Distinct Correlation Structure Supporting a Rate-Code for Sound Localization in the Owl’s Auditory Forebrain

Abstract

While a topographic map of auditory space exists in the vertebrate midbrain, it is absent in the forebrain. Yet, both brain regions are implicated in sound localization. The heterogeneous spatial tuning of adjacent sites in the forebrain compared to the midbrain reflects different underlying circuitries, which is expected to affect the correlation structure, i.e., signal (similarity of tuning) and noise (trial-by-trial variability) correlations. Recent studies have drawn attention to the impact of response correlations on the information readout from a neural population. We thus analyzed the correlation structure in midbrain and forebrain regions of the barn owl’s auditory system. Tetrodes were used to record in the midbrain and two forebrain regions, Field L and the downstream auditory arcopallium (AAr), in anesthetized owls. Nearby neurons in the midbrain showed high signal and noise correlations (RNCs), consistent with shared inputs. As previously reported, Field L was arranged in random clusters of similarly tuned neurons. Interestingly, AAr neurons displayed homogeneous monotonic azimuth tuning, while response variability of nearby neurons was significantly less correlated than the midbrain. Using a decoding approach, we demonstrate that low RNC in AAr restricts the potentially detrimental effect it can have on information, assuming a rate code proposed for mammalian sound localization. This study harnesses the power of correlation structure analysis to investigate the coding of auditory space. Our findings demonstrate distinct correlation structures in the auditory midbrain and forebrain, which would be beneficial for a rate-code framework for sound localization in the nontopographic forebrain representation of auditory space.

Effect of Stimulus-Dependent Spike Timing on Population Coding of Sound Location in the Owl’s Auditory Midbrain

“…This criterion led to five pairs of neurons being omitted; however, all neurons had at least one usable pair (n = 194 original pairs, 189 usable pairs). Nearby neurons in OT fired synchronously, as previously reported (Beckert et al, 2017). As predicted by the model, synchrony (assessed by the standard-CCG) was correlated with the GM firing rate both across the sampled population (r = 0.31; p , 0.0001; two-tailed t test; Fig.…”

“…We therefore hypothesize that binaural cue-dependent synchrony in ICcl underlies binaural cue-dependent synchrony downstream to ICx. Lastly, stimulus-dependent synchrony could be inherited from ICx to OT through the known shared point-topoint projections between these structures (Knudsen and Knudsen, 1983;Beckert et al, 2017). Simultaneous recording of nearby ICcl and ICx cells has proven challenging due to large evoked potentials corrupting spike sorting (Beckert MV and Pena JL unpublished observations).…”

“…Because the sound envelope is determined by the frequency spectrum (Louage et al, 2004), similar frequency selectivity in neurons with the same spatial tuning suggests these neurons may receive inputs with a similar envelope. In addition, it has recently been shown that nearby neurons in OT may share inputs (Beckert et al, 2017). However, neurons downstream the auditory pathway typically show reduced envelope locking (Lu et al, 2001;Joris et al, 2004;Louage et al, 2004;Christianson and Peña, 2007;Steinberg and Peña, 2011;Steinberg et al, 2013;Yao et al, 2015a,b).…”

Synthesis of Hemispheric ITD Tuning from the Readout of a Neural Map: Commonalities of Proposed Coding Schemes in Birds and Mammals

“…Studies in the owl's forebrain have reported evidence of a transformation in the neural code of ITD, where convergence across ITD channels leads to quasi-hemispherical ITD tuning Wagner, 2009, 2012). Furthermore, recent comparative population recordings in the owl's midbrain and forebrain showed differing correlation structure of nearby cells, where the hemispherical tuning of forebrain cells was associated with a significant drop in correlated variability of nearby cells, eliminating the potentially detrimental effect of noise correlation on information in a putative forebrain opponent-channel code (Beckert et al, 2017).…”

Neural Maps of Interaural Time Difference in the American Alligator: A Stable Feature in Modern Archosaurs

“…Transformation of the representation of ITDs may take place after the detection level (for review, see Vonderschen and Wagner, 2014). For example, there is evidence that in the owl forebrain a hemispheric rate code is realized (Beckert et al, 2017) in contrast to an ITD map in its midbrain (Wagner et al, 1987).…”