scholarly journals Stereotyped large amplitude cortical LFP events can be clustered and reveal precisely ordered phase-locking in neuronal populations

2019 ◽  
Author(s):  
Catalin C. Mitelut ◽  
Martin A. Spacek ◽  
Allen W. Chan ◽  
Tim H. Murphy ◽  
Nicholas V. Swindale
Keyword(s):  
Visual Cortex ◽  
Barrel Cortex ◽  
Slow Wave Sleep ◽  
Current Source ◽  
Field Potential ◽  
State Transitions ◽  
Stimulus Processing ◽  
Cortical Areas ◽  
Up States ◽  
Firing Order

AbstractDuring quiet wakefulness, slow-wave sleep and anesthesia, mammalian cortex exhibits a synchronised state during which transient changes in the local field potential (LFP) accompany periods of increased single neuron firing, known as UP-states. While UP-state genesis is still debated (Crunelli and Hughes, 2010) such transitions may constitute the default activity pattern of the entire cortex (Neske, 2016). Recent findings of preserved firing order between UP-state transitions and stimulus processing in high-firing rate (>2Hz) rat auditory and barrel cortex neurons (Luczak et al., 2015) support this hypothesis. Yet it is unknown whether UP-states are homogeneous and whether neurons with firing rates <2Hz in visual cortex or other species exhibit spiking order. Using extracellular recordings during anesthetized states in cat visual cortex and mouse visual, auditory and barrel cortex, we show that UP-states can be tracked and clustered based on the shape of the LFP waveform. We show that LFP event clusters (LECs) have current-source-density profiles that are common across different recordings or animals and using simultaneous electrophysiology and widefield voltage and calcium imaging in mouse we confirm that LEC transitions are cortex-wide phenomena. Individual LEC events can be resolved in time to within 1 – 4 ms and they elicit synchronous firing of over 75% of recorded neurons with most neurons synchronizing their firing to within ±5 – 15 ms relative LECs. Firing order of different neurons during LEC events was preserved over periods of ~30 minutes enabling future studies of UP-state transitions and firing order with near millisecond precision.Significant StatementDuring sleep and anesthetic states mammalian cortex undergoes substantial changes from awake active states. Recent studies show that single neurons in some cortical areas in rats undergo increased spiking during sleep and anesthetic states (called UP-state transitions) with some neurons firing in an order similar to awake states. This suggests that sensory processing may be similar across all states and that firing order is important for stimulus processing. Yet UP-state transitions remain poorly understood and it is unclear whether firing order is present in other cortical areas or species. Here we describe multiple classes of UP-state transitions and show most neurons in visual cortex in cats and visual, barrel and auditory cortex in mice exhibit firing order during such transitions.

scholarly journals LFP clustering in cortex reveals a taxonomy of Up states and near-millisecond, ordered phase-locking in cortical neurons

2019 ◽  
Vol 122 (4) ◽  
pp. 1794-1809
Author(s):  
Catalin C. Mitelut ◽  
Martin A. Spacek ◽  
Allen W. Chan ◽  
Tim H. Murphy ◽  
Nicholas V. Swindale
Keyword(s):  
Local Field ◽  
Local Field Potential ◽  
Cortical Neurons ◽  
State Transition ◽  
Slow Wave Sleep ◽  
Field Potential ◽  
State Transitions ◽  
Wide Field ◽  
Cortical Function ◽  
Up States

During slow-wave sleep and anesthesia, mammalian cortex exhibits a synchronized state during which neurons shift from a largely nonfiring to a firing state, known as an Up-state transition. Up-state transitions may constitute the default activity pattern of the entire cortex (Neske GT. Front Neural Circuits 9: 88, 2016) and could be critical to understanding cortical function, yet the genesis of such transitions and their interaction with single neurons is not well understood. It was recently shown that neurons firing at rates >2 Hz fire spikes in a stereotyped order during Up-state transitions (Luczak A, McNaughton BL, Harris KD. Nat Rev Neurosci 16: 745–755, 2015), yet it is still unknown if Up states are homogeneous and whether spiking order is present in neurons with rates <2 Hz (the majority). Using extracellular recordings from anesthetized cats and mice and from naturally sleeping rats, we show for the first time that Up-state transitions can be classified into several types based on the shape of the local field potential (LFP) during each transition. Individual LFP events could be localized in time to within 1–4 ms, more than an order of magnitude less than in previous studies. The majority of recorded neurons synchronized their firing to within ±5–15 ms relative to each Up-state transition. Simultaneous electrophysiology and wide-field imaging in mouse confirmed that LFP event clusters are cortex-wide phenomena. Our findings show that Up states are of different types and point to the potential importance of temporal order and millisecond-scale signaling by cortical neurons. NEW & NOTEWORTHY During cortical Up-state transitions in sleep and anesthesia, neurons undergo brief periods of increased firing in an order similar to that occurring in awake states. We show that these transitions can be classified into distinct types based on the shape of the local field potential. Transition times can be defined to <5 ms. Most neurons synchronize their firing to within ±5–15 ms of the transitions and fire in a consistent order.

Slow and fast rhythms generated in the cerebral cortex of the anesthetized mouse

2011 ◽  
Vol 106 (6) ◽  
pp. 2910-2921 ◽  
Author(s):  
Marcel Ruiz-Mejias ◽  
Laura Ciria-Suarez ◽  
Maurizio Mattia ◽  
Maria V. Sanchez-Vives
Keyword(s):  
Cerebral Cortex ◽  
Prefrontal Cortex ◽  
Firing Rate ◽  
Oscillatory Activity ◽  
State Transitions ◽  
Population Activity ◽  
Cortical Areas ◽  
Up States ◽  
High Gamma ◽  
Up And Down States

A characterization of the oscillatory activity in the cerebral cortex of the mouse was realized under ketamine anesthesia. Bilateral recordings were obtained from deep layers of primary visual, somatosensory, motor, and medial prefrontal cortex. A slow oscillatory activity consisting of up and down states was detected, the average frequency being 0.97 Hz in all areas. Different parameters of the oscillation were estimated across cortical areas, including duration of up and down states and their variability, speed of state transitions, and population firing rate. Similar values were obtained for all areas except for prefrontal cortex, which showed significant faster down-to-up state transitions, higher firing rate during up states, and more regular cycles. The wave propagation patterns in the anteroposterior axis in motor cortex and the mediolateral axis in visual cortex were studied with multielectrode recordings, yielding speed values between 8 and 93 mm/s. The firing of single units was analyzed with respect to the population activity. The most common pattern was that of neurons firing in >90% of the up states with 1–6 spikes. Finally, fast rhythms (beta, low gamma, and high gamma) were analyzed, all of them showing significantly larger power during up states than in down states. Prefrontal cortex exhibited significantly larger power in both beta and gamma bands (up to 1 order of magnitude larger in the case of high gamma) than the rest of the cortical areas. This study allows us to carry out interareal comparisons and provides a baseline to compare against cortical emerging activity from genetically altered animals.

scholarly journals Comprehensive mapping of whisker-evoked responses reveals broad, sharply tuned thalamocortical input to layer 4 of barrel cortex

2011 ◽  
Vol 105 (5) ◽  
pp. 2421-2437 ◽  
Author(s):  
Noah C. Roy ◽  
Thomas Bessaih ◽  
Diego Contreras
Keyword(s):  
Cortical Neurons ◽  
Barrel Cortex ◽  
Current Source ◽  
Field Potential ◽  
Fundamental Information ◽  
Layer 4 ◽  
Density Analysis ◽  
Evoked Activity ◽  
Rats And Mice

Cortical neurons are organized in columns, distinguishable by their physiological properties and input-output organization. Columns are thought to be the fundamental information-processing modules of the cortex. The barrel cortex of rats and mice is an attractive model system for the study of cortical columns, because each column is defined by a layer 4 (L4) structure called a barrel, which can be clearly visualized. A great deal of information has been collected regarding the connectivity of neurons in barrel cortex, but the nature of the input to a given L4 barrel remains unclear. We measured this input by making comprehensive maps of whisker-evoked activity in L4 of rat barrel cortex using recordings of multiunit activity and current source density analysis of local field potential recordings of animals under light isoflurane anesthesia. We found that a large number of whiskers evoked a detectable response in each barrel (mean of 13 suprathreshold, 18 subthreshold) even after cortical activity was abolished by application of muscimol, a GABAA agonist. We confirmed these findings with intracellular recordings and single-unit extracellular recordings in vivo. This constitutes the first direct confirmation of the hypothesis that subcortical mechanisms mediate a substantial multiwhisker input to a given cortical barrel.

scholarly journals Laminar Population Analysis: Estimating Firing Rates and Evoked Synaptic Activity From Multielectrode Recordings in Rat Barrel Cortex

2007 ◽  
Vol 97 (3) ◽  
pp. 2174-2190 ◽  
Author(s):  
Gaute T. Einevoll ◽  
Klas H. Pettersen ◽  
Anna Devor ◽  
Istvan Ulbert ◽  
Eric Halgren ◽  
...  
Keyword(s):  
Frequency Band ◽  
Barrel Cortex ◽  
Population Analysis ◽  
Current Source ◽  
Field Potential ◽  
Synaptic Activity ◽  
Data Sets ◽  
Synaptic Connections ◽  
Firing Activity ◽  
Forward Solution

We present a new method, laminar population analysis (LPA), for analysis of laminar-electrode (linear multielectrode) data, where physiological constraints are explicitly incorporated in the mathematical model: the high-frequency band [multiunit activity (MUA)] is modeled as a sum over contributions from firing activity of multiple cortical populations, whereas the low-frequency band [local field potential (LFP)] is assumed to reflect the dendritic currents caused by synaptic inputs evoked by this firing. The method is applied to stimulus-averaged laminar-electrode data from barrel cortex of anesthetized rat after single whisker flicks. Two sample data sets, distinguished by stimulus paradigm, type of applied anesthesia, and electrical boundary conditions, are studied in detail. These data sets are well accounted for by a model with four cortical populations: one supragranular, one granular, and two infragranular populations. Population current source densities (CSDs; the CSD signatures after firing in a particular population) provided by LPA are further used to estimate the synaptic connection pattern between the various populations using a new LFP template-fitting technique, where LFP population templates are found by the electrostatic forward solution based on results from compartmental modeling of morphologically reconstructed neurons. Our analysis confirms previous experimental findings regarding the synaptic connections from neurons in the granular layer onto neurons in the supragranular layers and provides predictions about other synaptic connections. Furthermore, the time dependence of the stimulus-evoked population firing activity is predicted, and the temporal ordering of response onset is found to be compatible with earlier findings.

Experience-dependent regulation of synchronized slow-wave sleep in visual cortex

2000 ◽  
Vol 38 ◽  
pp. S171
Author(s):  
H Miyamoto
Keyword(s):  
Visual Cortex ◽  
Slow Wave ◽  
Slow Wave Sleep

scholarly journals Superimposed gratings induce diverse response patterns of gamma oscillations in primary visual cortex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bin Wang ◽  
Chuanliang Han ◽  
Tian Wang ◽  
Weifeng Dai ◽  
Yang Li ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Field Potential ◽  
Gamma Oscillations ◽  
Neural Mechanisms ◽  
Model Parameters ◽  
Response Patterns ◽  
Region Difference ◽  
High Gamma ◽  
Spiking Activity

AbstractStimulus-dependence of gamma oscillations (GAMMA, 30–90 Hz) has not been fully understood, but it is important for revealing neural mechanisms and functions of GAMMA. Here, we recorded spiking activity (MUA) and the local field potential (LFP), driven by a variety of plaids (generated by two superimposed gratings orthogonal to each other and with different contrast combinations), in the primary visual cortex of anesthetized cats. We found two distinct narrow-band GAMMAs in the LFPs and a variety of response patterns to plaids. Similar to MUA, most response patterns showed that the second grating suppressed GAMMAs driven by the first one. However, there is only a weak site-by-site correlation between cross-orientation interactions in GAMMAs and those in MUAs. We developed a normalization model that could unify the response patterns of both GAMMAs and MUAs. Interestingly, compared with MUAs, the GAMMAs demonstrated a wider range of model parameters and more diverse response patterns to plaids. Further analysis revealed that normalization parameters for high GAMMA, but not those for low GAMMA, were significantly correlated with the discrepancy of spatial frequency between stimulus and sites’ preferences. Consistent with these findings, normalization parameters and diversity of high GAMMA exhibited a clear transition trend and region difference between area 17 to 18. Our results show that GAMMAs are also regulated in the form of normalization, but that the neural mechanisms for these normalizations might differ from those of spiking activity. Normalizations in different brain signals could be due to interactions of excitation and inhibitions at multiple stages in the visual system.

scholarly journals A direct interareal feedback-to-feedforward circuit in primate visual cortex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Caitlin Siu ◽  
Justin Balsor ◽  
Sam Merlin ◽  
Frederick Federer ◽  
Alessandra Angelucci
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Projection Neurons ◽  
V1 Neurons ◽  
Cortical Areas ◽  
Area V2 ◽  
Computational Work ◽  
Primate Visual Cortex ◽  
Similar Area ◽  
Hierarchical Computation

AbstractThe mammalian sensory neocortex consists of hierarchically organized areas reciprocally connected via feedforward (FF) and feedback (FB) circuits. Several theories of hierarchical computation ascribe the bulk of the computational work of the cortex to looped FF-FB circuits between pairs of cortical areas. However, whether such corticocortical loops exist remains unclear. In higher mammals, individual FF-projection neurons send afferents almost exclusively to a single higher-level area. However, it is unclear whether FB-projection neurons show similar area-specificity, and whether they influence FF-projection neurons directly or indirectly. Using viral-mediated monosynaptic circuit tracing in macaque primary visual cortex (V1), we show that V1 neurons sending FF projections to area V2 receive monosynaptic FB inputs from V2, but not other V1-projecting areas. We also find monosynaptic FB-to-FB neuron contacts as a second motif of FB connectivity. Our results support the existence of FF-FB loops in primate cortex, and suggest that FB can rapidly and selectively influence the activity of incoming FF signals.

scholarly journals Increased neural correlations in primate auditory cortex during slow-wave sleep

2013 ◽  
Vol 109 (11) ◽  
pp. 2732-2738 ◽  
Author(s):  
Elias B. Issa ◽  
Xiaoqin Wang
Keyword(s):  
Auditory Cortex ◽  
Spontaneous Activity ◽  
Slow Wave ◽  
Local Field ◽  
Local Field Potential ◽  
Slow Wave Sleep ◽  
Field Potential ◽  
Sensory Stimulation ◽  
Acoustic Stimulation ◽  
Functional Connections

During sleep, changes in brain rhythms and neuromodulator levels in cortex modify the properties of individual neurons and the network as a whole. In principle, network-level interactions during sleep can be studied by observing covariation in spontaneous activity between neurons. Spontaneous activity, however, reflects only a portion of the effective functional connectivity that is activated by external and internal inputs (e.g., sensory stimulation, motor behavior, and mental activity), and it has been shown that neural responses are less correlated during external sensory stimulation than during spontaneous activity. Here, we took advantage of the unique property that the auditory cortex continues to respond to sounds during sleep and used external acoustic stimuli to activate cortical networks for studying neural interactions during sleep. We found that during slow-wave sleep (SWS), local (neuron-neuron) correlations are not reduced by acoustic stimulation remaining higher than in wakefulness and rapid eye movement sleep and remaining similar to spontaneous activity correlations. This high level of correlations during SWS complements previous work finding elevated global (local field potential-local field potential) correlations during sleep. Contrary to the prediction that slow oscillations in SWS would increase neural correlations during spontaneous activity, we found little change in neural correlations outside of periods of acoustic stimulation. Rather, these findings suggest that functional connections recruited in sound processing are modified during SWS and that slow rhythms, which in general are suppressed by sensory stimulation, are not the sole mechanism leading to elevated network correlations during sleep.

Heterogeneity of Phasic Cholinergic Signaling in Neocortical Neurons

2007 ◽  
Vol 97 (3) ◽  
pp. 2215-2229 ◽  
Author(s):  
Allan T. Gulledge ◽  
Susanna B. Park ◽  
Yasuo Kawaguchi ◽  
Greg J. Stuart
Keyword(s):  
Visual Cortex ◽  
Calcium Release ◽  
Pyramidal Neurons ◽  
Potassium Conductance ◽  
Projection Neurons ◽  
Sk Channels ◽  
Cortical Areas ◽  
Neocortical Neurons ◽  
Cholinergic Signaling ◽  
Nonpyramidal Neurons

Acetylcholine (ACh) is a neurotransmitter critical for normal cognition. Here we demonstrate heterogeneity of cholinergic signaling in neocortical neurons in the rat prefrontal, somatosensory, and visual cortex. Focal ACh application (100 μM) inhibited layer 5 pyramidal neurons in all cortical areas via activation of an apamin-sensitive SK-type calcium-activated potassium conductance. Cholinergic inhibition was most robust in prefrontal layer 5 neurons, where it relies on the same signal transduction mechanism (M1-like receptors, IP3-dependent calcium release, and SK-channels) as exists in somatosensory pyramidal neurons. Pyramidal neurons in layer 2/3 were less responsive to ACh, but substantial apamin-sensitive inhibitory responses occurred in deep layer 3 neurons of the visual cortex. ACh was only inhibitory when presented near the somata of layer 5 pyramidal neurons, where repetitive ACh applications generated discrete inhibitory events at frequencies of up to ∼0.5 Hz. Fast-spiking (FS) nonpyramidal neurons in all cortical areas were unresponsive to ACh. When applied to non-FS interneurons in layers 2/3 and 5, ACh generated mecamylamine-sensitive nicotinic responses (38% of cells), apamin-insensitive hyperpolarizing responses, with or without initial nicotinic depolarization (7% of neurons), or no response at all (55% of cells). Responses in interneurons were similar across cortical layers and regions but were correlated with cellular physiology and the expression of biochemical markers associated with different classes of nonpyramidal neurons. Finally, ACh generated nicotinic responses in all layer 1 neurons tested. These data demonstrate that phasic cholinergic input can directly inhibit projection neurons throughout the cortex while sculpting intracortical processing, especially in superficial layers.

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