The tuning of tuning: How adaptation influences single cell information transfer.

Sensory neurons reconstruct the world from action potentials (spikes) impinging on them. To effectively transfer information about the stimulus to the next processing level, a neuron needs to be able to adapt its working range to the properties of the stimulus. Here, we focus on the intrinsic neural properties that influence information transfer in cortical neurons and how tightly their properties need to be tuned to the stimulus statistics for them to be effective. We start by measuring the intrinsic information encoding properties of putative excitatory and inhibitory neurons in L2/3 of the mouse barrel cortex. Excitatory neurons show high thresholds and strong adaptation, making them fire sparsely and resulting in a strong compression of information, whereas inhibitory neurons that favour fast spiking transfer more information. Next, we turn to computational modelling and ask how two properties influence information transfer: 1) spike-frequency adaptation and 2) the shape of the IV-curve. We find that a subthreshold (but not threshold) adaptation, the 'h-current', and a properly tuned leak conductance can increase the information transfer of a neuron, whereas threshold adaptation can increase its working range. Finally, we verify the effect of the IV-curve slope in our experimental recordings and show that excitatory neurons form a more heterogeneous population than inhibitory neurons. These relationships between intrinsic neural features and neural coding that had not been quantified before will aid computational, theoretical and systems neuroscientists in understanding how neuronal populations can alter their coding properties, such as through the impact of neuromodulators. Why the variability of intrinsic properties of excitatory neurons is larger than that of inhibitory ones is an exciting question, for which future research is needed.

Prominent Inhibitory Projections Guide Sensorimotor Computation: An Invertebrate Perspective.

From single-cell organisms to complex neural networks, all evolved to provide control solutions to generate context- and goal-specific actions. Neural circuits performing sensorimotor computation to drive navigation employ inhibitory control as a gating mechanism as they hierarchically transform (multi)sensory information into motor actions. Here, the focus is on this literature to critically discuss the proposition that prominent inhibitory projections form sensorimotor circuits. After reviewing the neural circuits of navigation across various invertebrate species, it is argued that with increased neural circuit complexity and the emergence of parallel computations, inhibitory circuits acquire new functions. The contribution of inhibitory neurotransmission for navigation goes beyond shaping the communication that drives motor neurons, and instead includes encoding of emergent sensorimotor representations. A mechanistic understanding of the neural circuits performing sensorimotor computations in invertebrates will unravel the minimum circuit requirements driving adaptive navigation.

Reduced Inhibition within Layer IV of Sert Knockout Rat Barrel Cortex is Associated with Faster Sensory Integration.

Neural activity is essential for the maturation of sensory systems. In the rodent primary somatosensory cortex (S1), high extracellular serotonin (5-HT) levels during development impair neural transmission between the thalamus and cortical input layer IV (LIV). Rodent models of impaired 5-HT transporter (SERT) function show disruption in their topological organization of S1 and in the expression of activity-regulated genes essential for inhibitory cortical network formation. It remains unclear how such alterations affect the sensory information processing within cortical LIV. Using serotonin transporter knockout (Sert-/-) rats, we demonstrate that high extracellular serotonin levels are associated with impaired feedforward inhibition (FFI), fewer perisomatic inhibitory synapses, a depolarized GABA reversal potential and reduced expression of KCC2 transporters in juvenile animals. At the neural population level, reduced FFI increases the excitatory drive originating from LIV, facilitating evoked representations in the supragranular layers II/III. The behavioral consequence of these changes in network excitability is faster integration of the sensory information during whisker-based tactile navigation, as Sert-/- rats require fewer whisker contacts with tactile targets and perform object localization with faster reaction times. These results highlight the association of serotonergic homeostasis with formation and excitability of sensory cortical networks, and consequently with sensory perception.

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

Somatosensory map expansion and altered processing of tactile inputs in a mouse model of fragile X syndrome.

Fragile X syndrome (FXS) is a common inherited form of intellectual disability caused by the absence or reduction of the fragile X mental retardation protein (FMRP) encoded by the FMR1 gene. In humans, one symptom of FXS is hypersensitivity to sensory stimuli, including touch. We used a mouse model of FXS (Fmr1 KO) to study sensory processing of tactile information conveyed via the whisker system. In vivo electrophysiological recordings in somatosensory barrel cortex showed layer-specific broadening of the receptive fields at the level of layer 2/3 but not layer 4, in response to whisker stimulation. Furthermore, the encoding of tactile stimuli at different frequencies was severely affected in layer 2/3. The behavioral effect of this broadening of the receptive fields was tested in the gap-crossing task, a whisker-dependent behavioral paradigm. In this task the Fmr1 KO mice showed differences in the number of whisker contacts with platforms, decrease in the whisker sampling duration and reduction in the whisker touch-time while performing the task. We propose that the increased excitability in the somatosensory barrel cortex upon whisker stimulation may contribute to changes in the whisking strategy as well as to other observed behavioral phenotypes related to tactile processing in Fmr1 KO mice.

Hippocampal GluA1 expression in Gria1-/- mice only partially restores spatial memory performance deficits.

Spatial working memory (SWM) is an essential cognitive function important for survival in a competitive environment. In rodents SWM requires an intact hippocampus and SWM expression is impaired in mice lacking the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor subunit GluA1 (Gria1-/- mice). Here we used viral gene transfer to show that re-expression of GluA1 in the hippocampus can affect the behavioral performance of GluA1 deficient mice. We found that Gria1-/- mice with hippocampus-specific rescue of GluA1 expression (Gria1Hpc mice) are more anxious, less hyperactive and only partly impaired in SWM expression in the Y-maze spatial novelty preference paradigm compared to Gria1-/- mice. However, Gria1Hpc mice still express SWM performance deficits when tested in the rewarded alternation T-maze task. Thus, the restoration of hippocampal function affects several behaviors of GluA1 deficient mice - including SWM expression - in different tasks. The virus-mediated GluA1 expression in Gria1-/- mice is not sufficient for a comprehensive SWM restoration, suggesting that both hippocampal as well as extra-hippocampal GluA1-containing AMPA receptors contribute to SWM.

A Developmental Switch for Hebbian Plasticity.

Hebbian forms of synaptic plasticity are required for the orderly development of sensory circuits in the brain and are powerful modulators of learning and memory in adulthood. During development, emergence of Hebbian plasticity leads to formation of functional circuits. By modeling the dynamics of neurotransmitter release during early postnatal cortical development we show that a developmentally regulated switch in vesicle exocytosis mode triggers associative (i.e. Hebbian) plasticity. Early in development spontaneous vesicle exocytosis (SVE), often considered as 'synaptic noise', is important for homogenization of synaptic weights and maintenance of synaptic weights in the appropriate dynamic range. Our results demonstrate that SVE has a permissive, whereas subsequent evoked vesicle exocytosis (EVE) has an instructive role in the expression of Hebbian plasticity. A timed onset for Hebbian plasticity can be achieved by switching from SVE to EVE and the balance between SVE and EVE can control the effective rate of Hebbian plasticity. We further show that this developmental switch in neurotransmitter release mode enables maturation of spike-timing dependent plasticity. A mis-timed or inadequate SVE to EVE switch may lead to malformation of brain networks thereby contributing to the etiology of neurodevelopmental disorders.

Tactile object localization by anticipatory whisker motion.

Rodents use rhythmic protractions of their whiskers to locate objects in space. The amplitude of these protractions is reduced when whiskers contact objects, leading to a tendency of whiskers to only lightly touch the environment. While the impact of this process on the sensory input has been studied, little is known about how sensory input causes this change in the motor pattern. Here, using high-speed imaging of whisking in mice, we simultaneously measured whisker contacts and the resulting whisking motion. We found that mice precisely target their whisker protractions to the distance at which they expect objects. This modulation does not depend on the current sensory input and remains stable for at least one whisking cycle when there is no object contact or when the object position is changed. As a result, the timing and other information carried by whisker contacts encodes how well each protraction was matched to the object, functioning as an error signal. Whisker contacts can thus encode a mismatch between expected object locations and the actual environment.

Nanophysiology: Bridging synapse ultrastructure, biology, and physiology using scanning ion conductance microscopy.

Synaptic communication is at the core of neural circuit function, and its plasticity allows the nervous system to adapt to the changes in its environment. Understanding the mechanisms of this synaptic (re)organization will benefit from novel methodologies that enable simultaneous study of synaptic ultrastructure, biology, and physiology in identified circuits. Here, we describe one of these methodologies, i.e., scanning ion conductance microscopy (SICM), for electrical mapping of the membrane anatomy in tens of nanometers resolution in living neurons. When combined with traditional patch-clamp and fluorescence microscopy techniques, and the newly emerging nanointerference methodologies, SICM has the potential to mechanistically bridge the synaptic structure and function longitudinally throughout the life of a synapse.

Nonlinear super-resolution signal processing allows intracellular tracking of calcium dynamics.

Objective.Traditional quantification of fluorescence signals, such asΔF/F, relies on ratiometric measures that necessitate a baseline for comparison, limiting their applicability in dynamic analyses. Our goal here is to develop a baseline-independent method for analyzing fluorescence data that fully exploits temporal dynamics to introduce a novel approach for dynamical super-resolution analysis, including in subcellular resolution.Approach.We introduce ARES (Autoregressive RESiduals), a novel method that leverages the temporal aspect of fluorescence signals. By focusing on the quantification of residuals following linear autoregression, ARES obviates the need for a predefined baseline, enabling a more nuanced analysis of signal dynamics.Main result.We delineate the foundational attributes of ARES, illustrating its capability to enhance both spatial and temporal resolution of calcium fluorescence activity beyond the conventional ratiometric measure (ΔF/F). Additionally, we demonstrate ARES's utility in elucidating intracellular calcium dynamics through the detailed observation of calcium wave propagation within a dendrite.Significance.ARES stands out as a robust and precise tool for the quantification of fluorescence signals, adept at analyzing both spontaneous and evoked calcium dynamics. Its ability to facilitate the subcellular localization of calcium signals and the spatiotemporal tracking of calcium dynamics-where traditional ratiometric measures falter-underscores its potential to revolutionize baseline-independent analyses in the field.

Experience-dependent regulation of dopaminergic signaling in the somatosensory cortex.

Dopamine critically influences reward processing, sensory perception, and motor control. Yet, the modulation of dopaminergic signaling by sensory experiences is not fully delineated. Here, by manipulating sensory experience using bilateral single-row whisker deprivation, we demonstrated that gene transcription in the dopaminergic signaling pathway (DSP) undergoes experience-dependent plasticity in both granular and supragranular layers of the primary somatosensory (barrel) cortex (S1). Sensory experience and deprivation compete for the regulation of DSP transcription across neighboring cortical columns, and sensory deprivation-induced changes in DSP are topographically constrained. These changes in DSP extend beyond cortical map plasticity and influence neuronal information processing. Pharmacological regulation of D2 receptors, a key component of DSP, revealed that D2 receptor activation suppresses excitatory neuronal excitability, hyperpolarizes the action potential threshold, and reduces the instantaneous firing rate. These findings suggest that the dopaminergic drive originating from midbrain dopaminergic neurons, targeting the sensory cortex, is subject to experience-dependent regulation and might create a regulatory feedback loop for modulating sensory processing. Finally, using topological gene network analysis and mutual information, we identify the molecular hubs of experience-dependent plasticity of DSP. These findings provide new insights into the mechanisms by which sensory experience shapes dopaminergic signaling in the brain and might help unravel the sensory deficits observed after dopamine depletion.

Where Top-Down Meets Bottom-Up: Cell-Type Specific Connectivity Map of the Whisker System.

Sensorimotor computation integrates bottom-up world state information with top-down knowledge and task goals to form action plans. In the rodent whisker system, a prime model of active sensing, evidence shows neuromodulatory neurotransmitters shape whisker control, affecting whisking frequency and amplitude. Since neuromodulatory neurotransmitters are mostly released from subcortical nuclei and have long-range projections that reach the rest of the central nervous system, mapping the circuits of top-down neuromodulatory control of sensorimotor nuclei will help to systematically address the mechanisms of active sensing. Therefore, we developed a neuroinformatic target discovery pipeline to mine the Allen Institute's Mouse Brain Connectivity Atlas. Using network connectivity analysis, we identified new putative connections along the whisker system and anatomically confirmed the existence of 42 previously unknown monosynaptic connections. Using this data, we updated the sensorimotor connectivity map of the mouse whisker system and developed the first cell-type-specific map of the network. The map includes 157 projections across 18 principal nuclei of the whisker system and neuromodulatory neurotransmitter-releasing. Performing a graph network analysis of this connectome, we identified cell-type specific hubs, sources, and sinks, provided anatomical evidence for monosynaptic inhibitory projections into all stages of the ascending pathway, and showed that neuromodulatory projections improve network-wide connectivity. These results argue that beyond the modulatory chemical contributions to information processing and transfer in the whisker system, the circuit connectivity features of the neuromodulatory networks position them as nodes of sensory and motor integration.

Spontaneous oscillations in intrinsic signals reveal the structure of cerebral vasculature.

Functional imaging of intrinsic signals allows minimally invasive spatiotemporal mapping of stimulus representations in the cortex, but representations are often corrupted by stimulus-independent spatial artifacts, especially those originating from the blood vessels. In this paper, we present novel algorithms for unsupervised identification of cerebral vascularization, allowing blind separation of stimulus representations from noise. These algorithms commonly take advantage of the temporal fluctuations in global reflectance to extract anatomic information. More specifically, the phase of low-frequency oscillations relative to global fluctuations reveals local vascular identity. Arterioles can be reconstructed using their characteristically high power in those frequencies corresponding to respiration, heartbeat, and vasomotion signals. By treating the vasculature as a dynamic flow network, we finally demonstrate that direction of blood perfusion can be quantitatively visualized. Application of these methods for removal of stimulus-independent changes in reflectance permits isolation of stimulus-evoked representations even if the representation spatially overlaps with blood vessels. The algorithms can be expanded further to extract temporal information on blood flow, monitor revascularization following a focal stroke, and distinguish arterioles from venules and parenchyma.

GluA1 and its PDZ-interaction: a role in experience-dependent behavioral plasticity in the forced swim test.

Glutamate receptor dependent synaptic plasticity plays an important role in the pathophysiology of depression. Hippocampal samples from clinically depressed patients display reduced mRNA levels for GluA1, a major subunit of AMPA receptors. Moreover, activation and synaptic incorporation of GluA1-containing AMPA receptors are required for the antidepressant-like effects of NMDA receptor antagonists. These findings argue that GluA1-dependent synaptic plasticity might be critically involved in the expression of depression. Using an animal model of depression, we demonstrate that global or hippocampus-selective deletion of GluA1 impairs expression of experience-dependent behavioral despair. This impairment is mediated by the interaction of GluA1 with PDZ-binding domain proteins, as deletion of the C-terminal leucine alone is sufficient to replicate the behavioral phenotype. Our results provide evidence for a significant role of hippocampal GluA1-containing AMPA receptors and their PDZ-interaction in experience-dependent expression of behavioral despair and link mechanisms of hippocampal synaptic plasticity with behavioral expression of depression.

Circuit mechanisms of GluA1-dependent spatial working memory.

Spatial working memory (SWM), the ability to process and manipulate spatial information over a relatively short period of time, requires an intact hippocampus, but also involves other forebrain nuclei in both in rodents and humans. Previous studies in mice showed that the molecular mechanism of SWM includes activation of AMPA receptors containing the GluA1 subunit (encoded by gria1) as GluA1 deletion in the whole brain (gria1(-/-)) results in strong SWM deficit. However, since these mice globally lack GluA1, the circuit mechanisms of GluA1 contribution to SWM remain unknown. In this study, by targeted expression of GluA1 containing AMPA receptors in the forebrain of gria1(-/-) mice or by removing GluA1 selectively from hippocampus of mice with "floxed" GluA1 alleles (gria1(fl/fl) ), we show that SWM requires GluA1 action in cortical circuits but is only partially dependent on GluA1-containing AMPA receptors in hippocampus. We further show that hippocampal GluA1 contribution to SWM is temporally restricted and becomes prominent at longer retention intervals (≥ 30 s). These findings provide a novel insight into the neural circuits required for SWM processing and argue that AMPA mediated signaling across forebrain and hippocampus differentially contribute to encoding of SWM.

Cortical Representation of Touch in Silico.

With its six layers and ~ 12,000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents'. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex's granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.

Neuromorphic computing hardware and neural architectures for robotics.

Neuromorphic hardware enables fast and power-efficient neural network-based artificial intelligence that is well suited to solving robotic tasks. Neuromorphic algorithms can be further developed following neural computing principles and neural network architectures inspired by biological neural systems. In this Viewpoint, we provide an overview of recent insights from neuroscience that could enhance signal processing in artificial neural networks on chip and unlock innovative applications in robotics and autonomous intelligent systems. These insights uncover computing principles, primitives, and algorithms on different levels of abstraction and call for more research into the basis of neural computation and neuronally inspired computing hardware.

Real-time contextual feedback for close-loop control of navigation.

OBJECTIVE: Close-loop control of brain and behavior will benefit from real-time detection of behavioral events to enable low-latency communication with peripheral devices. In animal experiments, this is typically achieved by using sparsely distributed (embedded) sensors that detect animal presence in select regions of interest. High-speed cameras provide high-density sampling across large arenas, capturing the richness of animal behavior, however, the image processing bottleneck prohibits real-time feedback in the context of rapidly evolving behaviors. APPROACH: Here we developed an open-source software, named PolyTouch, to track animal behavior in large arenas and provide rapid close-loop feedback in ~5.7 ms, ie. average latency from the detection of an event to analog stimulus delivery, e.g. auditory tone, TTL pulse, when tracking a single body. This stand-alone software is written in JAVA. The included wrapper for MATLAB provides experimental flexibility for data acquisition, analysis and visualization. MAIN RESULTS: As a proof-of-principle application we deployed the PolyTouch for place awareness training. A user-defined portion of the arena was used as a virtual target; visit (or approach) to the target triggered auditory feedback. We show that mice develop awareness to virtual spaces, tend to stay shorter and move faster when they reside in the virtual target zone if their visits are coupled to relatively high stimulus intensity (⩾49 dB). Thus, close-loop presentation of perceived aversive feedback is sufficient to condition mice to avoid virtual targets within the span of a single session (~20 min). SIGNIFICANCE: Neuromodulation techniques now allow control of neural activity in a cell-type specific manner in spiking resolution. Using animal behavior to drive closed-loop control of neural activity would help to address the neural basis of behavioral state and environmental context-dependent information processing in the brain.

Neocortical Microdissection at Columnar and Laminar Resolution for Molecular Interrogation.

The heterogeneous organization of the mammalian neocortex poses a challenge for elucidating the molecular mechanisms underlying its physiological processes. Although high-throughput molecular methods are increasingly deployed in neuroscience, their anatomical specificity is often lacking. In this unit, we introduce a targeted microdissection technique that enables extraction of high-quality RNA and proteins at high anatomical resolution from acutely prepared brain slices. We exemplify its utility by isolating single cortical columns and laminae from the mouse primary somatosensory (barrel) cortex. Tissues can be isolated from living slices in minutes, and the extracted RNA and protein are of sufficient quantity and quality to be used for RNA sequencing and mass spectrometry. This technique will help to increase the anatomical specificity of molecular studies of the neocortex, and the brain in general, as it is applicable to any brain structure that can be identified using optical landmarks in living slices. © 2018 by John Wiley & Sons, Inc.

Spectral Weighting Underlies Perceived Sound Elevation.

The brain estimates the two-dimensional direction of sounds from the pressure-induced displacements of the eardrums. Accurate localization along the horizontal plane (azimuth angle) is enabled by binaural difference cues in timing and intensity. Localization along the vertical plane (elevation angle), including frontal and rear directions, relies on spectral cues made possible by the elevation dependent filtering in the idiosyncratic pinna cavities. However, the problem of extracting elevation from the sensory input is ill-posed, since the spectrum results from a convolution between source spectrum and the particular head-related transfer function (HRTF) associated with the source elevation, which are both unknown to the system. It is not clear how the auditory system deals with this problem, or which implicit assumptions it makes about source spectra. By varying the spectral contrast of broadband sounds around the 6-9 kHz band, which falls within the human pinna's most prominent elevation-related spectral notch, we here suggest that the auditory system performs a weighted spectral analysis across different frequency bands to estimate source elevation. We explain our results by a model, in which the auditory system weighs the different spectral bands, and compares the convolved weighted sensory spectrum with stored information about its own HRTFs, and spatial prior assumptions.