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Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli.

Aumentado-Armstrong T, Metzen MG, Sproule MK, Chacron MJ - PLoS Comput. Biol. (2015)

Bottom Line: Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input.We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally.Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science, McGill University, Montreal, Quebec, Canada.

ABSTRACT
Neurons that respond selectively but in an invariant manner to a given feature of natural stimuli have been observed across species and systems. Such responses emerge in higher brain areas, thereby suggesting that they occur by integrating afferent input. However, the mechanisms by which such integration occurs are poorly understood. Here we show that midbrain electrosensory neurons can respond selectively and in an invariant manner to heterogeneity in behaviorally relevant stimulus waveforms. Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input. To test this hypothesis, we built a model based on the Hodgkin-Huxley formalism that received realistic afferent input. We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally. Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli. We discuss the implications of our findings for the electrosensory and other systems.

No MeSH data available.


Related in: MedlinePlus

Verifying the model’s prediction.A) Membrane potential response (blue) of an example feature invariant TS neuron to sinusoidal stimulation (black). Membrane depolarizations were observed during both the rising and the falling phases of the stimulus (red dashed lines). B) The average membrane potential response (blue) during one stimulus cycle (black) was clearly bimodal and displayed two peaks that were approximately 180° out of phase (red dashed lines). C) The membrane potential power spectrum displayed most power (red arrow) at frequencies higher than that of the sinusoidal stimulation (black arrow). Inset: Bimodality index computed from 2 feature invariant TS neurons that were recorded from intracellularly.
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pcbi.1004430.g009: Verifying the model’s prediction.A) Membrane potential response (blue) of an example feature invariant TS neuron to sinusoidal stimulation (black). Membrane depolarizations were observed during both the rising and the falling phases of the stimulus (red dashed lines). B) The average membrane potential response (blue) during one stimulus cycle (black) was clearly bimodal and displayed two peaks that were approximately 180° out of phase (red dashed lines). C) The membrane potential power spectrum displayed most power (red arrow) at frequencies higher than that of the sinusoidal stimulation (black arrow). Inset: Bimodality index computed from 2 feature invariant TS neurons that were recorded from intracellularly.

Mentions: To test 2), we investigated the membrane potential responses of feature invariant TS neurons to sinusoidal input. We note that ON and OFF-type ELL pyramidal cells respond only during the rising and falling phases of such stimuli, respectively [36, 37]. Thus, if feature invariant TS neurons receive excitatory input from both ON and OFF-type ELL pyramidal cells, then we would expect to see membrane potential depolarizations during both the rising and falling phases of the sinusoidal stimulus. Fig 9A shows the membrane potential response of an example TS neuron to sinusoidal stimulation. Confirming our hypothesis, we observed depolarizations during both the rising and falling phases of the stimulus (Fig 9A, dashed red lines). The average membrane potential response to one stimulus cycle (Fig 9B) was clearly bimodal. This was confirmed by computing the power spectral density of the membrane potential that showed maximum power at twice the stimulus frequency (Fig 9C, red arrow) and much less power at the stimulus frequency (Fig 9C, black arrow). We computed a bimodality index whose value is 1 if the neuron responds equally at two phases π radians apart and zero if the neuron only responds at one phase (see Methods). We found values of 0.67 and 0.52 for both TS neurons (Fig 9C, inset). The implications of these results are discussed below.


Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli.

Aumentado-Armstrong T, Metzen MG, Sproule MK, Chacron MJ - PLoS Comput. Biol. (2015)

Verifying the model’s prediction.A) Membrane potential response (blue) of an example feature invariant TS neuron to sinusoidal stimulation (black). Membrane depolarizations were observed during both the rising and the falling phases of the stimulus (red dashed lines). B) The average membrane potential response (blue) during one stimulus cycle (black) was clearly bimodal and displayed two peaks that were approximately 180° out of phase (red dashed lines). C) The membrane potential power spectrum displayed most power (red arrow) at frequencies higher than that of the sinusoidal stimulation (black arrow). Inset: Bimodality index computed from 2 feature invariant TS neurons that were recorded from intracellularly.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4608831&req=5

pcbi.1004430.g009: Verifying the model’s prediction.A) Membrane potential response (blue) of an example feature invariant TS neuron to sinusoidal stimulation (black). Membrane depolarizations were observed during both the rising and the falling phases of the stimulus (red dashed lines). B) The average membrane potential response (blue) during one stimulus cycle (black) was clearly bimodal and displayed two peaks that were approximately 180° out of phase (red dashed lines). C) The membrane potential power spectrum displayed most power (red arrow) at frequencies higher than that of the sinusoidal stimulation (black arrow). Inset: Bimodality index computed from 2 feature invariant TS neurons that were recorded from intracellularly.
Mentions: To test 2), we investigated the membrane potential responses of feature invariant TS neurons to sinusoidal input. We note that ON and OFF-type ELL pyramidal cells respond only during the rising and falling phases of such stimuli, respectively [36, 37]. Thus, if feature invariant TS neurons receive excitatory input from both ON and OFF-type ELL pyramidal cells, then we would expect to see membrane potential depolarizations during both the rising and falling phases of the sinusoidal stimulus. Fig 9A shows the membrane potential response of an example TS neuron to sinusoidal stimulation. Confirming our hypothesis, we observed depolarizations during both the rising and falling phases of the stimulus (Fig 9A, dashed red lines). The average membrane potential response to one stimulus cycle (Fig 9B) was clearly bimodal. This was confirmed by computing the power spectral density of the membrane potential that showed maximum power at twice the stimulus frequency (Fig 9C, red arrow) and much less power at the stimulus frequency (Fig 9C, black arrow). We computed a bimodality index whose value is 1 if the neuron responds equally at two phases π radians apart and zero if the neuron only responds at one phase (see Methods). We found values of 0.67 and 0.52 for both TS neurons (Fig 9C, inset). The implications of these results are discussed below.

Bottom Line: Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input.We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally.Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science, McGill University, Montreal, Quebec, Canada.

ABSTRACT
Neurons that respond selectively but in an invariant manner to a given feature of natural stimuli have been observed across species and systems. Such responses emerge in higher brain areas, thereby suggesting that they occur by integrating afferent input. However, the mechanisms by which such integration occurs are poorly understood. Here we show that midbrain electrosensory neurons can respond selectively and in an invariant manner to heterogeneity in behaviorally relevant stimulus waveforms. Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input. To test this hypothesis, we built a model based on the Hodgkin-Huxley formalism that received realistic afferent input. We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally. Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli. We discuss the implications of our findings for the electrosensory and other systems.

No MeSH data available.


Related in: MedlinePlus