scholarly journals Dissociation of broadband high-frequency activity and neuronal firing in the neocortex

2019 ◽  
Author(s):  
Marcin Leszczynski ◽  
Annamaria Barczak ◽  
Yoshinao Kajikawa ◽  
Istvan Ulbert ◽  
Arnaud Falchier ◽  
...  
Keyword(s):  
High Frequency ◽  
Field Potential ◽  
Bimodal Distribution ◽  
Neuronal Population ◽  
Superficial Layer ◽  
Blood Oxygenation ◽  
Neuronal Firing ◽  
Neural Firing ◽  
Action Potential Firing ◽  
High Frequency Activity

Broadband High-frequency Activity (BHA; 70-150 Hz), also known as "high gamma," a key analytic signal in human intracranial recordings is often assumed to reflect local neural firing (multiunit activity; MUA). Accordingly, BHA has been used to study neuronal population responses in auditory (1,2), visual (3,4), language (5), mnemonic processes (6-9) and cognitive control (10,11). BHA is arguably the electrophysiological measure best correlated with the Blood Oxygenation Level Dependent (BOLD) signal in fMRI (12-13). However, beyond the fact that BHA correlates with neuronal spiking (12, 14-16), the neuronal populations and physiological processes generating BHA are not precisely defined. Although critical for interpreting intracranial signals in human and non-human primates, the precise physiology of BHA remains unknown. Here, we show that BHA dissociates from MUA in primary visual and auditory cortex. Using laminar multielectrode data in monkeys, we found a bimodal distribution of stimulus-evoked BHA across depth of a cortical column: an early-deep, followed by a later-superficial layer response. Only, the early-deep layer BHA had a clear local MUA correlate, while the more prominent superficial layer BHA had a weak or undetectable MUA correlate. In many cases, particularly in V1 (70%), supragranular sites showed strong BHA in lieu of any detectable increase in MUA. Due to volume conduction, BHA from both the early-deep and the later-supragranular generators contribute to the field potential at the pial surface, though the contribution may be weighted towards the late-supragranular BHA. Our results demonstrate that the strongest generators of BHA are in the superficial cortical layers and show that the origins of BHA include a mixture of the neuronal action potential firing and dendritic processes separable from this firing. It is likely that the typically-recorded BHA signal emphasizes the latter processes to a greater extent than previously recognized.

scholarly journals Dissociation of broadband high-frequency activity and neuronal firing in the neocortex

2020 ◽  
Vol 6 (33) ◽  
pp. eabb0977 ◽  
Author(s):  
Marcin Leszczyński ◽  
Annamaria Barczak ◽  
Yoshinao Kajikawa ◽  
Istvan Ulbert ◽  
Arnaud Y. Falchier ◽  
...  
Keyword(s):  
High Frequency ◽  
Analytic Signal ◽  
Neuronal Firing ◽  
Neural Firing ◽  
Cortical Layers ◽  
Pial Surface ◽  
High Gamma ◽  
High Frequency Activity ◽  
Physiological Substrates ◽  
Temporal Overlap

Broadband high-frequency activity (BHA; 70 to 150 Hz), also known as “high gamma,” a key analytic signal in human intracranial (electrocorticographic) recordings, is often assumed to reflect local neural firing [multiunit activity (MUA)]. As the precise physiological substrates of BHA are unknown, this assumption remains controversial. Our analysis of laminar multielectrode data from V1 and A1 in monkeys outlines two components of stimulus-evoked BHA distributed across the cortical layers: an “early-deep” and “late-superficial” response. Early-deep BHA has a clear spatial and temporal overlap with MUA. Late-superficial BHA was more prominent and accounted for more of the BHA signal measured near the cortical pial surface. However, its association with local MUA is weak and often undetectable, consistent with the view that it reflects dendritic processes separable from local neuronal firing.

scholarly journals Emergence of Narrowband High Frequency Oscillations from Asynchronous, Uncoupled Neural Firing

2016 ◽  
Vol 27 (01) ◽  
pp. 1650049 ◽  
Author(s):  
Stephen V. Gliske ◽  
William C. Stacey ◽  
Eugene Lim ◽  
Katherine A. Holman ◽  
Christian G. Fink
Keyword(s):  
High Frequency ◽  
Feedback Inhibition ◽  
Experimental Studies ◽  
Field Potential ◽  
Epileptic Seizures ◽  
Spike Timing ◽  
Normal Brain ◽  
Neural Firing ◽  
Similar Frequency ◽  
High Frequency Oscillations

Previous experimental studies have demonstrated the emergence of narrowband local field potential oscillations during epileptic seizures in which the underlying neural activity appears to be completely asynchronous. We derive a mathematical model explaining how this counterintuitive phenomenon may occur, showing that a population of independent, completely asynchronous neurons may produce narrowband oscillations if each neuron fires quasi-periodically, without requiring any intrinsic oscillatory cells or feedback inhibition. This quasi-periodicity can occur through cells with similar frequency–current ([Formula: see text]–[Formula: see text]) curves receiving a similar, high amount of uncorrelated synaptic noise. Thus, this source of oscillatory behavior is distinct from the usual cases (pacemaker cells entraining a network, or oscillations being an inherent property of the network structure), as it requires no oscillatory drive nor any specific network or cellular properties other than cells that repetitively fire with continual stimulus. We also deduce bounds on the degree of variability in neural spike-timing which will permit the emergence of such oscillations, both for action potential- and postsynaptic potential-dominated LFPs. These results suggest that even an uncoupled network may generate collective rhythms, implying that the breakdown of inhibition and high synaptic input often observed during epileptic seizures may generate narrowband oscillations. We propose that this mechanism may explain why so many disparate epileptic and normal brain mechanisms can produce similar high frequency oscillations.

scholarly journals Phase-tuned neuronal firing encodes human contextual representations for navigational goals

2017 ◽  
Author(s):  
Andrew J Watrous ◽  
Jonathan Miller ◽  
Salman E Qasim ◽  
Itzhak Fried ◽  
Joshua Jacobs
Keyword(s):  
Firing Rate ◽  
Medial Temporal Lobe ◽  
Single Neuron ◽  
Detection Algorithm ◽  
Neuronal Firing ◽  
Neural Firing ◽  
Categorical Information ◽  
High Frequency Activity ◽  
Oscillation Detection ◽  
Intracranial Recordings

AbstractWe previously demonstrated that the phase of oscillations modulates neural activity representing categorical information using human intracranial recordings and high-frequency activity from local field potentials (Watrous et al., 2015b). We extend these findings here using human single-neuron recordings during a navigation task. We identify neurons in the medial temporal lobe with firing-rate modulations for specific navigational goals, as well as for navigational planning and goal arrival. Going beyond this work, using a novel oscillation detection algorithm, we identify phase-locked neural firing that encodes information about a person’s prospective navigational goal in the absence of firing rate changes. These results provide evidence for navigational planning and contextual accounts of human MTL function at the single-neuron level. More generally, our findings identify phase-coded neuronal firing as a component of the human neural code.

scholarly journals Dynamics of high-frequency synchronization during seizures

2013 ◽  
Vol 109 (10) ◽  
pp. 2423-2437 ◽  
Author(s):  
Giri P. Krishnan ◽  
Gregory Filatov ◽  
Maxim Bazhenov
Keyword(s):  
High Frequency ◽  
Epileptiform Activity ◽  
Epileptic Seizures ◽  
Temporal Analysis ◽  
Neuronal Firing ◽  
Extracellular Potassium ◽  
Epileptiform Discharges ◽  
Baseline Activity ◽  
High Frequency Activity

Pathological synchronization of neuronal firing is considered to be an inherent property of epileptic seizures. However, it remains unclear whether the synchrony increases for the high-frequency multiunit activity as well as for the local field potentials (LFPs). We present spatio-temporal analysis of synchronization during epileptiform activity using wide-band (up to 2,000 Hz) spectral analysis of multielectrode array recordings at up to 60 locations throughout the mouse hippocampus in vitro. Our study revealed a prominent structure of LFP profiles during epileptiform discharges, triggered by elevated extracellular potassium, with characteristic distribution of current sinks and sources with respect to anatomical structure. The cross-coherence of high-frequency activity (500–2,000 Hz) across channels was reduced during epileptic bursts compared with baseline activity and showed the opposite trend for lower frequencies. Furthermore, the magnitude of cross-coherence during epileptiform activity was dependent on distance: electrodes closer to the epileptic foci showed increased cross-coherence and electrodes further away showed reduced cross-coherence for high-frequency activity. These experimental observations were re-created and supported in a computational model. Our study suggests that different intrinsic and synaptic processes can mediate paroxysmal synchronization at low, medium, and high frequencies.

scholarly journals Ripples reflect a spectrum of synchronous spiking activity in human anterior temporal lobe

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Ai Phuong S Tong ◽  
Alex P Vaz ◽  
John H Wittig ◽  
Sara K Inati ◽  
Kareem A Zaghloul
Keyword(s):  
Temporal Lobe ◽  
High Frequency ◽  
Temporal Cortex ◽  
Field Potential ◽  
Human Memory ◽  
Dynamic Coordination ◽  
Macro Scale ◽  
High Frequency Activity ◽  
Fast Oscillations ◽  
Spiking Activity

Direct brain recordings have provided important insights into how high frequency activity captured through intracranial EEG (iEEG) supports human memory retrieval. The extent to which such activity is comprised of transient fluctuations that reflect the dynamic coordination of underlying neurons, however, remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that fast oscillations within the previously identified 80-120 Hz ripple band contribute to 70-200 Hz high frequency activity in the human cortex. These ripple oscillations exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human temporal lobe is organized into transient bouts of ripple oscillations that reflect underlying bursts of spiking activity.

scholarly journals Cortical ripples provide the conditions for consolidation during NREM sleep in humans

2021 ◽  
Author(s):  
Charles W Dickey ◽  
Ilya A Verzhbinsky ◽  
Xi Jiang ◽  
Burke Q Rosen ◽  
Sophie Kajfez ◽  
...  
Keyword(s):  
Memory Consolidation ◽  
High Frequency ◽  
Activity Patterns ◽  
Nrem Sleep ◽  
Spike Timing ◽  
Neuronal Firing ◽  
Human Cortex ◽  
Firing Patterns ◽  
High Frequency Activity ◽  
Intracranial Recordings

Hippocampal ripples index the reconstruction of spatiotemporal neuronal firing patterns essential for the consolidation of memories in the cortex during non-rapid eye movement (NREM) sleep. However, it is not known whether ripples are generated in the human cortex during sleep. Here, using human intracranial recordings, we show that ~70ms long ~80Hz ripples are ubiquitous in all regions of the cortex during NREM sleep as well as waking. During waking, cortical ripples occur on local high frequency activity peaks. During sleep, cortical ripples occur during spindles on the down-to-upstate transition, with unit-firing patterns consistent with generation by pyramidal-interneuron feedback. Cortical ripples mark the recurrence of spatiotemporal activity patterns from preceding waking, and they group co-firing within the window of spike-timing-dependent plasticity. Thus, cortical ripples guided by sequential sleep waves may facilitate memory consolidation during NREM sleep in humans.

scholarly journals Phase-tuned neuronal firing encodes human contextual representations for navigational goals

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Andrew J Watrous ◽  
Jonathan Miller ◽  
Salman E Qasim ◽  
Itzhak Fried ◽  
Joshua Jacobs
Keyword(s):  
Firing Rate ◽  
Medial Temporal Lobe ◽  
Single Neuron ◽  
Detection Algorithm ◽  
Neuronal Firing ◽  
Neural Firing ◽  
Categorical Information ◽  
High Frequency Activity ◽  
Oscillation Detection ◽  
Intracranial Recordings

We previously demonstrated that the phase of oscillations modulates neural activity representing categorical information using human intracranial recordings and high-frequency activity from local field potentials (Watrous et al., 2015b). We extend these findings here using human single-neuron recordings during a virtual navigation task. We identify neurons in the medial temporal lobe with firing-rate modulations for specific navigational goals, as well as for navigational planning and goal arrival. Going beyond this work, using a novel oscillation detection algorithm, we identify phase-locked neural firing that encodes information about a person’s prospective navigational goal in the absence of firing rate changes. These results provide evidence for navigational planning and contextual accounts of human MTL function at the single-neuron level. More generally, our findings identify phase-coded neuronal firing as a component of the human neural code.

scholarly journals High-frequency oscillations are prominent in the extended amygdala

2014 ◽  
Vol 112 (1) ◽  
pp. 110-119 ◽  
Author(s):  
Darrell Haufler ◽  
Denis Pare
Keyword(s):  
High Frequency ◽  
Slow Wave Sleep ◽  
Paradoxical Sleep ◽  
Field Potential ◽  
Neuronal Firing ◽  
Lateral Septum ◽  
Subcortical Structures ◽  
Bed Nucleus ◽  
Extended Amygdala ◽  
Cycle Basis

Previously, it was reported that various cortical and subcortical structures display high-frequency local field potential (LFP) oscillations in the 110- to 160-Hz range (HFOs), distinct from sharp-wave ripples. In the present study, we characterize HFOs in the extended amygdala. Rats were implanted with tetrode bundles in the bed nucleus of the stria terminalis (BNST), central amygdala (CeA), as well as adjacent regions (pallidum, caudate-putamen, and lateral septum). At all recorded sites, HFO power showed a systematic dependence on behavioral state: highest during quiet wakefulness, intermediate during paradoxical sleep, and lowest during active waking or slow-wave sleep. CO2 asphyxiation as well as anesthesia with isoflurane or urethane abolished HFOs. HFOs stood out relative to all other fast-frequency LFP components because they were highly coherent between distant sites of the extended amygdala, ipsi- and contralaterally. HFOs affected neuronal firing in two ways: firing rate could vary as a function of HFO power (rate modulation) or HFOs could entrain firing on a cycle-to-cycle basis (phase modulation). The incidence of phase-modulated neurons was about twice higher in BNST and CeA (20–40%) than in adjacent regions (≤8%). Among BNST and CeA neurons, many more were phase-modulated than rate-modulated, although about half of the latter were also phase-modulated. Overall, these results indicate that HFOs entrain the activity of a high proportion of neurons in the extended amygdala. A major challenge for future studies will be to identify the mechanisms supporting the high coherence of HFOs within and across hemispheres.

scholarly journals Dissociation of Broadband High-Frequency Activity and Neuronal Firing in the Neocortex

2019 ◽  
Author(s):  
Marcin Leszczynski ◽  
Annamaria Barczak ◽  
Yoshinao Kajikawa ◽  
Istvan Ulbert ◽  
Arnaud Y. Falchier ◽  
...  
Keyword(s):  
High Frequency ◽  
Neuronal Firing ◽  
High Frequency Activity

scholarly journals A deep convolutional visual encoding model of neuronal responses in the LGN

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly
Keyword(s):  
Firing Rate ◽  
Visual Information ◽  
Visual Stimulation ◽  
Neuronal Population ◽  
Neuronal Firing ◽  
Electrode Arrays ◽  
Deep Convolutional Neural Networks ◽  
Firing Rates ◽  
Spatiotemporal Representation

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

Sign in / Sign up

Export Citation Format

Share Document