Functional organization of the primary auditory cortex of the free-tailed bat Tadarida brasiliensis

Macías, Silvio; Bakshi, Kushal; Smotherman, Michael

doi:10.1007/s00359-020-01406-w

Cited by 6 publications

(7 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, information about the frequency response areas of the sampled neurons and the sensitivity to the partial overlap between the two echoes was lacking. In a survey of the response properties of neurons in the A1 of the Mexican free-tailed bat, the majority of neurons were more sensitive to dFM regardless of whether or not they contained spectral notches [40,64]. The dynamic range in spiking rates was similarly low in the Mexican free-tailed bat (roughly 0-6 spikes per stimulus) to that reported for the big-brown bat (0-3 spikes per stimulus) even at high amplitudes [8].…”

Section: Discussionmentioning

confidence: 76%

“…The A1 of the Mexican free-tailed bat is tonotopically organized following the general pattern found in mammals [39,40]. Neurons tuned to higher frequencies are positioned rostrally and have shorter response latencies than those tuned to lower frequencies [27,[40][41][42][43][44][45][46]. Since neurons tuned to higher frequencies have longer latencies, the presentation of a flat-spectrum dFM should cause a smooth sequential activation of neurons in A1 along the anterior-posterior axis.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Temporal coding of echo spectral shape in the bat auditory cortex

et al. 2020

Self Cite

View full text Add to dashboard Cite

Echolocating bats rely upon spectral interference patterns in echoes to reconstruct fine details of a reflecting object’s shape. However, the acoustic modulations required to do this are extremely brief, raising questions about how their auditory cortex encodes and processes such rapid and fine spectrotemporal details. Here, we tested the hypothesis that biosonar target shape representation in the primary auditory cortex (A1) is more reliably encoded by changes in spike timing (latency) than spike rates and that latency is sufficiently precise to support a synchronization-based ensemble representation of this critical auditory object feature space. To test this, we measured how the spatiotemporal activation patterns of A1 changed when naturalistic spectral notches were inserted into echo mimic stimuli. Neurons tuned to notch frequencies were predicted to exhibit longer latencies and lower mean firing rates due to lower signal amplitudes at their preferred frequencies, and both were found to occur. Comparative analyses confirmed that significantly more information was recoverable from changes in spike times relative to concurrent changes in spike rates. With this data, we reconstructed spatiotemporal activation maps of A1 and estimated the level of emerging neuronal spike synchrony between cortical neurons tuned to different frequencies. The results support existing computational models, indicating that spectral interference patterns may be efficiently encoded by a cascading tonotopic sequence of neural synchronization patterns within an ensemble of network activity that relates to the physical features of the reflecting object surface.

show abstract

Section: Discussionmentioning

confidence: 76%

Section: Introductionmentioning

confidence: 99%

Temporal coding of echo spectral shape in the bat auditory cortex

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although substantial effects of stimulus rate on tuning sharpness have been documented in former studies ( O’Neill and Suga, 1982 ; Wong et al, 1992 ; Wu and Jen, 1996 , 2006b ; Galazyuk et al, 2000 ; Smalling et al, 2001 ; Jen et al, 2002 ; Zhou and Jen, 2006 ), delay tuning is commonly examined by using synthesized call-echo pairs as acoustic stimuli ( Dear and Suga, 1995 ; Hagemann et al, 2010 ; Kössl et al, 2012 , 2015 ; Hechavarría et al, 2013 ; Macías et al, 2016a , 2020b ). These stimuli only mimic portions of the echolocation signals ( Figure 4A ) and are far beyond a naturalistic stimulus context ( Sullivan, 1982b ; Casseday and Covey, 1996 ; Galazyuk et al, 2005 ; Feng, 2011 ; Wenstrup et al, 2012 ; Hechavarría and Kössl, 2014 ; Suga, 2015 ).…”

Section: Influence Of the Temporal Context On Neural Processingmentioning

confidence: 99%

“…The accessibility of naturalistic orientation signals makes the investigation of the neural underpinnings of echolocation behavior a promising field of research. Traditionally, electrophysiological studies are conducted by using synthesized echolocation signals that represent only portions of naturalistic echolocation signals ( Dear and Suga, 1995 ; Kössl et al, 2015 ; Macías et al, 2020b ). Hereby, both the call dynamics and the temporal context of acoustic signals, i.e., the organization of echolocation signals in sequences, has often been neglected.…”

Section: Introductionmentioning

confidence: 99%

Neural Processing of Naturalistic Echolocation Signals in Bats

Beetz

Hechavarría

2022

Front. Neural Circuits

View full text Add to dashboard Cite

Echolocation behavior, a navigation strategy based on acoustic signals, allows scientists to explore neural processing of behaviorally relevant stimuli. For the purpose of orientation, bats broadcast echolocation calls and extract spatial information from the echoes. Because bats control call emission and thus the availability of spatial information, the behavioral relevance of these signals is undiscussable. While most neurophysiological studies, conducted in the past, used synthesized acoustic stimuli that mimic portions of the echolocation signals, recent progress has been made to understand how naturalistic echolocation signals are encoded in the bat brain. Here, we review how does stimulus history affect neural processing, how spatial information from multiple objects and how echolocation signals embedded in a naturalistic, noisy environment are processed in the bat brain. We end our review by discussing the huge potential that state-of-the-art recording techniques provide to gain a more complete picture on the neuroethology of echolocation behavior.

show abstract

“…The free-tailed bat auditory system is distinguished by possessing a prominent auditory fovea, or overrepresented frequency range of 20-30 kHz and an overall sensitivity range of about 12-80 kHz. The auditory fovea begins with biomechanical specializations in the cochlea (Vater and Siefer, 1995), continues through the inferior colliculus (Pollak et al, 1978) and extends to the auditory cortex (Macias et al, 2020b), and is believed to provide greater sensitivity for detecting prey at longer ranges and higher speeds. Thus, while their pulses extend above 100 kHz, neurophysiological results indicate that their auditory system is mostly constrained to a bandwidth of 20-80 kHz and especially sensitive to the first harmonic of the emitted pulses.…”

Section: Acoustic Measurementsmentioning

confidence: 99%

Biosonar discrimination of fine surface textures by echolocating free-tailed bats

2022

Self Cite

View full text Add to dashboard Cite

Echolocating bats are able to discriminate between different surface textures based on the spectral properties of returning echoes. This capability is likely to be important for recognizing prey and for finding suitably perching sites along smooth cave walls. Previous studies showed that bats may exploit echo spectral interference patterns in returning echoes to classify surface textures, but a systematic assessment of the limits of their discrimination performance is lacking and may provide important clues about the neural mechanisms by which bats reconstruct target features based on echo acoustic cues. We trained three Mexican free-tailed bats (Tadarida brasiliensis) on a Y-maze to discriminate between the surfaces of 10 different sheets of aluminum-oxide abrasive sandpapers differing in standardized grit sizes ranging from 40 grit (coarse, 425 μm mean particle diameter) to 240 grit (fine, 54 μm mean particle diameter). Bats were rewarded for choosing the coarsest of two choices. All three bats easily discriminated all abrasive surfaces from a smooth plexiglass control and between all sandpaper comparisons except the two with the smallest absolute difference in mean particle sizes, the 150 vs. 180 grit (92 vs. 82 μm) and the 220 vs. 240 grit (68 vs. 54 μm) surfaces. These results indicate that echolocating free-tailed bats can use slight variations in the echo spectral envelope to remotely classify very fine surface textures with an acuity of at least 23 μm, which rivals direct tactile discrimination performance of the human hand.

show abstract

Functional organization of the primary auditory cortex of the free-tailed bat Tadarida brasiliensis

Cited by 6 publications

References 60 publications

Temporal coding of echo spectral shape in the bat auditory cortex

Temporal coding of echo spectral shape in the bat auditory cortex

Neural Processing of Naturalistic Echolocation Signals in Bats

Biosonar discrimination of fine surface textures by echolocating free-tailed bats

Contact Info

Product

Resources

About