Delayed inhibition in cortical receptive fields and the discrimination of complex stimuli

Parvalbumin neurons enhance temporal coding and reduce cortical noise in complex auditory scenes

Cortical representations supporting many cognitive abilities emerge from underlying circuits comprised of several different cell types. However, cell type-specific contributions to rate and timing-based cortical coding are not well-understood. Here, we investigated the role of parvalbumin neurons in cortical complex scene analysis. Many complex scenes contain sensory stimuli which are highly dynamic in time and compete with stimuli at other spatial locations. Parvalbumin neurons play a fundamental role in balancing excitation and inhibition in cortex and sculpting cortical temporal dynamics; yet their specific role in encoding complex scenes via timing-based coding, and the robustness of temporal representations to spatial competition, has not been investigated. Here, we address these questions in auditory cortex of mice using a cocktail party-like paradigm, integrating electrophysiology, optogenetic manipulations, and a family of spike-distance metrics, to dissect parvalbumin neurons' contributions towards rate and timing-based coding. We find that suppressing parvalbumin neurons degrades cortical discrimination of dynamic sounds in a cocktail party-like setting via changes in rapid temporal modulations in rate and spike timing, and over a wide range of time-scales. Our findings suggest that parvalbumin neurons play a critical role in enhancing cortical temporal coding and reducing cortical noise, thereby improving representations of dynamic stimuli in complex scenes.

AIM: A network model of attention in auditory cortex

Attentional modulation of cortical networks is critical for the cognitive flexibility required to process complex scenes. Current theoretical frameworks for attention are based almost exclusively on studies in visual cortex, where attentional effects are typically modest and excitatory. In contrast, attentional effects in auditory cortex can be large and suppressive. A theoretical framework for explaining attentional effects in auditory cortex is lacking, preventing a broader understanding of cortical mechanisms underlying attention. Here, we present a cortical network model of attention in primary auditory cortex (A1). A key mechanism in our network is attentional inhibitory modulation (AIM) of cortical inhibitory neurons. In this mechanism, top-down inhibitory neurons disinhibit bottom-up cortical circuits, a prominent circuit motif observed in sensory cortex. Our results reveal that the same underlying mechanisms in the AIM network can explain diverse attentional effects on both spatial and frequency tuning in A1. We find that a dominant effect of disinhibition on cortical tuning is suppressive, consistent with experimental observations. Functionally, the AIM network may play a key role in solving the cocktail party problem. We demonstrate how attention can guide the AIM network to monitor an acoustic scene, select a specific target, or switch to a different target, providing flexible outputs for solving the cocktail party problem.

Selective attention plays a key role in how we navigate our everyday lives. For example, at a cocktail party, we can attend to friend’s speech amidst other speakers, music, and background noise. In stark contrast, hundreds of millions of people with hearing impairment and other disorders find such environments overwhelming and debilitating. Understanding the mechanisms underlying selective attention may lead to breakthroughs in improving the quality of life for those negatively affected. Here, we propose a mechanistic network model of attention in primary auditory cortex based on attentional inhibitory modulation (AIM). In the AIM model, attention targets specific cortical inhibitory neurons, which then modulate local cortical circuits to emphasize a particular feature of sounds and suppress competing features. We show that the AIM model can account for experimental observations across different species and stimulus domains. We also demonstrate that the same mechanisms can enable listeners to flexibly switch between attending to specific targets sounds and monitoring the environment in complex acoustic scenes, such as a cocktail party. The AIM network provides a theoretical framework which can work in tandem with new experiments to help unravel cortical circuits underlying attention.

Spiking network optimized for word recognition in noise predicts auditory system hierarchy

The auditory neural code is resilient to acoustic variability and capable of recognizing sounds amongst competing sound sources, yet, the transformations enabling noise robust abilities are largely unknown. We report that a hierarchical spiking neural network (HSNN) optimized to maximize word recognition accuracy in noise and multiple talkers predicts organizational hierarchy of the ascending auditory pathway. Comparisons with data from auditory nerve, midbrain, thalamus and cortex reveals that the optimal HSNN predicts several transformations of the ascending auditory pathway including a sequential loss of temporal resolution and synchronization ability, increasing sparseness, and selectivity. The optimal organizational scheme enhances performance by selectively filtering out noise and fast temporal cues such as voicing periodicity, that are not directly relevant to the word recognition task. An identical network arranged to enable high information transfer fails to predict auditory pathway organization and has substantially poorer performance. Furthermore, conventional single-layer linear and nonlinear receptive field networks that capture the overall feature extraction of the HSNN fail to achieve similar performance. The findings suggest that the auditory pathway hierarchy and its sequential nonlinear feature extraction computations enhance relevant cues while removing non-informative sources of noise, thus enhancing the representation of sounds in noise impoverished conditions.

The brain’s ability to recognize sounds in the presence of competing sounds or background noise is essential for everyday hearing tasks. How the brain accomplishes noise resiliency, however, is poorly understood. Using neural recordings from the ascending auditory pathway and an auditory spiking network model trained for sound recognition in noise we explore the computational strategies that enable noise robustness. Our results suggest that the hierarchical feature organization of the ascending auditory pathway and the resulting computations are critical for sound recognition in the presence of noise.

Decreased auditory GABA+ concentrations in presbycusis demonstrated by edited magnetic resonance spectroscopy

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the central auditory system. Altered GABAergic neurotransmission has been found in both the inferior colliculus and the auditory cortex in animal models of presbycusis. Edited magnetic resonance spectroscopy (MRS), using the MEGA-PRESS sequence, is the most widely used technique for detecting GABA in the human brain. However, to date there has been a paucity of studies exploring changes to the GABA concentrations in the auditory region of patients with presbycusis. In this study, sixteen patients with presbycusis (5 males/11 females, mean age 63.1 ± 2.6 years) and twenty healthy controls (6 males/14 females, mean age 62.5 ± 2.3 years) underwent audiological and MRS examinations. Pure tone audiometry from 0.125 to 8 kHz and tympanometry were used to assess the hearing abilities of all subjects. The pure tone average (PTA; the average of hearing thresholds at 0.5, 1, 2 and 4 kHz) was calculated. The MEGA-PRESS sequence was used to measure GABA+ concentrations in 4 × 3 × 3 cm(3) volumes centered on the left and right Heschl's gyri. GABA+ concentrations were significantly lower in the presbycusis group compared to the control group (left auditory regions: p = 0.002, right auditory regions: p = 0.008). Significant negative correlations were observed between PTA and GABA+ concentrations in the presbycusis group (r = -0.57, p = 0.02), while a similar trend was found in the control group (r = -0.40, p = 0.08). These results are consistent with a hypothesis of dysfunctional GABAergic neurotransmission in the central auditory system in presbycusis and suggest a potential treatment target for presbycusis.

Binaural gain modulation of spectrotemporal tuning in the interaural level difference-coding pathway

In the brainstem, the auditory system diverges into two pathways that process different sound localization cues, interaural time differences (ITDs) and level differences (ILDs). We investigated the site where ILD is detected in the auditory system of barn owls, the posterior part of the lateral lemniscus (LLDp). This structure is equivalent to the lateral superior olive in mammals. The LLDp is unique in that it is the first place of binaural convergence in the brainstem where monaural excitatory and inhibitory inputs converge. Using binaurally uncorrelated noise and a generalized linear model, we were able to estimate the spectrotemporal tuning of excitatory and inhibitory inputs to these cells. We show that the response of LLDp neurons is highly locked to the stimulus envelope. Our data demonstrate that spectrotemporally tuned, temporally delayed inhibition enhances the reliability of envelope locking by modulating the gain of LLDp neurons' responses. The dependence of gain modulation on ILD shown here constitutes a means for space-dependent coding of stimulus identity by the initial stages of the auditory pathway.

Early experience shapes vocal neural coding and perception in songbirds

Songbirds, like humans, are highly accomplished vocal learners. The many parallels between speech and birdsong and conserved features of mammalian and avian auditory systems have led to the emergence of the songbird as a model system for studying the perceptual mechanisms of vocal communication. Laboratory research on songbirds allows the careful control of early life experience and high-resolution analysis of brain function during vocal learning, production, and perception. Here, I review what songbird studies have revealed about the role of early experience in the development of vocal behavior, auditory perception, and the processing of learned vocalizations by auditory neurons. The findings of these studies suggest general principles for how exposure to vocalizations during development and into adulthood influences the perception of learned vocal signals.

Competing sound sources reveal spatial effects in cortical processing

Why is spatial tuning in auditory cortex weak, even though location is important to object recognition in natural settings? This question continues to vex neuroscientists focused on linking physiological results to auditory perception. Here we show that the spatial locations of simultaneous, competing sound sources dramatically influence how well neural spike trains recorded from the zebra finch field L (an analog of mammalian primary auditory cortex) encode source identity. We find that the location of a birdsong played in quiet has little effect on the fidelity of the neural encoding of the song. However, when the song is presented along with a masker, spatial effects are pronounced. For each spatial configuration, a subset of neurons encodes song identity more robustly than others. As a result, competing sources from different locations dominate responses of different neural subpopulations, helping to separate neural responses into independent representations. These results help elucidate how cortical processing exploits spatial information to provide a substrate for selective spatial auditory attention.

Coevolution in communication senders and receivers: vocal behavior and auditory processing in multiple songbird species

Communication is a strong selective pressure on brain evolution because the exchange of information between individuals is crucial for fitness-related behaviors, such as mating. Given the importance of communication, the brains of signal senders and receivers are likely to be functionally coordinated. We study vocal behavior and auditory processing in multiple species of estrildid finches with the goal of understanding how species identity and early experience interact to shape the neural systems that subserve communication. Male finches learn to produce species-specific songs, and both sexes learn to recognize songs. Our studies indicate that closely related species exhibit different auditory coding properties in the midbrain and forebrain and that early life experience of vocalizations contributes to these differences. Moreover, birds that naturally sing tonal songs can learn broadband songs from heterospecific tutors, providing an opportunity to examine the interplay between species identity and early experience in the development of vocal behavior and auditory tuning.

Difference in response reliability predicted by spectrotemporal tuning in the cochlear nuclei of barn owls

The brainstem auditory pathway is obligatory for all aural information. Brainstem auditory neurons must encode the level and timing of sounds, as well as their time-dependent spectral properties, the fine structure, and envelope, which are essential for sound discrimination. This study focused on envelope coding in the two cochlear nuclei of the barn owl, nucleus angularis (NA) and nucleus magnocellularis (NM). NA and NM receive input from bifurcating auditory nerve fibers and initiate processing pathways specialized in encoding interaural time (ITD) and level (ILD) differences, respectively. We found that NA neurons, although unable to accurately encode stimulus phase, lock more strongly to the stimulus envelope than NM units. The spectrotemporal receptive fields (STRFs) of NA neurons exhibit a pre-excitatory suppressive field. Using multilinear regression analysis and computational modeling, we show that this feature of STRFs can account for enhanced across-trial response reliability, by locking spikes to the stimulus envelope. Our findings indicate a dichotomy in envelope coding between the time and intensity processing pathways as early as at the level of the cochlear nuclei. This allows the ILD processing pathway to encode envelope information with greater fidelity than the ITD processing pathway. Furthermore, we demonstrate that the properties of the STRFs of the neurons can be quantitatively related to spike timing reliability.

What can spike train distances tell us about the neural code?

Time scale parametric spike train distances like the Victor and the van Rossum distances are often applied to study the neural code based on neural stimuli discrimination. Different neural coding hypotheses, such as rate or coincidence coding, can be assessed by combining a time scale parametric spike train distance with a classifier in order to obtain the optimal discrimination performance. The time scale for which the responses to different stimuli are distinguished best is assumed to be the discriminative precision of the neural code. The relevance of temporal coding is evaluated by comparing the optimal discrimination performance with the one achieved when assuming a rate code. We here characterize the measures quantifying the discrimination performance, the discriminative precision, and the relevance of temporal coding. Furthermore, we evaluate the information these quantities provide about the neural code. We show that the discriminative precision is too unspecific to be interpreted in terms of the time scales relevant for encoding. Accordingly, the time scale parametric nature of the distances is mainly an advantage because it allows maximizing the discrimination performance across a whole set of measures with different sensitivities determined by the time scale parameter, but not due to the possibility to examine the temporal properties of the neural code.

From coarse to fine? Spatial and temporal dynamics of cortical face processing

Primary vision segregates information along 2 main dimensions: orientation and spatial frequency (SF). An important question is how this primary visual information is integrated to support high-level representations. It is generally assumed that the information carried by different SF is combined following a coarse-to-fine sequence. We directly addressed this assumption by investigating how the network of face-preferring cortical regions processes distinct SF over time. Face stimuli were flashed during 75, 150, or 300 ms and masked. They were filtered to preserve low SF (LSF), middle SF (MSF), or high SF (HSF). Most face-preferring regions robustly responded to coarse LSF, face information in early stages of visual processing (i.e., until 75 ms of exposure duration). LSF processing decayed as a function of exposure duration (mostly until 150 ms). In contrast, the processing of fine HSF, face information became more robust over time in the bilateral fusiform face regions and in the right occipital face area. The present evidence suggests the coarse-to-fine strategy as a plausible modus operandi in high-level visual cortex.

Discrimination of communication vocalizations by single neurons and groups of neurons in the auditory midbrain

Many social animals including songbirds use communication vocalizations for individual recognition. The perception of vocalizations depends on the encoding of complex sounds by neurons in the ascending auditory system, each of which is tuned to a particular subset of acoustic features. Here, we examined how well the responses of single auditory neurons could be used to discriminate among bird songs and we compared discriminability to spectrotemporal tuning. We then used biologically realistic models of pooled neural responses to test whether the responses of groups of neurons discriminated among songs better than the responses of single neurons and whether discrimination by groups of neurons was related to spectrotemporal tuning and trial-to-trial response variability. The responses of single auditory midbrain neurons could be used to discriminate among vocalizations with a wide range of abilities, ranging from chance to 100%. The ability to discriminate among songs using single neuron responses was not correlated with spectrotemporal tuning. Pooling the responses of pairs of neurons generally led to better discrimination than the average of the two inputs and the most discriminating input. Pooling the responses of three to five single neurons continued to improve neural discrimination. The increase in discriminability was largest for groups of neurons with similar spectrotemporal tuning. Further, we found that groups of neurons with correlated spike trains achieved the largest gains in discriminability. We simulated neurons with varying levels of temporal precision and measured the discriminability of responses from single simulated neurons and groups of simulated neurons. Simulated neurons with biologically observed levels of temporal precision benefited more from pooling correlated inputs than did neurons with highly precise or imprecise spike trains. These findings suggest that pooling correlated neural responses with the levels of precision observed in the auditory midbrain increases neural discrimination of complex vocalizations.

Inhibitory plasticity in a lateral band improves cortical detection of natural vocalizations

The interplay between excitation and inhibition in the auditory cortex is crucial for the processing of acoustic stimuli. However, the precise role that inhibition plays in the distributed cortical encoding of natural vocalizations has not been well studied. We recorded single units (SUs) and local field potentials (LFPs) in the awake mouse auditory cortex while presenting pup isolation calls to animals that either do (mothers) or do not (virgins) recognize the sounds as behaviorally relevant. In both groups, we observed substantial call-evoked inhibition. However, in mothers this was earlier, longer, stronger, and more stereotyped compared to virgins. This difference was most apparent for recording sites tuned to tone frequencies lower than the pup calls' high-ultrasonic frequency range. We hypothesize that this auditory cortical inhibitory plasticity improves pup call detection in a relatively specific manner by increasing the contrast between call-evoked responses arising from high-ultrasonic and lateral frequency neural populations.

Rapid synaptic depression explains nonlinear modulation of spectro-temporal tuning in primary auditory cortex by natural stimuli

In this study, we explored ways to account more accurately for responses of neurons in primary auditory cortex (A1) to natural sounds. The auditory cortex has evolved to extract behaviorally relevant information from complex natural sounds, but most of our understanding of its function is derived from experiments using simple synthetic stimuli. Previous neurophysiological studies have found that existing models, such as the linear spectro-temporal receptive field (STRF), fail to capture the entire functional relationship between natural stimuli and neural responses. To study this problem, we compared STRFs for A1 neurons estimated using a natural stimulus, continuous speech, with STRFs estimated using synthetic ripple noise. For about one-third of the neurons, we found significant differences between STRFs, usually in the temporal dynamics of inhibition and/or overall gain. This shift in tuning resulted primarily from differences in the coarse temporal structure of the speech and noise stimuli. Using simulations, we found that the stimulus dependence of spectro-temporal tuning can be explained by a model in which synaptic inputs to A1 neurons are susceptible to rapid nonlinear depression. This dynamic reshaping of spectro-temporal tuning suggests that synaptic depression may enable efficient encoding of natural auditory stimuli.

Temporal coding of time-varying stimuli

Temporal structure is an inherent property of various sensory inputs and motor outputs of the brain. For example, auditory stimuli are defined by the sound waveform. Temporal structure is also an important feature of certain visual stimuli, for example, the image on the retina of a fly during flight. In many cases, this temporal structure of the stimulus is being represented by a time-dependent neuronal activity that is locked to certain features of the stimulus. Here, we study the information capacity of the temporal code. In particular we are interested in the following questions. First, how does the information content of the code depend on the observation time of the cell's response, and what is the effect of temporal noise correlations on this information capacity? Second, what is the effect on the information content of reading the code with a finite temporal resolution for the neural response? We address these questions in the framework of a statistical model for the neuronal temporal response to a time-varying stimulus in a two-alternative forced-choice paradigm. We show that information content of the temporal response scales linearly with the overall time of the response, even in the presence of temporal noise correlations. More precisely, we find that positive temporal noise correlations have a scaling effect that decreases the information content. Nevertheless, the information content of the response continues to scale linearly with the observation time. We further show that finite temporal resolution is sufficient for obtaining most of the information from the cell's response. This finite timescale is related to the response properties of the cell.

Development of inhibitory mechanisms underlying selectivity for the rate and direction of frequency-modulated sweeps in the auditory cortex

Although it is known that neural selectivity for species-specific vocalizations changes during development, the mechanisms underlying such changes are not known. This study followed the development of mechanisms underlying selectivity for the direction and rate of frequency-modulated (FM) sweeps in the auditory cortex of the pallid bat, a species that uses downward FM sweeps to echolocate. In the adult cortex, direction and rate selectivity arise as a result of different spectral and temporal properties of low-frequency inhibition (LFI) and high-frequency inhibition (HFI). A narrow band of delayed HFI shapes rate selectivity for downward FM sweeps. A broader band of early LFI shapes direction selectivity. Here we asked whether these differences in LFI and HFI are present at the onset of hearing in the echolocation range or whether the differences develop slowly. We also studied how the development of properties of inhibitory frequencies influences FM rate and direction selectivity. We found that adult-like FM rate selectivity is present at 2 weeks after birth, whereas direction selectivity matures 12 weeks after birth. The different developmental time course for direction and rate selectivity is attributable to the differences in the development of LFI and HFI. Arrival time and bandwidth of HFI are adult-like at 2 weeks. Average arrival time of LFI gradually becomes faster and bandwidth becomes broader between 2 and 12 weeks. Thus, two properties of FM sweeps that are important for vocalization selectivity follow different developmental time courses attributable to the differences in the development of underlying inhibitory mechanisms.

Auditory discrimination of amplitude modulations based on metric distances of spike trains

Sound envelope cues play a crucial role for the recognition and discrimination of communication signals in diverse taxa, such as vertebrates and arthropods. Using a classification based on metric similarities of spike trains we investigate how well amplitude modulations (AMs) of sound signals can be distinguished at three levels of the locust's auditory pathway: receptors and local and ascending neurons. The spike train metric has the advantage of providing information about the necessary evaluation time window and about the optimal temporal resolution of processing, thereby yielding clues to possible coding principles. It further allows one to disentangle the respective contributions of spike count and spike timing to the fidelity of discrimination. These results are compared with the traditional paradigm using modulation transfer functions. Spike trains of receptors and two primary-like local interneurons enable an excellent discrimination of different AM frequencies, up to about 150 Hz. In these neurons discriminability depends almost completely on the timing of spikes, which must be evaluated with a temporal resolution of <5 ms. Even short spike-train segments of 150 ms, equivalent to five to eight spikes, suffice for a high (70%) discrimination performance. For the third level of processing, the ascending interneurons, the overall discrimination accuracy is reduced. Spike count differences become more important for the discrimination whereas the exact timing of spikes contributes less. This shift in temporal resolution does not primarily depend on the investigated stimulus space. Rather it appears to reflect a transformation of how amplitude modulations are represented at more central stages of processing.

Cortical discrimination of complex natural stimuli: can single neurons match behavior?

A central finding in many cortical areas is that single neurons can match behavioral performance in the discrimination of sensory stimuli. However, whether this is true for natural behaviors involving complex natural stimuli remains unknown. Here we use the model system of songbirds to address this problem. Specifically, we investigate whether neurons in field L, the homolog of primary auditory cortex, can match behavioral performance in the discrimination of conspecific songs. We use a classification framework based on the (dis)similarity between single spike trains to quantify neural discrimination. We use this framework to investigate the discriminability of single spike trains in field L in response to conspecific songs, testing different candidate neural codes underlying discrimination. We find that performance based on spike timing is significantly higher than performance based on spike rate and interspike intervals. We then assess the impact of temporal correlations in spike trains on discrimination. In contrast to widely discussed effects of correlations in limiting the accuracy of a population code, temporal correlations appear to improve the performance of single neurons in the majority of cases. Finally, we compare neural performance with behavioral performance. We find a diverse range of performance levels in field L, with neural performance matching behavioral accuracy only for the best neurons using a spike-timing-based code.

Dynamic spatial processing originates in early visual pathways

A variety of studies in the visual system demonstrate that coarse spatial features are processed before those of fine detail. This aspect of visual processing is assumed to originate in striate cortex, where single cells exhibit a refinement of spatial frequency tuning over the duration of their response. However, in early visual pathways, well known temporal differences are present between center and surround components of receptive fields. Specifically, response latency of the receptive field center is relatively shorter than that of the surround. This spatiotemporal inseparability could provide the basis of coarse-to-fine dynamics in early and subsequent visual areas. We have investigated this possibility with three separate approaches. First, we predict spatial-frequency tuning dynamics from the spatiotemporal receptive fields of 118 cells in the lateral geniculate nucleus (LGN). Second, we compare these linear predictions to measurements of tuning dynamics obtained with a subspace reverse correlation technique. We find that tuning evolves dramatically in thalamic cells, and that tuning changes are generally consistent with the temporal differences between spatiotemporal receptive field components. Third, we use a model to examine how different sources of dynamic input from early visual pathways can affect tuning in cortical cells. We identify two mechanisms capable of producing substantial dynamics at the cortical level: (1) the center-surround delay in individual LGN neurons, and (2) convergent input from multiple cells with different receptive field sizes and response latencies. Overall, our simulations suggest that coarse-to-fine tuning in the visual cortex can be generated completely by a feedforward process.

Temporal processing and adaptation in the songbird auditory forebrain

Songbird auditory neurons must encode the dynamics of natural sounds at many volumes. We investigated how neural coding depends on the distribution of stimulus intensities. Using reverse-correlation, we modeled responses to amplitude-modulated sounds as the output of a linear filter and a nonlinear gain function, then asked how filters and nonlinearities depend on the stimulus mean and variance. Filter shape depended strongly on mean amplitude (volume): at low mean, most neurons integrated sound over many milliseconds, while at high mean, neurons responded more to local changes in amplitude. Increasing the variance (contrast) of amplitude modulations had less effect on filter shape but decreased the gain of firing in most cells. Both filter and gain changes occurred rapidly after a change in statistics, suggesting that they represent nonlinearities in processing. These changes may permit neurons to signal effectively over a wider dynamic range and are reminiscent of findings in other sensory systems.

Auditory processing of vocal sounds in birds

The avian auditory system has become a model system to investigate how vocalizations are memorized and processed by the brain in order to mediate behavioral discrimination and recognition. Recent studies have shown that most of the avian auditory system responds preferentially and efficiently to sounds that have natural spectro-temporal statistics. In addition, neurons in secondary auditory forebrain areas have plastic response properties and are the most active when processing behaviorally relevant vocalizations. Physiological measurements show differential responses for vocalizations that were recently learned in discrimination tasks, and for the tutor song, a longer-term auditory memory that is used to guide vocal learning in male songbirds.

Prospective contributions of transgenic mouse models to central auditory research

Neuroscientists are increasingly embracing mice as a means to address central nervous system questions at a molecular level. Examples abound from sensory systems like olfaction and vision. The use of mice to study central auditory processing, however, has remained relatively limited. In this commentary, I draw on some of the successes from other fields to highlight directions in which mouse models may contribute valuable and otherwise unattainable insights into the neural circuitry and plasticity within central auditory stations. Efforts towards this are beginning and would benefit from increased collaboration to generate useful transgenic mouse models for such studies.