The Efficiency of Sensory Information Coding by Mechanoreceptor Neurons

Juusola, Mikko; French, Andrew S.

doi:10.1016/s0896-6273(00)80335-9

Cited by 78 publications

(75 citation statements)

References 34 publications

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“…The constant value of R within each group of experiments probably means that the sensory neurons all have similar general structure and function, with approximately the same noise level, and similar nonlinear contributions from stages such as action-potential encoding. The range of information capacity values (ϳ3-15 Bits/s) is lower than the value of ϳ200 Bits/s typically observed in spiking mechanoreceptors (Juusola and French, 1997), but not unreasonable, given the smaller available bandwidth, less controlled input signal, and more demanding recording conditions.…”

Section: Information Capacity and Signal-to-noise Levelsmentioning

confidence: 73%

Dynamic Characterization ofDrosophilaAntennal Olfactory Neurons Indicates Multiple Opponent Signaling Pathways in Odor Discrimination

French

Torkkeli²,

Schückel³

2011

J. Neurosci.

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Opponent signaling refers to processes in which antagonistic signals are produced by different, but closely related, stimuli. It allows enhanced discrimination and more accurate behavioral responses. We explored opponent signaling in the Drosophila melanogaster olfactory system by measuring frequency response functions between odorant concentrations and primary olfactory neuron responses. Random fluctuations in concentration of two aliphatic and two aromatic fruit odorants were used to modulate action potentials from basiconic antennal sensilla. We separated action potentials by two-dimensional cluster analysis using amplitude and cross-correlation with a median action-potential template. Frequency response functions were fitted with either bandpass or second-order low-pass functions and then divided into two polarity groups, excitatory and inhibitory, by fitting the frequency response functions. Cluster analysis gave two, three, or four action potential clusters for each sensillum recording. Sensilla were then grouped by the patterns of response polarities of the individual neurons into four sensillum types, one with four neurons and three with two neurons. All four odorant compounds produced a mixture of excitatory, inhibitory, and null responses in different neurons. Statistical analysis of frequency response parameters for individual odorants gave only weak correlation between dynamics and some neuron types, even when comparing the dynamics of excitatory and inhibitory responses to the same odorant. However, response dynamics were significantly different between aliphatic and aromatic compounds, and between the two aliphatic compounds. Each odorant caused opposing excitatory and inhibitory signals to be sent to the antennal lobe along at least two pairs of axonal pathways.

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Section: Information Capacity and Signal-to-noise Levelsmentioning

confidence: 73%

Dynamic Characterization ofDrosophilaAntennal Olfactory Neurons Indicates Multiple Opponent Signaling Pathways in Odor Discrimination

French

Torkkeli²,

Schückel³

2011

J. Neurosci.

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“…It is desirable, however, to obtain a quantitative measure of this reliability that is independent of the features encoded, the particular shapes of the action potentials, or any underlying mechanisms. We used repeated trial experiments to calculate the rate of information transfer between input and output, a standard measure used previously for spike rates (MacKay and McCulloch, 1952;Barlow, 1961;de Polavieja, 2002), for spike times (Juusola and French, 1997;Strong et al, 1998;Reinagel and Reid, 2000), and for the responses of graded neurons (van Steveninck and Laughlin, 1996; Juusola and de Polavieja, 2003). We calculated the rate of information transfer for three different cases: the full voltage waveform, spike waveforms alone, and stereotyped action potential trains in which the actual action potentials are replaced by the average (stereotyped) action potential waveform (Fig.…”

Section: Reliability Of Encoding Of Stimulus History Into Spike Wavefmentioning

confidence: 99%

Stimulus History Reliably Shapes Action Potential Waveforms of Cortical Neurons

Polavieja

Harsch²,

Kleppe³

et al. 2005

Journal of Neuroscience

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Action potentials have been shown to shunt synaptic charge to a degree that depends on their waveform. In this way, they participate in synaptic integration, and thus in the probability of generating succeeding action potentials, in a shape-dependent way. Here we test whether the different action potential waveforms produced during dynamical stimulation in a single cortical neuron carry information about the conductance stimulus history. When pyramidal neurons in rat visual cortex were driven by a conductance stimulus that resembles natural synaptic input, somatic action potential waveforms showed a large variability that reliably signaled the history of the input for up to 50 ms before the spike. The correlation between stimulus history and action potential waveforms had low noise, resulting in information rates that were three to four times larger than for the instantaneous spike rate. The reliable correlation between stimulus history and spike waveforms then acts as a local encoding at the single-cell level. It also directly affects neuronal communication as different waveforms influence the production of succeeding spikes via differential shunting of synaptic charge. Modeling was used to show that slow conductances can implement memory of the stimulus history in cortical neurons, encoding this information in the spike shape.

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“…In some neurons, the information capacity for the spike train is 5-to 15-fold lower than for the graded potential (de Ruyter van Steveninck and Laughlin, 1996;Juusola and French 1997;Haag and Borst, 1998), implying 80 -95% information loss. The loss depends on the temporal structure of the stimulus and the response, on the noise properties of the neuron, and on the time scale used for analysis (Kretzberg et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the stochastically gated ion channels that comprise the spike generator contribute significantly to variability in the spike train (van Rossum et al, 2003). Together, such mechanisms reduce the signal-to-noise (S/N) ratio (Barlow, 1957), implying that, in the conversion to a spike train, the spike generator removes information, some selectively and some indiscriminately (Juusola and French, 1997).…”

Section: Introductionmentioning

confidence: 99%

Spike Generator Limits Efficiency of Information Transfer in a Retinal Ganglion Cell

Dhingra

Smith

2004

J. Neurosci.

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The quality of the signal a retinal ganglion cell transmits to the brain is important for preception because it sets the minimum detectable stimulus. The ganglion cell converts graded potentials into a spike train with a selective filter but in the process adds noise. To explore how efficiently information is transferred to spikes, we measured contrast detection threshold and increment threshold from graded potential and spike responses of brisk-transient ganglion cells. Intracellular responses to a spot flashed over the receptive field center of the cell were recorded in an intact mammalian retina maintained in vitro at 37°C. Thresholds were measured in a single-interval forced-choice procedure with an ideal observer. The graded potential gave a detection threshold of 1.5% contrast, whereas spikes gave 3.8%. The graded potential also gave increment thresholds approximately twofold lower and carried ϳ60% more gray levels. Increment threshold "dipped" below the detection threshold at a low contrast (Ͻ5%) but increased rapidly at higher contrasts. The magnitude of the "dipper" for both graded potential and spikes could be predicted from a threshold nonlinearity in the responses. Depolarization of the cell by current injection reduced the detection threshold for spikes but also reduced the range of contrasts they can transmit. This suggests that contrast sensitivity and dynamic range are related in an essential trade-off.

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The Efficiency of Sensory Information Coding by Mechanoreceptor Neurons

Cited by 78 publications

References 34 publications

Dynamic Characterization ofDrosophilaAntennal Olfactory Neurons Indicates Multiple Opponent Signaling Pathways in Odor Discrimination

Dynamic Characterization ofDrosophilaAntennal Olfactory Neurons Indicates Multiple Opponent Signaling Pathways in Odor Discrimination

Stimulus History Reliably Shapes Action Potential Waveforms of Cortical Neurons

Spike Generator Limits Efficiency of Information Transfer in a Retinal Ganglion Cell

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