scholarly journals Nonlocal spatiotemporal representation in the hippocampus of freely flying bats

Science ◽  
2021 ◽  
Vol 373 (6551) ◽  
pp. 242-247
Author(s):  
Nicholas M. Dotson ◽  
Michael M. Yartsev
Keyword(s):  
Neural Activity ◽  
Spatial Information ◽  
Present Moment ◽  
Present Position ◽  
Space And Time ◽  
High Speeds ◽  
Area Ca1 ◽  
Electrophysiological Recordings ◽  
Spatiotemporal Representation

Navigation occurs through a continuum of space and time. The hippocampus is known to encode the immediate position of moving animals. However, active navigation, especially at high speeds, may require representing navigational information beyond the present moment. Using wireless electrophysiological recordings in freely flying bats, we demonstrate that neural activity in area CA1 predominantly encodes nonlocal spatial information up to meters away from the bat’s present position. This spatiotemporal representation extends both forward and backward in time, with an emphasis on future locations, and is found during both random exploration and goal-directed navigation. The representation of position thus extends along a continuum, with each moment containing information about past, present, and future, and may provide a key mechanism for navigating along self-selected and remembered paths.

scholarly journals Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics

2017 ◽  
Vol 24 (3) ◽  
pp. 277-293 ◽  
Author(s):  
Selen Atasoy ◽  
Gustavo Deco ◽  
Morten L. Kringelbach ◽  
Joel Pearson
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Activity Patterns ◽  
Structural Connectivity ◽  
Building Blocks ◽  
Mental States ◽  
Brain Dynamics ◽  
Space And Time ◽  
Wide Range ◽  
The Brain

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at “rest.” Here, we introduce the concept of harmonic brain modes—fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

scholarly journals Enhancing GABAergic Tone in the Rostral Nucleus of the Solitary Tract Reconfigures Sensorimotor Neural Activity

2020 ◽  
Author(s):  
Joshua D. Sammons ◽  
Caroline E. Bass ◽  
Jonathan D. Victor ◽  
Patricia M. Di Lorenzo
Keyword(s):  
Neural Activity ◽  
Inhibitory Activity ◽  
Nucleus Tractus Solitarius ◽  
Artificial Saliva ◽  
Experimental Chamber ◽  
Response Patterns ◽  
Related Activity ◽  
Electrophysiological Recordings ◽  
Rostral Nucleus ◽  
The Relationship

ABSTRACTRecent work has shown that most cells in the rostral, gustatory portion of the nucleus tractus solitarius (rNTS) in awake, freely licking rats show lick-related firing. However, the relationship between taste-related and lick-related activity in rNTS remains unclear. Here, we tested if GABA-derived inhibitory activity regulates the balance of lick- and taste-driven neuronal activity. Combinatorial viral tools were used to restrict expression of ChR2-EYFP to GAD1+ GABAergic neurons. Viral infusions were bilateral in rNTS. 2-4wks later, an optical fiber attached to 8-16 drivable microwires was implanted into the rNTS. After recovery, water-deprived rats were presented with taste stimuli in an experimental chamber. Trials were 5 consecutive taste licks [NaCl, KCl, NH4Cl, sucrose, MSG/IMP, citric acid, quinine, or artificial saliva (AS)] separated by 5 AS licks on a VR5 schedule. Each taste lick triggered a 1s train of laser light (25Hz; 473nm; 8-10mW) in a random half of the trials. In all, 113 cells were recorded in the rNTS, 50 responded to one or more taste stimuli without GABA enhancement. Selective changes in response magnitude (spike count) within cells shifted across unit patterns but preserved inter-stimulus relationships. Cells where enhanced GABAergic tone increased lick coherence conveyed more information distinguishing basic taste qualities and different salts than other cells. In addition, GABA activation significantly amplified the amount of information that discriminated palatable vs. unpalatable tastants. By dynamically regulating lick coherence and remodeling the across-unit response patterns to taste, enhancing GABAergic tone in rNTS reconfigures the neural activity reflecting sensation and movement.Significance StatementThe rostral nucleus tractus solitarius (rNTS) is the first structure in the central gustatory pathway. Electrophysiological recordings from the rNTS in awake, freely-licking animals show that cells in this area have lick- as well as taste-related activity, but the relationship between these characteristics is not well understood. Here, we showed evidence that GABA activation can dynamically regulate both of these two properties in rNTS cells to enhance the information conveyed, especially about palatable vs. unpalatable tastants. These data provide insights into the role of inhibitory activity in the rNTS.

Ex Vivo Brain Preparation to Analyze Vocal Pathways of Xenopus Frogs

2021 ◽  
Vol 2021 (9) ◽  
pp. pdb.prot106872
Author(s):  
Ayako Yamaguchi
Keyword(s):  
Neural Activity ◽  
Ex Vivo ◽  
Neural Circuitry ◽  
Neural Basis ◽  
Vocal Production ◽  
Basic Principles ◽  
Electrophysiological Recordings ◽  
The Brain

Understanding the neural basis of behavior is a challenging task for technical reasons. Most methods of recording neural activity require animals to be immobilized, but neural activity associated with most behavior cannot be recorded from an anesthetized, immobilized animal. Using amphibians, however, there has been some success in developing in vitro brain preparations that can be used for electrophysiological and anatomical studies. Here, we describe an ex vivo frog brain preparation from which fictive vocalizations (the neural activity that would have produced vocalizations had the brain been attached to the muscle) can be elicited repeatedly. When serotonin is applied to the isolated brains of male and female African clawed frogs, Xenopus laevis, laryngeal nerve activity that is a facsimile of those that underlie sex-specific vocalizations in vivo can be readily recorded. Recently, this preparation was successfully used in other species within the genus including Xenopus tropicalis and Xenopus victorianus. This preparation allows a variety of techniques to be applied including extracellular and intracellular electrophysiological recordings and calcium imaging during vocal production, surgical and pharmacological manipulation of neurons to evaluate their impact on motor output, and tract tracing of the neural circuitry. Thus, the preparation is a powerful tool with which to understand the basic principles that govern the production of coherent and robust motor programs in vertebrates.

scholarly journals A waveform-independent measure of recurrent neural activity

2021 ◽  
Author(s):  
Immo Weber ◽  
Carina R. Oehrn
Keyword(s):  
Fourier Transform ◽  
Neural Activity ◽  
Brain Activity ◽  
Neural Oscillations ◽  
Frequency Spectra ◽  
Time Resolved ◽  
Human Motor Cortex ◽  
Electrophysiological Recordings ◽  
Neural Information ◽  
Processing And Storage

AbstractRhythmic neural activity, so called oscillations, play a key role for neural information transmission, processing and storage. Neural oscillations in distinct frequency bands are central to physiological brain function and alterations thereof have been associated with several neurological and psychiatric disorders. The most common methods to analyse neural oscillations, e.g. short-term Fourier transform or wavelet analysis, assume that measured neural activity is composed of a series of symmetric prototypical waveforms, e.g. sinusoids. However, usually the models generating the signal, including waveform shapes of experimentally measured neural activity are unknown. Decomposing asymmetric waveforms of nonlinear origin using these classic methods may result in spurious harmonics visible in the estimated frequency spectra. Here, we introduce a new method for capturing rhythmic brain activity based on recurrences of similar states in phase-space. This method allows for a time-resolved estimation of amplitude fluctuations of recurrent activity irrespective of or specific to waveform-shapes. The algorithm is derived from the well-established field of recurrence analysis, which has rarely been adopted in neuroscience. In this paper, we show its advantages and limitations in comparison to short-time Fourier transform and wavelet convolution using periodic signals of different waveform shapes. Further, we demonstrate its application using experimental data, i.e. intracranial electrophysiological recordings from the human motor cortex of one epilepsy patient.

scholarly journals A calibrated optogenetic toolbox of stable zebrafish opsin lines

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Paride Antinucci ◽  
Adna Dumitrescu ◽  
Charlotte Deleuze ◽  
Holly J Morley ◽  
Kristie Leung ◽  
...  
Keyword(s):  
High Throughput ◽  
Neural Activity ◽  
Ion Selectivity ◽  
Transgenic Zebrafish ◽  
Substantial Variation ◽  
Opsin Expression ◽  
Electrophysiological Recordings ◽  
Subcellular Resolution ◽  
Kinetics Of

Optogenetic actuators with diverse spectral tuning, ion selectivity and kinetics are constantly being engineered providing powerful tools for controlling neural activity with subcellular resolution and millisecond precision. Achieving reliable and interpretable in vivo optogenetic manipulations requires reproducible actuator expression and calibration of photocurrents in target neurons. Here, we developed nine transgenic zebrafish lines for stable opsin expression and calibrated their efficacy in vivo. We first used high-throughput behavioural assays to compare opsin ability to elicit or silence neural activity. Next, we performed in vivo whole-cell electrophysiological recordings to quantify the amplitude and kinetics of photocurrents and test opsin ability to precisely control spiking. We observed substantial variation in efficacy, associated with differences in both opsin expression level and photocurrent characteristics, and identified conditions for optimal use of the most efficient opsins. Overall, our calibrated optogenetic toolkit will facilitate the design of controlled optogenetic circuit manipulations.

scholarly journals Maintaining Consistency of Spatial Information in the Hippocampal Network: A Combinatorial Geometry Model

2016 ◽  
Vol 28 (6) ◽  
pp. 1051-1071 ◽  
Author(s):  
Y. Dabaghian
Keyword(s):  
Spatial Information ◽  
Synaptic Connection ◽  
Cell Activity ◽  
Internal Representation ◽  
Combinatorial Geometry ◽  
Place Cells ◽  
Geometry Model ◽  
Electrophysiological Recordings ◽  
Hippocampal Network ◽  
Proprioceptive Inputs

Place cells in the rat hippocampus play a key role in creating the animal’s internal representation of the world. During active navigation, these cells spike only in discrete locations, together encoding a map of the environment. Electrophysiological recordings have shown that the animal can revisit this map mentally during both sleep and awake states, reactivating the place cells that fired during its exploration in the same sequence in which they were originally activated. Although consistency of place cell activity during active navigation is arguably enforced by sensory and proprioceptive inputs, it remains unclear how a consistent representation of space can be maintained during spontaneous replay. We propose a model that can account for this phenomenon and suggest that a spatially consistent replay requires a number of constraints on the hippocampal network that affect its synaptic architecture and the statistics of synaptic connection strengths.

scholarly journals The evolving view of replay and its functions in wake and sleep

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Graham Findlay ◽  
Giulio Tononi ◽  
Chiara Cirelli
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Neural Activity ◽  
Memory Consolidation ◽  
Memory Trace ◽  
Methodological Issues ◽  
Credit Assignment ◽  
Considerable Uncertainty ◽  
High Speeds

Abstract The term hippocampal replay originally referred to the temporally compressed reinstantiation, during rest, of sequential neural activity observed during prior active wake. Since its description in the 1990s, hippocampal replay has often been viewed as the key mechanism by which a memory trace is repeatedly rehearsed at high speeds during sleep and gradually transferred to neocortical circuits. However, the methods used to measure the occurrence of replay remain debated, and it is now clear that the underlying neural events are considerably more complicated than the traditional narratives had suggested. “Replay-like” activity happens during wake, can play out in reverse order, may represent trajectories never taken by the animal, and may have additional functions beyond memory consolidation, from learning values and solving the problem of credit assignment to decision-making and planning. Still, we know little about the role of replay in cognition, and to what extent it differs between wake and sleep. This may soon change, however, because decades-long efforts to explain replay in terms of reinforcement learning (RL) have started to yield testable predictions and possible explanations for a diverse set of observations. Here, we (1) survey the diverse features of replay, focusing especially on the latest findings; (2) discuss recent attempts at unifying disparate experimental results and putatively different cognitive functions under the banner of RL; (3) discuss methodological issues and theoretical biases that impede progress or may warrant a partial revaluation of the current literature, and finally; (4) highlight areas of considerable uncertainty and promising avenues of inquiry.

scholarly journals The BioLuminescent-OptoGenetic in vivo Response to Coelenterazine is Proportional, Sensitive and Specific in Neocortex

2019 ◽  
Author(s):  
Manuel Gomez-Ramirez ◽  
Alexander I. More ◽  
Nina G. Friedman ◽  
Ute Hochgeschwender ◽  
Christopher I. Moore
Keyword(s):  
Neural Activity ◽  
Bioluminescence Imaging ◽  
Photon Emission ◽  
Gaussia Luciferase ◽  
Light Production ◽  
Electrophysiological Recordings ◽  
Dynamic Concentration ◽  
And Behavior ◽  
The Relationship

ABSTRACTBioLuminescent (BL) light production can modulate neural activity and behavior through coexpressed OptoGenetic (OG) elements, an approach termed ‘BL-OG’. Yet, the relationship between BL-OG effects and bioluminescent photon emission has not been characterized in vivo. Further, the degree to which BL-OG effects strictly depend on optogenetic mechanisms driven by bioluminescent photons is unknown. Crucial to every neuromodulation method is whether the activator shows a dynamic concentration range driving robust, selective, and non-toxic effects. We systematically tested the effects of four key components of the BL-OG mechanism (luciferin, oxidized luciferin, luciferin vehicle, and bioluminescence), and compared these against effects induced by the Luminopsin-3 (LMO3) BL-OG molecule, a fusion of slow burn Gaussia luciferase (sbGLuc) and Volvox ChannelRhodopsin-1 (VChR1). We performed combined bioluminescence imaging and electrophysiological recordings while injecting specific doses of Coelenterazine (substrate for sbGluc), Coelenteramide (CTM, the oxidized product of CTZ), or CTZ vehicle. CTZ robustly drove activity in mice expressing LMO3, with photon production proportional to firing rate. In contrast, low and moderate doses of CTZ, CTM, or vehicle did not modulate activity in mice that did not express LMO3. We also failed to find bioluminescence effects on neural activity in mice expressing an optogenetically non-sensitive LMO3 variant. We observed weak responses to the highest dose of CTZ in control mice, but these effects were significantly smaller than those observed in the LMO3 group. These results show that in neocortex in vivo, there is a large CTZ range wherein BL-OG effects are specific to its active chemogenetic mechanism.

scholarly journals Simultaneous GCaMP6-based Fiber Photometry and fMRI in Rats

2017 ◽  
Author(s):  
Zhifeng Liang ◽  
Yuncong Ma ◽  
Glenn D.R. Watson ◽  
Nanyin Zhang
Keyword(s):  
Neural Activity ◽  
Electromagnetic Interference ◽  
Visual Stimulation ◽  
Blood Oxygenation ◽  
Bold Signal ◽  
Cell Type Specificity ◽  
Neural Basis ◽  
Neuron Populations ◽  
Electrophysiological Recordings ◽  
Calcium Indicator

AbstractUnderstanding the relationship between neural and vascular signals is essential for interpretation of functional MRI (fMRI) results with respect to underlying neuronal activity. Simultaneously measuring neural activity using electrophysiology with fMRI has been highly valuable in elucidating the neural basis of the blood oxygenation-level dependent (BOLD) signal. However, this approach is also technically challenging due to the electromagnetic interference that is observed in electrophysiological recordings during MRI scanning. Recording optical correlates of neural activity, such as calcium signals, avoids this issue, and has opened a new avenue to simultaneously acquire neural and BOLD signals. The present study is the first to demonstrate the feasibility of simultaneously and repeatedly acquiring calcium and BOLD signals in animals using a genetically encoded calcium indicator, GCaMP6. This approach was validated with a visual stimulation experiment, during which robust increases of both calcium and BOLD signals in the superior colliculus were observed. In addition, repeated measurement in the same animal demonstrated reproducible calcium and BOLD responses to the same stimuli. Taken together, simultaneous GCaMP6-based fiber photometry and fMRI recording presents a novel, artifact-free approach to simultaneously measuring neural and fMRI signals. Furthermore, given the cell-type specificity of GCaMP6, this approach has the potential to mechanistically dissect the contributions of individual neuron populations with respect to BOLD signal, and ultimately reveal its underlying neural mechanisms.

scholarly journals Resonating neurons stabilize heterogeneous grid-cell networks

2020 ◽  
Author(s):  
Divyansh Mittal ◽  
Rishikesh Narayanan
Keyword(s):  
Neural Activity ◽  
Biological Networks ◽  
Spatial Information ◽  
Physiological Mechanism ◽  
Low Frequency ◽  
Two Dimensional ◽  
Attractor Network ◽  
Network Function ◽  
Frequency Components ◽  
The Impact

ABSTRACTGrid cells in the medial entorhinal cortex manifest multiple firing fields, patterned to tessellate external space with triangles. Although two-dimensional continuous attractor network (CAN) models have offered remarkable insights about grid-patterned activity generation, their functional stability in the presence of biological heterogeneities remains unexplored. In this study, we systematically incorporated three distinct forms of intrinsic and synaptic heterogeneities into a rate-based CAN model driven by virtual trajectories, developed here to mimic animal traversals and improve computational efficiency. We found that increasing degrees of biological heterogeneities progressively disrupted the emergence of grid-patterned activity and resulted in progressively large perturbations in neural activity. Quantitatively, grid score and spatial information associated with neural activity reduced progressively with increasing degree of heterogeneities, and perturbations were primarily confined to low-frequency neural activity. We postulated that suppressing low-frequency perturbations could ameliorate the disruptive impact of heterogeneities on grid-patterned activity. To test this, we formulated a strategy to introduce intrinsic neuronal resonance, a physiological mechanism to suppress low-frequency activity, in our rate-based neuronal model by incorporating filters that mimicked resonating conductances. We confirmed the emergence of grid-patterned activity in homogeneous CAN models built with resonating neurons and assessed the impact of heterogeneities on these models. Strikingly, CAN models with resonating neurons were resilient to the incorporation of heterogeneities and exhibited stable grid-patterned firing, through suppression of low-frequency components in neural activity. Our analyses suggest a universal role for intrinsic neuronal resonance, an established mechanism in biological neurons to suppress low-frequency neural activity, in stabilizing heterogeneous network physiology.SIGNIFICANCE STATEMENTA central theme that governs the functional design of biological networks is their ability to sustain stable function despite widespread parametric variability. However, several theoretical and modeling frameworks employ unnatural homogeneous networks in assessing network function owing to the enormous analytical or computational costs involved in assessing heterogeneous networks. Here, we investigate the impact of biological heterogeneities on a powerful two-dimensional continuous attractor network implicated in the emergence of patterned neural activity. We show that network function is disrupted by biological heterogeneities, but is stabilized by intrinsic neuronal resonance, a physiological mechanism that suppresses low-frequency perturbations. As low-frequency perturbations are pervasive across biological systems, mechanisms that suppress low-frequency components could form a generalized route to stabilize heterogeneous biological networks.

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