Fluctuations In Cortical Activity Research Articles

Spontaneous Spiking Is Governed by Broadband Fluctuations.

Populations of cortical neurons generate rhythmic fluctuations in their ongoing spontaneous activity. These fluctuations can be seen in the local field potential (LFP), which reflects summed return currents from synaptic activity in the local population near a recording electrode. The LFP is spectrally broad, and many researchers view this breadth as containing many narrowband oscillatory components that may have distinct functional roles. This view is supported by the observation that the phase of narrowband oscillations is often correlated with cortical excitability and can relate to the timing of spiking activity and the fidelity of sensory evoked responses. Accordingly, researchers commonly tune in to these channels by narrowband filtering the LFP. Alternatively, neural activity may be fundamentally broadband and composed of transient, nonstationary rhythms that are difficult to approximate as oscillations. In this view, the instantaneous state of the broad ensemble relates directly to the excitability of the local population with no particular allegiance to any frequency band. To test between these alternatives, we asked whether the spiking activity of neocortical neurons in marmoset of either sex is better aligned with the phase of the LFP within narrow frequency bands or with a broadband measure. We find that the phase of broadband LFP fluctuations provides a better predictor of spike timing than the phase after filtering in narrow bands. These results challenge the view of the neocortex as a system composed of narrowband oscillators and supports a view in which neural activity fluctuations are intrinsically broadband.SIGNIFICANCE STATEMENT Research into the dynamical state of neural populations often attributes unique significance to the state of narrowband oscillatory components. However, rhythmic fluctuations in cortical activity are nonstationary and broad spectrum. We find that the timing of spontaneous spiking activity is better captured by the state of broadband fluctuations over any latent oscillatory component. These results suggest narrowband interpretations of rhythmic population activity may be limited, and broader representations may provide higher fidelity in describing moment-to-moment fluctuations in cortical activity.

Spontaneous travelling cortical waves gate perception in behaving primates.

Perceptual sensitivity varies from moment to moment. One potential source of variability is spontaneous fluctuations in cortical activity that can travel as a wave1. Spontaneous traveling waves have been reported during anesthesia2–7, but it is not known whether spontaneous traveling waves play a role during waking perception. Using newly developed analytic techniques to characterize the moment-to-moment dynamics of noisy multielectrode data, we find spontaneous waves of activity in extrastriate visual cortex of awake, behaving marmosets (Callithrix jacchus). In monkeys trained to detect faint visual targets, the timing and position of spontaneous traveling waves, prior to target onset, predict the magnitude of target-evoked activity and the likelihood of target detection. In contrast, spatially disorganized fluctuations of neural activity are much less predictive. These results reveal an important role for spontaneous traveling waves in sensory processing through modulating neural and perceptual sensitivity.

"Fast" versus "slow" word integration of visual and olfactory objects: EEG biomarkers of decision speed variability.

In psychological experiments, behavioral speed varies across trials, and this variation is often associated with corresponding fluctuations in cortical activity. Little is known about such cortical variations in semantic priming tasks where target words are matched with preceding sensory object cues. Here, two visually presented target words ("pear" and "lilac") were repeatedly cued by corresponding odors or pictures, and the participants were to indicate matching or nonmatching combinations. Data were split in behaviorally "fast" versus "slow" trials. We hypothesized that slow trials would be associated with higher prestimulus alpha activity and reduced ERP amplitudes, and that response-time differences between odor-cued and picture-cued trials would be especially large in slow behavioral trials. Results confirmed that slow trials showed increased alpha-band activity prior to word target onset, as well as amplitude decreases in the sensory P1 and semantic N400 components. However, no interactions between cue-modality and processing speed were observed. Instead, odor-cue integration responses were uniquely delayed on incongruent trials, a novel behavioral effect that was not observed in EEG measures. The results show that semantic integration speed is reflected in cortical activity before and during stimulus processing. Behavioral interactions with cue modality did not correspond to observed cortical activity changes, perhaps because olfactory circuits are not readily observed in scalp-recorded EEG. We conclude that combining behavioral speed variability and cortical EEG measures is useful in understanding the fluctuating nature of cognitive processing sequences. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Pre-stimulus theta power is correlated with variation of motor evoked potential latency: a single-pulse TMS study

There has been a growing interest in the role of pre-stimulus oscillations on cortical excitability in visual and motor systems. Prior studies focused on the relationship between pre-stimulus neuronal activity and TMS-evoked motor evoked potentials (MEPs) have reported heterogeneous results. We aimed to assess the role of pre-stimulus neural activity on the latency of MEPs, which might enhance our understanding of the variability of MEP signals, and potentially provide information on the role played by cortical activity fluctuations in the excitability of corticospinal pathways. Near-threshold single-pulse TMS (spTMS) was applied at random intervals over the primary motor cortex of 14 healthy participants while they sat passively, to trigger hand muscle contractions. Multichannel EEG was recorded during spTMS blocks. Spearman correlations between both the variation in MEP onset latencies and peak-to-peak MEP amplitudes, and the pre-stimulus power of EEG oscillations were calculated across participants. We found that the variation in MEP latency was positively correlated with pre-stimulus power in the theta range (4-7Hz) in a broad time window (- 3.1 to - 1.9s) preceding the spTMS generating the MEP. No correlation between pre-stimulus power in any frequency band and MEP amplitude was found. Our results show that pre-stimulus theta oscillations are correlated with the variation in MEP latency, an outcome measure determined by fiber conduction velocity and synaptic delays along the corticospinal tract. This finding could prove useful for clinicians using MEP latency-based information in pre- or intra-operative diagnostics of corticospinal impairment.

Influence of vigilance on resting state brain activity

Aims: Despite task absence the brain remains functionally and metabolically active exhibiting coherent activity in characteristic sets of brain regions, called resting state networks (RSN). RSN manifest as correlation patterns in “spontaneous” BOLD signal fluctuations with 10–100 s period [1]. Their origins remain obscure. Typically, in a wake resting state experiment data stems from subjects resting with eyes closed in the MRI scanner for ~10 min [2]. Hypothesis: We hypothesized that in resting state experiments subjects do not maintain constant wakefulness but that (1) the temporal profiles of RSN are influenced by fluctuations in vigilance and (2) cortical activity fluctuations by subcortical brain activity [3]. Method: We studied 55 non sleep-deprived German subjects with EEG-fMRI under above-mentioned conditions. Vigilance throughout the experiment was scored [4]. Next, a support vector machine classifier was trained to perform sleep staging [5] based on RSN functional connectivity matrices and applied to an independent resting state fMRI data set of 76 Chinese subjects [6]. Results: 50% of the 55 subjects did not maintain steady wakefulness until minute 5, vigilance state switches occurred up to a rate of 1/min. Sleep stage classifier performance was 87%, and results could be reproduced in the independent data set (“Chinese”). Excluding the thalamus from the classification procedure resulted in poorer (<70%) sleep scoring performance. Conclusion: 1. changes in vigilance occur at a similar temporal scale as that of RSN fluctuations. 2. RSN configuration is sleep stage specific and highly dependent on thalamic activity. 4. In classical resting state experiments up to 50% of the subjects do not maintain steady wakefulness for beyond 5 minutes. When proposing RSN differences as biomarkers for diseases [7], vigilance bias between patient (e.g. resulting from drugs, encephalopathy, age) and control groups needs to be controlled for. Literatur: 1. Fox, M.D. and M.E. Raichle, Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci, 2007. 8(9): p. 700-11. 2. Van Dijk, K.R., et al., Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. Journal of neurophysiology, 2010. 103(1): p. 297-321. 3. Friston, K., Functional and Effective Connectivity in Neuroimaging: A Synthesis. Hum Brain Mapp, 1996. 2: p. 56-68. 4. AASM, The AASM Manual for the Scoring of Sleep and Associated Events- Rules, Terminology and Technical Specifications. 2007, Chicago: American Academy of Sleep Medicine. 5. Crisler, S., et al., Sleep-stage scoring in the rat using a support vector machine. Journal of neuroscience methods, 2008. 168(2): p. 524-34. 6. Biswal, B.B., et al., Toward discovery science of human brain function. Proceedings of the National Academy of Sciences of the United States of America, 2010. 107(10): p. 4734-9. 7. Greicius, M., Resting-state functional connectivity in neuropsychiatric disorders. Curr Opin Neurol, 2008. 21(4): p. 424-30. Funding: Bundesministerium fur Bildung und Forschung (grant 01 EV 0703) and Landes-Offensive zur Entwicklung Wissenschaftlich-okonomischer Exzellenz (LOEWE, Neuronale Koordination Forschungsschwerpunkt Frankfurt).

Modelling general anaesthesia as a first-order phase transition in the cortex

Since 1997 we have been developing a theoretical foundation for general anaesthesia. We have been able to demonstrate that the abrupt change in brain state brought on by anaesthetic drugs can be characterized as a first-order phase transition in the population-average membrane voltage of the cortical neurons. The theory predicts that, as the critical point of phase change into unconsciousness is approached, the electrical fluctuations in cortical activity will grow strongly in amplitude while slowing in frequency, becoming more correlated both in time and in space. Thus the bio-electrical change of brain-state has deep similarities with thermodynamic phase changes of classical physics. The theory further predicts the existence of a second critical point, hysteretically separated from the first, corresponding to the return path from comatose unconsciousness back to normal responsiveness. There is a steadily accumulating body of clinical evidence in support of all of the phase-transition predictions: low-frequency power surge in EEG activity; increased correlation time and correlation length in EEG fluctuations; hysteresis separation, with respect to drug concentration, between the point of induction and the point of emergence.

Cellular Mechanisms Contributing to Response Variability of Cortical NeuronsIn Vivo

Cortical neurons recorded in vivo exhibit highly variable responses to the repeated presentation of the same stimulus. To further understand the cellular mechanisms underlying this phenomenon, we performed intracellular recordings from neurons in cat striate cortex in vivo and examined the relationships between spontaneous activity and visually evoked responses. Activity was assessed on a trial-by-trial basis by measuring the membrane potential (Vm) fluctuations and spike activity during brief epochs immediately before and after the onset of an evoked response. We found that the response magnitude, expressed as a change in Vm relative to baseline, was linearly correlated with the preceding spontaneous Vm. This correlation was enhanced when the cells were hyperpolarized to reduce the activation of voltage-gated conductances. The output of the cells, expressed as spike counts and latencies, was only moderately correlated with fluctuations in the preceding spontaneous Vm. Spike-triggered averaging of Vm revealed that visually evoked action potentials arise from transient depolarizations having a rise time of approximately 10 msec. Consistent with this, evoked spike count was found to be linearly correlated with the magnitude of Vm fluctuations in the gamma (20-70 Hz) frequency band. We also found that the threshold of visually evoked action potentials varied over a range of approximately 10 mV. Examination of simultaneously recorded intracellular and extracellular activity revealed a correlation between Vm depolarization and spike discharges in adjacent cells. Together these results demonstrate that response variability is attributable largely to coherent fluctuations in cortical activity preceding the onset of a stimulus, but also to variations in action potential threshold and the magnitude of high-frequency fluctuations evoked by the stimulus.