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Electrosensory neural responses to natural electro-communication stimuli are distributed along a continuum

View Article: PubMed Central - PubMed

ABSTRACT

Neural heterogeneities are seen ubiquitously within the brain and greatly complicate classification efforts. Here we tested whether the responses of an anatomically well-characterized sensory neuron population to natural stimuli could be used for functional classification. To do so, we recorded from pyramidal cells within the electrosensory lateral line lobe (ELL) of the weakly electric fish Apteronotus leptorhynchus in response to natural electro-communication stimuli as these cells can be anatomically classified into six different types. We then used two independent methodologies to functionally classify responses: one relies of reducing the dimensionality of a feature space while the other directly compares the responses themselves. Both methodologies gave rise to qualitatively similar results: while ON and OFF-type cells could easily be distinguished from one another, ELL pyramidal neuron responses are actually distributed along a continuum rather than forming distinct clusters due to heterogeneities. We discuss the implications of our results for neural coding and highlight some potential advantages.

No MeSH data available.


Related in: MedlinePlus

Establishing a functional classification using naturalistic communication stimuli.A: There are two types of pyramidal neurons, On- (blue) and Off- (red) type, which can be distinguished anatomically by the presence and absence of basilar dendrites, respectively (top). On- and Off-type pyramidal cells can furthermore be subdivided into six classes: On and Off-type superficial (S) intermediate (I) and deep (D) types which each exhibits different sized apical dendritic trees. There is a strong negative correlation between the size of the apical dendritic tree and the baseline (i.e., in the absence of stimulation) firing rate (S1 Fig). The baseline firing rate is indicated by colour saturation as per the colour bar above the circuit diagram. At the circuit level (bottom) within the pyramidal cell layer (orange boarder) all neurons receive input from sensory afferents encoding the animal’s self-generated electric field. On-type cells receive direct inputs from these afferents whereas Off-type cells receive indirect input via local inhibitory interneurons. All neuron classes project to the midbrain torus Semicircularis (not pictured here) while only deep neurons project to praeminentialis dorsalis (Pd) which provides different degrees of inhibitory feedback to superficial and intermediate pyramidal neurons via the eminentia granularis pars posterior (EGP). B: The four chirp stimuli featured in this study are shown in dark grey. A 25 ms response window following chirp onset is also indicated by a light grey window for two On-type chirps (3π/2, π) and the two Off-type chirps (π/2, 0). The 5 Hz beat stimulus is shown in black. C: A stimulus waveform is played to an awake and behaving animal while recordings are obtained from pyramidal cells within the lateral segment (LS) of the ELL. Example recordings from one On-type and one Off-type neuron are shown in response to a 5 Hz beat. Spike waveforms identified using spike sorting software are indicated for each cell (blue and red). The spike times were used to generate raster plots and peristimulus time histograms (as seen below the experimental setup). Example cells have peak stimulus driven firing rates of 136 Hz (On-type) and 123 Hz (Off-type) and their responses to the beat are in anti-phase. The color gradient in the color bar (bottom) is indicative of the response magnitude of recorded units (i.e. On- or Off-type). The transition from blue to red reflects an increase in response magnitude as the logarithm in base 10 of the stimulus driven peak-firing rate. D: A priori it is unclear whether ELL pyramidal cells can be functionally classified based on their responses to natural communication signals alone. There are two hypotheses: 1. Responses form distinct clusters This is schematized by a heatmap of response magnitude showing distinct response profiles. Directly beneath a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) which is clearly divisible into distinct groups (dashed red line). 2. Responses do not form distinct clusters and instead form a continuum. The response heat map as in 1 thus gives rise to one clear transition between On- and Off-type cells. In this case a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) that is only divisible into two groups (dashed red line), each of which constitutes a continuum.
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pone.0175322.g001: Establishing a functional classification using naturalistic communication stimuli.A: There are two types of pyramidal neurons, On- (blue) and Off- (red) type, which can be distinguished anatomically by the presence and absence of basilar dendrites, respectively (top). On- and Off-type pyramidal cells can furthermore be subdivided into six classes: On and Off-type superficial (S) intermediate (I) and deep (D) types which each exhibits different sized apical dendritic trees. There is a strong negative correlation between the size of the apical dendritic tree and the baseline (i.e., in the absence of stimulation) firing rate (S1 Fig). The baseline firing rate is indicated by colour saturation as per the colour bar above the circuit diagram. At the circuit level (bottom) within the pyramidal cell layer (orange boarder) all neurons receive input from sensory afferents encoding the animal’s self-generated electric field. On-type cells receive direct inputs from these afferents whereas Off-type cells receive indirect input via local inhibitory interneurons. All neuron classes project to the midbrain torus Semicircularis (not pictured here) while only deep neurons project to praeminentialis dorsalis (Pd) which provides different degrees of inhibitory feedback to superficial and intermediate pyramidal neurons via the eminentia granularis pars posterior (EGP). B: The four chirp stimuli featured in this study are shown in dark grey. A 25 ms response window following chirp onset is also indicated by a light grey window for two On-type chirps (3π/2, π) and the two Off-type chirps (π/2, 0). The 5 Hz beat stimulus is shown in black. C: A stimulus waveform is played to an awake and behaving animal while recordings are obtained from pyramidal cells within the lateral segment (LS) of the ELL. Example recordings from one On-type and one Off-type neuron are shown in response to a 5 Hz beat. Spike waveforms identified using spike sorting software are indicated for each cell (blue and red). The spike times were used to generate raster plots and peristimulus time histograms (as seen below the experimental setup). Example cells have peak stimulus driven firing rates of 136 Hz (On-type) and 123 Hz (Off-type) and their responses to the beat are in anti-phase. The color gradient in the color bar (bottom) is indicative of the response magnitude of recorded units (i.e. On- or Off-type). The transition from blue to red reflects an increase in response magnitude as the logarithm in base 10 of the stimulus driven peak-firing rate. D: A priori it is unclear whether ELL pyramidal cells can be functionally classified based on their responses to natural communication signals alone. There are two hypotheses: 1. Responses form distinct clusters This is schematized by a heatmap of response magnitude showing distinct response profiles. Directly beneath a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) which is clearly divisible into distinct groups (dashed red line). 2. Responses do not form distinct clusters and instead form a continuum. The response heat map as in 1 thus gives rise to one clear transition between On- and Off-type cells. In this case a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) that is only divisible into two groups (dashed red line), each of which constitutes a continuum.

Mentions: Action potential times were defined using a spike sorting application available in the Spike2 software package. Spike waveform templates were created using an appropriate threshold. Separate templates judged to belong to the same neuron were merged and templates indicative of noise were discarded though in the majority of cases this was not necessary as a single template was often constructed by the software (i.e. the variance in spike waveform was minimal whereas the signal to noise ratio was maximal) (Fig 1C). For each of the 4 chirp stimuli, handled separately, stimulation and response channels were segmented into 20 equally sized sections slightly off center of each chirp event, -0.4 seconds to 0.5 seconds from chirp onset (Fig 1B). Each of these 20 segments was further segmented in the following manner: “beat cycle 1” (0–0.2 sec) “beat cycle 2” (0.2–0.4 sec) occurring pre chirp onset and “Chirp window” (0.4–0.5), “beat cycle 3” (0.5–0.7 sec) and “beat cycle 4” (0.7–0.9 sec) occurring post chirp onset. Beat cycles (1–4) were then time coded such that each beat cycle would commence at 0 mV and initially be positive going in sign. Additional segmentations include a general “chirp centered” segment (0.3–0.5 sec) and more specific segmentations catered to the 4 stimuli separately with the goal of concatenating these segments across stimuli. Specifically catered segmentations included; (chirp 0) “0 phase” commencing at onset and ending at the second instance of phase π/2, (chirp π/2) “90 phase” commencing at onset and ending at the second instance of phase π, (chirp π) “180 phase” commencing at onset and ending at the second instance of phase 3π/2 and lastly (chirp 3π/2) “270 phase” commencing at onset and ending at the second instance of phase 2π. These segments were concatenated in order of increasing phase value to generate an abbreviated representation of responses to all chirps used in the current study that we will refer to as “All chirp phases”. Some of these initial segments were further combined at later stages of processing for various purposes of analysis. Peristimulus time histograms (PSTHs) of stimulus segments were generated by building a histogram from spike times, dividing the histogram values by its bin size (0.1 ms) to impose a time domain, multiplying this result by the number of trials under consideration and then smoothing with a 6 ms long box car filter. Smoothing artefacts due to filtering onset and offset were eliminated by triplicating the histogram and taking the central portion as the final PSTH.


Electrosensory neural responses to natural electro-communication stimuli are distributed along a continuum
Establishing a functional classification using naturalistic communication stimuli.A: There are two types of pyramidal neurons, On- (blue) and Off- (red) type, which can be distinguished anatomically by the presence and absence of basilar dendrites, respectively (top). On- and Off-type pyramidal cells can furthermore be subdivided into six classes: On and Off-type superficial (S) intermediate (I) and deep (D) types which each exhibits different sized apical dendritic trees. There is a strong negative correlation between the size of the apical dendritic tree and the baseline (i.e., in the absence of stimulation) firing rate (S1 Fig). The baseline firing rate is indicated by colour saturation as per the colour bar above the circuit diagram. At the circuit level (bottom) within the pyramidal cell layer (orange boarder) all neurons receive input from sensory afferents encoding the animal’s self-generated electric field. On-type cells receive direct inputs from these afferents whereas Off-type cells receive indirect input via local inhibitory interneurons. All neuron classes project to the midbrain torus Semicircularis (not pictured here) while only deep neurons project to praeminentialis dorsalis (Pd) which provides different degrees of inhibitory feedback to superficial and intermediate pyramidal neurons via the eminentia granularis pars posterior (EGP). B: The four chirp stimuli featured in this study are shown in dark grey. A 25 ms response window following chirp onset is also indicated by a light grey window for two On-type chirps (3π/2, π) and the two Off-type chirps (π/2, 0). The 5 Hz beat stimulus is shown in black. C: A stimulus waveform is played to an awake and behaving animal while recordings are obtained from pyramidal cells within the lateral segment (LS) of the ELL. Example recordings from one On-type and one Off-type neuron are shown in response to a 5 Hz beat. Spike waveforms identified using spike sorting software are indicated for each cell (blue and red). The spike times were used to generate raster plots and peristimulus time histograms (as seen below the experimental setup). Example cells have peak stimulus driven firing rates of 136 Hz (On-type) and 123 Hz (Off-type) and their responses to the beat are in anti-phase. The color gradient in the color bar (bottom) is indicative of the response magnitude of recorded units (i.e. On- or Off-type). The transition from blue to red reflects an increase in response magnitude as the logarithm in base 10 of the stimulus driven peak-firing rate. D: A priori it is unclear whether ELL pyramidal cells can be functionally classified based on their responses to natural communication signals alone. There are two hypotheses: 1. Responses form distinct clusters This is schematized by a heatmap of response magnitude showing distinct response profiles. Directly beneath a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) which is clearly divisible into distinct groups (dashed red line). 2. Responses do not form distinct clusters and instead form a continuum. The response heat map as in 1 thus gives rise to one clear transition between On- and Off-type cells. In this case a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) that is only divisible into two groups (dashed red line), each of which constitutes a continuum.
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Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC5383285&req=5

pone.0175322.g001: Establishing a functional classification using naturalistic communication stimuli.A: There are two types of pyramidal neurons, On- (blue) and Off- (red) type, which can be distinguished anatomically by the presence and absence of basilar dendrites, respectively (top). On- and Off-type pyramidal cells can furthermore be subdivided into six classes: On and Off-type superficial (S) intermediate (I) and deep (D) types which each exhibits different sized apical dendritic trees. There is a strong negative correlation between the size of the apical dendritic tree and the baseline (i.e., in the absence of stimulation) firing rate (S1 Fig). The baseline firing rate is indicated by colour saturation as per the colour bar above the circuit diagram. At the circuit level (bottom) within the pyramidal cell layer (orange boarder) all neurons receive input from sensory afferents encoding the animal’s self-generated electric field. On-type cells receive direct inputs from these afferents whereas Off-type cells receive indirect input via local inhibitory interneurons. All neuron classes project to the midbrain torus Semicircularis (not pictured here) while only deep neurons project to praeminentialis dorsalis (Pd) which provides different degrees of inhibitory feedback to superficial and intermediate pyramidal neurons via the eminentia granularis pars posterior (EGP). B: The four chirp stimuli featured in this study are shown in dark grey. A 25 ms response window following chirp onset is also indicated by a light grey window for two On-type chirps (3π/2, π) and the two Off-type chirps (π/2, 0). The 5 Hz beat stimulus is shown in black. C: A stimulus waveform is played to an awake and behaving animal while recordings are obtained from pyramidal cells within the lateral segment (LS) of the ELL. Example recordings from one On-type and one Off-type neuron are shown in response to a 5 Hz beat. Spike waveforms identified using spike sorting software are indicated for each cell (blue and red). The spike times were used to generate raster plots and peristimulus time histograms (as seen below the experimental setup). Example cells have peak stimulus driven firing rates of 136 Hz (On-type) and 123 Hz (Off-type) and their responses to the beat are in anti-phase. The color gradient in the color bar (bottom) is indicative of the response magnitude of recorded units (i.e. On- or Off-type). The transition from blue to red reflects an increase in response magnitude as the logarithm in base 10 of the stimulus driven peak-firing rate. D: A priori it is unclear whether ELL pyramidal cells can be functionally classified based on their responses to natural communication signals alone. There are two hypotheses: 1. Responses form distinct clusters This is schematized by a heatmap of response magnitude showing distinct response profiles. Directly beneath a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) which is clearly divisible into distinct groups (dashed red line). 2. Responses do not form distinct clusters and instead form a continuum. The response heat map as in 1 thus gives rise to one clear transition between On- and Off-type cells. In this case a hierarchical agglomerative clustering algorithm applied to a pairwise distance matrix representing the above heatmap results in a dendrogram (green) that is only divisible into two groups (dashed red line), each of which constitutes a continuum.
Mentions: Action potential times were defined using a spike sorting application available in the Spike2 software package. Spike waveform templates were created using an appropriate threshold. Separate templates judged to belong to the same neuron were merged and templates indicative of noise were discarded though in the majority of cases this was not necessary as a single template was often constructed by the software (i.e. the variance in spike waveform was minimal whereas the signal to noise ratio was maximal) (Fig 1C). For each of the 4 chirp stimuli, handled separately, stimulation and response channels were segmented into 20 equally sized sections slightly off center of each chirp event, -0.4 seconds to 0.5 seconds from chirp onset (Fig 1B). Each of these 20 segments was further segmented in the following manner: “beat cycle 1” (0–0.2 sec) “beat cycle 2” (0.2–0.4 sec) occurring pre chirp onset and “Chirp window” (0.4–0.5), “beat cycle 3” (0.5–0.7 sec) and “beat cycle 4” (0.7–0.9 sec) occurring post chirp onset. Beat cycles (1–4) were then time coded such that each beat cycle would commence at 0 mV and initially be positive going in sign. Additional segmentations include a general “chirp centered” segment (0.3–0.5 sec) and more specific segmentations catered to the 4 stimuli separately with the goal of concatenating these segments across stimuli. Specifically catered segmentations included; (chirp 0) “0 phase” commencing at onset and ending at the second instance of phase π/2, (chirp π/2) “90 phase” commencing at onset and ending at the second instance of phase π, (chirp π) “180 phase” commencing at onset and ending at the second instance of phase 3π/2 and lastly (chirp 3π/2) “270 phase” commencing at onset and ending at the second instance of phase 2π. These segments were concatenated in order of increasing phase value to generate an abbreviated representation of responses to all chirps used in the current study that we will refer to as “All chirp phases”. Some of these initial segments were further combined at later stages of processing for various purposes of analysis. Peristimulus time histograms (PSTHs) of stimulus segments were generated by building a histogram from spike times, dividing the histogram values by its bin size (0.1 ms) to impose a time domain, multiplying this result by the number of trials under consideration and then smoothing with a 6 ms long box car filter. Smoothing artefacts due to filtering onset and offset were eliminated by triplicating the histogram and taking the central portion as the final PSTH.

View Article: PubMed Central - PubMed

ABSTRACT

Neural heterogeneities are seen ubiquitously within the brain and greatly complicate classification efforts. Here we tested whether the responses of an anatomically well-characterized sensory neuron population to natural stimuli could be used for functional classification. To do so, we recorded from pyramidal cells within the electrosensory lateral line lobe (ELL) of the weakly electric fish Apteronotus leptorhynchus in response to natural electro-communication stimuli as these cells can be anatomically classified into six different types. We then used two independent methodologies to functionally classify responses: one relies of reducing the dimensionality of a feature space while the other directly compares the responses themselves. Both methodologies gave rise to qualitatively similar results: while ON and OFF-type cells could easily be distinguished from one another, ELL pyramidal neuron responses are actually distributed along a continuum rather than forming distinct clusters due to heterogeneities. We discuss the implications of our results for neural coding and highlight some potential advantages.

No MeSH data available.


Related in: MedlinePlus