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Psarou, E.

Publications and source records attributed to Psarou, E..

7 recordsLinked to original sources

Surprising effects of stimulus repetition on neuronal firing rates and gamma-band synchronization in awake macaque V1

Stimulus repetition is abundant, because the environment is redundant and/or because it is redundantly sampled. This offers an opportunity to optimize the processing of repeated stimuli. Indeed, stimulus repetition leads to classically described neuronal response decreases, and to more recently described neuronal gamma synchronization increases (sometimes preceded by decreases for a few trials). Here, we used a full-screen colored background (FSCB) and a flashed black bar, while recording multi-unit activity (MUA) and local field potentials (LFP) from area V1 of an awake macaque monkey. We found that the FSCB repetition induced neuronal response increases (sometimes preceded by decreases for a few trials) and gamma synchronization decreases (preceded by increases for a few trials). These effects are largely opposite to the dominant previous findings. Intriguingly, these surprising effects reversed when we isolated the responses to the flashed black bar. We discuss these findings, considering differences to previous studies with regards to the subject of the study, the stimuli and the task. We notice that in studies reporting classical results for gamma, sometimes in combination with firing rates, the stimuli were typically (partly) predictive of the reward. Here, we found non-classical results for the FSCB that was not reward predictive, and classical results for the black bar that was reward predictive. Whether this has revealed a general effect of reward predictive versus non-predictive stimuli will require further investigation with stimuli and task designs tailored specifically for this question. SignificanceNatural visual experience often entails repetitions of the same stimulus. This allows optimization of the brains processing of those stimuli. Indeed, repeated stimuli typically induce decreasing firing rates and increasing gamma-band synchronization in many visual areas. However, in this study in awake macaque primary visual cortex, we report surprising opposite effects: under some conditions, stimulus repetition can result in neuronal firing rate increases and gamma-band synchronization decreases. We argue that these effects might relate to the fact that the repeated stimulus was not predictive of a reward. In fact, when we isolated the responses to a second stimulus that was added later in each trial and that was predictive of reward, the effects reverted again to the typical pattern.

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Repetition-related gamma plasticity in macaque V1 and V2 is highly stimulus specific and robust to stimulus set size

When a visual stimulus is repeated, the cortex has the opportunity to adjust its processing. Indeed, repeated stimuli induce reduced neuronal spike rates and increased neuronal gamma-band synchronization. Previous studies found the repetition-related gamma increase to occur both in human and non-human primates, for artificial and natural stimuli, to persist for minutes and to not transfer between strongly differing stimuli. Here, we further investigated the repetition-related effects using laminar recordings of multi-unit activity and local field potentials from awake macaque areas V1 and V2. We find that the effects on spike rate and gamma occur in all laminar compartments of V1 and V2. We quantify the degree of stimulus specificity with oriented gratings and find that the repetition-related gamma increase does not transfer to gratings differing by merely 10 {degrees}, the smallest difference tested. Furthermore, we find that the repetition-related effects are robust to stimulus set size, occurring both when one stimulus was repeated and when eighteen different interleaved stimuli were repeated. Finally, we show that alpha-beta activity increases and remains elevated when a stimulus is repeated, and decreases sharply when an unexpected stimulus is presented. These results suggest that repetition-related plasticity leads to changes in spike rates and rhythmic neuronal synchronization in different frequency bands that adjust the cortical processing of repeated stimuli.

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On variability in local field potentials

Neuronal coding and decoding would be compromised if neuronal responses were highly variable. Intriguingly, neuronal spike counts (SCs) show a reduction in across-trial variance (ATV) in response to sensory stimulation, when SC variance is normalized by SC mean, that is, when using the Fano factor 1. Inspired by this seminal finding, ATV has also been studied in electroencephalography (EEG) signals, revealing effects of various stimulus and cognitive factors as well as disease states. Here, we empirically show that outside of evoked potentials, the ATV of the EEG or local field potential (LFP) is very highly correlated to the intra-trial variance (ITV), which corresponds to the well-known power metric. We propose that the LFP power, rather than the raw LFP signal, should be considered with regard to putative changes of its variability. We quantify LFP power variability as the standard deviation of the logarithm of the power ratio between an active and a baseline condition, normalized by the mean of that log(power ratio), that is the coefficient of variation (CV) of the log(power ratio). This CV(log(power ratio)) is reduced for gamma and alpha power when they are enhanced by stimulation, and it is enhanced for alpha power when it is reduced by stimulation. This suggests a potential inverse relation between changes in band-limited power and the corresponding CV. We propose that the CV(log(power ratio)) is a useful metric that can be computed for numerous existing and future LFP, EEG or MEG datasets, which will provide insights into those signals frequency-specific variability and how they might be used for neuronal coding and decoding.

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Spectral estimation at the edge

Cognitive functions depend on neuronal communication, which is subserved by the synchronization of neuronal rhythms. Rhythms are characterized by their frequency, power and phase. If the phase of a rhythm just preceding an input is predictive of the neuronal or behavioral response to the input, this provides strong evidence for a functional role of the rhythm. Yet, this requires estimating the phase of a rhythm at the edge of the epoch. This is challenging, because any phase estimation that is spectrally specific requires a finite window length often combined with tapers that de-emphasize the signal close to the edge. To overcome this, we propose a method that builds on previously described approaches based on autoregressive modeling of the data and corresponding extrapolation beyond the edge. In contrast to related previous approaches, the modeling is based on the broadband signals, avoiding filtering-related group delays, and the extrapolation is performed multiple times, allowing averaging and thereby the reduction of extrapolation noise. The new method provided more accurate phase estimation at the edge for most simulated datasets, and for an empirical dataset from awake macaque area V4. We propose that the enhanced phase estimation accuracy at the edge might help to investigate the functional roles of brain rhythms and potentially also to improve phase-specific stimulation for clinical applications.

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Would you agree if N is three?On statistical inference for small N.

Non-human primate studies traditionally use two or three animals. We previously used standard statistics to argue for using either one animal, for an inference about that sample, or five or more animals, for a useful inference about the population. A recently proposed framework argued for testing three animals and accepting the outcome found in the majority as the outcome that is most representative for the population. The proposal tests this framework under various assumptions about the true probability of the representative outcome in the population, i.e. its typicality. On this basis, it argues that the framework is valid across a wide range of typicalities. Here, we show (1) that the error rate of the framework depends strongly on the typicality of the representative outcome, (2) that an acceptable error rate requires this typicality to be very high (87% for a single type of outlier), which actually renders empirical testing beyond a single animal obsolete, (3) that moving from one to three animals decreases error rates mainly for typicality values of 70-90%, and much less for both lower and higher values. Furthermore, we use conjunction analysis to demonstrate that two out of three animals with a given outcome only allow to infer a lower bound to typicality of 9%, which is of limited value. Thus, the use of two or three animals does not allow a useful inference about the population, and if this option is nevertheless chosen, the inferred lower bound of typicality should be reported.

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Modular, cement-free, customized headpost and connector-chamber implants for macaques

BackgroundNeurophysiological studies with awake macaques typically require chronic cranial implants. Headpost and connector-chamber implants are used to allow head stabilization and to house connectors of chronically implanted electrodes, respectively. New MethodWe present long- lasting, modular, cement-free headpost implants made of titanium that consist of two pieces: a baseplate and a top part. The baseplate is implanted first, covered by muscle and skin and allowed to heal and osseointegrate for several weeks to months. The percutaneous part is added in a second, brief surgery. Using a punch tool, a perfectly round skin cut is achieved providing a tight fit around the implant without any sutures. We describe the design, planning and production of manually bent and CNC-milled baseplates. We also developed a remote headposting technique that increases handling safety. Finally, we present a modular, footless connector chamber that is implanted in a similar two- step approach and achieves a minimized footprint on the skull. ResultsTwelve adult male macaques were successfully implanted with a headpost and one with the connector chamber. To date, we report no implant failure, great headpost stability and implant condition, in four cases even more than 9 years post-implantation. Comparison with Existing MethodsThe methods presented here build on several related previous methods and provide additional refinements to further increase implant longevity and handling safety. ConclusionsOptimized implants can remain stable and healthy for at least 9 years and thereby exceed the typical experiment durations. This minimizes implant-related complications and corrective surgeries and thereby significantly improves animal welfare. HighlightsO_LILong-lasting titanium implants for non-human primates C_LIO_LIRefined implantation techniques that reduce post-operative complications C_LIO_LIMinimized, footless connector chamber to house connectors of chronic arrays C_LIO_LITwelve adult male macaques were implanted with long-lasting headpost implants C_LIO_LIHeadpost implants so far without failure and with longevity up to > 9 years C_LI

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Phase leads between oscillatory visual stimuli induce a salience illusion

Neuronal populations often engage in oscillations, and corresponding theories and computational models propose that this affects their impact on other neurons. Specifically, when two neuronal populations oscillating at similar frequencies compete for impact, the phase-leading one might have an advantage by providing inputs to target neurons earlier. Here, we provide direct empirical support by driving visual neuronal responses with oscillating stimuli. We superimposed two orthogonal grating stimuli of temporally oscillating intensities, whose phase relations were precisely controlled. The leading stimulus was perceived as oscillating more intensely. This held for phase leads of a few milliseconds, and for each participant and almost every trial. Thus, we found a strong perceptual illusion directly predicted by theories on the functional role of oscillations for neuronal interactions.

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