesoscale synchronization. Furthermore, microstate features, and patterns of temporal correlations across microstates, were modulated by behavioural states such as movement and novel object exploration. These results support the existence of a functional mesoscopic organization across multiple brain areas, and open up the opportunity to investigate their relation to EEG microstates, of particular interest to the human research community.Significance StatementThe coordination of neural activity across the entire brain has remained elusive. Here we combine large-scale neural recordings at fine spatial resolution with the analysis of microstates, i.e. short-lived, recurring spatial patterns of neural activity. We demonstrate that the local activity in different brain areas can be accounted for by only a few microstates per region. These microstates exhibited temporal dynamics that were correlated across regions in rhythmic patterns. We demonstrate that these microstates are linked to behavior and exhibit different properties in the frequency domain during different behavioural states. In summary, LFP microstates provide an insightful approach to studying both mesoscopic and large-scale brain activation within and across regions.

The association of age and aerobic activity history with 40-Hz EEG activity during cognitive challenge

1996 ◽  
Author(s):  
B. Hatfield ◽  
D. Santa Maria ◽  
T. Spalding ◽  
C. Blanchard ◽  
A. Haufler ◽  
...  
Keyword(s):  
Eeg Activity ◽  
Aerobic Activity ◽  
Cognitive Challenge ◽  
40 Hz

scholarly journals Field Potential Signature of Distinct Multicellular Activity Patterns in the Mouse Hippocampus

2010 ◽  
Vol 30 (46) ◽  
pp. 15441-15449 ◽  
Author(s):  
S. Reichinnek ◽  
T. Kunsting ◽  
A. Draguhn ◽  
M. Both
Keyword(s):  
Activity Patterns ◽  
Field Potential ◽  
Mouse Hippocampus

scholarly journals Functional Brain Connectivity Revealed by Sparse Coding of Large-Scale Local Field Potential Dynamics

2018 ◽  
Vol 32 (2) ◽  
pp. 255-270 ◽  
Author(s):  
Han Wang ◽  
Kun Xie ◽  
Li Xie ◽  
Xiang Li ◽  
Meng Li ◽  
...  
Keyword(s):  
Local Field ◽  
Sparse Coding ◽  
Local Field Potential ◽  
Large Scale ◽  
Brain Connectivity ◽  
Field Potential ◽  
Functional Brain

scholarly journals Relationship between individual neuron and network spontaneous activity in developing mouse cortex

2014 ◽  
Vol 112 (12) ◽  
pp. 3033-3045 ◽  
Author(s):  
Heather M. Barnett ◽  
Julijana Gjorgjieva ◽  
Keiko Weir ◽  
Cara Comfort ◽  
Adrienne L. Fairhall ◽  
...  
Keyword(s):  
Normal Development ◽  
Activity Patterns ◽  
Piriform Cortex ◽  
Intrinsic Excitability ◽  
Intrinsic Activity ◽  
Dorsal Cortex ◽  
Synchronous Activity ◽  
Mouse Cortex ◽  
Propagating Waves ◽  
Autonomous Activity

Spontaneous synchronous activity (SSA) that propagates as electrical waves is found in numerous central nervous system structures and is critical for normal development, but the mechanisms of generation of such activity are not clear. In previous work, we showed that the ventrolateral piriform cortex is uniquely able to initiate SSA in contrast to the dorsal neocortex, which participates in, but does not initiate, SSA (Lischalk JW, Easton CR, Moody WJ. Dev Neurobiol 69: 407–414, 2009). In this study, we used Ca2+ imaging of cultured embryonic day 18 to postnatal day 2 coronal slices (embryonic day 17 + 1–4 days in culture) of the mouse cortex to investigate the different activity patterns of individual neurons in these regions. In the piriform cortex where SSA is initiated, a higher proportion of neurons was active asynchronously between waves, and a larger number of groups of coactive cells was present compared with the dorsal cortex. When we applied GABA and glutamate synaptic antagonists, asynchronous activity and cellular clusters remained, while synchronous activity was eliminated, indicating that asynchronous activity is a result of cell-intrinsic properties that differ between these regions. To test the hypothesis that higher levels of cell-autonomous activity in the piriform cortex underlie its ability to initiate waves, we constructed a conductance-based network model in which three layers differed only in the proportion of neurons able to intrinsically generate bursting behavior. Simulations using this model demonstrated that a gradient of intrinsic excitability was sufficient to produce directionally propagating waves that replicated key experimental features, indicating that the higher level of cell-intrinsic activity in the piriform cortex may provide a substrate for SSA generation.

scholarly journals Recurrent circuitry is required to stabilize piriform cortex odor representations across brain states

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Kevin A Bolding ◽  
Shivathmihai Nagappan ◽  
Bao-Xia Han ◽  
Fan Wang ◽  
Kevin M Franks
Keyword(s):  
Neural Activity ◽  
Neural Circuits ◽  
Activity Patterns ◽  
Piriform Cortex ◽  
Theoretical Studies ◽  
Pattern Completion ◽  
Attractor Networks ◽  
Attractor Dynamics ◽  
Brain States ◽  
Associative Function

Pattern completion, or the ability to retrieve stable neural activity patterns from noisy or partial cues, is a fundamental feature of memory. Theoretical studies indicate that recurrently connected auto-associative or discrete attractor networks can perform this process. Although pattern completion and attractor dynamics have been observed in various recurrent neural circuits, the role recurrent circuitry plays in implementing these processes remains unclear. In recordings from head-fixed mice, we found that odor responses in olfactory bulb degrade under ketamine/xylazine anesthesia while responses immediately downstream, in piriform cortex, remain robust. Recurrent connections are required to stabilize cortical odor representations across states. Moreover, piriform odor representations exhibit attractor dynamics, both within and across trials, and these are also abolished when recurrent circuitry is eliminated. Here, we present converging evidence that recurrently-connected piriform populations stabilize sensory representations in response to degraded inputs, consistent with an auto-associative function for piriform cortex supported by recurrent circuitry.

scholarly journals Representational drift in the mouse visual cortex

2020 ◽  
Author(s):  
Daniel Deitch ◽  
Alon Rubin ◽  
Yaniv Ziv
Keyword(s):  
Large Scale ◽  
Activity Patterns ◽  
Population Level ◽  
Population Activity ◽  
Cortical Areas ◽  
Electrophysiological Recordings ◽  
The Face ◽  
Visual Cortical ◽  
Mouse Visual Cortex ◽  
Over Time

AbstractNeuronal representations in the hippocampus and related structures gradually change over time despite no changes in the environment or behavior. The extent to which such ‘representational drift’ occurs in sensory cortical areas and whether the hierarchy of information flow across areas affects neural-code stability have remained elusive. Here, we address these questions by analyzing large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. We found representational drift over timescales spanning minutes to days across multiple visual areas. The drift was driven mostly by changes in individual cells’ activity rates, while their tuning changed to a lesser extent. Despite these changes, the structure of relationships between the population activity patterns remained stable and stereotypic, allowing robust maintenance of information over time. Such population-level organization may underlie stable visual perception in the face of continuous changes in neuronal responses.

Large-Scale 3D Baseline Measurement Based on Phase-Stabilized GNSS-over-Fiber System

2021 ◽  
pp. 1-1
Author(s):  
Xin Jiang ◽  
Xiangchuan Wang ◽  
Xi Liu ◽  
Lugang Wu ◽  
Chaosheng Huang ◽  
...  
Keyword(s):  
Large Scale ◽  
Baseline Measurement ◽  
Fiber System
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