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Conversion of phase information into a spike-count code by bursting neurons.

Samengo I, Montemurro MA - PLoS ONE (2010)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Centro Atómico Bariloche and Instituto Balseiro, San Carlos de Bariloche, Argentina.

ABSTRACT
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.

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Schematic representation of a phase code.Firing rate of a cell in response to three different stimuli. By reading out the number of spikes per unit time (the height of the bars), stimulus 1 is distinguishable from the other two stimuli. However, stimuli 2 and 3 induce the same response, and therefore cannot be discriminated on the basis of the firing rate alone. However, if also the timing with respect to the phase of the LFP is taken into account, stimuli 2 and 3 become distinguishable. Inspired on a figure from [11].
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pone-0009669-g001: Schematic representation of a phase code.Firing rate of a cell in response to three different stimuli. By reading out the number of spikes per unit time (the height of the bars), stimulus 1 is distinguishable from the other two stimuli. However, stimuli 2 and 3 induce the same response, and therefore cannot be discriminated on the basis of the firing rate alone. However, if also the timing with respect to the phase of the LFP is taken into account, stimuli 2 and 3 become distinguishable. Inspired on a figure from [11].

Mentions: Cortical networks have a rich repertoire of rhythmic oscillations [1]. Previous studies [2], [3] have suggested that coherent oscillations could be used in the brain as an effective time frame regulating neural coding. For example, in hippocampal place cells, the firing of a place cell indicates that the animal is inside the place field, and thereby provides coarse location information [4]. More detailed information about the precise position inside the place field can be obtained from the phase of the theta rhythm at burst onset [5], [6]. More generally, in several brain areas, the relative timing between the firing onset of pyramidal neurons and the local field potential (LFP) encodes additional information about the external stimulus, not present in spike counts alone. Although there have been suggestions that similar mechanisms could operate at the neocortical level [7], [8], direct quantitative evidence using information theoretic analysis of in-vivo data became available only recently for visual [9] and auditory [10] cortices. Those studies showed that when the timing of spikes is measured relative to the phase of the LFP, there is a significant increase in information about the stimulus carried by the spike train. The advantages of a phase-of-firing encoding are illustrated in Figure 1 [11]. The bars represent the firing rate of a cell in response to three different stimuli. Based on the traditional view that information is encoded in the mean firing rate, stimulus 1 can be discriminated from the other two stimuli, since it generates a weaker response. However, both stimuli 2 and 3 give rise to the same firing rate, and therefore cannot be discriminated using the firing rate alone. However, if the relative timing between firing onset and the phase of the ongoing LFP oscillation is also taken into account (phase-of-firing code), then the responses to stimuli 2 and 3 become distinguishable, since they occur at different phases of the LFP. In the figure we used a color code to represent the phase of the LFP in sections of π/2. The phase-of-firing code increased the information transmitted by cortical cells by around 54% in visual cortex [9] and by more than 100% in auditory cortex [10], when compared to the information conveyed by the spike rate alone. However, it is still unclear how phase information could be read out by distal downstream target cells, since the LFP at the soma of the pre-synaptic afferents is not directly accessible to remote neurons. The aim of this work is to show that cortical bursting neurons can translate phase information into a spike-count format, thus making it available to other brain regions.


Conversion of phase information into a spike-count code by bursting neurons.

Samengo I, Montemurro MA - PLoS ONE (2010)

Schematic representation of a phase code.Firing rate of a cell in response to three different stimuli. By reading out the number of spikes per unit time (the height of the bars), stimulus 1 is distinguishable from the other two stimuli. However, stimuli 2 and 3 induce the same response, and therefore cannot be discriminated on the basis of the firing rate alone. However, if also the timing with respect to the phase of the LFP is taken into account, stimuli 2 and 3 become distinguishable. Inspired on a figure from [11].
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2837377&req=5

pone-0009669-g001: Schematic representation of a phase code.Firing rate of a cell in response to three different stimuli. By reading out the number of spikes per unit time (the height of the bars), stimulus 1 is distinguishable from the other two stimuli. However, stimuli 2 and 3 induce the same response, and therefore cannot be discriminated on the basis of the firing rate alone. However, if also the timing with respect to the phase of the LFP is taken into account, stimuli 2 and 3 become distinguishable. Inspired on a figure from [11].
Mentions: Cortical networks have a rich repertoire of rhythmic oscillations [1]. Previous studies [2], [3] have suggested that coherent oscillations could be used in the brain as an effective time frame regulating neural coding. For example, in hippocampal place cells, the firing of a place cell indicates that the animal is inside the place field, and thereby provides coarse location information [4]. More detailed information about the precise position inside the place field can be obtained from the phase of the theta rhythm at burst onset [5], [6]. More generally, in several brain areas, the relative timing between the firing onset of pyramidal neurons and the local field potential (LFP) encodes additional information about the external stimulus, not present in spike counts alone. Although there have been suggestions that similar mechanisms could operate at the neocortical level [7], [8], direct quantitative evidence using information theoretic analysis of in-vivo data became available only recently for visual [9] and auditory [10] cortices. Those studies showed that when the timing of spikes is measured relative to the phase of the LFP, there is a significant increase in information about the stimulus carried by the spike train. The advantages of a phase-of-firing encoding are illustrated in Figure 1 [11]. The bars represent the firing rate of a cell in response to three different stimuli. Based on the traditional view that information is encoded in the mean firing rate, stimulus 1 can be discriminated from the other two stimuli, since it generates a weaker response. However, both stimuli 2 and 3 give rise to the same firing rate, and therefore cannot be discriminated using the firing rate alone. However, if the relative timing between firing onset and the phase of the ongoing LFP oscillation is also taken into account (phase-of-firing code), then the responses to stimuli 2 and 3 become distinguishable, since they occur at different phases of the LFP. In the figure we used a color code to represent the phase of the LFP in sections of π/2. The phase-of-firing code increased the information transmitted by cortical cells by around 54% in visual cortex [9] and by more than 100% in auditory cortex [10], when compared to the information conveyed by the spike rate alone. However, it is still unclear how phase information could be read out by distal downstream target cells, since the LFP at the soma of the pre-synaptic afferents is not directly accessible to remote neurons. The aim of this work is to show that cortical bursting neurons can translate phase information into a spike-count format, thus making it available to other brain regions.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Centro Atómico Bariloche and Instituto Balseiro, San Carlos de Bariloche, Argentina.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus