scholarly journals Precise spatial representations in the hippocampus of a food‑caching bird

2020 ◽  
Author(s):  
Hannah L. Payne ◽  
Galen F. Lynch ◽  
Dmitriy Aronov
Keyword(s):  
Neural Activity ◽  
Neural Circuit ◽  
Bird Species ◽  
Place Cells ◽  
Spatial Representations ◽  
Spatial Coding ◽  
Sharp Wave ◽  
Food Caching ◽  
Wide Range ◽  
Tufted Titmouse

SummaryThe hippocampus is an ancient neural circuit required for the formation of episodic memories. In mammals, this ability is thought to depend on well-documented patterns of neural activity, including place cells and sharp wave ripples. Notably, neither pattern has been found in non-mammals, despite compelling examples of episodic-like memory across a wide range of vertebrates. Does episodic memory nonetheless have a universal implementation across distant neural systems? We addressed this question by recording neural activity in the hippocampus of the tufted titmouse – an intense memory specialist from a food-caching family of birds. These birds cache large numbers of food items at scattered, concealed locations and use hippocampus-dependent memory to retrieve their caches. We found remarkably precise spatial representations akin to classic place cells, as well as sharp wave ripples, in the titmouse hippocampus. These patterns were organized along similar anatomical axes to those found in mammals. In contrast, spatial coding was weaker in a different, non-food-caching bird species. Our findings suggest a striking conservation of hippocampal mechanisms across distant vertebrates, in spite of vastly divergent anatomy and cytoarchitecture. At the same time, these results demonstrate that the exact implementation of such common mechanisms may conform to the unique ethological needs of different species.

scholarly journals Analysis of an open source, closed-loop, realtime system for hippocampal sharp-wave ripple disruption

2018 ◽  
Author(s):  
Shayok Dutta ◽  
Etienne Ackermann ◽  
Caleb Kemere
Keyword(s):  
Open Source ◽  
Neural Activity ◽  
Closed Loop ◽  
Detection System ◽  
Detection Accuracy ◽  
Sharp Wave ◽  
Trade Offs ◽  
Wide Range ◽  
Realtime System

AbstractTransient neural activity pervades hippocampal electrophysiological activity. During more quiescent states, brief ≈100 ms periods comprising large ≈150–250 Hz oscillations known as sharp-wave ripples (SWR) which co-occur with ensemble bursts of spiking activity, are regularly found in local field potentials recorded from area CA1. SWRs and their concomitant neural activity are thought to be important for memory consolidation, recall, and memory-guided decision making. Temporally-selective manipulations of hippocampal neural activity upon online hippocampal SWR detection have been used as causal evidence of the importance of SWR for mnemonic process as evinced by behavioral and/or physiological changes. However, though this approach is becoming more wide spread, the performance trade-offs involved in building a SWR detection and disruption system have not been explored, limiting the design and interpretation of SWR detection experiments. We present an open source, plug-and-play, online ripple detection system with a detailed performance characterization. Our system has been constructed to interface with an open source software platform, Trodes, and two hardware acquisition platforms, Open Ephys and SpikeGadgets. We show that our in vivo results — approximately 80% detection latencies falling in between ≈20–66 ms with ≈2 ms closed-loop latencies while maintaining <10 false detections per minute — are dependent upon both algorithmic trade-offs and acquisition hardware. We discuss strategies to improve detection accuracy and potential limitations of online ripple disruptions. By characterizing this system in detail, we present a template for analyzing other closed-loop neural detection and perturbation systems. Thus, we anticipate our modular, open source, realtime system will facilitate a wide range of carefully-designed causal closed-loop neuroscience experiments.

scholarly journals Breakdown of spatial coding and neural synchronization in epilepsy

2018 ◽  
Author(s):  
Tristan Shuman ◽  
Daniel Aharoni ◽  
Denise J. Cai ◽  
Christopher R. Lee ◽  
Spyridon Chavlis ◽  
...  
Keyword(s):  
Dentate Gyrus ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Population Level ◽  
Place Cells ◽  
Population Coding ◽  
Spatial Processing ◽  
Spatial Representations ◽  
Spatial Coding

AbstractTemporal lobe epilepsy causes significant cognitive deficits in both human patients and rodent models, yet the specific circuit mechanisms that alter cognitive processes remain unknown. There is dramatic and selective interneuron death and axonal reorganization within the hippocampus of both humans and animal models, but the functional consequences of these changes on information processing at the neuronal population level have not been well characterized. To examine spatial representations of epileptic and control mice, we developed a novel wire-free miniature microscope to allow for unconstrained behavior during in vivo calcium imaging of neuronal activity. We found that epileptic mice running on a linear track had severely impaired spatial processing in CA1 within a single session, as place cells were less precise and less stable, and population coding was impaired. Long-term stability of place cells was also compromised as place cells in epileptic mice were highly unstable across short time intervals and completely remapped across a week. Because of the large-scale reorganization of inhibitory circuits in epilepsy, we hypothesized that degraded spatial representations were caused by dysfunctional inhibition. To test this hypothesis, we examined the temporal dynamics of hippocampal interneurons using silicon probes to simultaneously record from CA1 and dentate gyrus during head-fixed virtual navigation. We found that epileptic mice had a profound reduction in theta coherence between the dentate gyrus and CA1 regions and altered interneuron synchronization. In particular, dentate interneurons of epileptic mice had altered phase preferences to ongoing theta oscillations, which decorrelated inhibitory population firing between CA1 and dentate gyrus. To assess the specific contribution of desynchronization on spatial coding, we built a CA1 network model to simulate hippocampal desynchronization. Critically, we found that desynchronized inputs reduced the information content and stability of CA1 neurons, consistent with the experimental data. Together, these results demonstrate that temporally precise intra-hippocampal communication is critical for forming the spatial code and that desynchronized firing of hippocampal neuronal populations contributes to poor spatial processing in epileptic mice.

scholarly journals Neural representations of space in the hippocampus of a food-caching bird

Science ◽  
2021 ◽  
Vol 373 (6552) ◽  
pp. 343-348
Author(s):  
H. L. Payne ◽  
G. F. Lynch ◽  
D. Aronov
Keyword(s):  
Spatial Memory ◽  
Neural Activity ◽  
Strong Dependence ◽  
Bird Species ◽  
Brain Regions ◽  
Food Caching ◽  
Neural Representations ◽  
Hippocampal Activity ◽  
Species Specific ◽  
Representations Of Space

Spatial memory in vertebrates requires brain regions homologous to the mammalian hippocampus. Between vertebrate clades, however, these regions are anatomically distinct and appear to produce different spatial patterns of neural activity. We asked whether hippocampal activity is fundamentally different even between distant vertebrates that share a strong dependence on spatial memory. We studied tufted titmice, food-caching birds capable of remembering many concealed food locations. We found mammalian-like neural activity in the titmouse hippocampus, including sharp-wave ripples and anatomically organized place cells. In a non–food-caching bird species, spatial firing was less informative and was exhibited by fewer neurons. These findings suggest that hippocampal circuit mechanisms are similar between birds and mammals, but that the resulting patterns of activity may vary quantitatively with species-specific ethological needs.

scholarly journals Omitted Variable Bias in GLMs of Neural Spiking Activity

2018 ◽  
Vol 30 (12) ◽  
pp. 3227-3258 ◽  
Author(s):  
Ian H. Stevenson
Keyword(s):  
Neural Activity ◽  
Single Neuron ◽  
Linear Models ◽  
Theory And Practice ◽  
Parameter Estimates ◽  
Omitted Variables ◽  
History Effects ◽  
Omitted Variable Bias ◽  
Wide Range ◽  
Variable Bias

Generalized linear models (GLMs) have a wide range of applications in systems neuroscience describing the encoding of stimulus and behavioral variables, as well as the dynamics of single neurons. However, in any given experiment, many variables that have an impact on neural activity are not observed or not modeled. Here we demonstrate, in both theory and practice, how these omitted variables can result in biased parameter estimates for the effects that are included. In three case studies, we estimate tuning functions for common experiments in motor cortex, hippocampus, and visual cortex. We find that including traditionally omitted variables changes estimates of the original parameters and that modulation originally attributed to one variable is reduced after new variables are included. In GLMs describing single-neuron dynamics, we then demonstrate how postspike history effects can also be biased by omitted variables. Here we find that omitted variable bias can lead to mistaken conclusions about the stability of single-neuron firing. Omitted variable bias can appear in any model with confounders—where omitted variables modulate neural activity and the effects of the omitted variables covary with the included effects. Understanding how and to what extent omitted variable bias affects parameter estimates is likely to be important for interpreting the parameters and predictions of many neural encoding models.

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 Hippocampal sharp wave-ripples and the associated sequence replay emerge from structured synaptic interactions in a network model of area CA3

2021 ◽  
Author(s):  
Andras Ecker ◽  
Bence Bagi ◽  
Eszter Vertes ◽  
Orsolya Steinbach-Nemeth ◽  
Maria Rita Karlocai ◽  
...  
Keyword(s):  
Place Cells ◽  
Data Driven ◽  
Long Term Memory ◽  
Term Memory ◽  
Cellular Adaptation ◽  
Sharp Wave ◽  
Synaptic Interactions ◽  
Area Ca3 ◽  
Reversed Order

Hippocampal place cells are activated sequentially as an animal explores its environment. These activity sequences are internally recreated ("replayed"), either in the same or reversed order, during bursts of activity (sharp wave-ripples; SWRs) that occur in sleep and awake rest. SWR-associated replay is thought to be critical for the creation and maintenance of long-term memory. We sought to identify the cellular and network mechanisms of SWRs and replay by constructing and simulating a data-driven model of area CA3 of the hippocampus. Our results show that the structure of recurrent excitatory interactions established during learning not only determines the content of replay, but is essential for the generation of the SWRs as well. We find that bidirectional replay requires the interplay of the experimentally confirmed, temporally symmetric plasticity rule, and cellular adaptation. Our model provides a unifying framework for diverse phenomena involving hippocampal plasticity, representations, and dynamics.

scholarly journals A novel device for real-time measurement and manipulation of licking behavior in head-fixed mice

2018 ◽  
Vol 120 (6) ◽  
pp. 2975-2987 ◽  
Author(s):  
Brice Williams ◽  
Anderson Speed ◽  
Bilal Haider
Keyword(s):  
Real Time ◽  
Neural Activity ◽  
Closed Loop ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Visual Behavior ◽  
Sensory Stimuli ◽  
Neural Recordings ◽  
Control Signals ◽  
Sensory Motor

The mouse has become an influential model system for investigating the mammalian nervous system. Technologies in mice enable recording and manipulation of neural circuits during tasks where they respond to sensory stimuli by licking for liquid rewards. Precise monitoring of licking during these tasks provides an accessible metric of sensory-motor processing, particularly when combined with simultaneous neural recordings. There are several challenges in designing and implementing lick detectors during head-fixed neurophysiological experiments in mice. First, mice are small, and licking behaviors are easily perturbed or biased by large sensors. Second, neural recordings during licking are highly sensitive to electrical contact artifacts. Third, submillisecond lick detection latencies are required to generate control signals that manipulate neural activity at appropriate time scales. Here we designed, characterized, and implemented a contactless dual-port device that precisely measures directional licking in head-fixed mice performing visual behavior. We first determined the optimal characteristics of our detector through design iteration and then quantified device performance under ideal conditions. We then tested performance during head-fixed mouse behavior with simultaneous neural recordings in vivo. We finally demonstrate our device’s ability to detect directional licks and generate appropriate control signals in real time to rapidly suppress licking behavior via closed-loop inhibition of neural activity. Our dual-port detector is cost effective and easily replicable, and it should enable a wide variety of applications probing the neural circuit basis of sensory perception, motor action, and learning in normal and transgenic mouse models. NEW & NOTEWORTHY Mice readily learn tasks in which they respond to sensory cues by licking for liquid rewards; tasks that involve multiple licking responses allow study of neural circuits underlying decision making and sensory-motor integration. Here we design, characterize, and implement a novel dual-port lick detector that precisely measures directional licking in head-fixed mice performing visual behavior, enabling simultaneous neural recording and closed-loop manipulation of licking.

scholarly journals The role of carbon dioxide in nematode behaviour and physiology

Parasitology ◽  
2019 ◽  
Vol 147 (8) ◽  
pp. 841-854 ◽  
Author(s):  
Navonil Banerjee ◽  
Elissa A. Hallem
Keyword(s):  
Carbon Dioxide ◽  
Neural Circuit ◽  
Physiological Responses ◽  
Life Stage ◽  
Free Living ◽  
Behavioural Responses ◽  
Wide Range ◽  
Sensory Cue ◽  
Context Dependent

AbstractCarbon dioxide (CO2) is an important sensory cue for many animals, including both parasitic and free-living nematodes. Many nematodes show context-dependent, experience-dependent and/or life-stage-dependent behavioural responses to CO2, suggesting that CO2 plays crucial roles throughout the nematode life cycle in multiple ethological contexts. Nematodes also show a wide range of physiological responses to CO2. Here, we review the diverse responses of parasitic and free-living nematodes to CO2. We also discuss the molecular, cellular and neural circuit mechanisms that mediate CO2 detection in nematodes, and that drive context-dependent and experience-dependent responses of nematodes to CO2.

Composition and replay of mnemonic sequences: The contributions of REM and slow-wave sleep to episodic memory

2013 ◽  
Vol 36 (6) ◽  
pp. 610-611 ◽  
Author(s):  
Sen Cheng ◽  
Markus Werning
Keyword(s):  
Episodic Memory ◽  
Eye Movement ◽  
Slow Wave ◽  
Rem Sleep ◽  
Neural Activity ◽  
Slow Wave Sleep ◽  
Place Cells ◽  
Object Representations ◽  
Episodic Memories ◽  
Gamma Band Oscillations

AbstractWe propose that rapid eye movement (REM) and slow-wave sleep contribute differently to the formation of episodic memories. REM sleep is important for building up invariant object representations that eventually recur to gamma-band oscillations in the neocortex. In contrast, slow-wave sleep is more directly involved in the consolidation of episodic memories through replay of sequential neural activity in hippocampal place cells.

scholarly journals Morphology predicts species' functional roles and their degree of specialization in plant–frugivore interactions

2016 ◽  
Vol 283 (1823) ◽  
pp. 20152444 ◽  
Author(s):  
D. Matthias Dehling ◽  
Pedro Jordano ◽  
H. Martin Schaefer ◽  
Katrin Böhning-Gaese ◽  
Matthias Schleuning
Keyword(s):  
Resource Use ◽  
Bird Species ◽  
Analytical Framework ◽  
Ecological Processes ◽  
Functional Roles ◽  
Functional Differences ◽  
Wide Range ◽  
Interaction Partners ◽  
Role Based ◽  
Morphological Differences

Species' functional roles in key ecosystem processes such as predation, pollination or seed dispersal are determined by the resource use of consumer species. An interaction between resource and consumer species usually requires trait matching (e.g. a congruence in the morphologies of interaction partners). Species' morphology should therefore determine species' functional roles in ecological processes mediated by mutualistic or antagonistic interactions. We tested this assumption for Neotropical plant–bird mutualisms. We used a new analytical framework that assesses a species's functional role based on the analysis of the traits of its interaction partners in a multidimensional trait space. We employed this framework to test (i) whether there is correspondence between the morphology of bird species and their functional roles and (ii) whether morphologically specialized birds fulfil specialized functional roles. We found that morphological differences between bird species reflected their functional differences: (i) bird species with different morphologies foraged on distinct sets of plant species and (ii) morphologically distinct bird species fulfilled specialized functional roles. These findings encourage further assessments of species' functional roles through the analysis of their interaction partners, and the proposed analytical framework facilitates a wide range of novel analyses for network and community ecology.

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