First, we plotted the average event-related potentials (ERPs) for each auditory stimulus in the marmosets (Figure 2). The auditory evoked potential (AEP) was prominent in the Noise condition, reflecting the clear onset of the stimuli (see Figure 1D). To compare the averaged ERPs between call types and noise stimuli, we applied a one-way analysis of variance (ANOVA) with stimuli as the between-subjects factor in Cz response. We found a significant main effect of stimuli on Cz activity at 13-18 ms, 28-36 ms, and 45-88 ms after stimulus onset, respectively (p < 0.05). Post hoc multiple comparison analysis with Tukey's method showed that the difference was between noise and other calls (p < 0.05), but there was no difference between marmoset call types. The result suggests that differences in brain activity by call type could not be observed from the event-related potentials alone.
Next, we conducted a time-frequency analysis for each subject. Figure 3 shows an example of the time-frequency maps for the Tsik-string call obtained by subject R (elder, Figure 3A) and subject Y (younger, Figure 3B). We found that event-related spectral power increased at a lower frequency of approximately 20-50 Hz immediately after stimulus onset. These responses were prominently observed in the Cz. In contrast, the gamma range power (over 30 Hz) decreased after stimulus onset compared to the baseline period. In addition, this decline lasted for 1 s. No decrease in event-related power was observed in elder individuals over 8 years. In these examples, the elder individuals had a stronger initial response to the call in the vertex region (Cz), while the younger individuals showed a sustained decrease in γ-band activity during the call presentation. The results suggest that there are differences in initial and sustained responses depending on the subject's age.
Finally, we investigated the relationship between subject age and event-related spectral perturbation (ERSP) power in the initial transient response (Figure 4A) and sustained response (Figure 4B). A two-way ANOVA with Stimulus type as a within-subject factor and age as a between-subject factor was conducted to determine the contribution of the type of auditory stimulus and the subject's age to EEG activity. The initial, transient responses in the Fz showed significant main effects of Stimulus type (F (3,24) = 9.020, p < 0.001) and Age (F (8,24) = 3.934, p = 0.004). However, there was no significant interaction between the Stimulus type and Age (p = 0.144). In the transient responses in Cz, there was a significant main effect of Stimulus type (F (3,24) = 8.533, p < 0.001), but no effect of Age (F (8,24) = 2.215, p = 0.073), and no interaction (p = 0.228). For sustained responses, there were significant main effects of both Stimulus type and Age (F (3,24) = 9.020, p < 0.001; F (8,24) = 3.934, p = 0.004, respectively) on Fz. No significant interaction was observed (P = 0.144). The sustained responses in Cz showed a significant main effect of Stimulus type (F (3,24) = 8.533, p < 0.001) but no main effect of Age (F(8,24) = 2.215, p = 0.073) or interaction (p = 0.228). These results suggest that in the middle-frontal area (Fz), initial transient responses to call and noise stimuli varied greatly with increasing age, and sustained responses were suppressed in younger age groups. These may reflect the functional maturation of the frontal region.
Previous neurophysiological studies have reported neuronal responses in the primary auditory cortex during vocalization in marmosets9,38. In addition, more than half of these neurons exhibit an inhibitory response that persists during vocalization9,38. Furthermore, previous electrophysiological studies in nonhuman primates and humans have shown that high gamma band activity in the local field potential (LFP) and ECoG correlates well with firing rates in neurons39,40,41,42. Scalp EEG is a spatiotemporally smoothed version of the LFP, integrated over an area of 1 cm2 or more43. Although the high-gamma component of the EEG has a lower correlation with firing rates than LFP and ECoG, it is thought to code the output signal as an integrated range of several centimeters. Therefore, the sustained decrease in gamma band power observed at Cz in our experiments may reflect the activity of neuronal clusters showing suppressed activity during call emission, which is found in the auditory cortices. In contrast, previous electrophysiological studies have reported that more neurons in the frontal cortex, mainly in the premotor cortex, exhibit excitatory responses during call vocalization13. Interestingly, sustained inhibitory activity was observed even when the Fz was placed in the frontal area in our experiments, although distinct neural mechanisms were observed between vocal perception and production. A recent fMRI study has further identified several subregions in the frontal cortex, including the anterior cingulate cortex as well as the premotor cortex, as 'vocal patches' that respond to species-specific calls in marmosets19. Our results reflect the overall brain activity in these regions.
In the current experiment, we used only midline positions for the exploration electrodes (Fz, Cz, Pz, and Oz); therefore, we cannot mention any differences between the right and left EEG activity of auditory processing. In the future, we need to investigate the laterality of the neural activity underlying vocal processing.
Prior studies have reported that low gamma activity in the LFP and ECoG is generated by synaptic inputs to pyramidal cells. Thus, a high gamma activity reflects a signal component closer to the output, whereas a low gamma activity reflects those closer to the input39. In the present study, we observed transient activity in the beta and low-gamma bands immediately following exposure to a call. These responses may reflect sensory input signals to the cortex. The advantage of our method is that it can capture the brain activity from different neuronal populations as dynamic changes with high temporal resolution. To our knowledge, this is the first study to reveal how scalp EEG signals change during species-specific vocal perception in marmosets. The present results provide new insights into the integration of neural representations through recordings of a wide range of brain regions.

Figure 1: Experimental setup. (A) An exemplar image of a subject during recording. The marmoset is seated in a chair and the head is fixed to the chair by a mask. The mouth is maintained open to facilitate breathing and drinking reward fluids, and the electrodes were attached to the top of the head. (B) Equipment: Sound stimuli are presented through a speaker. An amplifier, electrode input box, and a monitoring camera were also installed. (C) Location of electrodes: Electrodes were placed on Fz, Cz, Pz, Oz, A1, and A2 according to the International 10-20 System. We defined the location of electrodes using the inion, nasion, and bilateral preauricular points as anatomical landmarks. The C3 or C4 electrode was used as the ground electrode. (D) Sonograms (left panel) and spectrograms (left panel) for all audio stimuli. The Phee call is a single long call lasting less than 2 s. The Tsik-Ek call is a combination call of a Tsik followed by an Ek. Two sets of the compound call presented approximately 1 s. The Tsik-string call is a repetitive call of Tsik5, and four Tsik were presented approximately for 1 s in the stimulus. As a non-call stimulus, we used a white noise signal generated by a custom script that lasted about 1 s. The sound onset latencies were visually inspected on a digital audio editor. The red arrows indicate each latency, Phee call 49 ms, Tsik-Ek call 35 ms, Tsik-string call 16 ms, and white noise 0 ms. Please click here to view a larger version of this figure.

Figure 2: Grand-averaged event-related potentials to the Phee, Tsik-Ek, and Tsik-string calls and noise. (n = 9) The activity was aligned to the onset of each call or white noise. The black horizontal arrow indicates the period for the stimulus presentation. The Phee call lasted for approximately 2 s, the rest lasted for 1 s. The red horizontal lines at Cz indicate the periods with significant differences between the auditory stimuli. All of these were between the Noise and the other calls, and there were no differences between the calls. Please click here to view a larger version of this figure.

Figure 3: Example of time-frequency maps for calls. (A) The ERSP map for the Tsik-string call in subject R (145 months old); (B) The EPSP map for the same Tsik-string call in subject Y (23 months old). The left and right panels show the data recorded from the Fz and Cz electrodes, respectively. The red vertical lines indicate the timing of the onset of the auditory file, not the call onset. Abbreviation: EPSP = event-related spectral perturbation. Please click here to view a larger version of this figure.

Figure 4: Relationship between mean event-related power and age of subjects. (A) Relationship between mean event-related power at α and β-band and age of subjects. The mean ERSP power was calculated at 8-29 Hz from a 1-150 ms period from each stimulus onset compared to those in the baseline period (-200 to 0 ms before stimulus onset). The left and right panels show the data recorded from the Fz and Cz electrodes, respectively. (B) Relationship between mean event-related power at γ-band and age of subjects. The mean ERSP power was calculated at 30-100 Hz from a 151-950 ms period from each stimulus onset compared to those in the baseline period (-200 to 0 ms before stimulus onset). Thus, negative ERSP values indicate a decrease in power compared to that before the stimulus presentation. Abbreviation: ERSP = event-related spectral perturbation. Please click here to view a larger version of this figure.
Supplemental File 1: A zip file containing four audio files used in the experiments. The PH.wav file includes a stimulus with one long Phee call; TE.wav contains two Tsik-Ek calls with an interval between them; MB.wav contains a Tsik-string call stimulus with four consecutive Tsik (also called mobbing call); NO.wav contains a program-generated white Gaussian noise. Please click here to download this File.
Supplemental File 2: A zip file containing postprocessing code. Please click here to download this File.