1. Communication and Cortex The computational neuroethology of mouse vocalizations Robert Liu Sloan-Swartz Center for Theoretical Neurobiology University of California at San Francisco

2. Basic questions in neural coding How does the brain process behaviorally- relevant stimuli? Is the structure of natural stimuli “efficiently” represented by neurons?

3. Computational neuroethology Study organism in natural contexts (etho-)  Look for strong stimulus-behavior links  What are the properties of the stimulus? Determine relevant neural areas (neuro-)  How do neurons represent stimulus properties? Use behavior to constrain neural codes Study coding algorithms (compu-)  Use info theory to probe efficiency of neural codes

4. Auditory processing in mice Obvious behavioral context: communication  Vocalizations are natural input to auditory system  Behavioral response provides an observable output

5. Auditory processing in mice Obvious behavioral context: communication  Vocalizations are natural input to auditory system  Behavioral response provides an observable output Why the mouse?  Opportunities to employ genetic techniques  Extensive research on peripheral and non-cortical central auditory system  Rich ultrasound communication behaviors

6. Pup isolation calls maternal retrieval Mouse pup ultrasounds Time (ms) 0 200400600 25 100 25 100 25 100 Frequency (kHz)

7. Spectral domain  Categorical perception of bandwidth-limited ultrasound noise as pup-like (Ehret & Haack, 1982) Categorical perception of pup calls Time (ms) 0 4080120 30 90 Frequency (kHz) 60 Noise model

8. Spectral domain  Categorical perception of bandwidth-limited ultrasound noise as pup-like (Ehret & Haack, 1982) Categorical perception of pup calls Time (ms) 0 4080120 30 90 Frequency (kHz) 60 BW (kHz) 22.5 Response Noise model Pup-like

9. Adult mouse encounter calls Ultrasounds when males encounter females Time (ms) 0 200400600 25 100 25 100 25 100 Frequency (kHz)

10. Computational neuroethology Study organism in natural contexts (etho-)  Look for strong stimulus-behavior links  What are the properties of the stimulus? Determine relevant neural areas (neuro-)  How do neurons represent stimulus properties? Use behavior to constrain neural codes Study coding algorithms (compu-)  Use info theory to probe efficiency of neural codes

11. What frequencies make up a call? One frequency extracted as a function of time Frequency content of natural calls Time (ms) 04080 Number of 1 ms bins 02040 25 100 Frequency (kHz) 50 75 Spectrogram Histogram 25 100 Frequency (kHz) 50 75 Whistle-like simplicity

12. Typical frequency (kHz) 406080100 50 0 Duration (ms) 150 100 Pup call frequencies and durations Frequency and duration clusters  Main: 67 kHz/59 ms  Aux: 93 kHz/30 ms

13. Typical frequency (kHz) 406080100 50 0 Duration (ms) 150 100 Pup call frequencies and durations Frequency and duration clusters  Main: 67 kHz/59 ms  Aux: 93 kHz/30 ms Main cluster <22.5 kHz bandwidth for categorization  Natural distribution contributes to category formation?

14. Natural acoustic categories Typical frequency (kHz) 406080100 50 0 Duration (ms) 150 100 Adt: 80 kHz/23 ms Pup and adult calls clearly separate  ROC: 91% correct Adult call category to be distinguished from pup calls? Perhaps other cues also necessary to categorize

15. Call repetition periods Periods between call onsets different 0100200300400500 25 600 100 Time (ms) Freq (kHz) 25 100 Pup Adt

16. Call repetition periods Periods between call onsets different Adult calls repeat more quickly than pup calls  100 ms vs. 180 ms  ROC: 97% correct (frequency, duration, and period) Repetition period (ms) 0100200300400500 5 0 Probability (1/s) 10 0100200300400500 25 600 100 Time (ms) Freq (kHz) 25 100 Pup Adt

17. Conclusions Study organism in natural contexts (etho-)  What are the properties of the natural calls? Spectral and temporal clustering of pup and adult calls Determine relevant neural areas (neuro-)  How do neurons represent vocalization properties? Stimulus-locked neural oscillations reflect pup call periods Use behavior to constrain neural codes  The peak spike count in auditory cortex may support a categorical distinction

18. Collaborators Jennifer Linden Michael Merzenich Kenneth Miller Christoph Schreiner Mentors

20. Electrophysiology Experiments on recent CBA/CaJ mothers  Ketamine and medetomidine anesthesia  Multiunit activity recorded via tungsten electrodes inserted 400-600 microns below the surface  Targeted areas with ultrasound responses  Two free field speakers (low frequency range from 3 kHz to 40 kHz; high frequency range from 20 kHz to 100 kHz)  TDT System II equipment used to play out stimuli and record responses