scholarly journals Stimulus-specific neural encoding of a persistent, internal defensive state in the hypothalamus

2019 ◽  
Author(s):  
Ann Kennedy ◽  
Prabhat S. Kunwar ◽  
Lingyun Li ◽  
Daniel Wagenaar ◽  
David J. Anderson
Keyword(s):  
Neural Activity ◽  
Internal State ◽  
Stress Hormones ◽  
Ventromedial Hypothalamus ◽  
Persistent Activity ◽  
Neural Encoding ◽  
Population Activity ◽  
Defensive Responses ◽  
Neuroendocrine Mechanisms ◽  
Threatening Stimuli

SummaryPersistent neural activity has been described in cortical, hippocampal, and motor networks as mediating short-term working memory of transiently encountered stimuli1–4. Internal emotion states such as fear also exhibit persistence following exposure to an inciting stimulus5,6, but such persistence is typically attributed to circulating stress hormones7–9; whether persistent neural activity also plays a role has not been established. SF1+/Nr5a1+ neurons in the dorsomedial and central subdivision of the ventromedial hypothalamus (VMHdm/c) are necessary for innate and learned defensive responses to predators10–13. Optogenetic activation of VMHdmSF1 neurons elicits defensive behaviors that can outlast stimulation11,14, suggesting it induces a persistent internal state of fear or anxiety. Here we show that VMHdmSF1 neurons exhibit persistent activity lasting tens of seconds, in response to naturalistic threatening stimuli. This persistent activity was correlated with, and required for, persistent thigmotaxic (anxiety-like) behavior in an open-field assay. Microendoscopic imaging of VMHdmSF1 neurons revealed that persistence reflects dynamic temporal changes in population activity, rather than simply synchronous, slow decay of simultaneously activated neurons. Unexpectedly, distinct but overlapping VMHdmSF1 subpopulations were persistently activated by different classes of threatening stimuli. Computational modeling suggested that recurrent neural networks (RNNs) incorporating slow excitation and a modest degree of neurochemical or spatial bias can account for persistent activity that maintains stimulus identity, without invoking genetically determined “labeled lines”15. Our results provide causal evidence that persistent neural activity, in addition to well-established neuroendocrine mechanisms, can contribute to the ability of emotion states to outlast their inciting stimuli, and suggest a mechanism that could prevent over-generalization of defensive responses without the need to evolve hardwired circuits specific for each type of threat.

scholarly journals Slow drift of neural activity as a signature of impulsivity in macaque visual and prefrontal cortex

2020 ◽  
Author(s):  
Benjamin R. Cowley ◽  
Adam C. Snyder ◽  
Katerina Acar ◽  
Ryan C. Williamson ◽  
Byron M. Yu ◽  
...  
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Neural Activity ◽  
Internal State ◽  
Sensory Stimulus ◽  
Perceptual Decision Making ◽  
Population Activity ◽  
Perceptual Decision ◽  
Slow Drift ◽  
Sensory Evidence

AbstractAn animal’s decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This internal state is a product of cognitive factors, such as fatigue, motivation, and arousal, but it is unclear how these factors influence the neural processes that encode the sensory stimulus and form a decision. We discovered that, over the timescale of tens of minutes during a perceptual decision-making task, animals slowly shifted their likelihood of reporting stimulus changes. They did this unprompted by task conditions. We recorded neural population activity from visual area V4 as well as prefrontal cortex, and found that the activity of both areas slowly drifted together with the behavioral fluctuations. We reasoned that such slow fluctuations in behavior could either be due to slow changes in how the sensory stimulus is processed or due to a process that acts independently of sensory processing. By analyzing the recorded activity in conjunction with models of perceptual decision-making, we found evidence for the slow drift in neural activity acting as an impulsivity signal, overriding sensory evidence to dictate the final decision. Overall, this work uncovers an internal state embedded in the population activity across multiple brain areas, hidden from typical trial-averaged analyses and revealed only when considering the passage of time within each experimental session. Knowledge of this cognitive factor was critical in elucidating how sensory signals and the internal state together contribute to the decision-making process.

scholarly journals The neural basis for a persistent internal state in Drosophila females

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
David Deutsch ◽  
Diego Pacheco ◽  
Lucas Encarnacion-Rivera ◽  
Talmo Pereira ◽  
Ramie Fathy ◽  
...  
Keyword(s):  
Neural Activity ◽  
Neural Circuit ◽  
Internal State ◽  
Persistent Activity ◽  
Neural Basis ◽  
Electron Microscopic ◽  
Brain Areas ◽  
Female Behavior ◽  
Specific Subset ◽  
Female Brain

Sustained changes in mood or action require persistent changes in neural activity, but it has been difficult to identify the neural circuit mechanisms that underlie persistent activity and contribute to long-lasting changes in behavior. Here, we show that a subset of Doublesex+ pC1 neurons in the Drosophila female brain, called pC1d/e, can drive minutes-long changes in female behavior in the presence of males. Using automated reconstruction of a volume electron microscopic (EM) image of the female brain, we map all inputs and outputs to both pC1d and pC1e. This reveals strong recurrent connectivity between, in particular, pC1d/e neurons and a specific subset of Fruitless+ neurons called aIPg. We additionally find that pC1d/e activation drives long-lasting persistent neural activity in brain areas and cells overlapping with the pC1d/e neural network, including both Doublesex+ and Fruitless+ neurons. Our work thus links minutes-long persistent changes in behavior with persistent neural activity and recurrent circuit architecture in the female brain.

scholarly journals Learning is shaped by abrupt changes in neural engagement

2020 ◽  
Author(s):  
Jay A. Hennig ◽  
Emily R. Oby ◽  
Matthew D. Golub ◽  
Lindsay A. Bahureksa ◽  
Patrick T. Sadtler ◽  
...  
Keyword(s):  
Neural Activity ◽  
Internal State ◽  
Neural Population ◽  
Behavioral Performance ◽  
Population Activity ◽  
Large Fluctuations ◽  
Abrupt Changes ◽  
Internal States ◽  
Task Goals ◽  
And Behavior

AbstractInternal states such as arousal, attention, and motivation are known to modulate brain-wide neural activity, but how these processes interact with learning is not well understood. During learning, the brain must modify the neural activity it produces to improve behavioral performance. How do internal states affect the evolution of this learning process? Using a brain-computer interface (BCI) learning paradigm in non-human primates, we identified large fluctuations in neural population activity in motor cortex (M1) indicative of arousal-like internal state changes. These fluctuations drove population activity along dimensions we term neural engagement axes. Neural engagement increased abruptly at the start of learning, and then gradually retreated. In a BCI, the causal relationship between neural activity and behavior is known. This allowed us to understand how these changes impacted behavioral performance for different task goals. We found that neural engagement interacted with learning, helping to explain why animals learned some task goals more quickly than others.

scholarly journals Differential encoding of predator fear in the ventromedial hypothalamus and periaqueductal grey

2018 ◽  
Author(s):  
Maria Esteban Masferrer ◽  
Bianca A. Silva ◽  
Kensaku Nomoto ◽  
Susana Q. Lima ◽  
Cornelius T. Gross
Keyword(s):  
Internal State ◽  
Motor Pattern ◽  
Ventromedial Hypothalamus ◽  
Sympathetic Activation ◽  
Periaqueductal Grey ◽  
Differential Encoding ◽  
Defensive Responses ◽  
Electrophysiological Recordings ◽  
Mammalian Predator ◽  
Stimulation Of

AbstractThe ventromedial hypothalamus is a central node of the mammalian predator defense network. Stimulation of this structure in rodents and primates elicits abrupt defensive responses, including flight, freezing, sympathetic activation, and panic, while inhibition reduces defensive responses to predators. The major efferent target of the ventromedial hypothalamus is the dorsal periaqueductal grey, and stimulation of this structure also elicits flight, freezing, and sympathetic activation. However, reversible inhibition experiments suggest that the ventromedial hypothalamus and periaqueductal grey play distinct roles in the control of defensive behavior, with the former proposed to encode an internal state necessary for the motivation of defensive responses, while the latter serves as a motor pattern initiator. Here we used electrophysiological recordings of single units in behaving mice exposed to a rat to investigate the encoding of predator fear in the dorsomedial division of the ventromedial hypothalamus and the dorsal periaqueductal grey. Distinct correlates of threat intensity and motor responses were found in both structures, suggesting a distributed encoding of sensory and motor features in the medial hypothalamic-brainstem instinctive network.

scholarly journals Regression-Based Identification of Behavior-Encoding Neurons During Large-Scale Optical Imaging of Neural Activity at Cellular Resolution

2011 ◽  
Vol 105 (2) ◽  
pp. 964-980 ◽  
Author(s):  
Andrew Miri ◽  
Kayvon Daie ◽  
Rebecca D. Burdine ◽  
Emre Aksay ◽  
David W. Tank
Keyword(s):  
Time Series ◽  
Optical Imaging ◽  
Neural Activity ◽  
Laser Scanning ◽  
Large Scale ◽  
Neural Encoding ◽  
Quantitative Measurements ◽  
Cellular Resolution ◽  
Activity Measurements ◽  
General Regression

The advent of methods for optical imaging of large-scale neural activity at cellular resolution in behaving animals presents the problem of identifying behavior-encoding cells within the resulting image time series. Rapid and precise identification of cells with particular neural encoding would facilitate targeted activity measurements and perturbations useful in characterizing the operating principles of neural circuits. Here we report a regression-based approach to semiautomatically identify neurons that is based on the correlation of fluorescence time series with quantitative measurements of behavior. The approach is illustrated with a novel preparation allowing synchronous eye tracking and two-photon laser scanning fluorescence imaging of calcium changes in populations of hindbrain neurons during spontaneous eye movement in the larval zebrafish. Putative velocity-to-position oculomotor integrator neurons were identified that showed a broad spatial distribution and diversity of encoding. Optical identification of integrator neurons was confirmed with targeted loose-patch electrical recording and laser ablation. The general regression-based approach we demonstrate should be widely applicable to calcium imaging time series in behaving animals.

scholarly journals Spatial precision of population activity in primate area MT

2015 ◽  
Vol 114 (2) ◽  
pp. 869-878 ◽  
Author(s):  
Spencer C. Chen ◽  
John W. Morley ◽  
Samuel G. Solomon
Keyword(s):  
Neural Activity ◽  
Visual Processing ◽  
Receptive Fields ◽  
Object Motion ◽  
Spatial Position ◽  
Multielectrode Arrays ◽  
Visual World ◽  
Population Activity ◽  
Area Mt ◽  
Mt Neurons

The middle temporal (MT) area is a cortical area integral to the “where” pathway of primate visual processing, signaling the movement and position of objects in the visual world. The receptive field of a single MT neuron is sensitive to the direction of object motion but is too large to signal precise spatial position. Here, we asked if the activity of MT neurons could be combined to support the high spatial precision required in the where pathway. With the use of multielectrode arrays, we recorded simultaneously neural activity at 24–65 sites in area MT of anesthetized marmoset monkeys. We found that although individual receptive fields span more than 5° of the visual field, the combined population response can support fine spatial discriminations (<0.2°). This is because receptive fields at neighboring sites overlapped substantially, and changes in spatial position are therefore projected onto neural activity in a large ensemble of neurons. This fine spatial discrimination is supported primarily by neurons with receptive fields flanking the target locations. Population performance is degraded (by 13–22%) when correlations in neural activity are ignored, further reflecting the contribution of population neural interactions. Our results show that population signals can provide high spatial precision despite large receptive fields, allowing area MT to represent both the motion and the position of objects in the visual world.

scholarly journals Distinct neuroendocrine mechanisms control neural activity underlying sex differences in sexual motivation and performance

2013 ◽  
Vol 37 (5) ◽  
pp. 735-742 ◽  
Author(s):  
Jacques Balthazart ◽  
Céline Corbisier de Meaultsart ◽  
Gregory F. Ball ◽  
Charlotte A. Cornil
Keyword(s):  
Sex Differences ◽  
Neural Activity ◽  
Sexual Motivation ◽  
Neuroendocrine Mechanisms ◽  
And Performance

scholarly journals Induced cortical oscillations in turtle cortex are coherent at the mesoscale of population activity, but not at the microscale of the membrane potential of neurons

2017 ◽  
Vol 118 (5) ◽  
pp. 2579-2591 ◽  
Author(s):  
Mahmood S. Hoseini ◽  
Jeff Pobst ◽  
Nathaniel Wright ◽  
Wesley Clawson ◽  
Woodrow Shew ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Membrane Potential ◽  
Neural Activity ◽  
Visual Stimulation ◽  
Field Potential ◽  
Brain Regions ◽  
Large Trial ◽  
Population Activity ◽  
Potential Oscillations ◽  
Time Frequency

Bursts of oscillatory neural activity have been hypothesized to be a core mechanism by which remote brain regions can communicate. Such a hypothesis raises the question to what extent oscillations are coherent across spatially distant neural populations. To address this question, we obtained local field potential (LFP) and membrane potential recordings from the visual cortex of turtle in response to visual stimulation of the retina. The time-frequency analysis of these recordings revealed pronounced bursts of oscillatory neural activity and a large trial-to-trial variability in the spectral and temporal properties of the observed oscillations. First, local bursts of oscillations varied from trial to trial in both burst duration and peak frequency. Second, oscillations of a given recording site were not autocoherent; i.e., the phase did not progress linearly in time. Third, LFP oscillations at spatially separate locations within the visual cortex were more phase coherent in the presence of visual stimulation than during ongoing activity. In contrast, the membrane potential oscillations from pairs of simultaneously recorded pyramidal neurons showed smaller phase coherence, which did not change when switching from black screen to visual stimulation. In conclusion, neuronal oscillations at distant locations in visual cortex are coherent at the mesoscale of population activity, but coherence is largely absent at the microscale of the membrane potential of neurons. NEW & NOTEWORTHY Coherent oscillatory neural activity has long been hypothesized as a potential mechanism for communication across locations in the brain. In this study we confirm the existence of coherent oscillations at the mesoscale of integrated cortical population activity. However, at the microscopic level of neurons, we find no evidence for coherence among oscillatory membrane potential fluctuations. These results raise questions about the applicability of the communication through coherence hypothesis to the level of the membrane potential.

scholarly journals Decoding locomotion from population neural activity in moving C. elegans

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Kelsey M Hallinen ◽  
Ross Dempsey ◽  
Monika Scholz ◽  
Xinwei Yu ◽  
Ashley Linder ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Neural Activity ◽  
Single Neuron ◽  
Neural Representation ◽  
Correlation Structure ◽  
Experimental Measurements ◽  
Population Activity ◽  
Calcium Activity ◽  
C Elegans

We investigated the neural representation of locomotion in the nematode C. elegans by recording population calcium activity during movement. We report that population activity more accurately decodes locomotion than any single neuron. Relevant signals are distributed across neurons with diverse tunings to locomotion. Two largely distinct subpopulations are informative for decoding velocity and curvature, and different neurons’ activities contribute features relevant for different aspects of a behavior or different instances of a behavioral motif. To validate our measurements, we labeled neurons AVAL and AVAR and found that their activity exhibited expected transients during backward locomotion. Finally, we compared population activity during movement and immobilization. Immobilization alters the correlation structure of neural activity and its dynamics. Some neurons positively correlated with AVA during movement become negatively correlated during immobilization and vice versa. This work provides needed experimental measurements that inform and constrain ongoing efforts to understand population dynamics underlying locomotion in C. elegans.

scholarly journals Dual-color volumetric imaging of neural activity of cortical columns

2018 ◽  
Author(s):  
Shuting Han ◽  
Weijian Yang ◽  
Rafael Yuste
Keyword(s):  
Neural Activity ◽  
High Speed ◽  
Neural Circuits ◽  
Emergent Properties ◽  
Spatiotemporal Resolution ◽  
Population Activity ◽  
Volumetric Imaging ◽  
Two Photon ◽  
Dual Color

To capture the emergent properties of neural circuits, high-speed volumetric imaging of neural activity at cellular resolution is desirable. But while conventional two-photon calcium imaging is a powerful tool to study population activity in vivo, it is restrained to two-dimensional planes. Expanding it to 3D while maintaining high spatiotemporal resolution appears necessary. Here, we developed a two-photon microscope with dual-color laser excitation that can image neural activity in a 3D volume. We imaged the neuronal activity of primary visual cortex from awake mice, spanning from L2 to L5 with 10 planes, at a rate of 10 vol/sec, and demonstrated volumetric imaging of L1 long-range PFC projections and L2/3 somatas. Using this method, we map visually-evoked neuronal ensembles in 3D, finding a lack of columnar structure in orientation responses and revealing functional correlations between cortical layers which differ from trial to trial and are missed in sequential imaging. We also reveal functional interactions between presynaptic L1 axons and postsynaptic L2/3 neurons. Volumetric two-photon imaging appears an ideal method for functional connectomics of neural circuits.

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