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1.  How do neurons work together? Lessons from auditory cortex 
Hearing research  2010;271(1-2):37-53.
Recordings of single neurons have yielded great insights into the way acoustic stimuli are represented in auditory cortex. However, any one neuron functions as part of a population whose combined activity underlies cortical information processing. Here we review some results obtained by recording simultaneously from auditory cortical populations and individual morphologically identified neurons, in urethane-anesthetized and unanesthetized passively listening rats. Auditory cortical populations produced structured activity patterns both in response to acoustic stimuli, and spontaneously without sensory input. Population spike time patterns were broadly conserved across multiple sensory stimuli and spontaneous events, exhibiting a generally conserved sequential organization lasting approximately 100ms. Both spontaneous and evoked events exhibited sparse, spatially localized activity in layer 2/3 pyramidal cells, and densely distributed activity in larger layer 5 pyramidal cells and putative interneurons. Laminar propagation differed however, with spontaneous activity spreading upward from deep layers and slowly across columns, but sensory responses initiating in presumptive thalamorecipient layers, spreading rapidly across columns. In both unanesthetized and urethanized rats, global activity fluctuated between “desynchronized” state characterized by low amplitude, high-frequency local field potentials and a “synchronized” state of larger, lower-frequency waves. Computational studies suggested that responses could be predicted by a simple dynamical system model fitted to the spontaneous activity immediately preceding stimulus presentation. Fitting this model to the data yielded a nonlinear self-exciting system model in synchronized states and an approximately linear system in desynchronized states. We comment on the significance of these results for auditory cortical processing of acoustic and non-acoustic information.
doi:10.1016/j.heares.2010.06.006
PMCID: PMC2992581  PMID: 20603208
2.  Brain state-dependent abnormal LFP activity in the auditory cortex of a schizophrenia mouse model 
In schizophrenia, evoked 40-Hz auditory steady-state responses (ASSRs) are impaired, which reflects the sensory deficits in this disorder, and baseline spontaneous oscillatory activity also appears to be abnormal. It has been debated whether the evoked ASSR impairments are due to the possible increase in baseline power. GABAergic interneuron-specific NMDA receptor (NMDAR) hypofunction mutant mice mimic some behavioral and pathophysiological aspects of schizophrenia. To determine the presence and extent of sensory deficits in these mutant mice, we recorded spontaneous local field potential (LFP) activity and its click-train evoked ASSRs from primary auditory cortex of awake, head-restrained mice. Baseline spontaneous LFP power in the pre-stimulus period before application of the first click trains was augmented at a wide range of frequencies. However, when repetitive ASSR stimuli were presented every 20 s, averaged spontaneous LFP power amplitudes during the inter-ASSR stimulus intervals in the mutant mice became indistinguishable from the levels of control mice. Nonetheless, the evoked 40-Hz ASSR power and their phase locking to click trains were robustly impaired in the mutants, although the evoked 20-Hz ASSRs were also somewhat diminished. These results suggested that NMDAR hypofunction in cortical GABAergic neurons confers two brain state-dependent LFP abnormalities in the auditory cortex; (1) a broadband increase in spontaneous LFP power in the absence of external inputs, and (2) a robust deficit in the evoked ASSR power and its phase-locking despite of normal baseline LFP power magnitude during the repetitive auditory stimuli. The “paradoxically” high spontaneous LFP activity of the primary auditory cortex in the absence of external stimuli may possibly contribute to the emergence of schizophrenia-related aberrant auditory perception.
doi:10.3389/fnins.2014.00168
PMCID: PMC4077015  PMID: 25018691
auditory steady-state responses; GABAergic interneurons; gamma oscillation; local field potentials; NMDA receptors; parvalbumin; schizophrenia; mouse models
3.  Auditory Cortex Represents Both Pitch Judgments and the Corresponding Acoustic Cues 
Current Biology  2013;23(7):620-625.
Summary
The neural processing of sensory stimuli involves a transformation of physical stimulus parameters into perceptual features, and elucidating where and how this transformation occurs is one of the ultimate aims of sensory neurophysiology. Recent studies have shown that the firing of neurons in early sensory cortex can be modulated by multisensory interactions [1–5], motor behavior [1, 3, 6, 7], and reward feedback [1, 8, 9], but it remains unclear whether neural activity is more closely tied to perception, as indicated by behavioral choice, or to the physical properties of the stimulus. We investigated which of these properties are predominantly represented in auditory cortex by recording local field potentials (LFPs) and multiunit spiking activity in ferrets while they discriminated the pitch of artificial vowels. We found that auditory cortical activity is informative both about the fundamental frequency (F0) of a target sound and also about the pitch that the animals appear to perceive given their behavioral responses. Surprisingly, although the stimulus F0 was well represented at the onset of the target sound, neural activity throughout auditory cortex frequently predicted the reported pitch better than the target F0.
Highlights
► Auditory cortical responses were recorded while ferrets discriminated pitch shifts ► LFP and multiunit activity are sensitive to the sound’s fundamental frequency (F0) ► Neural activity related to animals’ reported pitch increases throughout the trial ► Cortical responses were more informative about behavioral choices than the sound F0
doi:10.1016/j.cub.2013.03.003
PMCID: PMC3696731  PMID: 23523247
4.  Encoding of Naturalistic Stimuli by Local Field Potential Spectra in Networks of Excitatory and Inhibitory Neurons 
PLoS Computational Biology  2008;4(12):e1000239.
Recordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely unknown. To understand the rules of translation between the structure of sensory stimuli and the fluctuations of cortical responses, we simulated a sparsely connected network of excitatory and inhibitory neurons modeling a local cortical population, and we determined how the LFPs generated by the network encode information about input stimuli. We first considered simple static and periodic stimuli and then naturalistic input stimuli based on electrophysiological recordings from the thalamus of anesthetized monkeys watching natural movie scenes. We found that the simulated network produced stimulus-related LFP changes that were in striking agreement with the LFPs obtained from the primary visual cortex. Moreover, our results demonstrate that the network encoded static input spike rates into gamma-range oscillations generated by inhibitory–excitatory neural interactions and encoded slow dynamic features of the input into slow LFP fluctuations mediated by stimulus–neural interactions. The model cortical network processed dynamic stimuli with naturalistic temporal structure by using low and high response frequencies as independent communication channels, again in agreement with recent reports from visual cortex responses to naturalistic movies. One potential function of this frequency decomposition into independent information channels operated by the cortical network may be that of enhancing the capacity of the cortical column to encode our complex sensory environment.
Author Summary
The brain displays rhythmic activity in almost all areas and over a wide range of frequencies and amplitudes. However, the role of these rhythms in the processing of sensory information is still unclear. To study the interplay between visual stimuli and ongoing oscillations in the brain, we developed a model of a local circuit of the visual cortex. We injected into the network the signal recorded in the thalamus of an anesthetized monkey watching a movie, to mimic the effect of a naturalistic stimulus arriving at the visual cortex. Our results are in striking agreement with recordings from the visual cortex. Furthermore, through manipulations of the signal and information analysis, we found that two specific frequency bands of the neurons' activity are used to encode independent stimuli features. These results describe how sensory stimuli can modulate frequency and amplitude of ongoing neural activity and how these modulations can be used to convey sensory information through the different layers of the brain.
doi:10.1371/journal.pcbi.1000239
PMCID: PMC2585056  PMID: 19079571
5.  Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex 
PLoS ONE  2012;7(5):e35850.
Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.
doi:10.1371/journal.pone.0035850
PMCID: PMC3346760  PMID: 22586452
6.  Influence of spiking activity on cortical local field potentials 
The Journal of Physiology  2013;591(Pt 21):5291-5303.
The intra-cortical local field potential (LFP) reflects a variety of electrophysiological processes including synaptic inputs to neurons and their spiking activity. It is still a common assumption that removing high frequencies, often above 300 Hz, is sufficient to exclude spiking activity from LFP activity prior to analysis. Conclusions based on such supposedly spike-free LFPs can result in false interpretations of neurophysiological processes and erroneous correlations between LFPs and behaviour or spiking activity. Such findings might simply arise from spike contamination rather than from genuine changes in synaptic input activity. Although the subject of recent studies, the extent of LFP contamination by spikes is unclear, and the fundamental problem remains. Using spikes recorded in the motor cortex of the awake monkey, we investigated how different factors, including spike amplitude, duration and firing rate, together with the noise statistic, can determine the extent to which spikes contaminate intra-cortical LFPs. We demonstrate that such contamination is realistic for LFPs with a frequency down to ∼10 Hz. For LFP activity below ∼10 Hz, such as movement-related potential, contamination is theoretically possible but unlikely in real situations. Importantly, LFP frequencies up to the (high-) gamma band can remain unaffected. This study shows that spike–LFP crosstalk in intra-cortical recordings should be assessed for each individual dataset to ensure that conclusions based on LFP analysis are valid. To this end, we introduce a method to detect and to visualise spike contamination, and provide a systematic guide to assess spike contamination of intra-cortical LFPs.
doi:10.1113/jphysiol.2013.258228
PMCID: PMC3936368  PMID: 23981719
7.  Influence of spiking activity on cortical local field potentials 
The Journal of Physiology  2013;591(21):5291-5303.
The intra-cortical local field potential (LFP) reflects a variety of electrophysiological processes including synaptic inputs to neurons and their spiking activity. It is still a common assumption that removing high frequencies, often above 300 Hz, is sufficient to exclude spiking activity from LFP activity prior to analysis. Conclusions based on such supposedly spike-free LFPs can result in false interpretations of neurophysiological processes and erroneous correlations between LFPs and behaviour or spiking activity. Such findings might simply arise from spike contamination rather than from genuine changes in synaptic input activity. Although the subject of recent studies, the extent of LFP contamination by spikes is unclear, and the fundamental problem remains. Using spikes recorded in the motor cortex of the awake monkey, we investigated how different factors, including spike amplitude, duration and firing rate, together with the noise statistic, can determine the extent to which spikes contaminate intra-cortical LFPs. We demonstrate that such contamination is realistic for LFPs with a frequency down to ∼10 Hz. For LFP activity below ∼10 Hz, such as movement-related potential, contamination is theoretically possible but unlikely in real situations. Importantly, LFP frequencies up to the (high-) gamma band can remain unaffected. This study shows that spike–LFP crosstalk in intra-cortical recordings should be assessed for each individual dataset to ensure that conclusions based on LFP analysis are valid. To this end, we introduce a method to detect and to visualise spike contamination, and provide a systematic guide to assess spike contamination of intra-cortical LFPs.
doi:10.1113/jphysiol.2013.258228
PMCID: PMC3936368  PMID: 23981719
8.  Sparse Representation of Sounds in the Unanesthetized Auditory Cortex 
PLoS Biology  2008;6(1):e16.
How do neuronal populations in the auditory cortex represent acoustic stimuli? Although sound-evoked neural responses in the anesthetized auditory cortex are mainly transient, recent experiments in the unanesthetized preparation have emphasized subpopulations with other response properties. To quantify the relative contributions of these different subpopulations in the awake preparation, we have estimated the representation of sounds across the neuronal population using a representative ensemble of stimuli. We used cell-attached recording with a glass electrode, a method for which single-unit isolation does not depend on neuronal activity, to quantify the fraction of neurons engaged by acoustic stimuli (tones, frequency modulated sweeps, white-noise bursts, and natural stimuli) in the primary auditory cortex of awake head-fixed rats. We find that the population response is sparse, with stimuli typically eliciting high firing rates (>20 spikes/second) in less than 5% of neurons at any instant. Some neurons had very low spontaneous firing rates (<0.01 spikes/second). At the other extreme, some neurons had driven rates in excess of 50 spikes/second. Interestingly, the overall population response was well described by a lognormal distribution, rather than the exponential distribution that is often reported. Our results represent, to our knowledge, the first quantitative evidence for sparse representations of sounds in the unanesthetized auditory cortex. Our results are compatible with a model in which most neurons are silent much of the time, and in which representations are composed of small dynamic subsets of highly active neurons.
Author Summary
How do neuronal populations in the auditory cortex represent sounds? Although sound-evoked neural responses in the anesthetized auditory cortex are mainly transient, recent experiments in the unanesthetized preparation have emphasized subpopulations with other response properties. We quantified the relative contributions of these different subpopulations in the auditory cortex of awake head-fixed rats. We recorded neuronal activity using cell-attached recordings with a glass electrode—a method for which isolation of individual neurons does not depend on neuronal activity—while probing neurons with a representative ensemble of sounds. Our data therefore address the question: What is the typical response to a particular stimulus? We find that the population response is sparse, with sounds typically eliciting high activity in less than 5% of neurons at any instant. The overall population response was well described by a lognormal distribution, rather than the exponential distribution that is often reported. Our results represent, to our knowledge, the first quantitative evidence for sparse representations of sounds in the unanesthetized auditory cortex. These results are compatible with a model in which most neurons are silent much of the time, and in which representations are composed of small dynamic subsets of highly active neurons.
Patch clamp recordings in the auditory cortex of unanesthetized rats reveal that the population response to sounds is sparse and that most neurons are silent most of the time.
doi:10.1371/journal.pbio.0060016
PMCID: PMC2214813  PMID: 18232737
9.  Predicting stimulus-locked single unit spiking from cortical local field potentials 
The rapidly increasing use of the local field potential (LFP) has motivated research to better understand its relation to the gold standard of neural activity, single unit (SU) spiking. We addressed this in an in vivo, awake, restrained mouse auditory cortical electrophysiology preparation by asking whether the LFP could actually be used to predict stimulus-evoked SU spiking. Implementing a Bayesian algorithm to predict the likelihood of spiking on a trial by trial basis from different representations of the despiked LFP signal, we were able to predict, with high quality and fine temporal resolution (2 ms), the time course of a SU's excitatory or inhibitory firing rate response to natural species-specific vocalizations. Our best predictions were achieved by representing the LFP by its wide-band Hilbert phase signal, and approximating the statistical structure of this signal at different time points as independent. Our results show that each SU's action potential has a unique relationship with the LFP that can be reliably used to predict the occurrence of spikes. This “signature” interaction can reflect both pre- and post-spike neural activity that is intrinsic to the local circuit rather than just dictated by the stimulus. Finally, the time course of this “signature” may be most faithful when the full bandwidth of the LFP, rather than specific narrow-band components, is used for representation.
doi:10.1007/s10827-010-0221-z
PMCID: PMC2935517  PMID: 20143142
LFP; Spike prediction; Auditory cortex; Gamma band; Theta band; Beta band; Oscillation; Bayesian algorithm; A1; Evoked potentials; Electroencephalography; EEG; Hilbert transform; Single cortical cells; Phase; Despiking
10.  Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials 
During anesthesia, slow-wave sleep and quiet wakefulness, neuronal membrane potentials collectively switch between de- and hyperpolarized levels, the cortical UP and DOWN states. Previous studies have shown that these cortical UP/DOWN states affect the excitability of individual neurons in response to sensory stimuli, indicating that a significant amount of the trial-to-trial variability in neuronal responses can be attributed to ongoing fluctuations in network activity. However, as intracellular recordings are frequently not available, it is important to be able to estimate their occurrence purely from extracellular data. Here, we combine in vivo whole cell recordings from single neurons with multi-site extracellular microelectrode recordings, to quantify the performance of various approaches to predicting UP/DOWN states from the deep-layer local field potential (LFP). We find that UP/ DOWN states in deep cortical layers of rat primary auditory cortex (A1) are predictable from the phase of LFP at low frequencies (< 4 Hz), and that the likelihood of a given state varies sinusoidally with the phase of LFP at these frequencies. We introduce a novel method of detecting cortical state by combining information concerning the phase of the LFP and ongoing multi-unit activity.
doi:10.1007/s10827-010-0228-5
PMCID: PMC3094772  PMID: 20225075
UP and DOWN states; LFP; State dependent coding; Neural coding; Spontaneous activity; Neural oscillations
11.  Synchronous Chaos and Broad Band Gamma Rhythm in a Minimal Multi-Layer Model of Primary Visual Cortex 
PLoS Computational Biology  2011;7(10):e1002176.
Visually induced neuronal activity in V1 displays a marked gamma-band component which is modulated by stimulus properties. It has been argued that synchronized oscillations contribute to these gamma-band activity. However, analysis of Local Field Potentials (LFPs) across different experiments reveals considerable diversity in the degree of oscillatory behavior of this induced activity. Contrast-dependent power enhancements can indeed occur over a broad band in the gamma frequency range and spectral peaks may not arise at all. Furthermore, even when oscillations are observed, they undergo temporal decorrelation over very few cycles. This is not easily accounted for in previous network modeling of gamma oscillations. We argue here that interactions between cortical layers can be responsible for this fast decorrelation. We study a model of a V1 hypercolumn, embedding a simplified description of the multi-layered structure of the cortex. When the stimulus contrast is low, the induced activity is only weakly synchronous and the network resonates transiently without developing collective oscillations. When the contrast is high, on the other hand, the induced activity undergoes synchronous oscillations with an irregular spatiotemporal structure expressing a synchronous chaotic state. As a consequence the population activity undergoes fast temporal decorrelation, with concomitant rapid damping of the oscillations in LFPs autocorrelograms and peak broadening in LFPs power spectra. We show that the strength of the inter-layer coupling crucially affects this spatiotemporal structure. We predict that layer VI inactivation should induce global changes in the spectral properties of induced LFPs, reflecting their slower temporal decorrelation in the absence of inter-layer feedback. Finally, we argue that the mechanism underlying the emergence of synchronous chaos in our model is in fact very general. It stems from the fact that gamma oscillations induced by local delayed inhibition tend to develop chaos when coupled by sufficiently strong excitation.
Author Summary
Visual stimulation elicits neuronal responses in visual cortex. When the contrast of the used stimuli increases, the power of this induced activity is boosted over a broad frequency range (30–100 Hz), called the “gamma band.” It would be tempting to hypothesize that this phenomenon is due to the emergence of oscillations in which many neurons fire collectively in a rhythmic way. However, previous models trying to explain contrast-related power enhancements using synchronous oscillations failed to reproduce the observed spectra because they originated unrealistically sharp spectral peaks. The aim of our study is to reconcile synchronous oscillations with broad-band power spectra. We argue here that, thanks to the interaction between neuronal populations at different depths in the cortical tissue, the induced oscillatory responses are synchronous, but, at the same time, chaotic. The chaotic nature of the dynamics makes it possible to have broad-band power spectra together with synchrony. Our modeling study allows us formulating qualitative experimental predictions that provide a potential test for our theory. We predict that if the interactions between cortical layers are suppressed, for instance by inactivating neurons in deep layers, the induced responses might become more regular and narrow isolated peaks might develop in their power spectra.
doi:10.1371/journal.pcbi.1002176
PMCID: PMC3188510  PMID: 21998568
12.  Sensory information in local field potentials and spikes from visual and auditory cortices: time scales and frequency bands 
Studies analyzing sensory cortical processing or trying to decode brain activity often rely on a combination of different electrophysiological signals, such as local field potentials (LFPs) and spiking activity. Understanding the relation between these signals and sensory stimuli and between different components of these signals is hence of great interest. We here provide an analysis of LFPs and spiking activity recorded from visual and auditory cortex during stimulation with natural stimuli. In particular, we focus on the time scales on which different components of these signals are informative about the stimulus, and on the dependencies between different components of these signals. Addressing the first question, we find that stimulus information in low frequency bands (<12 Hz) is high, regardless of whether their energy is computed at the scale of milliseconds or seconds. Stimulus information in higher bands (>50 Hz), in contrast, is scale dependent, and is larger when the energy is averaged over several hundreds of milliseconds. Indeed, combined analysis of signal reliability and information revealed that the energy of slow LFP fluctuations is well related to the stimulus even when considering individual or few cycles, while the energy of fast LFP oscillations carries information only when averaged over many cycles. Addressing the second question, we find that stimulus information in different LFP bands, and in different LFP bands and spiking activity, is largely independent regardless of time scale or sensory system. Taken together, these findings suggest that different LFP bands represent dynamic natural stimuli on distinct time scales and together provide a potentially rich source of information for sensory processing or decoding brain activity.
Electronic supplementary material
The online version of this article (doi:10.1007/s10827-010-0230-y) contains supplementary material, which is available to authorized users.
doi:10.1007/s10827-010-0230-y
PMCID: PMC2978898  PMID: 20232128
Information theory; Vision; Audition; Population coding; Oscillations; Firing rates
13.  Local Field Potentials in the Gustatory Cortex Carry Taste Information 
The Journal of Neuroscience  2014;34(26):8778-8787.
It has been recently shown that local field potentials (LFPs) from the auditory and visual cortices carry information about sensory stimuli, but whether this is a universal property of sensory cortices remains to be determined. Moreover, little is known about the temporal dynamics of sensory information contained in LFPs following stimulus onset. Here we investigated the time course of the amount of stimulus information in LFPs and spikes from the gustatory cortex of awake rats subjected to tastants and water delivery on the tongue. We found that the phase and amplitude of multiple LFP frequencies carry information about stimuli, which have specific time courses after stimulus delivery. The information carried by LFP phase and amplitude was independent within frequency bands, since the joint information exhibited neither synergy nor redundancy. Tastant information in LFPs was also independent and had a different time course from the information carried by spikes. These findings support the hypothesis that the brain uses different frequency channels to dynamically code for multiple features of a stimulus.
doi:10.1523/JNEUROSCI.0908-14.2014
PMCID: PMC4069356  PMID: 24966378
14.  Invariance of Firing Rate and Field Potential Dynamics to Stimulus Modulation Rate in Human Auditory Cortex 
Human brain mapping  2010;32(8):1181-1193.
The effect of stimulus modulation rate on the underlying neural activity in human auditory cortex is not clear. Human studies (using both invasive and noninvasive techniques) have demonstrated that at the population level, auditory cortex follows stimulus envelope. Here we examined the effect of stimulus modulation rate by using a rare opportunity to record both spiking activity and local field potentials (LFP) in auditory cortex of patients during repeated presentations of an audio-visual movie clip presented at normal, double, and quadruple speeds. Mean firing rate during evoked activity remained the same across speeds and the temporal response profile of firing rate modulations at increased stimulus speeds was a linearly scaled version of the response during slower speeds. Additionally, stimulus induced power modulation of local field potentials in the high gamma band (64–128 Hz) exhibited similar temporal scaling as the neuronal firing rate modulations. Our data confirm and extend previous studies in humans and anesthetized animals, supporting a model in which both firing rate, and high-gamma LFP power modulations in auditory cortex follow the temporal envelope of the stimulus across different modulation rates.
doi:10.1002/hbm.21100
PMCID: PMC3085610  PMID: 20665720
human; auditory cortex; spiking activity; local field potentials (LFP)
15.  Timing of Single-Neuron and Local Field Potential Responses in the Human Medial Temporal Lobe 
Current Biology  2014;24(3):299-304.
Summary
The relationship between the firing of single cells and local field potentials (LFPs) has received increasing attention, with studies in animals [1–11] and humans [12–14]. Recordings in the human medial temporal lobe (MTL) have demonstrated the existence of neurons with selective and invariant responses [15], with a relatively late but precise response onset around 300 ms after stimulus presentation [16–18] and firing only upon conscious recognition of the stimulus [19]. This represents a much later onset than expected from direct projections from inferotemporal cortex [16, 18]. The neural mechanisms underlying this onset remain unclear. To address this issue, we performed a joint analysis of single-cell and LFP responses during a visual recognition task. Single-neuron responses were preceded by a global LFP deflection in the theta range. In addition, there was a local and stimulus-specific increase in the single-trial gamma power. These LFP responses correlated with conscious recognition. The timing of the neurons’ firing was phase locked to these LFP responses. We propose that whereas the gamma phase locking reflects the activation of local networks encoding particular recognized stimuli, the theta phase locking reflects a global activation that provides a temporal window for processing consciously perceived stimuli in the MTL.
Highlights
•Global theta LFP increases immediately precede MTL single-cell responses•Gamma power reflects activations of local networks encoding specific stimuli•The timing of the neurons’ firing is phase locked to LFP responses•LFP responses give a temporal window for processing consciously perceived stimuli
Rey et al. show that, in human medial temporal lobe (MTL), single-cell responses triggered by consciously perceived stimuli are locked to global theta and local gamma LFP responses; the latter reflects local activations, but the former shortly precedes the spike responses and may provide a window for stimulus processing in the MTL.
doi:10.1016/j.cub.2013.12.004
PMCID: PMC3963414  PMID: 24462002
16.  Comparison of LFP-Based and Spike-Based Spectro-Temporal Receptive Fields and Cross-Correlation in Cat Primary Auditory Cortex 
PLoS ONE  2011;6(5):e20046.
Multi-electrode array recordings of spike and local field potential (LFP) activity were made from primary auditory cortex of 12 normal hearing, ketamine-anesthetized cats. We evaluated 259 spectro-temporal receptive fields (STRFs) and 492 frequency-tuning curves (FTCs) based on LFPs and spikes simultaneously recorded on the same electrode. We compared their characteristic frequency (CF) gradients and their cross-correlation distances. The CF gradient for spike-based FTCs was about twice that for 2–40 Hz-filtered LFP-based FTCs, indicating greatly reduced frequency selectivity for LFPs. We also present comparisons for LFPs band-pass filtered between 4–8 Hz, 8–16 Hz and 16–40 Hz, with spike-based STRFs, on the basis of their marginal frequency distributions. We find on average a significantly larger correlation between the spike based marginal frequency distributions and those based on the 16–40 Hz filtered LFP, compared to those based on the 4–8 Hz, 8–16 Hz and 2–40 Hz filtered LFP. This suggests greater frequency specificity for the 16–40 Hz LFPs compared to those of lower frequency content. For spontaneous LFP and spike activity we evaluated 1373 pair correlations for pairs with >200 spikes in 900 s per electrode. Peak correlation-coefficient space constants were similar for the 2–40 Hz filtered LFP (5.5 mm) and the 16–40 Hz LFP (7.4 mm), whereas for spike-pair correlations it was about half that, at 3.2 mm. Comparing spike-pairs with 2–40 Hz (and 16–40 Hz) LFP-pair correlations showed that about 16% (9%) of the variance in the spike-pair correlations could be explained from LFP-pair correlations recorded on the same electrodes within the same electrode array. This larger correlation distance combined with the reduced CF gradient and much broader frequency selectivity suggests that LFPs are not a substitute for spike activity in primary auditory cortex.
doi:10.1371/journal.pone.0020046
PMCID: PMC3100317  PMID: 21625385
17.  RESPONSE PROPERTIES OF LOCAL FIELD POTENTIALS AND NEIGHBORING SINGLE NEURONS IN AWAKE PRIMARY VISUAL CORTEX 
Recordings from local field potentials (LFPs) are becoming increasingly common in research and clinical applications, however, we still have a poor understanding of how LFP stimulus selectivity originates from the combined activity of single neurons. Here, we systematically compared the stimulus selectivity of LFP and neighboring single unit activity (SUA) recorded in area V1 of awake primates. We demonstrate that LFP and SUA have similar stimulus preferences for orientation, direction of motion, contrast, size, temporal frequency and even spatial phase. However, the average SUA had 50 times better signal to noise, 20% higher contrast sensitivity, 45% higher direction selectivity and 15% more tuning depth than the average LFP. Low LFP frequencies (< 30 Hz) were most strongly correlated with the spiking frequencies of neurons with non-linear spatial summation and poor orientation/direction selectivity that were located near cortical current sinks (negative LFPs). In contrast, LFP gamma frequencies (> 30 Hz) were correlated with a more diverse group of neurons located near cortical sources (positive LFPs). In summary, our results indicate that low- and high-frequency LFP pools signals from V1 neurons with similar stimulus preferences but different response properties and cortical depths.
doi:10.1523/JNEUROSCI.0429-12.2012
PMCID: PMC3436073  PMID: 22895722
LFP; area V1; striate cortex; orientation selectivity; visual cortex; receptive field
18.  Preparatory Attention Relies on Dynamic Interactions between Prelimbic Cortex and Anterior Cingulate Cortex 
Cerebral Cortex (New York, NY)  2012;23(3):729-738.
An emerging view of prefrontal cortex (PFC) function is that multiple PFC areas process information in parallel, rather than as distinct modules. Two key functions assigned to the PFC are the regulation of top-down attention and stimulus-guided action. Electrophysiology and lesion studies indicate the involvement of both the anterior cingulate cortex (ACC) and prelimbic cortex (PL) in these functions. Little is known, however, about how these cortical regions interact. We recorded single unit spiking and local field potentials (LFPs) simultaneously in rodents during a sustained attention task and assessed interactions between the ACC and PL by measuring spike–LFP phase synchrony and LFP–LFP phase synchrony between these areas. We demonstrate that the magnitude of synchrony between the ACC and PL, before stimulus onset, predicts the subjects' behavioral choice after the stimulus. Furthermore, neurons switched from a state of beta synchrony during attention to a state of delta synchrony before the instrumental action. Our results indicate that multiple PFC areas interact during attention and that the same neurons may participate in segregated assemblies that support both attention and action.
doi:10.1093/cercor/bhs057
PMCID: PMC3593701  PMID: 22419680
ADHD; functional connectivity; schizophrenia; phase synchrony; preparatory attention
19.  Local field potentials indicate network state and account for neuronal response variability 
Multineuronal recordings have revealed that neurons in primary visual cortex (V1) exhibit coordinated fluctuations of spiking activity in the absence and in the presence of visual stimulation. From the perspective of understanding a single cell’s spiking activity relative to a behavior or stimulus, these network flutuations are typically considered to be noise. We show that these events are highly correlated with another commonly recorded signal, the local field potential (LFP), and are also likely related to global network state phenomena which have been observed in a number of neural systems. Moreover, we show that attributing a component of cell firing to these network fluctuations via explicit modeling of the LFP improves the recovery of cell properties. This suggests that the impact of network fluctuations may be estimated using the LFP, and that a portion of this network activity is unrelated to the stimulus and instead reflects ongoing cortical activity. Thus, the LFP acts as an easily accessible bridge between the network state and the spiking activity.
doi:10.1007/s10827-009-0208-9
PMCID: PMC3604740  PMID: 20094906
Local field potential; correlation; network state; spontaneous activity; multielectrode array; decoding; population coding
20.  Context Matters: The Illusive Simplicity of Macaque V1 Receptive Fields 
PLoS ONE  2012;7(7):e39699.
Even in V1, where neurons have well characterized classical receptive fields (CRFs), it has been difficult to deduce which features of natural scenes stimuli they actually respond to. Forward models based upon CRF stimuli have had limited success in predicting the response of V1 neurons to natural scenes. As natural scenes exhibit complex spatial and temporal correlations, this could be due to surround effects that modulate the sensitivity of the CRF. Here, instead of attempting a forward model, we quantify the importance of the natural scenes surround for awake macaque monkeys by modeling it non-parametrically. We also quantify the influence of two forms of trial to trial variability. The first is related to the neuron’s own spike history. The second is related to ongoing mean field population activity reflected by the local field potential (LFP). We find that the surround produces strong temporal modulations in the firing rate that can be both suppressive and facilitative. Further, the LFP is found to induce a precise timing in spikes, which tend to be temporally localized on sharp LFP transients in the gamma frequency range. Using the pseudo R2 as a measure of model fit, we find that during natural scene viewing the CRF dominates, accounting for 60% of the fit, but that taken collectively the surround, spike history and LFP are almost as important, accounting for 40%. However, overall only a small proportion of V1 spiking statistics could be explained (R2∼5%), even when the full stimulus, spike history and LFP were taken into account. This suggests that under natural scene conditions, the dominant influence on V1 neurons is not the stimulus, nor the mean field dynamics of the LFP, but the complex, incoherent dynamics of the network in which neurons are embedded.
doi:10.1371/journal.pone.0039699
PMCID: PMC3389039  PMID: 22802940
21.  Stimulus selectivity and spatial coherence of gamma components of the local field potential 
The gamma frequencies of the local field potential (LFP) provide a physiological correlate for numerous perceptual and cognitive phenomena and have been proposed to play a role in cortical function. Understanding the spatial extent of gamma and its relationship to spiking activity is critical for interpreting this signal and elucidating its function, but previous studies have provided widely disparate views of these properties. We addressed these issues by simultaneously recording LFPs and spiking activity using microelectrode arrays implanted in the primary visual cortex of macaque monkeys. We find that the spatial extent of gamma and its relationship to local spiking activity is stimulus dependent. Small gratings, and those masked with noise, induce a broadband increase in spectral power. This signal is tuned similarly to spiking activity and has limited spatial coherence. Large gratings, on the other hand, induce a gamma rhythm characterized by a distinctive spectral “bump”, which is coherent across widely separated sites. This signal is well tuned, but its stimulus preference is similar across millimeters of cortex. The preference of this global gamma rhythm is sensitive to adaptation, in a manner consistent with it magnifying a bias in the neuronal representation of visual stimuli. Gamma thus arises from two sources that reflect different spatial scales of neural ensemble activity. Our results show that there is not a single, fixed ensemble contributing to gamma and that the selectivity of gamma cannot be used to infer its spatial extent.
doi:10.1523/JNEUROSCI.0645-11.2011
PMCID: PMC3133446  PMID: 21697389
22.  Specific Entrainment of Mitral Cells during Gamma Oscillation in the Rat Olfactory Bulb 
PLoS Computational Biology  2009;5(10):e1000551.
Local field potential (LFP) oscillations are often accompanied by synchronization of activity within a widespread cerebral area. Thus, the LFP and neuronal coherence appear to be the result of a common mechanism that underlies neuronal assembly formation. We used the olfactory bulb as a model to investigate: (1) the extent to which unitary dynamics and LFP oscillations can be correlated and (2) the precision with which a model of the hypothesized underlying mechanisms can accurately explain the experimental data. For this purpose, we analyzed simultaneous recordings of mitral cell (MC) activity and LFPs in anesthetized and freely breathing rats in response to odorant stimulation. Spike trains were found to be phase-locked to the gamma oscillation at specific firing rates and to form odor-specific temporal patterns. The use of a conductance-based MC model driven by an approximately balanced excitatory-inhibitory input conductance and a relatively small inhibitory conductance that oscillated at the gamma frequency allowed us to provide one explanation of the experimental data via a mode-locking mechanism. This work sheds light on the way network and intrinsic MC properties participate in the locking of MCs to the gamma oscillation in a realistic physiological context and may result in a particular time-locked assembly. Finally, we discuss how a self-synchronization process with such entrainment properties can explain, under experimental conditions: (1) why the gamma bursts emerge transiently with a maximal amplitude position relative to the stimulus time course; (2) why the oscillations are prominent at a specific gamma frequency; and (3) why the oscillation amplitude depends on specific stimulus properties. We also discuss information processing and functional consequences derived from this mechanism.
Author Summary
Olfactory function relies on a chain of neural relays that extends from the periphery to the central nervous system and implies neural activity with various timescales. A central question in neuroscience is how information is encoded by the neural activity. In the mammalian olfactory bulb, local neural activity oscillations in the 40–80 Hz range (gamma) may influence the timing of individual neuron activities such that olfactory information may be encoded in this way. In this study, we first characterize in vivo the detailed activity of individual neurons relative to the oscillation and find that, depending on their state, neurons can exhibit periodic activity patterns. We also find, at least qualitatively, a relation between this activity and a particular odor. This is reminiscent of general physical phenomena—the entrainment by an oscillation—and to verify this hypothesis, in a second phase, we build a biologically realistic model mimicking these in vivo conditions. Our model confirms quantitatively this hypothesis and reveals that entrainment is maximal in the gamma range. Taken together, our results suggest that the neuronal activity may be specifically formatted in time during the gamma oscillation in such a way that it could, at this stage, encode the odor.
doi:10.1371/journal.pcbi.1000551
PMCID: PMC2760751  PMID: 19876377
23.  Surround Modulation Characteristics of Local Field Potential and Spiking Activity in Primary Visual Cortex of Cat 
PLoS ONE  2013;8(5):e64492.
In primary visual cortex, spiking activity that evoked by stimulus confined in receptive field can be modulated by surround stimulus. This center-surround interaction is hypothesized to be the basis of visual feature integration and segregation. Spiking output has been extensively reported to be surround suppressive. However, less is known about the modulation properties of the local field potential (LFP), which generally reflects synaptic inputs. We simultaneously recorded spiking activity and LFP in the area 17 of anesthetized cats to examine and compare their modulation characteristics. When the stimulus went beyond the classical receptive field, LFP exhibited decreased power along the gamma band (30–100 Hz) in most of our recording sites. Further investigation revealed that suppression of the LFP gamma mean power (gLFP) depended on the angle between the center and surround orientations. The strongest suppression was induced when center and surround orientations were parallel. Moreover, the surround influence of the gLFP exhibited an asymmetric spatial organization. These results demonstrate that the gLFP has similar but not identical surround modulation properties, as compared to the spiking activity. The spatiotemporal integration of LFP implies that the oscillation and synchronization of local synaptic inputs may have important functions in surround modulation.
doi:10.1371/journal.pone.0064492
PMCID: PMC3655189  PMID: 23691231
24.  Interactions between Stimulus Dynamics and Network Activity in the Representation of Natural Auditory Scenes 
The efficient cortical encoding of natural scenes is essential for guiding adaptive behavior. As natural scenes and network activity in cortical circuits share similar temporal scales, it is necessary to understand how the temporal structure of natural scenes influences network dynamics in cortical circuits and thereby spiking output. We examined the relationship between the structure of natural acoustic scenes and its impact on network activity (as indexed by the LFP) and spiking responses in macaque primary auditory cortex. Natural auditory scenes led to a change in the power of the LFP in the 2 – 9 Hz and 16 – 30 Hz frequency ranges relative to the ongoing activity. In contrast, ongoing rhythmic activity in the 9 – 16 Hz range was largely unaffected by the natural scene. Phase coherence analysis showed that scene-related changes in LFP power were at least partially due to the locking of the LFP and spiking activity to the temporal structure in the scene— with locking extending up to 25 Hz for some scenes and cortical sites. Consistent with a distributed place and temporal representation, a key predictor of phase locking and power changes was the overlap between the spectral selectivity of a cortical site and the spectral structure of the scene. Finally, during the processing of natural acoustic scenes, spikes were locked to LFP phase at frequencies up to 30 Hz. These results are consistent with an idea that the cortical representation of natural scenes emerges from an interaction between network activity and stimulus dynamics.
doi:10.1523/JNEUROSCI.3174-10.2010
PMCID: PMC3005258  PMID: 20962214
Natural Scenes; LFP; Phase locking; Spike-field coherence
25.  Effects of Familiarity on Neural Activity in Monkey Inferior Temporal Lobe 
Cerebral Cortex (New York, NY)  2008;18(11):2540-2552.
Long-term familiarity facilitates recognition of visual stimuli. To better understand the neural basis for this effect, we measured the local field potential (LFP) and multiunit spiking activity (MUA) from the inferior temporal (IT) lobe of behaving monkeys in response to novel and familiar images. In general, familiar images evoked larger amplitude LFPs whereas MUA responses were greater for novel images. Familiarity effects were attenuated by image rotations in the picture plane of 45°. Decreasing image contrast led to more pronounced decreases in LFP response magnitude for novel, compared with familiar images, and resulted in more selective MUA response profiles for familiar images. The shape of individual LFP traces could be used for stimulus classification, and classification performance was better for the familiar image category. Recording the visual and auditory evoked LFP at multiple depths showed significant alterations in LFP morphology with distance changes of 2 mm. In summary, IT cortex shows local processing differences for familiar and novel images at a time scale and in a manner consistent with the observed behavioral advantage for classifying familiar images and rapidly detecting novel stimuli.
doi:10.1093/cercor/bhn015
PMCID: PMC2733316  PMID: 18296433
evoked potentials; familiarity; local field; monkey; novelty; potentials

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