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Diána Nyujtó Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary

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Ádám Kiss Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary

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Balázs Bodosi Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary

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Gabriella Eördegh Faculty of Health Sciences and Social Studies, University of Szeged, Szeged, Hungary

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Kálmán Tót Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary

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András Kelemen Department of Applied Informatics, University of Szeged, Szeged, Hungary

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Attila Nagy Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary

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https://orcid.org/0000-0002-7697-8414
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Abstract

Previous results show that halothane gas anaesthesia has a suppressive effect on the visually evoked single-cell activities in the feline caudate nucleus (CN). In this study, we asked whether the low-frequency neuronal signals, the local field potentials (LFP) are also suppressed in the CN of anaesthetized animals.

To answer this question, we compared the LFPs recorded from the CN of two halothane-anaesthetized (1.0%), paralyzed, and two awake, behaving cats during static and dynamic visual stimulation. The behaving animals were trained to perform a visual fixation task.

Our results denoted a lower proportion of significant power changes to visual stimulation in the CN of the anesthetized cats in each frequency range (from delta to beta) of the LFPs, except gamma. These differences in power changes were more obvious in static visual stimulation, but still, remarkable differences were found in dynamic stimulation, too. The largest differences were found in the alpha and beta frequency bands for static stimulation. Concerning dynamic stimulation, the differences were the biggest in the theta, alpha and beta bands.

Similar to the single-cell activities, remarkable differences were found between the visually evoked LFP changes in the CN of the anaesthetized, paralyzed and awake, behaving cats. The halothane gas anaesthesia and the immobilization suppressed the significant LFP power alterations in the CN to both static and dynamic stimulation. These results suggest the priority of the application of behaving animals even in the analysis of the visually evoked low-frequency electric signals, the LFPs recorded from the CN.

Abstract

Previous results show that halothane gas anaesthesia has a suppressive effect on the visually evoked single-cell activities in the feline caudate nucleus (CN). In this study, we asked whether the low-frequency neuronal signals, the local field potentials (LFP) are also suppressed in the CN of anaesthetized animals.

To answer this question, we compared the LFPs recorded from the CN of two halothane-anaesthetized (1.0%), paralyzed, and two awake, behaving cats during static and dynamic visual stimulation. The behaving animals were trained to perform a visual fixation task.

Our results denoted a lower proportion of significant power changes to visual stimulation in the CN of the anesthetized cats in each frequency range (from delta to beta) of the LFPs, except gamma. These differences in power changes were more obvious in static visual stimulation, but still, remarkable differences were found in dynamic stimulation, too. The largest differences were found in the alpha and beta frequency bands for static stimulation. Concerning dynamic stimulation, the differences were the biggest in the theta, alpha and beta bands.

Similar to the single-cell activities, remarkable differences were found between the visually evoked LFP changes in the CN of the anaesthetized, paralyzed and awake, behaving cats. The halothane gas anaesthesia and the immobilization suppressed the significant LFP power alterations in the CN to both static and dynamic stimulation. These results suggest the priority of the application of behaving animals even in the analysis of the visually evoked low-frequency electric signals, the LFPs recorded from the CN.

Introduction

Beside the prominent role of the caudate nucleus (CN) in motor processes, it is also involved in sensory information processing through cortical and subcortical loops in the mammalian brain [1, 2]. The primary source of the visual inputs to the basal ganglia is the ascending tectofugal visual system, which sends the information from the superior colliculus through the posterior thalamus to the CN. The CN also receives visual cortical inputs from the anterior ectosylvian cortex [3]. These inputs are responsible for the specific visual properties of the CN. Previous studies denoted that the CN neurons are sensitive to static and dynamic visual stimuli, too [4–13]. The particular spatial and temporal visual properties of the CN neurons, i.e., preferences for low spatial and high temporal frequencies and narrow spatiotemporal spectral tuning [9, 14] suggest the contribution of these neurons to motion and novelty detection. Thus, the CN seems to belong to those brain structures that have the capacity to sample and evaluate a wide variety of changes in the visual environment.

The control of eye movements is obligatory in visual electrophysiological experiments because of various reasons. First of all, the spatial position of the visual stimulus has to overlap with the receptive field of the investigated neuron. Additionally, several visually active brain structures possess visuomotor activity, such as saccadic responses [15, 16]. Therefore, the researchers must eliminate the effect of eye movements on neuronal activities. Acute, anaesthetized, paralyzed, and awake, behaving animals are often used in visual electrophysiological research. Both models have their own advantages and disadvantages. The work in acute animals seems to be easier because there is no long behavioural training to restrict eye movement prior to the electrophysiological recordings [13, 17]. On the other hand, this increases the number of animals sacrificed, and the anaesthetics can also influence the activity of the brain. The deep brain sensorimotor structures, i.e., the cerebellum and the basal ganglia, are extremely sensitive to anaesthesia [18, 19]. Single-cell activity analysis revealed significant differences between the neuronal activities recorded from the feline CN in anaesthetized and behaving cats. The anaesthesia and the immobilization significantly suppressed the neuronal activity and the visual responsiveness of the CN. Furthermore, it was almost impossible to analyse phasically active neurons, the dominant neuronal population of the CN, due to the low neuronal activities. [20]. These results suggest the necessity of the behaving animals if the activity of the single CN cell is the focus of the research. The training and preparation of cats is often a challenging process that may last up to 9 months [17, 20]. Beside single cell activities, the low-frequency signals (local field potentials = LFPs) can also carry information from the visual environment. The visually evoked LFP changes can give information about the sum of the cortical and subcortical visual inputs in the CN. The question raises whether the LFP activities and the visually evoked LFP changes are suppressed similarly in the anaesthetized animals as the single-cell activities. To address these questions, we compared the LFPs recorded from the CN in halothane anaesthetized, paralyzed, artificially ventilated and awake, behaving cats. An earlier study denoted that the median of visual onset response latencies was 100 ms in the CN (the range was 20–200 ms, [11]. Additionally, the CN is involved in novelty detection and the detection of changes in the visual environment [2, 9]. We have focused on the alterations in different frequency bands (theta, alpha, beta, and gamma) of the LFPs in the first 320 ms time after the appearance of the static visual stimulus, and in the first 320 ms after the starting of the movement of the dynamic visual stimulus.

Materials and methods

We recorded from the CN of two halothane anaesthetized, paralyzed, and two awake, behaving adult, domestic cats that weighed between 2.5 and 5 kg. The acute recordings lasted for 3 days. The recording sessions of the behaving cats lasted 30 min to 1 hour per day, four to five times a week.

All procedures were performed to minimize the number and the discomfort of the animals, and the experimental protocol was accepted by the Government Office based on the suggestion of the Ethical Committee for Animal Research of Albert Szent-Györgyi Medical and Pharmaceutical Centre at the University of Szeged (No.: XIV./518/2018 and XIV/1818/2021) and was conducted in full accordance with the Directive 2010/63/EU of the European Parliament and the Council on the Protection of Animals Used for Scientific Purposes and the guidelines of the Committee.

Surgical procedure of the anaesthetized animals

The animals were initially anaesthetized with ketamine hydrochloride (Calypsol (Gedeon Richter LTD), 30 mg kg−1 i.m.). A subcutaneous injection of 0.2 ml 0.1% atropine sulphate was administered preoperatively to reduce salivation and bronchial secretion. All wound edges and pressure points were treated regularly with a local anesthetic (1% procaine hydrochloride). The trachea and the femoral vein were cannulated, and then the animals were placed in a stereotaxic frame. The cats were artificially ventilated with 1.2–1.6% halothane during surgery, which was reduced to 0.8–1.0% during the recording sessions to minimize the effects of anesthesia. The depth of the anesthesia was monitored continuously with the end-tidal anesthetic concentration and heart rate. The minimal alveolar anesthetic concentration (MAC) values calculated from the end-tidal halothane concentration were kept in a recommended range [21]. The end-tidal halothane concentration, MAC values and the peak expired CO2 concentrations were monitored with a capnometer (CapnomacUltima, Datex-Ohmeda, ICN). The O2 saturation of the capillary blood was monitored by pulse oximetry. The peak expired CO2 concentration was kept within the range of 3.8–4.2% by adjustment of the respiratory rate or volume. The animals were immobilized with an initial 2 ml intravenous bolus of gallamine triethiodide (Flaxedil, 20 mg kg−1, Sigma, St. Louis, MO, USA). During the whole experiment, a mixture containing gallamine triethiodide (8 mg kg−1 h−1), glucose (10 mg kg−1 h−1) and dextran (50 mg kg−1 h−1) in Ringer lactate solution was infused continuously at a rate of 4 mL h−1. The body temperature of the cats was maintained at 37 °C by an electric heating blanket. Craniotomy was performed with a dental drill to allow a vertical approach to the target structures. The dura mater was removed, and the skull hole was covered with a 4% solution of 37 °C agar dissolved in Ringer's solution. The eye contralateral to the subcortical recording site was treated locally with atropine sulphate (one or two drops, 0.1%) and phenylephrine hydrochloride (one or two drops, 10%) to dilate the pupils, block accommodation and retract the nictitating membranes, and was equipped with a +2 diopter contact lens. During the recordings, the ipsilateral eye was covered.

Visual paradigm and recording in anaesthetized animals

The recording sessions took place in a dark, quiet room where the background luminance was 2 cd m−2. Vertical penetrations made within the Horsley-Clarke coordinates anterior 14 mm and lateral 4–5 mm, at a stereotaxic depth of 10–15.3 mm. The extracellular electrophysiological recordings were carried out with a 64-channel 2 shank (32 channel/shank, diameter: 300 µm/shank) platinum-iridium linear probe (Neuronelektród Ltd., Hungary). The vertical distance between each channel was 50 µm. The reference electrode was a 125 μm tungsten electrode which was inserted in the white matter in the position of anterior 7 and lateral 8 according to the Horsley-Clarke coordinates. The electrical signals were amplified and digitalized with Intan rhd 2132 chips and Hinstra Dedas data acquisition system (Hinstra Instruments Ltd., Hungary). Amplified neuronal activities were recorded at a 20 kHz sampling rate and stored for offline analysis. The stimulus presentation was controlled by a custom-made software and was presented on an 18-inch CRT monitor (refresh rate: 100 Hz) 57 cm in front of the animal. A single trial (one repetition of the whole stimulation protocol) consisted of 3 epochs (phases): first a blank, black screen was presented to obtain background activity without visual stimulation for 2000 ms; then a random dot pattern appeared on the screen for 1,500 ms as a stationary stimulus; that was followed by the dynamic stimulus, where the same white dots started to move randomly either toward the periphery (center-out flow field) or toward the center (center-in flow field) of the screen. The dynamic stimulus also lasted 1,500 ms. The size of each dot was 0.1° in diameter in both the static and the dynamic stimulus. The speed of dot movement increased from 0 to 7°/s toward the periphery. One recording session lasted 15 min, where 50 trials were presented from for each of the center in and center out conditions in a pseudo-random order. Between the recordings, the electrode position was changed (200 µm downward), and a 30-min break was kept before the next recording.

Surgical procedure in case of awake, behaving animals

The preparation before the surgery was carried out the same way as with the anaesthetized animals. First, the cats were initially anaesthetized with ketamine hydrochloride (Calypsol (Gedeon Richter®), 30 mg kg−1 i.m), then a subcutaneous injection of 0.2 ml 0.1% atropine sulphate was administered. In addition, a preventive dose of antibiotic (1,000 mg ceftriaxon, i.m., Rocephin 500 mg (Roche®)) was given preoperatively. The surgical preparation started with the cannulation of the femoral vein, then continued with the implantation of a scleral search coil (Cooner wire, Owensmouth, CA, USA) into one eye to monitor the eye movements of the cats during the recordings [17, 22–27]. After the intubation of the trachea, the cats were placed in a stereotaxic frame. All pressure points and wounds were treated with local anesthetic (1% procaine hydrochloride). During the surgery, the anesthesia was maintained with 1.5% halothane in a 2:1 mixture of N2O and oxygen. The depth of the anesthesia was monitored by continuously checking the end-tidal halothane concentration, MAC values, the peak expired CO2 concentrations and the O2 saturation. Firstly, a stainless steel head-holder was installed on the skull to fixate the head during the recordings. After this, the craniotomy was performed with a dental drill; the dura mater was preserved, and the skull hole was covered with a 4% solution of 38 °C agar dissolved in Ringer's solution. Then a reclosable plastic recording chamber (20 mm in diameter) was cemented on the skull to avoid any contamination and to protect the microdrive system and the extracellular electrodes. Following this, eight wire electrodes covered by a guiding tube were implanted above the CN according to the Horsley-Clarke coordinates anterior 12–14 mm, lateral 4–6.5 mm. Recordings were performed at the stereotaxic depths between 10 and 16 mm. The electrodes were implanted in the brain with the help of an adjustable microdrive system [28, 29].

On the first five postoperative days, ceftriaxone antibiotic was administered intramuscularly (Rocephine, 50 mg kg−1). Nalbuphin (0.25 mg kg−1) and non-steroidal anti-inflammatory drugs were administered until the seventh postoperative day.

Behavioural training of awake, behaving cats

The detailed description of the training process and the recordings can be found in our previous studies [13, 17, 20]. The cats were suspended in the experimental stand by a canvas harness. The cats were trained to perform the behavioural fixation paradigm while their heads were fixed to the stereotaxic frame. The stereotaxic frame with the animal was placed within an electromagnetic field, which is generated by metal coils installed into the wall of the experimental stand. During the fixation training, the fixation time was gradually increased from 100 to 2500 ms. Square fixation windows were used. The size of the initial fixation window was ±10° for both cats. During the training period, it was reduced to ±2.5° in ±2.5° steps. The animals were trained to hold their eyes in the center of the monitor during recordings of neuronal activities to different kinds of visual stimulation. The behavioral training lasted 9–12 months approximately 1–2 hours per day, four to five times a week. The training phases and later the recordings took place in a dark, quiet laboratory room.

Visual paradigm and recordings in case of awake, behaving cats

The electrophysiological extracellular recordings were carried out with perylene isolated platinum-iridium wire-electrodes with a diameter of 25 µm for the first cat; and formvar insulated nickel-chrome wire-electrodes with a diameter of 50 µm for the second cat. Each recording electrode contained 8 wires and one wire contained one recording channel. The reference electrode was positioned in the white matter in anterior 3 and lateral 8 according to the Horsley-Clarke coordinates. The recording of the eye movements, stimulus presentation, reward delivery, and data collection were controlled by a custom-made LabView software via a 16-channel National Instruments data acquisition card. The sampling rate was 10 kHz. Eye movements were monitored and recorded with a search coil system (DNI Instruments, Newark, DE, USA). A standard 17-inch CRT monitor (refresh rate: 100 Hz) was placed in front of the animal at a viewing distance of 57 cm for the visual stimulation. The fixation point and the visual stimuli were generated by a custom-made script written in Matlab and using the Psychophysics Toolbox® [30]. A fixation point was projected on the center of the monitor to help maintain the fixation on the middle of the monitor during the relevant stimulus phases. The size of the fixation point was 0.8° in diameter, the fixation window was 5° in diameter (5° × 5° square). In the case of the behaving, awake animals, a trial (one repetition of the whole stimulation protocol) consisted of 5 epochs (phases). First, a green fixation point was presented in the center of the monitor. The cats had to direct their gaze to the fixation point and keep fixating for 500 ms. The visual stimulation task started immediately after the successful fixation phase. It means that the cat held his eye in the above described ±2.5° fixation window. This was similar to the stimulation used in the anaesthetized experiments: a static random dot pattern appeared first, which was followed by a dynamic center-in or center-out flow field stimulation in random order. The duration of both the static and the dynamic stimuli was 1,000 ms. If the cats managed to fixate throughout all the stimulation phases of a single trial, they received a food reward, and it was considered a correct trial. If the cats broke fixation during any of the stimulation phases, the trial was aborted immediately, it was not accepted, and no reward was given. Between two trials, there was a random 5,000–10,000 ms long intertrial interval (reward was given at the beginning of this time range), where no stimuli appeared, only a black screen. This phase was long enough so that the cat could eat the reward without muscle activity interfering with the recordings of the next trial. One recording session lasted 30–45 min. The number of successful trials, where the animal could hold the fixation during the whole stimulation protocol, were analyzed. These varied between 80 and 200 in each recording.

Data analysis

For the data analysis and the statistical analysis, Matlab R2021a software (The Mathworks, Natic, MA, USA) was used. During the analysis, the power of the delta (1–3 Hz), theta (4–7 Hz), alpha (8–13 Hz), beta (14–30 Hz), and gamma (31–70 Hz) bands were calculated.

The first step was the visual inspection of the recorded raw data (Fig. 1). Channels with high amplitude noise and/or bad signal-noise ratio were excluded from further analysis. After the subtraction of these channels, the downsampling of the remaining channels was performed for further mathematical analysis. It was done by applying a low pass filter and decimation to 500 Hz for the raw data using the Matlab decimate function. After the downsampling of the original dataset, Fourier analysis was performed. The power spectrum was then video-filtered (smoothed) by a ten-bin rectangle window. A whitening compensation was used to visualize higher frequency bands more equally, however, the calculations were made from the original raw data. After the whitening, a median filter (Matlab medfilt1) was also used with the default parameters. During the visualization of the Fourier spectra, the bins near 50 Hz were cut off.

Fig. 1.
Fig. 1.

Spectral image of the LFP recordings

Part A shows the Fourier spectrum of a recorded signal (Cecilia589_ch4) from a behaving cat. Part B denotes the Fourier spectrum of a recorded signal (Igor067_ch11) from an anaesthetized cat. The blue colour shows the raw Fourier spectrum and the orange colour denotes the whitened one. Part C and Part D denote the spectral power of the same recorded signals calculated with the Welch function

Citation: Physiology International 111, 1; 10.1556/2060.2023.00240

Filtering and power calculation

The raw data of each channel was decimated to 500 Hz by the Matlab decimate function. The decimation filter was an finite impulse response filter (FIR) one, and its length was chosen to 20 ms, not to alias brain events through each other.

For each band, a digital superheterodyne test receiver was implemented. The center frequency of every band was shifted to 0 Hz by multiplying the signal with a complex rotating vector. After this step, a Chebyshev infinite impulse response filter (IIR) filter was used, and the signal was decimated to a lower sampling frequency. The filtering and decimating steps were repeated in order to reach the desired width of the band, and fulfil the stability criteria of the filters (Fig. 2). The final decimation was done for 25 Hz. For the theta signal (the lowest interesting frequency band in this study), the resulting stable filters require a 25 Hz sampling frequency. Calculating the power of signals hence shows t = 1/f = 40 ms time resolution. The higher frequency band was also summated and decimated with the same time resolution and sampling frequency. Having the 25 Hz complex signal for each band, the absolute value of these signals represents the power of the signal for each 40 ms wide sample.

Fig. 2.
Fig. 2.

Spectral coverage of the applied band pass filters

The characteristics of the filters in each frequency band can be seen with different colors (green-delta, purple-theta, yellow-alpha, orange-beta, blue-gamma) section. Note the overlap between the frequency-based neighbouring filters and their sharp filtering properties

Citation: Physiology International 111, 1; 10.1556/2060.2023.00240

Statistical analysis

The powers of a randomly selected 320 ms period (the average of eight 40 ms wide bins (samples described above) from the background activity and 320 ms periods (the average of eight 40 ms wide samples described above) immediately after the appearance of the stationary stimulus and the start of the dynamic stimulus were calculated in each trial and each frequency band, both in the behaving and the anaesthetized LFP recordings. The powers of these 320 ms periods in each frequency band from all trials were non-normally distributed (Shapiro-Wilk P < 0.05). Thus, they were compared with the Friedman ANOVA test with Bonferroni correction both in the behaving and anaesthetized LFP recordings. If this test denoted a significant difference (P < 0.05) in one LFP recording, it would indicate that at least one of the three conditions (background activity, response to static or dynamic stimulation) differs from the others. In this case, the Wilcoxon matched pair test was used for a pairwise comparison as a post hoc analysis to check which part of the stimulated activity (static, dynamic, or both) differs significantly from the background activity the different frequency bands. The significant differences from the background activity were considered in the present study as dynamic and static visual responses in the CN.

Results

Altogether 226 local field potential (LFP) recordings from awake, behaving cats and 960 LFP recordings from anaesthetized cats were involved in the data analysis. Each LFP recording (which contained at least 80 trials) was analysed separately. The LFPs were analysed in five different frequency bands (delta (1–3 Hz), theta (4–7 Hz), alpha (8–13 Hz), beta (14–30 Hz), and gamma (31–70 Hz)).

The summary of the detailed descriptive statistics can be seen in Table 1. Comparing the response activity during visual stimuli to the background activity, Wilcoxon matched pair test revealed that 90% (N = 207) of all registered LFPs from awake, and only 63% (N = 609) from the anaesthetized cats showed significant responses at least in one visual condition (static, dynamic) and one frequency band. Figure 3 denotes examples of the visually evoked power changes in the awake, behaving, and Fig. 4 in anaesthetized animals.

Table 1.

Descriptive statistics of visually evoked LFPs during visual stimuli from awake, behaving, and anaesthetized animals

Awake (N = 226)Anesthetized (N = 960)
N%N%
Delta803516817
Theta984317819
Alpha1215618119
Beta1446421022
Gamma532322023
All2049060963

In awake animals the percentage of LFPs that showed significant changes to visual stimulation in delta, theta, alpha and beta frequency band was higher than in the anesthetized animals.

Fig. 3.
Fig. 3.

Visually evoked changes of the local field potentials in awake animal

Cumulated power of the wave bands (from delta to gamma) after applying the given spectral filter (see Fig. 2) for each frequency band. The blue curve represents the mean activity for all trials. The vertical lines denote the borders between the different epochs of the visual paradigm (from left to right): background activity, fixation activity, response to static visual stimulus, response to dynamic visual stimulus and reward. The abscissa denotes the time relationship of the signals. The ordinate denotes the channel power in linear metrics

Citation: Physiology International 111, 1; 10.1556/2060.2023.00240

Fig. 4.
Fig. 4.

Visually evoked changes of the local field potentials in halothane anaesthetized cat

Cumulated power of the wave bands (from delta to gamma) after applying the given spectral filter for each frequency band. The blue curve represents the mean activity for all trials. The vertical lines denote the borders between the different epochs of the visual paradigm (from left to right): background activity, response to static visual stimulus and response to dynamic visual stimulus. The abscissa denotes the time relationship of the signals. The ordinate denotes the channel power in linear metrics

Citation: Physiology International 111, 1; 10.1556/2060.2023.00240

The percentage of LFPs that showed significant changes to static and/or dynamic stimulation in theta, alpha and beta frequency bands was higher in awake, behaving cats. In the theta band, the percentage was 43% (N = 98) in awake and only 19% (N = 178) in anaesthetized cats. In the alpha band, the percentage was 56% (N = 121) in awake and 19% (N = 181) in anaesthetized cats. In the beta frequency band, the percentage of the significant LFPs was 64% (N = 114) in awake and 22% (N = 210) in anaesthetized cats. In the gamma frequency band, the percentage of the significant LFP changes was 23% in both (N = 34) the awake and the anaesthetized cats (Table 1).

Responses to static visual stimulation

The proportion of LFPs that showed significant response during static visual stimulation was much higher in awake, behaving cats (83%, N = 122) than in anaesthetized cats (63%, N = 177). A higher percentage of visually evoked LFP changes can be observed in almost each frequency range in the behaving animals. The only exception is the theta band where the same percentages were found (Wilcoxon match paired test, see descriptive statistical data in Table 2). These differences are the most obvious in the alpha and the beta frequency bands. In the case of the alpha band, the percentage was 49% (N = 110) in awake and only 24% (N = 228) in anaesthetized cats. In the case of the beta band the percentage of the significant LFP changes was 49% (N = 110) in behaving cats, and it was only 23% (N = 221) in anaesthetized cats.

Table 2.

Descriptive statistics of response activity during static and dynamic visual stimuli

StaticDynamic
Awake (N = 226)Anesthetized (N = 960)Awake (N = 226)Anesthetized (N = 960)
N%N%N%N%
Delta683017819612721823
Theta582628229893918319
Alpha1104922824763414715
Beta1104922123693120321
Gamma723222523462021522
All18783602631727661164

Higher percentage of visually evoked LFP changes during static stimulation can be observed in the delta, alpha, beta, gamma frequency range in the behaving animals. This tendency can be observed in the theta, alpha, beta frequency bands during dynamic visual stimulation.

Responses to dynamic visual stimulation

In comparison to the effect of the static stimulation (83%, N = 187) a bit lower amount of the analysed LFPs showed significant changes to dynamic stimulation (76%, N = 172) in behaving cats. However, the percentage of the responsive LFPs to static and dynamic stimulation were similar in the anaesthetized animals, 63% (N = 602) and 64% (N = 611), respectively.

Similarly, to the static visual stimulation, the proportion of LFPs that showed significant responses during dynamic visual stimulation was higher in awake, behaving cats (76%, N = 172) than in anaesthetized ones (64%, N = 611, Wilcoxon match paired test, see descriptive statistical data in Table 2). These differences are the most notable in the theta, alpha and the beta frequency bands. In the case of the theta band, the percentage was 39% (N = 89) in awake, and only 19% (N = 183) in anaesthetized cats. In the alpha band the percentage was 34% (N = 76) in the behaving animals and 15% in the anaesthetized cats. The percentage of the significant LFP changes was 31% (N = 69) in behaving, and it was lower 21% (N = 37) in anaesthetized cats in the beta frequency band.

Discussion

To our knowledge, this is the first descriptive study that compares the low-frequency neuronal activities (local field potentials, LFPs) recorded from the CN during visual stimulation in anaesthetized, paralyzed, and awake, behaving cats. In line with the findings of our previous study on the single cell activities [20], the present results clearly demonstrated that the applied halothane anesthesia indeed suppresses the visually evoked LFP changes at a remarkable level. Thus, lower proportion of significant power changes was detected to visual stimulation in the anaesthetized animals in each frequency range (from delta to gamma) of the LFPs.

In visual electrophysiological experiments, both anaesthetized, paralyzed, and awake, behaving models are commonly used. Both have their advantages and disadvantages. The control of eye movements in visual electrophysiology is critical. The spatial position of the visual stimulus must overlap with the receptive field of the investigated neuron, and oculomotor activity can also be found in some extrastriate visual structures [15, 16]. If one would like to eliminate these disturbing factors, there are two possibilities. In anaesthetized and paralyzed animal models, eye movements are inhibited through muscle relaxants. However, the applied anesthetics and muscle relaxants can influence the activity of the central nervous system. It is also assumed that this effect is not the same as in the cortex or the deeper brain structures [31]. The basal ganglia are strongly sensitive to different kinds of anesthesia [18, 19]. In the case of the single-cell activities in the CN, the anesthesia influences the timing of the action potential and the discharge rates significantly [20]. Beside these high-frequency signals, the LFPs could also be influenced. Based on our previous experiences that the halothane influences the neuronal activities less in the CN than other gas anesthetics (i.e., isoflurane), although we cannot exclude the effect of the anesthesia from the results in anaesthetized animals. The big advantage of the application of this anaesthetized animal is the quick application of it without any training of the animals. The second solution for the elimination of the effect of eye movements on neuronal activities is the application of eye movement controlled fixating behaving animals. The disadvantage of the experiments with behaving animals is the long-lasting behavioral and fixation training, which could last for 9–12 months before the start of the electrophysiological recordings. However, there is no disturbing effect of anesthetics in this case.

The question raises whether the benefit of experiments performed in the CN of awake, behaving animals is in balance with the hardness of the preparation of the animals for visual electrophysiological recordings. The results of the visual information processing in the CN revealed that both the background activities and the neuronal responses to static and dynamic visual stimulation were strongly reduced in the anaesthetized animals. The most drastic differences can be seen in the biggest neuronal population in the medium spiny neurons of the caudate body [20]. Concerning the significant changes in LFP in response to visual stimulation, the differences between the two models are also obvious. The vast majority (90%) of the LFPs recorded in behaving cats showed significant responses at least in one visual condition (static, dynamic) and one frequency band. On the other hand, it was a smaller proportion of the LFPs (61%) in anaesthetized cats. These differences in power changes were the stronger concerning static visual stimulation (83% vs 63%). Less, but still obvious differences were found to dynamic stimulation, too (76% vs 64%). The higher proportion of the evoked LFP responses were detectable in both static and dynamic stimulation in each investigated frequency band from the lower delta to the highest gamma band. However, the biggest differences were concerning static stimulation in the alpha and the beta frequency bands and concerning dynamic stimulation to the theta, the alpha and the beta bands.

Similar to human EEG results, the increased theta activity could arise from the coordinated reactivation of information represented in visual areas [32–36]. The elevated cortical alpha activity is also connected to visual and audio-visual processing [37–39]. Another function that has been attributed to alpha activity is a mechanism of sensory suppression, thus functionally gating information in the task-irrelevant brain areas [40, 41]. It is also assumed that the normal beta activity is a necessary cortical outcome of the normal action of the basal ganglia in visual information processing [42]. Since the analysis addressed the first 320 ms time window of both static and dynamic stimulation, novelty detection and the connected sensory gating could be the task that shows these differences between the anaesthetized, paralyzed, and awake, behaving animals [2, 9].

Beyond the lack of halothane anesthesia and immobilization, our behaving model differed from anaesthetized models also in a third way: both eyes of the animal were open during stimulation (in anaesthetized cats, recordings are made only from one eye, while the other eye is covered, [43]). This monocular-binocular difference could influence the magnitude of visual responses, but such strong difference, as seen in this study, is not likely to stem from this factor only [44–46]. It is noteworthy to mention that the anaesthetized cats were cycloplegic, and the awake ones had normal pupils and lenses, but in the case of anaesthetized cats the visus was corrected with appropriate lenses. As the background luminance was the same for the two models and the same CRT monitor was used, these do not explain the observed difference either. An important shortcoming of the study is that the recordings from behaving and anaesthetized cats were performed with different recording systems with different background noise levels. Thus, the direct comparison of the magnitude of the visual responses was not possible in this study. Therefore, we could only concentrate on whether the changes were significant or not and we could give the presented a descriptive statistic about the percentage of these visually-evoked changes. Another limitation is that electrodes with different geometries were applied in the behaving (wire electrodes) and anaesthetized (linear probe) experiments. It is known that the geometry of the electrodes could influence the magnitude of the recorded LFPs [47]. But if we compare the baseline power spectrum density of one channel with the power spectrum density during visual stimulation of the same channel, it will not influence the number of significant changes and the differences between the two models. The different electrodes, 8-channel wire electrodes in the behaving experiments, and 64-channel linear probes in the anaesthetized experiments, explain the higher number of recorded LFPs from the anaesthetized animals.

To summarize our findings, we demonstrated similarly to the single cell activities [20], marked differences between the visually evoked LFP changes in the CN of the anaesthetized, paralyzed, and awake, behaving cats. The halothane gas anesthesia and the immobilization significantly suppressed the significant LFP power alterations to both static and dynamic stimulation. Although the work with behaving cats in visual electrophysiology is much more difficult, we argue that the benefits outweigh the costs, and we suggest the application of the behaving animal model even in the analysis of the low-frequency electric signals, the LFPs.

Funding

This work was supported by a grant from SZTE ÁOK-KKA Grant No. 2019/270-62-2 and SZTE SZAOK-KKA-SZGYA Grant No: 2023/5S479.

Author contributions

DN, GE, and AN designed the study; DN, GE, KT, NA and BB performed the assessment and documented the findings; ÁK, AK and NA analysed the data; DN, ÁK, AK, BB and NA organized the study and wrote the manuscript.

Competing interest

The author(s) declare no competing interests (both financial and non-financial).

Acknowledgements

The authors thank to Siposné Gabriella Dósai-Molnár and László Rácz for the technical assistance and to Robert Averkin for the microdrives and the wire electrodes.

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  • 1.

    McHaffie JG, Stanford TR, Stein BE, Coizet V, Redgrave P. Subcortical loops through the basal ganglia. Trends Neurosci 2005; 28(8): 4017. https://doi.org/10.1016/j.tins.2005.06.006.

    • Search Google Scholar
    • Export Citation
  • 2.

    Benedek G, Keri S, Nagy A, Braunitzer G, Norita M. A multimodal pathway including the basal ganglia in the feline brain. Physiol Int 2019; 106(2): 95113. https://doi.org/10.1556/2060.106.2019.09.

    • Search Google Scholar
    • Export Citation
  • 3.

    Rokszin A, Markus Z, Braunitzer G, Berenyi A, Benedek G, Nagy A. Visual pathways serving motion detection in the mammalian brain. Sensors (Basel) 2010; 10(4): 321842. https://doi.org/10.3390/s100403218.

    • Search Google Scholar
    • Export Citation
  • 4.

    Strecker RE, Jacobs BL. Substantia nigra dopaminergic unit activity in behaving cats: effect of arousal on spontaneous discharge and sensory evoked activity. Brain Res 1985; 361(1–2): 33950. https://doi.org/10.1016/0006-8993(85)91304-6.

    • Search Google Scholar
    • Export Citation
  • 5.

    Rolls ET, Thorpe SJ, Maddison SP. Responses of striatal neurons in the behaving monkey. 1. Head of the caudate nucleus. Behav Brain Res 1983; 7(2): 179210. https://doi.org/10.1016/0166-4328(83)90191-2.

    • Search Google Scholar
    • Export Citation
  • 6.

    Hikosaka O, Sakamoto M, Usui S. Functional properties of monkey caudate neurons. II. Visual and auditory responses. J Neurophysiol 1989; 61(4): 799813. https://doi.org/10.1152/jn.1989.61.4.799.

    • Search Google Scholar
    • Export Citation
  • 7.

    Chudler EH, Sugiyama K, Dong WK. Multisensory convergence and integration in the neostriatum and globus pallidus of the rat. Brain Res 1995; 674(1): 3345. https://doi.org/10.1016/0006-8993(94)01427-j.

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    • Export Citation
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    Nagy A, Eordegh G, Benedek G. Extents of visual, auditory and bimodal receptive fields of single neurons in the feline visual associative cortex. Acta Physiol Hung 2003; 90(4): 30512. https://doi.org/10.1556/APhysiol.90.2003.4.3.

    • Search Google Scholar
    • Export Citation
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    Nagy A, Paroczy Z, Markus Z, Berenyi A, Wypych M, Waleszczyk WJ, et al. Drifting grating stimulation reveals particular activation properties of visual neurons in the caudate nucleus. Eur J Neurosci 2008; 27(7): 18018. https://doi.org/10.1111/j.1460-9568.2008.06137.x.

    • Search Google Scholar
    • Export Citation
  • 10.

    Gombkoto P, Rokszin A, Berenyi A, Braunitzer G, Utassy G, Benedek G, et al. Neuronal code of spatial visual information in the caudate nucleus. Neuroscience 2011; 182: 22531. https://doi.org/10.1016/j.neuroscience.2011.02.048.

    • Search Google Scholar
    • Export Citation
  • 11.

    Rokszin A, Gombkoto P, Berenyi A, Markus Z, Braunitzer G, Benedek G, et al. Visual stimulation synchronizes or desynchronizes the activity of neuron pairs between the caudate nucleus and the posterior thalamus. Brain Res 2011; 1418: 5263. https://doi.org/10.1016/j.brainres.2011.08.015.

    • Search Google Scholar
    • Export Citation
  • 12.

    Vicente AF, Bermudez MA, Romero Mdel C, Perez R, Gonzalez F. Putamen neurons process both sensory and motor information during a complex task. Brain Res 2012; 1466: 7081. https://doi.org/10.1016/j.brainres.2012.05.037.

    • Search Google Scholar
    • Export Citation
  • 13.

    Nagypal T, Gombkoto P, Barkoczi B, Benedek G, Nagy A. Activity of caudate nucleus neurons in a visual fixation paradigm in behaving cats. PLoS One 2015; 10(11): e0142526. https://doi.org/10.1371/journal.pone.0142526.

    • Search Google Scholar
    • Export Citation
  • 14.

    Nagy A, Berenyi A, Wypych M, Waleszczyk WJ, Benedek G. Spectral receptive field properties of visually active neurons in the caudate nucleus. Neurosci Lett 2010; 480(2): 14853. https://doi.org/10.1016/j.neulet.2010.06.030.

    • Search Google Scholar
    • Export Citation
  • 15.

    Hikosaka O, Takikawa Y, Kawagoe R. Role of the basal ganglia in the control of purposive saccadic eye movements. Physiol Rev 2000; 80(3): 95378. https://doi.org/10.1152/physrev.2000.80.3.953.

    • Search Google Scholar
    • Export Citation
  • 16.

    Munoz DP, Fecteau JH. Vying for dominance: dynamic interactions control visual fixation and saccadic initiation in the superior colliculus. Prog Brain Res 2002; 140: 319. https://doi.org/10.1016/S0079-6123(02)40039-8.

    • Search Google Scholar
    • Export Citation
  • 17.

    Nagypal T, Gombkoto P, Utassy G, Averkin RG, Benedek G, Nagy A. A new, behaving, head restrained, eye movement-controlled feline model for chronic visual electrophysiological recordings. J Neurosci Methods 2014; 221: 17. https://doi.org/10.1016/j.jneumeth.2013.09.004.

    • Search Google Scholar
    • Export Citation
  • 18.

    Franks NP, Zecharia AY. Sleep and general anesthesia. Can J Anaesth 2011; 58(2): 13948. https://doi.org/10.1007/s12630-010-9420-3.

  • 19.

    Kaisti KK, Langsjo JW, Aalto S, Oikonen V, Sipila H, Teras M, et al. Effects of sevoflurane, propofol, and adjunct nitrous oxide on regional cerebral blood flow, oxygen consumption, and blood volume in humans. Anesthesiology 2003; 99(3): 60313. https://doi.org/10.1097/00000542-200309000-00015.

    • Search Google Scholar
    • Export Citation
  • 20.

    Barkoczi B, Nagypal T, Nyujto D, Katona X, Eordegh G, Bodosi B, et al. Background activity and visual responsiveness of caudate nucleus neurons in halothane anesthetized and in awake, behaving cats. Neuroscience 2017; 356: 18292. https://doi.org/10.1016/j.neuroscience.2017.05.028.

    • Search Google Scholar
    • Export Citation
  • 21.

    Villeneuve MY, Casanova C. On the use of isoflurane versus halothane in the study of visual response properties of single cells in the primary visual cortex. J Neurosci Methods 2003; 129(1): 1931. https://doi.org/10.1016/s0165-0270(03)00198-5.

    • Search Google Scholar
    • Export Citation
  • 22.

    Huxlin KR, Pasternak T. Training-induced recovery of visual motion perception after extrastriate cortical damage in the adult cat. Cereb Cortex 2004; 14(1): 8190. https://doi.org/10.1093/cercor/bhg106.

    • Search Google Scholar
    • Export Citation
  • 23.

    Pigarev IN, Levichkina EV. Distance modulated neuronal activity in the cortical visual areas of cats. Exp Brain Res 2011; 214(1): 10511. https://doi.org/10.1007/s00221-011-2810-0.

    • Search Google Scholar
    • Export Citation
  • 24.

    Pigarev IN, Rodionova EI. Two visual areas located in the middle suprasylvian gyrus (cytoarchitectonic field 7) of the cat's cortex. Neuroscience 1998; 85(3): 71732. https://doi.org/10.1016/s0306-4522(97)00642-8.

    • Search Google Scholar
    • Export Citation
  • 25.

    Populin LC, Yin TC. Behavioral studies of sound localization in the cat. J Neurosci 1998; 18(6): 214760. https://doi.org/10.1523/JNEUROSCI.18-06-02147.1998.

    • Search Google Scholar
    • Export Citation
  • 26.

    Populin LC, Yin TC. Bimodal interactions in the superior colliculus of the behaving cat. J Neurosci 2002; 22(7): 282634. https://doi.org/10.1523/jneurosci.22-07-02826.2002.

    • Search Google Scholar
    • Export Citation
  • 27.

    Tollin DJ, Populin LC, Moore JM, Ruhland JL, Yin TC. Sound-localization performance in the cat: the effect of restraining the head. J Neurophysiol 2005; 93(3): 122334. https://doi.org/10.1152/jn.00747.2004.

    • Search Google Scholar
    • Export Citation
  • 28.

    Korshunov VA. Miniature microdrive for extracellular recording of neuronal activity in freely moving animals. J Neurosci Methods 1995; 57(1): 7780. https://doi.org/10.1016/0165-0270(94)00130-9.

    • Search Google Scholar
    • Export Citation
  • 29.

    McKown MD, Schadt JC. A modification of the Harper-McGinty microdrive for use in chronically prepared rabbits. J Neurosci Methods 2006; 153(2): 23942. https://doi.org/10.1016/j.jneumeth.2005.10.020.

    • Search Google Scholar
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Editor-in-Chief

László ROSIVALL (Semmelweis University, Budapest, Hungary)

Managing Editor

Anna BERHIDI (Semmelweis University, Budapest, Hungary)

Co-Editors

  • Gábor SZÉNÁSI (Semmelweis University, Budapest, Hungary)
  • Ákos KOLLER (Semmelweis University, Budapest, Hungary)
  • Zsolt RADÁK (University of Physical Education, Budapest, Hungary)
  • László LÉNÁRD (University of Pécs, Hungary)
  • Zoltán UNGVÁRI (Semmelweis University, Budapest, Hungary)

Assistant Editors

  • Gabriella DÖRNYEI (Semmelweis University, Budapest, Hungary)
  • Zsuzsanna MIKLÓS (Semmelweis University, Budapest, Hungary)
  • György NÁDASY (Semmelweis University, Budapest, Hungary)

Hungarian Editorial Board

  • György BENEDEK (University of Szeged, Hungary)
  • Zoltán BENYÓ (Semmelweis University, Budapest, Hungary)
  • Mihály BOROS (University of Szeged, Hungary)
  • László CSERNOCH (University of Debrecen, Hungary)
  • Magdolna DANK (Semmelweis University, Budapest, Hungary)
  • László DÉTÁRI (Eötvös Loránd University, Budapest, Hungary)
  • Zoltán GIRICZ (Semmelweis University, Budapest, Hungary and Pharmahungary Group, Szeged, Hungary)
  • Zoltán HANTOS (Semmelweis University, Budapest and University of Szeged, Hungary)
  • Zoltán HEROLD (Semmelweis University, Budapest, Hungary) 
  • László HUNYADI (Semmelweis University, Budapest, Hungary)
  • Gábor JANCSÓ (University of Pécs, Hungary)
  • Zoltán KARÁDI (University of Pecs, Hungary)
  • Miklós PALKOVITS (Semmelweis University, Budapest, Hungary)
  • Gyula PAPP (University of Szeged, Hungary)
  • Gábor PAVLIK (University of Physical Education, Budapest, Hungary)
  • András SPÄT (Semmelweis University, Budapest, Hungary)
  • Gyula SZABÓ (University of Szeged, Hungary)
  • Zoltán SZELÉNYI (University of Pécs, Hungary)
  • Lajos SZOLLÁR (Semmelweis University, Budapest, Hungary)
  • Gyula TELEGDY (MTA-SZTE, Neuroscience Research Group and University of Szeged, Hungary)
  • József TOLDI (MTA-SZTE Neuroscience Research Group and University of Szeged, Hungary)
  • Árpád TÓSAKI (University of Debrecen, Hungary)

International Editorial Board

  • Dragan DJURIC (University of Belgrade, Serbia)
  • Christopher H.  FRY (University of Bristol, UK)
  • Stephen E. GREENWALD (Blizard Institute, Barts and Queen Mary University of London, UK)
  • Osmo Otto Päiviö HÄNNINEN (Finnish Institute for Health and Welfare, Kuopio, Finland)
  • Helmut G. HINGHOFER-SZALKAY (Medical University of Graz, Austria)
  • Tibor HORTOBÁGYI (University of Groningen, Netherlands)
  • George KUNOS (National Institutes of Health, Bethesda, USA)
  • Massoud MAHMOUDIAN (Iran University of Medical Sciences, Tehran, Iran)
  • Tadaaki MANO (Gifu University of Medical Science, Japan)
  • Luis Gabriel NAVAR (Tulane University School of Medicine, New Orleans, USA)
  • Hitoo NISHINO (Nagoya City University, Japan)
  • Ole H. PETERSEN (Cardiff University, UK)
  • Ulrich POHL (German Centre for Cardiovascular Research and Ludwig-Maximilians-University, Planegg, Germany)
  • Andrej A. ROMANOVSKY (University of Arizona, USA)
  • Anwar Ali SIDDIQUI (Aga Khan University, Karachi, Pakistan)
  • Csaba SZABÓ (University of Fribourg, Switzerland)
  • Eric VICAUT (Université de Paris, UMRS 942 INSERM, France)
  • Nico WESTERHOF (Vrije Universiteit Amsterdam, The Netherlands)

 

Editorial Correspondence:
Physiology International
Semmelweis University
Faculty of Medicine, Institute of Translational Medicine
Nagyvárad tér 4, H-1089 Budapest, Hungary
Phone/Fax: +36-1-2100-100
E-mail: pi@semmelweis-univ.hu

Indexing and Abstracting Services:

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  • Referativnyi Zhurnal
  • SCOPUS
  • WoS - Science Citation Index Expanded

 

2022  
Web of Science  
Total Cites
WoS
335
Journal Impact Factor 1.4
Rank by Impact Factor

Physiology (Q4)

Impact Factor
without
Journal Self Cites
1.4
5 Year
Impact Factor
1.6
Journal Citation Indicator 0.42
Rank by Journal Citation Indicator

Physiology (Q4)

Scimago  
Scimago
H-index
33
Scimago
Journal Rank
0.362
Scimago Quartile Score

Physiology (medical) (Q3)
Medicine (miscellaneous) (Q3)

Scopus  
Scopus
Cite Score
2.8
Scopus
CIte Score Rank
Physiology 68/102 (33rd PCTL)
Scopus
SNIP
0.508

2021  
Web of Science  
Total Cites
WoS
330
Journal Impact Factor 1,697
Rank by Impact Factor

Physiology 73/81

Impact Factor
without
Journal Self Cites
1,697
5 Year
Impact Factor
1,806
Journal Citation Indicator 0,47
Rank by Journal Citation Indicator

Physiology 69/86

Scimago  
Scimago
H-index
31
Scimago
Journal Rank
0,32
Scimago Quartile Score Medicine (miscellaneous) (Q3)
Physiology (medical) (Q3)
Scopus  
Scopus
Cite Score
2,7
Scopus
CIte Score Rank
Physiology (medical) 69/101 (Q3)
Scopus
SNIP
0,591

 

2020  
Total Cites 245
WoS
Journal
Impact Factor
2,090
Rank by Physiology 62/81 (Q4)
Impact Factor  
Impact Factor 1,866
without
Journal Self Cites
5 Year 1,703
Impact Factor
Journal  0,51
Citation Indicator  
Rank by Journal  Physiology 67/84 (Q4)
Citation Indicator   
Citable 42
Items
Total 42
Articles
Total 0
Reviews
Scimago 29
H-index
Scimago 0,417
Journal Rank
Scimago Physiology (medical) Q3
Quartile Score  
Scopus 270/1140=1,9
Scite Score  
Scopus Physiology (medical) 71/98 (Q3)
Scite Score Rank  
Scopus 0,528
SNIP  
Days from  172
submission  
to acceptance  
Days from  106
acceptance  
to publication  

2019  
Total Cites
WoS
137
Impact Factor 1,410
Impact Factor
without
Journal Self Cites
1,361
5 Year
Impact Factor
1,221
Immediacy
Index
0,294
Citable
Items
34
Total
Articles
33
Total
Reviews
1
Cited
Half-Life
2,1
Citing
Half-Life
9,3
Eigenfactor
Score
0,00028
Article Influence
Score
0,215
% Articles
in
Citable Items
97,06
Normalized
Eigenfactor
0,03445
Average
IF
Percentile
12,963
Scimago
H-index
27
Scimago
Journal Rank
0,267
Scopus
Scite Score
235/157=1,5
Scopus
Scite Score Rank
Physiology (medical) 73/99 (Q3)
Scopus
SNIP
0,38

 

Physiology International
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Physiology International
Language English
Size B5
Year of
Foundation
2006 (1950)
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2498-602X (Print)
ISSN 2677-0164 (Online)

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