scholarly journals Communicability systematically explains transmission speed in a cortical macro-connectome

2017 ◽  
Author(s):  
Masanori Shimono ◽  
Naomichi Hatano
Keyword(s):  
Propagation Velocity ◽  
Single Unit ◽  
Temporal Dynamics ◽  
Global Dynamics ◽  
Theoretical Understanding ◽  
Graph Theoretic ◽  
Temporal Aspects ◽  
Single Unit Recordings ◽  
The Brain ◽  
Anatomical Constraints

AbstractGlobal dynamics in the brain can be captured using fMRI, MEG, or electrocorticography (ECoG), but models are often restricted by anatomical constraints. Complementary single-/multi-unit recordings have described local fast temporal dynamics. However, because of anatomical constraints, global fast temporal dynamics remain incompletely understood. Therefore, we compared temporal aspects of cross-area propagations of single-unit recordings and ECoG, and investigated their anatomical bases. First, we demonstrated how both evoked and spontaneous ECoGs can accurately predict latencies of single-unit recordings. Next, we estimated the propagation velocity (1.0–1.5 m/s) from brain-wide data and found that it was fairly stable among different conscious levels. We also found that the anatomical topology strongly predicted the latencies. Finally, Communicability, a novel graph-theoretic measure, could systematically capture the balance between shorter or longer pathways. These results demonstrate that macro-connectomic perspective is essential for evaluating detailed temporal dynamics in the brain.Author SummaryThis study produced four main findings: First, we demonstrated that ECoG signals could predict the timing of evoked electrical spikes of neurons elicited by visual stimuli. Second, we showed that spontaneous ECoG recorded under a blindfold condition (without any stimuli) could also predict the timing of visually evoked neuronal spikes. We also clarified that performance predictions from blindfold data are essentially supported by the constraints of structural paths. Third, we quantified the propagation velocity (conductance velocity) as 1.0–1.5 m/s, and found that the velocity was stable among different conscious levels. Fourth, Communicability successfully characterized the relative contributions of shorter and longer paths. This study represents an important contribution to the theoretical understanding of the brain in terms of connectomics, dynamical propagations, and multi-scale architectures.

Sources of the Scalp-Recorded Amplitude-Modulation Following Response

2002 ◽  
Vol 13 (04) ◽  
pp. 188-204 ◽  
Author(s):  
Shigeyuki Kuwada ◽  
Julia S. Anderson ◽  
Ranjan Batra ◽  
Douglas C. Fitzpatrick ◽  
Natacha Teissier ◽  
...  
Keyword(s):  
Animal Model ◽  
Amplitude Modulation ◽  
Single Unit ◽  
Modulation Frequency ◽  
Multiple Sources ◽  
High Modulation ◽  
Before And After ◽  
Single Unit Recordings ◽  
Composite Response ◽  
The Brain

The scalp-recorded amplitude-modulation following response (AMFR)” is gaining recognition as an objective audiometric tool, but little is known about the neural sources that underlie this potential. We hypothesized, based on our human studies and single-unit recordings in animals, that the scalp-recorded AMFR reflects the interaction of multiple sources. We tested this hypothesis using an animal model, the unanesthetized rabbit. We compared AMFRs recorded from the surface of the brain at different locations and before and after the administration of agents likely to enhance or suppress neural generators. We also recorded AMFRs locally at several stations along the auditory neuraxis. We conclude that the surface-recorded AMFR is indeed a composite response from multiple brain generators. Although the response at any modulation frequency can reflect the activity of more than one generator, the AMFRs to low and high modulation frequencies appear to reflect a strong contribution from cortical and subcortical sources, respectively.

scholarly journals Integration of vestibular and hindlimb inputs by vestibular nucleus neurons: Multisensory influences on postural control

2019 ◽  
Author(s):  
Derek M. Miller ◽  
Carey D. Balaban ◽  
Andrew A. McCall
Keyword(s):  
Single Unit ◽  
Goodness Of Fit ◽  
Temporal Dynamics ◽  
Balance Control ◽  
Vestibular Nucleus ◽  
Body Position ◽  
Additive Model ◽  
Whole Body ◽  
Body Rotation ◽  
Single Unit Recordings

1.AbstractWe recently demonstrated in both decerebrate and conscious cat preparations that hindlimb somatosensory inputs converge with vestibular afferent input onto neurons in multiple CNS locations that participate in balance control. While it is known that head position and limb state modulate postural reflexes, presumably through both vestibulospinal and reticulospinal pathways, the combined influence of the two inputs on the activity of neurons in these brainstem regions is unknown. In the present study, we evaluated the responses of vestibular nucleus (VN) neurons to vestibular and hindlimb stimuli delivered separately and together in conscious cats. We hypothesized that VN neuronal firing during activation of vestibular and limb proprioceptive inputs would be well-fit by an additive model. Extracellular single-unit recordings were obtained from neurons in the caudal aspects of the VN. Sinusoidal whole-body rotation in the roll plane was used as the search stimulus. Units responding to the search stimulus were tested for their responses to 10° ramp-and-hold roll body rotation, 10° extension hindlimb movement, and both movements delivered simultaneously. Composite response histograms were fit by a model of low and high pass filtered limb and body position signals using least squares nonlinear regression. We found that VN neuronal activity during combined vestibular and hindlimb proprioceptive stimulation in the conscious cat is well-fit by a simple additive model for signals with similar temporal dynamics. The mean R2 value for goodness of fit across all units was 0.74 ± 0.17. It is likely that VN neurons that exhibit these integrative properties participate in adjusting vestibulospinal outflow in response to limb state.New and NoteworthyVestibular nucleus neurons receive convergent information from hindlimb somatosensory inputs and vestibular inputs. In this study, extracellular single unit recordings of vestibular nucleus neurons during conditions of passively applied limb movement, passive whole-body rotations, and combined stimulation, were well fit by an additive model. The integration of hindlimb somatosensory inputs with vestibular inputs at the first stage of vestibular processing suggests vestibular nucleus neurons account for limb position in determining vestibulospinal responses to postural perturbations.

Implications of neural networks for how we think about brain function

1992 ◽  
Vol 15 (4) ◽  
pp. 644-655
Author(s):  
David A. Robinson
Keyword(s):  
Neural Networks ◽  
Control Systems ◽  
Brain Function ◽  
Single Unit ◽  
Task Complexity ◽  
The Other ◽  
Network Function ◽  
A Cell ◽  
Single Unit Recordings ◽  
The Brain

Abstract Engineers use neural networks to control systems too complex for conventional engineering solutions. To examine the behavior of individual hidden units would defeat the purpose of this approach because it would be largely uninterpretable. Yet neurophysiologists spend their careers doing just that! Hidden units contain bits and scraps of signals that yield only arcane hints about network function and no information about how its individual units process signals. Most literature on single-unit recordings attests to this grim fact. On the other hand, knowing a system's function and describing it with elegant mathematics tell one very little about what to expect of interneuronal behavior. Examples of simple networks based on neurophysiology are taken from the oculomotor literature to suggest how single-unit interpretability might decrease with increasing task complexity. It is argued that trying to explain how any real neural network works on a cell-by-cell, reductionist basis is futile and we may have to be content with trying to understand the brain at higher levels of organization.

scholarly journals Stereotypical modulations in dynamic functional connectivity explained by changes in BOLD variance

2017 ◽  
Author(s):  
Katharina Glomb ◽  
Adrián Ponce-Alvarez ◽  
Matthieu Gilson ◽  
Petra Ritter ◽  
Gustavo Deco
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Random Noise ◽  
Surrogate Data ◽  
Global Dynamics ◽  
Resting State Networks ◽  
Sliding Windows ◽  
Data Phase ◽  
Time Courses ◽  
The Brain

AbstractSpontaneous activity measured in human subject under the absence of any task exhibits complex patterns of correlation that largely correspond to large-scale functional topographies obtained with a wide variety of cognitive and perceptual tasks. These “resting state networks” (RSNs) fluctuate over time, forming and dissolving on the scale of seconds to minutes. While these fluctuations, most prominently those of the default mode network, have been linked to cognitive function, it remains unclear whether they result from random noise or whether they index a non-stationary process which could be described as state switching.In this study, we use a sliding windows-approach to relate temporal dynamics of RSNs to global modulations in correlation and BOLD variance. We compare empirical data, phase-randomized surrogate data, and data simulated with a stationary model. We find that RSN time courses exhibit a large amount of coactivation in all three cases, and that the modulations in their activity are closely linked to global dynamics of the underlying BOLD signal.We find that many properties of the observed fluctuations in FC and BOLD, including their ranges and their correlations amongst each other, are explained by fluctuations around the average FC structure. However, we also encounter interesting characteristics that are not explained in this way. In particular, we find that the brain spends more time in the troughs of modulations than can be expected from stationary dynamics.

scholarly journals Neural signatures of dynamic emotion constructs in the human brain

2017 ◽  
Author(s):  
Tijl Grootswagers ◽  
Briana L. Kennedy ◽  
Steven B. Most ◽  
Thomas A. Carlson
Keyword(s):  
Temporal Dynamics ◽  
Emotional Experience ◽  
Extended Period ◽  
Neural Representation ◽  
Discrete Emotions ◽  
Theoretical Understanding ◽  
Behavioral Ratings ◽  
Valence And Arousal ◽  
Multivariate Pattern ◽  
The Brain

AbstractHow is emotion represented in the brain: is it categorical or along dimensions? In the present study, we applied multivariate pattern analysis (MVPA) to magnetoencephalography (MEG) to study the brain’s temporally unfolding representations of different emotion constructs. First, participants rated 525 images on the dimensions of valence and arousal and by intensity of discrete emotion categories (happiness, sadness, fear, disgust, and sadness). Thirteen new participants then viewed subsets of these images within an MEG scanner. We used Representational Similarity Analysis (RSA) to compare behavioral ratings to the unfolding neural representation of the stimuli in the brain. Ratings of valence and arousal explained significant proportions of the MEG data, even after corrections for low-level image properties. Additionally, behavioral ratings of the discrete emotions fear, disgust, and happiness significantly predicted early neural representations, whereas rating models of anger and sadness did not. Different emotion constructs also showed unique temporal signatures. Fear and disgust – both highly arousing and negative – were rapidly discriminated by the brain, but disgust was represented for an extended period of time relative to fear. Overall, our findings suggest that 1) dimensions of valence and arousal are quickly represented by the brain, as are some discrete emotions, and 2) different emotion constructs exhibit unique temporal dynamics. We discuss implications of these findings for theoretical understanding of emotion and for the interplay of discrete and dimensional aspects of emotional experience.

scholarly journals Stability and flexibility in multisensory sampling: insights from perceptual illusions

2019 ◽  
Vol 121 (5) ◽  
pp. 1588-1590 ◽  
Author(s):  
Luca Casartelli
Keyword(s):  
Temporal Dynamics ◽  
Multisensory Processing ◽  
General Idea ◽  
Perceptual Illusions ◽  
The Brain ◽  
Multisensory Processes

Neural, oscillatory, and computational counterparts of multisensory processing remain a crucial challenge for neuroscientists. Converging evidence underlines a certain efficiency in balancing stability and flexibility of sensory sampling, supporting the general idea that multiple parallel and hierarchically organized processing stages in the brain contribute to our understanding of the (sensory/perceptual) world. Intriguingly, how temporal dynamics impact and modulate multisensory processes in our brain can be investigated benefiting from studies on perceptual illusions.

scholarly journals Duplicate Detection of Spike Events: A Relevant Problem in Human Single-Unit Recordings

2021 ◽  
Vol 11 (6) ◽  
pp. 761
Author(s):  
Gert Dehnen ◽  
Marcel S. Kehl ◽  
Alana Darcher ◽  
Tamara T. Müller ◽  
Jakob H. Macke ◽  
...  
Keyword(s):  
Data Quality ◽  
Single Unit ◽  
Human Subjects ◽  
External Noise ◽  
Hospital Environment ◽  
Noise Sources ◽  
Recording Channels ◽  
Waveform Similarity ◽  
Therapeutic Procedures ◽  
Single Unit Recordings

Single-unit recordings in the brain of behaving human subjects provide a unique opportunity to advance our understanding of neural mechanisms of cognition. These recordings are exclusively performed in medical centers during diagnostic or therapeutic procedures. The presence of medical instruments along with other aspects of the hospital environment limit the control of electrical noise compared to animal laboratory environments. Here, we highlight the problem of an increased occurrence of simultaneous spike events on different recording channels in human single-unit recordings. Most of these simultaneous events were detected in clusters previously labeled as artifacts and showed similar waveforms. These events may result from common external noise sources or from different micro-electrodes recording activity from the same neuron. To address the problem of duplicate recorded events, we introduce an open-source algorithm to identify these artificial spike events based on their synchronicity and waveform similarity. Applying our method to a comprehensive dataset of human single-unit recordings, we demonstrate that our algorithm can substantially increase the data quality of these recordings. Given our findings, we argue that future studies of single-unit activity recorded under noisy conditions should employ algorithms of this kind to improve data quality.

scholarly journals The brain timewise: how timing shapes and supports brain function

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Generative Models ◽  
Network Activity ◽  
Brain Diseases ◽  
Specific Information ◽  
Non Invasive ◽  
The Brain

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

A device enabling single unit recordings during head movements in cats

1982 ◽  
Vol 8 (4) ◽  
pp. 443-444 ◽  
Author(s):  
J.S. Schneider ◽  
A.A. Castaldi ◽  
T.I. Lidsky
Keyword(s):  
Single Unit ◽  
Head Movements ◽  
Single Unit Recordings

Single-unit recordings of arterial chemoreceptors from mouse petrosal ganglia in vitro

2000 ◽  
Vol 88 (4) ◽  
pp. 1489-1495 ◽  
Author(s):  
David F. Donnelly ◽  
Ricardo Rigual
Keyword(s):  
Mouse Model ◽  
Carotid Body ◽  
Unit Activity ◽  
Action Potentials ◽  
Single Unit ◽  
Gene Deletions ◽  
Suction Electrode ◽  
Single Unit Recordings ◽  
Unit Action

A preparation was developed that allows for the recording of single-unit chemoreceptor activity from mouse carotid body in vitro. An anesthetized mouse was decapitated, and each carotid body was harvested, along with the sinus nerve, glossopharyngeal nerve, and petrosal ganglia. After exposure to collagenase/trypsin, the cleaned complex was transferred to a recording chamber where it was superfused with oxygenated saline. The ganglia was searched for evoked or spontaneous unit activity by using a glass suction electrode. Single-unit action potentials were 57 ± 10 (SE) ( n = 16) standard deviations above the recording noise, and spontaneous spikes were generated as a random process. Decreasing superfusate[Formula: see text] to near 20 Torr caused an increase in spiking activity from 1.3 ± 0.4 to 14.1 ± 1.9 Hz ( n = 16). The use of mice for chemoreceptor studies may be advantageous because targeted gene deletions are well developed in the mouse model and may be useful in addressing unresolved questions regarding the mechanism of chemotransduction.

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