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date: 17 July 2019

Developmental Cortical Plasticity in the Central Auditory System

Abstract and Keywords

The brain has a tremendous ability to change as a result of experience. While the brain is plastic throughout life, during early development, the nervous system seems much more sensitive to changes in neural activity or experience. During postnatal critical or sensitive periods, sensory experience can significantly restructure cortical networks, leading to long-term changes in central representations that can affect perception and behavior. This chapter reviews how the parameters of the acoustic environment and inhibitory circuitry can regulate cortical plasticity during early life experience. It highlights newly identified cortical circuit elements that are specifically recruited to engage critical-period plasticity mechanisms.

Keywords: auditory, cortex, development, plasticity, critical period


Neural circuits in the developing brain are uniquely sensitive to experience, allowing brains and organisms to sensibly interact and adapt to environments. Early life experiences can result in significant modifications to brain structure, function, and ability. Human infants, for example, learn a unique language depending on the environment they are raised in, and will eventually acquire native fluency. Similarly, juvenile songbirds must hear tutor song early in life, typically from their father, to accurately reproduce the song later in life (Amin, Gastpar, & Theunissen, 2013; Marler & Peters, 1982). Similarly, juvenile zebra finches can learn the song of heterospecifics such as the Bengalese finch when tutored by an adult Bengalese finch (Woolley, Hauber, & Theunissen, 2010), demonstrating the remarkable experience-dependent flexibility of the developing auditory system. These specific epochs during development in which the brain is particularly susceptible to certain changes are referred to as “critical periods.” During a critical period, sensory experience results in significant modifications in structure and function.

This exquisite ability of the brain to adapt and learn is present throughout life. However, extensive studies conducted in numerous species indicate that there are important differences between the learning that occurs during development and that which occurs in adulthood. For example, exposure to passive stimuli early in development can result in significant changes to rodent primary auditory cortex (AI) tonotopic maps (Barkat, Polley, & Hensch, 2011; Chang & Merzenich, 2003; de Villers-Sidani, Chang, Bao, & Merzenich, 2007; Han, Köver, Insanally, Semerdjian, & Bao, 2007; Insanally, Köver, Kim, & Bao, 2009; Zhang, Bao, & Merzenich, 2001). In contrast, long-term modifications of adult auditory cortex generally require engagement of neuromodulatory systems that are activated during heightened periods of arousal and attention, or otherwise signal changes in behavioral context (Atiani et al., 2014; Bao, Chang, Davis, Gobeske, & Merzenich, 2003; Carcea, Insanally, & Froemke, 2017; David, Fritz, & Shamma, 2012; Fritz, David, Radtke-Schuller, Yin, & Shamma, 2010; Fritz, Shamma, Elhilali, & Klein, 2003; Froemke, Merzenich, & Schreiner, 2007; Kilgard, 2003; Kilgard & Merzenich, 1998; Kuchibhotla et al., 2017; Martins & Froemke, 2015; Otazu, Tai, Yang, & Zador, 2009).

Stimulus-Specific Critical Period Plasticity

The postnatal development of AI is particularly susceptible to the acoustic environment, and even relatively brief amounts of experience (or deafness) can have profound consequences for the development and function of this brain region. Specifically, rearing rodent pups in a single pulsed pure tone (i.e., an auditory stimulus composed of a single-frequency sinusoidal waveform) environment, for instance, results in an enlarged cortical representation for the experienced tone (Barkat et al., 2011; de Villers-Sidani et al., 2007; Han et al., 2007; Zhang et al., 2001). The critical period for tonotopic map organization in rodent A1 has been defined to be from postnatal days (P) 11 to 13 (de Villers-Sidani et al., 2007). This study delineated a time period during postnatal development of rat AI in which frequency representation can be manipulated simply through passive exposure. Moreover, early exposure to pure tones from P9–11 has been shown to accelerate the maturation of synaptic receptive fields of individual neurons at P12–16, and providing patterned stimulation precociously closes the critical period (Dorrn, Yuan, Barker, Schreiner, & Froemke, 2010).

In addition to pure tone stimuli, broadband white noise (i.e., an auditory stimulus having equal intensity at different frequencies, giving it a constant power spectral density) is a stimulus that has also been widely used to study critical-period plasticity. For example, rearing rats during the first month of life in pulsed white noise disrupts tonotopicity, degrades frequency tuning, and reduces temporal correlation between populations of neurons in A1 (Insanally, Albanna, & Bao, 2010; Zhang, Bao, & Merzenich, 2002), but it does not affect speech processing (Ranasinghe et al., 2012). In contrast, exposing animals to continuous white noise (rather than periodic noise bursts) for the first month of life seems to delay AI development; multi-unit frequency tuning profiles remain broad, and the AI map is poorly organized (Chang & Merzenich, 2003; Zhang et al., 2001; Zhou, Panizzutti, de Villers-Sidani, Madeira, & Merzenich, 2011). Rearing animals in continuous environmental noise for the first month of life also prolongs the duration of the AI tonotopic map critical period such that subsequent exposure to a single pure tone after the first month of life results in greater representation for that tone (Chang & Merzenich, 2003). Therefore, the temporal structure of noise inputs results in different plasticity effects in A1. Notably, early exposure of animals to a continuous tone seems to prolong the duration of the critical period (Zhou, Nagarajan, Mossop, & Merzenich, 2008). These studies indicate that the closure of the critical period window in AI requires temporally structured input.

In addition to the temporal structure, the spectral content of the acoustic environment also affects critical-period plasticity. Exposing animals to spectral band-notched noise results in critical-period closure for the portion of AI representing those absent frequencies, while exposing animals to band-pass noise kept the critical period open for those frequencies (de Villers-Sidani, Simpson, Lu, Lin, & Merzenich, 2008). Interestingly, chronic exposure to moderate-level noise in juvenile or adult rats can reopen a window for passive exposure to modify cortical organization similar to critical-period plasticity (Xiaoming Zhou et al., 2011). In addition, non-auditory cues such as visual experience have been shown to influence the duration and closure of auditory critical periods, suggesting a role for cross-modal plasticity during development (Mowery, Kotak, & Sanes, 2016).

While many studies of AI critical periods use either pure tones or white noise, presentation of other stimuli reveals that critical periods can be hierarchical and dynamic processes. When rats are exposed to frequency-modulated (FM) sweeps (i.e., an auditory stimulus where frequency varies in time) at different stages in early development, AI responses develop progressively, with selectivity for simpler acoustic features preceding those for more complex acoustic features (Insanally et al., 2009). Specifically, early exposure to FM sweeps results in altered characteristic frequency representations (Window 1: P8–15) and broadened spectral tuning in AI neurons (Window 2: P16–23, Figure 1A). In contrast, later exposure to the same FM sweeps leads to greater selectivity for the sweep rate and direction (Window 3: P24–31, and Window 4: P32–39, Figure 1B. These results indicate that cortical representations of different acoustic features are shaped by complex sounds in a series of distinct critical periods.

Developmental Cortical Plasticity in the Central Auditory SystemClick to view larger

Figure 1. Multiple critical periods in the primary auditory cortex of FM sweep exposed animals.

(A): Exposure to downward FM sounds in Window 2 (P16–23) broadens frequency tuning. Representative cortical tuning bandwidth (BW) maps based on BWs measured at 70 dB sound pressure level (SPL). Insets are representative receptive fields that had been recorded in the locations outlined in the bandwidth maps. The vertical axis of the receptive field plots depicts sound intensity from 0–70 dB SPL. The horizontal axis depicts frequencies from 1–32 kHz. The heatmap scale bar represents BWs in octaves. (B): Representative cortical maps based on χ2-based sweep direction selectivity. Experimental animals were exposed to downward sweeps in four different time windows. Animals that had heard the downward sweeps in Window 4 (P32–39) showed a negative shift of the selectivity index, indicating that the neurons were more selective for downward sweeps than those of the other groups. The heatmap scale bar represents a chi-squared–based sweep direction selectivity index (χ2 –SDSI).

Adapted with permission from Insanally et al., 2009.

Collectively, these studies provide strong evidence for the flexibility of cortical sound representations during development, after hearing-onset in rodents in the second postnatal week. Furthermore, the spectral and temporal structures of sound stimuli influence the formation of frequency tuning characteristics as well as the closure and time course of the critical period in rodent A1.

Behavioral Consequences of Critical-Period Plasticity

Manipulating the acoustic environment during development can have profound effects on perception. In a landmark study that was one of the first to demonstrate a direct effect of early experience on perception in rodents, exposure to pure tones from P9–30 enlarged cortical representation of the experienced frequency, but impaired perceptual discrimination near that frequency (Han et al., 2007). After sound-rearing, adult animals were trained on a frequency-discrimination task to detect a target tone from a sequence of standard tones. While discrimination near over-represented frequencies was impaired, discrimination of nearby under-represented frequencies improved, coinciding with the flanking frequency bands of the cortical tuning curve. This change in behavioral performance could be fully explained by plasticity effects in cortical frequency representations alone.

In contrast, rearing animals in environmental noise resulted in impaired gap-detection thresholds and an increase in N-methyl-D-aspartate (NMDA)-2B but not NMDA-2A receptor expression in auditory cortex (Sun, Tang, & Allman, 2011). This elevated expression of NMDA-2B receptors is consistent with a previous finding demonstrating an enhancement of NMDA-2B receptor-dependent long-term potentiation in rat auditory cortex following developmental noise exposure (Hogsden & Dringenberg, 2009). Strikingly, both extensive training and environmental acoustic enrichment during young adulthood can reverse the impairment in auditory cortical processing following early noise exposure (Zhou & Merzenich, 2009; Zhu et al., 2014). Rearing animals that were previously exposed to noise as juveniles in an acoustically enriched environment restored cortical response thresholds, cortical frequency tuning, and behavioral performance on a frequency discrimination task to near normal levels (Zhou & Merzenich, 2009). Similarly, intensive training on a temporal rate-discrimination task in noise-reared rats improved auditory cortical entrainment to higher repetition rates at 10–20 pulses per second (Zhu et al., 2014).

Auditory deprivation during development also affects cortical processing, sound localization and auditory perception (King, Parsons, & Moore, 2000; Knudsen, Esterly, & Knudsen, 1984; Knudsen, Knudsen, & Esterly, 1984; Kotak, Breithaupt, & Sanes, 2007; Kotak, Takesian, MacKenzie, & Sanes, 2013; Mowery, Kotak, & Sanes, 2015; Mowery et al., 2017; Parsons, Lanyon, Schnupp, & King, 1999; Polley, Thompson, & Guo, 2013; Popescu & Polley, 2010; Takesian, Kotak, Sharma, & Sanes, 2013). Even brief episodes of auditory deprivation from P11–23 can impair performance on an amplitude-modulation detection task in juveniles and adults (Bao, 2015; Caras & Sanes, 2015; Sanes & Woolley, 2011). It is unlikely that auditory deprivation leads to programmed cell death in the central auditory system, since cochlear lesions result in an expanded cortical representation of the frequencies adjacent to the lesion frequencies (Robertson & Irvine, 1989).

Inhibitory Regulation of AI Critical-Period Plasticity

What synaptic mechanisms account for the opening and closing of cortical critical periods? An extensive literature from the visual cortex implicates inhibitory circuits and synapses in the visual cortical critical period for ocular dominance plasticity (Bradshaw, Figueroa Velez, Habeeb, & Gandhi, 2018; Kuhlman et al., 2013; Morishita & Hensch, 2008). Likewise, developmental plasticity of auditory cortical circuits is thought to be controlled by inhibitory circuits (Chang, Bao, Imaizumi, Schreiner, & Merzenich, 2005; de Villers-Sidani et al., 2007; Froemke, 2015; Insanally et al., 2009; Polley et al., 2013; Popescu & Polley, 2010; Razak & Fuzessery, 2007). Both AI excitatory and inhibitory inputs are refined during development. Excitatory inputs have been shown to mature first and exhibit adult-like frequency tuning by P14 (Dorrn et al., 2010). Inhibitory inputs are present and can be strong upon hearing onset, but do not simply monotonically increase with age (Dorrn et al., 2010; Sun et al., 2010), and in general, inhibitory tuning has a protracted developmental time course relative to excitation (Chang et al., 2005; Dorrn et al., 2010). For the first two postnatal weeks, inhibitory inputs are initially poorly tuned, and become co-tuned with excitation during the third postnatal week (~P21) in normal-hearing animals. However, providing sensory input via patterned stimulation significantly sharpens inhibitory input in young, but not adult, animals and precludes further synaptic plasticity (Dorrn et al., 2010).

A recent study highlighted the importance of layer 1 interneurons for AI critical period plasticity. The 5-hydroxytryptamine 3a receptor-expressing (5HT3AR+ ) layer 1 interneurons receive both direct auditory thalamic input and neuromodulatory cholinergic inputs, making these neurons uniquely suited for controlling plasticity in deeper layers (Figure 2A). While dendritic arbors are restricted to the superficial layers, axonal projections of 5HT3AR+ interneurons descend to layer 4 where they directly target and inhibit parvalbumin (PV) interneurons (Figure 2B). Activation of these layer 1 interneurons can suppress thalamic-driven responses in layer 4 PV interneurons, consequently disinhibiting layer 4 pyramidal cells and providing a potential mechanism for critical-period plasticity. Inactivating 5HT3AR+ interneurons from P12–15 resulted in a loss of critical-period plasticity as measured by changes in medial geniculate body to primary auditory cortex (MGB-A1) connectivity in thalamocortical slices (Figure 2C–F). Interestingly, cholinergic recruitment of 5HT3AR+ layer 1 interneurons reopened critical-period plasticity in AI, suggesting a dual role for the inhibitory and neuromodulatory control of developmental cortical plasticity. This circuit organization is strikingly similar to neuromodulatory involvement and cortical disinhibition for auditory fear conditioning in adult animals (Letzkus et al., 2011). Notably, serotonergic projections from raphe nuclei are widespread throughout the central auditory system (Hurley & Hall, 2011), and 5-T receptor agonists have also been shown to modulate auditory cortical plasticity by inducing best frequency (defined as the tone frequency that results in the largest increase in activity) shifts when tones are paired with electrical shock (Ji & Suga, 2007).

Developmental Cortical Plasticity in the Central Auditory SystemClick to view larger

Figure 2. Inhibitory control of auditory critical period plasticity.

(A): Representative image of cholinergic and auditory thalamic axons targeting layer 1 cells in AI. (B): Representative image of 5-HT3AR+ cell axons contacting PV interneurons in layer 4 of AI. (C): Schematic of experimental timeline for silencing 5-HT3AR+ interneurons during the critical period. (D): Schematic of thalamocortical slice showing six different stimulation sites in MGB and locations responses were recorded from in layer 4 of A1. (E): AI responses to MGB stimulation at 6 different sites. (F): Mean topographic slopes for naïve, control, and silenced groups. E and F both demonstrate that inactivating 5-HT3AR+ interneurons from P12–15 prevented auditory critical period plasticity.

Adapted with permission from Takesian et al., 2018.

While inhibitory circuits are significantly modified during early postnatal development, these maturational changes are stunted by auditory deprivation (Sanes & Kotak, 2011; Takesian, Kotak, & Sanes, 2009). The effect of hearing loss on the inhibitory circuitry is most profound when inhibitory synapses are in the process of maturation (Takesian, Kotak, & Sanes, 2012). Developmental hearing loss results in an increase in auditory cortical excitability, a disruption to pre- and post-synaptic gamma-aminobutyric acid (GABA)-ergic synapses (Sarro, Kotak, Sanes, & Aoki, 2008), a decrease in inhibitory postsynaptic current (IPSC) amplitude, and a reduction in cortical GABA receptor function (Kotak, Takesian, & Sanes, 2008). Excitatory thalamic modulation of cortical interneurons has also been shown to be altered by hearing loss in developing animals (Takesian et al., 2013). These studies confirm that, in addition to excitatory circuits, inhibitory circuits are also strongly susceptible to the acoustic parameters of the environment.


While the acoustic regulation of critical-period dynamics has been extensively described (Barkat et al., 2011; Chang & Merzenich, 2003; de Villers-Sidani et al., 2007; Dorrn et al., 2010; Insanally et al., 2010, 2009; Zhou et al., 2008; Zhu et al., 2014), the functional consequences of developmental cortical plasticity remain vastly understudied (Bao, 2015; Han et al., 2007). Future studies, focusing on a mechanistic understanding of the circuit elements that drive perceptual shifts during development and in adulthood as a result of experience, will be crucial for revealing how the brain adapts to its environment. While intracortical inhibition plays an important role in regulating critical-period plasticity in a very narrow developmental window from P12–15 (Takesian, Bogart, Lichtman, & Hensch, 2018), inhibitory synaptic development continues for the first postnatal month. What is the functional significance of this protracted circuit restructuring? Finally, understanding how cortical neuromodulation and intracortical inhibition work in concert to remodel cortical circuits during development using modern optical techniques represents an exciting new avenue of research.


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