Abstract
Cortical areas are highly interconnected both via cortical and subcortical pathways, and primary sensory cortices are not isolated from this general structure. In primary sensory cortical areas, these pre-existing functional connections serve to provide contextual information for sensory processing and can mediate adaptation when a sensory modality is lost. Cross-modal plasticity in broad terms refers to widespread plasticity across the brain in response to losing a sensory modality, and largely involves two distinct changes: cross-modal recruitment and compensatory plasticity. The former involves recruitment of the deprived sensory area, which includes the deprived primary sensory cortex, for processing the remaining senses. Compensatory plasticity refers to plasticity in the remaining sensory areas, including the spared primary sensory cortices, to enhance the processing of its own sensory inputs. Here, we will summarize potential cellular plasticity mechanisms involved in cross-modal recruitment and compensatory plasticity, and review cortical and subcortical circuits to the primary sensory cortices which can mediate cross-modal plasticity upon loss of vision.
Introduction
It is well established that sensory experience can alter cortical and subcortical circuits, especially during early development. In addition, proper sensory experience is crucial for interacting with our environment. Upon loss of a sensory modality, for example, vision, an individual has to rely on the remaining senses to navigate the world. It has been documented that blind individuals show enhanced ability to discriminate auditory (Lessard et al., 1998; Röder et al., 1999; Gougoux et al., 2004; Voss et al., 2004), tactile (Grant et al., 2000; Van Boven et al., 2000) or olfactory (Cuevas et al., ; Renier et al., 2013) information. Plastic changes involved can be robust and long–lasting. For example, individuals with congenital bilateral cataracts demonstrate heightened reaction times to auditory stimuli even in adulthood long after surgical removal of cataracts (De Heering et al., ). Experimental evidence suggests that there is a rather widespread functional plasticity in the adult sensory cortices upon loss of a sensory modality (Lee and Whitt, 2015), which could constitute the neural basis for cross-modal plasticity (Bavelier and Neville, ; Merabet and Pascual-Leone, 2010). Here we use the terminology “cross-modal plasticity” in a broad context to refer to plasticity triggered across sensory modalities to allow adaptation to the loss of sensory input. Changes associated with cross-modal plasticity are often attributed to two distinct plasticity mechanisms that take place across various sensory cortices, some of which manifest at the level of primary sensory cortices (Figure 1). One process is functional adaptation of the primary sensory cortex deprived of its own inputs, which is referred to as “cross-modal recruitment” (Lee and Whitt, 2015) or as “cross-modal plasticity” in its narrower definition (Bavelier and Neville, ; Merabet and Pascual-Leone, 2010). The other process, manifested as changes in the functional circuit of the spared sensory cortices, is termed “compensatory plasticity” (Rauschecker, 1995; Lee and Whitt, 2015). A dramatic example of cross-modal recruitment is the activation of visual cortical areas, including the primary visual cortex, when blind individuals are reading braille (Sadato et al., 1996; Buchel et al., ; Burton and McLaren, ). Compensatory plasticity is observed as functional changes in the circuits of primary auditory and somatosensory cortices of blind individuals (Pascual-Leone and Torres, 1993; Sterr et al., 1998a, b; Elbert et al., ). The former is thought to enhance the processing of the remaining senses by recruiting the deprived sensory cortex for increasing the capacity of processing the remaining senses, while the latter is thought to allow refinement of the ability of the spared cortices to process the remaining sensory inputs.
Figure 1
At the neural level, depriving vision leads to specific adaptation of functional circuits within the primary visual cortex (V1), and a distinct set of changes in the primary auditory (A1) and the primary somatosensory (S1) cortices (Figure 2). As will be discussed in more detail in the subsequent sections, the former involves potentiation of lateral intracortical connections to the principal neurons in the superficial layers of V1 (Petrus et al., 2015; Chokshi et al., ), and the latter manifests as potentiation of the feedforward inputs that convey sensory inputs to the cortex (Petrus et al., 2014, 2015; Rodríguez et al., 2018) as well as functional refinement of the cortical circuits (Meng et al., 2015, 2017; Solarana et al., 2019). Cellular mechanisms underlying these two distinct plasticity modes involve both Hebbian and homeostatic metaplasticity as we will describe below, and are thought to be the plasticity of pre-existing functional circuits.
Figure 2
Central to understanding the phenomenon of cross-modal plasticity is the question of what functional circuits allow multisensory information to influence cross-modal recruitment and compensatory changes in primary sensory cortices. The focus of this review will be identifying these potential cortical and subcortical circuits. Most of our discussion will be focused on studies from rodents, which recently have generated cell-type specific data on functional and anatomical connections.
Cross-Modal Recruitment
Cross-modal recruitment describes the co-opting of a cortical area deprived of its own sensory input by the spared sensory modalities, so that those spared modalities may better guide behavior. While earlier studies have shown such cross-modal recruitment in early-onset blind individuals (Sadato et al., 1996; Buchel et al., ; Röder et al., 1999), a more recent study suggests that this can also manifest more acutely in adults. For example, temporarily blindfolding adults while training on braille leads to activation of V1 within a week as visualized in functional magnetic resonance imaging (fMRI; Merabet et al., 2008). Furthermore, this study demonstrated that V1 activity was essential for enhanced learning of braille reading in blindfolded individuals by showing that transcranial magnetic stimulation (TMS) of V1 removes this advantage in blindfolded adults. Cross-modal recruitment is not only restricted to the recruitment of V1 for other senses in blind but has been observed as activation of the auditory cortex by visual stimulation in deaf individuals (Sandmann et al., 2012). Hence such plasticity is thought to be a general principle across sensory cortices. While cross-modal recruitment is viewed as providing adaptive benefits to an individual, it has also been shown to restrict functional recovery of a deprived sense. For example, the success of restoring speech perception in deaf individuals using cochlear implants is inversely correlated with the degree of cross-modal recruitment of A1 by visual inputs (Sandmann et al., 2012).
Cellular and circuit-level plasticity related to cross-modal recruitment can be inferred from studies using various experimental paradigms designed to examine how the deprived cortices change following the loss of their respective sensory modalities. Sensory deprivation paradigms have been traditionally used to examine how sensory experience sculpts the developing sensory cortices. Starting from the initial pioneering work of Hubel and Wiesel, various visual deprivation studies have established the essential role of early visual experience in the proper development of both subcortical and cortical circuits serving visual processing (Hooks and Chen, 2020). While such studies demonstrate that visual cortical plasticity, i.e., ocular dominance plasticity (ODP), is limited to early development termed the “critical period,” the adult visual cortex is not devoid of plasticity. In particular, total deprivation of vision, for example in the form of dark-rearing, has been shown to extend the critical period for ODP (Cynader and Mitchell, ; Mower et al., 1981), and the current model is that such deprivation paradigm triggers homeostatic metaplasticity or changes in cortical inhibition to promote Hebbian plasticity involved in ODP (Cooke and Bear, ; Hooks and Chen, 2020). Furthermore, total deprivation of vision later in life, in the form of dark-exposure, has been shown to restore ODP in the adult visual cortex (He et al., 2007). At a cellular level, the ability to induce long-term synaptic plasticity, such as long-term potentiation (LTP) and long-term depression (LTD), in sensory cortices is critically dependent on the lamina location of these synapses. For example, across primary sensory cortices, thalamocortical synapses to layer 4 (L4) has an early critical period for plasticity (Crair and Malenka, ; Feldman et al., ; Jiang et al., 2007; Barkat et al., ), but synapses from L4 to L2/3 undergo plasticity through adulthood (Jiang et al., 2007). Interestingly, L2/3 is considered a location where top-down contextual information is provided for sensory processing and has been shown to exhibit modulation of activity by other sensory modalities (Lakatos et al., 2007; Iurilli et al., 2012; Ibrahim et al., 2016; Chou et al., ). L2/3 is a logical substrate for cross-modal recruitment because of its susceptibility to adult plasticity and its role in integrating top-down multisensory inputs.
Plasticity of V1 Circuit That Can Support Cross-modal Recruitment
Vision loss alters the strength of both excitatory and inhibitory synaptic transmission on V1 L2/3 principal neurons. Experiments in rodents have demonstrated that even as little as 2 days of visual deprivation leads to the strengthening of excitatory synapses observed as increases in the average amplitude of miniature excitatory postsynaptic currents (mEPSCs; Desai et al., ; Goel and Lee, 2007; Maffei and Turrigiano, 2008; Gao et al., 2010; He et al., 2012; Chokshi et al., ). This plasticity, which was initially interpreted as a form of in vivo synaptic scaling (Desai et al., ; Goel and Lee, 2007), is observed around the 3rd postnatal week (Desai et al., ; Goel and Lee, 2007) and persists through adulthood (Goel and Lee, 2007; Petrus et al., 2015). However, strengthening of excitatory synapses by visual deprivation is dependent on the mode of visual deprivation, such that total loss of vision is necessary, and it is not observed with bilateral lid-suture (He et al., 2012). Lid-suture is different from other modes of visual deprivation, such as dark-exposure, enucleation, or intraocular tetrodotoxin (TTX) injection, in that visual stimuli through the closed eyelids can elicit visually evoked potentials (VEPs) in V1 (Blais et al., ). This suggests that residual vision through the closed eyelids is sufficient to prevent visual deprivation-induced synaptic scaling. Sensory deprivation-induced strengthening of excitatory synapses is not restricted to V1 L2/3 but is observed in A1 L2/3 following a conductive hearing loss (Kotak et al., 2005). Interestingly, whisker deprivation is typically unable to increase the strength of excitatory synapses in barrel cortex L2/3 neurons (Bender et al., ; He et al., 2012; Li et al., 2014; see Glazewski et al., 2017 for exception) which suggests that whisker deprivation may be similar to lid-suture in that it may not completely remove all inputs to the barrel cortex.
In addition to the plasticity of the excitatory synapses, inhibitory synapses on principal neurons in V1 also undergo lamina-specific adaptation to visual deprivation, which differs depending on the developmental age. In V1 L4 of rodents, monocular deprivation before the critical period leads to a reduction of inhibition, measured as a decrease in both spontaneous and evoked inhibitory postsynaptic currents (IPSCs) in the deprived monocular zone of V1 (Maffei et al., 2004), whereas monocular deprivation during the critical period leads to an increase in inhibition (Maffei et al., 2006; Nahmani and Turrigiano, 2014). With L4 serving as the main thalamorecipient layer, this increase in inhibition within L4 later in development could serve to lower the recurrent activity and reduce the propagation of sensory information in V1. In L2/3, a few days of visual deprivation during the critical period leads to a reduction in the frequency of miniature inhibitory postsynaptic currents (mIPSCs; Gao et al., 2010, 2014). This decrease in mIPSC frequency correlated with a reduction in the density of perisomatic GAD65 punta (Gao et al., 2014) suggesting a decrease in the number of inhibitory synaptic contacts likely from local parvalbumin-positive (PV) interneurons. However, visual deprivation-induced plasticity of inhibitory synapses in the adult V1 L2/3 is different in that it is specific to action potential-independent inhibitory synaptic transmission (Barnes et al., ; Gao et al., 2017), which suggests that it is not likely due to changes in the number of inhibitory synapses. The selective plasticity of action potential independent mIPSCs is thought to benefit sensory processing in the mature cortex by maintaining temporal coding while providing homeostasis of overall neural activity (Gao et al., 2017).
In terms of the mode of plasticity, initial studies have interpreted the overall increase in mEPSC amplitudes following visual deprivation in the framework of synaptic scaling (Desai et al., ; Goel and Lee, 2007). However, recent data suggest that the changes are not global across all synapses but are input-specific and restricted mainly to intracortical synapses without changes in the feedforward input from L4 (Petrus et al., 2015; Figure 2A). Furthermore, the increase in mEPSC amplitudes with visual deprivation requires NMDA receptor (NMDAR) activation (Rodríguez et al., 2018), which distinguishes it from synaptic scaling which has been shown not to require the activity of NMDARs (O’Brien et al., 1998; Turrigiano et al., 1998). On the contrary, experimental evidence suggests that synaptic scaling induced by inactivity is accelerated when blocking NMDARs (Sutton et al., 2006). The observation that visual deprivation-induced potentiation of excitatory synapses in V1 L2/3 is input-specific and dependent on NMDAR activity suggests that it is likely a manifestation of Hebbian LTP following metaplasticity as proposed by the Bienenstock-Cooper-Monroe (BCM) model (Bienenstock et al., ; Bear et al., ; Cooper and Bear, ; Lee and Kirkwood, 2019; Figure 3). The BCM model, often referred to as the “sliding threshold” model, posits that the synaptic modification threshold for LTP/LTD induction “slides” is a function of the past history of neural activity. An overall reduction in neural activity, as would occur in V1 following visual deprivation, is expected to lower the synaptic modification threshold to promote LTP induction. Indeed, studies have demonstrated that visual deprivation can lower the LTP induction threshold in V1 L2/3 (Kirkwood et al., 1996; Guo et al., 2012). However, to induce LTP with the lowered synaptic modification threshold, synaptic activity is required. While visual deprivation reduces the overall activity in V1, a recent study reported that spontaneous activity is increased following a few days of visual deprivation in the form of dark exposure (Bridi et al., ). In addition, the study demonstrated that this increase in spontaneous activity is critical for strengthening excitatory synapses on V1 L2/3 neurons dependent on the activity of the GluN2B subunit of NMDARs (Bridi et al., ). It is possible that visual deprivation-induced reduction in the inhibitory synaptic transmission (Gao et al., 2010, 2014; Barnes et al., ) may contribute to enhance spontaneous activity or help facilitate the induction of LTP. Collectively, these studies suggest a novel model in which visual deprivation reduces the threshold for LTP induction, and the increase in spontaneous activity acts on NMDARs to trigger potentiation of excitatory synapses, which tend to be of intracortical origin. Therefore, understanding the potential source of these intracortical synapses to V1 L2/3 will provide insights into how V1 may undergo cross-modal recruitment in the absence of vision.
Figure 3
In the following sections, we will review potential cortical and subcortical structures that can mediate cross-modal plasticity observed with vision loss. The anatomical locations of these structures are highlighted in Figure 4. First, we will provide information on potential functional circuits involved in cross-modal recruitment of V1, which involve cortico-cortical connections from multisensory or spared sensory cortices. Some of these cortical interactions involve indirect functional circuits mediated by subcortical structures. In addition, we will outline various neuromodulatory systems, which can enhance or enable plasticity of these intracortical and subcortical inputs to V1.
Figure 4

Anatomical structures implicated in cross-modal plasticity induced by vision loss. Six coronal sections of a mouse brain are listed in order from posterior to anterior. Structures involved in cross-modal recruitment are labeled in green (V1, LM, PM, AM, AL, RSP, ACg, LD, PO), structures involved in compensatory plasticity are labeled in orange (A1, S1, MD, TRN), and those involved in both are labeled with stripes of green and orange (LC, superior colliculus (SC), RA, LP, BF). Darker shades (V1, A1, S1) represent cortical structures that have been experimentally demonstrated to undergo plasticity with visual deprivation, while lighter shades are tentative structures implicated in the plasticity. Primary sensory thalamic nuclei are labeled in gray (dLGN, MGBv, VPM). Inset in each panel shows the location of the coronal section plane. (A) The locus coeruleus (LC) contains the cell bodies of most norepinephrine expressing neurons. These cells send vast projections across cortical areas and are involved in both attention and arousal. Following vision loss, the increased salience of auditory and somatosensory cues might be conveyed through norepinephrine projections, facilitating potentiation in spared sensory cortices (compensatory plasticity) as well as potentiation of spared inputs into V1 (cross-modal recruitment). The relative concentration of norepinephrine is thought to play a role in determining the polarity spike-timing-dependent of plasticity (STDP; Seol et al., 2007). (B) The lateral medial visual area (LM) and the posteromedial visual area (PM) are both HVAs, which flank V1. HVAs process higher-order visual information and provide feedback connections to V1 which modulate V1 activity. Visual deprivation leads to plasticity specifically of intracortical inputs in L2/3 pyramidal neurons without changes in the strength of feedforward inputs from the thalamus to L4 or from L4 to L2/3 (Petrus et al., 2014, 2015; Chokshi et al.,
Cortical Inputs to V1 L2/3 That Can Mediate Cross-modal Recruitment
V1 L2/3 cells are a probable substrate for multimodal recruitment of V1 due to their extensive and varied inputs. Intracortical inputs onto L2/3 of V1 originate from various sources, including local connections from within V1, feedback projections from higher-order visual areas (HVAs), other sensory cortices, as well as other cortical areas (e.g., Wertz et al., 2015; Figure 5). A recent monosynaptic tracing of presynaptic partners of a single V1 L2/3 pyramidal neuron showed that these neurons receive inputs from 70 to 800 neurons across many brain regions with the majority of them (50–700 neurons) situated within V1 (Wertz et al., 2015). In addition to these local inputs, V1 L2/3 neurons receive multisensory information from other cortical areas via direct long-range intracortical connections, as well as indirectly via subcortical structures (Figure 5; “Subcortical Sources of Inputs to V1 L2/3 That Can Mediate Cross-modal Recruitment” section). Therefore, V1 L2/3 could mediate a role in cross-modal recruitment in the absence of vision.
Figure 5

Cortical and subcortical circuits for multisensory influence on V1. The laminar profile of subcortical inputs from dLGN and LP to V1 is shown on the left. Major interlaminar excitatory connections are shown next in blue arrows followed by the inhibitory local circuit in L2/3. Next, the major outputs of L5 and L6 neurons are shown. At the rightmost side, the origins and laminar profiles of cortical inputs to V1 are shown. Subcortical structures are shown below V1 and cortical structures are listed on the right side. Arrows (→) depict excitatory inputs and inputs ending in a round circle (—•) show inhibitory connections. The extent of the spread of inputs to V1 that span different laminae are depicted as vertical bars. V1 L2/3 and L5A neurons form reciprocal connections with HVA neurons (Kim et al., 2015; Glickfeld and Olsen, 2017), which is omitted in the figure for clarity. Direct cortico-cortical connections that can provide multisensory information to V1 originate from HVA, A1, S1, RSP, and ACg. In addition, as depicted in the figure many of the subcortical and cortical structures form cortico-thalamo-cortical loops that can provide multisensory influence on V1: for example, HVA–LP–V1, PFC–MD–TRN–dLGN–V1, S1/A1–TRN–dLGN–V1, and S1/A1–SC–LP–V1.
Cortical inputs that reside locally within V1 serve as the major source of excitatory inputs onto L2/3 neurons with local L2/3 inputs being the most numerous (Binzegger et al.,
A second major source of cortical inputs to V1 L2/3 is feedback connections from HVAs (Wertz et al., 2015). In higher mammals, including humans and primates, HVAs integrate and process higher-order visual information, such as form and movement of objects (Orban, 2008). In rodents, 10 HVAs are anatomically identified, using intrinsic signal imaging, surrounding V1 (Garrett et al., 2014; Glickfeld and Olsen, 2017). While in primates and carnivores, HVAs are mostly hierarchically organized such that the main feedback to V1 is from the secondary visual cortex (V2, area 18; Felleman and Van Essen,
The influence of HVA feedback connections in V1 is highlighted by a phenomenon called the perceptual “filling-in” effect (Weil and Rees, 2011). Individuals with a focal scotoma will perceive the missing visual space as being “filled-in” such that the person is often unaware of the scotoma (Bender and Teuber,
In addition to the indirect route through HVAs, other sensory modalities can also gain access to V1 via direct connections (Figure 5). Anatomical tracing studies have demonstrated direct cortico-cortical projections from A1 (Iurilli et al., 2012; Wertz et al., 2015; Ibrahim et al., 2016; Deneux et al.,
Multisensory cortical regions serve as another source through which V1 can be recruited by other sensory modalities after the loss of vision (Figure 5). One such region is the anterior cingulate cortex (ACg). Using tracing methods, it was shown that ACg neurons contain two distinct populations, L2/3, and L5 neurons that project directly to V1 and neurons primarily in L5 that project to the superior colliculus (SC; Zhang et al., 2016). Consistent with this anatomy, ACg has been shown to directly (Zhang et al., 2016) and indirectly (Hu et al., 2019) modulate the activity of V1 neurons. Optogenetic activation of ACg axons elicits a short latency monosynaptic EPSC and a longer latency disynaptic IPSC in V1 L2/3 neurons (Zhang et al., 2014), which illustrates recruitment of both excitatory and inhibitory networks. There are two indirect routes through which the ACg exerts its modulatory activity on V1 neurons. The first is through the SC and the posterior lateral posterior nucleus of the thalamus (pLP; ACg-SC-pLP-V1) and the second via the anterior LP (ACg-aLP-V1; Hu et al., 2019). Activating both pathways enhances visual behavior as well as responses in V1 neurons (Hu et al., 2019). While LP receives inputs from ACg and projects to V1, whether the ACg recipient LP neurons are the ones projecting to V1 is unclear. A recent study suggests that ACg projects to medial LP (mLP), which does not project directly to V1, but to HVAs (AL, RL, AM, PM; Bennett et al.,
The retrosplenial cortex (RSP) is another multisensory area directly linked to V1. Neurons from the RSP were shown to directly synapse unto V1 L2/3 neurons (Wertz et al., 2015) and L6 cortico-thalamic neurons (Vélez-Fort et al., 2014). These V1 projecting RSP neurons were also shown to be responsive to rotation implicating them as a potential source of head-related motion signals to V1 (Vélez-Fort et al., 2014). The RSP also received inputs directly from A1 and indirectly from S1 through the claustrum (Todd et al., 2019). RSP also forms reciprocal cortico-cortical connections between ACg and V1 (ACg–RSP–V1; Zhang et al., 2016). The influence of multisensory cortex on sensory processing is not limited to V1. Pairing of a tone with the activation of the frontal cortex leads to enhanced frequency selectivity and functional organization in A1 neurons (Winkowski et al., 2018).
Recently, posterior parietal cortex (PPC) has been suggested to play a role in cross-modal recruitment (Gilissen and Arckens, 2021). This is based on the multisensory nature of PPC and its functional modulation of V1 (Hishida et al., 2018). Recent studies demonstrated that PPC is involved in resolving sensory conflict during auditory-visual discrimination tasks (Song et al., 2017) and is involved in transferring sensory-specific signals to higher order association areas (Gallero-Salas et al.,
Subcortical Sources of Inputs to V1 L2/3 That Can Mediate Cross-modal Recruitment
In addition to inputs from cortical areas, V1 also receives multimodal information from various subcortical regions (Figure 5). The lateral posterior nucleus (LP), posterior thalamic nucleus (PO), and lateral dorsal nucleus of the thalamus (LD) all project directly to V1 and might be potential sources of multimodal input subserving cross-modal recruitment.
The higher-order visual thalamus, called the lateral posterior nucleus (LP) in rodents, is equivalent to the pulvinar in primates (Baldwin et al.,
The posterior thalamic nucleus (PO) and lateral dorsal nucleus of thalamus (LD) also project directly to V1 (van Groen and Wyss, 1992; Charbonneau et al.,
Neuromodulatory Influences on Cross-modal Recruitment
As described above, there are numerous sources of cortical and subcortical input to V1 that could serve as substrates for allowing other sensory systems to recruit V1. One key plasticity mechanism that can aid in the cross-modal recruitment is the potentiation of the lateral intracortical inputs to V1 L2/3 observed following several days of total visual deprivation (Petrus et al., 2015). This particular study did not identify the source of these glutamatergic intracortical inputs, and these synapses were defined as intracortical based on exclusion criteria that they were not from L4 (Petrus et al., 2015). Hence, in addition to “true” intracortical inputs carrying multisensory information, they could also include subcortical excitatory synapses described above. The functional consequence of potentiating these intracortical excitatory synapses is that it would allow the normally subthreshold multisensory influences to potentially cross the action potential threshold to recruit the dormant V1 for processing information from the intact senses. As discussed in a previous section (“Plasticity of V1 Circuit That Can Support Cross-modal Recruitment” section), the synaptic plasticity mechanism that is thought to allow potentiation of these intracortical synapses is likely a reduction in the synaptic modification threshold via metaplasticity triggered by the loss of visually evoked activity in V1. As intracortical inputs would retain activity driven from the intact senses, it is possible that their activity would cross the lowered synaptic modification threshold to produce NMDAR-dependent LTP (Figure 3A). However, in addition to the lowered synaptic modification threshold, other factors might be at play to enhance the plasticity of the intracortical inputs.
Neuromodulators such as acetylcholine, norepinephrine, and serotonin play a key role in facilitating plasticity (Gu, 2002). In V1 L2/3, norepinephrine and acetylcholine are involved in sharpening spike timing-dependent plasticity (STDP), and their relative concentrations are thought to determine the polarity of STDP (Seol et al., 2007; Huang et al., 2012). While the initial studies showed that activation of beta-adrenergic receptors and muscarinic acetylcholine receptors (mAchRs) are respectively critical for LTP and LTD, it is now clear that this effect is due to the differential coupling of these receptors to downstream second messenger signaling. Regardless of the neuromodulators, activation of cAMP-coupled receptors is critical for LTP while phospholipase C (PLC)-coupled receptors are involved in LTD (Huang et al., 2012). Both norepinephrine and acetylcholine have been shown critical for in vivo sensory experience-dependent plasticity, as they are necessary for (Bear and Singer,
Serotonin has received some attention as promoting plasticity in the adult brain. The role of serotonin in sensory perception has been historically revealed through studies of hallucinogenic serotonin receptor agonists such as LSD and psilocybin, but recent studies highlight its role in adult cortical plasticity. For example, administration of a serotonin reuptake inhibitor, fluoxetine, was found to reinstate ODP in adult V1 of rats (Maya Vetencourt et al., 2008). This suggests that juvenile forms of plasticity could be enabled in the adult brain by serotonin. Of interest, serotonin has also been specifically implicated in cross-modal recruitment in adults. Lombaert et al. (2018) found evidence that serotonin tone is higher in the deprived V1 using a monocular enucleation paradigm, and that serotonin facilitates recruitment of the deprived V1 by whisker stimulation (Lombaert et al., 2018). In particular, long–term cross-modal recruitment was dependent on activation of 5HT-2A and 5HT-3A receptors as determined by specific antagonists.
At the circuit level, neuromodulators, in particular serotonin and acetylcholine, act through VIP interneurons in the superficial layers of V1 (Tremblay et al., 2016), which is the same circuit element that allows cross-modal modulated of V1 by sound (Ibrahim et al., 2016). Coincidently, VIP interneurons are a subset of 5HT-3A receptor expressing inhibitory interneurons (Tremblay et al., 2016), which may explain the dependence of cross-modal recruitment on 5HT-3A receptors (Lombaert et al., 2018). Collectively, these findings suggest that VIP interneuron-mediated disinhibitory circuit may be a common element for gating cross-modal information flow into L2/3 of V1 to mediate cross-modal recruitment.
Compensatory Plasticity
In addition to cross-modal recruitment of V1, which may add capacity to the processing of the remaining senses, there is evidence that the cortical areas serving the spared senses also undergo their own unique adaptation to enhance the processing of their sensory inputs. This phenomenon is referred to as “compensatory plasticity” (Rauschecker, 1995; Lee and Whitt, 2015; Figure 1). Such compensatory changes are seen in parts of the cortex serving both somatosensation and audition. Blind individuals who use a single finger to read Braille exhibit increased representation of that reading finger in the sensorimotor cortex compared to nonreading fingers and compared to sighted controls (Pascual-Leone and Torres, 1993). The auditory cortex likewise undergoes expansion as measured by magnetic source imaging (Elbert et al.,
Cortical Plasticity of Spared Sensory Cortices
In animal models, vision loss leads to plasticity within A1 and S1. Mice deprived of vision since birth have enlarged whisker representations in S1 (Rauschecker et al., 1992). Visual deprivation from birth also results in decreased amplitude of mEPSCs in L2/3 of A1 and S1 in rodents (Goel et al., 2006), which as discussed later, may reflect a shift in processing of information from intracortical towards feedforward sources (Petrus et al., 2015). In an animal model, where visual deprivation can be done before the development of retinogeniculate connections, anatomical changes in cortical and subcortical inputs to S1 have been observed (Dooley and Krubitzer,
Improvement in auditory or tactile discrimination abilities reported in blind human subjects is, however, not universal and may depend on perceptual learning (Grant et al., 2000; Wong et al., 2011). This may stem from the fact that compensatory changes observed in the spared sensory cortices are dependent on their own sensory inputs (He et al., 2012; Petrus et al., 2014). Removing whiskers or deafening mice that are undergoing visual deprivation prevents synaptic plasticity changes observed in S1 barrel cortex (He et al., 2012) and A1 (Petrus et al., 2014), respectively. These findings suggest that the potentiation of feedforward inputs to the spared primary sensory cortices is likely driven by an experience-dependent synaptic plasticity mechanism, such as LTP. Consistent with this idea, deafening normal sighted mice recover LTP of thalamocortical inputs to L4 in V1 of adult mice (Rodriguez et al., 2019). Potentiation of feedforward connections is then expected to induce metaplasticity to compensate for the increased overall input activity, which would slide the synaptic modification threshold up to promote LTD (Figure 3B). This shift in the synaptic modification threshold would preferentially weaken intracortical synapses via LTD to provide homeostasis in neural activity.
One interesting aspect of compensatory synaptic plasticity observed in the spared primary sensory cortices is that it requires a less drastic loss in vision than is required for cross-modal recruitment. As discussed earlier, V1 plasticity induced by vision loss requires a complete loss of retinal inputs and is not observed with bilateral lid-suture (He et al., 2012). However, lid-suture is sufficient to induce compensatory synaptic plasticity in the spared cortex (He et al., 2012). This suggests that total loss of retinal input is required for cross-modal recruitment of V1, while a milder degradation of vision that would hinder using vision to guide behavior may trigger compensatory plasticity in the spared cortical areas. This also indicates that cross-modal recruitment and compensatory plasticity are likely induced independently. Another difference between the two plasticity mechanisms is the duration of visual deprivation required: V1 plasticity can be triggered by a shorter duration (i.e., 2 days is sufficient) of visual deprivation (Goel and Lee, 2007; Gao et al., 2010; He et al., 2012; Chokshi et al.,
While compensatory plasticity observed in A1 and S1 following vision loss is not critically tied to the plasticity in V1, it nonetheless needs to be triggered by the loss of vision. Therefore, there must be functional circuits that carry information or convey the state of visual experience to A1 and S1 to gate compensatory plasticity. There are several possible functional circuits that can provide information on vision to A1 and S1. One is via direct or indirect (via higher-order sensory cortices or through higher-order thalamic nucleus) functional projections between V1 and A1/S1. This may involve gating inhibition in the target A1/S1 circuit to enable plasticity. A second possibility is through neuromodulatory systems since the loss of vision would likely change the global arousal or attentional state of an individual to the spared sensory stimuli. A third possibility is via a bottom-up “spot-light” attentional control within each spared modality.
Intracortical Circuits That Can Mediate Compensatory Plasticity
As mentioned in a previous section (section 2.2), there are direct cortico-cortical connections between the primary sensory cortices, and there is evidence that this functional pathway can gate plasticity. In gerbils, a direct connection from V1 gates the critical period plasticity in A1, where early eye-opening leads to termination of the critical period for A1 plasticity while delayed eye opening extends it (Mowery et al., 2016). While this study did not determine how the direct functional input from V1 gates plasticity of the feedforward circuit in A1, the observation that visual deprivation can extend the critical period is consistent with other studies demonstrating recovery of thalamocortical plasticity in the adult primary sensory cortices with cross-modal sensory deprivation (Petrus et al., 2014; Rodríguez et al., 2018).
In addition to the direct projections, feedback from higher-order sensory cortices or multisensory cortical areas also can provide information on visual experience to the spared primary sensory cortices either through direct cortico-cortical connections or indirect connections via the higher-order thalamus. As explained previously, both cortico-cortical and trans-thalamic connections arrive through L1 and influence the inhibitory circuits present in L2/3 (Ibrahim et al., 2016; Roth et al., 2016; Zhou et al., 2017). It is well documented that inhibitory circuits are well poised to gate cortical plasticity (Jiang et al., 2005). In the S1 barrel cortex, input from POm, a higher-order somatosensory thalamus, is critical for gating potentiation of whisker inputs to L2/3 (Gambino et al., 2014). In particular, POm activation generates NMDAR-mediated dendritic plateau potentials in the principal neurons in L2/3, which are necessary for the observed LTP (Gambino et al., 2014). A follow-up study demonstrated that POm gating of L4 to L2/3 LTP in the S1 barrel cortex is due to disinhibition of L2/3 principal neurons via activation of VIP- and PV-interneurons and a concomitant decrease in SOM-interneuron activity (Williams and Holtmaat, 2019). These studies suggest that POm activity stimulates VIP-interneurons, which in turn inhibit SOM-interneurons. SOM-interneurons are known to target inhibition to dendrites (Tremblay et al., 2016). Hence, reduced SOM-interneuron activity would cause disinhibition of dendrites of L2/3 principal neurons, which could support the activation of NMDAR-mediated dendritic plateau potentials to induce LTP of the feedforward synapses from L4. As mentioned before (see “Subcortical Sources of Inputs to V1 L2/3 That Can Mediate Cross-modal Recruitment” section), trans-thalamic connections through higher-order thalamic nuclei can transmit multisensory information to primary sensory cortices. In particular, we discussed evidence on how LP conveys visual information to A1 to modulate auditory responses (Chou et al.,
Thalamic Circuits That May Gate Compensatory Plasticity
Considering that compensatory plasticity of feedforward circuits in A1 and S1 depends on their respective sensory inputs (He et al., 2012; Petrus et al., 2014), there is also a possibility that gating of this plasticity could occur at the level of the thalamus. The TRN is a thin band of inhibitory neurons that surrounds and projects to the primary sensory thalamic nuclei, controlling information flow to the primary sensory cortex (Halassa and Acsády, 2016; Crabtree,
Another potential mode by which TRN can gate activity through the spared primary thalamic nucleus is via feedback projections from the respective spared primary sensory cortex. Corticothalamic L6 neurons provide feedback control of their respective primary sensory thalamic nuclei via direct excitation and disynaptic inhibition through the TRN. It was demonstrated in the somatosensory system of rodents that the feedback control is activity-dependent, such that low-frequency activation of L6 neurons in the barrel cortex predominantly inhibits VPM while higher frequency stimulation leads to activation (Crandall et al.,
It is important to note that increasing activity of thalamocortical inputs alone cannot support potentiation. It is known that stimulation of thalamocortical inputs to L4 in cortical slices is unable to induce LTP beyond the early critical period (Crair and Malenka,
Neuromodulatory Control of Compensatory Plasticity
As discussed in the context of cross-modal recruitment, neuromodulators play a critical role in enabling plasticity in the primary sensory cortices, even in adults. There are reports that the levels of serotonin and norepinephrine are relatively higher in spared cortices than deprived cortex following visual deprivation (Qu et al., 2000; Jitsuki et al., 2011). As will be discussed in more detail below, VIP-interneuron mediated disinhibitory circuit seems a key circuit component that can be recruited for neuromodulatory control of compensatory plasticity, in addition to cortical and subcortical control, following the loss of vision.
Loss of vision could increase the behavioral relevance or salience of the remaining sensory inputs (De Heering et al.,
The norepinephrine system has been shown to impact network activity and plasticity in sensory cortices (Salgado et al., 2016). For example, iontophoretic application of norepinephrine to A1 of awake rodents causes A1 neurons to exhibit a greater degree of frequency selectivity (Manunta and Edeline, 1997, 1999). This is reminiscent of the sharpened frequency selectivity of A1 L4 neurons following visual deprivation (Petrus et al., 2014). It has been shown that norepinephrine acting through beta-adrenergic receptors facilitates the induction of LTP and suppresses LTD (Seol et al., 2007; Huang et al., 2012). Beta-adrenergic receptors have a lower affinity to norepinephrine compared to alpha-adrenergic receptors (Salgado et al., 2016). Therefore, higher noradrenergic tone in the spared cortical area accompanying visual deprivation (Qu et al., 2000) could activate these receptors and encourage potentiation of feedforward circuits in A1.
Among the neuromodulators discussed here, serotonin has the most concrete evidence to support a role in compensatory plasticity. As mentioned in a previous section, serotonin is critical for recovering adult cortical plasticity (Maya Vetencourt et al., 2008) and cross-modal recruitment (Lombaert et al., 2018). Of relevance to compensatory plasticity, which involves recovering thalamocortical LTP in adults (Rodríguez et al., 2018), certain serotonin receptor antagonists can block thalamocortical LTP in anesthetized rats (Lee et al., 2018). Furthermore, there is direct evidence that serotonin is specifically involved in the cross-modal compensatory plasticity of the feedforward circuit. In rats that were visually deprived via bilateral lid suture, serotonin levels were elevated in the barrel cortex, but not in V1 (Jitsuki et al., 2011). Elevated serotonin levels triggered the insertion of AMPA receptors into the synapse between L4 and L2/3 cells, enhancing feedforward processing of whisker information after visual deprivation (Jitsuki et al., 2011). How serotonin levels increase specifically in deprived (Lombaert et al., 2018) vs. spared sensory cortices (Qu et al., 2000; Jitsuki et al., 2011) is unclear, but could be due to differences in the visual deprivation paradigm. Lombaert and colleagues used monocular enucleation, while Jitsuki and colleagues performed bilateral lid-suture. As mentioned previously, lid-suture is ineffective at driving changes in V1 but induces plasticity in S1 (He et al., 2012). In any case, these studies highlight the importance of the serotonergic system in coordinating cross-modal plasticity in adults.
Functional Circuits for Bottom-Up “Spotlight” Attentional Control of Compensatory Plasticity
A great deal of interest has been devoted recently to the concept of an attentional spotlight, also referred to as selective attention or feature-based attention. The attentional spotlight, which in higher mammals has been described as a neocortical attribute, also heavily relies on subcortical mechanisms for directing attention and cognitive resources towards one salient stimulus or modality, while de-emphasizing others (Saalmann and Kastner, 2011; Halassa and Kastner, 2017; Krauzlis et al., 2018). Global neuromodulatory systems are likely enabling factors for compensatory plasticity, while continued sensory input and spotlight attentional mechanisms may play an instructive role to shape the plasticity in the spared sensory cortices. Spotlight attention is thought to act at a subcortical level to gate the information ascending to the cortex, hence controlling the flow of activity necessary for inducing activity-dependent plasticity. Therefore, turning the attentional spotlight towards auditory and somatosensory inputs in response to visual deprivation would heighten or alter the pattern of activity reaching A1 and S1 in such a way as to drive plasticity. As mentioned before, instructive mechanisms, such as increased sensory gating, cannot alone result in plasticity at synapses that have a defined critical period for plasticity, such as the thalamocortical synapses (Crair and Malenka,
Superior colliculus (SC) is an evolutionarily old part of the brain which processes sensory input and computes a saliency map of the environment (Krauzlis et al., 2013). As discussed above (see “Subcortical Sources of Inputs to V1 L2/3 That Can Mediate Cross-modal Recruitment” section), SC has long been appreciated to participate in visual processing but also harbors multimodal cells in the deeper layers which integrate tactile, visual, and auditory stimuli (Krauzlis et al., 2013; Cang et al.,
The mediodorsal nucleus (MD) is a higher-order thalamic nucleus considered to be important in attention and learning (Mitchell and Chakraborty, 2013; Mitchell, 2015), in part due to its extensive and reciprocal connections with the prefrontal cortex (Zikopoulos and Barbas, 2007; Mitchell and Chakraborty, 2013; Mitchell, 2015). In addition, MD projects to all parts of the TRN, which differs from primary thalamic nuclei which have projections mainly limited to a subregion of TRN (Zikopoulos and Barbas, 2007; Mitchell, 2015). These features suggest that MD may provide a functional connection between prefrontal cortical networks involved in the attentional selection and TRN to gate sensory input (Zikopoulos and Barbas, 2007; Mitchell, 2015). The prefrontal cortex has been shown to modulate performance on a multimodal attentional task via its effect on TRN activity (Wimmer et al., 2015). The close connection between MD and TRN thus offers a potential substrate for attentional regulation of input from the thalamus to primary sensory cortices.
Conclusions
Primary sensory cortices are highly interconnected to multisensory cortical and subcortical structures, which under normal circumstances provide contextual and saliency information needed for proper sensory processing. We suggest that these cortical and subcortical functional connections play a critical role in mediating cross-modal plasticity when a sensory modality is lost, such that an organism can effectively navigate its environment based on the remaining senses. As summarized in this review, these functional connections will allow cross-modal recruitment of the deprived sensory cortex for processing the spared sensory information, as well as enabling and instructing plasticity needed for refining sensory processing of the spared sensory cortices. Visual-deprivation studies highlight the involvement of Hebbian and homeostatic metaplasticity in sculpting the cortical circuits for cross-modal plasticity, which involves not only the plasticity of excitatory synapses, but also that of inhibitory synapses. Cross-modal plasticity across sensory cortices is likely coordinated globally via direct connection across sensory cortices, indirect connectivity through cortico-thalamo-cortical loops or indirect cortical connections through multisensory cortical areas. It is likely that global neuromodulatory systems are engaged to enable plasticity across the sensory cortices. In parallel, multisensory functional inputs that target cortical inhibitory circuits could also gate plasticity within each cortical area. Instructive signals for plasticity likely arise through activity from cortical and subcortical multisensory inputs to V1 and feedforward inputs to the spared cortices. The latter may involve subcortical structures that provide “spotlight” attention to sculpt the spared cortices to better process the most relevant information. While future studies are needed to clarify the role of these diverse functional circuits in cross-modal plasticity, this extensive network of functional connectivity highlights the rich array of contextual information that can influence sensory processing even at the level of primary sensory cortices.
Statements
Author contributions
GE, SP, and H-KL wrote the manuscript. AL and YJ compiled information used for the text and generated the figures with the help of GE, SP, and H-KL. All authors contributed to the article and approved the submitted version.
Funding
This work was supported by National Institutes of Health (NIH) grant R01-EY014882 to H-KL and NRSA F31-EY031946 to SP.
Acknowledgments
We would like to thank Dr. Alfredo Kirkwood for helpful discussions.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
- 5HT
5-hydroxytryptamine
- A1
primary auditory cortex
- ACg
anterior cingulate cortex
- AChR
acetylcholine receptor
- AL
anterolateral area
- aLP
anterior-ventral lateral posterior nucleus
- AM
anteromedial area
- AMPA
α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid
- BCM
Bienenstock-Cooper-Monroe
- cAMP
cyclic adenosine 3, 5-monophosphate
- dLGN
dorsal lateral geniculate nucleus
- EEG
electroencephalogram
- EPSC
excitatory postsynaptic current
- fMRI
functional magnetic resonance imaging
- GAD65
glutamic acid decarboxylase 65
- GluN2B
glutamate receptor N-methyl-D-aspartate receptor subunit 2B
- HVA
higher order visual areas
- IC
intracortical
- IPSC
inhibitory postsynaptic current
- L1
layer 1
- L2/3
layer 2/3
- L4
layer 4
- L5
layer 5
- L6
layer 6
- LD
lateral dorsal nucleus
- LI
laterointermediate area
- LM
lateromedial area
- LP
lateral posterior nucleus
- LSD
lysergic acid diethylamide
- LTD
long-term depression
- LTP
long-term potentiation
- mAChR
muscarinic acetylcholine receptor
- MD
mediodorsal nucleus
- mEPSC
miniature excitatory postsynaptic current
- mIPSC
miniature inhibitory postsynaptic current
- MGBv
ventral division of medial geniculate body
- mLP
medial lateral posterior nucleus
- nAChR
nicotinic acetylcholine receptor
- NMDAR
N-methyl-D-aspartate receptor
- NTSR1
neurotensin receptor 1
- ODP
ocular dominance plasticity
- PFC
prefrontal cortex
- PLC
phospholipase C
- pLP
posterior-dorsal lateral posterior nucleus
- PM
posteromedial area
- PO
posterior thalamic nucleus
- POm
posterior medial thalamic nucleus
- POR
postrhinal area
- PV
parvalbumin
- RL
rostolateral area
- RSP
retrosplenial cortex
- S1
primary somatosensory cortex
- SC
superior colliculus
- SOM
somatostatin
- STDP
spike timing dependent plasticity
- TMS
transcranial magnetic stimulation
- TRN
thalamic reticular nucleus
- TTX
tetrodotoxin
- V1
primary visual cortex
- V2
secondary visual cortex
- V2L
lateral secondary visual cortex
- VEPs
visually evoked potentials
- VIP
vasoactive intestinal peptide
- VPM
ventral posteromedial nucleus.
Abbreviations
References
1
AlittoH. J.DanY. (2012). Cell-type-specific modulation of neocortical activity by basal forebrain input. Front. Syst. Neurosci.6:79. 10.3389/fnsys.2012.00079
2
BaiW.-Z.IshidaM.ArimatsuY. (2004). Chemically defined feedback connections from infragranular layers of sensory association cortices in the rat. Neuroscience123, 257–267. 10.1016/j.neuroscience.2003.08.056
3
BaldwinM. K. L.BalaramP.KaasJ. H. (2017). The evolution and functions of nuclei of the visual pulvinar in primates. J. Comp. Neurol.525, 3207–3226. 10.1002/cne.24272
4
BarkatT. R.PolleyD. B.HenschT. K. (2011). A critical period for auditory thalamocortical connectivity. Nat. Neurosci.14, 1189–1194. 10.1038/nn.2882
5
BarnesS. J.SammonsR. P.JacobsenR. I.MackieJ.KellerG. B.KeckT. (2015). Subnetwork-specific homeostatic plasticity in mouse visual cortex in vivo. Neuron86, 1290–1303. 10.1016/j.neuron.2015.05.010
6
BavelierD.NevilleH. J. (2002). Cross-modal plasticity: where and how?Nat. Rev. Neurosci.3, 443–452. 10.1038/nrn848
7
BearM. F.CooperL. N.EbnerF. F. (1987). A physiological basis for a theory of synapse modification. Science237, 42–48. 10.1126/science.3037696
8
BearM. F.SingerW. (1986). Modulation of visual cortical plasticity by acetylcholine and noradrenaline. Nature320, 172–176. 10.1038/320172a0
9
BenderK. J.AllenC. B.BenderV. A.FeldmanD. E. (2006). Synaptic basis for whisker deprivation-induced synaptic depression in rat somatosensory cortex. J. Neurosci.26, 4155–4165. 10.1523/JNEUROSCI.0175-06.2006
10
BenderM. B.TeuberH. L. (1946). Phenomena of fluctuation, extinction and completion in visual perception. Arch. Neurol. Psychiatry55, 627–658. 10.1001/archneurpsyc.1946.02300170075008
11
BennettC.GaleS. D.GarrettM. E.NewtonM. L.CallawayE. M.MurphyG. J.et al. (2019). Higher-order thalamic circuits channel parallel streams of visual information in mice. Neuron102, 477.e5–492.e5. 10.1016/j.neuron.2019.02.010
12
BezdudnayaT.KellerA. (2008). Laterodorsal nucleus of the thalamus: a processor of somatosensory inputs. J. Comp. Neurol.507, 1979–1989. 10.1002/cne.21664
13
BienenstockE. L.CooperL. N.MunroP. W. (1982). Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. J. Neurosci.2, 32–48. 10.1523/JNEUROSCI.02-01-00032.1982
14
BinzeggerT.DouglasR. J.MartinK. A. (2004). A quantitative map of the circuit of cat primary visual cortex. J. Neurosci.24, 8441–8453. 10.1523/JNEUROSCI.1400-04.2004
15
BlaisB. S.FrenkelM. Y.KuindersmaS. R.MuhammadR.ShouvalH. Z.CooperL. N.et al. (2008). Recovery from monocular deprivation using binocular deprivation. J. Neurophysiol.100, 2217–2224. 10.1152/jn.90411.2008
16
BortoneD. S.OlsenS. R.ScanzianiM. (2014). Translaminar inhibitory cells recruited by layer 6 corticothalamic neurons suppress visual cortex. Neuron82, 474–485. 10.1016/j.neuron.2014.02.021
17
BridiM. C. D.De PasqualeR.LantzC. L.GuY.BorrellA.ChoiS. Y.et al. (2018). Two distinct mechanisms for experience-dependent homeostasis. Nat. Neurosci.21, 843–850. 10.1038/s41593-018-0150-0
18
BuchelC.PriceC.FrackowiakR. S.FristonK. (1998). Different activation patterns in the visual cortex of late and congenitally blind subjects. Brain121, 409–419. 10.1093/brain/121.3.409
19
BurtonH.McLarenD. G. (2006). Visual cortex activation in late-onset, Braille naive blind individuals: an fMRI study during semantic and phonological tasks with heard words. Neurosci. Lett.392, 38–42. 10.1016/j.neulet.2005.09.015
20
CangJ.SavierE.BarchiniJ.LiuX. (2018). Visual function, organization, and development of the mouse superior colliculus. Annu. Rev. Vis. Sci.4, 239–262. 10.1146/annurev-vision-091517-034142
21
CappeC.BaroneP. (2005). Heteromodal connections supporting multisensory integration at low levels of cortical processing in the monkey. Eur. J. Neurosci.22, 2886–2902. 10.1111/j.1460-9568.2005.04462.x
22
CharbonneauV.LaraméeM.-E.BoucherV.BronchtiG.BoireD. (2012). Cortical and subcortical projections to primary visual cortex in anophthalmic, enucleated and sighted mice. Eur. J. Neurosci.36, 2949–2963. 10.1111/j.1460-9568.2012.08215.x
23
ChokshiV.GaoM.GrierB. D.OwensA.WangH.WorleyP. F.et al. (2019). Input-specific metaplasticity in the visual cortex requires homer1a-mediated mGluR5 signaling. Neuron104, 736.e6–748.e6.10.1016/j.neuron.2019.08.017
24
ChouX.-L.FangQ.YanL.ZhongW.PengB.LiH.et al. (2020). Contextual and cross-modality modulation of auditory cortical processing through pulvinar mediated suppression. eLife9:e54157. 10.7554/eLife.54157
25
ChunS.BayazitovI. T.BlundonJ. A.ZakharenkoS. S. (2013). Thalamocortical long-term potentiation becomes gated after the early critical period in the auditory cortex. J. Neurosci.33, 7345–7357. 10.1523/JNEUROSCI.4500-12.2013
26
CookeS. F.BearM. F. (2014). How the mechanisms of long-term synaptic potentiation and depression serve experience-dependent plasticity in primary visual cortex. Philos. Trans. R. Soc. Lond. B Biol. Sci.369:20130284. 10.1098/rstb.2013.0284
27
CooperL. N.BearM. F. (2012). The BCM theory of synapse modification at 30: interaction of theory with experiment. Nat. Rev. Neurosci.13, 798–810. 10.1038/nrn3353
28
CrabtreeJ. W. (2018). Functional diversity of thalamic reticular subnetworks. Front. Syst. Neurosci.12:41. 10.3389/fnsys.2018.00041
29
CrairM. C.MalenkaR. C. (1995). A critical period for long-term potentiation at thalamocortical synapses. Nature375, 325–328. 10.1038/375325a0
30
CrandallS. R.CruikshankS. J.ConnorsB. W. (2015). A corticothalamic switch: controlling the thalamus with dynamic synapses. Neuron86, 768–782. 10.1016/j.neuron.2015.03.040
31
CuevasI.PlazaP.RombauxP.De VolderA. G.RenierL. (2009). Odour discrimination and identification are improved in early blindness. Neuropsychologia47, 3079–3083. 10.1016/j.neuropsychologia.2009.07.004
32
CynaderM.MitchellD. E. (1980). Prolonged sensitivity to monocular deprivation in dark-reared cats. J. Neurophysiol.43, 1026–1040. 10.1152/jn.1980.43.4.1026
33
De HeeringA.DormalG.PellandM.LewisT.MaurerD.CollignonO. (2016). A brief period of postnatal visual deprivation alters the balance between auditory and visual attention. Curr. Biol.26, 3101–3105. 10.1016/j.cub.2016.10.014
34
DeneuxT.HarrellE. R.KempfA.CeballoS.FilipchukA.BathellierB. (2019). Context-dependent signaling of coincident auditory and visual events in primary visual cortex. eLife8:e44006. 10.7554/eLife.44006
35
DesaiN. S.CudmoreR. H.NelsonS. B.TurrigianoG. G. (2002). Critical periods for experience-dependent synaptic scaling in visual cortex. Nat. Neurosci.5, 783–789. 10.1038/nn878
36
DooleyJ. C.KrubitzerL. A. (2019). Alterations in cortical and thalamic connections of somatosensory cortex following early loss of vision. J. Comp. Neurol.527, 1675–1688. 10.1002/cne.24582
37
DringenbergH. C.HamzeB.WilsonA.SpeechleyW.KuoM. C. (2007). Heterosynaptic facilitation of in vivo thalamocortical long-term potentiation in the adult rat visual cortex by acetylcholine. Cereb. Cortex17, 839–848. 10.1093/cercor/bhk038
38
ElbertT.SterrA.RockstrohB.PantevC.MullerM. M.TaubE. (2002). Expansion of the tonotopic area in the auditory cortex of the blind. J. Neurosci.22, 9941–9944. 10.1523/JNEUROSCI.22-22-09941.2002
39
FalchierA.ClavagnierS.BaroneP.KennedyH. (2002). Anatomical evidence of multimodal integration in primate striate cortex. J. Neurosci.22, 5749–5759. 10.1523/JNEUROSCI.22-13-05749.2002
40
FangQ.ChouX.-L.PengB.ZhongW.ZhangL. I.TaoH. W. (2020). A differential circuit via retino-colliculo-pulvinar pathway enhances feature selectivity in visual cortex through surround suppression. Neuron105, 355.e6–369.e6. 10.1016/j.neuron.2019.10.027
41
FeldmanD. E.NicollR. A.MalenkaR. C.IsaacJ. T. (1998). Long-term depression at thalamocortical synapses in developing rat somatosensory cortex. Neuron21, 347–357. 10.1016/s0896-6273(00)80544-9
42
FellemanD. J.Van EssenD. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex1, 1–47. 10.1093/cercor/1.1.1
43
Gallero-SalasY.HanS.SychY.VoigtF. F.LaurenczyB.GiladA.et al. (2021). Sensory and behavioral components of neocortical signal flow in discrimination tasks with short-term memory. Neuron109, 135.e6–148.e6. 10.1016/j.neuron.2020.10.017
44
GamanutR.KennedyH.ToroczkaiZ.Ercsey-RavaszM.Van EssenD. C.KnoblauchK.et al. (2018). The mouse cortical connectome, characterized by an ultra-dense cortical graph, maintains specificity by distinct connectivity profiles. Neuron97, 698.e10–715.e10. 10.1016/j.neuron.2017.12.037
45
GambinoF.PagèsS.KehayasV.BaptistaD.TattiR.CarletonA.et al. (2014). Sensory-evoked LTP driven by dendritic plateau potentials in vivo. Nature515, 116–119. 10.1038/nature13664
46
GaoM.MaynardK. R.ChokshiV.SongL.JacobsC.WangH.et al. (2014). Rebound potentiation of inhibition in juvenile visual cortex requires vision-induced BDNF expression. J. Neurosci.34, 10770–10779. 10.1523/JNEUROSCI.5454-13.2014
47
GaoM.SossaK.SongL.ErringtonL.CummingsL.HwangH.et al. (2010). A specific requirement of Arc/Arg3.1 for visual experience-induced homeostatic synaptic plasticity in mouse primary visual cortex. J. Neurosci.30, 7168–7178. 10.1523/JNEUROSCI.1067-10.2010
48
GaoM.WhittJ. L.HuangS.LeeA.MihalasS.KirkwoodA.et al. (2017). Experience-dependent homeostasis of ‘noise’ at inhibitory synapses preserves information coding in adult visual cortex. Philos. Trans. R. Soc. Lond. B Biol. Sci.372:20160156. 10.1098/rstb.2016.0156
49
GarrettM. E.NauhausI.MarshelJ. H.CallawayE. M. (2014). Topography and areal organization of mouse visual cortex. J. Neurosci.34, 12587–12600. 10.1523/JNEUROSCI.1124-14.2014
50
GharaeiS.HonnuraiahS.ArabzadehE.StuartG. J. (2020). Superior colliculus modulates cortical coding of somatosensory information. Nat. Commun.11:1693. 10.1038/s41467-020-15443-1
51
GilZ.ConnorsB. W.AmitaiY. (1997). Differential regulation of neocortical synapses by neuromodulators and activity. Neuron19, 679–686. 10.1016/s0896-6273(00)80380-3
52
GilissenS.ArckensL. (2021). Posterior parietal cortex contributions to cross-modal brain plasticity upon sensory loss. Curr. Opin. Neurobiol.67, 16–25. 10.1016/j.conb.2020.07.001
53
GilissenS. R. J.FarrowK.BoninV.ArckensL. (2021). Reconsidering the border between the visual and posterior parietal cortex of mice. Cereb. Cortex31, 1675–1692. 10.1093/cercor/bhaa318
54
GlazewskiS.GreenhillS.FoxK. (2017). Time-course and mechanisms of homeostatic plasticity in layers 2/3 and 5 of the barrel cortex. Philos. Trans. R. Soc. Lond. B Biol. Sci.372:20160150. 10.1098/rstb.2016.0150
55
GlickfeldL. L.OlsenS. R. (2017). Higher-order areas of the mouse visual cortex. Annu. Rev. Vis. Sci.3, 251–273. 10.1146/annurev-vision-102016-061331
56
GoelA.JiangB.XuL. W.SongL.KirkwoodA.LeeH. K. (2006). Cross-modal regulation of synaptic AMPA receptors in primary sensory cortices by visual experience. Nat. Neurosci.9, 1001–1003. 10.1038/nn1725
57
GoelA.LeeH.-K. (2007). Persistence of experience-induced homeostatic synaptic plasticity through adulthood in superficial layers of mouse visual cortex. J. Neurosci.27, 6692–6700. 10.1523/JNEUROSCI.5038-06.2007
58
GongS.DoughtyM.HarbaughC. R.CumminsA.HattenM. E.HeintzN.et al. (2007). Targeting Cre recombinase to specific neuron populations with bacterial artificial chromosome constructs. J. Neurosci.27, 9817–9823. 10.1523/JNEUROSCI.2707-07.2007
59
GougouxF.LeporeF.LassondeM.VossP.ZatorreR. J.BelinP. (2004). Neuropsychology: pitch discrimination in the early blind. Nature430:309. 10.1038/430309a
60
GrantA. C.ThiagarajahM. C.SathianK. (2000). Tactile perception in blind Braille readers: a psychophysical study of acuity and hyperacuity using gratings and dot patterns. Percept. Psychophys.62, 301–312. 10.3758/bf03205550
61
GuQ. (2002). Neuromodulatory transmitter systems in the cortex and their role in cortical plasticity. Neuroscience111, 815–835. 10.1016/s0306-4522(02)00026-x
62
GuoY.HuangS.De PasqualeR.McGehrinK.LeeH.-K.ZhaoK.et al. (2012). Dark exposure extends the integration window for spike-timing-dependent plasticity. J. Neurosci.32, 15027–15035. 10.1523/JNEUROSCI.2545-12.2012
63
HalassaM. M.AcsádyL. (2016). Thalamic inhibition: diverse sources, diverse scales. Trends Neurosci.39, 680–693. 10.1016/j.tins.2016.08.001
64
HalassaM. M.KastnerS. (2017). Thalamic functions in distributed cognitive control. Nat. Neurosci.20, 1669–1679. 10.1038/s41593-017-0020-1
65
HeK.PetrusE.GammonN.LeeH. K. (2012). Distinct sensory requirements for unimodal and cross-modal homeostatic synaptic plasticity. J. Neurosci.32, 8469–8474. 10.1523/JNEUROSCI.1424-12.2012
66
HeH.-Y.RayB.DennisK.QuinlanE. M. (2007). Experience-dependent recovery of vision following chronic deprivation amblyopia. Nat. Neurosci.10, 1134–1136. 10.1038/nn1965
67
HeynenA. J.BearM. F. (2001). Long-term potentiation of thalamocortical transmission in the adult visual cortex in vivo. J. Neurosci.21, 9801–9813. 10.1523/JNEUROSCI.21-24-09801.2001
68
HishidaR.HorieM.TsukanoH.TohmiM.YoshitakeK.MeguroR.et al. (2018). Feedback inhibition derived from the posterior parietal cortex regulates the neural properties of the mouse visual cortex. Eur. J. Neurosci.50, 2970–2987. 10.1111/ejn.14424
69
HongS. Z.HuangS.SeverinD.KirkwoodA. (2020). Pull-push neuromodulation of cortical plasticity enables rapid bi-directional shifts in ocular dominance. eLife9:e54455. 10.7554/eLife.54455
70
HooksB. M.ChenC. (2020). Circuitry underlying experience-dependent plasticity in the mouse visual system. Neuron106, 21–36. 10.1016/j.neuron.2020.01.031
71
HuF.KamigakiT.ZhangZ.ZhangS.DanU.DanY. (2019). Prefrontal corticotectal neurons enhance visual processing through the superior colliculus and pulvinar thalamus. Neuron104, 1141.e4–1152.e4. 10.1016/j.neuron.2019.09.019
72
HuangS.TreviñoM.HeK.ArdilesA.PasqualeR.GuoY.et al. (2012). Pull-push neuromodulation of LTP and LTD enables bidirectional experience-induced synaptic scaling in visual cortex. Neuron73, 497–510. 10.1016/j.neuron.2011.11.023
73
IbrahimL. A.MesikL.JiX. Y.FangQ.LiH. F.LiY. T.et al. (2016). Cross-modality sharpening of visual cortical processing through layer-1-mediated inhibition and disinhibition. Neuron89, 1031–1045. 10.1016/j.neuron.2016.01.027
74
ImamuraK.KasamatsuT. (1989). Interaction of noradrenergic and cholinergic systems in regulation of ocular dominance plasticity. Neurosci. Res.6, 519–536. 10.1016/0168-0102(89)90042-4
75
IurilliG.GhezziD.OlceseU.LassiG.NazzaroC.ToniniR.et al. (2012). Sound-driven synaptic inhibition in primary visual cortex. Neuron73, 814–828. 10.1016/j.neuron.2011.12.026
76
JiangB.HuangZ. J.MoralesB.KirkwoodA. (2005). Maturation of GABAergic transmission and the timing of plasticity in visual cortex. Brain Res. Rev.50, 126–133. 10.1016/j.brainresrev.2005.05.007
77
JiangB.TreviñoM.KirkwoodA. (2007). Sequential development of long-term potentiation and depression in different layers of the mouse visual cortex. J. Neurosci.27, 9648–9652. 10.1523/JNEUROSCI.2655-07.2007
78
JitsukiS.TakemotoK.KawasakiT.TadaH.TakahashiA.BecamelC.et al. (2011). Serotonin mediates cross-modal reorganization of cortical circuits. Neuron69, 780–792. 10.1016/j.neuron.2011.01.016
79
JohnsonR. R.BurkhalterA. (1996). Microcircuitry of forward and feedback connections within rat visual cortex. J. Comp. Neurol.368, 383–398. 10.1002/(SICI)1096-9861(19960506)368:3<383::AID-CNE5>3.0.CO;2-1
80
JohnsonR. R.BurkhalterA. (1997). A polysynaptic feedback circuit in rat visual cortex. J. Neurosci.17, 7129–7140. 10.1523/JNEUROSCI.17-18-07129.1997
81
KellerA. J.RothM. M.ScanzianiM. (2020). Feedback generates a second receptive field in neurons of the visual cortex. Nature582, 545–549. 10.1038/s41586-020-2319-4
82
KimE. J.JuavinettA. L.KyubwaE. M.JacobsM. W.CallawayE. M. (2015). Three types of cortical layer 5 neurons that differ in brain-wide connectivity and function. Neuron88, 1253–1267. 10.1016/j.neuron.2015.11.002
83
KimuraA. (2014). Diverse subthreshold cross-modal sensory interactions in the thalamic reticular nucleus: implications for new pathways of cross-modal attentional gating function. Eur. J. Neurosci.39, 1405–1418. 10.1111/ejn.12545
84
KirkwoodA.RioultM. C.BearM. F. (1996). Experience-dependent modification of synaptic plasticity in visual cortex. Nature381, 526–528. 10.1038/381526a0
85
KoH.HoferS. B.PichlerB.BuchananK. A.SjostromP. J.Mrsic-FlogelT. D. (2011). Functional specificity of local synaptic connections in neocortical networks. Nature473, 87–91. 10.1038/nature09880
86
KotakV. C.FujisawaS.LeeF. A.KarthikeyanO.AokiC.SanesD. H. (2005). Hearing loss raises excitability in the auditory cortex. J. Neurosci.25, 3908–3918. 10.1523/JNEUROSCI.5169-04.2005
87
KrauzlisR. J.BogadhiA. R.HermanJ. P.BollimuntaA. (2018). Selective attention without a neocortex. Cortex102, 161–175. 10.1016/j.cortex.2017.08.026
88
KrauzlisR. J.LovejoyL. P.ZénonA. (2013). Superior colliculus and visual spatial attention. Annu. Rev. Neurosci.36, 165–182. 10.1146/annurev-neuro-062012-170249
89
LakatosP.ChenC.-M.O’ConnellM. N.MillsA.SchroederC. E. (2007). Neuronal oscillations and multisensory interaction in primary auditory cortex. Neuron53, 279–292. 10.1016/j.neuron.2006.12.011
90
LamY.-W.ShermanS. M. (2011). Functional organization of the thalamic input to the thalamic reticular nucleus. J. Neurosci.31, 6791–6799. 10.1523/JNEUROSCI.3073-10.2011
91
LarameeM. E.KurotaniT.RocklandK. S.BronchtiG.BoireD. (2011). Indirect pathway between the primary auditory and visual cortices through layer V pyramidal neurons in V2L in mouse and the effects of bilateral enucleation. Eur. J. Neurosci.34, 65–78. 10.1111/j.1460-9568.2011.07732.x
92
LeeW.-C. A.BoninV.ReedM.GrahamB. J.HoodG.GlattfelderK.et al. (2016). Anatomy and function of an excitatory network in the visual cortex. Nature532, 370–374. 10.1038/nature17192
93
LeeH.-K.KirkwoodA. (2019). Mechanisms of homeostatic synaptic plasticity in vivo. Front. Cell. Neurosci.13:520. 10.3389/fncel.2019.00520
94
LeeK. K. Y.SoutarC. N.DringenbergH. C. (2018). Gating of long-term potentiation (LTP) in the thalamocortical auditory system of rats by serotonergic (5-HT) receptors. Brain Res.1683, 1–11. 10.1016/j.brainres.2018.01.004
95
LeeH.-K.WhittJ. L. (2015). Cross-modal synaptic plasticity in adult primary sensory cortices. Curr. Opin. Neurobiol.35, 119–126. 10.1016/j.conb.2015.08.002
96
LessardN.ParéM.LeporeF.LassondeM. (1998). Early-blind human subjects localize sound sources better than sighted subjects. Nature395, 278–280. 10.1038/26228
97
LiL.GaineyM. A.GoldbeckJ. E.FeldmanD. E. (2014). Rapid homeostasis by disinhibition during whisker map plasticity. Proc. Natl. Acad. Sci. U S A111, 1616–1621. 10.1073/pnas.1312455111
98
LombaertN.HennesM.GilissenS.SchevenelsG.AertsL.VanlaerR.et al. (2018). 5-HTR2A and 5-HTR3A but not 5-HTR1A antagonism impairs the cross-modal reactivation of deprived visual cortex in adulthood. Mol. Brain11:65. 10.1186/s13041-018-0404-5
99
LuJ.TucciaroneJ.LinY.HuangZ. J. (2014). Input-specific maturation of synaptic dynamics of parvalbumin interneurons in primary visual cortex. Proc. Natl. Acad. Sci. U S A111, 16895–16900. 10.1073/pnas.1400694111
100
MaffeiA.NatarajK.NelsonS. B.TurrigianoG. G. (2006). Potentiation of cortical inhibition by visual deprivation. Nature443, 81–84. 10.1038/nature05079
101
MaffeiA.NelsonS. B.TurrigianoG. G. (2004). Selective reconfiguration of layer 4 visual cortical circuitry by visual deprivation. Nat. Neurosci.7, 1353–1359. 10.1038/nn1351
102
MaffeiA.TurrigianoG. G. (2008). Multiple modes of network homeostasis in visual cortical layer 2/3. J. Neurosci.28, 4377–4384. 10.1523/JNEUROSCI.5298-07.2008
103
ManuntaY.EdelineJ. M. (1997). Effects of noradrenaline on frequency tuning of rat auditory cortex neurons. Eur. J. Neurosci.9, 833–847. 10.1111/j.1460-9568.1997.tb01433.x
104
ManuntaY.EdelineJ. M. (1999). Effects of noradrenaline on frequency tuning of auditory cortex neurons during wakefulness and slow-wave sleep. Eur. J. Neurosci.11, 2134–2150. 10.1046/j.1460-9568.1999.00633.x
105
MaruyamaA. T.KomaiS. (2018). Auditory-induced response in the primary sensory cortex of rodents. PLoS One13:e0209266. 10.1371/journal.pone.0209266
106
Maya VetencourtJ. F.SaleA.ViegiA.BaroncelliL.De PasqualeR.O’LearyO. F.et al. (2008). The antidepressant fluoxetine restores plasticity in the adult visual cortex. Science320, 385–388. 10.1126/science.1150516
107
MeijerG. T.MarchesiP.MejiasJ. F.MontijnJ. S.LansinkC. S.PennartzC. M. A. (2020). Neural correlates of multisensory detection behavior: comparison of primary and higher-order visual cortex. Cell Rep.31:107636. 10.1016/j.celrep.2020.107636
108
MengX.KaoJ. P.LeeH.-K.KanoldP. O. (2015). Visual deprivation causes refinement of intracortical circuits in the auditory cortex. Cell Rep.12, 955–964. 10.1016/j.celrep.2015.07.018
109
MengX.KaoJ. P.LeeH. K.KanoldP. O. (2017). Intracortical circuits in thalamorecipient layers of auditory cortex refine after visual deprivation. eNeuro4:ENEURO.0092-17.2017. 10.1523/ENEURO.0092-17.2017
110
MerabetL. B.HamiltonR.SchlaugG.SwisherJ. D.KiriakopoulosE. T.PitskelN. B.et al. (2008). Rapid and reversible recruitment of early visual cortex for touch. PLoS One3:e3046. 10.1371/journal.pone.0003046
111
MerabetL. B.Pascual-LeoneA. (2010). Neural reorganization following sensory loss: the opportunity of change. Nat. Rev. Neurosci.11, 44–52. 10.1038/nrn2758
112
MesikL.HuangJ. J.ZhangL. I.TaoH. W. (2019). Sensory- and motor-related responses of layer 1 neurons in the mouse visual cortex. J. Neurosci.39, 10060–10070. 10.1523/JNEUROSCI.1722-19.2019
113
MetherateR. (2011). Functional connectivity and cholinergic modulation in auditory cortex. Neurosci. Biobehav. Rev.35, 2058–2063. 10.1016/j.neubiorev.2010.11.010
114
MetherateR.CoxC. L.AsheJ. H. (1992). Cellular bases of neocortical activation: modulation of neural oscillations by the nucleus basalis and endogenous acetylcholine. J. Neurosci.12, 4701–4711. 10.1523/JNEUROSCI.12-12-04701.1992
115
MitchellA. S. (2015). The mediodorsal thalamus as a higher order thalamic relay nucleus important for learning and decision-making. Neurosci. Biobehav. Rev.54, 76–88. 10.1016/j.neubiorev.2015.03.001
116
MitchellA. S.ChakrabortyS. (2013). What does the mediodorsal thalamus do?Front. Syst. Neurosci.7:37. 10.3389/fnsys.2013.00037
117
MizumoriS. J.WilliamsJ. D. (1993). Directionally selective mnemonic properties of neurons in the lateral dorsal nucleus of the thalamus of rats. J. Neurosci.13, 4015–4028. 10.1523/JNEUROSCI.13-09-04015.1993
118
MowerG. D.BerryD.BurchfielJ. L.DuffyF. H. (1981). Comparison of the effects of dark rearing and binocular suture on development and plasticity of cat visual cortex. Brain Res.220, 255–267. 10.1016/0006-8993(81)91216-6
119
MoweryT. M.KotakV. C.SanesD. H. (2016). The onset of visual experience gates auditory cortex critical periods. Nat. Commun.7:10416. 10.1038/ncomms10416
120
NahmaniM.TurrigianoG. G. (2014). Deprivation-induced strengthening of presynaptic and postsynaptic inhibitory transmission in layer 4 of visual cortex during the critical period. J. Neurosci.34, 2571–2582. 10.1523/JNEUROSCI.4600-13.2014
121
O’BrienR. J.KambojS.EhlersM. D.RosenK. R.FischbachG. D.HuganirR. L. (1998). Activity-dependent modulation of synaptic AMPA receptor accumulation. Neuron21, 1067–1078. 10.1016/s0896-6273(00)80624-8
122
OlceseU.IurilliG.MediniP. (2013). Cellular and synaptic architecture of multisensory integration in the mouse neocortex. Neuron79, 579–593. 10.1016/j.neuron.2013.06.010
123
OlsenS. R.BortoneD. S.AdesnikH.ScanzianiM. (2012). Gain control by layer six in cortical circuits of vision. Nature483, 47–52. 10.1038/nature10835
124
OrbanG. A. (2008). Higher order visual processing in macaque extrastriate cortex. Physiol. Rev.88, 59–89. 10.1152/physrev.00008.2007
125
PakA.RyuE.LiC.ChubykinA. A. (2020). Top-down feedback controls the cortical representation of illusory contours in mouse primary visual cortex. J. Neurosci.40, 648–660. 10.1523/JNEUROSCI.1998-19.2019
126
Pascual-LeoneA.TorresF. (1993). Plasticity of the sensorimotor cortex representation of the reading finger in Braille readers. Brain116, 39–52. 10.1093/brain/116.1.39
127
PetrusE.IsaiahA.JonesA. P.LiD.WangH.LeeH. K.et al. (2014). Crossmodal induction of thalamocortical potentiation leads to enhanced information processing in the auditory cortex. Neuron81, 664–673. 10.1016/j.neuron.2013.11.023
128
PetrusE.RodriguezG.PattersonR.ConnorB.KanoldP. O.LeeH. K. (2015). Vision loss shifts the balance of feedforward and intracortical circuits in opposite directions in mouse primary auditory and visual cortices. J. Neurosci.35, 8790–8801. 10.1523/JNEUROSCI.4975-14.2015
129
PolleyD. B.SteinbergE. E.MerzenichM. M. (2006). Perceptual learning directs auditory cortical map reorganization through top-down influences. J. Neurosci.26, 4970–4982. 10.1523/JNEUROSCI.3771-05.2006
130
QuY.EyselU. T.VandesandeF.ArckensL. (2000). Effect of partial sensory deprivation on monoaminergic neuromodulators in striate cortex of adult cat. Neuroscience101, 863–868. 10.1016/s0306-4522(00)00441-3
131
RamachandranV. S.GregoryR. L. (1991). Perceptual filling in of artificially induced scotomas in human vision. Nature350, 699–702. 10.1038/350699a0
132
RamaswamyS.MarkramH. (2015). Anatomy and physiology of the thick-tufted layer 5 pyramidal neuron. Front. Cell. Neurosci.9:233. 10.3389/fncel.2015.00233
133
RauscheckerJ. P. (1995). Compensatory plasticity and sensory substitution in the cerebral cortex. Trends Neurosci.18, 36–43. 10.1016/0166-2236(95)93948-w
134
RauscheckerJ. P.TianB.KorteM.EgertU. (1992). Crossmodal changes in the somatosensory vibrissa/barrel system of visually deprived animals. Proc. Natl. Acad. Sci. U S A89, 5063–5067. 10.1073/pnas.89.11.5063
135
RenierL.CuévasI.GrandinC. B.DricotL.PlazaP.LerensE.et al. (2013). Right occipital cortex activation correlates with superior odor processing performance in the early blind. PLoS One8:e71907. 10.1371/journal.pone.0071907
136
RöderB.Teder-SälejärviW.SterrA.RöslerF.HillyardS. A.NevilleH. J. (1999). Improved auditory spatial tuning in blind humans. Nature400, 162–166. 10.1038/22106
137
RodríguezG.ChakrabortyD.SchrodeK. M.SahaR.UribeI.LauerA. M.et al. (2018). Cross-modal reinstatement of thalamocortical plasticity accelerates ocular dominance plasticity in adult mice. Cell Rep.24, 3433.e4–3440.e4. 10.1016/j.celrep.2018.08.072
138
RodriguezG.MesikL.GaoM.ParkinsS.SahaR.LeeH. K. (2019). Disruption of NMDA receptor function prevents normal experience-dependent homeostatic synaptic plasticity in mouse primary visual cortex. J. Neurosci.39, 7664–7673. 10.1523/JNEUROSCI.2117-18.2019
139
RothM. M.DahmenJ. C.MuirD. R.ImhofF.MartiniF. J.HoferS. B. (2016). Thalamic nuclei convey diverse contextual information to layer 1 of visual cortex. Nat. Neurosci.19, 299–307. 10.1038/nn.4197
140
SaalmannY. B.KastnerS. (2011). Cognitive and perceptual functions of the visual thalamus. Neuron71, 209–223. 10.1016/j.neuron.2011.06.027
141
SadatoN.Pascual-LeoneA.GrafmanJ.IbañezV.DeiberM. P.DoldG.et al. (1996). Activation of the primary visual cortex by Braille reading in blind subjects. Nature380, 526–528. 10.1038/380526a0
142
SalgadoH.TreviñoM.AtzoriM. (2016). Layer- and area-specific actions of norepinephrine on cortical synaptic transmission. Brain Res.1641, 163–176. 10.1016/j.brainres.2016.01.033
143
SandersonK. J.DreherB.GayerN. (1991). Prosencephalic connections of striate and extrastriate areas of rat visual cortex. Exp. Brain Res.85, 324–334. 10.1007/BF00229410
144
SandmannP.DillierN.EicheleT.MeyerM.KegelA.Pascual-MarquiR. D.et al. (2012). Visual activation of auditory cortex reflects maladaptive plasticity in cochlear implant users. Brain135, 555–568. 10.1093/brain/awr329
145
ScheyltjensI.VreysenS.Van den HauteC.SabanovV.BalschunD.BaekelandtV.et al. (2018). Transient and localized optogenetic activation of somatostatin-interneurons in mouse visual cortex abolishes long-term cortical plasticity due to vision loss. Brain Struct. Funct.223, 2073–2095. 10.1007/s00429-018-1611-7
146
SeolG. H.ZiburkusJ.HuangS.SongL.KimI. T.TakamiyaK.et al. (2007). Neuromodulators control the polarity of spike-timing-dependent synaptic plasticity. Neuron55, 919–929. 10.1016/j.neuron.2007.08.013
147
ShaoZ.BurkhalterA. (1996). Different balance of excitation and inhibition in forward and feedback circuits of rat visual cortex. J. Neurosci.16, 7353–7365. 10.1523/JNEUROSCI.16-22-07353.1996
148
ShermanS. M. (2016). Thalamus plays a central role in ongoing cortical functioning. Nat. Neurosci.19, 533–541. 10.1038/nn.4269
149
ShibataH. (2000). Organization of retrosplenial cortical projections to the laterodorsal thalamic nucleus in the rat. Neurosci. Res.38, 303–311. 10.1016/s0168-0102(00)00174-7
150
SolaranaK.LiuJ.BowenZ.LeeH. K.KanoldP. O. (2019). Temporary visual deprivation causes decorrelation of spatiotemporal population responses in adult mouse auditory cortex. eNeuro6:ENEURO.0269-19.2019. 10.1523/ENEURO.0269-19.2019
151
SongY.-H.KimJ.-H.JeongH.-W.ChoiI.JeongD.KimK.et al. (2017). A neural circuit for auditory dominance over visual perception. Neuron93, 1236–1237. 10.1016/j.neuron.2017.02.026
152
SterrA.MüllerM. M.ElbertT.RockstrohB.PantevC.TaubE. (1998a). Changed perceptions in Braille readers. Nature391, 134–135. 10.1038/34322
153
SterrA.MüllerM. M.ElbertT.RockstrohB.PantevC.TaubE. (1998b). Perceptual correlates of changes in cortical representation of fingers in blind multifinger Braille readers. J. Neurosci.18, 4417–4423. 10.1523/JNEUROSCI.18-11-04417.1998
154
StevensA. A.WeaverK. E. (2009). Functional characteristics of auditory cortex in the blind. Behav. Brain Res.196, 134–138. 10.1016/j.bbr.2008.07.041
155
SundbergS. C.LindstromS. H.SanchezG. M.GransethB. (2018). Cre-expressing neurons in visual cortex of Ntsr1-Cre GN220 mice are corticothalamic and are depolarized by acetylcholine. J. Comp. Neurol.526, 120–132. 10.1002/cne.24323
156
SuttonM. A.ItoH. T.CressyP.KempfC.WooJ. C.SchumanE. M. (2006). Miniature neurotransmission stabilizes synaptic function via tonic suppression of local dendritic protein synthesis. Cell125, 785–799. 10.1016/j.cell.2006.03.040
157
ThomsonA. M. (2010). Neocortical layer 6, a review. Front. Neuroanat.4:13. 10.3389/fnana.2010.00013
158
ToddT. P.FournierD. I.BucciD. J. (2019). Retrosplenial cortex and its role in cue-specific learning and memory. Neurosci. Biobehav. Rev.107, 713–728. 10.1016/j.neubiorev.2019.04.016
159
TremblayR.LeeS.RudyB. (2016). GABAergic interneurons in the neocortex: from cellular properties to circuits. Neuron91, 260–292. 10.1016/j.neuron.2016.06.033
160
TurrigianoG. G.LeslieK. R.DesaiN. S.RutherfordL. C.NelsonS. B. (1998). Activity-dependent scaling of quantal amplitude in neocortical neurons. Nature391, 892–896. 10.1038/36103
161
Van BovenR. W.HamiltonR. H.KauffmanT.KeenanJ. P.Pascual-LeoneA. (2000). Tactile spatial resolution in blind braille readers. Neurology54, 2230–2236. 10.1212/wnl.54.12.2230
162
Van BrusselL.GeritsA.ArckensL. (2011). Evidence for cross-modal plasticity in adult mouse visual cortex following monocular enucleation. Cereb. Cortex21, 2133–2146. 10.1093/cercor/bhq286
163
van GroenT.WyssJ. M. (1992). Projections from the laterodorsal nucleus of the thalamus to the limbic and visual cortices in the rat. J. Comp. Neurol.324, 427–448. 10.1002/cne.903240310
164
Vélez-FortM.RousseauC. V.NiedworokC. J.WickershamI. R.RanczE. A.BrownA. P.et al. (2014). The stimulus selectivity and connectivity of layer six principal cells reveals cortical microcircuits underlying visual processing. Neuron83, 1431–1443. 10.1016/j.neuron.2014.08.001
165
VossP.LassondeM.GougouxF.FortinM.GuillemotJ. P.LeporeF. (2004). Early- and late-onset blind individuals show supra-normal auditory abilities in far-space. Curr. Biol.14, 1734–1738. 10.1016/j.cub.2004.09.051
166
WeilR. S.ReesG. (2011). A new taxonomy for perceptual filling-in. Brain Res. Rev.67, 40–55. 10.1016/j.brainresrev.2010.10.004
167
WertzA.TrenholmS.YoneharaK.HillierD.RaicsZ.LeinweberM.et al. (2015). Single-cell-initiated monosynaptic tracing reveals layer-specific cortical network modules. Science349, 70–74. 10.1126/science.aab1687
168
WilliamsL. E.HoltmaatA. (2019). Higher-order thalamocortical inputs gate synaptic long-term potentiation via disinhibition. Neuron101, 91.e4–102.e4. 10.1016/j.neuron.2018.10.049
169
WimmerR. D.SchmittL. I.DavidsonT. J.NakajimaM.DeisserothK.HalassaM. M. (2015). Thalamic control of sensory selection in divided attention. Nature526, 705–709. 10.1038/nature15398
170
WinkowskiD. E.NagodeD. A.DonaldsonK. J.YinP.ShammaS. A.FritzJ. B.et al. (2018). Orbitofrontal cortex neurons respond to sound and activate primary auditory cortex neurons. Cereb. Cortex28, 868–879. 10.1093/cercor/bhw409
171
WongM.GnanakumaranV.GoldreichD. (2011). Tactile spatial acuity enhancement in blindness: evidence for experience-dependent mechanisms. J. Neurosci.31, 7028–7037. 10.1523/JNEUROSCI.6461-10.2011
172
YangW.CarrasquilloY.HooksB. M.NerbonneJ. M.BurkhalterA. (2013). Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex. J. Neurosci.33, 17373–17384. 10.1523/JNEUROSCI.2515-13.2013
173
YilmazM.MeisterM. (2013). Rapid innate defensive responses of mice to looming visual stimuli. Curr. Biol.23, 2011–2015. 10.1016/j.cub.2013.08.015
174
ZhangS.XuM.ChangW.-C.MaC.Hoang DoJ. P.JeongD.et al. (2016). Organization of long-range inputs and outputs of frontal cortex for top-down control. Nat. Neurosci.19, 1733–1742. 10.1038/nn.4417
175
ZhangS.XuM.KamigakiT.Hoang DoJ. P.ChangW. C.JenvayS.et al. (2014). Selective attention. Long-range and local circuits for top-down modulation of visual cortex processing. Science345, 660–665. 10.1126/science.1254126
176
ZhouN. A.MaireP. S.MastersonS. P.BickfordM. E. (2017). The mouse pulvinar nucleus: organization of the tectorecipient zones. Vis. Neurosci.34:E011. 10.1017/S0952523817000050
177
ZikopoulosB.BarbasH. (2007). Circuits formultisensory integration and attentional modulation through the prefrontal cortex and the thalamic reticular nucleus in primates. Rev. Neurosci.18, 417–438. 10.1515/revneuro.2007.18.6.417
178
ZinggB.ChouX.-L.ZhangZ.-G.MesikL.LiangF.TaoH. W.et al. (2017). AAV-mediated anterograde transsynaptic tagging: mapping corticocollicular input-defined neural pathways for defense behaviors. Neuron93, 33–47. 10.1016/j.neuron.2016.11.045
179
ZurD.UllmanS. (2003). Filling-in of retinal scotomas. Vis. Res.43, 971–982. 10.1016/s0042-6989(03)00038-5
Summary
Keywords
cross-modal plasticity, cortical plasticity, cortical circuits, subcortical circuits, sensory loss, multi-sensory interaction, metaplasticity, functional connectivity
Citation
Ewall G, Parkins S, Lin A, Jaoui Y and Lee H-K (2021) Cortical and Subcortical Circuits for Cross-Modal Plasticity Induced by Loss of Vision. Front. Neural Circuit 15:665009. doi: 10.3389/fncir.2021.665009
Received
06 February 2021
Accepted
14 April 2021
Published
25 May 2021
Volume
15 - 2021
Edited by
Julio C. Hechavarría, Goethe University Frankfurt, Germany
Reviewed by
Lutgarde Arckens, KU Leuven, Belgium; Kai-Wen He, Interdisciplinary Research Center on Biology and Chemistry (CAS), China
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Copyright
© 2021 Ewall, Parkins, Lin, Jaoui and Lee.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hey-Kyoung Lee heykyounglee@jhu.edu
†These authors have contributed equally to this work and share first authorship
Disclaimer
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