Subplate neurons are the first cortical neurons to respond to sensory stimuli.

In utero experience, such as maternal speech in humans, can shape later perception, although the underlying cortical substrate is unknown. In adult mammals, ascending thalamocortical projections target layer 4, and the onset of sensory responses in the cortex is thought to be dependent on the onset of thalamocortical transmission to layer 4 as well as the ear and eye opening. In developing animals, thalamic fibers do not target layer 4 but instead target subplate neurons deep in the developing white matter. We investigated if subplate neurons respond to sensory stimuli. Using electrophysiological recordings in young ferrets, we show that auditory cortex neurons respond to sound at very young ages, even before the opening of the ears. Single unit recordings showed that auditory responses emerged first in cortical subplate neurons. Subsequently, responses appeared in the future thalamocortical input layer 4, and sound-evoked spike latencies were longer in layer 4 than in subplate, consistent with the known relay of thalamic information to layer 4 by subplate neurons. Electrode array recordings show that early auditory responses demonstrate a nascent topographic organization, suggesting that topographic maps emerge before the onset of spiking responses in layer 4. Together our results show that sound-evoked activity and topographic organization of the cortex emerge earlier and in a different layer than previously thought. Thus, early sound experience can activate and potentially sculpt subplate circuits before permanent thalamocortical circuits to layer 4 are present, and disruption of this early sensory activity could be utilized for early diagnosis of developmental disorders.

Decoding sound level in the marmoset primary auditory cortex.

Neurons that respond favorably to a particular sound level have been observed throughout the central auditory system, becoming steadily more common at higher processing areas. One theory about the role of these level-tuned or nonmonotonic neurons is the level-invariant encoding of sounds. To investigate this theory, we simulated various subpopulations of neurons by drawing from real primary auditory cortex (A1) neuron responses and surveyed their performance in forming different sound level representations. Pure nonmonotonic subpopulations did not provide the best level-invariant decoding; instead, mixtures of monotonic and nonmonotonic neurons provided the most accurate decoding. For level-fidelity decoding, the inclusion of nonmonotonic neurons slightly improved or did not change decoding accuracy until they constituted a high proportion. These results indicate that nonmonotonic neurons fill an encoding role complementary to, rather than alternate to, monotonic neurons.NEW & NOTEWORTHY Neurons with nonmonotonic rate-level functions are unique to the central auditory system. These level-tuned neurons have been proposed to account for invariant sound perception across sound levels. Through systematic simulations based on real neuron responses, this study shows that neuron populations perform sound encoding optimally when containing both monotonic and nonmonotonic neurons. The results indicate that instead of working independently, nonmonotonic neurons complement the function of monotonic neurons in different sound-encoding contexts.

GAUSS-EM, guided accumulation of ultrathin serial sections with a static magnetic field for volume electron microscopy.

Serial sectioning electron microscopy (EM) of millimeter-scale three-dimensional (3D) anatomical volumes requires the collection of thousands of ultrathin sections. Here, we report a high-throughput automated approach, GAUSS-EM (guided accumulation of ultrathin serial sections-EM), utilizing a static magnetic field to collect and densely pack thousands of sections onto individual silicon wafers. The method is capable of sectioning hundreds of microns of tissue per day at section thicknesses down to 35 nm. Relative to other automated volume EM approaches, GAUSS-EM democratizes the ability to collect large 3D EM volumes because it is simple and inexpensive to implement. We present two exemplar EM volumes of a zebrafish eye and mouse olfactory bulb collected with the method.

Acid extrusion via blood-brain barrier causes brain alkalosis and seizures after neonatal asphyxia.

Birth asphyxia is often associated with a high seizure burden that is predictive of poor neurodevelopmental outcome. The mechanisms underlying birth asphyxia seizures are unknown. Using an animal model of birth asphyxia based on 6-day-old rat pups, we have recently shown that the seizure burden is linked to an increase in brain extracellular pH that consists of the recovery from the asphyxia-induced acidosis, and of a subsequent plateau level well above normal extracellular pH. In the present study, two-photon imaging of intracellular pH in neocortical neurons in vivo showed that pH changes also underwent a biphasic acid-alkaline response, resulting in an alkaline plateau level. The mean alkaline overshoot was strongly suppressed by a graded restoration of normocapnia after asphyxia. The parallel post-asphyxia increase in extra- and intracellular pH levels indicated a net loss of acid equivalents from brain tissue that was not attributable to a disruption of the blood-brain barrier, as demonstrated by a lack of increased sodium fluorescein extravasation into the brain, and by the electrophysiological characteristics of the blood-brain barrier. Indeed, electrode recordings of pH in the brain and trunk demonstrated a net efflux of acid equivalents from the brain across the blood-brain barrier, which was abolished by the Na/H exchange inhibitor, N-methyl-isobutyl amiloride. Pharmacological inhibition of Na/H exchange also suppressed the seizure activity associated with the brain-specific alkalosis. Our findings show that the post-asphyxia seizures are attributable to an enhanced Na/H exchange-dependent net extrusion of acid equivalents across the blood-brain barrier and to consequent brain alkalosis. These results suggest targeting of blood-brain barrier-mediated pH regulation as a novel approach in the prevention and therapy of neonatal seizures.

msemalign: a pipeline for serial section multibeam scanning electron microscopy volume alignment.

Serial section multibeam scanning electron microscopy (ssmSEM) is currently among the fastest technologies available for acquiring 3D anatomical data spanning relatively large neural tissue volumes, on the order of 1 mm3 or larger, at a resolution sufficient to resolve the fine detail of neuronal morphologies and synapses. These petabyte-scale volumes can be analyzed to create connectomes, datasets that contain detailed anatomical information including synaptic connectivity, neuronal morphologies and distributions of cellular organelles. The mSEM acquisition process creates hundreds of millions of individual image tiles for a single cubic-millimeter-sized dataset and these tiles must be aligned to create 3D volumes. Here we introduce msemalign, an alignment pipeline that strives for scalability and design simplicity. The pipeline can align petabyte-scale datasets such that they contain smooth transitions as the dataset is navigated in all directions, but critically that does so in a fashion that minimizes the overall magnitude of section distortions relative to the originally acquired micrographs.

Level-tuned neurons in primary auditory cortex adapt differently to loud versus soft sounds.

The responses of auditory neurons tuned to stimulus intensity (i.e., nonmonotonic rate-level responders) have typically been analyzed with stimulus paradigms that eliminate neuronal adaptation to recent stimulus statistics. This procedure is usually accomplished by presenting individual sounds with long silent periods between them. Studies using such paradigms have led to hypotheses that nonmonotonic neurons may play a role in amplitude spectrum coding or level-invariant representations of complex spectral shapes. We have previously proposed an alternate hypothesis that level-tuned neurons may represent specialized coders of low sound levels because they preserve their sensitivity to low levels even when average sound level is relatively high. Here we demonstrate that nonmonotonic neurons in awake marmoset primary auditory cortex accomplish this feat by adapting their upper dynamic range to encode sounds with high mean level, leaving the lower dynamic range available for encoding relatively rare low-level sounds. This adaptive behavior manifests in nonmonotonic relative to monotonic neurons as 1) a lesser amount of overall shifting of rate-level response thresholds and (2) a nonmonotonic gain adjustment with increasing mean stimulus level.

A computational framework for topographies of cortical areas.

Self-organizing feature maps (SOFMs) represent a dimensionality-reduction algorithm that has been used to replicate feature topographies observed experimentally in primary visual cortex (V1). We used the SOFM algorithm to model possible topographies of generic sensory cortical areas containing up to five arbitrary physiological features. This study explored the conditions under which these multi-feature SOFMs contained two features that were mapped monotonically and aligned orthogonally with one another (i.e., "globally orthogonal"), as well as the conditions under which the map of one feature aligned with the longest anatomical dimension of the modeled cortical area (i.e., "dominant"). In a single SOFM with more than two features, we never observed more than one dominant feature, nor did we observe two globally orthogonal features in the same map in which a dominant feature occurred. Whether dominance or global orthogonality occurred depended upon how heavily weighted the features were relative to one another. The most heavily weighted features are likely to correspond to those physical stimulus properties transduced directly by the sensory epithelium of a particular sensory modality. Our results imply, therefore, that in the primary cortical area of sensory modalities with a two-dimensional sensory epithelium, these two features are likely to be organized globally orthogonally to one another, and neither feature is likely to be dominant. In the primary cortical area of sensory modalities with a one-dimensional sensory epithelium, however, this feature is likely to be dominant, and no two features are likely to be organized globally orthogonally to one another. Because the auditory system transduces a single stimulus feature (i.e., frequency) along the entire length of the cochlea, these findings may have particular relevance for topographic maps of primary auditory cortex.

Visual and nonvisual contributions to three-dimensional heading selectivity in the medial superior temporal area.

Robust perception of self-motion requires integration of visual motion signals with nonvisual cues. Neurons in the dorsal subdivision of the medial superior temporal area (MSTd) may be involved in this sensory integration, because they respond selectively to global patterns of optic flow, as well as translational motion in darkness. Using a virtual-reality system, we have characterized the three-dimensional (3D) tuning of MSTd neurons to heading directions defined by optic flow alone, inertial motion alone, and congruent combinations of the two cues. Among 255 MSTd neurons, 98% exhibited significant 3D heading tuning in response to optic flow, whereas 64% were selective for heading defined by inertial motion. Heading preferences for visual and inertial motion could be aligned but were just as frequently opposite. Moreover, heading selectivity in response to congruent visual/vestibular stimulation was typically weaker than that obtained using optic flow alone, and heading preferences under congruent stimulation were dominated by the visual input. Thus, MSTd neurons generally did not integrate visual and nonvisual cues to achieve better heading selectivity. A simple two-layer neural network, which received eye-centered visual inputs and head-centered vestibular inputs, reproduced the major features of the MSTd data. The network was trained to compute heading in a head-centered reference frame under all stimulus conditions, such that it performed a selective reference-frame transformation of visual, but not vestibular, signals. The similarity between network hidden units and MSTd neurons suggests that MSTd may be an early stage of sensory convergence involved in transforming optic flow information into a (head-centered) reference frame that facilitates integration with vestibular signals.

The Effects of Auditory Contrast Tuning upon Speech Intelligibility.

We have previously identified neurons tuned to spectral contrast of wideband sounds in auditory cortex of awake marmoset monkeys. Because additive noise alters the spectral contrast of speech, contrast-tuned neurons, if present in human auditory cortex, may aid in extracting speech from noise. Given that this cortical function may be underdeveloped in individuals with sensorineural hearing loss, incorporating biologically-inspired algorithms into external signal processing devices could provide speech enhancement benefits to cochlear implantees. In this study we first constructed a computational signal processing algorithm to mimic auditory cortex contrast tuning. We then manipulated the shape of contrast channels and evaluated the intelligibility of reconstructed noisy speech using a metric to predict cochlear implant user perception. Candidate speech enhancement strategies were then tested in cochlear implantees with a hearing-in-noise test. Accentuation of intermediate contrast values or all contrast values improved computed intelligibility. Cochlear implant subjects showed significant improvement in noisy speech intelligibility with a contrast shaping procedure.

Extracellular space preservation aids the connectomic analysis of neural circuits.

Dense connectomic mapping of neuronal circuits is limited by the time and effort required to analyze 3D electron microscopy (EM) datasets. Algorithms designed to automate image segmentation suffer from substantial error rates and require significant manual error correction. Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data. We explored preserving extracellular space (ECS) during chemical tissue fixation to improve the ability to segment neurites and to identify synaptic contacts. ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates. In addition, we observed that electrical synapses are readily identified in ECS preserved tissue. Finally, we determined that antibodies penetrate deep into ECS preserved tissue with only minimal permeabilization, thereby enabling correlated light microscopy (LM) and EM studies. We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.

Spatial pattern of intra-laminar connectivity in supragranular mouse auditory cortex.

Neuronal responses and topographic organization of feature selectivity in the cerebral cortex are shaped by ascending inputs and by intracortical connectivity. The mammalian primary auditory cortex has a tonotopic arrangement at large spatial scales (greater than 300 microns). This large-scale architecture breaks down in supragranular layers at smaller scales (around 300 microns), where nearby frequency and sound level tuning properties can be quite heterogeneous. Since layer 4 has a more homogeneous architecture, the heterogeneity in supragranular layers might be caused by heterogeneous ascending input or via heterogeneous intralaminar connections. Here we measure the functional 2-dimensional spatial connectivity pattern of the supragranular auditory cortex on micro-column scales. In general connection probability decreases with radial distance from each neuron, but the decrease is steeper in the isofrequency axis leading to an anisotropic distribution of connection probability with respect to the tonotopic axis. In addition to this radial decrease in connection probability we find a patchy organization of inhibitory and excitatory synaptic inputs that is also anisotropic with respect to the tonotopic axis. These periodicities are at spatial scales of ~100 and ~300 µm. While these spatial periodicities show anisotropy in auditory cortex, they are isotropic in visual cortex, indicating region specific differences in intralaminar connections. Together our results show that layer 2/3 neurons in auditory cortex show specific spatial intralaminar connectivity despite the overtly heterogeneous tuning properties.

Rate-level responses in awake marmoset auditory cortex.

Investigations of auditory neuronal firing rate as a function of sound level have revealed a wide variety of rate-level function shapes, including neurons with nonmonotonic or level-tuned functions. These neurons have an unclear role in auditory processing but have been found to be quite common. In the present study of awake marmoset primary auditory cortex (A1) neurons, 56% (305 out of 544), when stimulated with tones at the highest sound level tested, exhibited a decrement in driven rate of at least 50% from the maximum. These nonmonotonic neurons demonstrated significantly lower response thresholds than monotonic neurons, although both populations exhibited thresholds skewed toward lower values. Nonmonotonic neurons significantly outnumbered monotonic neurons in the frequency range 6-13 kHz, which is the frequency range containing most marmoset vocalization energy. Spontaneous rate was inversely correlated with threshold in both populations, and spontaneous rates of nonmonotonic neurons had significantly lower values than spontaneous rates of monotonic neurons, although distributions of maximum driven rates were not significantly different. Finally, monotonicity was found to be organized within electrode penetrations like characteristic frequency but with less structure. These findings are consistent with the hypothesis that nonmonotonic neurons play a unique role in representing sound level, particularly at the lowest sound levels and for complex vocalizations.

Evaluation of techniques used to estimate cortical feature maps.

Functional properties of neurons are often distributed nonrandomly within a cortical area and form topographic maps that reveal insights into neuronal organization and interconnection. Some functional maps, such as in visual cortex, are fairly straightforward to discern with a variety of techniques, while other maps, such as in auditory cortex, have resisted easy characterization. In order to determine appropriate protocols for establishing accurate functional maps in auditory cortex, artificial topographic maps were probed under various conditions, and the accuracy of estimates formed from the actual maps was quantified. Under these conditions, low-complexity maps such as sound frequency can be estimated accurately with as few as 25 total samples (e.g., electrode penetrations or imaging pixels) if neural responses are averaged together. More samples are required to achieve the highest estimation accuracy for higher complexity maps, and averaging improves map estimate accuracy even more than increasing sampling density. Undersampling without averaging can result in misleading map estimates, while undersampling with averaging can lead to the false conclusion of no map when one actually exists. Uniform sample spacing only slightly improves map estimation over nonuniform sample spacing typical of serial electrode penetrations. Tessellation plots commonly used to visualize maps estimated using nonuniform sampling are always inferior to linearly interpolated estimates, although differences are slight at higher sampling densities. Within primary auditory cortex, then, multiunit sampling with at least 100 samples would likely result in reasonable feature map estimates for all but the highest complexity maps and the highest variability that might be expected.

Theoretical limitations on functional imaging resolution in auditory cortex.

Functional imaging can reveal detailed organizational structure in cerebral cortical areas, but neuronal response features and local neural interconnectivity can influence the resulting images, possibly limiting the inferences that can be drawn about neural function. Discerning the fundamental principles of organizational structure in the auditory cortex of multiple species has been somewhat challenging historically both with functional imaging and with electrophysiology. A possible limitation affecting any methodology using pooled neuronal measures may be the relative distribution of response selectivity throughout the population of auditory cortex neurons. One neuronal response type inherited from the cochlea, for example, exhibits a receptive field that increases in size (i.e., decreases in selectivity) at higher stimulus intensities. Even though these neurons appear to represent a minority of auditory cortex neurons, they are likely to contribute disproportionately to the activity detected in functional images, especially if intense sounds are used for stimulation. To evaluate the potential influence of neuronal subpopulations upon functional images of primary auditory cortex, a model array representing cortical neurons was probed with virtual imaging experiments under various assumptions about the local circuit organization. As expected, different neuronal subpopulations were activated preferentially under different stimulus conditions. In fact, stimulus protocols that can preferentially excite selective neurons, resulting in a relatively sparse activation map, have the potential to improve the effective resolution of functional auditory cortical images. These experimental results also make predictions about auditory cortex organization that can be tested with refined functional imaging experiments.

Specialized neuronal adaptation for preserving input sensitivity.

Some neurons in auditory cortex respond to recent stimulus history by adapting their response functions to track stimulus statistics directly, as might be expected. In contrast, some neurons respond to loud sounds by adjusting their response functions away from high intensities and consequently remain sensitive to softer sounds. In marmoset monkey auditory cortex, the latter type of adaptation appears to exist only in neurons tuned to stimulus intensity.