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

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.

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

Journal of Neurophysiology ◽

10.1152/jn.00695.2012 ◽

2013 ◽

Vol 109 (11) ◽

pp. 2732-2738 ◽

Cited By ~ 10

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.

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

10.1101/519454 ◽

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.

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Modeling state transition of hippocampal local field potential between theta rhythm and large irregular amplitude activity by bifurcation between a limit cycle and chaotic dynamics

10.1063/1.4776514 ◽

2013 ◽

Author(s):

K. Tokuda ◽

Y. Katori ◽

K. Aihara

Keyword(s):

Limit Cycle ◽

Local Field ◽

Local Field Potential ◽

Chaotic Dynamics ◽

Theta Rhythm ◽

State Transition ◽

Field Potential

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Visual cortex neurons phase-lock selectively to subsets of LFP oscillations

Journal of Neurophysiology ◽

10.1152/jn.00496.2018 ◽

2019 ◽

Vol 121 (6) ◽

pp. 2364-2378 ◽

Cited By ~ 1

Author(s):

N. V. Swindale ◽

M. A. Spacek

Keyword(s):

Visual Cortex ◽

Receptive Field ◽

Local Field ◽

Rem Sleep ◽

Local Field Potential ◽

Cortical Neurons ◽

Field Potential ◽

Frequency Selective ◽

Visual Cortex Neurons ◽

Local Field Potential Lfp

It is generally thought that apart from receptive field differences, such as preferred orientation and spatial frequency selectivity, primary visual cortex neurons are functionally similar to each other. However, the genetic diversity of cortical neurons plus the existence of inputs additional to those required to explain known receptive field properties might suggest otherwise. Here we report the existence of desynchronized states in anesthetized cat area 17 lasting up to 45 min, characterized by variable narrow-band local field potential (LFP) oscillations in the range 2–100 Hz and the absence of a synchronized 1/ f frequency spectrum. During these periods, spontaneously active neurons phase-locked to variable subsets of LFP oscillations. Individual neurons often ignored frequencies that others phase-locked to. We suggest that these desynchronized periods may correspond to REM sleep-like episodes occurring under anesthesia. Frequency-selective codes may be used for signaling during these periods. Hence frequency-selective combination and frequency-labeled pathways may represent a previously unsuspected dimension of cortical organization. NEW & NOTEWORTHY We investigated spontaneous neuronal firing during periods of desynchronized local field potential (LFP) activity, resembling REM sleep, in anesthetized cats. During these periods, neurons synchronized their spikes to specific phases of multiple LFP frequency components, with some neurons ignoring frequencies that others were synchronized to. Some neurons fired at phase alignments of frequency pairs, thereby acting as phase coincidence detectors. These results suggest that internal brain signaling may use frequency combination codes to generate temporally structured spike trains.

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Coupling of synaptic inputs to local cortical activity differs among neurons and adapts after stimulus onset

Journal of Neurophysiology ◽

10.1152/jn.00398.2017 ◽

2017 ◽

Vol 118 (6) ◽

pp. 3345-3359 ◽

Cited By ~ 4

Author(s):

Nathaniel C. Wright ◽

Mahmood S. Hoseini ◽

Tansel Baran Yasar ◽

Ralf Wessel

Keyword(s):

Local Field ◽

Visual Processing ◽

Local Field Potential ◽

Cortical Neurons ◽

Pyramidal Neurons ◽

Field Potential ◽

Cortical Activity ◽

Stimulus Onset ◽

Synaptic Inputs ◽

Network Properties

Cortical activity contributes significantly to the high variability of sensory responses of interconnected pyramidal neurons, which has crucial implications for sensory coding. Yet, largely because of technical limitations of in vivo intracellular recordings, the coupling of a pyramidal neuron’s synaptic inputs to the local cortical activity has evaded full understanding. Here we obtained excitatory synaptic conductance ( g) measurements from putative pyramidal neurons and local field potential (LFP) recordings from adjacent cortical circuits during visual processing in the turtle whole brain ex vivo preparation. We found a range of g-LFP coupling across neurons. Importantly, for a given neuron, g-LFP coupling increased at stimulus onset and then relaxed toward intermediate values during continued visual stimulation. A model network with clustered connectivity and synaptic depression reproduced both the diversity and the dynamics of g-LFP coupling. In conclusion, these results establish a rich dependence of single-neuron responses on anatomical, synaptic, and emergent network properties. NEW & NOTEWORTHY Cortical neurons are strongly influenced by the networks in which they are embedded. To understand sensory processing, we must identify the nature of this influence and its underlying mechanisms. Here we investigate synaptic inputs to cortical neurons, and the nearby local field potential, during visual processing. We find a range of neuron-to-network coupling across cortical neurons. This coupling is dynamically modulated during visual processing via biophysical and emergent network properties.

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Origins of 1/f2 scaling in the power spectrum of intracortical local field potential

Journal of Neurophysiology ◽

10.1152/jn.00470.2011 ◽

2012 ◽

Vol 107 (3) ◽

pp. 984-994 ◽

Cited By ~ 19

Author(s):

Gytis Baranauskas ◽

Emma Maggiolini ◽

Alessandro Vato ◽

Giannicola Angotzi ◽

Andrea Bonfanti ◽

...

Keyword(s):

Membrane Potential ◽

Power Spectrum ◽

Local Field ◽

Local Field Potential ◽

Field Potential ◽

Neuronal Firing ◽

Neuronal Membrane ◽

Up States ◽

Up And Down States ◽

Spiking Activity

It has been noted that the power spectrum of intracortical local field potential (LFP) often scales as 1/f−2. It is thought that LFP mostly represents the spiking-related neuronal activity such as synaptic currents and spikes in the vicinity of the recording electrode, but no 1/f2 scaling is detected in the spike power. Although tissue filtering or modulation of spiking activity by UP and DOWN states could account for the observed LFP scaling, there is no consensus as to how it arises. We addressed this question by recording simultaneously LFP and single neurons (“single units”) from multiple sites in somatosensory cortex of anesthetized rats. Single-unit data revealed the presence of periods of high activity, presumably corresponding to the “UP” states when the neuronal membrane potential is depolarized, and periods of no activity, the putative “DOWN” states when the membrane potential is close to resting. As expected, the LFP power scaled as 1/f2 but no such scaling was found in the power spectrum of spiking activity. Our analysis showed that 1/f2 scaling in the LFP power spectrum was largely generated by the steplike transitions between UP and DOWN states. The shape of the LFP signal during these transitions, but not the transition timing, was crucial to obtain the observed scaling. These transitions were probably induced by synchronous changes in the membrane potential across neurons. We conclude that a 1/f2 scaling in the LFP power indicates the presence of steplike transitions in the LFP trace and says little about the statistical properties of the associated neuronal firing.

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