Sequence Sensitivity of Neurons in Cat Primary Auditory Cortex

Coleman Laboratory, W.M. Keck Center for Integrative Neuroscience, University of California at San Francisco, San Francisco, CA 94143-0732, USA.
Cerebral Cortex (Impact Factor: 8.67). 01/2001; 10(12):1155-67. DOI: 10.1093/cercor/10.12.1155
Source: PubMed


Properties of sequence-sensitive neurons in primary auditory cortex of cats were explored in detail. Stimuli were sequences of two tones, in which the frequency and intensity of the first tone and the temporal separation between the first and second, or probe, tone were parametrically varied. After presentation of the first tone, the responses of 32 single units and 48 multiunits to the probe tone were found to be enhanced up to 140-5270% (median 340%) above the response obtained in the single-tone condition. Probe tone enhancement was induced from a considerable number of sequence conditions and depended on the frequency and intensity of the first tone and on the temporal separation between the onsets of the first and the probe tone. On average, the maximally enhanced response occurred when the first tone was 1 octave below or above the probe tone and its intensity was 14 dB louder than the probe tone. The most effective temporal separation of the tones for an enhancement effect was approximately 100 ms. The range of enhancing tones was largely outside the excitatory tuning curve of a neuron. Results extend previous findings of properties of sequence-sensitive neurons in the auditory cortex of echolocating bats and non-echolocating mammals, and suggest that sequence-sensitive neurons are quite common and involved in the cortical representation of spectrotemporal patterns of acoustic signals.

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    • "Bartlett & Wang, 2005; Brosch & Scheich, 2008; Sadagopan & Wang, 2009). With both fast-and slowly-decaying synaptic adaptation , 16% of columns in the model showed facilitation – a lower proportion than the 40–60% values found in single-unit measurements in primates (Brosch & Schreiner, 2000; Bartlett & Wang, 2005; Brosch & Scheich, 2008). Irrespective of the time constant of synaptic adaptation, the magnitude of facilitation peaked in the lower range (110–140%), resembling the results from primate studies . "
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    ABSTRACT: Incoming sounds are represented in the context of preceding events, and this requires a memory mechanism that integrates information over time. Here, it was demonstrated that response adaptation, the suppression of neural responses due to stimulus repetition, might reflect a computational solution that auditory cortex uses for temporal integration. Adaptation is observed in single-unit measurements as two-tone forward masking effects and as stimulus-specific adaptation (SSA). In non-invasive observations, the amplitude of the auditory N1m response adapts strongly with stimulus repetition, and it is followed by response recovery (the so-called mismatch response) to rare deviant events. The current computational simulations described the serial core-belt-parabelt structure of auditory cortex, and included synaptic adaptation, the short-term, activity-dependent depression of excitatory corticocortical connections. It was found that synaptic adaptation is sufficient for columns to respond selectively to tone pairs and complex tone sequences. These responses were defined as combination sensitive, thus reflecting temporal integration, when a strong response to a stimulus sequence was coupled with weaker responses both to the time-reversed sequence and to the isolated sequence elements. The temporal complexity of the stimulus seemed to be reflected in the proportion of combination-sensitive columns across the different regions of the model. Our results suggest that while synaptic adaptation produces facilitation and suppression effects, including SSA and the modulation of the N1m response, its functional significance may actually be in its contribution to temporal integration. This integration seems to benefit from the serial structure of auditory cortex. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
    European Journal of Neuroscience 03/2015; 41(5):615-30. DOI:10.1111/ejn.12820 · 3.18 Impact Factor
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    • "Brosch et al. (1999) observed maximal enhancement of multi-unit responses in A1 of anesthetized macaque monkeys when a pair of tones were delivered with a stimulus-onset-asynchrony of 120 ms and a frequency separation of about one octave. A similar observation was made in A1 of anesthetized cats where the maximally enhanced responses occurred when the first tone was above one octave below or above the subsequently delivered second tone (Brosch and Schreiner, 2000). Brosch et al. (2013) reported that, in the caudomedial field of anesthetized macaque monkey auditory cortex, the likelihood of synchronization between spontaneous firings of a pair of simultaneously recorded multi-unit clusters was highest when the best frequencies of the two clusters were about an octave apart. "
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    ABSTRACT: A fundamental structure of sounds encountered in the natural environment is the harmonicity. Harmonicity is an essential component of music found in all cultures. It is also a unique feature of vocal communication sounds such as human speech and animal vocalizations. Harmonics in sounds are produced by a variety of acoustic generators and reflectors in the natural environment, including vocal apparatuses of humans and animal species as well as music instruments of many types. We live in an acoustic world full of harmonicity. Given the widespread existence of the harmonicity in many aspects of the hearing environment, it is natural to expect that it be reflected in the evolution and development of the auditory systems of both humans and animals, in particular the auditory cortex. Recent neuroimaging and neurophysiology experiments have identified regions of non-primary auditory cortex in humans and non-human primates that have selective responses to harmonic pitches. Accumulating evidence has also shown that neurons in many regions of the auditory cortex exhibit characteristic responses to harmonically related frequencies beyond the range of pitch. Together, these findings suggest that a fundamental organizational principle of auditory cortex is based on the harmonicity. Such an organization likely plays an important role in music processing by the brain. It may also form the basis of the preference for particular classes of music and voice sounds.
    Frontiers in Systems Neuroscience 12/2013; 7:114. DOI:10.3389/fnsys.2013.00114
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    • "Spectral analysis would therefore seem to be a redundant task for auditory cortex, and it has been suggested that its function is to perform temporal binding (Nelken, 2004). In indirect support of this, there is a wealth of observations from cortex confirming the fact that nerve cells respond selectively to temporally complex sounds (McKenna et al., 1989; Rauschecker et al., 1995; Wang et al., 1995; Brosch and Schreiner, 1997, 2000; Rauschecker, 1997; Brosch et al., 1999; Tian et al., 2001; Kilgard and Merzenich, 2002; Bartlett and Wang, 2005; Brosch and Scheich, 2008; Recanzone, 2008; Sadagopan and Wang, 2009). Behaviorally, temporal binding appears to operate concurrently on many time scales, as is made evident by our ability to make sense of speech both on the word and sentence levels. "
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    ABSTRACT: The ability to represent and recognize naturally occuring sounds such as speech depends not only on spectral analysis carried out by the subcortical auditory system but also on the ability of the cortex to bind spectral information over time. In primates, these temporal binding processes are mirrored as selective responsiveness of neurons to species-specific vocalizations. Here, we used computational modeling of auditory cortex to investigate how selectivity to spectrally and temporally complex stimuli is achieved. A set of 208 microcolumns were arranged in a serial core-belt-parabelt structure documented in both humans and animals. Stimulus material comprised multiple consonant-vowel (CV) pseudowords. Selectivity to the spectral structure of the sounds was commonly found in all regions of the model (N = 122 columns out of 208), and this selectivity was only weakly affected by manipulating the structure and dynamics of the model. In contrast, temporal binding was rarer (N = 39), found mostly in the belt and parabelt regions. Thus, the serial core-belt-parabelt structure of auditory cortex is necessary for temporal binding. Further, adaptation due to synaptic depression-rendering the cortical network malleable by stimulus history-was crucial for the emergence of neurons sensitive to the temporal structure of the stimuli. Both spectral selectivity and temporal binding required that a sufficient proportion of the columns interacted in an inhibitory manner. The model and its structural modifications had a small-world structure (i.e., columns formed clusters and were within short node-to-node distances from each other). However, simulations showed that a small-world structure is not a necessary condition for spectral selectivity and temporal binding to emerge. In summary, this study suggests that temporal binding arises out of (1) the serial structure typical to the auditory cortex, (2) synaptic adaptation, and (3) inhibitory interactions between microcolumns.
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