scholarly journals Microscale physiological events on the human cortical surface

2019 ◽  
Author(s):  
Angelique C. Paulk ◽  
Jimmy C. Yang ◽  
Daniel R. Cleary ◽  
Daniel J. Soper ◽  
Milan Halgren ◽  
...  
Keyword(s):  
Rhythmic Activity ◽  
Human Cognition ◽  
Discrete Events ◽  
Population Activity ◽  
Neuronal Populations ◽  
Ultrahigh Density ◽  
Human Participants ◽  
Electrical Stimuli ◽  
Aggregate Population ◽  
Somatic Action Potentials

AbstractDespite ongoing advancements in our understanding of the local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their ‘intermediate’ microscale local circuit dynamics. Here, we utilized ultrahigh density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper layers of the grey matter. They were also observed in rodents, non-human primates, and semi-chronic recordings in humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that with the proper combination of high resolution microelectrodes and analytic techniques it is possible to capture neuronal dynamics that lay between somatic action potentials and aggregate population activity and that understanding these intermediate microscale dynamics may reveal important details of the full circuit behavior in human cognition.

scholarly journals Inference of a Mesoscopic Population Model from Population Spike Trains

2020 ◽  
Vol 32 (8) ◽  
pp. 1448-1498 ◽  
Author(s):  
Alexandre René ◽  
André Longtin ◽  
Jakob H. Macke
Keyword(s):  
Population Model ◽  
Single Neuron ◽  
Simulated Data ◽  
Population Data ◽  
Model Parameters ◽  
Population Activity ◽  
Mcmc Sampling ◽  
Wide Range ◽  
Low Dimensional ◽  
Aggregate Population

Understanding how rich dynamics emerge in neural populations requires models exhibiting a wide range of behaviors while remaining interpretable in terms of connectivity and single-neuron dynamics. However, it has been challenging to fit such mechanistic spiking networks at the single-neuron scale to empirical population data. To close this gap, we propose to fit such data at a mesoscale, using a mechanistic but low-dimensional and, hence, statistically tractable model. The mesoscopic representation is obtained by approximating a population of neurons as multiple homogeneous pools of neurons and modeling the dynamics of the aggregate population activity within each pool. We derive the likelihood of both single-neuron and connectivity parameters given this activity, which can then be used to optimize parameters by gradient ascent on the log likelihood or perform Bayesian inference using Markov chain Monte Carlo (MCMC) sampling. We illustrate this approach using a model of generalized integrate-and-fire neurons for which mesoscopic dynamics have been previously derived and show that both single-neuron and connectivity parameters can be recovered from simulated data. In particular, our inference method extracts posterior correlations between model parameters, which define parameter subsets able to reproduce the data. We compute the Bayesian posterior for combinations of parameters using MCMC sampling and investigate how the approximations inherent in a mesoscopic population model affect the accuracy of the inferred single-neuron parameters.

scholarly journals Primary motor cortex activity traces distinct trajectories of population dynamics during spontaneous facial motor sequences in mice

2021 ◽  
Author(s):  
Juan Carlos Boffi ◽  
Tristan Wiessalla ◽  
Robert Prevedel
Keyword(s):  
Population Dynamics ◽  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Neuronal Population ◽  
Future Research ◽  
Sequencing Analysis ◽  
Population Activity ◽  
Neuronal Populations ◽  
Custom Made ◽  
Facial Area

AbstractWe explore the link between on-going neuronal activity at primary motor cortex (M1) and face movement in awake mice. By combining custom-made behavioral sequencing analysis and fast volumetric Ca2+-imaging, we simultaneously tracked M1 population activity during many different facial motor sequences. We show that a facial area of M1 displays distinct trajectories of neuronal population dynamics across different spontaneous facial motor sequences, suggesting an underlying population dynamics code.Significance statementHow our brain controls a seemingly limitless diversity of body movements remains largely unknown. Recent research brings new light into this subject by showing that neuronal populations at the primary motor cortex display different dynamics during forelimb reaching movements versus grasping, which suggests that different motor sequences could be associated with distinct motor cortex population dynamics. To explore this possibility, we designed an experimental paradigm for simultaneously tracking the activity of neuronal populations in motor cortex across many different motor sequences. Our results support the concept that distinct population dynamics encode different motor sequences, bringing new insight into the role of motor cortex in sculpting behavior while opening new avenues for future research.

scholarly journals Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system

2019 ◽  
Author(s):  
Arjen Stolk ◽  
Loek Brinkman ◽  
Mariska J. Vansteensel ◽  
Erik Aarnoutse ◽  
Frans S. S. Leijten ◽  
...  
Keyword(s):  
Sensorimotor Cortex ◽  
Rhythmic Activity ◽  
Neuronal Population ◽  
Imagery Task ◽  
Beta Band ◽  
Neuronal Populations ◽  
Band Power ◽  
Movement Selection ◽  
Spatiotemporal Coordination ◽  
Phase Relationships

AbstractThis study uses electrocorticography in humans to assess how alpha- and beta-band rhythms modulate excitability of the sensorimotor cortex during movement selection, as indexed through a psychophysically-controlled movement imagery task. Both rhythms displayed effector-specific modulations, tracked spectral markers of action potentials in the local neuronal population, and showed spatially systematic phase relationships (traveling waves). Yet, alpha- and beta-band rhythms differed in their anatomical and functional properties, were weakly correlated, and traveled along opposite directions across the sensorimotor cortex. Increased alpha-band power in the somatosensory cortex ipsilateral to the selected arm was associated with spatially-unspecific inhibition. Decreased beta-band power over contralateral motor cortex was associated with a focal shift from relative inhibition to excitation. These observations indicate the relevance of both inhibition and disinhibition mechanisms for precise spatiotemporal coordination of neuronal populations during movement selection. Those mechanisms are implemented through the substantially different neurophysiological properties of sensorimotor alpha- and beta-band rhythms.

scholarly journals Tagging active neurons by soma-targeted Cal-Light

2021 ◽  
Author(s):  
Jung Ho Hyun ◽  
Kenichiro Nagahama ◽  
Ho Namkung ◽  
Neymi Mignocchi ◽  
Patrick Hannan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Action Potentials ◽  
Choice Behavior ◽  
Signal To Noise Ratio ◽  
Temporal Precision ◽  
Neuronal Populations ◽  
Cell Type Specific ◽  
Lever Pressing ◽  
Interaction Behaviors ◽  
Somatic Action Potentials

Verifying causal effects of neural circuits is essential for proving direct a circuit-behavior relationship. However, techniques for tagging only active neurons with high spatiotemporal precision remain at the beginning stages. Here we developed the soma-targeted Cal-Light (ST-Cal-Light) which selectively converts somatic calcium rise triggered by action potentials into gene expression. Such modification simultaneously increases the signal-to-noise ratio (SNR) of reporter gene expression and reduces the light requirement for successful labeling. Because of the enhanced efficacy, the ST-Cal-Light enables the tagging of functionally engaged neurons in various forms of behaviors, including context-dependent fear conditioning, lever-pressing choice behavior, and social interaction behaviors. We also targeted kainic acid-sensitive neuronal populations in the hippocampus which subsequently suppressed seizure symptoms, suggesting its applicability in controlling disease-related neurons. Furthermore, the generation of a conditional ST-Cal-Light knock-in (KI) mouse provides an opportunity to tag active neurons in a region- or cell-type specific manner via crossing with other Cre-driver lines. Thus, the versatile ST-Cal-Light system links somatic action potentials to behaviors with high temporal precision, and ultimately allows functional circuit dissection at a single cell resolution.

scholarly journals Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Arjen Stolk ◽  
Loek Brinkman ◽  
Mariska J Vansteensel ◽  
Erik Aarnoutse ◽  
Frans SS Leijten ◽  
...  
Keyword(s):  
Sensorimotor Cortex ◽  
Rhythmic Activity ◽  
Neuronal Population ◽  
Beta Band ◽  
Neuronal Populations ◽  
Band Power ◽  
Spatiotemporal Coordination ◽  
Contralateral Motor ◽  
Relative Inhibition ◽  
Phase Relationships

This study uses electrocorticography in humans to assess how alpha- and beta-band rhythms modulate excitability of the sensorimotor cortex during psychophysically-controlled movement imagery. Both rhythms displayed effector-specific modulations, tracked spectral markers of action potentials in the local neuronal population, and showed spatially systematic phase relationships (traveling waves). Yet, alpha- and beta-band rhythms differed in their anatomical and functional properties, were weakly correlated, and traveled along opposite directions across the sensorimotor cortex. Increased alpha-band power in the somatosensory cortex ipsilateral to the selected arm was associated with spatially-unspecific inhibition. Decreased beta-band power over contralateral motor cortex was associated with a focal shift from relative inhibition to excitation. These observations indicate the relevance of both inhibition and disinhibition mechanisms for precise spatiotemporal coordination of movement-related neuronal populations, and illustrate how those mechanisms are implemented through the substantially different neurophysiological properties of sensorimotor alpha- and beta-band rhythms.

Introduction to Research with Human Participants

2021 ◽  
Author(s):  
Carl H. Coleman
Keyword(s):  
The United States ◽  
Legal Framework ◽  
Human Cognition ◽  
The European Union ◽  
Medical Interventions ◽  
Policy Interventions ◽  
Investigational Drugs ◽  
Human Participants ◽  
And Behavior ◽  
The Impact

Research with human participants is conducted for a variety of reasons, including developing drugs, medical devices, or other medical interventions; understanding human cognition and behavior; and evaluating the impact of public policy interventions. It can provide enormous social benefits, but it also raises significant ethical dilemmas. These dilemmas stem from a tension that is inherent in the nature of the activity: the goal is to generate knowledge for the potential benefit of persons in the future, but achieving this goal often requires exposing individuals in the present to the possibility of harm. This tension is particularly pronounced in clinical trials involving investigational drugs, devices, or other medical interventions, where the risks of participation may be particularly significant. The chapter presents a brief sketch of the legal framework surrounding research with human participants in two important centers of research: the United States and the European Union.

Minor Contribution of Principal Excitatory Pathways to Hippocampal LFPs in the Anesthetized Rat: A Combined Independent Component and Current Source Density Study

2010 ◽  
Vol 104 (1) ◽  
pp. 484-497 ◽  
Author(s):  
A. Korovaichuk ◽  
J. Makarova ◽  
V. A. Makarov ◽  
N. Benito ◽  
O. Herreras
Keyword(s):  
Time Course ◽  
Specific Activity ◽  
Current Source ◽  
Current Source Density ◽  
Independent Component ◽  
Synaptic Activity ◽  
Population Activity ◽  
Neuronal Populations ◽  
Source Density ◽  
Sparse Population

Analysis of local field potentials (LFPs) helps understand the function of the converging neuronal populations that produce the mixed synaptic activity in principal cells. Recently, using independent component analysis (ICA), we resolved ongoing hippocampal activity into several major contributions of stratified LFP-generators. Here, using pathway-specific LFP reconstruction, we isolated LFP-generators that describe the activity of Schaffer-CA1 and Perforant-Dentate excitatory inputs in the anesthetized rat. First, we applied ICA and current source density analysis to LFPs evoked by electrical subthreshold stimulation of the pathways. The results showed that pathway specific activity is selectively captured by individual components or LFP-generators. Each generator matches the known distribution of axonal terminal fields in the hippocampus and recovers the specific time course of their activation. Second, we use sparse weak electrical stimulation to prime ongoing LFPs with activity of a known origin. Decomposition of ongoing LFPs yields a few significant LFP-generators with distinct spatiotemporal characteristics for the Schaffer and Perforant inputs. Both pathways convey an irregular temporal pattern in bouts of population activity of varying amplitude. Importantly, the contribution of Schaffer and Perforant inputs to the power of raw LFPs in the hippocampus is minor (7 and 5%, respectively). The results support the hypothesis on a sparse population code used by excitatory populations in the entorhino-hippocampal system, and they validate the separation of LFP-generators as a powerful tool to explore the computational function of neuronal circuits in real time.

scholarly journals On the structure of population activity under fluctuations in attentional state

2015 ◽  
Author(s):  
Alexander S Ecker ◽  
George H Denfield ◽  
Matthias Bethge ◽  
Andreas S Tolias
Keyword(s):  
Simple Model ◽  
Limited Range ◽  
Neural Response ◽  
Response Modulation ◽  
Attentional State ◽  
Population Activity ◽  
Neuronal Populations ◽  
Correlated Activity ◽  
State Affect ◽  
Structure Of Population

Attention is commonly thought to improve behavioral performance by increasing response gain and suppressing shared variability in neuronal populations. However, both the focus and the strength of attention are likely to vary from one experimental trial to the next, thereby inducing response variability unknown to the experimenter. Here we study analytically how fluctuations in attentional state affect the structure of population responses in a simple model of spatial and feature attention. In our model, attention acts on the neural response exclusively by modulating each neuron's gain. Neurons are conditionally independent given the stimulus and the attentional gain, and correlated activity arises only from trial-to-trial fluctuations of the attentional state, which are unknown to the experimenter. We find that this simple model can readily explain many aspects of neural response modulation under attention, such as increased response gain, reduced individual and shared variability, increased correlations with firing rates, limited range correlations, and differential correlations. We therefore suggest that attention may act primarily by increasing response gain of individual neurons without affecting their correlation structure. The experimentally observed reduction in correlations may instead result from reduced variability of the attentional gain when a stimulus is attended. Moreover, we show that attentional gain fluctuations – even if unknown to a downstream readout – do not impair the readout accuracy despite inducing limited-range correlations.

scholarly journals Human electrocorticography reveals a common neurocognitive pathway for mentalizing about the self and others

2021 ◽  
Author(s):  
Kevin Tan ◽  
Amy Daitch ◽  
Pedro Pinheiro-Chagas ◽  
Kieran Fox ◽  
Josef Parvizi ◽  
...  
Keyword(s):  
Social Cognitive ◽  
Response Times ◽  
Human Subjects ◽  
Neuronal Population ◽  
Spatiotemporal Resolution ◽  
Population Activity ◽  
Psychological Traits ◽  
Self And Other ◽  
Neuronal Populations ◽  
The Social

Abstract Hundreds of neuroimaging studies show that mentalizing (i.e., theory of mind) recruits default mode network (DMN) regions with remarkable consistency. Nevertheless, the social-cognitive functions of individual DMN regions remain unclear, perhaps due to the limited spatiotemporal resolution of neuroimaging. We used electrocorticography (ECoG) to record neuronal population activity while 16 human subjects judged the psychological traits of themselves and others. Self- and other-mentalizing recruited near-identical neuronal populations in a common spatiotemporal sequence: activations were earliest in visual cortex, followed by temporoparietal DMN regions, and finally medial prefrontal cortex. Critically, regions with later activations showed greater functional specificity for mentalizing, greater self/other differentiation, and stronger associations with behavioral response times. Moreover, other-mentalizing evoked slower and lengthier activations than self-mentalizing across successive DMN regions, suggesting temporally extended demands on higher-level processes. Our results reveal a common neurocognitive pathway for self- and other-mentalizing that follows a hierarchy of functional specialization across DMN regions.

scholarly journals Evidence for the rhythmic perceptual sampling of auditory scenes

2019 ◽  
Author(s):  
Christoph Kayser
Keyword(s):  
Time Scale ◽  
Temporal Structure ◽  
Rhythmic Activity ◽  
Acoustic Information ◽  
Electrophysiological Recordings ◽  
Delta Band ◽  
Human Participants ◽  
Auditory Scenes ◽  
The Brain ◽  
Perceptual Weights

AbstractConverging results suggest that perception is controlled by rhythmic processes in the brain. In the auditory domain, neuroimaging studies show that the perception of brief sounds is shaped by rhythmic activity prior to the stimulus and electrophysiological recordings have linked delta band (1-2 Hz) activity to the functioning of individual neurons. These results have promoted theories of rhythmic modes of listening and generally suggest that the perceptually relevant encoding of acoustic information is structured by rhythmic processes along auditory pathways. A prediction from this perspective – which so far has not been tested – is that such rhythmic processes also shape how acoustic information is combined over time to judge extended soundscapes. The present study was designed to directly test this prediction. Human participants judged the overall change in perceived frequency content in temporally extended (1.2 to 1.8 s) soundscapes, while the perceptual use of the available sensory evidence was quantified using psychophysical reverse correlation. Model-based analysis of individual participant’s perceptual weights revealed a rich temporal structure, including linear trends, a U-shaped profile tied to the overall stimulus duration, and importantly, rhythmic components at the time scale of 1 to 2Hz. The collective evidence found here across four versions of the experiment supports the notion that rhythmic processes operating on the delta band time scale structure how perception samples temporally extended acoustic scenes.

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