Breathing coordinates cortico-hippocampal dynamics in mice during offline states

Network dynamics have been proposed as a mechanistic substrate for the information transfer across cortical and hippocampal circuits. However, little is known about the mechanisms that synchronize and coordinate these processes across widespread brain regions during offline states. Here we address the hypothesis that breathing acts as an oscillatory pacemaker, persistently coupling distributed brain circuit dynamics. Using large-scale recordings from a number of cortical and subcortical brain regions in behaving mice, we uncover the presence of an intracerebral respiratory corollary discharge, that modulates neural activity across these circuits. During offline states, the respiratory modulation underlies the coupling of hippocampal sharp-wave ripples and cortical DOWN/UP state transitions, which mediates systems memory consolidation. These results highlight breathing, a perennial brain rhythm, as an oscillatory scaffold for the functional coordination of the limbic circuit that~supports the segregation and integration of information flow across neuronal networks during offline states

Phasic oxygen dynamics confounds fast choline-sensitive biosensor signals in the brain of behaving rodents

Cholinergic fast time-scale modulation of cortical physiology is critical for cognition, but direct local measurement of neuromodulators in vivo is challenging. Choline oxidase (ChOx)-based electrochemical biosensors have been used to capture fast cholinergic signals in behaving animals. However, these transients might be biased by local field potential and O2-evoked enzymatic responses. Using a novel Tetrode-based Amperometric ChOx (TACO) sensor, we performed highly sensitive and selective simultaneous measurement of ChOx activity (COA) and O2. In vitro and in vivo experiments, supported by mathematical modeling, revealed that non-steady-state enzyme responses to O2 give rise to phasic COA dynamics. This mechanism accounts for most of COA transients in the hippocampus, including those following locomotion bouts and sharp-wave/ripples. Our results suggest that it is unfeasible to probe phasic cholinergic signals under most behavioral paradigms with current ChOx biosensors. This confound is generalizable to any oxidase-based biosensor, entailing rigorous controls and new biosensor designs

Ratcave: A 3D graphics python package for cognitive psychology experiments

We present here a free, open source Python 3D graphics library called Ratcave that extends existing Python psychology stimulus software by allowing scientists to load, display, and transform 3D stimuli created in 3D modeling software. This library makes 3D programming intuitive to new users by providing 3D graphics engine concepts (Mesh, Scene, Light, and Camera classes) that can be manipulated using an interface similar to existing 2D stimulus libraries. In addition, the use of modern OpenGL constructs by Ratcave helps scientists create fast, hardware-accelerated dynamic stimuli using the same intuitive high-level, lightweight interface. Because Ratcave supplements, rather than replaces, existing Python stimulus libraries, scientists can continue to use their preferred libraries by simply adding Ratcave graphics to their existing experiments. We hope this tool will be useful both as a stimulus library and as an example of how tightly-focused libraries can add quality to the existing scientific open-source software ecosystem. Cognitive psychology and neuroscience experiments use software that presents stimuli to a subject, detects subject responses, and logs events for future analysis, all with high temporal accuracy. An ever-expanding list of other features included in this software are compatibility with third-party hardware devices (e.g. button boxes, amplifiers, eye tracking systems), support for custom experimental designs, and online analysis for adaptive stimulus sequences; these tools are available both as self-enclosed software solutions (e.g. Neurobs Presentation, BCI2000, SuperLab, E-Prime) and open-source libraries (e.g. Psychtoolbox by Brainard, 1997; PsychoPy by Peirce, 2007; VisionEgg by Straw, 2008; Expyriment by Krause & Lindemann, 2013; for a review of psychophysics libraries, see Kötter, 2009). However, these popular libraries are missing 3D graphics support, needed for a wide range visual psychophysics experiments, such as 3D mental rotation or object recognition, virtual reality in spatial navigation research, to name a few. While 3D graphics libraries do exist in Python (e.g. Panda3D, PyOgre, Vizard) and other languages (e.g. Unity3D, Unreal Engine), the stimuli, logging, and hardware support of all of these libraries are designed to work with the windows and event loops they supply, making it difficult to integrate 3D graphics functionality into different psychophysics libraries without (sometimes-extensive) modification (e.g. to mix PsychoPy’s DotStim and Expyriment’s video support). In practice, this means that each software suite is relatively self-contained; researchers who require 3D stimuli, for example, have to, thereby, resort to use or develop different experiment control software when employing 3D visual stimuli (essentially, building interface to 3D game engines), losing out on the rich features that exist in the psychophysics software ecosystem developed for the 2D graphics. Extension libraries help reduce these feature-tradeoff decisions; for example, OpenSesame, a Python-powered GUI (Mathôt & Theeuwes, 2012), uses PsychoPy, Expyriment, and PyGame as “backends” to its experiment-building graphical interface, thereby supporting all researchers who rely on those libraries. A similar extension approach could be used for 3D stimuli--not to compete with the existing 3D frameworks on a feature-by-feature basis, but to simply add simple-to-use 3D stimulus presentation and manipulation support to the feature list of existing 2D stimulus libraries in Python. In this paper, we present an open-source, cross-platform Python library called Ratcave that adds 3D stimulus support to all OpenGL-based 2D Python stimulus libraries, including VisionEgg, Psychopy, Pyglet, and PyGame. We review the core features of Ratcave (https://github.com/ratcave/ratcave) and highlight key connections of its interface to underlying graphics programming strategies (a thorough manual, complete with API guide and tutorials for first-time users can be found at https://ratcave.readthedocs.org). This library, which derives its name from our high-speed RatcaveVR experimental setup (Del Grosso, Graboski, Chen, Hernández, & Sirota, 2017), is designed to increase accessibility of 3D graphics programming to the existing ecosystem of psychology software for Python

Transcranial Electric Stimulation Entrains Cortical Neuronal Populations in Rats

Low intensity electric fields have been suggested to affect the ongoing neuronal activity in vitro and in human studies. However, the physiological mechanism of how weak electrical fields affect and interact with intact brain activity is not well understood. We performed in vivo extracellular and intracellular recordings from the neocortex and hippocampus of anesthetized rats and extracellular recordings in behaving rats. Electric fields were generated by sinusoid patterns at slow frequency (0.8, 1.25 or 1.7 Hz) via electrodes placed on the surface of the skull or the dura. Transcranial electric stimulation (TES) reliably entrained neurons in widespread cortical areas, including the hippocampus. The percentage of TES phase-locked neurons increased with stimulus intensity and depended on the behavioral state of the animal. TES-induced voltage gradient, as low as 1 mV/mm at the recording sites, was sufficient to phase-bias neuronal spiking. Intracellular recordings showed that both spiking and subthreshold activity were under the combined influence of TES forced fields and network activity. We suggest that TES in chronic preparations may be used for experimental and therapeutic control of brain activity

Virtual Reality system for freely-moving rodents

Spatial navigation, active sensing, and most cognitive functions rely on a tight link between motor output and sensory input. Virtual reality (VR) systems simulate the sensorimotor loop, allowing flexible manipulation of enriched sensory input. Conventional rodent VR systems provide 3D visual cues linked to restrained locomotion on a treadmill, leading to a mismatch between visual and most other sensory inputs, sensory-motor conflicts, as well as restricted naturalistic behavior. To rectify these limitations, we developed a VR system (ratCAVE) that provides realistic and low-latency visual feedback directly to head movements of completely unrestrained rodents. Immersed in this VR system, rats displayed naturalistic behavior by spontaneously interacting with and hugging virtual walls, exploring virtual objects, and avoiding virtual cliffs. We further illustrate the effect of ratCAVE-VR manipulation on hippocampal place fields. The newly-developed methodology enables a wide range of experiments involving flexible manipulation of visual feedback in freely-moving behaving animals

Quantitative and Discrete Evolutionary Changes in the Egg-Laying Behavior of Single Drosophila Females

How a nervous system assembles and coordinates a suite of elementary behavioral steps into a complex behavior is not well understood. While often presented as a stereotyped sequence of events, even extensively studied behaviors such as fly courtship are rarely a strict repetition of the same steps in a predetermined sequence in time. We are focusing on oviposition, the act of laying an egg, in flies of the genus Drosophila to describe the elementary behavioral steps or microbehaviors that a single female fly undertakes prior to and during egg laying. We have analyzed the hierarchy and relationships in time of these microbehaviors in three closely related Drosophila species with divergent egg-laying preferences and uncovered cryptic differences in their behavioral patterns. Using high-speed imaging, we quantified in depth the oviposition behavior of single females of Drosophila suzukii, Drosophila biarmipes and Drosophila melanogaster in a novel behavioral assay. By computing transitions between microbehaviors, we identified a common ethogram structure underlying oviposition of all three species. Quantifying parameters such as relative time spent on a microbehavior and its average duration, however, revealed clear differences between species. In addition, we examined the temporal dynamics and probability of transitions to different microbehaviors relative to a central event of oviposition, ovipositor contact. Although the quantitative analysis highlights behavioral variability across flies, it reveals some interesting trends for each species in the mode of substrate sampling, as well as possible evolutionary differences. Larger datasets derived from automated video annotation will overcome this paucity of data in the future, and use the same framework to reappraise these observed differences. Our study reveals a common architecture to the oviposition ethogram of three Drosophila species, indicating its ancestral state. It also indicates that Drosophila suzukii’s behavior departs quantitatively and qualitatively from that of the outgroup species, in line with its known divergent ethology. Together, our results illustrate how a global shift in ethology breaks down in the quantitative reorganization of the elementary steps underlying a complex behavior

Sensory Island Task (SIT): A New Behavioral Paradigm to Study Sensory Perception and Neural Processing in Freely Moving Animals

A central function of sensory systems is the gathering of information about dynamic interactions with the environment during self-motion. To determine whether modulation of a sensory cue was externally caused or a result of self-motion is fundamental to perceptual invariance and requires the continuous update of sensory processing about recent movements. This process is highly context-dependent and crucial for perceptual performances such as decision-making and sensory object formation. Yet despite its fundamental ecological role, voluntary self-motion is rarely incorporated in perceptual or neurophysiological investigations of sensory processing in animals. Here, we present the Sensory Island Task (SIT), a new freely moving search paradigm to study sensory processing and perception. In SIT, animals explore an open-field arena to find a sensory target relying solely on changes in the presented stimulus, which is controlled by closed-loop position tracking in real-time. Within a few sessions, animals are trained via positive reinforcement to search for a particular area in the arena (“target island”), which triggers the presentation of the target stimulus. The location of the target island is randomized across trials, making the modulated stimulus feature the only informative cue for task completion. Animals report detection of the target stimulus by remaining within the island for a defined time (“sit-time”). Multiple “non-target” islands can be incorporated to test psychometric discrimination and identification performance. We exemplify the suitability of SIT for rodents (Mongolian gerbil, Meriones unguiculatus) and small primates (mouse lemur, Microcebus murinus) and for studying various sensory perceptual performances (auditory frequency discrimination, sound source localization, visual orientation discrimination). Furthermore, we show that pairing SIT with chronic electrophysiological recordings allows revealing neuronal signatures of sensory processing under ecologically relevant conditions during goal-oriented behavior. In conclusion, SIT represents a flexible and easily implementable behavioral paradigm for mammals that combines self-motion and natural exploratory behavior to study sensory sensitivity and decision-making and their underlying neuronal processing

Multiplexed neural sensor array of graphene solution-gated field-effect transistors

Altres ajuts: this work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS 'NANBIOSIS', more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBERBBN) at the IMB-CNM.Electrocorticography (ECoG) is a well-established technique to monitor electrophysiological activity from the surface of the brain and has proved crucial for the current generation of neural prostheses and brain-computer interfaces. However, existing ECoG technologies still fail to provide the resolution necessary to accurately map highly localized activity across large brain areas, due to the rapidly increasing size of connector footprint with sensor count. This work demonstrates the use of a flexible array of graphene solution-gated field-effect transistors (gSGFET), exploring the concept of multiplexed readout using an external switching matrix. This approach does not only allow for an increased sensor count, but due to the use of active sensing devices (i.e. transistors) over microelectrodes it makes additional buffer transistors redundant, which drastically eases the complexity of device fabrication on flexible substrates. The presented results pave the way for upscaling the gSGFET technology towards large-scale, high-density μECoG-arrays, eventually capable of resolving neural activity down to a single neuron level, while simultaneously mapping large brain regions