Intracortical multiplication of thalamocortical signals in mouse auditory cortex

"Distinct inhibitory neurons differently shape neuronal codes for sound intensity in the auditory cortex"

Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise bursts representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity level activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially modulated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensity. By contrast, VIP neuronal activation shifted responses towards a more distributed code, in which sounds of different intensity level are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the auditory cortex dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.

SIGNIFICANCE

Information about sounds is represented in the auditory cortex by neuronal population activity that has a characteristic sparse structure. Cortical neuronal populations comprise multiple types of excitatory and inhibitory neurons. Here, we find that activating different types of inhibitory neurons differentially controls population neuronal representations, with one type of inhibitory neurons increasing the differences in the identity of the cells recruited to represent the different sounds, and another inhibitory neuron type changing the relative activity level of overlapping neuronal populations. Such transformations may be beneficial for different types of auditory behaviors, suggesting that these different types of inhibitory neurons may be recruited under different behavioral constraints in optimizing neuronal representations of sounds.

Variation and convergence in the morpho-functional properties of the mammalian neocortex

Man's natural inclination to classify and hierarchize the living world has prompted neurophysiologists to explore possible differences in brain organisation between mammals, with the aim of understanding the diversity of their behavioural repertoires. But what really distinguishes the human brain from that of a platypus, an opossum or a rodent? In this review, we compare the structural and electrical properties of neocortical neurons in the main mammalian radiations and examine their impact on the functioning of the networks they form. We discuss variations in overall brain size, number of neurons, length of their dendritic trees and density of spines, acknowledging their increase in humans as in most large-brained species. Our comparative analysis also highlights a remarkable consistency, particularly pronounced in marsupial and placental mammals, in the cell typology, intrinsic and synaptic electrical properties of pyramidal neuron subtypes, and in their organisation into functional circuits. These shared cellular and network characteristics contribute to the emergence of strikingly similar large-scale physiological and pathological brain dynamics across a wide range of species. These findings support the existence of a core set of neural principles and processes conserved throughout mammalian evolution, from which a number of species-specific adaptations appear, likely allowing distinct functional needs to be met in a variety of environmental contexts.

Synapse-type-specific competitive Hebbian learning forms functional recurrent networks

Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circuits, this competition enables the formation and decorrelation of inhibition-balanced receptive fields. Networks develop an assembly structure with stronger synaptic connections between similarly tuned excitatory and inhibitory neurons and exhibit response normalization and orientation-specific center-surround suppression, reflecting the stimulus statistics during training. These results demonstrate how neurons can self-organize into functional networks and suggest an essential role for synapse-type-specific competitive learning in the development of cortical circuits.

The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations

When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.

Primate neocortex performs balanced sensory amplification

The sensory cortex amplifies relevant features of external stimuli. This sensitivity and selectivity arise through the transformation of inputs by cortical circuitry. We characterize the circuit mechanisms and dynamics of cortical amplification by making large-scale simultaneous measurements of single cells in awake primates and testing computational models. By comparing network activity in both driven and spontaneous states with models, we identify the circuit as operating in a regime of non-normal balanced amplification. Incoming inputs are strongly but transiently amplified by strong recurrent feedback from the disruption of excitatory-inhibitory balance in the network. Strong inhibition rapidly quenches responses, thereby permitting the tracking of time-varying stimuli.

The logic of recurrent circuits in the primary visual cortex

Recurrent cortical activity sculpts visual perception by refining, amplifying or suppressing visual input. However, the rules that govern the influence of recurrent activity remain enigmatic. We used ensemble-specific two-photon optogenetics in the mouse visual cortex to isolate the impact of recurrent activity from external visual input. We found that the spatial arrangement and the visual feature preference of the stimulated ensemble and the neighboring neurons jointly determine the net effect of recurrent activity. Photoactivation of these ensembles drives suppression in all cells beyond 30 µm but uniformly drives activation in closer similarly tuned cells. In nonsimilarly tuned cells, compact, cotuned ensembles drive net suppression, while diffuse, cotuned ensembles drive activation. Computational modeling suggests that highly local recurrent excitatory connectivity and selective convergence onto inhibitory neurons explain these effects. Our findings reveal a straightforward logic in which space and feature preference of cortical ensembles determine their impact on local recurrent activity.

Enhancement and contextual modulation of visuospatial processing by thalamocollicular projections from ventral lateral geniculate nucleus

In the mammalian visual system, the ventral lateral geniculate nucleus (vLGN) of the thalamus receives salient visual input from the retina and sends prominent GABAergic axons to the superior colliculus (SC). However, whether and how vLGN contributes to fundamental visual information processing remains largely unclear. Here, we report in mice that vLGN facilitates visually-guided approaching behavior mediated by the lateral SC and enhances the sensitivity of visual object detection. This can be attributed to the extremely broad spatial integration of vLGN neurons, as reflected in their much lower preferred spatial frequencies and broader spatial receptive fields than SC neurons. Through GABAergic thalamocollicular projections, vLGN specifically exerts prominent surround suppression of visuospatial processing in SC, leading to a fine tuning of SC preferences to higher spatial frequencies and smaller objects in a context-dependent manner. Thus, as an essential component of the central visual processing pathway, vLGN serves to refine and contextually modulate visuospatial processing in SC-mediated visuomotor behaviors via visually-driven long-range feedforward inhibition.

The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations

When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.

A developmental switch between electrical and neuropeptide communication in the ventromedial hypothalamus

Dissecting neural connectivity patterns within local brain regions is an essential step to understanding the function of the brain.¹ Neural microcircuits in brain regions, such as the neocortex and the hippocampus, have been extensively studied.² By contrast, the microcircuit in the hypothalamus remains largely uncharacterized. The hypothalamus is crucial for animals' survival and reproduction.³ Knowledge of how different hypothalamic nuclei coordinate with each other and outside brain regions for hypothalamus-related functions has been significantly advanced.^4-9 Although there are limited studies on the neural microcircuit in the lateral hypothalamus (LHA)^10,11 and the suprachiasmatic nucleus (SCN),^12,13 the patterns of neural microcircuits in most of the given hypothalamic nuclei remain largely unknown. This study applied combinatory approaches to address the local neural circuit pattern in the ventromedial hypothalamus (VMH) and other hypothalamic nuclei. We discovered a unique neural circuit design in the VMH. Neurons in the VMH were electrically coupled at the early postnatal stage like ones in the neocortex.¹⁴ However, unlike neocortical neurons,^14,15 they developed very few chemical synapses after the disappearance of electrical synapses. Instead, VMH neurons communicated with neuropeptides. The similar scarceness of synaptic connectivity found in other hypothalamic nuclei further indicated that the lack of synaptic connections is a unique feature for local neural circuits in most adult hypothalamic nuclei. Thus, our findings provide a solid synaptic basis at the cellular level to understand hypothalamic functions better.

Translaminar recurrence from layer 5 suppresses superficial cortical layers

Information flow in the sensory cortex has been described as a predominantly feedforward sequence with deep layers as the output structure. Although recurrent excitatory projections from layer 5 (L5) to superficial L2/3 have been identified by anatomical and physiological studies, their functional impact on sensory processing remains unclear. Here, we use layer-selective optogenetic manipulations in the primary auditory cortex to demonstrate that feedback inputs from L5 suppress the activity of superficial layers regardless of the arousal level, contrary to the prediction from their excitatory connectivity. This suppressive effect is predominantly mediated by translaminar circuitry through intratelencephalic neurons, with an additional contribution of subcortical projections by pyramidal tract neurons. Furthermore, L5 activation sharpened tone-evoked responses of superficial layers in both frequency and time domains, indicating its impact on cortical spectro-temporal integration. Together, our findings establish a translaminar inhibitory recurrence from deep layers that sharpens feature selectivity in superficial cortical layers.

Sparse balance: Excitatory-inhibitory networks with small bias currents and broadly distributed synaptic weights

Cortical circuits generate excitatory currents that must be cancelled by strong inhibition to assure stability. The resulting excitatory-inhibitory (E-I) balance can generate spontaneous irregular activity but, in standard balanced E-I models, this requires that an extremely strong feedforward bias current be included along with the recurrent excitation and inhibition. The absence of experimental evidence for such large bias currents inspired us to examine an alternative regime that exhibits asynchronous activity without requiring unrealistically large feedforward input. In these networks, irregular spontaneous activity is supported by a continually changing sparse set of neurons. To support this activity, synaptic strengths must be drawn from high-variance distributions. Unlike standard balanced networks, these sparse balance networks exhibit robust nonlinear responses to uniform inputs and non-Gaussian input statistics. Interestingly, the speed, not the size, of synaptic fluctuations dictates the degree of sparsity in the model. In addition to simulations, we provide a mean-field analysis to illustrate the properties of these networks.

Dissection of brain-wide resting-state and functional somatosensory circuits by fMRI with optogenetic silencing

To further advance functional MRI (fMRI)-based brain science, it is critical to dissect fMRI activity at the circuit level. To achieve this goal, we combined brain-wide fMRI with neuronal silencing in well-defined regions. Since focal inactivation suppresses excitatory output to downstream pathways, intact input and suppressed output circuits can be separated. Highly specific cerebral blood volume-weighted fMRI was performed with optogenetic stimulation of local GABAergic neurons in mouse somatosensory regions. Brain-wide spontaneous somatosensory networks were found mostly in ipsilateral cortical and subcortical areas, which differed from the bilateral homotopic connections commonly observed in resting-state fMRI data. The evoked fMRI responses to somatosensory stimulation in regions of the somatosensory network were successfully dissected, allowing the relative contributions of spinothalamic (ST), thalamocortical (TC), corticothalamic (CT), corticocortical (CC) inputs, and local intracortical circuits to be determined. The ventral posterior thalamic nucleus receives ST inputs, while the posterior medial thalamic nucleus receives CT inputs from the primary somatosensory cortex (S1) with TC inputs. The secondary somatosensory cortex (S2) receives mostly direct CC inputs from S1 and a few TC inputs from the ventral posterolateral nucleus. The TC and CC input layers in cortical regions were identified by laminar-specific fMRI responses with a full width at half maximum of <150 µm. Long-range synaptic inputs in cortical areas were amplified approximately twofold by local intracortical circuits, which is consistent with electrophysiological recordings. Overall, whole-brain fMRI with optogenetic inactivation revealed brain-wide, population-based, long-range circuits, which could complement data typically collected in conventional microscopic functional circuit studies.

Distinct neuron populations for simple and compound calls in the primary auditory cortex of awake marmosets

Marmosets are highly social non-human primates that live in families. They exhibit rich vocalization, but the neural basis underlying this complex vocal communication is largely unknown. Here we report the existence of specific neuron populations in marmoset A1 that respond selectively to distinct simple or compound calls made by conspecific marmosets. These neurons were spatially dispersed within A1 but distinct from those responsive to pure tones. Call-selective responses were markedly diminished when individual domains of the call were deleted or the domain sequence was altered, indicating the importance of the global rather than local spectral-temporal properties of the sound. Compound call-selective responses also disappeared when the sequence of the two simple-call components was reversed or their interval was extended beyond 1 s. Light anesthesia largely abolished call-selective responses. Our findings demonstrate extensive inhibitory and facilitatory interactions among call-evoked responses, and provide the basis for further study of circuit mechanisms underlying vocal communication in awake non-human primates.

Inhibition in the auditory cortex

The auditory system provides us with extremely rich and precise information about the outside world. Once a sound reaches our ears, the acoustic information it carries travels from the cochlea all the way to the auditory cortex, where its complexity and nuances are integrated. In the auditory cortex, functional circuits are formed by subpopulations of intermingled excitatory and inhibitory cells. In this review, we discuss recent evidence of the specific contributions of inhibitory neurons in sound processing and integration. We first examine intrinsic properties of three main classes of inhibitory interneurons in the auditory cortex. Then, we describe how inhibition shapes the responsiveness of the auditory cortex to sound. Finally, we discuss how inhibitory interneurons contribute to the sensation and perception of sounds. Altogether, this review points out the crucial role of cortical inhibitory interneurons in integrating information about the context, history, or meaning of a sound. It also highlights open questions to be addressed for increasing our understanding of the staggering complexity leading to the subtlest auditory perception.

What is the dynamical regime of cerebral cortex?

Many studies have shown that the excitation and inhibition received by cortical neurons remain roughly balanced across many conditions. A key question for understanding the dynamical regime of cortex is the nature of this balancing. Theorists have shown that network dynamics can yield systematic cancellation of most of a neuron's excitatory input by inhibition. We review a wide range of evidence pointing to this cancellation occurring in a regime in which the balance is loose, meaning that the net input remaining after cancellation of excitation and inhibition is comparable in size with the factors that cancel, rather than tight, meaning that the net input is very small relative to the canceling factors. This choice of regime has important implications for cortical functional responses, as we describe: loose balance, but not tight balance, can yield many nonlinear population behaviors seen in sensory cortical neurons, allow the presence of correlated variability, and yield decrease of that variability with increasing external stimulus drive as observed across multiple cortical areas.

Stimulus Feature-Specific Control of Layer 2/3 Subthreshold Whisker Responses by Layer 4 in the Mouse Primary Somatosensory Cortex

In the barrel field of the rodent primary somatosensory cortex (S1bf), excitatory cells in layer 2/3 (L2/3) display sparse firing but reliable subthreshold response during whisker stimulation. Subthreshold responses encode specific features of the sensory stimulus, for example, the direction of whisker deflection. According to the canonical model for the flow of sensory information across cortical layers, activity in L2/3 is driven by layer 4 (L4). However, L2/3 cells receive excitatory inputs from other regions, raising the possibility that L4 partially drives L2/3 during whisker stimulation. To test this hypothesis, we combined patch-clamp recordings from L2/3 pyramidal neurons in S1bf with selective optogenetic inhibition of L4 during passive whisker stimulation in both anesthetized and awake head-restrained mice. We found that L4 optogenetic inhibition did not abolish the subthreshold whisker-evoked response nor it affected spontaneous membrane potential fluctuations of L2/3 neurons. However, L4 optogenetic inhibition decreased L2/3 subthreshold responses to whisker deflections in the preferred direction, and it increased L2/3 responses to stimuli in the nonpreferred direction, leading to a change in the direction tuning. Our results contribute to reveal the circuit mechanisms underlying the processing of sensory information in the rodent S1bf.

Phasic Off responses of auditory cortex underlie perception of sound duration

It has been proposed that sound information is separately streamed into onset and offset pathways for parallel processing. However, how offset responses contribute to auditory perception remains unclear. Here, loose-patch and whole-cell recordings in awake mouse primary auditory cortex (A1) reveal that a subset of pyramidal neurons exhibit a transient "Off" response, with its onset tightly time-locked to the sound termination and its frequency tuning similar to that of the transient "On" response. Both responses are characterized by excitation briefly followed by inhibition, with the latter mediated by parvalbumin (PV) inhibitory neurons. Optogenetically manipulating sound-evoked A1 responses at different temporal phases or artificially creating phantom sounds in A1 further reveals that the A1 phasic On and Off responses are critical for perceptual discrimination of sound duration. Our results suggest that perception of sound duration is dependent on precisely encoding its onset and offset timings by phasic On and Off responses.

Sustained Activation of PV+ Interneurons in Core Auditory Cortex Enables Robust Divisive Gain Control for Complex and Naturalistic Stimuli

Sensory cortices must flexibly adapt their operations to internal states and external requirements. Sustained modulation of activity levels in different inhibitory interneuron populations may provide network-level mechanisms for adjustment of sensory cortical processing on behaviorally relevant timescales. However, understanding of the computational roles of inhibitory interneuron modulation has mostly been restricted to effects at short timescales, through the use of phasic optogenetic activation and transient stimuli. Here, we investigated how modulation of inhibitory interneurons affects cortical computation on longer timescales, by using sustained, network-wide optogenetic activation of parvalbumin-positive interneurons (the largest class of cortical inhibitory interneurons) to study modulation of auditory cortical responses to prolonged and naturalistic as well as transient stimuli. We found highly conserved spectral and temporal tuning in auditory cortical neurons, despite a profound reduction in overall network activity. This reduction was predominantly divisive, and consistent across simple, complex, and naturalistic stimuli. A recurrent network model with power-law input-output functions replicated our results. We conclude that modulation of parvalbumin-positive interneurons on timescales typical of sustained neuromodulation may provide a means for robust divisive gain control conserving stimulus representations.

Network dynamics underlying OFF responses in the auditory cortex

Across sensory systems, complex spatio-temporal patterns of neural activity arise following the onset (ON) and offset (OFF) of stimuli. While ON responses have been widely studied, the mechanisms generating OFF responses in cortical areas have so far not been fully elucidated. We examine here the hypothesis that OFF responses are single-cell signatures of recurrent interactions at the network level. To test this hypothesis, we performed population analyses of two-photon calcium recordings in the auditory cortex of awake mice listening to auditory stimuli, and compared them to linear single-cell and network models. While the single-cell model explained some prominent features of the data, it could not capture the structure across stimuli and trials. In contrast, the network model accounted for the low-dimensional organization of population responses and their global structure across stimuli, where distinct stimuli activated mostly orthogonal dimensions in the neural state-space.

Diversity of Receptive Fields and Sideband Inhibition with Complex Thalamocortical and Intracortical Origin in L2/3 of Mouse Primary Auditory Cortex

Receptive fields of primary auditory cortex (A1) neurons show excitatory neuronal frequency preference and diverse inhibitory sidebands. While the frequency preferences of excitatory neurons in local A1 areas can be heterogeneous, those of inhibitory neurons are more homogeneous. To date, the diversity and the origin of inhibitory sidebands in local neuronal populations and the relation between local cellular frequency preference and inhibitory sidebands are unknown. To reveal both excitatory and inhibitory subfields, we presented two-tone and pure tone stimuli while imaging excitatory neurons (Thy1) and two types of inhibitory neurons (parvalbumin and somatostatin) in L2/3 of mice A1. We classified neurons into six classes based on frequency response area (FRA) shapes and sideband inhibition depended both on FRA shapes and cell types. Sideband inhibition showed higher local heterogeneity than frequency tuning, suggesting that sideband inhibition originates from diverse sources of local and distant neurons. Two-tone interactions depended on neuron subclasses with excitatory neurons showing the most nonlinearity. Onset and offset neurons showed dissimilar spectral integration, suggesting differing circuits processing sound onset and offset. These results suggest that excitatory neurons integrate complex and nonuniform inhibitory input. Thalamocortical terminals also exhibited sideband inhibition, but with different properties from those of cortical neurons. Thus, some components of sideband inhibition are inherited from thalamocortical inputs and are further modified by converging intracortical circuits. The combined heterogeneity of frequency tuning and diverse sideband inhibition facilitates complex spectral shape encoding and allows for rapid and extensive plasticity.SIGNIFICANCE STATEMENT Sensory systems recognize and differentiate between different stimuli through selectivity for different features. Sideband inhibition serves as an important mechanism to sharpen stimulus selectivity, but its cortical mechanisms are not entirely resolved. We imaged pyramidal neurons and two common classes of interneurons suggested to mediate sideband inhibition (parvalbumin and somatostatin positive) in the auditory cortex and inferred their inhibitory sidebands. We observed a higher degree of variability in the inhibitory sideband than in the local frequency tuning, which cannot be predicted from the relative high homogeneity of responses by inhibitory interneurons. This suggests that cortical sideband inhibition is nonuniform and likely results from a complex interplay between existing functional inhibition in the feedforward input and cortical refinement.

Recurrent network dynamics shape direction selectivity in primary auditory cortex

Detecting the direction of frequency modulation (FM) is essential for vocal communication in both animals and humans. Direction-selective firing of neurons in the primary auditory cortex (A1) has been classically attributed to temporal offsets between feedforward excitatory and inhibitory inputs. However, it remains unclear how cortical recurrent circuitry contributes to this computation. Here, we used two-photon calcium imaging and whole-cell recordings in awake mice to demonstrate that direction selectivity is not caused by temporal offsets between synaptic currents, but by an asymmetry in total synaptic charge between preferred and non-preferred directions. Inactivation of cortical somatostatin-expressing interneurons (SOM cells) reduced direction selectivity, revealing its cortical contribution. Our theoretical models showed that charge asymmetry arises due to broad spatial topography of SOM cell-mediated inhibition which regulates signal amplification in strongly recurrent circuitry. Together, our findings reveal a major contribution of recurrent network dynamics in shaping cortical tuning to behaviorally relevant complex sounds.

In Vivo Patch-Clamp Studies

Intact and functioning brain enables quantification of neural activities directly associated with real world such as visual and auditory information. In vivo patch clamp can record different types of neuronal activity, such as spiking responses, membrane potential dynamics, and synaptic currents (e.g., EPSC, IPSC) in either anesthetized or awake or even free moving animals. Researchers can not only directly measure these neuronal activities but also quantify and unravel synaptic contribution from excitatory and inhibitory circuits. Here, we describe the requirements and standard protocols to perform in vivo patch clamp recording. The key factors of successful recording based on references and our experiences are also provided.

Inhibitory stabilization and cortical computation

Neuronal networks with strong recurrent connectivity provide the brain with a powerful means to perform complex computational tasks. However, high-gain excitatory networks are susceptible to instability, which can lead to runaway activity, as manifested in pathological regimes such as epilepsy. Inhibitory stabilization offers a dynamic, fast and flexible compensatory mechanism to balance otherwise unstable networks, thus enabling the brain to operate in its most efficient regimes. Here we review recent experimental evidence for the presence of such inhibition-stabilized dynamics in the brain and discuss their consequences for cortical computation. We show how the study of inhibition-stabilized networks in the brain has been facilitated by recent advances in the technological toolbox and perturbative techniques, as well as a concomitant development of biologically realistic computational models. By outlining future avenues, we suggest that inhibitory stabilization can offer an exemplary case of how experimental neuroscience can progress in tandem with technology and theory to advance our understanding of the brain.

Variation of connectivity across exemplar sensory and associative thalamocortical loops in the mouse

The thalamus engages in sensation, action, and cognition, but the structure underlying these functions is poorly understood. Thalamic innervation of associative cortex targets several interneuron types, modulating dynamics and influencing plasticity. Is this structure-function relationship distinct from that of sensory thalamocortical systems? Here, we systematically compared function and structure across a sensory and an associative thalamocortical loop in the mouse. Enhancing excitability of mediodorsal thalamus, an associative structure, resulted in prefrontal activity dominated by inhibition. Equivalent enhancement of medial geniculate excitability robustly drove auditory cortical excitation. Structurally, geniculate axons innervated excitatory cortical targets in a preferential manner and with larger synaptic terminals, providing a putative explanation for functional divergence. The two thalamic circuits also had distinct input patterns, with mediodorsal thalamus receiving innervation from a diverse set of cortical areas. Altogether, our findings contribute to the emerging view of functional diversity across thalamic microcircuits and its structural basis.

Sparse Representation in Awake Auditory Cortex: Cell-type Dependence, Synaptic Mechanisms, Developmental Emergence, and Modulation

Sparse representation is considered an important coding strategy for cortical processing in various sensory modalities. It remains unclear how cortical sparseness arises and is being regulated. Here, unbiased recordings from primary auditory cortex of awake adult mice revealed salient sparseness in layer (L)2/3, with a majority of excitatory neurons exhibiting no increased spiking in response to each of sound types tested. Sparse representation was not observed in parvalbumin (PV) inhibitory neurons. The nonresponding neurons did receive auditory-evoked synaptic inputs, marked by weaker excitation and lower excitation/inhibition (E/I) ratios than responding cells. Sparse representation arises during development in an experience-dependent manner, accompanied by differential changes of excitatory input strength and a transition from unimodal to bimodal distribution of E/I ratios. Sparseness level could be reduced by suppressing PV or L1 inhibitory neurons. Thus, sparse representation may be dynamically regulated via modulating E/I balance, optimizing cortical representation of the external sensory world.

Synaptic Mechanisms for Bandwidth Tuning in Awake Mouse Primary Auditory Cortex

Spatial size tuning in the visual cortex has been considered as an important neuronal functional property for sensory perception. However, an analogous mechanism in the auditory system has remained controversial. In the present study, cell-attached recordings in the primary auditory cortex (A1) of awake mice revealed that excitatory neurons can be categorized into three types according to their bandwidth tuning profiles in response to band-passed noise (BPN) stimuli: nonmonotonic (NM), flat, and monotonic, with the latter two considered as non-tuned for bandwidth. The prevalence of bandwidth-tuned (i.e., NM) neurons increases significantly from layer 4 to layer 2/3. With sequential cell-attached and whole-cell voltage-clamp recordings from the same neurons, we found that the bandwidth preference of excitatory neurons is largely determined by the excitatory synaptic input they receive, and that the bandwidth selectivity is further enhanced by flatly tuned inhibition observed in all cells. The latter can be attributed at least partially to the flat tuning of parvalbumin inhibitory neurons. The tuning of auditory cortical neurons for bandwidth of BPN may contribute to the processing of complex sounds.

Organoids, Assembloids, and Novel Biotechnology: Steps Forward in Developmental and Disease-Related Neuroscience

In neuroscience research, the efforts to find the model through which we can mimic the in vivo microenvironment of a developing or defective brain have been everlasting. While model organisms are used for over a hundred years, many more methods have been introduced with immortalized or primary cell lines and later induced pluripotent stem cells and organoids to be some of these. As the use of organoids becomes more and more common by many laboratories in biology and neuroscience in particular, it is crucial to deeper understand the challenges and possible pitfalls of their application in research, many of which can be surpassed with the support of state-of-the art bioengineering solutions. In this review, after a brief chronicle of the path to the discovery of organoids, we focus on the latest approaches to study neuroscience related topics with organoids, such as the use of assembloids, CRISPR technology, patch-clamp and optogenetics techniques and discuss how modern 3-dimensional biomaterials, miniaturized bioreactors and microfluidic chips can help to overcome the disadvantages of their use.

Network control through coordinated inhibition

Coordinated excitatory and inhibitory activity is required for proper brain functioning. Recent computational and experimental studies have demonstrated that activity patterns in recurrent cortical networks are dominated by inhibition. Whereas previous studies have suggested that inhibitory plasticity is important for homeostatic control, this new framework puts inhibition in the driver's seat. Complex neuronal networks in the brain comprise many configurations in parallel, controlled by external and internal 'switches'. Context-dependent modulation and plasticity of inhibitory connections play a key role in memory and learning. It is therefore important to realize that synaptic plasticity is often multisynaptic and that a proper balance between excitation and inhibition is not fixed, but depends on context and activity level.

Interhemispheric Callosal Projections Sharpen Frequency Tuning and Enforce Response Fidelity in Primary Auditory Cortex

Sensory cortical areas receive glutamatergic callosal projections that link information processing between brain hemispheres. In primary auditory cortex (A1), ipsilateral principal cells from a particular tonotopic region project to neurons in matching frequency space of the contralateral cortex. However, the role of interhemispheric projections in shaping cortical responses to sound and frequency tuning in awake animals is unclear. Here, we use translaminar single-unit recordings and optogenetic approaches to probe how callosal inputs modulate spontaneous and tone-evoked activity in A1 of awake mice. Brief activation of callosal inputs drove either short-latency increases or decreases in firing of individual neurons. Across all cortical layers, the majority of responsive regular spiking (RS) cells received short-latency inhibition, whereas fast spiking (FS) cells were almost exclusively excited. Consistent with the callosal-evoked increases in FS cell activity in vivo, brain slice recordings confirmed that parvalbumin (PV)-expressing cells received stronger callosal input than pyramidal cells or other interneuron subtypes. Acute in vivo silencing of the contralateral cortex generally increased spontaneous firing across cortical layers and linearly transformed responses to pure tones via both divisive and additive operations. The net effect was a decrease in signal-to-noise ratio for evoked responses and a broadening of frequency tuning curves. Together, these results suggest that callosal input regulates both the salience and tuning sharpness of tone responses in A1 via PV cell-mediated feedforward inhibition.

Parallel Processing of Sound Dynamics across Mouse Auditory Cortex via Spatially Patterned Thalamic Inputs and Distinct Areal Intracortical Circuits

Natural sounds have rich spectrotemporal dynamics. Spectral information is spatially represented in the auditory cortex (ACX) via large-scale maps. However, the representation of temporal information, e.g., sound offset, is unclear. We perform multiscale imaging of neuronal and thalamic activity evoked by sound onset and offset in awake mouse ACX. ACX areas differed in onset responses (On-Rs) and offset responses (Off-Rs). Most excitatory L2/3 neurons show either On-Rs or Off-Rs, and ACX areas are characterized by differing fractions of On and Off-R neurons. Somatostatin and parvalbumin interneurons show distinct temporal dynamics, potentially amplifying Off-Rs. Functional network analysis shows that ACX areas contain distinct parallel onset and offset networks. Thalamic (MGB) terminals show either On-Rs or Off-Rs, indicating a thalamic origin of On and Off-R pathways. Thus, ACX areas spatially represent temporal features, and this representation is created by spatial convergence and co-activation of distinct MGB inputs and is refined by specific intracortical connectivity.

Subthreshold Activity Underlying the Diversity and Selectivity of the Primary Auditory Cortex Studied by Intracellular Recordings in Awake Marmosets

Extracellular recording studies have revealed diverse and selective neural responses in the primary auditory cortex (A1) of awake animals. However, we have limited knowledge on subthreshold events that give rise to these responses, especially in non-human primates, as intracellular recordings in awake animals pose substantial technical challenges. We developed a novel intracellular recording technique in awake marmosets to systematically study subthreshold activity of A1 neurons that underlies their diverse and selective spiking responses. Our findings showed that in contrast to predominantly transient depolarization observed in A1 of anesthetized animals, both transient and sustained depolarization (during or beyond the stimulus period) were observed. Comparing with spiking responses, subthreshold responses were often longer lasting in duration and more broadly tuned in frequency, and showed narrower intensity tuning in non-monotonic neurons and lower response threshold in monotonic neurons. These observations demonstrated the enhancement of stimulus selectivity from subthreshold to spiking responses in individual A1 neurons. Furthermore, A1 neurons classified as regular- or fast-spiking subpopulation based on their spike shapes exhibited distinct response properties in frequency and intensity domains. These findings provide valuable insights into cortical integration and transformation of auditory information at the cellular level in auditory cortex of awake non-human primates.

Temporary Visual Deprivation Causes Decorrelation of Spatiotemporal Population Responses in Adult Mouse Auditory Cortex

Although within-modality sensory plasticity is limited to early developmental periods, cross-modal plasticity can occur even in adults. In vivo electrophysiological studies have shown that transient visual deprivation (dark exposure, DE) in adult mice improves the frequency selectivity and discrimination of neurons in thalamorecipient layer 4 (L4) of primary auditory cortex (A1). Since sound information is processed hierarchically in A1 by populations of neurons, we investigated whether DE alters network activity in A1 L4 and layer 2/3 (L2/3). We examined neuronal populations in both L4 and L2/3 using in vivo two-photon calcium (Ca²⁺) imaging of transgenic mice expressing GCaMP6s. We find that one week of DE in adult mice increased the sound evoked responses and frequency selectivity of both L4 and L2/3 neurons. Moreover, after DE the frequency representation changed with L4 and L2/3 showing a reduced representation of cells with best frequencies (BFs) between 8 and 16 kHz and an increased representation of cells with BFs above 32 kHz. Cells in L4 and L2/3 showed decreased pairwise signal correlations (SCs) consistent with sharper tuning curves. The decreases in SCs were larger in L4 than in L2/3. The decreased pairwise correlations indicate a sparsification of A1 responses to tonal stimuli. Thus, cross-modal experience in adults can both alter the sound-evoked responses of A1 neurons and change activity correlations within A1 potentially enhancing the encoding of auditory stimuli.

Spatial Asymmetry and Short-Term Suppression Underlie Direction Selectivity of Synaptic Excitation in the Mouse Visual Cortex

Direction selectivity (DS) of neuronal responses is fundamental for motion detection. With in vivo whole-cell voltage-clamp recordings from layer (L)4 neurons in the mouse visual cortex, we observed a strong correlation between DS and spatial asymmetry in the distribution of excitatory input strengths. This raises an interesting possibility that the latter may contribute to DS. The preferred direction of excitatory input was found from the stronger to weaker side of its spatial receptive field. A simple linear summation of asymmetrically distributed excitatory responses to stationary flash stimuli however failed to predict the correct directionality: it at best resulted in weak DS with preferred direction opposite to what was observed experimentally. Further studies with sequential 2 flash-bar stimulation revealed a short-term suppression of excitatory input evoked by the late bar. More importantly, the level of the suppression positively correlated with the relative amplitude of the early-bar response. Implementing this amplitude-dependent suppressive interaction can successfully predict DS of excitatory input. Our results suggest that via nonlinear temporal interactions, the spatial asymmetry can be transformed into differential temporal integration of inputs under opposite directional movements. This mechanism may contribute to the DS of excitatory inputs to L4 neurons.

Cortical Circuits of Callosal GABAergic Neurons

Anatomical studies have shown that the majority of callosal axons are glutamatergic. However, a small proportion of callosal axons are also immunoreactive for glutamic acid decarboxylase, an enzyme required for gamma-aminobutyric acid (GABA) synthesis and a specific marker for GABAergic neurons. Here, we test the hypothesis that corticocortical parvalbumin-expressing (CC-Parv) neurons connect the two hemispheres of multiple cortical areas, project through the corpus callosum, and are a functional part of the local cortical circuit. Our investigation of this hypothesis takes advantage of viral tracing and optogenetics to determine the anatomical and electrophysiological properties of CC-Parv neurons of the mouse auditory, visual, and motor cortices. We found a direct inhibitory pathway made up of parvalbumin-expressing (Parv) neurons which connects corresponding cortical areas (CC-Parv neurons → contralateral cortex). Like other Parv cortical neurons, these neurons provide local inhibition onto nearby pyramidal neurons and receive thalamocortical input. These results demonstrate a previously unknown long-range inhibitory circuit arising from a genetically defined type of GABAergic neuron that is engaged in interhemispheric communication.

Reorganization of Recurrent Layer 5 Corticospinal Networks Following Adult Motor Training

Recurrent synaptic connections between neighboring neurons are a key feature of mammalian cortex, accounting for the vast majority of cortical inputs. Although computational models indicate that reorganization of recurrent connectivity is a primary driver of experience-dependent cortical tuning, the true biological features of recurrent network plasticity are not well identified. Indeed, whether rewiring of connections between cortical neurons occurs during behavioral training, as is widely predicted, remains unknown. Here, we probe M1 recurrent circuits following motor training in adult male rats and find robust synaptic reorganization among functionally related layer 5 neurons, resulting in a 2.5-fold increase in recurrent connection probability. This reorganization is specific to the neuronal subpopulation most relevant for executing the trained motor skill, and behavioral performance was impaired following targeted molecular inhibition of this subpopulation. In contrast, recurrent connectivity is unaffected among neighboring layer 5 neurons largely unrelated to the trained behavior. Training-related corticospinal cells also express increased excitability following training. These findings establish the presence of selective modifications in recurrent cortical networks in adulthood following training.SIGNIFICANCE STATEMENT Recurrent synaptic connections between neighboring neurons are characteristic of cortical architecture, and modifications to these circuits are thought to underlie in part learning in the adult brain. We now show that there are robust changes in recurrent connections in the rat motor cortex upon training on a novel motor task. Motor training results in a 2.5-fold increase in recurrent connectivity, but only within the neuronal subpopulation most relevant for executing the new motor behavior; recurrent connectivity is unaffected among adjoining neurons that do not execute the trained behavior. These findings demonstrate selective reorganization of recurrent synaptic connections in the adult neocortex following novel motor experience, and illuminate fundamental properties of cortical function and plasticity.

Selective Strengthening of Intracortical Excitatory Input Leads to Receptive Field Refinement during Auditory Cortical Development

In the primary auditory cortex (A1) of rats, refinement of excitatory input to layer (L)4 neurons contributes to the sharpening of their frequency selectivity during postnatal development. L4 neurons receive both feedforward thalamocortical and recurrent intracortical inputs, but how potential developmental changes of each component can account for the sharpening of excitatory input tuning remains unclear. By combining in vivo whole-cell recording and pharmacological silencing of cortical spiking in young rats of both sexes, we examined developmental changes at three hierarchical stages: output of auditory thalamic neurons, thalamocortical input and recurrent excitatory input to an A1 L4 neuron. In the thalamus, the tonotopic map matured with an expanded range of frequency representations, while the frequency tuning of output responses was unchanged. On the other hand, the tuning shape of both thalamocortical and intracortical excitatory inputs to a L4 neuron became sharpened. In particular, the intracortical input became better tuned than thalamocortical excitation. Moreover, the weight of intracortical excitation around the optimal frequency was selectively strengthened, resulting in a dominant role of intracortical excitation in defining the total excitatory input tuning. Our modeling work further demonstrates that the frequency-selective strengthening of local recurrent excitatory connections plays a major role in the refinement of excitatory input tuning of L4 neurons.SIGNIFICANCE STATEMENT During postnatal development, sensory cortex undergoes functional refinement, through which the size of sensory receptive field is reduced. In the rat primary auditory cortex, such refinement in layer (L)4 is mainly attributed to improved selectivity of excitatory input a L4 neuron receives. In this study, we further examined three stages along the hierarchical neural pathway where excitatory input refinement might occur. We found that developmental refinement takes place at both thalamocortical and intracortical circuit levels, but not at the thalamic output level. Together with modeling results, we revealed that the optimal-frequency-selective strengthening of intracortical excitation plays a dominant role in the refinement of excitatory input tuning.

Fine Control of Sound Frequency Tuning and Frequency Discrimination Acuity by Synaptic Zinc Signaling in Mouse Auditory Cortex

Neurons in the auditory cortex are tuned to specific ranges of sound frequencies. Although the cellular and network mechanisms underlying neuronal sound frequency selectivity are well studied and reflect the interplay of thalamocortical and intracortical excitatory inputs and further refinement by cortical inhibition, the precise synaptic signaling mechanisms remain less understood. To gain further understanding on these mechanisms and their effects on sound-driven behavior, we used in vivo imaging as well as behavioral approaches in awake and behaving female and male mice. We discovered that synaptic zinc, a modulator of neurotransmission and responsiveness to sound, sharpened the sound frequency tuning of principal and parvalbumin-expressing neurons and widened the sound frequency tuning of somatostatin-expressing inhibitory neurons in layer 2/3 of the primary auditory cortex. In the absence of cortical synaptic zinc, mice exhibited reduced acuity for detecting changes in sound frequencies. Together, our results reveal that cell-type-specific effects of zinc contribute to cortical sound frequency tuning and enhance acuity for sound frequency discrimination.SIGNIFICANCE STATEMENT Neuronal tuning to specific features of sensory stimuli is a fundamental property of cortical sensory processing that advantageously supports behavior. Despite the established roles of synaptic thalamocortical and intracortical excitation and inhibition in cortical tuning, the precise synaptic signaling mechanisms remain unknown. Here, we investigated these mechanisms in the mouse auditory cortex. We discovered a previously unknown signaling mechanism linking synaptic zinc signaling with cell-specific cortical tuning and enhancement in sound frequency discrimination acuity. Given the abundance of synaptic zinc in all sensory cortices, this newly discovered interaction between synaptic zinc and cortical tuning can provide a general mechanism for modulating neuronal stimulus specificity and sensory-driven behavior.

Synaptic topography - Converging connections and emerging function

Brain circuits are constituted of individual neurons that are interconnected with a vast array of synapses. In order to understand how brain function emerges from this complex synaptic network, immense efforts have been made to trace the synaptic topography, i.e. arrangement of synaptic connections, of the network. In addition to anatomically elaborating the synaptic layout at multiple levels across brain regions, recent studies have attempted to elucidate the fundamental wiring principles that govern neural information processing in the brain, establishing a link between anatomy and function. In this review, I will discuss recent discoveries on the topographical organization of synaptic connections at the cell-to-cell and subcellular levels in the cortex and hippocampus. Accumulating evidence leads us to acknowledge the highly structured, non-random synaptic connectivity that emerges together with sensory feature preferences of neurons and synchronous neuronal activity.

Membrane Potential Correlates of Network Decorrelation and Improved SNR by Cholinergic Activation in the Somatosensory Cortex

The nucleus basalis (NB) projects cholinergic axons to the cortex, where they play a major role in arousal, attention, and learning. Cholinergic inputs shift cortical dynamics from synchronous to asynchronous and improve the signal-to-noise ratio (SNR) of sensory responses. However, the underlying mechanisms of these changes remain unclear. Using simultaneous extracellular and whole-cell patch recordings in layer 4 of the mouse barrel cortex, we show that electrical or optogenetic activation of the cholinergic system has a differential effect on ongoing and sensory evoked activities. Cholinergic activation profoundly reduced the large spontaneous fluctuations in membrane potential and decorrelated ongoing activity. However, NB stimulation had no effect on the response to whisker stimulation or on signal correlations. These effects of cholinergic activation provide a unified explanation for the increased SNR of sensory response and for the reduction in noise correlations and explain the shift into the desynchronized cortical state, which are the hallmarks of arousal and attention.SIGNIFICANCE STATEMENT Attention increases the signal-to-noise ratio (SNR) of cortical sensory response, which may reflect either reduction in background firing rate or increased sensory response. Extracellular recordings showed that attention also reduces the correlation in network activity. These effects are partially mediated by cholinergic axons from the nucleus basalis projecting to the entire cortex. To reveal the cellular and synaptic correlates of these cholinergic effects, we performed simultaneous intracellular and LFP recordings in the somatosensory cortex. Global or local cholinergic activation increased the SNR of sensory response mainly by reducing the rate and amplitude of background synaptic activity and also reduced network correlations. Therefore, coding of sensory information is enhanced by the cholinergic system mainly due to a reduction in spontaneous activity.

Specific excitatory connectivity for feature integration in mouse primary visual cortex

Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a 'like-to-like' scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a 'feature binding' scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.

Cornu Ammonis Regions-Antecedents of Cortical Layers?

Studying neocortex and hippocampus in parallel, we are struck by the similarities. All three to four layered allocortices and the six layered mammalian neocortex arise in the pallium. All receive and integrate multiple cortical and subcortical inputs, provide multiple outputs and include an array of neuronal classes. During development, each cell positions itself to sample appropriate local and distant inputs and to innervate appropriate targets. Simpler cortices had already solved the need to transform multiple coincident inputs into serviceable outputs before neocortex appeared in mammals. Why then do phylogenetically more recent cortices need multiple pyramidal cell layers? A simple answer is that more neurones can compute more complex functions. The dentate gyrus and hippocampal CA regions-which might be seen as hippocampal antecedents of neocortical layers-lie side by side, albeit around a tight bend. Were the millions of cells of rat neocortex arranged in like fashion, the surface area of the CA pyramidal cell layers would be some 40 times larger. Even if evolution had managed to fold this immense sheet into the space available, the distances between neurones that needed to be synaptically connected would be huge and to maintain the speed of information transfer, massive, myelinated fiber tracts would be needed. How much more practical to stack the "cells that fire and wire together" into narrow columns, while retaining the mechanisms underlying the extraordinary precision with which circuits form. This demonstrably efficient arrangement presents us with challenges, however, not the least being to categorize the baffling array of neuronal subtypes in each of five "pyramidal layers." If we imagine the puzzle posed by this bewildering jumble of apical dendrites, basal dendrites and axons, from many different pyramidal and interneuronal classes, that is encountered by a late-arriving interneurone insinuating itself into a functional circuit, we can perhaps begin to understand why definitive classification, covering every aspect of each neurone's structure and function, is such a challenge. Here, we summarize and compare the development of these two cortices, the properties of their neurones, the circuits they form and the ordered, unidirectional flow of information from one hippocampal region, or one neocortical layer, to another.

Thalamic input to auditory cortex is locally heterogeneous but globally tonotopic

Topographic representation of the receptor surface is a fundamental feature of sensory cortical organization. This is imparted by the thalamus, which relays information from the periphery to the cortex. To better understand the rules governing thalamocortical connectivity and the origin of cortical maps, we used in vivo two-photon calcium imaging to characterize the properties of thalamic axons innervating different layers of mouse auditory cortex. Although tonotopically organized at a global level, we found that the frequency selectivity of individual thalamocortical axons is surprisingly heterogeneous, even in layers 3b/4 of the primary cortical areas, where the thalamic input is dominated by the lemniscal projection. We also show that thalamocortical input to layer 1 includes collaterals from axons innervating layers 3b/4 and is largely in register with the main input targeting those layers. Such locally varied thalamocortical projections may be useful in enabling rapid contextual modulation of cortical frequency representations.

Cell-specific gain modulation by synaptically released zinc in cortical circuits of audition

In many excitatory synapses, mobile zinc is found within glutamatergic vesicles and is coreleased with glutamate. Ex vivo studies established that synaptically released (synaptic) zinc inhibits excitatory neurotransmission at lower frequencies of synaptic activity but enhances steady state synaptic responses during higher frequencies of activity. However, it remains unknown how synaptic zinc affects neuronal processing in vivo. Here, we imaged the sound-evoked neuronal activity of the primary auditory cortex in awake mice. We discovered that synaptic zinc enhanced the gain of sound-evoked responses in CaMKII-expressing principal neurons, but it reduced the gain of parvalbumin- and somatostatin-expressing interneurons. This modulation was sound intensity-dependent and, in part, NMDA receptor-independent. By establishing a previously unknown link between synaptic zinc and gain control of auditory cortical processing, our findings advance understanding about cortical synaptic mechanisms and create a new framework for approaching and interpreting the role of the auditory cortex in sound processing.

Network-Level Control of Frequency Tuning in Auditory Cortex

Lateral inhibition is a fundamental circuit operation that sharpens the tuning properties of cortical neurons. This operation is classically attributed to an increase in GABAergic synaptic input triggered by non-preferred stimuli. Here we use in vivo whole-cell recording and two-photon Ca²⁺ imaging in awake mice to show that lateral inhibition shapes frequency tuning in primary auditory cortex via an unconventional mechanism: non-preferred tones suppress both excitatory and inhibitory synaptic inputs onto layer 2/3 cells ("network suppression"). Moreover, optogenetic inactivation of inhibitory interneurons elicits a paradoxical increase in inhibitory synaptic input. These results indicate that GABAergic interneurons regulate cortical activity indirectly via the suppression of recurrent excitation. Furthermore, the network suppression underlying lateral inhibition was blocked by inactivation of somatostatin-expressing interneurons (SOM cells), but not parvalbumin-expressing interneurons (PV cells). Together, these findings reveal that SOM cells govern lateral inhibition and control cortical frequency tuning through the regulation of reverberating recurrent circuits.

A Mechanistic Link from GABA to Cortical Architecture and Perception

Understanding both the organization of the human cortex and its relation to the performance of distinct functions is fundamental in neuroscience. The primary sensory cortices display topographic organization, whereby receptive fields follow a characteristic pattern, from tonotopy to retinotopy to somatotopy [1]. GABAergic signaling is vital to the maintenance of cortical receptive fields [2]; however, it is unclear how this fine-grain inhibition relates to measurable patterns of perception [3, 4]. Based on perceptual changes following perturbation of the GABAergic system, it is conceivable that the resting level of cortical GABAergic tone directly relates to the spatial specificity of activation in response to a given input [5, 6, 7]. The specificity of cortical activation can be considered in terms of cortical tuning: greater cortical tuning yields more localized recruitment of cortical territory in response to a given input. We applied a combination of fMRI, MR spectroscopy, and psychophysics to substantiate the link between the cortical neurochemical milieu, the tuning of cortical activity, and variability in perceptual acuity, using human somatosensory cortex as a model. We provide data that explain human perceptual acuity in terms of both the underlying cellular and metabolic processes. Specifically, higher concentrations of sensorimotor GABA are associated with more selective cortical tuning, which in turn is associated with enhanced perception. These results show anatomical and neurochemical specificity and are replicated in an independent cohort. The mechanistic link from neurochemistry to perception provides a vital step in understanding population variability in sensory behavior, informing metabolic therapeutic interventions to restore perceptual abilities clinically.

•

GABAergic tone correlates with perceptual acuity in the human somatosensory system

•

This relationship is mediated by the tuning of activity in somatosensory cortex

•

We explain perceptual acuity via the underlying cellular and metabolic processes

Diversity in Excitation-Inhibition Mismatch Underlies Local Functional Heterogeneity in the Rat Auditory Cortex

Cortical neurons are heterogeneous in their functional properties. This heterogeneity is fundamental for the processing of different features of sensory information. However, functional diversity within a local group of neurons is poorly understood. Here, we demonstrate that neighboring cortical neurons in layer 5 but not those of layer 4 of the rat anterior auditory field (AAF) exhibited a surprisingly high level of diversity in tonal receptive fields. In vivo whole-cell voltage-clamp recordings revealed that the diversity of frequency representation was due to a spectral mismatch between synaptic excitation and inhibition to varying degrees. The spectral distribution of excitation was skewed at different levels, whereas inhibition was homogeneous and non-skewed, similar to the summed spiking activity of local neuronal ensembles, which further enhanced diversity. Our results indicate that AAF in the auditory cortex is involved in processing auditory information in a highly refined manner that is important for complex pattern recognition.

Intracortical Circuits in Thalamorecipient Layers of Auditory Cortex Refine after Visual Deprivation

Sensory cortices do not work in isolation. The functional responses of neurons in primary sensory cortices can be affected by activity from other modalities. For example, short-term visual deprivations, or dark exposure (DE), leads to enhanced neuronal responses and frequency selectivity to sounds in layer 4 (L4) of primary auditory cortex (A1). Circuit changes within A1 likely underlie these changes. Prior studies revealed that DE enhanced thalamocortical transmission to L4 in A1. Because the frequency selectivity of L4 neurons is determined by both thalamocortical and intracortical inputs, changes in intralaminar circuits to L4 neurons might also contribute to improved sound responses. We thus investigated in mouse A1 whether intracortical circuits to L4 cells changed after DE. Using in vitro whole-cell patch recordings in thalamocortical slices from mouse auditory cortex, we show that DE can lead to refinement of interlaminar excitatory as well as inhibitory connections from L2/3 to L4 cells, manifested as a weakening of these connections. The circuit refinement is present along the tonotopic axis, indicating reduced integration along the tonotopic axis. Thus, cross-modal influences may alter the spectral and temporal processing of sensory stimuli in multiple cortical layers by refinement of thalamocortical and intracortical circuits.

Stimulus-specific adaptation in a recurrent network model of primary auditory cortex

Stimulus-specific adaptation (SSA) occurs when neurons decrease their responses to frequently-presented (standard) stimuli but not, or not as much, to other, rare (deviant) stimuli. SSA is present in all mammalian species in which it has been tested as well as in birds. SSA confers short-term memory to neuronal responses, and may lie upstream of the generation of mismatch negativity (MMN), an important human event-related potential. Previously published models of SSA mostly rely on synaptic depression of the feedforward, thalamocortical input. Here we study SSA in a recurrent neural network model of primary auditory cortex. When the recurrent, intracortical synapses display synaptic depression, the network generates population spikes (PSs). SSA occurs in this network when deviants elicit a PS but standards do not, and we demarcate the regions in parameter space that allow SSA. While SSA based on PSs does not require feedforward depression, we identify feedforward depression as a mechanism for expanding the range of parameters that support SSA. We provide predictions for experiments that could help differentiate between SSA due to synaptic depression of feedforward connections and SSA due to synaptic depression of recurrent connections. Similar to experimental data, the magnitude of SSA in the model depends on the frequency difference between deviant and standard, probability of the deviant, inter-stimulus interval and input amplitude. In contrast to models based on feedforward depression, our model shows true deviance sensitivity as found in experiments.

Micro-connectomics: probing the organization of neuronal networks at the cellular scale

Defining the organizational principles of neuronal networks at the cellular scale, or micro-connectomics, is a key challenge of modern neuroscience. In this Review, we focus on graph theoretical parameters of micro-connectome topology, often informed by economical principles that conceptually originated with Ramón y Cajal's conservation laws. First, we summarize results from studies in intact small organisms and in samples from larger nervous systems. We then evaluate the evidence for an economical trade-off between biological cost and functional value in the organization of neuronal networks. Various results suggest that many aspects of neuronal network organization are indeed the outcome of competition between these two fundamental selection pressures.