Balanced excitation and inhibition: Model based analysis of local field potentials (original) (raw)
Related papers
Modelling and analysis of local field potentials for studying the function of cortical circuits
2013
Electrical signals from the cortical surface of animals were recorded as early as 1875 (REF. 1), 50 years before the advent of electroencephalography (EEG) 2 . Subsequent work revealed that the high-frequency part (above ~500 Hz) of the recorded potentials provides information about the spiking activity of neurons located around the electrode 3 . By contrast, the part of the signal that has frequencies below ~500 Hz, the so-called 'local field potential' (LFP), was found more difficult to interpret in terms of the underlying neural activity. Although the introduction of current source density (CSD) analysis in the 1950s 4 rejuvenated the use of the LFP in the following decades 5-7 , interest decreased in the 1980s and 1990s, probably owing to the focus on new single-neuron techniques (for example, patch-clamp recordings) and on understanding the link between single-neuron activity and perception.
Reconstruction of post-synaptic potentials by reverse modeling of local field potentials
Journal of Neural Engineering
Among electrophysiological signals, Local Field Potentials (LFPs) are extensively used to study brain activity, either in vivo or in vitro. LFPs are recorded with extracellular electrodes implanted in brain tissue. They reflect intermingled excitatory and inhibitory processes in neuronal assemblies. In cortical structures, LFPs mainly originate from the summation of post-synaptic potentials (PSPs), either excitatory (ePSPs) or inhibitory (iPSPs) generated at the level of pyramidal cells. The challenging issue, addressed in this paper, is to estimate, from a single extracellularlyrecorded signal, both ePSP and iPSP components of the LFP. The proposed method is based on a model-based reverse engineering approach in which the measured LFP is fed into a physiologically-grounded neural mass model (mesoscopic level) to estimate the synaptic activity of a sub-population of pyramidal cells interacting with local GABAergic interneurons. The method was first validated using simulated LFPs for which excitatory and inhibitory components are known a priori and can thus serve as a ground truth. It was then evaluated on in vivo data (PTZ-induced seizures, rat; PTZinduced excitability increase, mouse; epileptiform discharges, mouse) and on in clinico data (human seizures recorded with depth-EEG electrodes). Under these various conditions, results showed that the proposed reverse engineering method provides a reliable estimation of the average excitatory and inhibitory post-synaptic potentials originating of the measured LFPs. They also indicated that the method allows for monitoring of the excitation/inhibition ratio. The method has potential for multiple applications in neuroscience, typically when a dynamical tracking of local excitability changes is required.
INTRODUCTION: 1. Backpropagating spikes in pyramidal neurons follow an activation sequence. They contribute as much as 40% to the antidromic population spike amplitude. 2. Recent work showed the exact propagation of the depolarization of these back propagating spikes. 3. The strength and attenuation in a burst of backpropagating spikes varies between different neuronal types. 4. Dendritic branching and diameter are important for analyzing the genesis of MEG and EEG signals. 5. A net intracellular current dipole, Q, in each cell and each cell compartment can be calculated. METHODS: We take data from detailed computational models of pyramidal cells in the hippocampus. We then calculate the extracellular field that can be generated when a population of backpropagating spikes moves synchronously in a wave-like pattern. We use the mathematical formalism described in Gomez-Molina, Restrepo and Botero, 2015. The field in certain points is also calculated based on depolarizations that follows alpha and gabor functions. Computer simulations for discrete states vs. continuous functions are both run in MATLAB. Additional analysis was done using Python-NEURON for user-interfaces. We explore computationally what physiological variables are relevant for scaling and field wave- form. DISCUSSION: 1. Does the relative contribution of backpropagation vs. forward depolarizations depend on the population EPSP vs. pIPSP? 2. Can they explain the peak and valleys of the Sharp wave–ripple complexes? 3. In which conditions and scenarios the use of discrete states is a good simplification? PRELIMINARY CONCLUSION: For electrodes located at a long distant d from the source, the selection of source-model can be more important than the determination of the exact spatial position of the source in the dendrite. KEY WORDS: backpropagating action potential, pyramidal neurons, dendrites, extracellular potentials, waves, EEG Submitted by May/2016. PI, Initiative,development and Implementation: Juan Fernando Gomez Molina, International Group of Neuroscience, IGN. ACKNOWLEDGMENT. I am thankful to Dr. J. C. Bel for his advice and feedback and to Dr. R.M. for his assistance with software.
PLoS ONE, 2013
Fluctuations in successive waves of oscillatory local field potentials (LFPs) reflect the ongoing processing of neuron populations. However, their amplitude, polarity and synaptic origin are uncertain due to the blending of electric fields produced by multiple converging inputs, and the lack of a baseline in standard AC-coupled recordings. Consequently, the estimation of underlying currents by laminar analysis yields spurious sequences of inward and outward currents. We devised a combined analytical/experimental approach that is suitable to study laminated structures. The approach was essayed on an experimental oscillatory LFP as the Schaffer-CA1 gamma input in anesthetized rats, and it was verified by parallel processing of model LFPs obtained through a realistic CA1 aggregate of compartmental units. This approach requires laminar LFP recordings and the isolation of the oscillatory input from other converging pathways, which was achieved through an independent component analysis. It also allows the spatial and temporal components of pathway-specific LFPs to be separated. While reconstructed Schaffer-specific LFPs still show spurious inward/outward current sequences, these were clearly stratified into distinct subcellular domains. These spatial bands guided the localized delivery of neurotransmitter blockers in experiments. As expected, only Glutamate but not GABA blockers abolished Schaffer LFPs when applied to the active but not passive subcellular domains of pyramidal cells. The known chemical nature of the oscillatory LFP allowed an empirical offset of the temporal component of Schaffer LFPs, such that following reconstruction they yield only sinks or sources at the appropriate sites. In terms of number and polarity, some waves increased and others decreased proportional to the concomitant inputs in native multisynaptic LFPs. Interestingly, the processing also retrieved the initiation time for each wave, which can be used to discriminate afferent from postsynaptic cells in standard spike-phase correlations. The applicability of this approach to other pathways and structures is discussed.
Understanding population activities of underlying neurons reveal emergent behavior as patterns of information flow in neural circuits. Evoked local field potentials (LFPs) arise from complex interactions of spatial distribution of current sources, time dynamics, and spatial distribution of dipoles apart underlying conductive properties of the extracellular medium. We reconstructed LFP to test and parameterize the molecular mechanisms of cellular function with network properties. The sensitivity of LFP to local excitatory and inhibitory connections was tested using two novel techniques. In the first, we used a single granule neuron as a model kernel for reconstructing population activity. The second technique consisted using a detailed network model. LTP and LTD regulating the spatiotemporal pattern of granular layer responses to mossy fiber inputs was studied. The effect of changes in synaptic release probability and modulation in intrinsic excitability of granule cell on LFP was studied. The study revealed cellular function and plasticity were represented in LFP wave revealing the activity of underlying neurons. Changes to single cell properties during LTP and LTD were reflected in the LFP wave suggesting the sparse recoding function of granule neurons as spatial pattern generators. Both modeling approaches generated LFP in vitro and in vivo waveforms as reported in experiments and predict that the expression mechanisms revealed in vitro can explain the LFP changes associated with LTP and LTD in vivo.
Journal of Neurophysiology, 2010
Korovaichuk A, Makarova J, Makarov VA, Benito N, Herreras O. Minor contribution of principal excitatory pathways to hippocampal LFPs in the anesthetized rat: A combined independent component and current source density study. Analysis of local field potentials (LFPs) helps understand the function of the converging neuronal populations that produce the mixed synaptic activity in principal cells. Recently, using independent component analysis (ICA), we resolved ongoing hippocampal activity into several major contributions of stratified LFP-generators. Here, using pathway-specific LFP reconstruction, we isolated LFP-generators that describe the activity of Schaffer-CA1 and Perforant-Dentate excitatory inputs in the anesthetized rat. First, we applied ICA and current source density analysis to LFPs evoked by electrical subthreshold stimulation of the pathways. The results showed that pathway specific activity is selectively captured by individual components or LFPgenerators. Each generator matches the known distribution of axonal terminal fields in the hippocampus and recovers the specific time course of their activation. Second, we use sparse weak electrical stimulation to prime ongoing LFPs with activity of a known origin. Decomposition of ongoing LFPs yields a few significant LFP-generators with distinct spatiotemporal characteristics for the Schaffer and Perforant inputs. Both pathways convey an irregular temporal pattern in bouts of population activity of varying amplitude. Importantly, the contribution of Schaffer and Perforant inputs to the power of raw LFPs in the hippocampus is minor (7 and 5%, respectively). The results support the hypothesis on a sparse population code used by excitatory populations in the entorhino-hippocampal system, and they validate the separation of LFP-generators as a powerful tool to explore the computational function of neuronal circuits in real time.
Journal of Computational Neuroscience manuscript No. (will be inserted by the editor)
2016
We examine the properties of the transfer function F T = V m /V LFP between the intracellular membrane potential (V m) and the local field potential (V LFP) in cerebral cortex. We first show theoretically that, in the subthreshold regime, the frequency dependence of the extracellular medium and that of the membrane potential have a clear incidence on F T. The calculation of F T from experiments and the matching with theoretical expressions is possible for desynchronized states where individual current sources can be considered as independent. Using a mean-field approximation, we obtain a method to estimate the impedance of the extracellular medium without injecting currents. We examine the transfer function for bipolar (differential) LFPs and compare to simultaneous recordings of V m and V LFP during desynchronized states in rat barrel cortex in vivo. The experimentally derived F T matches the one derived theoretically, only if one assumes that the impedance of the extracellular medium is frequency-dependent, and varies as 1/ √ ω (Warburg impedance) for frequencies between 3 and 500 Hz. This constitutes indirect evidence that the extracellular medium is non-resistive, which has many possible consequences for modeling LFPs.
2009
Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs) (a circuit property) and spiking multiunit activity (MUA). Recently, there has been increased interest in LFPs because of their correlation with functional magnetic resonance imaging blood oxygenation level-dependent measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same electrode or nearby electrodes. We used "signal estimation theory" to show that a linear filter operation on the activity of one or a few neurons can explain a significant fraction of the LFP time course in the macaque monkey primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positive time lags. The filter was similar across different neocortical regions and behavioral conditions, including spontaneous activity and visual stimulation. The estimations had a spatial resolution of ϳ1 mm and a temporal resolution of ϳ200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than the negative time lags. Additionally, we showed that spikes occurring within ϳ10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In summary, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons.
Neuroelectric potentials derived from an extended version of the Hodgkin-Huxley model
Journal of Theoretical Biology, 1966
In 1952, Hodgkin and Huxley and others generated a revolution in our concept of the axon membrane and how it propagates the action potential. In 1959, Bullock described another revolution, a "quiet revolution" in our concept of the functions performed by the remainder of the nerve cell. In this paper we have attempted to show a possible connection between these two revolutions. We have proposed that a single unifying concept, that of the Modem Ionic Hypothesis, can account for almost all of the diverse behavior described by Bullock. In addition, we have attempted to demonstrate the value of electronic analogs in the study of systems as complex as that of the neural membrane.