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What is measured by electroencephalograms and local field potentials?

What is measured by electroencephalograms and local field potentials?


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In the Scholarpedia article on local field potentials (2013), I read:

The current view is that EEG and LFPs are generated by synchronized synaptic currents arising on cortical neurons, possibly through the formation of dipoles (Niedermeyer and Lopes da Silva, 1998; Nunez and Srinivasan, 2005).

There are three things I do not understand:

  1. What does "on neurons" mean? Why not "in" or "around neurons"?
  2. I assume that what is measured is the electric potential in an electric field that is generated by charges (the ions). So only the changes of the measured potential are due to currents, the potential itself (at any given point in time) is only due to the distribution of charges. Is that view correct? Independent of the nature of the charges.
  3. What exactly are the above mentioned dipoles? Of which are they formed and what is their size? (At least, the article says "possibly generated through the formation of dipoles".)

Does all this sum up to the picture that it is all and only about the ions that pass through the ligand-gated channels at a synapse and the electric field and potential generated by them, the contribution of all other charges being cancelled and filtered out?


[I give this as a sketchy answer being aware that it might be nonsense. So feel free to downvote in this case. I should have mentioned - thanks to Bryan for having remembered me - that this answer has been inspired by Buzsáki/Anastassiou/Koch's article on The origin of extracellular fields and currents and just tries to sketch the mental image this article evoked in me.]

I assume that what is actually measured by an EEG electrode is an effective dipole moment in the upper cortical layers underneath the electrode (which decays with $1/r^2$). The way this dipole moment is created by "brain currents" is the matter of this answer.

There seem to be some premises under which a measurable EEG signal (= a dipole) can be detected:

  1. The presynaptic action potentials must arrive highly synchronized. (Additive superposition.).

  2. The apic dendrites of the pyramidal neurons that give rise to the dipole must be vertically oriented (pointing to the skull, resp. the electrode). (Orientation of the dipole.)

  3. The sodium potassium pumps trying to restore the rest potential are unevenly distributed, i.e. mainly located at the soma. (Breaking the symmetry.)

This is the situation for the neuron (gray) at rest:

The dipole then forms as follows in three steps:

Step 1: An presynaptic action potential releases neurotransmitters that open ligand-gated ion channels causing sodium ions to enter the neuron.

Step 2: The extra sodium ions wander quickly to the soma. This happens passively, i.e. driven by repulsion and diffusion. At the end of step 2, all ions inside the neuron are distributed approximately evenly (i.e. not giving rise to an inner dipole).

Step 3: At the soma sodium ions are pumped out of the neuron. During this step equidistribution of ions is maintained inside the neuron (still no dipole inside the neuron).

In the extracellular medium, we now have an observable dipole.

Summary: What is measured by an EEG are not directly "brain currents" but an effective dipole moment that results from three different currents on different time scales:

  1. Ions passing the membrane of apic dendrites into the neuron. (Slow.)
  2. A net flow of ions wandering from dendrite to soma (driven by repulsion and diffusion). (Fast.)
  3. Ions leaving the soma, e.g. by sodium pottasium pumps. (Slow.)

1) Is on neurons because here neurons are considered as population, in this case the cortical neurons.

2) Yes this point of view is correct since the electric potential is generate by charges present outside and inside of the cell. Is the movement of this charge that could generate the electric field.

3)According to wikipedia

An electric dipole is a separation of positive and negative charges. The simplest example of this is a pair of electric charges of equal magnitude but opposite sign, separated by some (usually small) distance

In this case the cortical neurons have some zone where they are positive charges and other zone where they are negatively charged give to them the propriety to be considered as dipole.

The ability to generate a potential by neurons is due by the ions that pass through the channel that could be voltage-gate (open when a specific potential is reach) or ligand-gate (active in presence of a ligand). Depending on the concentration of a specific ions found inside and outside of neurons, this ion can exit or enter the cell if the correct channel is open.

Hope this could help you.


Even though this image is to depict the neuronal origins of the fMRI hemodynamic response, doesn't it also depict quite well the neural origins of the EEG response:

from Scott Huettel, Neuroimaging the Aging Mind, p. 14


Summary

Electroencephalography (EEG) is the non-invasive measurement of the brain’s electric fields. Electrodes placed on the scalp record voltage potentials resulting from current flow in and around neurons. EEG is nearly a century old: this long history has afforded EEG a rich and diverse spectrum of applications. On the one hand, foundations of EEG in clinical diagnostics have dovetailed more recently into brain-triggered neurorehabilitation treatments. On the other hand, EEG has not only been a workhorse for providing brain correlates of constructs in the field of experimental psychology, but has also been used as a true neuroimaging method with more recent extensions in translational as well as computational neuroscience. The versatility and accessibility of the technique, in combination with advances in signal processing, allow for this ‘old dog’ to still deliver new tricks and innovations.


Contents

Classical electrophysiological techniques Edit

Principle and mechanisms Edit

Electrophysiology is the branch of physiology that pertains broadly to the flow of ions (ion current) in biological tissues and, in particular, to the electrical recording techniques that enable the measurement of this flow. Classical electrophysiology techniques involve placing electrodes into various preparations of biological tissue. The principal types of electrodes are:

  1. simple solid conductors, such as discs and needles (singles or arrays, often insulated except for the tip),
  2. tracings on printed circuit boards or flexible polymers, also insulated except for the tip, and
  3. hollow tubes filled with an electrolyte, such as glass pipettes filled with potassium chloride solution or another electrolyte solution.

The principal preparations include:

  1. living organisms,
  2. excised tissue (acute or cultured),
  3. dissociated cells from excised tissue (acute or cultured),
  4. artificially grown cells or tissues, or
  5. hybrids of the above.

Neuronal electrophysiology is the study of electrical properties of biological cells and tissues within the nervous system. With neuronal electrophysiology doctors and specialists can determine how neuronal disorders happen, by looking at the individual's brain activity. Activity such as which portions of the brain light up during any situations encountered. If an electrode is small enough (micrometers) in diameter, then the electrophysiologist may choose to insert the tip into a single cell. Such a configuration allows direct observation and recording of the intracellular electrical activity of a single cell. However, this invasive setup reduces the life of the cell and causes a leak of substances across the cell membrane. Intracellular activity may also be observed using a specially formed (hollow) glass pipette containing an electrolyte. In this technique, the microscopic pipette tip is pressed against the cell membrane, to which it tightly adheres by an interaction between glass and lipids of the cell membrane. The electrolyte within the pipette may be brought into fluid continuity with the cytoplasm by delivering a pulse of negative pressure to the pipette in order to rupture the small patch of membrane encircled by the pipette rim (whole-cell recording). Alternatively, ionic continuity may be established by "perforating" the patch by allowing exogenous pore-forming agent within the electrolyte to insert themselves into the membrane patch (perforated patch recording). Finally, the patch may be left intact (patch recording).

The electrophysiologist may choose not to insert the tip into a single cell. Instead, the electrode tip may be left in continuity with the extracellular space. If the tip is small enough, such a configuration may allow indirect observation and recording of action potentials from a single cell, termed single-unit recording. Depending on the preparation and precise placement, an extracellular configuration may pick up the activity of several nearby cells simultaneously, termed multi-unit recording.

As electrode size increases, the resolving power decreases. Larger electrodes are sensitive only to the net activity of many cells, termed local field potentials. Still larger electrodes, such as uninsulated needles and surface electrodes used by clinical and surgical neurophysiologists, are sensitive only to certain types of synchronous activity within populations of cells numbering in the millions.

Other classical electrophysiological techniques include single channel recording and amperometry.

Electrographic modalities by body part Edit

Electrophysiological recording in general is sometimes called electrography (from electro- + -graphy, "electrical recording"), with the record thus produced being an electrogram. However, the word electrography has other senses (including electrophotography), and the specific types of electrophysiological recording are usually called by specific names, constructed on the pattern of electro- + [body part combining form] + -graphy (abbreviation ExG). Relatedly, the word electrogram (not being needed for those other senses) often carries the specific meaning of intracardiac electrogram, which is like an electrocardiogram but with some invasive leads (inside the heart) rather than only noninvasive leads (on the skin). Electrophysiological recording for clinical diagnostic purposes is included within the category of electrodiagnostic testing. The various "ExG" modes are as follows:

Modality Abbreviation Body part Prevalence in clinical use
electrocardiography ECG or EKG heart (specifically, the cardiac muscle), with cutaneous electrodes (noninvasive) 1—very common
electroatriography EAG atrial cardiac muscle 3—uncommon
electroventriculography EVG ventricular cardiac muscle 3—uncommon
intracardiac electrogram EGM heart (specifically, the cardiac muscle), with intracardiac electrodes (invasive) 2—somewhat common
electroencephalography EEG brain (usually the cerebral cortex), with extracranial electrodes 2—somewhat common
electrocorticography ECoG or iEEG brain (specifically the cerebral cortex), with intracranial electrodes 2—somewhat common
electromyography EMG muscles throughout the body (usually skeletal, occasionally smooth) 1—very common
electrooculography EOG eye—entire globe 2—somewhat common
electroretinography ERG eye—retina specifically 2—somewhat common
electronystagmography ENG eye—via the corneoretinal potential 2—somewhat common
electroolfactography EOG olfactory epithelium in mammals 3—uncommon
electroantennography EAG olfactory receptors in arthropod antennae 4—not applicable clinically
electrocochleography ECOG or ECochG cochlea 2—somewhat common
electrogastrography EGG stomach smooth muscle 2—somewhat common
electrogastroenterography EGEG stomach and bowel smooth muscle 2—somewhat common
electroglottography EGG glottis 3—uncommon
electropalatography EPG palatal contact of tongue 3—uncommon
electroarteriography EAG arterial flow via streaming potential detected through skin [2] 3—uncommon
electroblepharography EBG eyelid muscle 3—uncommon
electrodermography EDG skin 3—uncommon
electrohysterography EHG uterus 3—uncommon
electroneuronography ENeG or ENoG nerves 3—uncommon
electropneumography EPG lungs (chest movements) 3—uncommon
electrospinography ESG spinal cord 3—uncommon
electrovomerography EVG vomeronasal organ 3—uncommon

Optical electrophysiological techniques Edit

Optical electrophysiological techniques were created by scientists and engineers to overcome one of the main limitations of classical techniques. Classical techniques allow observation of electrical activity at approximately a single point within a volume of tissue. Classical techniques singularize a distributed phenomenon. Interest in the spatial distribution of bioelectric activity prompted development of molecules capable of emitting light in response to their electrical or chemical environment. Examples are voltage sensitive dyes and fluorescing proteins.

After introducing one or more such compounds into tissue via perfusion, injection or gene expression, the 1 or 2-dimensional distribution of electrical activity may be observed and recorded.

Intracellular recording involves measuring voltage and/or current across the membrane of a cell. To make an intracellular recording, the tip of a fine (sharp) microelectrode must be inserted inside the cell, so that the membrane potential can be measured. Typically, the resting membrane potential of a healthy cell will be -60 to -80 mV, and during an action potential the membrane potential might reach +40 mV. In 1963, Alan Lloyd Hodgkin and Andrew Fielding Huxley won the Nobel Prize in Physiology or Medicine for their contribution to understanding the mechanisms underlying the generation of action potentials in neurons. Their experiments involved intracellular recordings from the giant axon of Atlantic squid (Loligo pealei), and were among the first applications of the "voltage clamp" technique. [3] Today, most microelectrodes used for intracellular recording are glass micropipettes, with a tip diameter of < 1 micrometre, and a resistance of several megohms. The micropipettes are filled with a solution that has a similar ionic composition to the intracellular fluid of the cell. A chlorided silver wire inserted into the pipet connects the electrolyte electrically to the amplifier and signal processing circuit. The voltage measured by the electrode is compared to the voltage of a reference electrode, usually a silver chloride-coated silver wire in contact with the extracellular fluid around the cell. In general, the smaller the electrode tip, the higher its electrical resistance, so an electrode is a compromise between size (small enough to penetrate a single cell with minimum damage to the cell) and resistance (low enough so that small neuronal signals can be discerned from thermal noise in the electrode tip).

Voltage clamp Edit

The voltage clamp technique allows an experimenter to "clamp" the cell potential at a chosen value. This makes it possible to measure how much ionic current crosses a cell's membrane at any given voltage. This is important because many of the ion channels in the membrane of a neuron are voltage-gated ion channels, which open only when the membrane voltage is within a certain range. Voltage clamp measurements of current are made possible by the near-simultaneous digital subtraction of transient capacitive currents that pass as the recording electrode and cell membrane are charged to alter the cell's potential.

Current clamp Edit

The current clamp technique records the membrane potential by injecting current into a cell through the recording electrode. Unlike in the voltage clamp mode, where the membrane potential is held at a level determined by the experimenter, in "current clamp" mode the membrane potential is free to vary, and the amplifier records whatever voltage the cell generates on its own or as a result of stimulation. This technique is used to study how a cell responds when electric current enters a cell this is important for instance for understanding how neurons respond to neurotransmitters that act by opening membrane ion channels.

Most current-clamp amplifiers provide little or no amplification of the voltage changes recorded from the cell. The "amplifier" is actually an electrometer, sometimes referred to as a "unity gain amplifier" its main purpose is to reduce the electrical load on the small signals (in the mV range) produced by cells so that they can be accurately recorded by low-impedance electronics. The amplifier increases the current behind the signal while decreasing the resistance over which that current passes. Consider this example based on Ohm's law: A voltage of 10 mV is generated by passing 10 nanoamperes of current across 1 MΩ of resistance. The electrometer changes this "high impedance signal" to a "low impedance signal" by using a voltage follower circuit. A voltage follower reads the voltage on the input (caused by a small current through a big resistor). It then instructs a parallel circuit that has a large current source behind it (the electrical mains) and adjusts the resistance of that parallel circuit to give the same output voltage, but across a lower resistance.

Patch-clamp recording Edit

This technique was developed by Erwin Neher and Bert Sakmann who received the Nobel Prize in 1991. [4] Conventional intracellular recording involves impaling a cell with a fine electrode patch-clamp recording takes a different approach. A patch-clamp microelectrode is a micropipette with a relatively large tip diameter. The microelectrode is placed next to a cell, and gentle suction is applied through the microelectrode to draw a piece of the cell membrane (the 'patch') into the microelectrode tip the glass tip forms a high resistance 'seal' with the cell membrane. This configuration is the "cell-attached" mode, and it can be used for studying the activity of the ion channels that are present in the patch of membrane. If more suction is now applied, the small patch of membrane in the electrode tip can be displaced, leaving the electrode sealed to the rest of the cell. This "whole-cell" mode allows very stable intracellular recording. A disadvantage (compared to conventional intracellular recording with sharp electrodes) is that the intracellular fluid of the cell mixes with the solution inside the recording electrode, and so some important components of the intracellular fluid can be diluted. A variant of this technique, the "perforated patch" technique, tries to minimise these problems. Instead of applying suction to displace the membrane patch from the electrode tip, it is also possible to make small holes on the patch with pore-forming agents so that large molecules such as proteins can stay inside the cell and ions can pass through the holes freely. Also the patch of membrane can be pulled away from the rest of the cell. This approach enables the membrane properties of the patch to be analysed pharmacologically.

Sharp electrode recording Edit

In situations where one wants to record the potential inside the cell membrane with minimal effect on the ionic constitution of the intracellular fluid a sharp electrode can be used. These micropipettes (electrodes) are again like those for patch clamp pulled from glass capillaries, but the pore is much smaller so that there is very little ion exchange between the intracellular fluid and the electrolyte in the pipette. The electrical resistance of the micropipette electrode is reduced by filling with 2-4M KCl, rather than a salt concentration which mimics the intracellular ionic concentrations as used in patch clamping. [5] Often the tip of the electrode is filled with various kinds of dyes like Lucifer yellow to fill the cells recorded from, for later confirmation of their morphology under a microscope. The dyes are injected by applying a positive or negative, DC or pulsed voltage to the electrodes depending on the polarity of the dye.

Single-unit recording Edit

An electrode introduced into the brain of a living animal will detect electrical activity that is generated by the neurons adjacent to the electrode tip. If the electrode is a microelectrode, with a tip size of about 1 micrometre, the electrode will usually detect the activity of at most one neuron. Recording in this way is in general called "single-unit" recording. The action potentials recorded are very much like the action potentials that are recorded intracellularly, but the signals are very much smaller (typically about 1 mV). Most recordings of the activity of single neurons in anesthetized and conscious animals are made in this way. Recordings of single neurons in living animals have provided important insights into how the brain processes information. For example, David Hubel and Torsten Wiesel recorded the activity of single neurons in the primary visual cortex of the anesthetized cat, and showed how single neurons in this area respond to very specific features of a visual stimulus. [6] Hubel and Wiesel were awarded the Nobel Prize in Physiology or Medicine in 1981. [7]

Multi-unit recording Edit

If the electrode tip is slightly larger, then the electrode might record the activity generated by several neurons. This type of recording is often called "multi-unit recording", and is often used in conscious animals to record changes in the activity in a discrete brain area during normal activity. Recordings from one or more such electrodes that are closely spaced can be used to identify the number of cells around it as well as which of the spikes come from which cell. This process is called spike sorting and is suitable in areas where there are identified types of cells with well defined spike characteristics. If the electrode tip is bigger still, in general the activity of individual neurons cannot be distinguished but the electrode will still be able to record a field potential generated by the activity of many cells.

Field potentials Edit

Extracellular field potentials are local current sinks or sources that are generated by the collective activity of many cells. Usually, a field potential is generated by the simultaneous activation of many neurons by synaptic transmission. The diagram to the right shows hippocampal synaptic field potentials. At the right, the lower trace shows a negative wave that corresponds to a current sink caused by positive charges entering cells through postsynaptic glutamate receptors, while the upper trace shows a positive wave that is generated by the current that leaves the cell (at the cell body) to complete the circuit. For more information, see local field potential.

Amperometry Edit

Amperometry uses a carbon electrode to record changes in the chemical composition of the oxidized components of a biological solution. Oxidation and reduction is accomplished by changing the voltage at the active surface of the recording electrode in a process known as "scanning". Because certain brain chemicals lose or gain electrons at characteristic voltages, individual species can be identified. Amperometry has been used for studying exocytosis in the nervous and endocrine systems. Many monoamine neurotransmitters e.g., norepinephrine (noradrenalin), dopamine, and serotonin (5-HT) are oxidizable. The method can also be used with cells that do not secrete oxidizable neurotransmitters by "loading" them with 5-HT or dopamine.

Planar patch clamp is a novel method developed for high throughput electrophysiology. [8] Instead of positioning a pipette on an adherent cell, cell suspension is pipetted on a chip containing a microstructured aperture. A single cell is then positioned on the hole by suction and a tight connection (Gigaseal) is formed. The planar geometry offers a variety of advantages compared to the classical experiment:

  • It allows for integration of microfluidics, which enables automatic compound application for ion channel screening.
  • The system is accessible for optical or scanning probe techniques. of the intracellular side can be performed.

Schematic drawing of the classical patch clamp configuration. The patch pipette is moved to the cell using a micromanipulator under optical control. Relative movements between the pipette and the cell have to be avoided in order to keep the cell-pipette connection intact.

Scanning electron microscope image of a patch pipette.

In planar patch configuration, the cell is positioned by suction. Relative movements between cell and aperture can then be excluded after sealing. An antivibration table is not necessary.

Scanning electron microscope image of a planar patch clamp chip. Both the pipette and the chip are made from borosilicate glass.

Solid-supported membrane (SSM)-based Edit

With this electrophysiological approach, proteoliposomes, membrane vesicles, or membrane fragments containing the channel or transporter of interest are adsorbed to a lipid monolayer painted over a functionalized electrode. This electrode consists of a glass support, a chromium layer, a gold layer, and an octadecyl mercaptane monolayer. Because the painted membrane is supported by the electrode, it is called a solid-supported membrane. It is important to note that mechanical perturbations, which usually destroy a biological lipid membrane, do not influence the life-time of an SSM. The capacitive electrode (composed of the SSM and the absorbed vesicles) is so mechanically stable that solutions may be rapidly exchanged at its surface. This property allows the application of rapid substrate/ligand concentration jumps to investigate the electrogenic activity of the protein of interest, measured via capacitive coupling between the vesicles and the electrode. [9]

Bioelectric recognition assay (BERA) Edit

The bioelectric recognition assay (BERA) is a novel method for determination of various chemical and biological molecules by measuring changes in the membrane potential of cells immobilized in a gel matrix. Apart from the increased stability of the electrode-cell interface, immobilization preserves the viability and physiological functions of the cells. BERA is used primarily in biosensor applications in order to assay analytes that can interact with the immobilized cells by changing the cell membrane potential. In this way, when a positive sample is added to the sensor, a characteristic, "signature-like" change in electrical potential occurs. BERA is the core technology behind the recently launched pan-European FOODSCAN project, about pesticide and food risk assessment in Europe. [10] BERA has been used for the detection of human viruses (hepatitis B and C viruses and herpes viruses), [11] veterinary disease agents (foot and mouth disease virus, prions, and blue tongue virus), and plant viruses (tobacco and cucumber viruses) [12] in a specific, rapid (1–2 minutes), reproducible, and cost-efficient fashion. The method has also been used for the detection of environmental toxins, such as pesticides [13] [14] [15] and mycotoxins [16] in food, and 2,4,6-trichloroanisole in cork and wine, [17] [18] as well as the determination of very low concentrations of the superoxide anion in clinical samples. [19] [20]

A BERA sensor has two parts:

A recent advance is the development of a technique called molecular identification through membrane engineering (MIME). This technique allows for building cells with defined specificity for virtually any molecule of interest, by embedding thousands of artificial receptors into the cell membrane. [22]

Computational electrophysiology Edit

While not strictly constituting an experimental measurement, methods have been developed to examine the conductive properties of proteins and biomembranes in silico. These are mainly molecular dynamics simulations in which a model system like a lipid bilayer is subjected to an externally applied voltage. Studies using these setups have been able to study dynamical phenomena like electroporation of membranes [23] and ion translocation by channels. [24]

The benefit of such methods is the high level of detail of the active conduction mechanism, given by the inherently high resolution and data density that atomistic simulation affords. There are significant drawbacks, given by the uncertainty of the legitimacy of the model and the computational cost of modeling systems that are large enough and over sufficient timescales to be considered reproducing the macroscopic properties of the systems themselves. While atomistic simulations may access timescales close to, or into the microsecond domain, this is still several orders of magnitude lower than even the resolution of experimental methods such as patch-clamping. [ citation needed ]

Clinical electrophysiology is the study of how electrophysiological principles and technologies can be applied to human health. For example, clinical cardiac electrophysiology is the study of the electrical properties which govern heart rhythm and activity. Cardiac electrophysiology can be used to observe and treat disorders such as arrhythmia (irregular heartbeat). For example, a doctor may insert a catheter containing an electrode into the heart to record the heart muscle's electrical activity.

Another example of clinical electrophysiology is clinical neurophysiology. In this medical specialty, doctors measure the electrical properties of the brain, spinal cord, and nerves. Scientists such as Duchenne de Boulogne (1806–1875) and Nathaniel A. Buchwald (1924–2006) are considered to have greatly advanced the field of neurophysiology, enabling its clinical applications.

Clinical reporting guidelines Edit

Minimum Information (MI) standards or reporting guidelines specify the minimum amount of meta data (information) and data required to meet a specific aim or aims in a clinical study. The "Minimum Information about a Neuroscience investigation" (MINI) family of reporting guideline documents aims to provide a consistent set of guidelines in order to report an electrophysiology experiment. In practice a MINI module comprises a checklist of information that should be provided (for example about the protocols employed) when a data set is described for publication. [25]


Abstract

Local field potentials (LFPs) are commonly thought to reflect the aggregate dynamics in local neural circuits around recording electrodes. However, we show that when LFPs are recorded in awake behaving animals against a distal reference on the skull as commonly practiced, LFPs are significantly contaminated by non-local and non-neural sources arising from the reference electrode and from movement-related noise. In a data set with simultaneously recorded LFPs and electroencephalograms (EEGs) across multiple brain regions while rats perform an auditory oddball task, we used independent component analysis (ICA) to identify signals arising from electrical reference and from volume-conducted noise based on their distributed spatial pattern across multiple electrodes and distinct power spectral features. These sources of distal electrical signals collectively accounted for 23–77% of total variance in unprocessed LFPs, as well as most of the gamma oscillation responses to the target stimulus in EEGs. Gamma oscillation power was concentrated in volume-conducted noise and was tightly coupled with the onset of licking behavior, suggesting a likely origin of muscle activity associated with body movement or orofacial movement. The removal of distal signal contamination also selectively reduced correlations of LFP/EEG signals between distant brain regions but not within the same region. Finally, the removal of contamination from distal electrical signals preserved an event-related potential (ERP) response to auditory stimuli in the frontal cortex and also increased the coupling between the frontal ERP amplitude and neuronal activity in the basal forebrain, supporting the conclusion that removing distal electrical signals unmasked local activity within LFPs. Together, these results highlight the significant contamination of LFPs by distal electrical signals and caution against the straightforward interpretation of unprocessed LFPs. Our results provide a principled approach to identify and remove such contamination to unmask local LFPs.


Retinal Glia

Generation of the electroretinogram

A consequence of K + current flow through Müller cells is the generation of extracellular field potentials within the retina. These light-evoked potentials can be recorded with an electrode on the cornea as components of the electroretinogram (ERG). For many years, the b-wave, the most prominent component of the ERG, was believed to be generated by K + current flow through Müller cells. However, if K + siphoning is prevented by blocking Müller cell Kir channels with Ba 2+ , or if the channels are eliminated by employing Kir4.1 knockout animals, the b-wave is not reduced. These experiments demonstrate conclusively that Müller cells do not generate the ERG b-wave. The b-wave is generated, instead, by bipolar cells, as originally suggested by Tomita.

Other components of the ERG are generated by light-evoked K + current flow through Müller cells, however. The slow PIII response, the retinal component of the ERG c-wave, is generated by Müller cell K + current flow established by a decrease in [K + ]o in the distal retina. Müller cells also generate the scotopic threshold response, a rod-driven response generated at the ON of light in mammals, and the M-wave, a negative response with prominent ON and OFF components. Both responses are generated by K + current flow through Müller cells established by [K + ]o increases in the inner plexiform layer.


Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. LIF network and 3D morphological…

Fig 1. LIF network and 3D morphological network.

(A) Sketch of the leaky integrate-and-fire (LIF)…

Fig 2. Simulated local field potentials (LFPs)…

Fig 2. Simulated local field potentials (LFPs) as a function of depth and lateral position…

Fig 3. Contribution from individual neuron types…

Fig 3. Contribution from individual neuron types to simulated LFP signal.

Decomposition of LFP obtained…

Fig 4. Performance of candidate LFP proxies.

Fig 4. Performance of candidate LFP proxies.

(A) Illustrations of predictions of LFP time courses…

Fig 5. New proxy explaining more than…

Fig 5. New proxy explaining more than 90% of the variance in the LFP signal.

Fig 6. Effects of dynamic network states…

Fig 6. Effects of dynamic network states of the LIF model on the simulated LFP…

Fig 7. Spectral analysis of LFP signal.

Fig 7. Spectral analysis of LFP signal.

(A) Power spectra of the LFP signal at…

Fig 8. Effect of neuronal morphologies on…

Fig 8. Effect of neuronal morphologies on neural signal.

(A) Manipulation of the relative position…

Fig 9. LFP signal and synaptic distribution.

Fig 9. LFP signal and synaptic distribution.

(A) Example cases for different synaptic distributions. Left:…

Fig 10. Effects of modulation of inputs…

Fig 10. Effects of modulation of inputs with conductance-based synaptic model.


Each chemical species (for example, "water molecules", "sodium ions", "electrons", etc.) has an electrochemical potential (a quantity with units of energy) at any given point in space, which represents how easy or difficult it is to add more of that species to that location. If possible, a species will move from areas with higher electrochemical potential to areas with lower electrochemical potential in equilibrium, the electrochemical potential will be constant everywhere for each species (it may have a different value for different species). For example, if a glass of water has sodium ions (Na + ) dissolved uniformly in it, and an electric field is applied across the water, then the sodium ions will tend to get pulled by the electric field towards one side. We say the ions have electric potential energy, and are moving to lower their potential energy. Likewise, if a glass of water has a lot of dissolved sugar on one side and none on the other side, each sugar molecule will randomly diffuse around the water, until there is equal concentration of sugar everywhere. We say that the sugar molecules have a "chemical potential", which is higher in the high-concentration areas, and the molecules move to lower their chemical potential. These two examples show that an electrical potential and a chemical potential can both give the same result: A redistribution of the chemical species. Therefore, it makes sense to combine them into a single "potential", the electrochemical potential, which can directly give the net redistribution taking both into account.

It is (in principle) easy to measure whether or not two regions (for example, two glasses of water) have the same electrochemical potential for a certain chemical species (for example, a solute molecule): Allow the species to freely move back and forth between the two regions (for example, connect them with a semi-permeable membrane that lets only that species through). If the chemical potential is the same in the two regions, the species will occasionally move back and forth between the two regions, but on average there is just as much movement in one direction as the other, and there is zero net migration (this is called "diffusive equilibrium"). If the chemical potentials of the two regions are different, more molecules will move to the lower chemical potential than the other direction.

Moreover, when there is not diffusive equilibrium, i.e., when there is a tendency for molecules to diffuse from one region to another, then there is a certain free energy released by each net-diffusing molecule. This energy, which can sometimes be harnessed (a simple example is a concentration cell), and the free-energy per mole is exactly equal to the electrochemical potential difference between the two regions.

It is common in electrochemistry and solid-state physics to discuss both the chemical potential and the electrochemical potential of the electrons. However, in the two fields, the definitions of these two terms are sometimes swapped. In electrochemistry, the electrochemical potential of electrons (or any other species) is the total potential, including both the (internal, nonelectrical) chemical potential and the electric potential, and is by definition constant across a device in equilibrium, whereas the chemical potential of electrons is equal to the electrochemical potential minus the local electric potential energy per electron. [1] In solid-state physics, the definitions are normally compatible with this, [2] but occasionally [3] the definitions are swapped.

This article uses the electrochemistry definitions.

In generic terms, electrochemical potential is the mechanical work done in bringing 1 mole of an ion from a standard state to a specified concentration and electrical potential. According to the IUPAC definition, [4] it is the partial molar Gibbs energy of the substance at the specified electric potential, where the substance is in a specified phase. Electrochemical potential can be expressed as

μ i is the electrochemical potential of species i, in J/mol, μi is the chemical potential of the species i, in J/mol, zi is the valency (charge) of the ion i, a dimensionless integer, F is the Faraday constant, in C/mol, Φ is the local electrostatic potential, in V.

In the special case of an uncharged atom, zi = 0, and so μ i = μi.

Electrochemical potential is important in biological processes that involve molecular diffusion across membranes, in electroanalytical chemistry, and industrial applications such as batteries and fuel cells. It represents one of the many interchangeable forms of potential energy through which energy may be conserved.

In cell membranes, the electrochemical potential is the sum of the chemical potential and the membrane potential.

The term electrochemical potential is sometimes used to mean an electrode potential (either of a corroding electrode, an electrode with a non-zero net reaction or current, or an electrode at equilibrium). In some contexts, the electrode potential of corroding metals is called "electrochemical corrosion potential", [5] which is often abbreviated as ECP, and the word "corrosion" is sometimes omitted. This usage can lead to confusion. The two quantities have different meanings and different dimensions: the dimension of electrochemical potential is energy per mole while that of electrode potential is voltage (energy per charge).


Author Summary

The first recording of electrical potential from brain activity was reported already in 1875, but still the interpretation of the signal is debated. To take full advantage of the new generation of microelectrodes with hundreds or even thousands of electrode contacts, an accurate quantitative link between what is measured and the underlying neural circuit activity is needed. Here we address the question of how the observed frequency dependence of recorded local field potentials (LFPs) should be interpreted. By use of a well-established biophysical modeling scheme, combined with detailed reconstructed neuronal morphologies, we find that correlations in the synaptic inputs onto a population of pyramidal cells may significantly boost the low-frequency components and affect the spatial profile of the generated LFP. We further find that these low-frequency components may be less ‘local’ than the high-frequency LFP components in the sense that (1) the size of signal-generation region of the LFP recorded at an electrode is larger and (2) the LFP generated by a synaptically activated population spreads further outside the population edge due to volume conduction.

Citation: Łęski S, Lindén H, Tetzlaff T, Pettersen KH, Einevoll GT (2013) Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential. PLoS Comput Biol 9(7): e1003137. https://doi.org/10.1371/journal.pcbi.1003137

Editor: Olaf Sporns, Indiana University, United States of America

Received: February 19, 2013 Accepted: May 29, 2013 Published: July 18, 2013

Copyright: © 2013 Łęski et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: We acknowledge support from the The Research Council of Norway (eVita, NOTUR, Yggdrasil), the Polish Ministry of Science and Higher Education (grants N N303 542839 and IP2011 030971), EU Grant 269921 (BrainScaleS), the Helmholtz Association (HASB and portfolio theme SMHB), and the Jülich Aachen Research Alliance (JARA). The project has been implemented with support granted by Iceland, Liechtenstein, and Norway, through a grant from the funds of the Financial Mechanism of the European Economic Area and the Norwegian Financial Mechanism under the Scholarship and Training Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.


Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. LIF network and 3D morphological…

Fig 1. LIF network and 3D morphological network.

(A) Sketch of the leaky integrate-and-fire (LIF)…

Fig 2. Simulated local field potentials (LFPs)…

Fig 2. Simulated local field potentials (LFPs) as a function of depth and lateral position…

Fig 3. Contribution from individual neuron types…

Fig 3. Contribution from individual neuron types to simulated LFP signal.

Decomposition of LFP obtained…

Fig 4. Performance of candidate LFP proxies.

Fig 4. Performance of candidate LFP proxies.

(A) Illustrations of predictions of LFP time courses…

Fig 5. New proxy explaining more than…

Fig 5. New proxy explaining more than 90% of the variance in the LFP signal.

Fig 6. Effects of dynamic network states…

Fig 6. Effects of dynamic network states of the LIF model on the simulated LFP…

Fig 7. Spectral analysis of LFP signal.

Fig 7. Spectral analysis of LFP signal.

(A) Power spectra of the LFP signal at…

Fig 8. Effect of neuronal morphologies on…

Fig 8. Effect of neuronal morphologies on neural signal.

(A) Manipulation of the relative position…

Fig 9. LFP signal and synaptic distribution.

Fig 9. LFP signal and synaptic distribution.

(A) Example cases for different synaptic distributions. Left:…

Fig 10. Effects of modulation of inputs…

Fig 10. Effects of modulation of inputs with conductance-based synaptic model.


Firing synchrony as a code for sensory information in thalamus

The size of the early component of the LFP increases with deflection velocity/acceleration but is unaffected by final deflection amplitude. These findings are strikingly similar to the relationship between initial thalamic population firing synchrony and whisker deflection velocity reported by Pinto et al. (2000). In their study, the investigators recorded single thalamic units, one at a time, using virtually the same stimuli used here. Thalamic population firing synchrony was inferred from summed PSTHs, and deflection velocity was found to be highly correlated with populationfiring rates during the first 2–7 ms of the response, a period virtually identical to the time course of the early LFP component. This relationship was found only for the population measure, not for the firing rates of individual neurons, whose stimulus-response relationships varied widely. Barrel circuitry is highly sensitive to population firing synchrony, and therefore barrel neurons fire most vigorously in response to high-velocity deflections of the PW. The present findings show that a similar code exists for distinguishing movement direction and deflection of principal versus adjacent whiskers.

A larger magnitude of the LFP early component may reflect an increase in the number and/or amplitude of whisker-evoked lemniscal-mediated EPSPs and/or a decrease in both the onset latency of EPSP/spike generation and its variability. These factors would translate into a higher probability of any given barreloid neuron firing a short-latency, stimulus-locked action potential, thus producing high initial population firing synchrony. In rat and cat VPl, correlated firing over small time intervals (<5 ms) is observed among nearby thalamocortical neurons when cutaneous stimuli are applied to common regions of their receptive fields (Alloway et al. 1995), and synchronous thalamic events enhance cortical responsiveness (Roy and Alloway 2001). Similar mechanisms have been shown to operate in the geniculocortical system as well (Alonso et al. 1996 Usrey et al. 2000).

The present study provides evidence for synchronous activity in VPm that is generated by neighboring barreloid neurons having overlapping receptive fields (i.e., the same PW). Shoykhet et al. (2000) showed that trigeminal ganglion neurons can encode whisker deflection velocity in their population firing rates during the first 2.0 ms of their response as well as in the distribution of their response latencies. Higher velocities were associated with both a higher response probability and shorter response latency. Our results predict that the same coding strategies are preserved in brain stem. Strong trigeminothalamic synapses (Castro-Alamancos 2002b) would ensure reliable transmission of information to the thalamus even if a single thalamic neuron were contacted by one or only a few afferent fibers (Alloway et al. 1994 Usrey et al. 1999). By contrast, cortical neurons are contacted relatively weakly by many thalamocortical neurons (Alonso et al. 1996 Bruno and Simons 2002 Roy and Alloway 2001 Swadlow 1995). Hence, thalamic firing synchrony is likely to play a critical role in sensory coding in the whisker-to-barrel pathway.

We thank A. Myers for histological assistance.

This work was supported by National Institutes of Health Grants IBN-19950 and MH-61372.


Watch the video: Measuring the local field potential (September 2022).


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