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Ergodicity talk 2

Spike trains in the auditory pathway. Ergodicity talk 2. Petr Marsalek Department of Pathological Physiology, First Medical Faculty, Charles University in Prague, Czech Republic Max Planck Institute for the Physics of Complex Systems, Dresden, Germany

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Ergodicity talk 2

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  1. Spike trains in the auditory pathway Ergodicity talk 2 Petr Marsalek Department of Pathological Physiology, First Medical Faculty, Charles University in Prague, Czech Republic Max Planck Institute for the Physics of Complex Systems, Dresden, Germany Group Retreat, Oberwiesenthal, 2018

  2. Normal audiogram: x-axis, sound frequency (Hz), y-axis, sound pressure (Pa).Red top curve is pain threshold. Hearing threshold is Green bottom curve. Bluearecurvesof subjectively equivalent loudness level. dB SPL is objective unit, phone is subjective unit.Yellow blob is speech region.Gray lineis reference frequency 1000 Hz. Normal audiogram [loudness depending on pitch, in a textbook: Silbernagl, Despopoulos, Thieme, 2000]

  3. Objective /to Subjective Barrier;Physical /to Perceptual Energy • amplitude • frequency • spectrum • duration • azimuth modulation, etc • loudness • pitch • timbre • length • direction roughness, etc

  4. Objective /to Internal /to Subjective;transform is described as: psychophysical law,is also called psychometric function, R=f(S) Touch, stimulus: skin indenta-tion stimuli, internal response: spike trains in mechano- receptive fibers, Subjective: touch percept [Werner, Mountcastle, 1965]

  5. Vector strength, has values from 0 to 1. Is similar to correlation coefficient (which has values from –1 to 1). [Joris et al, 2006] [Goldberg and Brown, 1969]

  6. High, Middle and Low Spontaneous Rate auditory nerve fibres High, Middle and Low S.R. dB SPL, decibels of sound pressure level (objective units) spike rate (internal units) x-axis: stimulus intensity, dB SPL, y-axis: neuronal spike rate per s [WINTER I.M., PALMER A.R. Intensity coding in low-frequency auditory-nerve fibres of the guinea pig. J AcoustSoc Am 1991, 90, pp. 1958–1967] [Winter and Palmer, 1991]

  7. Physical /to Internal Representation ofPercept; Modality of Percept;Internal Representationby Spike Trains [Camalet, Duke, Julicher, Prost, 2000] [Winter and Palmer, 1991]

  8. “Canonical” spiking auditory model [Toth, Marsalek, Pokora, 2017]

  9. Circular statistics Circular statistics is used in description of repetitive events (time domain). It can cover time repetition on different time scales. (Examples: sound period, time gap in sound.) Can be used in description of horizontal sound localization (for different quantities: time or space). [Toth, Marsalek, Pokora, 2017]

  10. Examples with values r = 0.5, 0.8, 0.05 Vector strength r (Narrow) rectangular pulse, r = 0.8 sine with DC component, r = 0.05 [Toth, Marsalek, Pokora, 2017]

  11. Vector strength, spike timing jitter and other variability measures [Toth, Marsalek, Pokora, 2017]

  12. Discussion We present the relation of vector strength and dispersion as our original result; I found now that [Koeppl C, 1997] shows similar relation in barn owl spike trains

  13. sound azimuth, model and subjective response [Bouse, Vencovsky, Rund, Marsalek, submitted]

  14. (Coincidence) detection probability of two spikes converging on MSO neuron [Marsalek, Lansky, 2005]

  15. Reaction times [Toth, Marsalek, Pokora, 2017]

  16. Where is ergodicity used: Evoked (Response) Potentials AEP – auditory EP VEP – visual EP Repetition rate in brainstem ER audiometry Can be of low freq. sound (40 Hz). [R. Hari et al., Exp. Brain Res., 1980]

  17. Literary references [Werner, Mountcastle, J. Physiology, 1965], [Goldberg and Brown, J. Physiology 1969], [R. Hari et al., Exp. Brain Res., 1980] [C. Koeppl, J. Neuroscience, 1997], [Camalet, Duke, Julicher, Prost, Proc. Natl. Acad. Sci. USA, 2000], [Joris, et al., Hear. Res., 2006], etc [Marsalek, Lansky, Biol. Cybernetics, 2005], [Toth, Marsalek, Pokora, Biol. Cybernetics, 2017] [Bouse, Vencovsky, Rund, Marsalek, submited to: J. Acoust. Soc. Am., 2018] etc

  18. Conclusions 0 this is theoretical/ technical talk about how to construct models and/ or formulate hypotheses with statistical description in mind 1 aim is to model neurons in auditory (visual or any other sensory) pathway 2 description level is at spikes (action potentials) in neural circuits and post-synaptic potentials. they are unitary neuronal events 3 this is also known as neuronal “arithmetic” = computations with action potentials and post-synaptic potentials 4 (ergodic property is explained) 5 some examples of neuronal populations, time scales and statistical descriptions (in particular circular statistics) are discussed

  19. Sometimes the walls move…

  20. Thank you for your attention

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