scholarly journals Hippocampal theta bursting and waveform shape reflect CA1 spiking patterns

2018 ◽  
Author(s):  
Scott Cole ◽  
Bradley Voytek
Keyword(s):  
Local Field ◽  
Pyramidal Neurons ◽  
Field Potential ◽  
Brain Regions ◽  
Neuronal Firing ◽  
Detectable Effect ◽  
Field Recordings ◽  
Cognitive States ◽  
Open Questions ◽  
Hippocampal Theta

AbstractBrain rhythms are nearly always analyzed in the spectral domain in terms of their power, phase, and frequency. While this conventional approach has uncovered spike-field coupling, as well as correlations to normal behaviors and pathological states, emerging work has highlighted the physiological and behavioral importance of multiple novel oscillation features. Oscillatory bursts, for example, uniquely index a variety of cognitive states, and the nonsinusoidal shape of oscillations relate to physiological changes, including Parkinson’s disease. Open questions remain regarding how bursts and nonsinusoidal features relate to circuit-level processes, and how they interrelate. By analyzing unit and local field recordings in the rodent hippocampus, we uncover a number of significant relationships between oscillatory bursts, nonsinusoidal waveforms, and local inhibitory and excitatory spiking patterns. Bursts of theta oscillations are surprisingly related to a decrease in pyramidal neuron synchrony, and have no detectable effect on firing sequences, despite significant increases in neuronal firing rates during periods of theta bursting. Theta burst duration is predicted by the asymmetries of its first cycle, and cycle asymmetries relate to firing rate, synchrony, and sequences of pyramidal neurons and interneurons. These results provide compelling physiological evidence that time-domain features, of both nonsinusoidal hippocampal theta waveform and the theta bursting state, reflects local circuit properties. These results point to the possibility of inferring circuit states from local field potential features in the hippocampus and perhaps other brain regions with other rhythms.

scholarly journals Optogenetic activation of SST-positive interneurons restores hippocampal theta oscillation impairment induced by soluble amyloid beta oligomersin vivo

2018 ◽  
Author(s):  
Hyowon Chung ◽  
Kyerl Park ◽  
Hyun Jae Jang ◽  
Michael M Kohl ◽  
Jeehyun Kwag
Keyword(s):  
Learning And Memory ◽  
Peak Power ◽  
Pyramidal Neurons ◽  
Hippocampal Slices ◽  
Field Potential ◽  
Theta Oscillations ◽  
Ca1 Pyramidal Neurons ◽  
Theta Frequency ◽  
Hippocampal Theta

AbstractAbnormal accumulation of amyloid β oligomers (AβO) is a hallmark of Alzheimer’s disease (AD), which leads to learning and memory deficits. Hippocampal theta oscillations that are critical in spatial navigation, learning and memory are impaired in AD. Since GABAergic interneurons, such as somatostatin-positive (SST+) and parvalbumin-positive (PV+) interneurons, are believed to play key roles in the hippocampal oscillogenesis, we asked whether AβO selectively impairs these SST+ and PV+ interneurons. To selectively manipulate SST+ or PV+ interneuron activity in mice with AβO pathologyin vivo, we co-injected AβO and adeno-associated virus (AAV) for expressing floxed channelrhodopsin-2 (ChR2) into the hippocampus of SST-Cre or PV-Cre mice. Local field potential (LFP) recordingsin vivoin these AβO–injected mice showed a reduction in the peak power of theta oscillations and desynchronization of spikes from CA1 pyramidal neurons relative to theta oscillations compared to those in control mice. Optogenetic-activation of SST+ but not PV+ interneurons in AβO–injected mice fully restored the peak power of theta oscillations and resynchronized the theta spike phases to a level observed in control mice.In vitrowhole-cell voltage-clamp recordings in CA1 pyramidal neurons in hippocampal slices treated with AβO revealed that short-term plasticity of SST+ interneuron inhibitory inputs to CA1 pyramidal neurons at theta frequency were selectively disrupted while that of PV+ interneuron inputs were unaffected. Together, our results suggest that dysfunction in inputs from SST+ interneurons to CA1 pyramidal neurons may underlie the impairment of theta oscillations observed in AβO-injected micein vivo.Our findings identify SST+ interneurons as a target for restoring theta-frequency oscillations in early AD.

scholarly journals The functional organization of human epileptic hippocampus

2016 ◽  
Vol 115 (6) ◽  
pp. 3140-3145 ◽  
Author(s):  
Petr Klimes ◽  
Juliano J. Duque ◽  
Ben Brinkmann ◽  
Jamie Van Gompel ◽  
Matt Stead ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Local Field ◽  
Medial Temporal Lobe ◽  
Slow Wave Sleep ◽  
Functional Organization ◽  
Spectral Power ◽  
Spatial Scales ◽  
Field Potential ◽  
Brain Regions ◽  
Behavioral State

The function and connectivity of human brain is disrupted in epilepsy. We previously reported that the region of epileptic brain generating focal seizures, i.e., the seizure onset zone (SOZ), is functionally isolated from surrounding brain regions in focal neocortical epilepsy. The modulatory effect of behavioral state on the spatial and spectral scales over which the reduced functional connectivity occurs, however, is unclear. Here we use simultaneous sleep staging from scalp EEG with intracranial EEG recordings from medial temporal lobe to investigate how behavioral state modulates the spatial and spectral scales of local field potential synchrony in focal epileptic hippocampus. The local field spectral power and linear correlation between adjacent electrodes provide measures of neuronal population synchrony at different spatial scales, ∼1 and 10 mm, respectively. Our results show increased connectivity inside the SOZ and low connectivity between electrodes in SOZ and outside the SOZ. During slow-wave sleep, we observed decreased connectivity for ripple and fast ripple frequency bands within the SOZ at the 10 mm spatial scale, while the local synchrony remained high at the 1 mm spatial scale. Further study of these phenomena may prove useful for SOZ localization and help understand seizure generation, and the functional deficits seen in epileptic eloquent cortex.

scholarly journals Large- and multi-scale networks in the rodent brain during novelty exploration

2020 ◽  
Author(s):  
Michael X Cohen ◽  
Bernhard Englitz ◽  
Arthur S C França
Keyword(s):  
Prefrontal Cortex ◽  
Parietal Cortex ◽  
Local Field ◽  
Neural Activity ◽  
Large Scale ◽  
Field Potential ◽  
Brain Regions ◽  
Data Availability ◽  
Data Matrix ◽  
Temporal Scales

AbstractNeural activity is coordinated across multiple spatial and temporal scales, and these patterns of coordination are implicated in both healthy and impaired cognitive operations. However, empirical cross-scale investigations are relatively infrequent, due to limited data availability and to the difficulty of analyzing rich multivariate datasets. Here we applied frequency-resolved multivariate source-separation analyses to characterize a large-scale dataset comprising spiking and local field potential activity recorded simultaneously in three brain regions (prefrontal cortex, parietal cortex, hippocampus) in freely-moving mice. We identified a constellation of multidimensional, inter-regional networks across a range of frequencies (2-200 Hz). These networks were reproducible within animals across different recording sessions, but varied across different animals, suggesting individual variability in network architecture. The theta band (~4-10 Hz) networks had several prominent features, including roughly equal contribution from all regions and strong inter-network synchronization. Overall, these findings demonstrate a multidimensional landscape of large-scale functional activations of cortical networks operating across multiple spatial, spectral, and temporal scales during open-field exploration.Significance statementNeural activity is synchronized over space, time, and frequency. To characterize the dynamics of large-scale networks spanning multiple brain regions, we recorded data from the prefrontal cortex, parietal cortex, and hippocampus in awake behaving mice, and pooled data from spiking activity and local field potentials into one data matrix. Frequency-specific multivariate decomposition methods revealed a cornucopia of neural networks defined by coherent spatiotemporal patterns over time. These findings reveal a rich, dynamic, and multivariate landscape of large-scale neural activity patterns during foraging behavior.

scholarly journals Weak representation of awake/sleep states by local field potentials in aged mice

2021 ◽  
Author(s):  
Daichi Konno ◽  
Yuji Ikegaya ◽  
Takuya Sasaki
Keyword(s):  
Local Field ◽  
Field Potential ◽  
Brain Regions ◽  
Machine Learning Algorithms ◽  
Network Activity ◽  
Aged Mice ◽  
Neuronal Network Activity ◽  
Induced Changes ◽  
Old Mice ◽  
Young Mice

Senescence affects various aspects of sleep, and it remains unclear how sleep-related neuronal network activity is altered by senescence. Here, we recorded local field potential signals from multiple brain regions covering the forebrain in young (10-week-old) and aged (2-year-old) mice. Interregional LFP correlations across these brain regions showed smaller differences between awake and sleep states in aged mice. Multivariate analyses with machine learning algorithms with uniform manifold approximation and projection (UMAP) and robust continuous clustering (RCC) demonstrated that these LFP correlational patterns in aged mice less represented awake/sleep states than those in young mice. By housing aged mice in an enriched environment, the LFP patterns were restored to those observed in young mice. Our results demonstrate senescence-induced changes in neuronal activity at the network level and provide insight into the prevention of pathological symptoms associated with sleep disturbance in senescence.

scholarly journals Modeling unitary fields and the single-neuron contribution to local field potentials in the hippocampus

2019 ◽  
Author(s):  
Maria Teleńczuk ◽  
Bartosz Teleńczuk ◽  
Alain Destexhe
Keyword(s):  
Local Field ◽  
Computational Models ◽  
Pyramidal Neurons ◽  
Field Potential ◽  
Pyramidal Cells ◽  
Inhibitory Synapses ◽  
Simple Method ◽  
Hippocampal Pyramidal Neurons

AbstractSynaptic currents represent a major contribution to the local field potential (LFP) in brain tissue, but the respective contribution of excitatory and inhibitory synapses is not known. Here, we provide estimates of this contribution by using computational models of hippocampal pyramidal neurons, constrained by in vitro recordings. We focus on the unitary LFP (uLFP) generated by single neurons in the CA3 region of the hippocampus. We first reproduce experimental results for hippocampal basket cells, and in particular how inhibitory uLFP are distributed within hippocampal layers. Next, we calculate the uLFP generated by pyramidal neurons, using morphologically-reconstructed CA3 pyramidal cells. The model shows that the excitatory uLFP is of small amplitude, smaller than inhibitory uLFPs. Indeed, when the two are simulated together, inhibitory uLFPs mask excitatory uLFPs, which might create the illusion that the inhibitory field is generated by pyramidal cells. These results provide an explanation for the observation that excitatory and inhibitory uLFPs are of the same polarity, in vivo and in vitro. These results also show that somatic inhibitory currents are large contributors of the LFP, which is important information to interpret this signal. Finally, the results of our model might form the basis of a simple method to compute the LFP, which could be applied to point neurons for each cell type, thus providing a simple biologically-grounded method to calculate LFPs from neural networks.

scholarly journals A kernel-based method to calculate local field potentials from networks of spiking neurons

2020 ◽  
Author(s):  
Bartosz Telenczuk ◽  
Maria Telenczuk ◽  
Alain Destexhe
Keyword(s):  
Local Field ◽  
Pyramidal Neurons ◽  
Field Potential ◽  
Point Of View ◽  
Spiking Neurons ◽  
Inhibitory Neurons ◽  
List Type ◽  
Synaptic Currents ◽  
Hippocampal Pyramidal Neurons ◽  
Low Pass

AbstractBackgroundThe local field potential (LFP) is usually calculated from current sources arising from transmembrane currents, in particular in asymmetric cellular morphologies such as pyramidal neurons.New methodHere, we adopt a different point of view and relate the spiking of neurons to the LFP through efferent synaptic connections and provide a method to calculate LFPs.ResultsWe show that the so-called unitary LFPs (uLFP) provide the key to such a calculation. We show experimental measurements and simulations of uLFPs in neocortex and hippocampus, for both excitatory and inhibitory neurons. We fit a “kernel” function to measurements of uLFPs, and we estimate its spatial and temporal spread by using simulations of morphologically detailed reconstructions of hippocampal pyramidal neurons. Assuming that LFPs are the sum of uLFPs generated by every neuron in the network, the LFP generated by excitatory and inhibitory neurons can be calculated by convolving the trains of action potentials with the kernels estimated from uLFPs. This provides a method to calculate the LFP from networks of spiking neurons, even for point neurons for which the LFP is not easily defined. We show examples of LFPs calculated from networks of point neurons and compare to the LFP calculated from synaptic currents.ConclusionsThe kernel-based method provides a practical way to calculate LFPs from networks of point neurons.HighlightsWe provide a method to estimate the LFP from spiking neuronsThis method is based on kernels, estimated from experimental dataWe show applications of this method to calculate the LFP from networks of spiking neuronsWe show that the kernel-based method is a low-pass filtered version of the LFP calculated from synaptic currents

scholarly journals Enhanced hippocampal theta rhythmicity and emergence of eta oscillation in virtual reality

2020 ◽  
Author(s):  
Karen Safaryan ◽  
Mayank R. Mehta
Keyword(s):  
Virtual Reality ◽  
Neural Activity ◽  
Pyramidal Neurons ◽  
Cell Layer ◽  
Field Potential ◽  
Theta Oscillations ◽  
Spatial Coding ◽  
Slow Oscillations ◽  
Hippocampal Theta ◽  
Local Field Potential Lfp

AbstractHippocampal theta oscillations in rodents profoundly impact neural activity, spatial coding, and synaptic plasticity and learning. What are the sensory mechanisms governing slow oscillations? We hypothesized that the nature of multisensory inputs is a crucial factor in hippocampal rhythmogenesis. We compared the rat hippocampal slow oscillations in the multisensory-rich real world (RW) and in a body-fixed, visual virtual reality (VR). The amplitude and rhythmicity of the hippocampal ~8 Hz theta were enhanced in VR compared to RW. This was accompanied by the emergence of a ~4 Hz oscillation, termed the eta rhythm, evident in the local field potential (LFP) in VR, but not in RW. Similar to theta, eta band amplitude increased with running speed in VR, but not in RW. However, contrary to theta, eta amplitude was highest in the CA1 cell layer, implicating intra-CA1 mechanisms. Consistently, putative CA1 interneurons, but not pyramidal neurons, showed substantially more eta modulation in VR than in RW. These results elucidate the multisensory mechanisms of hippocampal rhythms and the surprising effects of VR on enhancing these rhythms, which has not been achieved pharmacologically and has significant broader implications for VR use in humans.One Sentence SummaryNavigation in virtual reality greatly enhances hippocampal 8Hz theta rhythmicity, and generates a novel, ~4Hz eta rhythm that is localized in the CA1 cell layer and influences interneurons more than pyramidal neurons.

scholarly journals Primary sensorimotor cortex exhibits complex dependencies of spike-field coherence on neuronal firing rates, field power, and behavior

2018 ◽  
Vol 120 (1) ◽  
pp. 226-238 ◽  
Author(s):  
F. I. Arce-McShane ◽  
B. J. Sessle ◽  
C. F. Ross ◽  
N. G. Hatsopoulos
Keyword(s):  
Functional Connectivity ◽  
Firing Rate ◽  
Local Field ◽  
Sensorimotor Cortex ◽  
Field Potential ◽  
Neuronal Firing ◽  
Firing Rates ◽  
Linear Relationships ◽  
And Behavior ◽  
Field Coherence

Spike-field coherence (SFC) is widely used to assess cortico-cortical interactions during sensorimotor behavioral tasks by measuring the consistency of the relative phases between the spike train of a neuron and the concurrent local field potentials (LFPs). Interpretations of SFC as a measure of functional connectivity are complicated by theoretical work suggesting that estimates of SFC depend on overall neuronal activity. We evaluated the dependence of SFC on neuronal firing rates, LFP power, and behavior in the primary motor (MIo) and primary somatosensory (SIo) areas of the orofacial sensorimotor cortex of monkeys ( Macaca mulatta) during performance of a tongue-protrusion task. Although we occasionally observed monotonically increasing linear relationships between coherence and firing rate, we most often found highly complex, nonmonotonic relationships in both SIo and MIo and sometimes even found that coherence decreased with increasing firing rate. The lack of linear relationships was also true for both LFP power and tongue-protrusive force. Moreover, the ratio between maximal firing rate and the firing rate at peak coherence deviated significantly from unity, indicating that MIo and SIo neurons achieved maximal SFC at a submaximal level of spiking. Overall, these results point to complex relationships of SFC to firing rates, LFP power, and behavior during sensorimotor cortico-cortical interactions: coherence is a measure of functional connectivity whose magnitude is not a mere monotonic reflection of changes in firing rate, LFP power, or the relevantly controlled behavioral parameter. NEW & NOTEWORTHY The concern that estimates of spike-field coherence depend on the firing rates of single neurons has influenced analytical methods employed by experimental studies investigating the functional interactions between cortical areas. Our study shows that the overwhelming majority of the estimated spike-field coherence exhibited complex relations with firing rates of neurons in the orofacial sensorimotor cortex. The lack of monotonic relations was also evident after testing the influence of local field potential power and force on spike-field coherence.

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