Biology subjects

Adesnik, H.

Publications and source records attributed to Adesnik, H..

25 records · Page 2Linked to original sources

bioRxiv2021

Antagonistic inhibitory subnetworks control cooperation and competition across cortical space

The cortical microcircuit can dynamically adjust to dramatic changes in the strength, scale, and complexity of its input. In the primary visual cortex (V1), pyramidal cells (PCs) integrate widely across space when signals are weak, but narrowly when signals are strong, a phenomenon known as contrast-dependent surround suppression. Theoretical work has proposed that local interneurons could mediate a shift from cooperation to competition of PCs across cortical space, underlying this computation. We combined calcium imaging and electrophysiology to constrain a stabilized supralinear network model that explains how the four principal cell types in layer 2/3 (L2/3) of mouse V1- somatostatin (SST), parvalbumin (PV), and vasoactive intestinal peptide (VIP) interneurons, and PCs- transform inputs from layer 4 (L4) PCs to encode drifting gratings of varying size and contrast. Using bidirectional optogenetic perturbations, we confirmed key predictions of the model. Our data and modeling showed that recurrent amplification drives a transition from a positive PC[->]VIP{dashv}SST{dashv}PC feedback loop at small size and low contrast to a negative PC[->]SST{dashv}PC feedback loop at large size and high contrast to contribute to this flexible computation. This may represent a widespread mechanism for gating competition across cortical space to optimally meet task demands.

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bioRxiv2020

Structure and variability of optogenetic responses identify the operating regime of cortex

The visual cortex receives non-sensory inputs containing behavioral and brain state information. Here we propose a parallel between optogenetic and behavioral modulations of activity and characterize their impact on cell-type-specific V1 processing under a common theoretical framework. We infer cell-type-specific circuitry from large-scale V1 recordings and demonstrate that, given strong recurrent excitation, the cell-type-specific responses imply key aspects of the known connectivity. In the inferred models, parvalbumin-expressing (PV), but not other, interneurons have responses to perturbations that we show theoretically imply that their activity stabilizes the circuit. We infer inputs that explain locomotion-induced changes in firing rates and find that, contrary to hypotheses of simple disinhibition, locomotory drive to VIP cells and to SOM cells largely cancel, with enhancement of excitatory-cell visual responses likely due to direct locomotory drive to them. We show that this SOM/VIP cancellation is a property emerging from V1 connectivity structure.

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bioRxiv2020

Ultrasound activates mechanosensitive TRAAK K+ channels directly through the lipid membrane

Ultrasound modulates the electrical activity of excitable cells and offers advantages over other neuromodulatory techniques; for example, it can be non-invasively transmitted through skull and focused to deep brain regions. However, the fundamental cellular, molecular, and mechanistic bases of ultrasonic neuromodulation are largely unknown. Here, we demonstrate ultrasound activation of the mechanosensitive K+ channel TRAAK with sub-millisecond kinetics to an extent comparable to canonical mechanical activation. Single channel recordings reveal a common basis for ultrasonic and mechanical activation with stimulus-graded destabilization of long-duration closures and promotion of full conductance openings. Ultrasonic energy is transduced to TRAAK directly through the membrane in the absence of other cellular components, likely increasing membrane tension to promote channel opening. We further demonstrate ultrasonic modulation of neuronally expressed TRAAK. These results suggest mechanosensitive channels underlie physiological responses to ultrasound and provides a framework for developing channel-based sonogentic actuators for acoustic neuromodulation of genetically targeted cells.

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bioRxiv2020

Three-dimensional Multi-site Random Access Photostimulation (3D-MAP)

Optical control of neural ensemble activity is crucial for understanding brain function and disease, yet no technology can achieve optogenetic control of very large numbers of neurons at extremely fast rate over a large volume. State-of-the-art multiphoton holographic optogenetics requires high power illumination that only addresses relatively small populations of neurons in parallel. Conversely, one-photon holographic techniques can stimulate more neurons with 2-3 orders lower power, but with a trade-off between resolution and addressable volume. Perhaps most problematically, two-photon holographic optogenetic systems are extremely expensive and sophisticated which has precluded their broader adoption in the neuroscience community. To address this technical gap, we introduce a new one-photon light sculpting technique, Three- Dimensional Multi-site random Access Photostimulation (3D-MAP), that overcomes these limitations by modulating light dynamically, both in the spatial and in the angular domain at multi-kHz rates. We use 3D-MAP to interrogate neural circuits in 3D and demonstrate simultaneous photostimulation and imaging of dozens of user-selected neurons in the intact mouse brain in vivo with high spatiotemporal resolution. 3D-MAP could be broadly adopted for high-throughput all-optical interrogation of brain circuits owing to its powerful combination of scale, speed, simplicity, and cost.

neuroscience↗

bioRxiv2020

Synthesis of higher order feature codes through stimulus-specific supra-linear summation

How cortical circuits build representations of complex objects is poorly understood. The massive dimensional expansion from the thalamus to the primary sensory cortex may enable sparse, comprehensive representations of higher order features to facilitate object identification. To generate such a code, cortical neurons must integrate broadly over space, yet simultaneously obtain sharp tuning to specific stimulus features. The logic of cortical integration that may synthesize such a sparse, high dimensional code for complex features is not known. To address this question, we probed the integration and population coding of higher order stimuli in the somatosensory and visual cortices of awake mice using two-photon calcium imaging across cortical layers. We found that somatosensory and visual cortical neurons sum highly specific combinations of sensory inputs supra-linearly, but integrate other inputs sub-linearly, leading to selective responses to higher order features. This integrative process generates a sparse, but comprehensive code for complex stimuli from the earliest stages of cortical processing. These results from multiple sensory modalities imply that input-specific supra-linear summation may represent a widespread cortical mechanism for the synthesis of higher order feature codes. This new mechanism may explain how the brain exploits the thalamocortical expansion of dimensionality to encode arbitrary complex features of sensory stimuli.

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bioRxiv2020

Spatial integration during active tactile sensation drives elementary shape perception

Active haptic sensation is critical for object identification and manipulation, such as for tool use in humans, or prey capture in rodents. The neural circuit basis for recognizing objects through active touch alone is poorly understood. To address this gap, we combined optogenetics, two photon imaging, and high-speed behavioral tracking in mice solving a novel surface orientation discrimination task with their whiskers. We found that orientation discrimination required animals to summate input from multiple whiskers specifically along the whisker arc. Many animals discriminated the orientation of the stimulus per se, as their performance was invariant to the specific location of the presented stimulus. Two photon imaging showed that populations of neurons in the barrel cortex encoded each of the discriminated orientations, and this coding depended on integration over the whisker array. Finally, acute optogenetic inactivation of the barrel cortex strongly impaired surface orientation discrimination, and even cell-type specific optogenetic suppression of layer 4 excitatory neurons degraded performance, implying a role for superficial layers in this computation. These data suggest a model in which spatial summation over an active haptic array generates representations of an objects surface orientations. These computations may facilitate the encoding of complex three-dimensional objects during active exploration.

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bioRxiv2018

Complementary subnetworks of cortical somatostatin interneurons

The neocortex is organized into discrete layers of excitatory neurons: layer 4 receives the densest bottom up projection carrying external sensory data, while layers 2/3 and 5 receive top down inputs from higher cortical areas that may convey sensory expectations and behavioral goals. A subset of cortical somatostatin (SST) neurons gate top down input and control sensory computation by inhibiting the apical dendrites of pyramidal cells in layers 2/3 and 5. However, it is unknown whether an analogous inhibitory mechanism separately and specifically controls activity in layer 4. We hypothesized that distinct SST circuits might exist to inhibit specific cortical layers. By enforcing layer-specific inhibition, distinct SST subnetworks could mediate pathway-specific gain control, such as regulating the balance between bottom up and top down input. Employing a combination of high precision circuit mapping, in vivo optogenetic perturbations, and single cell transcriptional profiling, we reveal distinct and complementary SST circuits that specifically and reciprocally interconnect with excitatory cells in either layer 4 or layers 2/3 and 5. Our data further define a transcriptionally distinct SST neuronal sub-class that powerfully gates bottom up sensory activity during active sensation by regulating layer 4 activity. This integrated paradigm further represents a potentially generalizable approach to identify and characterize neuronal cell types and reveal their in vivo function.

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