extfieldsofstudy: Biology Medicine

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A humanized version of Foxp2 does not affect ultrasonic vocalization in adult mice

The transcription factor FOXP2 has been linked to severe speech and language impairments in humans. An analysis of the evolution of the FOXP2 gene has identified two amino acid substitutions that became fixed after the split of the human and chimpanzee lineages. Studying the functional consequences of these two substitutions in the endogenous Foxp2 gene of mice showed alterations in dopamine levels, striatal synaptic plasticity, neuronal morphology and cortico‐striatal‐dependent learning. In addition, ultrasonic vocalizations (USVs) of pups had a significantly lower average pitch than control littermates. To which degree adult USVs would be affected in mice carrying the ‘humanized’ Foxp2 variant remained unclear. In this study, we analyzed USVs of 68 adult male mice uttered during repeated courtship encounters with different females. Mice carrying the Foxp2hum/hum allele did not differ significantly in the number of call elements, their element structure or in their element composition from control littermates. We conclude that neither the structure nor the usage of USVs in adult mice is affected by the two amino acid substitutions that occurred in FOXP2 during human evolution. The reported effect for pup vocalization thus appears to be transient. These results are in line with accumulating evidence that mouse USVs are hardly influenced by vocal learning. Hence, the function and evolution of genes that are necessary, but not sufficient for vocal learning in humans, must be either studied at a different phenotypic level in mice or in other organisms.

Humans are the only primates that have developed volitional control over their sound production. Monkeys and apes lack the ability to imitate sounds vocally. Further, nonhuman primates do not need auditory input to develop their species-specific vocalization structure (Ackermann et al. 2014;Egnor & Hauser 2004;Jürgens 2009). Except for some few anecdotal findings, which suggest that captive apes may show some limited capacity for vocal production learning (Wich et al. 2012), the majority of studies showed that vocal learning does not play a role in the normal development of nonhuman primate vocalizations (Arriaga et al. 2012;Fitch 2010;. In terrestrial mammals and humans, the basic neurological and muscular systems necessary for vocalizations overlap to a large degree (Ackermann et al. 2014;Jürgens 2002). The present view is that a direct projection from the motor cortex to the laryngeal motor neurons, similar to the direct forebrain projection to vocal motor neurons in birds, is necessary for the ability to gain control over vocal production. Monkeys and apes lack such a direct projection (Arriaga et al. 2012;Hage et al. 2013;Simonyan 2014;Simonyan & Jürgens 2003).
One of the pressing questions is therefore to understand how the neurological basis for volitional vocal control emerged during evolution. Potentially, the tuning of cortico-striatal circuits, similar to the anterior forebrain pathway in birds with its specialized striatal region Area X, might have paved the way for recruiting neural circuits for vocal learning (Enard 2011;Murugan et al. 2013;Pfenning et al. 2014;Simonyan et al. 2012). In the search for the genetic basis that gave rise to such adaptations, FOXP2 is a strong candidate gene. Humans that are heterozygous for a non-functional FOXP2 allele suffer from an impairment that especially affects their speech and language development (Lai et al. 2001;Macdermot et al. 2005;Vargha-Khadem et al. 2005;Watkins 2011). Analyses of the evolution of the FOXP2 gene showed two amino acid substitutions, which became fixed in the human lineage after its separation from the chimpanzee. It was suggested that these two substitutions underwent positive selection potentially due to their effect on speech and language (Enard et al. 2002;Zhang et al. 2002).
To test the functional consequences of these two substitutions, Enard and colleagues established a mouse model, which carries these substitutions in the endogenous mouse Foxp2 gene (Enard et al. 2009). Mice homozygous for this humanized Foxp2 allele (Foxp2 hum/hum ) show specific alterations in the cortico-basal ganglia circuits, including changes to tissue dopamine levels, striatal synaptic plasticity, dendrite morphology and gene expression (Enard 2011;Enard et al. 2009;Reimers-Kipping et al. 2011;Schreiweis et al. 2014). Strikingly, pups carrying the humanized Foxp2 gene differed in their ultrasonic vocalizations (USVs). Although both Foxp hum/hum pups and their wild-type littermates were able to produce isolation calls within the normal strain-specific range and did not differ in their calling activity, the isolation calls themselves showed significant differences in the level of peak frequency (main energy), i.e. in the pitch of their USVs (Enard et al. 2009).
Importantly, the available evidence suggests that the structure of mouse vocalizations is largely innate and that auditory learning is not a prerequisite for the production of species (or strain) typical vocalizations (Ehret 2005;Hammerschmidt et al. 2012bHammerschmidt et al. , 2015. Nevertheless, it might be that the humanized version of Foxp2 affects the motor patterns sub-serving vocal production. If this is the case, the differences between adult mice carrying the humanized Foxp2 version and their wild-type littermates should be more pronounced because adult mice produce far more complex USVs than pups do (Fischer & Hammerschmidt 2011;Holy & Guo 2005). To explore this possibility, we studied the courtship vocalization of adult males by exposing resident males of different Foxp2 genotypes to encounters with females ( Fig. 1a). We compared the structure of the emitted USVs among genotypes and specifically predicted more elaborate temporal and/or spectral patterns in Foxp2 hum/hum male mice.

Mice and recording setup
We used mice carrying the humanized Foxp2 allele (Foxp2 hum ) before the neomycin cassette was removed [derived from the Bl6 ES cell 5H10, as described in the study of Enard et al. (2009)] and mice carrying the humanized Foxp2 allele after the neomycin cassette had been removed [Foxp2 humΔneo ; 5H10 line as described in the study of Enard et al. (2009)]. We used these two lines as the presence of a neomycin cassette can in principle have effects in addition to the two amino acid changes and to make maximal use of the available mice in the colony. A total of 144 virgin mice, aged 9-16 weeks, were grouped into 24 analysis units of six mice each (13 units/line Foxp2 hum and 11 units/line Foxp2 humΔneo ). Each unit was composed of one homozygous, one heterozygous and one wild-type male and female mice. These were matched as much as possible for age and litter among the genotypes and housed in groups of two to five individuals (for number of males per genotype and line, see Table 1). Approximately 48 h prior to testing, the three females of one unit were group-housed in a clean cage and received dirty bedding from cages containing the males of the unit. Approximately 24 h prior to testing, males were single-housed. Vocalization recordings took place in a separate testing room after a short habituation period between 0800 and 1700 h. The lid, food grid and water bottle of the home cage containing the single-housed male were removed and the cage was put into a sound-proof plexiglass chamber (custom-made), which was cleaned with an anti-odorant disinfectant (Decosept, Borer Chemie, Zuchwil, Switzerland). To obtain a more consistent call quality, we reduced the home cage surface by inserting a plexiglass separator into the male home cage and positioned the ultrasound microphone (CM16) centrally above the remaining home cage surface. Ultrasonic vocalizations have a highly confined active space and the plexiglass separator limited the distance between the male and the microphone. After 120 seconds of habituation, the male was recorded for 30 seconds (control recording) before a female was added to the cage, the chamber was closed and ultrasonic courtship songs were recorded for 2 min. We decided to use this time frame because preliminary experience (pre-study) had indicated that subjects frequently fall silent after the first 2 min. The order of male/female encounters of each unit were pseudo-randomly assigned so that each male (i.e. of each genotype) encountered each female (i.e. of each genotype) once and no animal was tested twice consecutively (Fig. 1a). Units of each line were recorded on separate days, except for the last recording day, where two units of the Foxp2 humΔneo line and one unit of the Foxp2 hum line were recorded. For the recordings, the microphone was connected to a preamplifier (UltraSoundGate 116, hardware and software: Avisoft Bioacoustics, Glienicke, Germany), which was connected to a computer using the recording software AVISOFT SASLAB PRO v4.33 with a sampling frequency of 300 kHz (hardware and software: Avisoft Bioacoustics, Glienicke, Germany). Mice were housed at a 10 h/14 h dark/light cycle under standard conditions in isolated ventilated racks (lights on at 0700 h). All animal work was performed in accordance with guidelines of the Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, and federal regulations of Saxony, Germany.

Analysis of element structure
The sampling frequency of 300 kHz resulted in a frequency range of 150 kHz. To reduce background noise at lower frequencies, which could negatively influence the estimation of whistle tracking algorithm, we used a high-pass FIR filter of 35 kHz. We used the whistle tracking algorithm of AVISOFT SAS LAB PRO 5.2 (Avisoft Bioacoustics) with the following settings: monotonic, maximum change per step 8 pix = 4.7 kHz, minimum continuity = 8 milliseconds, hold time = 15 milliseconds. These criteria were compared with previous analyses of male mouse vocalizations (Fischer & Hammerschmidt 2011;Hammerschmidt et al. 2012a;Jamain et al. 2008). Based on these settings, we calculated the number of given call elements, inter-element interval (ICI: from the end of an element to the start of the next element) and element duration.
For the analysis of call structure, we used the AVISOFT RECORDER 4.2 (Avisoft Bioacoustics) to store the single elements as separated wav files. We used the same whistle tracking algorithm with the same settings as described above. From the stored elements, we calculated spectrograms (frequency range: 150 kHz, frequency resolution: 293 Hz, time resolution: 0.21 milliseconds). The spectrograms were submitted to the custom software program LMA 2012 [developed by K. Hammerschmidt, see Fischer et al. (2013)] to estimate characteristic acoustic parameters (Fig. 1b,c). As mice typically concentrate the energy of their calls into one small frequency band, so-called whistles or pure tone-like sounds (see Figs. 1c, S1), we focused on the peak frequency, i.e. the loudest frequency in the spectrum, which corresponds in most cases to the fundamental frequency (F0). Mice often produce soft sounds, and minor head movements as well as close body contact can lead to strong amplitude fluctuations in USVs. Therefore, we used LMA to control the estimated peak frequency visually and excluded incorrectly estimated elements from the analysis.
For each call element, we determined the duration and the duration of amplitude gaps. We defined the start of an element when the sound energy of a time segment exceeded 10% of the mean maximum amplitude of the respective element. We used the same criterion to determine the end of an element. 'Duration' was calculated as the difference between these two measurements in milliseconds. An amplitude gap within an element is defined if the sound energy of a time segment falls below 10% of the mean maximum amplitude. The parameter 'amplitude gap' represents the sum of all time segments below the 10% threshold multiplied by the time resolution in milliseconds. Furthermore, we determined the start (PF start), maximum peak frequency (PF max), as well as the greatest difference in peak frequency between two consecutive 0.21-millisecond bins (so-called frequency jumps; PF jump). In addition, we calculated the location of the maximum frequency measured in relation to element duration ((1/duration) × location). To describe the element modulation, we calculated the slope of a linear trend ('element slope') through the peak frequencies of consecutive 0.21-millisecond bins.
To achieve a balanced distribution of elements per subject, we selected 150 elements per subject of the 120-second recordings (50 elements within every 40-second interval). In total, we analyzed 24 661 out of 85 635 recorded elements from 68 males. To measure structural differences between genotypes, we first compared the acoustic parameters across the entire vocal repertoire, i.e. irrespective of the specific element type ('unpartitioned vocal repertoire'). Next, we conducted the analysis at the level of different element types. We used a two-step cluster analysis (IBM SPSS STATISTICS 21, Armonk, New York, USA) with the log-likelihood distance measure and the Schwarz-Bayesian information criterion (BIC) to find the cluster solution with the best fit. First, we tested a three-cluster solution, which was the solution with the best BIC value, like in former mouse studies (Hammerschmidt et al. 2012a(Hammerschmidt et al. ,2012b. In addition, we chose the six-cluster solution, which turned out to be the solution with the highest number of cluster by same silhouette coefficient (S C = 0.3). Cluster solutions with a higher number of clusters dropped clearly under S C of 0.3. Silhouette values ranged between −1.0 and 1.0 and values exceeding 0.5 are usually considered as solid solutions, silhouette values below 0.3 are seen as insufficient solutions (Rousseeuw 1987).

Element composition
To test whether mice carrying the humanized Foxp2 differ in the structure of the calls, we analyzed the sequential composition. We did this at an even finer grained level of analysis, using a visual classification. We did this for two reasons: firstly, the automated characterization is only suited for calls with a high signal-to-noise ratio. The exclusion of all call elements that were disturbed by background noise, for instance, would have hampered the sequential analysis. Secondly, these finer categories made a type II error less likely. The visual classification was similar to previous descriptions of male mouse courtship vocalizations (Ey et al. 2012;Scattoni et al. 2008). We classified the elements of a call into 19 element types. In addition, we grouped these element types into three general element categories (Fig. S1). We calculated the percentage of given element types  (element type and general element category), transition rates of both categorizations, as well as chain lengths per subject and encounter.

Further statistical procedures
All data were analyzed using an LMM (IBM SPSS STATISTICS 21, USA), including genotype and line (Foxp2 hum and Foxp2 humΔneo ) as fixed factors, and the interaction between genotype and line. For the description of general vocal behavior across all call types (unpartitioned repertoire), we included encounter order as a fixed factor. Whenever we used repeated recordings per subject, we included subject as random factor. We corrected all P-values for multiple testing using Simes correction.
To exclude the possibility that acoustic differences would be restricted to elements with a short duration, as in the case of pup isolation calls (Enard et al. 2009), we conducted an additional analysis, focusing on short elements   (<50 milliseconds) only. The analysis did not show any significant differences in the structure of the calls between wild-type males (wt/wt) and males carrying the humanized version of the Foxp2 gene (hum/hum, Table 2) either.

Difference in element structure
The analysis of the unpartitioned vocal repertoire showed no significant differences in relation to genotype, line or genotype/line interaction (Fig. 2, Table 3). We only found significant differences in relation to repetitive encounters. Dependent on whether the males had the first, second or third encounter with females, we found an increase in element duration, and a decrease in peak frequency (Fig. 3, Table 3).
The two-step cluster analysis identified a three-cluster solution as the best solution. The first cluster comprised long elements with major frequency jumps. The second cluster consisted of elements with medium duration and a general descending frequency course. The third element cluster contained short elements without frequency jumps. The analysis showed no significant differences in relation to genotypes or line in any of the different call types (Table 4).
In addition, we tested a similarly good cluster solution with six clusters to compare the obtained results with a more differentiated data set. We found significant differences between genotypes only in one cluster (CT5), in two of the acoustic parameters: PF jump [wt/wt = 30.1 ± 0.79 kHz (mean ± SEM); hum/wt = 32.9 ± 0.67 kHz; hum/hum = 33.9 ± 0.68 kHz], PF max loc (wt/wt = 0.55 ± 0.018; hum/wt = 0.51 ± 0.14; hum/hum = 0.48 ± 0.014). This suggests that males homozygous for humanized Foxp2 produced call elements with slightly more pronounced frequency jumps and a slightly earlier frequency maximum (Table S1).

Differences in element composition
We tested 65 males, for which we had a sufficient number of elements to conduct a meaningful sequence analysis. The  We tested the chain length, how many times successive elements fell into the same element type and the transition rate, i.e. how often a subject changed from one element type to another. We did these comparisons at two levels: at the level of the 19 single element types and with the three general element categories to compare changes and transition of short, medium and long elements. We found no significant differences in any of these measurements between mice with the humanized Foxp2 gene, heterozygous or wild types (Table 5). We also found no significant differences in element type usage (Table S2).

Discussion
We did not find a significant influence of the humanized Foxp2 allele on USVs of adult mice. This result was independent from the way we classified the elements, i.e. whether we tested the unpartitioned data set containing all elements or focused on single element types. We also found no differences in our sequential analysis. Wild-type mice and mice carrying the humanized Foxp2 gene did not differ in the percentage of element types or in their sequential order. In all of these comparisons, we found only one significant difference in one element type (ET5) that was identified via a cluster solution with a total of six clusters. In this cluster, we found a minor difference in the amount of frequency jump and the location of the maximum peak. Given the number of statistical tests carried out in this study, it appears possible that this difference constitutes a false positive. Whether or not this change is of biological significance remains unclear in any case. The obvious problem with interpreting negative results is that we cannot exclude whether an alternative method would have picked up some differences that our method may have missed. In a pilot study, we had determined many more acoustic variables, but these were highly correlating with the variables in the present analysis. We therefore decided to use the present reduced set of acoustic variables, to reduce the likelihood of type 2 error in the subsequent statistical tests. This set of parameters has proved to be sensitive in other studies (Enard et al. 2009;Fischer & Hammerschmidt 2011;Hammerschmidt et al. 2012a), and they picked up differences in relation to the number of encounters. We are therefore relatively confident that the lack of a significant difference between genotypes is not simply due to an inefficient method. In addition, mice have a very limited frequency resolution in the frequency range of their courtship vocalizations (Portfors et al. 2011); therefore, it is unlikely that further acoustic analysis or playback experiments could show a positive result. Ultimately, this would be an empirical question.
For now, our present results strongly suggest that the two amino acid substitutions in Foxp2 do not have a substantial effect on adult mouse vocalization. Yet, we found that repeated encounters had a significant influence on song structure. This variation in vocal output, specifically the decreased number of call elements, could reflect motivational changes. Behavioral observations would be needed to clarify whether the mice explored less, for instance, and therefore produced not only fewer, but also longer vocalizations.
Apparently, the two amino acid substitutions are not sufficient to affect adult mouse vocalization patterns. This may be due to the fact that mice are not obligate vocal learners. The finding that male courtship songs of mice have a high structural complexity (Holy & Guo 2005) and that the structure of calls in pups change with age and social context (Grimsley et al. 2011) suggested that mice have a considerable amount of vocal flexibility. However, to what extent these variations in vocal repertoires are influenced by cortical control, motivational status and/or maturation processes is not yet clear.
Interestingly, Arriaga et al. (2012) identified a weak direct cortical projection to brainstem vocal motor neurons suggesting that mice should be able to have a limited degree of volitional control. However, several other studies show that deaf mice or cross-fostered mice still develop their strain-specific vocalizations (Hammerschmidt et al. 2012b;Kikusui et al. 2011;Mahrt et al. 2013). Hence, auditory feedback -a key feature for vocal learning -does not appear to be required for mouse vocalizations. In a recent study, Emx1-CRE;Esco2 fl/fl male mice lacking the hippocampus and large parts of the cortex show no differences in structure and complexity of courtship vocalization in comparison to control males (Hammerschmidt et al. 2015). This shows that cortical areas are not necessary for the production of USVs in mice irrespective of the putative direct cortical projection to brainstem vocal motor neurons (Arriaga et al. 2012). Hence, mouse vocalizations appear to depend much less on cortical influence and structures than human speech. Thus, if the humanized Foxp2 affects cortico-basal ganglia circuits as suggested (Enard et al. 2009), they may indeed have no effects on mouse adult vocalizations.
As the adult vocalizations appear to be unaffected by the human-specific amino acid substitutions, their previously described effects on element pitch and peak frequency modulation of pup isolation calls (Enard et al. 2009) are presumably transient. Both studies have the same methodological background and the same recording time. In both cases, we controlled for multiple testing. An interesting question is how such small differences (e.g. mean peak frequency of 77 ± 0.7 and 73.7 ± 0.7 kHz for wt/wt and hum/hum littermates, respectively) may be caused. In principle, a large range of even small developmental effects of humanized Foxp2 on neural and non-neural structures affecting pup vocalizations could be responsible. In our view, such effects would be very difficult to discover and study. Thus, we do not currently view the pup vocalization phenotype as a promising route to further study the effects of humanized Foxp2.
A more promising approach may be to study the genetic and neural basis of human speech in other model organisms that do show vocal learning such as song birds (Wohlgemuth et al. 2014) or develop new model species such as bats (Morell 2014). Nevertheless, the practical and scientific advantages of studying mice are huge and there is accumulating evidence that they have validity for studying at least some aspects of the genetic basis of human evolution (Enard 2014). If the cortical and subcortical effects on vocalizations are difficult or even impossible to study in mice, one may be able to study them indirectly by measuring other correlated phenotypes or endophenotypes, i.e. phenotypes which are more directly related to the genotype than vocalization. More work needs to be carried out to identify such phenotypes and clarify if they have validity for human speech. Motor learning paradigms have been suggested to be valid to decipher the effects of heterozygous loss-of-function mutations in Foxp2 French et al. 2012;Groszer et al. 2008). Some aspects of motor learning are indeed affected in mice carrying humanized Foxp2 (Schreiweis et al. 2014) as these mice learn stimulus-response associations faster than wild-type littermates potentially because the balance of activity between striatal regions is altered as indicated by measuring dopamine levels, gene expression patterns and an NMDA (N-methyl-D-aspartate) receptor-dependent form of long-term depression (Schreiweis et al. 2014). The study of such phenotypes may hopefully be used to better understand the human-specific function of FOXP2.

Supporting Information
Additional supporting information may be found in the online version of this article at the publisher's web-site: Figure S1: Examples of calls describing the categories used for visual classification.
Table S1: Significant differences between genotypes' six-cluster solution. Results are given as P-values and are corrected for multiple testing (Simes). Significant differences are marked in bold. Table S2: Differences in element type usage. ET, element type; GEC, general element category; P-values show differences in relation to genotype and line and are corrected for multiple testing (Simes). Significant differences are marked in bold.


Progressive decline of glucocerebrosidase in aging and Parkinson's disease

The principal risk factor for developing most adult onset neurodegenerative diseases is aging, with incidence rising significantly after age 50. Despite research efforts, the causes of Parkinson's disease (PD) remain unknown. As neurons age, they show signs of diminished lysosomal and mitochondrial function, including increased oxidative stress and accumulation of misfolded proteins, and these changes become exacerbated PD. We show that activity of the lysosomal hydrolase glucocerebrosidase gradually diminishes with age in the substantia nigra and putamen of healthy controls. This reduction is comparable to glucocerebrosidase activity in GBA1-mutation carrier PD patients. These data, demonstrate for the first time that an age-dependent reduction in glucocerebrosidase activity may lower the threshold for developing PD.

Introduction
Parkinson's disease (PD) is relatively rare before age 40, after age 50 the prevalence rises almost exponentially. 1 By the eighth decade, the estimated prevalence in European and North American populations is between 1000 and 3000 cases per 100,000 population. 1 This age-related risk may be related to the convergence of genetic impairments and age-related decline in cellular function, which include deficits in degradation pathways and elevated mitochondrial damage. As neurons age, they show signs of increased oxidative stress, disturbances in mitochondrial function, and accumulation of misfolded proteins, which are exacerbated in PD. If the role of lysosomal function could be better defined during the aging process, this may lead to more effective therapeutic options to treat PD.
Neuronal aging is unique because neurons are postmitotic cells, and therefore they rely heavily on protein clearance mechanisms to maintain homeostasis. The two major proteolytic systems responsible for intracellular protein turnover are the autophagy-lysosomal system and the ubiquitin-proteasome system. Aging lysosomal systems undergo dramatic changes including, increased volume and decreased stability and accumulation of indigestible materials. 2 This is significant given that lysosomes are responsible for the clearance of proteins, such as asynuclein as well as the removal of damaged organelles, such as mitochondria. 3,4 The gene GBA1 encodes for the lysosomal hydrolase glucocerebrosidase (GCase), and This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. reductions in GCase activity results in the accumulation of the glycolipids glucosylceramide (GluCer) and glucosylsphingosine (GluSph). Heterozygous loss-of-function mutations in GBA1 occur at a frequency of 4-7% in idiopathic PD patients. [5][6][7] Approximately, 6-7% of early onset PD (<51 years) are carriers of either the N370S or L444P GBA mutations. 8 These patients also develop clinical symptoms at an earlier age than nonmutation carriers. 9 Moreover, PD patients who harbor a loss-of-function GBA1 mutation usually develop more severe cognitive symptoms, are often diagnosed younger, and are associated with increased a-synuclein accumulation relative to non-GBA1 mutation carrier (nonGBA1) PD patients. 7,10-12 A recent report demonstrated that early stage nonGBA1 PD patients are associated with a reduction in GCase activity and dysfunctional lysosomes. 11 Despite the overwhelming evidence linking GBA1 and diminished GCase activity with PD, 7,12,13 it is presently unclear when this reduction occurs and how it is related to cellular aging and therefore its role the initiation and pathogenesis of the disease.
Elucidating some of the intracellular changes that occur with normal aging may give insight into the early changes that occur in PD. Our data suggest that aging lysosomes may contribute to the early pathology in PD and offers a broader perspective of how aging can lower the threshold and contribute to the onset of the disease. Here, we present data that show that GCase activity is reduced in non-GBA1 PD patients in the sixth, seven, and eight decade of life, which is associated with an increase in GluSph levels. Remarkably, healthy subject controls exhibit a gradual age-related reduction in GCase activity in the substantia nigra and putamen, which became evident during the seventh and eighth decade of life, respectively. These data suggest that GCase activity or more broadly diminished lysosomal function may be a critical age-related risk factor that increases the vulnerability of dopamine neurons and lower the threshold for developing PD.

Patients
Frozen postmortem brain tissue from male and female neurologically unaffected patients (healthy subject controls) and sporadic PD patients were provided by the Harvard Brain Tissue Resource Center (HBTRC; McLean Hospital, Belmont, MA). All PD cases met a pathological diagnosis of PD made by the brain bank, which was based on the extent of neuronal (pigment) loss in the substantia nigra and locus coeruleus (0-4), and Braak staging (0-6). Postmortem brains from healthy subject controls and PD patients were closely matched for age, sex, and postmortem interval ( Table 1). All of the PD patient brain tissue was sequenced for GBA1 mutations (the GBA1 pseudogene was taken into account) at Beckman Coulter Genomics (Danvers, MA) and any PD patient with a GBA1 mutation was removed from further analysis.

Glucocerebrosidase activity analysis
Brain tissue was resuspended in ice-cold MilliQ water and homogenized for 15 sec. A portion of the homogenate was used for protein determination (BCA Assay, Pierce, Pierce Biotechnology, Rockford/IL, USA). To determine GCase activity, brain homogenates were diluted in a 2 mg/mL bovine serum albumin, citric acid sodium phosphate buffer (pH 5).

Results
Glucocerebrosidase activity progressively declines in the substantia nigra with normal aging Brain tissue from nonGBA1 mutation carrying sporadic PD patients was collected and GCase activity was mea-sured in substantia nigra and putamen. Our data show a clear age-dependent decrease in GCase activity in the substantia nigra that spans the sixth to eighth decade of life (r = À0.643, P < 0.001) in healthy subject controls (Fig. 1A). A similar trend was also observed in the putamen across the sixth to eighth decade of life in healthy subject controls. This gradual decline in GCase activity in healthy subject controls became similar to nonGBA1 mutation carrying PD patients by the seventh decade in the substantia nigra (F 2,35 = 28.26, P < 0.0001) and the eighth decade in the putamen (F 2,32 = 7.16, P < 0.05). GluSph levels were increased in sporadic PD patients at the sixth decade of life (F 2,35 = 14.52, P < 0.001) in the substantia nigra. We measured both GluCer and GluSph in sporadic PD patient tissue, however, due to an interfering peak, only GluSph was analyzed.

Glucocerebrosidase activity is decreased in the brains of sporadic PD patients coinciding with an accumulation of GluSph
GCase activity and levels of GluSph were also assayed in the frontal cortex, hippocampus, and cerebellum of non-GBA1 PD patients and age-matched healthy controls between their 70 and 80 years of age. GCase activity was significantly decreased in the hippocampus (T 1,8 = 2.405, P < 0.05) and cerebellum (T 1,16 = 2.439, P < 0.05) in nonGBA1 PD patients in comparison to age-matched controls. We found a significant increase in GluSph in the hippocampus (T 1,10 = 3.19, P < 0.05) of nonGBA1 PD patients. There was a trend toward an increase for GluSph in the cerebellum of nonGBA1 PD patients in comparison to age-matched controls (Fig. 2B).

Discussion
Age-dependent reductions in GCase activity occur in normal aging and in sporadic PD patients The involvement of GCase in the pathogenesis of PD is still not understood. Postmortem brain samples from nonGBA1 PD patients show a significant decrease in GCase activity and protein levels in the substantia nigra and cerebellum. 14 We demonstrate for the first time that GCase activity gradually declines in the substantia nigra of healthy subject controls, eventually becoming comparable to PD patients by the seventh decade of life. Similarly, GCase activity also progressively declines in the putamen becoming comparable to PD patients by the eighth decade of life. Reductions in GCase activity may represent a progressive reduction in lysosomal function with normal aging, which may eventually become pathological to the cell. This is supported by recent evidence demonstrating that a reduction in GCase activity accelerates the progression and symptoms of PD. 12,15 This reduction in GCase activity is accompanied by an accumulation of GluSph in the substantia nigra. This is the first report, to the best of our knowledge that has measured glycolipids in the brain of PD patients. We observed the accumulation in GluSph in the substantia nigra may reflect diminished lysosomal clearance capacity. Although PD is rare before age 40, the prevalence rises almost exponentially after 50 years of age. 1 It is possible that when the amount of functioning GCase is reduced below a critical level, it may directly influence lysosomal clearance capacity causing inefficient protein degradation, and may eventually become pathological promoting the accumulation of misfolded proteins, and dysfunctional mitochondria GBA1 mutations are twice as common in early onset PD in comparison to late onset PD cases. 8 PD patients with a heterozygous GBA1 mutation are associated with 30-50% reduction in GCase activity. 12 These patients usually develop the disease earlier and are associated with more advanced a-synuclein pathology. 8,11 The motor impairments among GBA1 PD patients usually occur 6-7 years earlier in comparison to nonGBA1 PD patients. 8,16 The data reported here indicate that with age, the levels of GCase activity in healthy subjects eventually reach a level of GCase reduction that is similar to GBA1 haploid insufficient PD patients. Given that the cell biological processes caused by GBA1 haploid-insufficiency predispose individuals to PD by leading to early degeneration and a-synuclein pathology with onset of the disease in the sixth decade, it is therefore reasonable to assume that a 30-50% age-dependent reduction in GCase activity in the seventh and eighth decade of life (during normal aging) would significantly increase the risk for developing PD in a nonGBA1 carrier. Moreover, sporadic PD is likely caused by a combination of convergent mechanisms that include age-related risk factors that contribute to DA neuron vulnerability such as accumulation of dysfunctional mitochondria, deficits in protein degradation systems, and aggregated a-synuclein accumulation. These age-related biological deficits likely contribute to the exponential rise in PD in the seventh and eighth decade of life. Tracking GCase activity levels during aging and during the preclinical phase of the disease may provide a unique opportunity to identify changes Figure 2. GCase activity is decreased and GluSph is increased in sporadic PD patient brains. GCase is a lysosomal enzyme responsible for the hydrolysis of the lipid substrates GluCer into ceramide and glucose, and GluSph into sphingosine and glucose. Data show that GBA activity is diminished in the putamen, hippocampus, substantia nigra, and cerebellum of sporadic PD patients in comparison to age-matched controls (A). Diminished GBA activity corresponded to accumulation of GluSph in the hippocampus (B). *P < 0.05, unpaired t-test. N = 6-12/group. Graphs are expressed as mean AE SEM. GCase, glucocerebrosidase; GluSph, glucosylsphingosine; GluCer, glucosylceramide; PD, Parkinson's disease; SEM, standard error of the mean; ANOVA, analysis of variance.
that occur prior to the pathophysiology that leads to the onset of PD symptoms.
Diminished GCase activity and GluSph accumulation occur in sporadic non-GBA mutation PD patients We found widespread reduction in GCase activity in the cerebellum and hippocampus, in addition to the putamen and substantia nigra of sporadic PD patients that are non-GBA mutation carriers, which coincided with an increase in GluSph. These results show that the GluSph lipid substrate is accumulated in the brain of sporadic PD patients. It is possible that this accumulation of the GluSph disrupts intralysosomal homeostasis and promotes aggregation of a-synuclein, thus enhancing neuronal vulnerability. Recent observations have suggested a reciprocal relationship exists between GCase and a-synuclein. 17,18 Moreover, a landmark finding supports this reciprocal relationship between GCase and a-synuclein by demonstrating that a partial loss of GCase activity can interfere with protein degradation in the lysosome, promote accumulation of a-synuclein, and enhance a-synuclein-mediated neurotoxicity. 17 Therefore, accumulation of GluSph, and possibly GluCer, may contribute to the pathophysiology of PD by disrupting lysosomal function.


extfieldsofstudy: Psychology Medicine

s2fieldsofstudy: Biology Psychology

text:
Sensory Deprivation during Early Postnatal Period Alters the Density of Interneurons in the Mouse Prefrontal Cortex

Early loss of one sensory system can cause improved function of other sensory systems. However, both the time course and neuronal mechanism of cross-modal plasticity remain elusive. Recent study using functional MRI in humans suggests a role of the prefrontal cortex (PFC) in cross-modal plasticity. Since this phenomenon is assumed to be associated with altered GABAergic inhibition in the PFC, we have tested the hypothesis that early postnatal sensory deprivation causes the changes of inhibitory neuronal circuit in different regions of the PFC of the mice. We determined the effects of sensory deprivation from birth to postnatal day 28 (P28) or P58 on the density of parvalbumin (PV), calbindin (CB), and calretinin (CR) neurons in the prelimbic, infralimbic, and dorsal anterior cingulate cortices. The density of PV and CB neurons was significantly increased in layer 5/6 (L5/6). Moreover, the density of CR neurons was higher in L2/3 in sensory deprived mice compared to intact mice. These changes were more prominent at P56 than at P28. These results suggest that long-term sensory deprivation causes the changes of intracortical inhibitory networks in the PFC and the changes of inhibitory networks in the PFC may contribute to cross-modal plasticity.

Introduction
The brain can adapt to sensory loss by neuronal plasticity. Blind individuals compensate their lack of visual input by improving sensitivity to auditory or somatosensory inputs. This type of plasticity is known as cross-modal plasticity [1,2]. Although dynamic cortical reorganization among different sensory areas seemed to be critical for cross-modal plasticity, the molecular and cellular mechanisms underlying it are still poorly understood [1,2]. The elucidation of the mechanisms underlying cross-modal plasticity provides the clues for developing therapeutic approaches to help sensory recovery and substitution after brain infraction and trauma.
The improved functions of intact sensory systems have been explained by anatomical and functional reorganization of neural circuit in the sensory deprived primary sensory cortex [1,[3][4][5][6][7][8]. Reorganization of neural circuit in the sensory deprived primary cortex involves formation of aberrant corticocortical or thalamocortical inputs from intact sensory systems, or unmasking of preexisting latent corticocortical and/or thalamocortical inputs. In mice enuleated bilateral eyes immediately after birth, somatosensory axons invade also into the dorsal lateral geniculate nucleus in addition to the ventral lateral nucleus, but the barrel cortex and auditory cortex appear to expand [9]. It indicates cross-modal interactions between somatosensory/auditory and visual area [10][11][12]. Also in cats, early postnatal visual deprivation induces both somatosensory and auditory cross-modal innervations into the primary visual cortex [4,13,14]. Single-unit recordings from a multisensory area called the anterior ectosylvian cortex show that, in visually deprived cats, cortical areas that respond to auditory stimuli expand significantly and neurons in this area are more sharply tuned to auditory spatial localization [13,15]. Multisensory integration enhances overall perceptual accuracy and saliency [16]. Therefore, it is reasonable to assume that anatomical and functional changes 2 Neural Plasticity of neuronal networks including the multisensory cortices contribute to improved function of intact sensory systems following loss of one system. Neuronal plasticity is regulated by higher cognitive functions such as mental arousal and attention [17,18]. Cross-modal reorganization of different sensory systems may require a coordinated shift of attention from the deprived to the intact sense [19,20]. A recent study using functional MRI in humans suggests the importance of the prefrontal cortex (PFC) for cross-modal plasticity [21]. The middle temporal complex (MT/MST) specialized for motion perception. In congenitally blind individuals, functional connectivity between MT/MST and dorsal lateral PFC is enhanced, but functional connectivity between MT/MST and primary auditory cortex is not enhanced. The results suggest that crossmodal plasticity may be mediated by the PFC and critical period for cross-modal plasticity may be critical period for plasticity in the PFC but not in the auditory cortex [22].
Converging evidence indicates importance of inhibitory interneurons, in activity-dependent synaptic plasticity and in cross-modal plasticity [9]. Recent studies using experimental models of cross-modal plasticity suggest that changes in the density, laminar distribution, and morphology of interneurons could be a key component in cross-modal plasticity processes following sensory deprivation early in life [9,23]. The majority of inhibitory interneurons express at least one of the calcium-binding proteins parvalbumin (PV), calbindin (CB), and calretinin (CR), and these proteins have been shown to be excellent markers of distinct interneuron subtypes [24][25][26][27]. Together, they account for more than 80% of the total GABAergic interneurons in the rodent PFC [28], highlighting the importance of specific calcium dynamics in interneuronal function. Changes in the expression of calcium-binding proteins can define the functional characteristics of interneurons that impact the inhibitory control of prefrontal output.
Development of GABAergic circuits is a prolonged process that is complete by the end of adolescence [29][30][31][32]. The prolonged development of interneurons may constitute a sensitive period where environmental changes can lead to permanent alterations in the inhibitory circuitry. Within the sensory system, neocortical inhibitory networks exhibit experience-dependent maturation [33][34][35][36][37][38]. However, the influence of experience-dependent plasticity of inhibitory networks and its underlying mechanisms in the PFC is unclear. Destruction of olfactory epithelium by formaldehyde in FVB mice at postnatal day 12 (P12) increases number and neurites complexity of somatostatin neurons in L4 of the barrel cortex and improves tactile sensation [23]. Enucleation of bilateral eyes in hamsters at birth increases PV neurons in L4 and decreases PV neurons and CB neurons in L5 of the primary visual cortex [9]. As a consequence, laminar distribution of PV and CB neurons in the primary visual cortex becomes similar to that in the auditory cortex. Interneurons, particularly CB neurons and PV neurons, have a protracted development reaching their neurochemical and morphological maturity only by the end of adolescence making them very sensitive to sensory experiences [27,39,40]. In rodent PFC, the functional maturation of GABAergic inhibition experiences profound changes during adolescence [29][30][31][32]. However, it is not clear whether the change of sensory deprivation on interneuron density during postnatal period can be induced in the developing mouse PFC.
In the present study, we examined the effects of sensory deprivation by whisker trimming or dark rearing on the density of PV, CB, and CR neurons in the PFC. We found that sensory deprivation from P0 to P56 increased the density of PV, CB, and CR neurons in the PFC. The results suggest that the changes of interneuron density in the PFC may contribute to cross-modal plasticity.

Animals and Sensory
Deprivation. New born C57BL/6N mice were used. All efforts were made to minimize animal's pain and stress. Mice were divided into four groups: (i) whisker trimmed, (ii) dark reared, (iii) dark rearing of whisker trimmed, and (iv) non-treated mice. To examine the effect of somatic sensory deprivation, all principal whiskers on bilateral snouts were trimmed to less than one mm in length everyday using surgical scissors from P2 to P28 or P56. Because whiskers quickly regrow, whisker trimming was performed every day. Due to the short manipulation time, no anesthesia was used. Control mice were also handled every day in the same way but did not have their whiskers trimmed. To examine the effect of visual deprivation, animals were reared in dark condition instead of 12 h light/dark conditions before birth until perfusion at P28 or P56.
The study was carried out in accordance with the National Institute of Health (NIH) Guide for the Care and Use of Laboratory Animals (NIH Publications number 80-23, revised in 1996) and approved by the Committee for Animal Experiments at Okayama University Advanced Research Center. All efforts were made to minimize the number of animals used. Animals were purchased from Charles River Laboratories (Kanagawa, Japan). The animals were housed in cages (3-5 animals per cage) with food and water provided ad libitum under 12 h light/dark conditions at 23-26 ∘ C.

Tissue Preparation.
The animals were anesthetized with a lethal dose of sodium pentobarbital (Nembutal, Dainippon Sumitomo Pharma, Osaka, Japan; P28 and P56 animals, 100 mg/kg, i.p.) and transcardially perfused with ice-cold 0.01 M phosphate buffer (PB) for 2 min, followed by 4% paraformaldehyde and 0.2% picric acid in 0.1 M PB, pH 7.4, for 10 min. The brains were dissected and postfixed overnight in the same fixative at 4 ∘ C. They were then cryoprotected by incubation in 15% sucrose for 7 h followed by 30% sucrose for 20 h at 4 ∘ C. The brains were then frozen in O.C.T. compound (Tissue-Tek, Sakura Finetek, Tokyo, Japan) by freezing in dry ice-cold normal hexane. Serial 40 m coronal sections were prepared on a cryostat (CM-1900, Leica, Wetzlar, Germany) at −20 ∘ C. Every section at the level of the PFC was collected and placed in ice-cold phosphate-buffered saline (PBS).

Quantification of Interneurons.
For preparation of digital images, light microscopic images were captured by Lumi-naVision software (version 2.4.0, Mitani Corporation, Fukui, Japan), and brightness and contrast were slightly adjusted.
The medial regions of PFC (prelimbic cortex (PL), infralimbic cortex (IL), and dorsal regions of anterior cingulate cortex (dAC)) were parcellated according to cytoarchitectonic criteria [41], with reference to [42]. All cytoarchitectural boundaries were assessed at 4x magnification ( Figure 1). To visualize pyramidal neuron somata, we used NeuN immunoreactivity. NeuN is thought to be a pan-neuronal marker. The PL, IL, and dAC regions were identified using NeuN staining. The border between the PL and dAC is marked by a widening of layer 5 (L5) and an increase in the density of L3 cells in the dAC as compared to the PL. The posterior border of the dAC and ventral regions of anterior cingulate cortex (vAC) is defined by an increase in the density of cells in, L2 and by the presence of clearly distinguishable L3. The border between IL and PL is made principally on the basis of the transition between L1-L3; the most superficial cells in L2 of IL extend into L1 whereas the boundary between L1 and L2 in the PL is much more distinct. L2 cells are more densely packed in the PL as compared to IL. L2/3 and L5/6 were measured separately (mouse PFC lacks L4). Beginning with the first section containing white matter, prefrontal cortical areas were parcellated on each section collected until the first section in which the genu of the corpus callosum appeared. This results in parcellation of both hemispheres in 25 sections per animal. Five sections (1 in 5 series) through the entire region were selected and stained with NeuN, and volume was calculated. The average number of immunoreactive neurons at each level in a region was obtained from bilateral counts in a single section and estimated number of neurons calculated according to Abercrombie's formula [43]. For quantification of interneurons and measurement of each region, immunohistochemical images captured by LuminaVision software were analyzed using NIH imageJ software (NIH, Bethesda, MD; http://rsb.info.nih.gov/nih-image/). Estimations of neural density (cells/mm 2 ) were carried out.

Data
Analysis. The quantification was performed by an observer who was blinded to the sensory deprivation. Data are expressed as mean ± S.E.M. of six animals per group. Statistical comparisons were performed using ANOVA or Mann-Whitney test, and statistical significance was set at <0.05.

Results
As shown in Figure 2, all interneuron subtypes were present in the mouse PFC at P28. In the PL, PV neurons were located in both L2/3 and L5/6 ( Figure 2(a)). The processes of PV neurons were distributed through all layers. Also CB neurons were present in both L2/3 and 5/6 ( Figure 2(b)). Although the principal neurons in L2 are weakly immunopositive to CB [44], CB positive interneurons were darkly stained compared to principal neurons. The majority of CB neurons were multipolar, but bipolar neurons were also observed ( Figure 2(B)). CR neurons were more abundant in L2/3 than L5/6 ( Figure 2(c)). They displayed bipolar arbor-like morphology (Figure 2(C)). These distribution patterns of calcium-binding proteins were consistent with previous literature [28,[44][45][46][47]. In order to evaluate whether specific interneuronal population might be more susceptible to sensory deprivation, we analyzed the density of PV, CB, and CR neurons.

Changes of the Density of PV Neurons in the Primary
Sensory Cortices at P28. Bilateral trimming of all principal whiskers significantly decreased the density of PV neurons in L4 of the barrel cortex at P28 (Figures 3(a) and 3(c)). The decrease of PV neuron density in L4 by whisker trimming in neonatal mice was consistent with the previous study [48]. Whisker trimming decreased PV neuron density in L4 and 5/6 of the primary visual cortex (Figure 3(d)).
At P28 dark rearing increased the density of PV neurons in L2/3 and 4 in the primary visual cortex (Figures 3(b) and 3(d)). In addition, dark rearing caused atrophy of the primary visual cortex as described in hamsters enucleated bilateral eyes at birth [9]. Dark rearing increased PV neuron density in all layers of the barrel cortex (Figures 3(a) and 3(c)). A possible reason of the increase of PV neuron density in the barrel cortex is increased whisking activity following dark rearing. To examine this, we performed dark rearing in whisker trimmed mice. Whisker trimming cancelled the increase of PV neuron density in L2/3 and 5/6 of the barrel cortex. However, the increase of PV neuron density in L4 was still significant in whisker trimmed mice (Figures 3(a) and 3(c)). Whisker trimming also cancelled the increase of PV neuron density in L4 of the primary visual cortex. However, the increase of PV neuron density in L2/3 was not cancelled (Figure 3(d)). Furthermore, the atrophy of the primary visual cortex by visual deprivation was not rescued by whisker trimming (Figures 3(b) and 3(d)).

Effects of Sensory Deprivation on the Density of PV Neurons in the PFC at P28.
There was no change in the density of PV neurons between intact mice and sensory deprived mice in the PL (Figure 4(a)). In L2/3 of the IL, whisker trimming, dark rearing, or dark rearing of whisker trimmed mice significantly decreased PV neuron density (Figure 4(c)). Moreover, whisker trimming significantly decreased PV neuron density in L5/6 of the IL (Figure 4(c)). Whisker trimming, dark rearing, or dark rearing of whisker trimmed mice significantly increased PV neuron density in L5/6 but not in L2/3 of the dAC (Figure 4(e)).

Effects of Sensory Deprivation on the Density of PV Neurons in the PFC at P56.
Representative examples of PV staining of the PL from each group are shown in Figure 5. The effect of sensory deprivation from P0 to P56 in the PL was different compared with P28. Whisker trimming or dark rearing of whisker trimmed mice significantly increased PV neuron density both in L2/3 and 5/6 of the PL (Figure 4(b)). Dark rearing increased PV neuron density in L5/6 of the PL (Figure 4(b)). Dark rearing or dark rearing of whisker  trimmed mice increased PV neuron density in L5/6 of the IL (Figure 4(d)). Whisker trimming or dark rearing of whisker trimmed mice significantly increased PV neuron density in both L2/3 and L5/6 of the dAC (Figure 4(f)). Dark rearing increased PV neuron density in only L5/6 of the dAC (Figure 4(f)).

Effects of Sensory Deprivation on the Density of CB
Neurons in the PFC at P28. We found no difference in CB neuron density both in the PL and in the IL for mice sensory deprived compared with intact mice (Figures 6(a) and 6(c)). In contrast to the PL and IL, we found a significant increase in the density of CB neurons in the dAC L5/6 of sensory deprived mice (Figure 6(e)).

Effects of Sensory Deprivation on the Density of CB
Neurons in the PFC at P56. Similar to the finding at P28 no significant difference in the density of CB neurons was found between intact mice and sensory deprived mice in the PL at P56 (Figure 6(b)). Whisker trimming or dark rearing significantly increased CB neuron density in L5/6 of the IL (Figure 6(d)). Dark rearing of whisker trimmed mice significantly increased CB neuron density in both L2/3 and 5/6 of the IL (Figure 6(d)). Similar to finding at P28, whisker trimming, dark rearing, or dark rearing of whisker trimmed mice significantly increased CB neuron density in L5/6 of the dAC (Figure 6(f)).

Effects of Sensory Deprivation on the Density of CR Neurons in the PFC at P28.
There was no significant difference in CR neuron density between sensory deprived mice and intact mice in the PFC at P28 (Figures 7(a), 7(c), and 7(e)).

Effects of Sensory Deprivation on the Density of CR Neurons in the PFC at P56
. Whisker trimming, dark rearing, or dark rearing of whisker trimmed mice significantly increased CR neuron density in L2/3 of the PL (Figure 7(b)). Dark rearing of whisker trimmed mice also increased CR neuron density in L5/6 of the PL (Figure 7(b)). Whisker trimming or dark rearing of whisker trimmed mice increased CR neuron density in L2/3 of the IL (Figure 7(d)). In contrast, the upregulation of the density of CR neurons by only dark rearing was not observed in the IL (Figure 7(d)). Whisker trimming, dark rearing, or dark rearing of whisker trimmed mice significantly increased CR neuron density in L2/3 but not in L5/6 of the dAC (Figure 7(f)).

Changes of the Interneuron Density in the Primary Sensory
Cortices by Sensory Deprivation. PV neurons appear to be coincident with the onset of critical period of the formation of receptive field in the barrel cortex [49] and for ocular dominance plasticity in the primary visual cortex [35,50,51]. Sensory deprivation retards the appearance of PV neurons and maturation of synapse formation by PV neurons in the barrel cortex [48] and the primary visual cortex [33,52]. PV neurons are more sensitive to sensory deprivation than excitatory neurons [53]. Therefore, we at first examined the appearance of PV neurons in the barrel cortex and primary visual cortex to confirm that whisker trimming or/and dark rearing induces cross-modal plasticity in the primary sensory cortices. Dark rearing increased PV neurons in the barrel cortex (Figure 3(c)). This is likely in most part due to increase of whisking activity because the increase of PV neuron density in L2/3 and L5/6 was cancelled by whisker trimming. However, the increase of PV neuron density in L4 was not cancelled by whisker trimming (Figure 3(c)). The latter suggests the presence of corticocortical or corticothalamocortical interactions between the barrel cortex and other sensory cortices (e.g., primary auditory cortex) or multimodal association cortices. Dark rearing also increased PV neuron density may be in part due to atrophy of the primary visual cortex (Figure 3(d)). However, whisker trimming cancelled the increase of PV neuron density in L4 without protecting the atrophy of the primary visual cortex (Figures 3(b) and  3(d)). The result suggests that the increase of PV neurons in L4 is in part caused by recruitment or unmasking of somatosensory inputs to the primary visual cortex. However, the increase of PV neurons in L2/3 is unlikely due to unmasking or recruitment of somatosensory input because it was not cancelled by whisker trimming. Whisker trimming decreased PV neurons in L4 and L5/6 in the primary visual cortex (Figure 3(d)). The decrease of PV neurons by whisker trimming was cancelled by dark rearing (Figure 3(d)). One possible explanation for the decrease of PV neurons by whisker trimming is competitive interaction or reciprocal inhibition between visual and somatosensory thalamocortical projections to the visual cortex. Presence of latent somatosensory input to the visual cortex is shown in adult mice [54]. Somatosensory input to the visual cortex is supposed to dominate visual input in neonatal mice because maturation of receptive field in the barrel cortex completes in the second postnatal week [49] whereas formation of ocular dominance column in the primary visual cortex completes in the fourth postnatal week [35,50,51]. Therefore, neonatal visual deprivation may enhance somatosensory input to the visual cortex whereas somatosensory deprivation attenuates it. Consistent with this notion, whisker trimming plus dark rearing increased PV neuron density in L2/3 (Figure 3(d)). It is difficult to explain this by recruitment or unmasking of intact sensory inputs to the primary visual cortex. It suggests the presence of corticocortical or corticothalamocortical interactions between the primary visual cortex and other sensory cortices (e.g., primary auditory cortex) or association cortices.
Together, whisker trimming or/and dark rearing induced unimodal and cross-modal changes of PV neuron density in the primary sensory cortices that were in part considered to be due to corticocortical interactions.

Changes of the Interneuron Density in the PFC by Sensory
Deprivation. The expression of calcium-binding proteins PV, CB, and CR was differently regulated in the PFC during developmental period [29][30][31][32]. PV expression is very low at early postnatal stages and is significantly increased by early adulthood. In contrast, the expression of CR is reduced from juvenile to early adulthood, whereas the expression of CB remains unaltered during development period [32].
The density of CB neurons significantly increased in L5/6, whereas the density of CR neurons increased in L2/3 of the PFC of the sensory deprived mice at P56. CB neurons innervate distal dendritic shafts and dendritic spines of pyramidal neurons. Recent in vivo studies using two-photon laser scanning microscopy and fluorescently tagged gephyrin have demonstrated that pruning of inhibitory synapse terminals at distal dendritic spines of pyramidal neurons is major mechanisms of ocular dominance plasticity in the adult visual cortex [55,56]. Although both studies have not identified interneurons providing inhibitory synapse terminals at distal dendrites, the most possible candidates are CB/somatostatin neurons. If this is the case, sensory deprivation may increase inhibitory synapse terminals on distal dendrites of pyramidal neurons in the PFC. CR neurons mainly innervate dendritic shafts of pyramidal neurons. Furthermore, CR neurons innervate other interneurons, particularly CB neurons, in supragranular layer of cerebral cortex, and their excitation causes disinhibition of pyramidal neurons [57][58][59][60]. A recent study has demonstrated that inhibitory inputs on dendrites are more powerful than inhibitory inputs to perisomatic regions for inhibiting firing of CA1 pyramidal neurons in the hippocampus [61]. Therefore, the increase of L5/6 CB and L2/3 CR neuron densities by sensory deprivation may reflect enhanced synaptic inhibition on pyramidal neuron dendrites and reduced excitation of pyramidal neurons. Alternatively the increase of CB and CR neurons may reflect compensatory mechanism for increased excitatory inputs to protect excessive excitation of pyramidal neurons. The density of PV neurons increased in L2/3 and L5/6 of the PFC of the sensory deprived mice, compared to intact mice, at P56. The protein level of PV is lowest in juveniles and increases during adolescence to levels similar to those observed in adulthood [32]. The increased PV expression during adolescence is an activity-driven event at a time when metabolic demand of energy increased [62]. An increase of PV neurons in the PFC by sensory deprivation has not been reported. PV basket neurons control synchronous firing and output of pyramidal neurons [63]. Therefore, the results suggest that somatosensory deprivation and visual deprivation enhance the control by PV neurons on synchronous firing of pyramidal neurons in the PFC although electrophysiological analysis is required to clarify these points. And, the alteration of PV neurons by sensory deprivation was likely the result of an increase of the survival rate of PV neurons. Anyway the alterations of the interneuron density of the PFC in sensory deprived mice indicate that alternative pathway for cross-modal plasticity may be present.

Regional Variability in Sensory Deprived Alteration of
Interneurons. The change of the density of PV, CB, and CR interneurons after sensory deprivation was similar among the PL, IL, and dAC. These results confirm our prediction that early sensory deprivation interferes with the development of distinct interneuron subtypes in the PL, IL, and dAC. The PFC receives multimodal corticocortical projections from auditory, somatosensory, visual, gustatory, and limbic cortices and has a role as nodal station of cortical networks [64]. Pyramidal neurons in L5/6 of the PFC project to L2/3 of the primary sensory cortices [57]. Therefore, it seems likely that the increase of PV neuron density around L5/6 pyramidal neurons by sensory deprivation modifies outputs from the PFC to the primary sensory cortices. The increase of PV neurons in L2/3 of the primary visual cortex by somatosensory plus visual deprivation (Figure 3(d)) may be a result of increased input from the prefrontal cortex. On the neuroanatomical level, the dorsal and ventral PFC has different connections with other brain regions. The dAC predominantly has reciprocal connections with motor, somatosensory, visual, and retrosplenial cortices. The PL and IL are distinguishable from dAC by relatively greater connectivity with the hippocampus and other limbic structures [64]. The dAC contributes to the formation of emotional and motivational behaviors, attention, and visceral function by interactions with the PL and IL. Attention is required for certain forms of associative learning [17] and involves the function of the dAC in rodents [65][66][67].

Possible Role of PFC in Cross-Modal Plasticity.
Recent studies have shown that thalamocortical projection is already well-segregated into eye-specific bands before the onset of critical period for ocular dominance plasticity [68,69].
In the rat barrel cortex, supragranular neurons selectively respond to a single principal whisker before the critical period for the formation of receptive field in L2/3 [70]. Therefore, a role of experience-dependent plasticity may be sharpening receptive fields and balancing excitatory and inhibitory inputs to principal neurons [71]. Another possible role of sensory experience is enhancement of anatomical and functional connections between sensory cortices and association cortices that integrate multisensory inputs [71].
In this context, it is not surprising that the PFC mediates sensory information to association cortices or primary sensory cortices to compensate loss of a sensory input. Our results indicate that sensory deprivation modifies inhibitory control of synaptic inputs to pyramidal neurons and of outputs from pyramidal neurons in the PFC and suggest that the anatomical and functional changes of inhibitory neuronal circuit in the PFC may contribute to cross-modal plasticity.

Conclusions
We show for the first time somatosensory or/and visual deprivation increased PV, CB, and CR neuron densities in the PFC. The results suggest that sensory deprivation enhances inhibitory control of synaptic inputs to pyramidal neurons and of synchronous firing of pyramidal neurons in the PFC, and anatomical and functional changes of inhibitory neuronal circuit in the PFC may contribute to cross-modal plasticity. And, these findings indicate that sensory input is needed for the normal development of interneurons in the PFC.