scholarly journals Two distinctive stages of novelty processing revealed by high-density EEG based source imaging

2021 ◽  
Author(s):  
Eric Tsang ◽  
RUI SUN ◽  
Xueyan Niu ◽  
Wei Yan Renee Fung ◽  
Akaysha C. Tang
Keyword(s):  
Neural Activity ◽  
Novelty Detection ◽  
Brain Regions ◽  
High Density ◽  
Two Stage ◽  
Source Imaging ◽  
Theta Power ◽  
P300 Component ◽  
Power Increase ◽  
Novelty Processing

Novelty detection is an evolutionarily significant and ancient function as well as a relatively stable function whose early life status marks for long-term developmental outcomes and predicts a range of adult functions. While various brain regions have been shown to respond to environmental novelty, how different brain regions coordinate in novelty related information processing remains under-explored. Here using a combination of high-density EEG, second order blind identification (SOBI), and a standard visual oddball task, we test, in humans, a two-stage novelty processing hypothesis which states that two distinct stages of novelty processing exist, one involves early-occurring domain-specific neural activity in the sensory processing areas of the brain and the other involves later-occurring domain-general neural activity involving brain regions beyond the sensory cortices. We found that: (1) a significant Novelty effect (oddball effects) not only in the SOBI-recovered Late component (P300 component) but also in the Early component (N150 visual) offering first EEG evidence for oddball effect in the sensory domain; (2) a significant Stage (Early vs Late) by Frequency (delta, theta, alpha, beta, and gamma) interaction effect indicating two functionally dissociable mechanisms underlying novelty detection; (3) a significantly shorter latency in odd-ball related theta power increase in the Early visual than in the late P300 component. These results not only offer support for the two-stage novelty processing theory but also provide new evidence for an early involvement of theta power increase in the novelty processing.

scholarly journals Neural substrates of propranolol-induced impairments in the reconsolidation of nicotine-associated memories in smokers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao Lin ◽  
Jiahui Deng ◽  
Kai Yuan ◽  
Qiandong Wang ◽  
Lin Liu ◽  
...  
Keyword(s):  
Neural Activity ◽  
Neural Substrates ◽  
Brain Regions ◽  
Reward Processing ◽  
Memory Reconsolidation ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Postcentral Gyrus ◽  
Propranolol Group ◽  
Propranolol Administration

AbstractThe majority of smokers relapse even after successfully quitting because of the craving to smoking after unexpectedly re-exposed to smoking-related cues. This conditioned craving is mediated by reward memories that are frequently experienced and stubbornly resistant to treatment. Reconsolidation theory posits that well-consolidated memories are destabilized after retrieval, and this process renders memories labile and vulnerable to amnestic intervention. This study tests the retrieval reconsolidation procedure to decrease nicotine craving among people who smoke. In this study, 52 male smokers received a single dose of propranolol (n = 27) or placebo (n = 25) before the reactivation of nicotine-associated memories to impair the reconsolidation process. Craving for smoking and neural activity in response to smoking-related cues served as primary outcomes. Functional magnetic resonance imaging was performed during the memory reconsolidation process. The disruption of reconsolidation by propranolol decreased craving for smoking. Reactivity of the postcentral gyrus in response to smoking-related cues also decreased in the propranolol group after the reconsolidation manipulation. Functional connectivity between the hippocampus and striatum was higher during memory reconsolidation in the propranolol group. Furthermore, the increase in coupling between the hippocampus and striatum positively correlated with the decrease in craving after the reconsolidation manipulation in the propranolol group. Propranolol administration before memory reactivation disrupted the reconsolidation of smoking-related memories in smokers by mediating brain regions that are involved in memory and reward processing. These findings demonstrate the noradrenergic regulation of memory reconsolidation in humans and suggest that adjunct propranolol administration can facilitate the treatment of nicotine dependence. The present study was pre-registered at ClinicalTrials.gov (registration no. ChiCTR1900024412).

Analysis on control methods of two-stage positioning for high-density optical disk mastering

2005 ◽  
Author(s):  
Quanhong Shen ◽  
Peijun Jiang ◽  
Guosheng Qi ◽  
Duanyi Xu ◽  
Jie Song
Keyword(s):  
Optical Disk ◽  
High Density ◽  
Control Methods ◽  
Two Stage

scholarly journals Dissociable oscillatory networks support gain and loss processing in human orbitofrontal cortex

2021 ◽  
Author(s):  
Ignacio Saez ◽  
Jack Lin ◽  
Edward Chang ◽  
Josef Parvizi ◽  
Robert T. Knight ◽  
...  
Keyword(s):  
Neural Activity ◽  
Orbitofrontal Cortex ◽  
Low Frequency ◽  
Brain Regions ◽  
Reward Processing ◽  
Neural Oscillations ◽  
Beta Band ◽  
Neuronal Ensembles ◽  
Gain And Loss

AbstractHuman neuroimaging and animal studies have linked neural activity in orbitofrontal cortex (OFC) to valuation of positive and negative outcomes. Additional evidence shows that neural oscillations, representing the coordinated activity of neuronal ensembles, support information processing in both animal and human prefrontal regions. However, the role of OFC neural oscillations in reward-processing in humans remains unknown, partly due to the difficulty of recording oscillatory neural activity from deep brain regions. Here, we examined the role of OFC neural oscillations (<30Hz) in reward processing by combining intracranial OFC recordings with a gambling task in which patients made economic decisions under uncertainty. Our results show that power in different oscillatory bands are associated with distinct components of reward evaluation. Specifically, we observed a double dissociation, with a selective theta band oscillation increase in response to monetary gains and a beta band increase in response to losses. These effects were interleaved across OFC in overlapping networks and were accompanied by increases in oscillatory coherence between OFC electrode sites in theta and beta band during gain and loss processing, respectively. These results provide evidence that gain and loss processing in human OFC are supported by distinct low-frequency oscillations in networks, and provide evidence that participating neuronal ensembles are organized functionally through oscillatory coherence, rather than local anatomical segregation.

scholarly journals Multi-shanks SiNAPS Active Pixel Sensor CMOS probe: 1024 simultaneously recording channels for high-density intracortical brain mapping

2019 ◽  
Author(s):  
Fabio Boi ◽  
Nikolas Perentos ◽  
Aziliz Lecomte ◽  
Gerrit Schwesig ◽  
Stefano Zordan ◽  
...  
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Brain Area ◽  
Large Population ◽  
Brain Structures ◽  
High Density ◽  
Single Neurons ◽  
Electrode Arrays ◽  
Unit Recording ◽  
Recording Channels

AbstractThe advent of implantable active dense CMOS neural probes opened a new era for electrophysiology in neuroscience. These single shank electrode arrays, and the emerging tailored analysis tools, provide for the first time to neuroscientists the neurotechnology means to spatiotemporally resolve the activity of hundreds of different single-neurons in multiple vertically aligned brain structures. However, while these unprecedented experimental capabilities to study columnar brain properties are a big leap forward in neuroscience, there is the need to spatially distribute electrodes also horizontally. Closely spacing and consistently placing in well-defined geometrical arrangement multiple isolated single-shank probes is methodologically and economically impractical. Here, we present the first high-density CMOS neural probe with multiple shanks integrating thousand’s of closely spaced and simultaneously recording microelectrodes to map neural activity across 2D lattice. Taking advantage from the high-modularity of our electrode-pixels-based SiNAPS technology, we realized a four shanks active dense probe with 256 electrode-pixels/shank and a pitch of 28 µm, for a total of 1024 simultaneously recording channels. The achieved performances allow for full-band, whole-array read-outs at 25 kHz/channel, show a measured input referred noise in the action potential band (300-7000 Hz) of 6.5 ± 2.1µVRMS, and a power consumption <6 µW/electrode-pixel. Preliminary recordings in awake behaving mice demonstrated the capability of multi-shanks SiNAPS probes to simultaneously record neural activity (both LFPs and spikes) from a brain area >6 mm2, spanning cortical, hippocampal and thalamic regions. High-density 2D array enables combining large population unit recording across distributed networks with precise intra- and interlaminar/nuclear mapping of the oscillatory dynamics. These results pave the way to a new generation of high-density and extremely compact multi-shanks CMOS-probes with tunable layouts for electrophysiological mapping of brain activity at the single-neurons resolution.

scholarly journals Locus Coeruleus to Paraventricular Thalamus Projections Facilitate Emergence From Isoflurane Anesthesia in Mice

2021 ◽  
Vol 12 ◽  
Author(s):  
Yawen Ao ◽  
Bo Yang ◽  
Caiju Zhang ◽  
Bo Wu ◽  
Xuefen Zhang ◽  
...  
Keyword(s):  
Locus Coeruleus ◽  
Neural Activity ◽  
Brain Regions ◽  
Cortical Arousal ◽  
Emergence Time ◽  
General Anesthetic ◽  
Common Pathway ◽  
Isoflurane Anesthesia ◽  
New Strategy ◽  
Paraventricular Thalamus

Locus coeruleus (LC) sends widespread outputs to many brain regions to modulate diverse functions, including sleep/wake states, attention, and the general anesthetic state. The paraventricular thalamus (PVT) is a critical thalamic area for arousal and receives dense tyrosine-hydroxylase (TH) inputs from the LC. Although anesthesia and sleep may share a common pathway, it is important to understand the processes underlying emergence from anesthesia. In this study, we hypothesize that LC TH neurons and the TH:LC-PVT circuit may be involved in regulating emergence from anesthesia. Only male mice are used in this study. Here, using c-Fos as a marker of neural activity, we identify LC TH expressing neurons are active during anesthesia emergence. Remarkably, chemogenetic activation of LC TH neurons shortens emergence time from anesthesia and promotes cortical arousal. Moreover, enhanced c-Fos expression is observed in the PVT after LC TH neurons activation. Optogenetic activation of the TH:LC-PVT projections accelerates emergence from anesthesia, whereas, chemogenetic inhibition of the TH:LC-PVT circuit prolongs time to wakefulness. Furthermore, optogenetic activation of the TH:LC-PVT projections produces electrophysiological evidence of arousal. Together, these results demonstrate that activation of the TH:LC-PVT projections is helpful in facilitating the transition from isoflurane anesthesia to an arousal state, which may provide a new strategy in shortening the emergence time after general anesthesia.

scholarly journals Imaging of neural oscillations with embedded inferential and group prevalence statistics

2017 ◽  
Author(s):  
Peter W. Donhauser ◽  
Esther Florin ◽  
Sylvain Baillet
Keyword(s):  
Brain Activity ◽  
Signal Strength ◽  
Brain Regions ◽  
Oscillatory Activity ◽  
Neural Oscillations ◽  
Source Reconstruction ◽  
Signal To Noise ◽  
Source Imaging ◽  
Methodological Challenges ◽  
Oscillatory Power

AbstractMagnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. Imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges1. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.Author summaryThe oscillatory activity of the brain produces a repertoire of signal dynamics that is rich and complex. Noninvasive recording techniques such as scalp magnetoencephalography and electroencephalography (MEG, EEG) are key methods to advance our comprehension of the role played by neural oscillations in brain functions and dysfunctions. Yet, there are methodological challenges in mapping these elusive components of brain activity that have remained unresolved. We introduce a new mapping technique, called imaging with embedded statistics (iES), which alleviates these difficulties. With iES, signal detection is constrained explicitly to the operational hypotheses of the study design. We show, in a variety of experimental contexts, how iES emphasizes the oscillatory components of brain activity, if any, that match the experimental hypotheses, even in deeper brain regions where signal strength is expected to be weak in MEG. Overall, the proposed method is a new imaging tool to respond to a wide range of neuroscience questions concerning the scaffolding of brain dynamics via anatomically-distributed neural oscillations.

Abstract WMP117: Regional Homogeneity Changes In Patients With Transient Ischemic Attack: A Resting-state Functional Magnetic Resonance Imaging Study

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Jian Guo ◽  
Ning Chen ◽  
Muke Zhou ◽  
Pian Wang ◽  
Li He
Keyword(s):  
Transient Ischemic Attack ◽  
Neural Activity ◽  
Resting State ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Imaging Study ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Anterior Cingulate ◽  
Ischemic Attack

Background: Transient ischemic attack (TIA) can increase the risk of some neurologic dysfunctions, of which the mechanism remains unclear. Resting-state functional MRI (rfMRI) is suggested to be a valuable tool to study the relation between spontaneous brain activity and behavioral performance. However, little is known about whether the local synchronization of spontaneous neural activity is altered in TIA patients. The purpose of this study is to detect differences in regional spontaneous activities throughout the whole brain between TIAs and normal controls. Methods: Twenty one TIA patients suffered an ischemic event in the right hemisphere and 21 healthy volunteers were enrolled in the study. All subjects were investigated using cognitive tests and rfMRI. The regional homogeneity (ReHo) was calculate and compared between two groups. Then a correlation analysis was performed to explore the relationship between ReHo values of brain regions showing abnormal resting-state properties and clinical variables in TIA group. Results: Compared with controls, TIA patients exhibited decreased ReHo in right dorsolateral prefrontal cortex (DLPFC), right inferior prefrontal gyrus, right ventral anterior cingulate cortex and right dorsal posterior cingular cortex. Moreover, the mean ReHo in right DLPFC and right inferior prefrontal gyrus were significantly correlated with MoCA in TIA patients. Conclusions: Neural activity in the resting state is changed in patients with TIA. The positive correlation between regional homogeneity of rfMRI and cognition suggests that ReHo may be a promising tool to better our understanding of the neurobiological consequences of TIA.

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