Cortical synthesis of azimuth-sensitive single-unit responses with nonmonotonic level tuning: a thalamocortical comparison in the cat

1996 ◽  
Vol 75 (3) ◽  
pp. 1206-1220 ◽  
Author(s):  
P. Barone ◽  
J. C. Clarey ◽  
W. A. Irons ◽  
T. J. Imig

1. Azimuth and sound pressure level (SPL) tuning to noise stimulation was characterized in single-unit samples obtained from primary auditory cortex (AI) and in areas of the medial geniculate body (MGB) that project to AI. The primary aim of the study was to test the hypothesis that AI is an important site of synthesis of single-unit responses that exhibit both azimuth sensitivity (tendency for directionally restricted responsiveness) and nonmonotonic (NM) level tuning (tendency for decreased responsiveness with increasing SPL). This was accomplished by comparing the proportions of such responses in AI and MGB. 2. Samples consisted of high-best-frequency (BF) single units located in MGB (n = 217) and AI (n = 216) of barbiturate-anesthetized cats. The MGB sample was obtained mainly from recording sites located in two nuclei that project to AI, the ventral nucleus (VN, n = 118) and the lateral part of the posterior group of thalamic nuclei (Po, n = 84). In addition, a few MGB units were obtained from the medial division (n = 8) or uncertain locations (n = 7). Each unit's responses were studied using noise bursts presented from azimuthal sound directions distributed throughout 180 degrees of the frontal hemifield at 0 degrees elevation. SPL was varied over an 80-dB range in steps of < or = 20 dB at each location. Similarities and differences in azimuth and level tuning were evaluated statistically by comparing the AI sample with the entire MGB sample. If they were found to differ, the AI, VN, and Po samples were compared. 3. Azimuth function modulation was used as a measure of azimuth sensitivity, and its mean was greater in AI than in MGB. NM strength was defined as the percentage reduction in level function value at 75 dB SPL and its mean was greater in AI (showing a greater tendency for decreased responsiveness) than in MGB. Azimuth-sensitive (AS) NM units were identified by jointly categorizing each sample according to both azimuth sensitivity (sensitive and insensitive categories) and NM strength (NM and monotonic categories). AS NM units were much more common in the AI sample than in any of the MGB samples, suggesting that some such responses are synthesized in AI. 4. A vast majority of AI NM units have been reported to be AS, showing a preferential association (linkage) between these two response properties. This finding was confirmed in AI, but was not found to be the case in MGB. This suggests that a linkage between these response properties emerges in the cortex, presumably as a result of synthesis of NM AS responses. Although the functional significance of the linkage is unknown, NM responses may reflect excitatory/inhibitory antagonism that provides AS AI neurons with sensitivity to stimulus features beyond that which is present in MGB. 5. Breadth of azimuth tuning of AS cells was measured as the portion of the frontal hemifield over which azimuth function values were > 75% of maximum (preferred azimuth range, PAR). PARs were broadly distributed in each structure, and mean PAR was narrower in AI than in MGB. A preferred level range (PLR) was defined for NM level functions as the range over which values were > 75% of maximum, and mean PLRs were similar in each sample. There was a weak, but significant, positive correlation between PARs and PLRs in AI but not in MGB. This further suggests a linkage between azimuth and level tuning in AI that does not exist in MGB. 6. Best azimuth (midpoint of the PAR) was used to classify cells as contralateral preferring, ipsilateral preferring, midline preferring, or multipeaked. Samples from AI and MGB exhibited similar distributions of these categories. Contralateral-preferring cells represented a majority of each sample, whereass midline-preferring, ipsilateral-preferring, and multipeaked cells each represented smaller proportions. This suggests that the azimuth preference distribution in AI largely reflects that in MGB. 7. A best SPL was defined as the midpoint of the PLR. This wa

2000 ◽  
Vol 84 (3) ◽  
pp. 1330-1345 ◽  
Author(s):  
Frank K. Samson ◽  
Pascal Barone ◽  
W. Andrew Irons ◽  
Janine C. Clarey ◽  
Pierre Poirier ◽  
...  

Azimuth tuning of high-frequency neurons in the primary auditory cortex (AI) is known to depend on binaural disparity and monaural spectral (pinna) cues present in broadband noise bursts. Single-unit response patterns differ according to binaural interactions, strength of monaural excitatory input from each ear, and azimuth sensitivity to monaural stimulation. The latter characteristic has been used as a gauge of neural sensitivity to monaural spectral directional cues. Azimuth sensitivity may depend predominantly on binaural disparity cues, exclusively on monaural spectral cues, or on both. The primary goal of this study was to determine whether each cortical response pattern corresponds to a similar pattern in the medial geniculate body (MGB) or whether some patterns are unique to the cortex. Single-unit responses were recorded from the ventral nucleus (Vn) and lateral part of the posterior group of thalamic nuclei (Po), tonotopic subdivisions of the MGB. Responses to free-field presentation of noise bursts that varied in azimuth and sound pressure level were obtained using methods identical to those used previously in field AI. Many units were azimuth sensitive, i.e., they responded well at some azimuths, and poorly, if at all, at others. These were studied further by obtaining responses to monaural noise stimulation, approximated by reversible plugging of one ear. Monaural directional (MD) cells were sensitive to the azimuth of monaural noise stimulation, whereas binaural directional (BD) cells were either insensitive to its azimuth or monaurally unresponsive. Thus BD and MD cells show differential sensitivity to monaural spectral cues. Monaural azimuth sensitivity could not be used to interpret the spectral sensitivity of predominantly binaural cells that exhibited strong binaural facilitation because they were either unresponsive or poorly responsive to monaural stimulation. The available evidence suggests that some such cells are sensitive to spectral cues. The results do not indicate the presence of any response types in AI that are not present in the MGB. Vn and Po contain similar classes of MD and BD cells. Because Po neurons project to the anterior auditory field, neurons in this cortical area also are likely to exhibit differential sensitivity to binaural disparity and monaural spectral cues. Comparison of these MGB data with a published report of cochlear nucleus (CN) single-unit azimuth tuning shows that MGB sensitivity to spectral cues is considerably stronger than CN sensitivity.


2020 ◽  
Vol 30 (5) ◽  
pp. 3130-3147
Author(s):  
Jonathan Y Shih ◽  
Kexin Yuan ◽  
Craig A Atencio ◽  
Christoph E Schreiner

Abstract Classic spectrotemporal receptive fields (STRFs) for auditory neurons are usually expressed as a single linear filter representing a single encoded stimulus feature. Multifilter STRF models represent the stimulus-response relationship of primary auditory cortex (A1) neurons more accurately because they can capture multiple stimulus features. To determine whether multifilter processing is unique to A1, we compared the utility of single-filter versus multifilter STRF models in the medial geniculate body (MGB), anterior auditory field (AAF), and A1 of ketamine-anesthetized cats. We estimated STRFs using both spike-triggered average (STA) and maximally informative dimension (MID) methods. Comparison of basic filter properties of first maximally informative dimension (MID1) and second maximally informative dimension (MID2) in the 3 stations revealed broader spectral integration of MID2s in MGBv and A1 as opposed to AAF. MID2 peak latency was substantially longer than for STAs and MID1s in all 3 stations. The 2-filter MID model captured more information and yielded better predictions in many neurons from all 3 areas but disproportionately more so in AAF and A1 compared with MGBv. Significantly, information-enhancing cooperation between the 2 MIDs was largely restricted to A1 neurons. This demonstrates significant differences in how these 3 forebrain stations process auditory information, as expressed in effective and synergistic multifilter processing.


1985 ◽  
Vol 53 (3) ◽  
pp. 836-851 ◽  
Author(s):  
T. J. Imig ◽  
A. Morel

Responses of single units and clusters of units to tone-burst stimulation were recorded at 100-micron intervals along vertical electrode penetrations through the lateral part of the posterior group of thalamic nuclei (Po) in five barbiturate-anesthetized cats. Best frequencies and minimum response latencies to tone-burst stimulation were studied at each location along a penetration. Most of Po is located rostral to the medial geniculate body (MGB) and is contiguous with the ventral nucleus and medial division. Po is characterized physiologically by narrowly tuned, short-latency (less than 40 ms) responses. Considerable scatter of best frequencies occurs along electrode penetrations, although a clear tonotopic organization is apparent in the distribution of best frequencies obtained from several electrode penetrations located in the same frontal plane of an individual brain. A "single" frequency is represented as an irregularly shaped lamina. A three-dimensional "block" model of the tonotopic organization of Po is described in which the highest best frequencies are located caudally, and the lowest best frequencies are located rostrally within the nucleus. The high-frequency representation of Po is contiguous with the high-frequency representation of the ventral nucleus of the MGB. The low- and middle-frequency representations of the ventral nucleus and Po are discontinuous. The ventral nucleus and Po have similar physiological properties and together constitute the tonotopic division of the auditory thalamus in the cat. Neurons in the medial division adjacent to the medial border of Po are larger than neurons in Po, lack tonotopic organization, and respond at short latencies.


2002 ◽  
Vol 445 (1) ◽  
pp. 78-96 ◽  
Author(s):  
Justin S. Cetas ◽  
Robin O. Price ◽  
David S. Velenovsky ◽  
Jennifer J. Crowe ◽  
Donal G. Sinex ◽  
...  

2021 ◽  
Author(s):  
Yuanqing Zhang ◽  
Xiaohui Wang ◽  
Lin Zhu ◽  
Siyi Bai ◽  
Rui Li ◽  
...  

Cortical feedback has long been considered crucial for modulation of sensory processing. In the mammalian auditory system, studies have suggested that corticofugal feedback can have excitatory, inhibitory, or both effects on the response of subcortical neurons, leading to controversies regarding the role of corticothalamic influence. This has been further complicated by studies conducted under different brain states. In the current study, we used cryo-inactivation in the primary auditory cortex (A1) to examine the role of corticothalamic feedback on medial geniculate body (MGB) neurons in awake marmosets. The primary effects of A1 inactivation were a frequency-specific decrease in the auditory response of MGB neurons coupled with an increased spontaneous firing rate, which together resulted in a decrease in the signal-to-noise ratio. In addition, we report for the first-time that A1 robustly modulated the long-lasting sustained response of MGB neurons which changed the frequency tuning after A1 inactivation, e.g., neurons with sharp tuning increased tuning bandwidth whereas those with broad tuning decreased tuning bandwidth. Taken together, our results demonstrate that corticothalamic modulation in awake marmosets serves to enhance sensory processing in a way similar to center-surround models proposed in visual and somatosensory systems, a finding which supports common principles of corticothalamic processing across sensory systems.


2007 ◽  
Vol 98 (2) ◽  
pp. 681-695 ◽  
Author(s):  
Philip H. Smith ◽  
Edward L. Bartlett ◽  
Anna Kowalkowski

The paralaminar nuclei, including the medial division of the medial geniculate nucleus, surround the auditory thalamus medially and ventrally. This multimodal area receives convergent inputs from auditory, visual, and somatosensory structures and sends divergent outputs to cortical layer 1, amygdala, basal ganglia, and elsewhere. Studies implicate this region in the modulation of cortical 40-Hz oscillations, cortical information binding, and the conditioned fear response. We recently showed that the basic anatomy and intrinsic physiology of paralaminar cells are unlike that of neurons elsewhere in sensory thalamus. Here we evaluate the synaptic inputs to paralaminar cells from the inferior and superior colliculi and the cortex. Combined physiological and anatomical evidence indicates that paralaminar cells receive both excitatory and inhibitory inputs from both colliculi and excitatory cortical inputs. Excitatory inputs from all three sources typically generate small summating EPSPs composed of AMPA and NMDA components and terminate primarily on smaller dendrites and occasionally on dendritic spines. The cortical input shows strong paired-pulse facilitation (PPF), whereas both collicular inputs show weak PPF or paired-pulse depression (PPD). EPSPs of cells with no low-threshold calcium conductance do not evoke a burst response when the cell is hyperpolarized. Longer-latency EPSPs were seen and our evidence indicates that these arise from axon collateral inputs of other synaptically activated paralaminar cells. The inhibitory collicular inputs are GABAergic, activate GABAA receptors, and terminate on dendrites. Their activation can greatly alter EPSP-generated spike number and timing.


1983 ◽  
Vol 11 (2) ◽  
pp. 235-247 ◽  
Author(s):  
E. Rouiller ◽  
Y. de Ribaupierre ◽  
A. Morel ◽  
F. de Ribaupierre

2001 ◽  
Vol 85 (6) ◽  
pp. 2303-2323 ◽  
Author(s):  
Alon Fishbach ◽  
Israel Nelken ◽  
Yehezkel Yeshurun

Primary segmentation of visual scenes is based on spatiotemporal edges that are presumably detected by neurons throughout the visual system. In contrast, the way in which the auditory system decomposes complex auditory scenes is substantially less clear. There is diverse physiological and psychophysical evidence for the sensitivity of the auditory system to amplitude transients, which can be considered as a partial analogue to visual spatiotemporal edges. However, there is currently no theoretical framework in which these phenomena can be associated or related to the perceptual task of auditory source segregation. We propose a neural model for an auditory temporal edge detector, whose underlying principles are similar to classical visual edge detector models. Our main result is that this model reproduces published physiological responses to amplitude transients collected at multiple levels of the auditory pathways using a variety of experimental procedures. Moreover, the model successfully predicts physiological responses to a new set of amplitude transients, collected in cat primary auditory cortex and medial geniculate body. Additionally, the model reproduces several published psychoacoustical responses to amplitude transients as well as the psychoacoustical data for amplitude edge detection reported here for the first time. These results support the hypothesis that the response of auditory neurons to amplitude transients is the correlate of psychoacoustical edge detection.


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