Limits...
Identifying the synaptic origin of ongoing neuronal oscillations through spatial discrimination of electric fields.

Fernández-Ruiz A, Herreras O - Front Comput Neurosci (2013)

Bottom Line: However, multi-site recording devices now provide high-resolution spatial profiles of local field potentials (LFPs) and when coupled to modern mathematical analyses that discriminate signals with distinct but overlapping spatial distributions, they open the door to better understand these potentials.Accordingly, some oscillatory patterns can now be viewed as a periodic succession of synchronous synaptic currents that reflect the time envelope of spiking activity in given presynaptic populations.These analyses modify our concept of brain rhythms as abstract entities, molding them into mechanistic representations of network activity and allowing us to work in the time domain, reducing the loss of information inherent to data-chopping frequency treatment.

View Article: PubMed Central - PubMed

Affiliation: Experimental and Computational Neurophysiology, Department of Systems Neuroscience, Cajal Institute - Consejo Superior de Investigaciones Científicas Madrid, Spain.

ABSTRACT
Although intracerebral field potential oscillations are commonly used to study information processing during cognition and behavior, the cellular and network processes underlying such events remain unclear. The limited spatial resolution of standard single-point recordings does not clarify whether field oscillations reflect the activity of one or many afferent presynaptic populations. However, multi-site recording devices now provide high-resolution spatial profiles of local field potentials (LFPs) and when coupled to modern mathematical analyses that discriminate signals with distinct but overlapping spatial distributions, they open the door to better understand these potentials. Here we review recent insights that help disentangle certain pathway-specific activities. Accordingly, some oscillatory patterns can now be viewed as a periodic succession of synchronous synaptic currents that reflect the time envelope of spiking activity in given presynaptic populations. These analyses modify our concept of brain rhythms as abstract entities, molding them into mechanistic representations of network activity and allowing us to work in the time domain, reducing the loss of information inherent to data-chopping frequency treatment.

No MeSH data available.


Related in: MedlinePlus

Application of ICA to disentangle pathway-specific hippocampal LFPs. (A) Ongoing raw LFPs across the CA1 and CA3 fields (black and gray traces, respectively). The dashed red line marks the time of a subthreshold stimulus applied to the ipsilateral CA3. The evoked field potential is amplified in the right inset. (B) CSD of the evoked potential (right) yields the standard distribution of inward (blue) and outward (yellow-red) currents across the CA1 region, while that of ongoing LFPs (left) renders a complex poorly informative mixture. (C) ICA of LFPs provides four main LFP generators, each defined by the curve of spatial weights (top panel) and a time course (bottom traces). Note that only the Schaffer generator (G4) captures the Schaffer-evoked activity (arrows). (D) Reconstructed (virtual) Schaffer LFPs for the raw LFP segment and evoked potential analyzed. The pronounced activity at electrodes 5–10 in the second half of the segment corresponds to a complex of sharp waves. (E) CSD of the virtual Schaffer LFPs provides precise spatiotemporal maps of inward/outward currents for unique spatially coherent membrane events. Note how clean the map of currents is after the concomitant activity elicited by other inputs is eliminated. (Modified from Fernández-Ruiz et al., 2012a).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3569616&req=5

Figure 1: Application of ICA to disentangle pathway-specific hippocampal LFPs. (A) Ongoing raw LFPs across the CA1 and CA3 fields (black and gray traces, respectively). The dashed red line marks the time of a subthreshold stimulus applied to the ipsilateral CA3. The evoked field potential is amplified in the right inset. (B) CSD of the evoked potential (right) yields the standard distribution of inward (blue) and outward (yellow-red) currents across the CA1 region, while that of ongoing LFPs (left) renders a complex poorly informative mixture. (C) ICA of LFPs provides four main LFP generators, each defined by the curve of spatial weights (top panel) and a time course (bottom traces). Note that only the Schaffer generator (G4) captures the Schaffer-evoked activity (arrows). (D) Reconstructed (virtual) Schaffer LFPs for the raw LFP segment and evoked potential analyzed. The pronounced activity at electrodes 5–10 in the second half of the segment corresponds to a complex of sharp waves. (E) CSD of the virtual Schaffer LFPs provides precise spatiotemporal maps of inward/outward currents for unique spatially coherent membrane events. Note how clean the map of currents is after the concomitant activity elicited by other inputs is eliminated. (Modified from Fernández-Ruiz et al., 2012a).

Mentions: Multisite linear recordings are well-suited to a method that has been employed to find the current generators underlying field potentials, known as current source density (CSD) analysis (Freeman and Nicholson, 1975). This approach has been very useful to determine the contributing cells and the location of synaptic membranes activated by afferent stimuli in laminar structures, such as the hippocampus or neocortex (Leung, 1979; Herreras, 1990; Schroeder et al., 1998). However, while interpreting CSD maps is simple for voltage profiles elicited by stimulating only one afferent pathway (Figures 1A,B, right panels), their application to ongoing LFPs renders complex spatial maps of intermingled inward and outward currents (left panels), and in general it is not feasible to identify the multiple synaptic generators. Partial success has been obtained in a few stereotypic LFP patterns, such as sharp-waves (SPWs: Ylinen et al., 1995), or the theta (Brankačk et al., 1993) and gamma rhythms (Csicsvari et al., 2003) in the hippocampus. But not even in these cases has it been possible to unequivocally determine whether one or several inputs contribute to the field oscillation due to unavoidable technical artifacts.


Identifying the synaptic origin of ongoing neuronal oscillations through spatial discrimination of electric fields.

Fernández-Ruiz A, Herreras O - Front Comput Neurosci (2013)

Application of ICA to disentangle pathway-specific hippocampal LFPs. (A) Ongoing raw LFPs across the CA1 and CA3 fields (black and gray traces, respectively). The dashed red line marks the time of a subthreshold stimulus applied to the ipsilateral CA3. The evoked field potential is amplified in the right inset. (B) CSD of the evoked potential (right) yields the standard distribution of inward (blue) and outward (yellow-red) currents across the CA1 region, while that of ongoing LFPs (left) renders a complex poorly informative mixture. (C) ICA of LFPs provides four main LFP generators, each defined by the curve of spatial weights (top panel) and a time course (bottom traces). Note that only the Schaffer generator (G4) captures the Schaffer-evoked activity (arrows). (D) Reconstructed (virtual) Schaffer LFPs for the raw LFP segment and evoked potential analyzed. The pronounced activity at electrodes 5–10 in the second half of the segment corresponds to a complex of sharp waves. (E) CSD of the virtual Schaffer LFPs provides precise spatiotemporal maps of inward/outward currents for unique spatially coherent membrane events. Note how clean the map of currents is after the concomitant activity elicited by other inputs is eliminated. (Modified from Fernández-Ruiz et al., 2012a).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3569616&req=5

Figure 1: Application of ICA to disentangle pathway-specific hippocampal LFPs. (A) Ongoing raw LFPs across the CA1 and CA3 fields (black and gray traces, respectively). The dashed red line marks the time of a subthreshold stimulus applied to the ipsilateral CA3. The evoked field potential is amplified in the right inset. (B) CSD of the evoked potential (right) yields the standard distribution of inward (blue) and outward (yellow-red) currents across the CA1 region, while that of ongoing LFPs (left) renders a complex poorly informative mixture. (C) ICA of LFPs provides four main LFP generators, each defined by the curve of spatial weights (top panel) and a time course (bottom traces). Note that only the Schaffer generator (G4) captures the Schaffer-evoked activity (arrows). (D) Reconstructed (virtual) Schaffer LFPs for the raw LFP segment and evoked potential analyzed. The pronounced activity at electrodes 5–10 in the second half of the segment corresponds to a complex of sharp waves. (E) CSD of the virtual Schaffer LFPs provides precise spatiotemporal maps of inward/outward currents for unique spatially coherent membrane events. Note how clean the map of currents is after the concomitant activity elicited by other inputs is eliminated. (Modified from Fernández-Ruiz et al., 2012a).
Mentions: Multisite linear recordings are well-suited to a method that has been employed to find the current generators underlying field potentials, known as current source density (CSD) analysis (Freeman and Nicholson, 1975). This approach has been very useful to determine the contributing cells and the location of synaptic membranes activated by afferent stimuli in laminar structures, such as the hippocampus or neocortex (Leung, 1979; Herreras, 1990; Schroeder et al., 1998). However, while interpreting CSD maps is simple for voltage profiles elicited by stimulating only one afferent pathway (Figures 1A,B, right panels), their application to ongoing LFPs renders complex spatial maps of intermingled inward and outward currents (left panels), and in general it is not feasible to identify the multiple synaptic generators. Partial success has been obtained in a few stereotypic LFP patterns, such as sharp-waves (SPWs: Ylinen et al., 1995), or the theta (Brankačk et al., 1993) and gamma rhythms (Csicsvari et al., 2003) in the hippocampus. But not even in these cases has it been possible to unequivocally determine whether one or several inputs contribute to the field oscillation due to unavoidable technical artifacts.

Bottom Line: However, multi-site recording devices now provide high-resolution spatial profiles of local field potentials (LFPs) and when coupled to modern mathematical analyses that discriminate signals with distinct but overlapping spatial distributions, they open the door to better understand these potentials.Accordingly, some oscillatory patterns can now be viewed as a periodic succession of synchronous synaptic currents that reflect the time envelope of spiking activity in given presynaptic populations.These analyses modify our concept of brain rhythms as abstract entities, molding them into mechanistic representations of network activity and allowing us to work in the time domain, reducing the loss of information inherent to data-chopping frequency treatment.

View Article: PubMed Central - PubMed

Affiliation: Experimental and Computational Neurophysiology, Department of Systems Neuroscience, Cajal Institute - Consejo Superior de Investigaciones Científicas Madrid, Spain.

ABSTRACT
Although intracerebral field potential oscillations are commonly used to study information processing during cognition and behavior, the cellular and network processes underlying such events remain unclear. The limited spatial resolution of standard single-point recordings does not clarify whether field oscillations reflect the activity of one or many afferent presynaptic populations. However, multi-site recording devices now provide high-resolution spatial profiles of local field potentials (LFPs) and when coupled to modern mathematical analyses that discriminate signals with distinct but overlapping spatial distributions, they open the door to better understand these potentials. Here we review recent insights that help disentangle certain pathway-specific activities. Accordingly, some oscillatory patterns can now be viewed as a periodic succession of synchronous synaptic currents that reflect the time envelope of spiking activity in given presynaptic populations. These analyses modify our concept of brain rhythms as abstract entities, molding them into mechanistic representations of network activity and allowing us to work in the time domain, reducing the loss of information inherent to data-chopping frequency treatment.

No MeSH data available.


Related in: MedlinePlus