23 research outputs found

    A computational study on altered theta-gamma coupling during learning and phase coding

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    There is considerable interest in the role of coupling between theta and gamma oscillations in the brain in the context of learning and memory. Here we have used a neural network model which is capable of producing coupling of theta phase to gamma amplitude firstly to explore its ability to reproduce reported learning changes and secondly to memory-span and phase coding effects. The spiking neural network incorporates two kinetically different GABAA receptor-mediated currents to generate both theta and gamma rhythms and we have found that by selective alteration of both NMDA receptors and GABAA,slow receptors it can reproduce learning-related changes in the strength of coupling between theta and gamma either with or without coincident changes in theta amplitude. When the model was used to explore the relationship between theta and gamma oscillations, working memory capacity and phase coding it showed that the potential storage capacity of short term memories, in terms of nested gamma-subcycles, coincides with the maximal theta power. Increasing theta power is also related to the precision of theta phase which functions as a potential timing clock for neuronal firing in the cortex or hippocampus

    Remodeling of cholinergic input to the hippocampus after noise exposure and tinnitus induction in Guinea pigs

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    Here, we investigate remodeling of hippocampal cholinergic inputs after noise exposure and determine the relevance of these changes to tinnitus. To assess the effects of noise exposure on the hippocampus, guinea pigs were exposed to unilateral noise for 2 hr and 2 weeks later, immunohistochemistry was performed on hippocampal sections to examine vesicular acetylcholine transporter (VAChT) expression. To evaluate whether the changes in VAChT were relevant to tinnitus, another group of animals was exposed to the same noise band twice to induce tinnitus, which was assessed using gap‐prepulse Inhibition of the acoustic startle (GPIAS) 12 weeks after the first noise exposure, followed by immunohistochemistry. Acoustic Brainstem Response (ABR) thresholds were elevated immediately after noise exposure for all experimental animals but returned to baseline levels several days after noise exposure. ABR wave I amplitude‐intensity functions did not show any changes after 2 or 12 weeks of recovery compared to baseline levels. In animals assessed 2‐weeks following noise‐exposure, hippocampal VAChT puncta density decreased on both sides of the brain by 20–60% in exposed animals. By 12 weeks following the initial noise exposure, changes in VAChT puncta density largely recovered to baseline levels in exposed animals that did not develop tinnitus, but remained diminished in animals that developed tinnitus. These tinnitus‐specific changes were particularly prominent in hippocampal synapse‐rich layers of the dentate gyrus and areas CA3 and CA1, and VAChT density in these regions negatively correlated with tinnitus severity. The robust changes in VAChT labeling in the hippocampus 2 weeks after noise exposure suggest involvement of this circuitry in auditory processing. After chronic tinnitus induction, tinnitus‐specific changes occurred in synapse‐rich layers of the hippocampus, suggesting that synaptic processing in the hippocampus may play an important role in the pathophysiology of tinnitus.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150542/1/hipo23058.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150542/2/hipo23058_am.pd

    With long intervals, inter-stimulus interval is the critical determinant of P300 amplitude

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    Contains fulltext : 64376.pdf (publisher's version ) (Closed access)Previous research, using short inter-stimulus intervals (1-4 s), suggests that the P300 of the human event-related potential during oddball and single-stimulus tasks is mainly affected by target-to-target interval (TTI). The present study tested the validity of this claim at longer intervals in a learning task. Participants were assigned to either an oddball task with an inter-stimulus interval (ISI) of 9-20 s or a single-stimulus task with an ISI of 9-20 or 40-90 s and had to learn when to respond to the stimuli. In the oddball task, the target elicited larger amplitudes than did the standard. When comparing the stimuli from the short- and long-ISI conditions with the target from the oddball condition, it was found that the P300 was more positive at long-ISI stimuli than at short-ISI stimuli or oddball targets, and short-ISI stimuli and oddball targets elicited equally large P300 amplitudes. These results suggest that, in oddball tasks with long intervals, besides cognitive factors, ISI rather than TTI affects the P300 amplitude

    EEG gamma frequency and sleep–wake scoring in mice: Comparing two types of supervised classifiers

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    There is growing interest in sleep research and increasing demand for screening of circadian rhythms in genetically modified animals. This requires reliable sleep stage scoring programs. Present solutions suffer, however, from the lack of flexible adaptation to experimental conditions and unreliable selection of stage-discriminating variables. EEG was recorded in freely moving C57BL/6 mice and different sets of frequency variables were used for analysis. Parameters included conventional power spectral density functions as well as period-amplitude analysis. Manual staging was compared with the performance of two different supervised classifiers, linear discriminant analysis (LDA) and Classification Tree. Gamma activity was particularly high during REM (rapid eye movements) sleep and waking. Four out of 73 variables were most effective for sleep–wake stage separation: amplitudes of upper gamma-, delta- and upper theta-frequency bands and neck muscle EMG. Using small sets of training data, LDA produced better results than Classification Tree or a conventional threshold formula. Changing epoch duration (4 to 10 s) had only minor effects on performance with 8 to 10 s yielding the best results. Gamma and upper theta activity during REM sleep is particularly useful for sleep–wake stage separation. Linear discriminant analysis performs best in supervised automatic staging procedures. Reliable semi-automatic sleep scoring with LDA substantially reduces analysis time

    DECONcert: Making Waves with Water, EEG, and Music

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    Selective entrainment of gamma subbands by different slow network oscillations

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    Theta oscillations (4–12 Hz) are thought to provide a common temporal reference for the exchange of information among distant brain networks. On the other hand, faster gamma-frequency oscillations (30–160 Hz) nested within theta cycles are believed to underlie local information processing. Whether oscillatory coupling between global and local oscillations, as showcased by theta-gamma coupling, is a general coding mechanism remains unknown. Here, we investigated two different patterns of oscillatory network activity, theta and respiration-induced network rhythms, in four brain regions of freely moving mice: olfactory bulb (OB), prelimbic cortex (PLC), parietal cortex (PAC), and dorsal hippocampus [cornu ammonis 1 (CA1)]. We report differential state- and region-specific coupling between the slow large-scale rhythms and superimposed fast oscillations. During awake immobility, all four regions displayed a respiration-entrained rhythm (RR) with decreasing power from OB to CA1, which coupled exclusively to the 80- to 120-Hz gamma subband (γ2). During exploration, when theta activity was prevailing, OB and PLC still showed exclusive coupling of RR with γ2 and no thetagamma coupling, whereas PAC and CA1 switched to selective coupling of theta with 40- to 80-Hz (γ1) and 120- to 160-Hz (γ3) gamma subbands. Our data illustrate a strong, specific interaction between neuronal activity patterns and respiration. Moreover, our results suggest that the coupling between slow and fast oscillations is a general brain mechanism not limited to the theta rhythm
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