Sound localization and timing computations in the auditory

Sound localization and timing computations in the auditory brain stem. J Rinzel, NYU • Computational and experimental study – coincidence detection and ITD coding (gerbil MSO, in vitro) • Subthreshold dynamic negative feedback: GKLT activ’n; phasic firing; brief temporal integration window; integration of noisy inputs (STA) • The definitive feedforword neuron: bipolar dendrites and distrib’n of Iion • Coding: • population coding (slope or place code? ); role of inhibition; role of EPSP asymmetries + IKLT; • stimulus dependent filter/selectivity. with G Svirskis, R Dodla, V Kotak, D Sanes, M Day, B Doiron, P Jercog, N Golding Funded by NIMH, NIDCD and NSF.

In vivo data from the barn owl shows NL neurons encode ITD -30 µsec 4409 Hz 5 0 -300 -150 0 150 left ear leads right ear leads INTERAURAL TIME DIFFERENCE (µsec) 300 DELAY LINE INPUTS 50 A B C D E DELAY LINE INPUTS % MAXIMUM RESPONSE 100 ITD sensitivity arises from a coincidence detection mechanism, as in the Jeffress model PLACE CODE OUTPUTS

… place code or slope code? • in vivo gerbil: ITD-tuning peak is outside physiol range. • Inhibition shapes ITD-tuning. Brand et al. Nature, 2002

MSO neurons fire phasically, not to slow inputs. Blocking I KLT may convert to tonic. J Neurosci, 2002 Even after reducing I KLT, some neurons (older) remained phasic. INa fairly inactivated near rest.

HH-type model with currents: INa IKHT and subthreshold IKLT J Neurosci, 2002 IKHT IKLT Idealized model: integrate and fire with “IKLT” Network, 2003. INa m. V Phasic firing properties m. V msec

Slow ramp: no spike Fast ramp: one spike

Schematic of circuit for low frequency coincidence detection in mammals. (D Sanes w/ focus on gerbil. )

Network, 2003. Spike-generating current by reverse correlation. I, n. A 0. 2 Poisson PSGs from Nex + Ninh input fibers leaky I&F + IKLT below RMP 0. 1 spont rate Some expts: Detection of subthreshold signal amidst noisy background 0. 0 -8 -6 -4 -2 0 time before spike, ms IKLT narrows temporal integration window. Notice “dip”: IKLT is partially active at rest; transient hyperpolarization promotes spiking by deactivating IKLT.

J Neurosci, 2002 Poisson PSGs from Nex + Ninh input fibers DTX (IKLT blocker) ==> -- widening of integration window -- reduction of “dip” Spike triggered average “Isyn”, expeimental Response of MSO cell to brief “signal” in noise. Control After DTX

Selectivity endowed by IKLT depends on spectral profile of the input. w/ Day, Doiron J Neurophys, 2008. • Rothman-Manis (HH-type) 2003 model: Dynamic vs Frozen IKLT • Noisy input I(t); STEs {IST(tj)} discrete time ti 2 clouds in vector space • Discriminant analysis (feature extraction) finds “direction” that maximizes “distance” between clouds (Fisher criterion) projections of {IST(tj)} • For white noise input: no difference in STAs. Stim selec’n diff’ce (SSD)= 1 -misclassification error 150 Hz 650 Hz

Coincidence detection – a role for dendrites Compartmental model; 2 -variable minimal phasic model Gradient of length along tonotopic axis. Reduction of “false positives” Agmon-Snir, Carr, Rinzel: Nature ‘ 98

Biophysical model: gerbil MSO -- dendrites w/ P Jercog and Golding lab … ongoing “HH-type” cable model, based on I, V-clamp data (in vitro, gerbil, Golding, 2006). gex(t), τex=0. 2 ms g. KLT in S, IS and weak in D; active or “frozen” (passive); g. Na only in Axon. spike generation l/λ ≈ 0. 6 -0. 8 τm ≈ 0. 6 -1 ms

EPSP attenuation and temporal sharpening - subthreshold Theory Jercog, Rinzel Experiment Golding lab + V-clamp If g. KLT is “frozen”.

Attenuation and sharpening grow with propagation distance in model. Experiment Theory

Time difference sensitivity, enhanced for inputs to dendrite – subthreshold case.

Motion direction sensitivity. Passive cable, Rall (1964). Proximal to distal sequence: rapid rise, broad EPSP at soma. Distal to proximal sequence: latency, buildup to higher peak EPSP. “direction selectivity”

Response to “near then far” input is disadvantaged by wake of (dendritic) g. KLT along path to Soma.

Synaptic input must be fast for spike generation. Include axonal spike generation τex=0. 2 … spike τex=0. 5 no spike

Coincidence detection in model… with spikes in axon the definitive feedforward neuron. “ITD” = 0. 1 ms “ITD” = 0. 15 ms No back-propagating action potential.

Tuning for Interaural Time Difference (ITD), shaped by transient inhibition in vivo, gerbil Brand et al, 2002 • ITD peak is outside physiol range • Blocking inhibition shifts the ITD -tuning curve to “ 0”. Place code or slope code? • Contralateral excitation is preceded by inhibition. • Ipsilateral excitation precedes inhibition. Grothe, New roles for synaptic inhibition in sound localization, Nat. Rev. (2003)

ITD tuning in small mammals is sensitive to timed inhibition slope code Brand et al, Nature, 2002 ITD ipsi contra Δ Results with MSO cell model. Rothman et al ’ 93 Key parameters: τinh= 0. 1 ms, Δ = 0. 2 ms

Asymmetry in EPSPs shapes ITD tuning w/ Jercog, Sanes, Svirksis, Kotak - ongoing Contra EPSPs slower than Ipsi EPSPs Ipsi leading Contra leading If contra-EPSP is slower-rising, it recruits more IKLT before fast rise to threshold – lowering probability to fire. In vitro thick slice ITD in dish.

Asymmetry in EPSPs shapes ITD tuning w/ Jercog, Sanes, Svirksis, Kotak - ongoing In vitro thick slice ITD in dish. Contra pathway is longer greater latency for EPSPs Contra inputs are slower rising.

Effect of inhibition -- counteracts the advantage of faster-rising ipsi inputs. . . With inhibition Inhibition blocked τinh = 2 ms

Sound localization and timing computations in the auditory brain stem. J Rinzel, NYU • Computational and experimental study – coincidence detection and ITD coding (gerbil MSO, in vitro) • Subthreshold dynamic negative feedback: GKLT activ’n; phasic firing; brief temporal integration window; integration of noisy inputs (STA) • The definitive feedforword neuron: bipolar dendrites and distrib’n of Iion • Coding: • population coding (slope or place code? ); role of inhibition; role of EPSP asymmetries + IKLT; • stimulus dependent filter/selectivity. with G Svirskis, R Dodla, V Kotak, D Sanes, M Day, B Doiron, P Jercog, N Golding Funded by NIMH, NIDCD and NSF.