Cue-triggered recall of learned temporal sequences is an important cognitive function that has been attributed to higher brain areas. Here, recordings in both anesthetized and awake rats demonstrate that after repeated stimulation with a moving spot that evoked sequential firing of an ensemble of primary visual cortex (V1) neurons, just a brief flash at the starting point of the motion path was sufficient to evoke a sequential firing pattern that reproduced the activation order evoked by the moving spot. The speed of recalled spike sequences may reflect the internal dynamics of the network rather than the motion speed. In awake animals, such recall was observed during a synchronized (“quiet wakeful”) brain state with large-amplitude, low-frequency local field potential (LFP), but not in a desynchronized (“active”) state with low-amplitude, high-frequency LFP. Such conditioning-enhanced, cue-evoked sequential spiking of a V1 ensemble may contribute to experience-based perceptual inference in a brain state-dependent manner.
We examined the representation of stimulus center frequencies by the distribution of cortical activity. Recordings were made from the primary auditory cortex (area A1) of ketamine-anesthetized guinea pigs. Cortical images of tones and noise bands were visualized as the simultaneously recorded spike activity of neurons at 16 sites along the tonotopic gradient of cortical frequency representation. The cortical image of a pure tone showed a restricted focus of activity along the tonotopic gradient. As the stimulus frequency was increased, the location of the activation focus shifted from rostral to caudal. When cochlear activation was broadened by increasing the stimulus level or bandwidth, the cortical image broadened. An artificial neural network algorithm was used to quantify the accuracy of center-frequency representation by small populations of cortical neurons. The artificial neural network identified stimulus center frequency based on single-trial spike counts at as few as ten sites. The performance of the artificial neural network under various conditions of stimulus level and bandwidth suggests that the accuracy of representation of center frequency is largely insensitive to changes in the width of cortical images.
auditory cortex; guinea pig; tonotopy; neural ensembles; functional imaging
Neurons in visual cortex are linked by an extensive network of lateral connections. To study the effect of these connections on neural responses, we recorded spikes and local field potentials (LFPs) from multi-electrode arrays that were implanted in monkey and cat primary visual cortex. Spikes at each location generated outward traveling LFP waves. When the visual stimulus was absent or had low contrast, these LFP waves had large amplitudes and traveled over long distances. Their effect was strong: LFP traces at any site could be predicted by the superposition of waves that were evoked by spiking in a ∼1.5-mm radius. As stimulus contrast increased, both the magnitude and the distance traveled by the waves progressively decreased. We conclude that the relative weight of feedforward and lateral inputs in visual cortex is not fixed, but rather depends on stimulus contrast. Lateral connections dominate at low contrast, when spatial integration of signals is perhaps most beneficial.
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.
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
Single neurons in the cerebral cortex are immersed in a fluctuating electric field, the local field potential (LFP), which mainly originates from synchronous synaptic input into the local neural neighborhood. As shown by recent studies in visual and auditory cortices, the angular phase of the LFP at the time of spike generation adds significant extra information about the external world, beyond the one contained in the firing rate alone. However, no biologically plausible mechanism has yet been suggested that allows downstream neurons to infer the phase of the LFP at the soma of their pre-synaptic afferents. Therefore, so far there is no evidence that the nervous system can process phase information. Here we study a model of a bursting pyramidal neuron, driven by a time-dependent stimulus. We show that the number of spikes per burst varies systematically with the phase of the fluctuating input at the time of burst onset. The mapping between input phase and number of spikes per burst is a robust response feature for a broad range of stimulus statistics. Our results suggest that cortical bursting neurons could play a crucial role in translating LFP phase information into an easily decodable spike count code.
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.
The responses of neocortical cells to sensory stimuli are variable and state-dependent. It has been hypothesized that intrinsic cortical dynamics play an important role in trial-to-trial variability; the precise nature of this dependence, however, is poorly understood. We show here that in auditory cortex of urethane-anesthetized rats, population responses to click stimuli can be quantitatively predicted on a trial-by-trial basis by a simple dynamical system model estimated from spontaneous activity immediately preceding stimulus presentation. Changes in cortical state correspond consistently to changes in model dynamics, reflecting a nonlinear self-exciting system in synchronized states and an approximately linear system in desynchronized states. We propose that the complex and state-dependent pattern of trial-to-trial variability can be explained by a simple principle: that sensory responses are shaped by the same intrinsic dynamics that govern ongoing spontaneous activity.
cortex; dynamics; state; auditory; dynamical system; variability
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.
human; auditory cortex; spiking activity; local field potentials (LFP)
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.
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.
Memories are thought to be encoded as a distributed representation in the neocortex. The medial prefrontal cortex (mPFC) has been shown to support the expression of memories that initially depend on the hippocampus (HPC), yet the mechanisms by which the HPC and mPFC access the distributed representations in the neocortex are unknown. By measuring phase synchronization of local field potential (LFP) oscillations, we found that learning initiated changes in neuronal communication of the HPC and mPFC with the lateral entorhinal cortex (LEC), an area that is connected with many other neocortical regions. LFPs were recorded simultaneously from the three brain regions while rats formed an association between an auditory stimulus (CS) and eyelid stimulation (US) in a trace eyeblink conditioning paradigm, as well as during retention 1 month following learning. Over the course of learning, theta oscillations in the LEC and mPFC became strongly synchronized following presentation of the CS on trials in which rats exhibited a conditioned response (CR), and this strengthened synchronization was also observed during remote retention. In contrast, CS-evoked theta synchronization between the LEC and HPC decreased with learning. Our results suggest that communication between the LEC and mPFC are strengthened with learning whereas the communication between the LEC and HPC are concomitantly weakened, suggesting that enhanced LEC–mPFC communication may be a neuronal correlate for theoretically proposed neocortical reorganization accompanying encoding and consolidation of a memory.
consolidation; episodic memory; trace conditioning; EEG; rats
Neuronal oscillations in the gamma frequency range have been reported in many cortical areas, but the role they play in cortical processing remains unclear. We tested a recently proposed hypothesis that the intensity of sensory input is coded in the timing of action potentials relative to the phase of gamma oscillations, thus converting amplitude information to a temporal code. We recorded spikes and local field potential (LFP) from secondary somatosensory (SII) cortex in awake monkeys while presenting a vibratory stimulus at different amplitudes. We developed a novel technique based on matching pursuit to study the interaction between the highly transient gamma oscillations and spikes with high time-frequency resolution. We found that spikes were weakly coupled to LFP oscillations in the gamma frequency range (40−80 Hz), and strongly coupled to oscillations in higher gamma frequencies. However, the phase relationship of neither low-gamma nor high-gamma oscillations changed with stimulus intensity, even with a ten-fold increase. We conclude that, in SII, gamma oscillations are synchronized with spikes, but their phase does not vary with stimulus intensity. Furthermore, high-gamma oscillations (>60 Hz) appear to be closely linked to the occurrence of action potentials, suggesting that LFP high-gamma power could be a sensitive index of the population firing rate near the microelectrode.
Secondary somatosensory cortex; gamma; high-gamma; phase coding; local field potential; matching pursuit
When a cortical neuron is repeatedly injected with the same fluctuating current stimulus (frozen noise) the timing of the spikes is highly precise from trial to trial and the spike pattern appears to be unique. We show here that the same repeated stimulus can produce more than one reliable temporal pattern of spikes. A new method is introduced to find these patterns in raw multitrial data and is tested on surrogate data sets. Using it, multiple coexisting spike patterns were discovered in pyramidal cells recorded from rat prefrontal cortex in vitro, in data obtained in vivo from the middle temporal area of the monkey (Buracas et al., 1998) and from the cat lateral geniculate nucleus (Reinagel and Reid, 2002). The spike patterns lasted from a few tens of milliseconds in vitro to several seconds in vivo. We conclude that the prestimulus history of a neuron may influence the precise timing of the spikes in response to a stimulus over a wide range of time scales.
cluster; lateral geniculate (LGB, LGN); network; synapse; vision; MT
In the primate visual cortex, the phase of spikes relative to oscillations in the local field potential (LFP) in the gamma frequency range (30–80 Hz) can be shifted by stimulus features such as orientation and thus the phase may carry information about stimulus identity. According to the principle of communication through coherence (CTC), the relative LFP phase between the LFPs in the sending and receiving circuits affects the effectiveness of the transmission. CTC predicts that phase shifting can be used for stimulus selection. We review and investigate phase shifting in models of periodically driven single neurons and compare it with phase shifting in models of cortical networks. In a single neuron, as the driving current is increased, the spike phase varies systematically while the firing rate remains constant. In a network model of reciprocally connected excitatory (E) and inhibitory (I) cells phase shifting occurs in response to both injection of constant depolarizing currents and to brief pulses to I cells. These simple models provide an account for phase-shifting observed experimentally and suggest a mechanism for implementing CTC. We discuss how this hypothesis can be tested experimentally using optogenetic techniques.
attention; gamma oscillations; synchrony; phase shifting; phase locking
Cortical circuits spontaneously generate coordinated activity even in the absence of external inputs. The character of this activity depends on cortical state. We investigated how state affects the organization of spontaneous activity across layers of rat auditory cortex in vivo, using juxtacellular recording of morphologically identified neurons and large-scale electrophysiological recordings. Superficial pyramidal cells (PCs) and putative fast-spiking interneurons (FSs) were consistently suppressed during cortical desynchronization. PCs in deep layers showed heterogeneous responses to desynchronization, with some cells showing increased rates, typically large tufted PCs of high baseline firing rate, but not FSs. Consistent results were found between desynchronization occurring spontaneously in unanesthetized animals, and desynchronization evoked by electrical stimulation of the pedunculopontine tegmental (PPT) nucleus under urethane anesthesia. We hypothesize that reduction in superficial layer firing may enhance the brain's extraction of behaviorally relevant signals from noisy brain activity.
sensory cortex; cell-type; cortical circuit; ensemble recording; slow oscillation
Characterizing the functional connectivity between neurons is key for understanding brain function. We recorded spikes and local field potentials (LFP) from multi-electrode arrays implanted in monkey visual cortex to test the hypotheses that spikes generated outward traveling LFP waves and the strength of functional connectivity depended on stimulus contrast, as described recently. These hypotheses were proposed based on the observation that the latency of the peak negativity of the spike-triggered LFP average (STA) increased with distance between the spike and LFP electrodes, and the magnitude of the STA negativity and the distance over which it was observed decreased with increasing stimulus contrast. Detailed analysis of the shape of the STA, however, revealed contributions from two distinct sources – a transient negativity in the LFP locked to the spike (∼0 ms) that attenuated rapidly with distance, and a low frequency rhythm with peak negativity ∼25 ms after the spike that attenuated slowly with distance. The overall negative peak of the LFP, which combined both these components, shifted from ∼0 to ∼25 ms going from electrodes near the spike to electrodes far from the spike, giving an impression of a traveling wave, although the shift was fully explained by changing contributions from the two fixed components. The low frequency rhythm was attenuated during stimulus presentations, decreasing the overall magnitude of the STA. These results highlight the importance of accounting for the network activity while using STAs to determine functional connectivity.
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.
LFP; area V1; striate cortex; orientation selectivity; visual cortex; receptive field
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.
Information theory; Vision; Audition; Population coding; Oscillations; Firing rates
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.
The hypothesis that cortical networks employ the coordinated activity of groups of neurons, termed assemblies, to process information is debated. Results from multiple single-unit recordings are not conclusive because of the dramatic undersampling of the system. However, the local field potential (LFP) is a mesoscopic signal reflecting synchronized network activity. This raises the question whether the LFP can be employed to overcome the problem of undersampling. In a recent study in the motor cortex of the awake behaving monkey based on the locking of coincidences to the LFP we determined a lower bound for the fraction of spike coincidences originating from assembly activation. This quantity together with the locking of single spikes leads to a lower bound for the fraction of spikes originating from any assembly activity. Here we derive a statistical method to estimate the fraction of spike synchrony caused by assemblies—not its lower bound—from the spike data alone. A joint spike and LFP surrogate data model demonstrates consistency of results and the sensitivity of the method. Combining spike and LFP signals, we obtain an estimate of the fraction of spikes resulting from assemblies in the experimental data.
LFP; Synchrony; Oscillations; Network dynamics; Motor cortex
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.
evoked potentials; familiarity; local field; monkey; novelty; potentials
Memory and its underlying neural plasticity play important roles in sensory discrimination and cortical pattern recognition in olfaction. Given the reported function of slow-wave sleep states in neocortical and hippocampal memory consolidation, we hypothesized that activity during slow-wave states within the piriform cortex may be shaped by recent olfactory experience. Rats were anesthetized with urethane and allowed to spontaneously shift between slow-wave and fast-wave states as recorded in LFPs within the anterior piriform cortex. Single-unit activity of piriform cortical layer II/III neurons was recorded simultaneously. The results suggest that piriform cortical activity during slow-wave states is shaped by recent (several minutes) odor experience. The temporal structure of single-unit activity during slow-waves was modified if the animal had been stimulated with an odor within that cell’s receptive field. If no odor had been delivered, the activity of the cell during slow-wave activity was stable across the two periods. The results demonstrate that piriform cortical activity during slow-wave state is shaped by recent odor experience, which could contribute to odor memory consolidation.
memory; consolidation; sleep; olfaction; perceptual learning; slow-wave state
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.
The basolateral amygdala (BLA) mediates the facilitating effects of emotions on memory. The BLA enhancing influence extends to various types of memories, including striatal–dependent habit formation. To shed light on the underlying mechanisms, we performed unit and local field potentials (LFP) recordings in BLA, striatum, auditory cortex, and intralaminar thalamus in cats trained on a stimulus-response task where the presentation of one of two tones (CS+) predicted reward delivery. The coherence of BLA but not cortical or thalamic LFPs was highest with striatal gamma activity and intra-BLA muscimol infusions selectively reduced striatal gamma power. Moreover, coupling of BLA-striatal unit activity increased when LFP gamma power augmented. Early in training, the CS+ and unrewarded tone elicited a modest increase in coherent BLA-striatal gamma. As learning progressed, this gamma coupling selectively increased in relation to the CS+. Thus, coherent gamma oscillations coordinate amygdalostriatal interactions during learning and might facilitate synaptic plasticity.
Stimulus-evoked oscillatory synchronization of neurons has been observed in a wide range of species. Here, we combined genetic strategies with paired intracellular and local field potential (LFP) recordings from the intact brain of Drosophila to study mechanisms of odor-evoked neural oscillations. We found common food odors at natural concentrations elicited oscillations in LFP recordings made from the mushroom body (MB), a site of sensory integration and analogous to the vertebrate pyriform cortex. The oscillations were reversibly abolished by application of the GABAa blocker picrotoxin. Intracellular recordings from local and projection neurons within the antennal lobe (AL, analogous to the olfactory bulb) revealed odor-elicited spikes and sub-threshold membrane potential oscillations that were tightly phase-locked to LFP oscillations recorded downstream in the MBs. These results suggested that, as in locusts, odors may elicit the oscillatory synchronization of AL neurons by means of GABAergic inhibition from local neurons (LNs). An analysis of the morphologies of genetically distinguished LNs revealed two populations of GABAergic neurons in the AL. One population of LNs innervated parts of glomeruli lacking terminals of receptor neurons, whereas the other branched more widely, innervating throughout the glomeruli, suggesting the two populations might participate in different neural circuits. To test the functional roles of these LNs, we used the temperature-sensitive dynamin mutant gene, shibire, to conditionally and reversibly block chemical transmission from each or both of these populations of LNs. We found only the more widely branching population of LNs is necessary for generating odor-elicited oscillations.
antennal lobe; local neuron; mushroom body; olfaction; coding; synchrony
The goal of the present study was to determine the phase relationships of the slow oscillatory activity that emerges in basal ganglia nuclei in anesthetized rats after dopamine cell lesion in order to gain insight into the passage of this oscillatory activity through the basal ganglia network. Spike train recordings from striatum, subthalamic nucleus (STN), globus pallidus (GP), and substantia nigra pars reticulata (SNpr) were paired with simultaneous local field potential (LFP) recordings from SNpr or motor cortex ipsilateral to a unilateral lesion of substantia nigra dopamine neurons in urethane anesthetized rats. Dopamine cell lesion induced a striking increase in incidence of slow oscillations (0.3-2.5 Hz) in firing rate in all nuclei. Phase relationships assessed through paired recordings using SNpr LFP as a temporal reference showed that slow oscillatory activity in GP spike trains is predominantly antiphase with oscillations in striatum, and slow oscillatory activity in STN spike trains is in-phase with oscillatory activity in cortex but predominantly antiphase with GP oscillatory activity. Taken together, these results imply that after dopamine cell lesion in urethane anesthetized rats, increased oscillatory activity in GP spike trains is shaped more by increased phasic inhibitory input from the striatum than by phasic excitatory input from STN. In addition, results show that oscillatory activity in SNpr spike trains is typically antiphase with GP oscillatory activity and in-phase with STN oscillatory activity. While these observations do not rule out additional mechanisms contributing to the emergence of slow oscillations in the basal ganglia after dopamine cell lesion in the anesthetized preparation, they are compatible with 1) increased oscillatory activity in the GP facilitated by an effect of dopamine loss on striatal ‘filtering’ of slow components of oscillatory cortical input, 2) increased oscillatory activity in STN spike trains supported by convergent antiphase inhibitory and excitatory oscillatory input from GP and cortex, respectively, and 3) increased oscillatory activity in SNpr spike trains organized by convergent antiphase inhibitory and excitatory oscillatory input from GP and STN, respectively.
Parkinson’s disease; subthalamic nucleus; substantia nigra; globus pallidus; striatum; bursting; local field potentials