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Eric E Thomson

Publications and source records attributed to Eric E Thomson.

3 recordsLinked to original sources

Encoding and decoding touch location in the leech CNS.

Spike times encode stimulus values in many sensory systems, but it is generally unknown whether such temporal variations are decoded (i.e., whether they influence downstream networks that control behavior). In the present study, we directly address this decoding problem by quantifying both sensory encoding and decoding in the leech. By mechanically stimulating the leech body wall while recording from mechanoreceptors, we show that pairs of leech sensory neurons with overlapping receptive fields encode touch location by their relative latencies, number of spikes, and instantaneous firing rates, with relative latency being the most accurate indicator of touch location. We then show that the relative latency and count are decoded by manipulating these variables in sensory neuron pairs while simultaneously monitoring the resulting behavior. Although both variables are important determinants of leech behavior, the decoding mechanisms are more sensitive to changes in relative spike count than changes in relative latency.

Action Potentials↗

Location and intensity discrimination in the leech local bend response quantified using optic flow and principal components analysis.

In response to touches to their skin, medicinal leeches shorten their body on the side of the touch. We elicited local bends by delivering precisely controlled pressure stimuli at different locations, intensities, and durations to body-wall preparations. We video-taped the individual responses, quantifying the body-wall displacements over time using a motion-tracking algorithm based on making optic flow estimates between video frames. Using principal components analysis (PCA), we found that one to three principal components fit the behavioral data much better than did previous (cosine) measures. The amplitudes of the principal components (i.e., the principal component scores) nicely discriminated the responses to stimuli both at different locations and of different intensities. Leeches discriminated (i.e., produced distinguishable responses) between touch locations that are approximately a millimeter apart. Their ability to discriminate stimulus intensity depended on stimulus magnitude: discrimination was very acute for weak stimuli and less sensitive for stronger stimuli. In addition, increasing the stimulus duration improved the leech's ability to discriminate between stimulus intensities. Overall, the use of optic flow fields and PCA provide a powerful framework for characterizing the discrimination abilities of the leech local bend response.

Animals↗

Quantifying stimulus discriminability: a comparison of information theory and ideal observer analysis.

Performance in sensory discrimination tasks is commonly quantified using either information theory or ideal observer analysis. These two quantitative frameworks are often assumed to be equivalent. For example, higher mutual information is said to correspond to improved performance of an ideal observer in a stimulus estimation task. To the contrary, drawing on and extending previous results, we show that five information-theoretic quantities (entropy, response-conditional entropy, specific information, equivocation, and mutual information) violate this assumption. More positively, we show how these information measures can be used to calculate upper and lower bounds on ideal observer performance, and vice versa. The results show that the mathematical resources of ideal observer analysis are preferable to information theory for evaluating performance in a stimulus discrimination task. We also discuss the applicability of information theory to questions that ideal observer analysis cannot address.

Algorithms↗