Thirty-eight C57BL/6 mice were used in the current study (weighing between 20 g and 30 g) and allocated as follows for each experiment: SNR measurements at 9.4 T – 16 male mice; SNR, visual, and whisker stimulation measurements at 14 T – 13 mice (6F/7M); random stimulation measurements at 14 T – 9 mice (4F/5M). Mice were group-housed (3–4/cage) under a 12 hr light/dark cycle with food and water ad libitum. All animal procedures were conducted in accordance with protocols approved by the Massachusetts General Hospital (MGH) Institutional Animal Care and Use Committee (IACUC) under protocol number 2020N000073, and animals were cared for according to the requirements of the National Research Council’s Guide for the Care and Use of Laboratory Animals.

The awake mouse cradle was designed in Blender (Blender Foundation, Amsterdam, NL) and 3D printed using a Formlabs 3L 3D printer (Formlabs Inc, Somerville, MA, USA). The design incorporated a sliding track which accepted the printed circuit board (PCB) chip transceiver circuit to slide in while the mouse was inserted into the cradle. Two transceiver circuit designs were built, a single loop and a ‘figure 8’ design. Each one keeps the B₁ direction orthogonal to the B₀. The single loop allows for full brain coverage at sufficient depths for subcortical investigation. The ‘figure 8’ design, due to its smaller coil loops and B₁ direction, is limited to precise measurements of shallow brain regions but provides a significant increase in SNR which is beneficial to cortical-specific studies which do not have a need to look deeper into subcortical regions but would benefit from a much higher SNR. The single loop or ‘figure 8’ shape RF coils were built to optimize tuning/matching performance when affixed onto the mouse skull. The coils serve to optimize the B₀ homogeneity by minimizing the air-tissue interface. Each coil was built to weigh ~2.5 g minimizing the recovery/neck strengthening time of each mouse. The standardized RF coil was acquired from MRIBOT LLC (Malden, MA, USA) using the circuit diagram shown in Figure 1—figure supplement 1.

Mice underwent surgery to affix the RF coil to the head. Animals were anesthetized for surgery using isoflurane. Induction was accomplished using 5% isoflurane and 1 L/min of medical air and 0.2 L/min additional O₂ flow. Animals were maintained at 1.5–2% isoflurane using respiration rate as a monitor for anesthesia depth. To attach the head coil, mice were affixed in a stereotaxic stage to stabilize the head with ear and bite bars. The scalp was shaved sterilized with ethanol and iodine and an incision was made to expose an area of the skull the size of the RF coil ring. The skull was cleared of residual tissue and cleaned with 0.3% H₂O₂ and PBS before being dried. The coil was then positioned over the skull covering the underlying brain. The coil ring was lifted ~0.3–0.5 mm above the surface of the skull to avoid over-loading effects and held in place while a thin layer of cyanoacrylate glue was applied to connect the coil to the skull. Once dried (~5–8 min), two-part dental cement (Stoelting Co., Wood Dale, IL, USA) was mixed and applied to cover the coil and exposed bone paying special note to the base of the coil to firmly secure it and avoid air bubbles and drips toward the eyes. The edges of the skin were then glued to close the surgical site. After the dental cement had fully hardened (~10 min), the mouse was released from the stereotaxic stage and received subcutaneous injections of dexamethasone and cefazolin. Mice were then allowed to recover in their home cage for at least 1 week to ensure ample neck strengthening had occurred and the mice could walk with normal head posture.

To acclimate the animals to the MRI environment, each mouse underwent 5 weeks of intermittent habituation procedures to train animals before fMRI experiments by using the following method:

Training days pre-surgery (Phase 1)

Holder training days post-surgery (after recovery) (Phase 2)

Mock-MRI training days (Phase 3)

Training days inside MRI (resting-state and stimulation) (Phase 4)

Following this, data acquisition began, and pupil changes were monitored during scans. During all pupil recordings, animals were secured in the holder and ensured the environment for recording did not allow external light to reach the pupil. Illumination was achieved from a 660 nm LED light source (Thorlabs, Inc, Newton, NJ, USA) delivered via fiber-optic cable. Videos were captured at 30 fps using a 1/3” CMOS camera and 12 mm focal length lens (Tru Components, Chicago, IL, USA).

The pupils of awake mice were recorded during training sessions, allowing investigation into eye movements and pupil diameter changes as potential surrogate of stress-related readouts of the animals. The pupil recordings were measured over 12 training days across 3–4 weeks in Phases 2–4 (Table 1). In Phase 1, animals were gently held in hands, not head-fixed in the cradle. In the second half of Phase 4, head-fixed animals were exposed to air-puff stimulation inside the MR scanner during echo planar imaging (EPI) sequences acquisition. At this stage, animals tended to close their eyes in response to air-puff, so pupil measurements were not feasible to be included for data analysis. The increased eye movements were well detected in Phase 3 when animals were exposed to the real MRI acoustic noise in the head-fixed position (located in the RF shielded box attached to the 14 T magnet, i.e. the CCM box) (Figure 2—figure supplement 1A). Interestingly, in Phase 4, animals showed significantly reduced eye movements during the first day when animals were positioned inside the MR scanner with EPI scanning, while an increase in eye movement went back to the level of Phase 3 in the following training days. The pupil diameter changes were also measured as the function of training days. The power spectral analysis showed ultra-slow pupil dynamic changes with peaked bandwidths less than 0.02 Hz. Interestingly, the power of the ultra-slow pupil dynamics also increased as the function of time similar to eye movements, in particular, during Phase 3. Meanwhile, power reduction in the first day of in-bore training followed with recovered pupil dynamics in the following days was also observed during Phase 4. Although the actual stress of the animals during scanning remains to be further investigated following the 5-week training procedure, the motion-induced image distortion has been dramatically reduced in well-trained animals compared to the start of in-bore training.

While acquiring images to measure SNR improvements, all animals were anesthetized for the duration of MR scanning. Mice were induced using 5% isoflurane in medical air and maintained with 1.0–2.0% isoflurane, adjusted to retain stable physiological conditions while in the magnet. The gas mixture was supplied through the hollow bite bar directly to the mouth and nose of the animal at a rate of 1.0 L/min. Animals were anesthetized to minimize artifacts associated with motion. Physiological monitoring of the animal was performed through the integration of a Small Animal Monitoring and Gating System (Model 1030, SA Instruments, Inc, Stony Brook, NY, USA) capable of recording respiration, body temperature, electrocardiogram, and other parameters. The animal’s breathing rate was continuously monitored and recorded during scanning using a pressure-sensitive sensor-pad and maintained between 50 and 80 breath/min. Animals were kept at a constant temperature of 37°C in the MRI scanner by means of blowing warm air through the bore and recorded using a rectal thermometer probe.

¹H MRI data was acquired using the 14 T and 9.4 T horizontal MRI scanners (Magnex Sci, UK) located at the Athinoula A. Martinos Center for Biomedical Imaging in Boston, MA. The 14 T magnet is equipped with a Bruker Avance Neo Console (Bruker-Biospin, Billerica, MA, USA) and is operated using ParaVision 360 V.3.3. A microimaging gradient system (Resonance Research, Inc, Billerica, MA, USA) provides a peak gradient strength of 1.2 T/m over a 60 mm diameter. The 9.4 T scanner is equipped with a Bruker Avance III HD Console (Bruker-Biospin, Billerica, MA, USA) and is operated using ParaVision 6. A dual microimaging gradient system comprises a Bruker gradient coil capable of 44 G/cm, and a Resonance Research gradient insert capable of 150 G/cm.

The visual and vibrissa stimulation block paradigm was designed as follows: 5 baseline scans, 1 stimulation trigger scan, 19 inter-stimulation scans, and 10 epochs. The visual stimulation used two different wavelengths of light: 530 nm and 490 nm, which flashed at 5 Hz and 5.1 Hz, respectively, for 8 s with a 20 ms ‘on’ time of each illumination. The whisker air-puff stimulation used the same block design as the visual stimulation but was stimulated with a 10 ms puff duration and an 8 Hz firing rate for 8 s. Due to the use of two segments for these experiments, the effective TR was 2 s. Therefore, the stimulation duration for both visual and vibrissa experiments resulted in four consecutive scans being included in the ‘on’ stimulation period and 16 consecutive scans being included in the ‘rest’ period (Figure 3—figure supplement 1). The random vibrissa stimulation paradigm used the same 10 ms air-puff at 8 Hz for 8 s but randomized the ‘rest’ duration. ‘Rest’ durations were 12 s, 22 s, 32 s, and 42 s and randomized in three different sequences maintaining a scan duration of 205 TRs for each experiment.

SNR was computed by dividing mean signal over the standard deviation of the noise. SNR line profile signal data was collected using Amira software (Thermo Fisher Scientific Inc, Waltham, MA, USA). fMRI data was processed using Analysis of Functional Neuroimages (AFNI) (Cox, 1996; Cox and Hyde, 1997). Bruker 2dseq images of the EPI and FLASH scans were converted to AFNI format using ‘to3d’ before masking and aligning the dataset to a template.

To process the high-resolution stimulated BOLD response from the visual and vibrissa stimulation paradigms, we developed a processing pipeline (Figure 3—figure supplement 2). For each experiment, FLASH data were averaged for anatomical localization and the EPI scans were time averaged before registration. The time-averaged EPI was then registered to the FLASH and then to the Australian Mouse Brain Mapping Consortium (AMBMC) atlas (Janke and Ullmann, 2015) where a mask was generated. Each time series for each experiment was concatenated so each experiment contains one long time series dataset using the ‘3dTcat’ command. Data were then despiked before each EPI time point was registered, via a 6-degree transformation, to the atlas using the ‘volreg’ command after which the previously generated mask was applied. The ‘blur’ command was used to smooth the newly transformed data before it was scaled and underwent a linear regression. All concatenated data was then split and summed, per each experimental study, to undergo motion correction and outlier removal. The corrected data was then summed and averaged with the remaining processed data to generate a single time series across all experiments. A clustering threshold was set at 100 voxels and the Pearson correlation values were limited to p≤0.01 (corrected) with estimated false discover rate at q=0.00078. For the random stimulation design, the three runs were concatenated into a single time series each ensuring they all followed the same series of random timings.

We have developed an implantable RF coil which effectively boosted the SNR in ultra-high field MRI. Here, we compared two prototypes: a simple single loop coil design and a ‘figure 8’ coil design. These coils were used to check SNR in anatomical data of anesthetized mice at 9.4 T and 14 T. Figure 1 shows examples of the prototyped RF coils (Figure 1A). The acquired SNR values for each prototype design are shown in Figure 1B. Here, we used a commercial four phase-array coil (400 MHz for 9.4 T) as a control to compare with the implantable RF coils. The single loop implantable coils improved SNR over 100% compared the commercial option while the ‘figure 8’ style showed a more than five times increase at 9.4 T in the cortical regions. The SNR along the dorsal-ventral axis was plotted to compare the B₁ field sensitivity of the single loop and ‘figure 8’ RF coils in comparison with the phase-array coil at 9.4 T, showing significantly increased SNR up to 4 mm depth (Figure 1B). Moving up to 14 T, the SNR improvements increased proportionally as a factor of field strength (Pohmann et al., 2016). This improved SNR allows for high spatial resolution fMRI studies of awake mice. The single loop coil tuned to 14 T (600 MHz) was used for functional data collection in the manuscript. The ‘figure 8’ coil was only used as part of development to show the improvement of the coil design for cortical MR signal measurements.

The RF coil was implanted on the mouse skull to serve as an attachment for head-fixation during awake mouse fMRI at 14 T (Figure 2A). The awake mouse fMRI setup was designed using a 3D printed cradle incorporating a sliding track which enabled the PCB chip mounted on the mouse head to slide through. The PCB chip was then fixed in place at the end of the cradle using friction screws (Video 1). Once the mouse was fixed in the animal cradle, either a mirror or air tube was positioned for pupillometry recording or vibrissa stimulation, respectively. Additionally, an MRI-compatible camera was incorporated to record the pupil dynamic changes and whisking behavior of awake mice during scanning. One key feature of the awake mouse fMRI setup is the plug and play capability for scanning.

This awake mouse fMRI setup enabled high-resolution EPI data acquisition at 100 µm×100 µm×200 µm spatial resolution with a 2 s effective repetition time (TR). The EPI-based T2* images acquired from head-fixed awake mice show little air-tissue interface-induced image distortion with the same spatial resolution as anatomical images (Figure 2C and D). Motion artifacts were detected at some time points of the fMRI time course, presenting large EPI image distortions (Figure 3E, Video 2), but can be removed using a censoring function during data analysis (Figure 3—figure supplement 2). These results have shown that the multi-slice 2D EPI enables brain-wide functional mapping of awake mice.

To map the brain function of awake mice with this high-resolution fMRI method, we first introduced a visual stimulation paradigm. Based on a block design regression analysis, we detected robust BOLD responses. Brain-wide functional maps using the visual stimulation paradigm were seen with activated areas highlighted along the visual pathways (Figure 3). These areas included the visual cortex (VC), superior colliculus (SC), lateral geniculate nucleus (LGN), and association cortex in the ACA. The ROI-specific localization was well characterized by overlapping the brain atlas and functional maps (Figure 3C). The ROI-based time courses demonstrated robust BOLD responses detected in awake mice (Figure 3B).

In contrast to a visual sensation, awake mice may flinch due to the sudden physical vibrissa stimulation causing severe motion artifacts during scanning. Prolonged training was needed to reduce motion artifacts during air-puff stimulation as shown in Video 2 allowing for high-resolution fMRI of awake mice. The activated barrel cortex (BC) and ventroposterior medial nucleus (VPM) were seen related to stimulation of the contralateral whisker pad (time courses in Figure 4B, Figure 3—figure supplement 3). Brain-wide functional maps also showed activation in the motor cortex and a small portion of the ipsilateral BC. These results demonstrated the importance of distinguishing BOLD activation between external stimulation and voluntary movements while also confirming the feasibility to map brain-wide brain activations in awake behaving mice with 14 T fMRI.

An interesting observation from the vibrissa stimulation was the activated VRA. The VRA only showed brief responses to air-puff in contrast to the typical duration of hemodynamic responses observed in the BC and VPM. This presents a good landmark for studying higher-level processing of vibrissa sensation. Voxel-wise cross-correlation analysis was performed based on the VRA-specific fMRI dynamic changes. At a zero time shift (map developed from peak BOLD response), the VRA is strongly correlated with the hippocampus, cingulate cortex, and central thalamic regions (Figure 5A). Nevertheless, at a –6 s time shift (i.e. 2 s before stimulation onset), stronger correlation was observed at the contralateral BC, indicating anticipation of the repetitive air-puff in the block design (Figure 5A). To validate that this early BC activation was caused by learned anticipation of the time-fixed repetitive air-puff stimulation, we also analyzed the VRA-specific cross-correlation in a control group using a randomized stimulation paradigm. Although VRA remained strongly coupled with the other association cortices and subcortical regions at the zero time shift, no correlation was observed from the contralateral BC at the –6 s time shift (Figure 5B). The fMRI time course analysis from the contralateral BC also showed increased BOLD responses before the air-puff in the block design group, but not the randomized control group (Figure 5C). Quantitative analysis showed a significantly higher BOLD signal 2 s before the air-puff stimulation in the standard block design group when compared with the randomized group (Figure 5D). It should be noted that VRA responses between the two groups were similar, further confirming the anticipation-related early BC activation to repetitive air-puff stimulation.

A few important factors should be considered to improve data quality using the implanted RF coils described in the present study. The first is animal motion. As this design was used for awake and minimally restrained mice, the animals would eventually move to adjust themselves (scratching, grooming, teeth grinding, etc.) during the scan. This will affect B₀ homogeneity and can cause ghosting if severe enough. This can be minimized through acclimation training which will also reduce unwanted stress. Other studies have animal restraint mechanisms that seek to restrain the body of the animal (Desai et al., 2011; Chen et al., 2020; Madularu et al., 2017b; Harris et al., 2015) but have the potential to cause unwanted stress which can affect the desired fMRI signals. Furthermore, B₁ variability was present through motion as well due to the current design of the coil. As the RF circuit chip sits above the animal’s neck, body movement could alter the loading of the circuit, inducing B₁ artifacts through lifting or dropping the body toward or away from the circuit chip. Again, these artifacts can be minimized through proper training and stress reduction which was well accomplished for our study through the design and training method (Xu et al., 2022). Here, we see that while animal motion still exists (Figure 2—figure supplement 2) large struggling movements are minimized after the training method. Still, mice have a thin skull, which leads to the air-tissue interface being a non-negligible factor at ultra-high fields (e.g. 14 T). Therefore, the coil implantation shown here has reduced this source of inhomogeneity (Figure 2—figure supplements 1 and 2) and allowed for a consistent and stable shim. By implanting the coil on the surface of the skull, we can achieve a significantly higher SNR which can be comparable to cryoprobe designs at close distances. Moreso, this is the case with the ‘figure 8’ coil shown in this study which gives a five times increase in SNR over the standard commercially available four array mouse head coil for 9.4 T (both operating at room temperature) (Figure 1). This improvement allows much higher spatial resolution in awake mouse fMRI, at a two nanoliter voxel volume, compared to contemporary efforts in human brain mapping at sub-millimeter resolution (0.5–0.8 mm isotropic), a difference of two orders of magnitude (Haenelt et al., 2023; Heidemann et al., 2012; Margalit et al., 2020; Feinberg et al., 2018).

Despite the extensive training procedure of the present work in comparison to the existing awake mouse fMRI studies (training strategies for awake mice fMRI have been reviewed by Mandino et al., 2024 to show the overall training duration of existing studies), stress remains a confounding factor for the brain functional mapping in head-fixed mice. During animal training, we have measured both pupil dynamic and eye motion features from training sessions, both of which could be considered as potential surrogate of the stress levels of animals. It should be noted that stress may be related to increased frequency of eye blinking or twitching movements in human subjects (Marcos-Ramiro et al., 2014; Haak et al., 2009; Del Carretto and Sessam, 2023). However, the eyeblink of head-fixed mice has been used for behavioral conditioning to investigate motor learning in normal behaving mice (Heiney et al., 2014; Chettih et al., 2011; Siegel et al., 2015). Importantly, head-fixed mouse studies have shown that eye movements are significantly reduced compared to the free-moving mice (Meyer et al., 2020). The increased eye movement during the acclimation process would indicate an alleviated stress level of the head-fixed mice in our cases. Meanwhile, stress-related pupillary dilation could dominate the pupil dynamics at the early phase of training (Zeng et al., 2022). We have observed a gradually increased pupil dynamic power spectrum at the ultra-slow frequency during Phase 3, presenting the alleviated stress-related pupil dilation but recovered pupil dynamics to other factors, including arousal, locomotion, startles, etc. in normal behaving mice. Nevertheless, a recent study (Juczewski et al., 2020) shows that the corticosterone concentration in the blood samples of head-fixed mice is significantly reduced on day 25 following the training but remains higher than in the control mice. Also, the time-dependent changes of stress level during scanning could further confound the functional mapping results if longer than 1 hr. Thus, the impact of stress on brain functional mapping with awake mouse fMRI would need further investigation, of which the stress-related functional changes should not be neglected from the existing studies.

There are fMRI studies investigating the visual system in both anesthetized and awake mice (Dinh et al., 2021; Zeng et al., 2022; Huang et al., 1996; Lee et al., 2019; Niranjan et al., 2016; Lungu et al., 2022). In contrast to brain activation patterns at the VC, SC, and LGN (Dinh et al., 2021), robust ACA activation was also detected for awake mouse fMRI in this study (Figure 3). Since ACA has been closely involved in pupil dynamics, as well as arousal state regulation (Ebitz and Platt, 2015; Joshi et al., 2016; Pfeffer et al., 2022), the mapping of the ACA in awake mice during visual stimulation provides a meaningful way to validate the conscious state of mice during scanning. Similarly, there are extensive rodent fMRI studies of vibrissa stimulation (You et al., 2021; Van der Knaap et al., 2021; Lu et al., 2004; Balasco et al., 2022; Ferrier et al., 2020; Choi et al., 2023). In contrast to the anesthetized state, this awake mouse fMRI detected not only activated contralateral BC and VPM, but also spread activation in the motor cortex, and small portion of the ipsilateral BC with positive BOLD signals. Although the air-puff stimulation was set and verified to deflect the whiskers of chosen side, videos of the mouse during scanning show that active bilateral whisking could be initiated upon air-puff. This could lead to bilateral activation of the motor cortex and the ipsilateral BC. Furthermore, studies have been performed to understand the transcallosal activity-mediated excitatory/inhibitory circuits by both fMRI and optical imaging (Chen et al., 2022; Shim et al., 2020; Fujita et al., 2012; Grefkes et al., 2008; Lenzi et al., 2007; Reddy et al., 2000). The potential transcallosal mediation of the negative BOLD signal detected in the superficial cortical area near BC will need to be further investigated. Also, these negative BOLD signals were detected across a large brain area, which is consistent with astrocyte-mediated negative BOLD during brain state changes reported in anesthetized rats (Wang et al., 2018b) and eye open/close-coupled arousal changes in unanesthetized monkeys (Chang et al., 2016). Although astrocytic Ca²⁺ transients coincide with positive BOLD responses in the activated cortical areas, which align with the neurovascular coupling mechanism (Takata et al., 2018), there is emerging evidence to show that astrocytic Ca²⁺ transients are coupled with both positive and negative BOLD responses in anesthetized rats (Wang et al., 2018b) and awake mice (Tong et al., 2024). An intriguing observation is that cortex-wide negative BOLD signals coupled with the spontaneous astrocytic Ca²⁺ transients could co-exist with the positive BOLD signal detected at the activated cortex. Studies have shown that astrocytes are involved in regulating brain state changes (Poskanzer and Yuste, 2016), in particular, during locomotion (Paukert et al., 2014), and startle responses (Srinivasan et al., 2015). These brain state-dependent global negative BOLD responses are also related to the arousal changes of both non-human primates (Chang et al., 2016) and human subjects (Setzer et al., 2022). The established awake mouse fMRI platform with ultra-high spatial resolution will enable the brain-wide activity mapping of the functional nuclei contributing to the brain state changes of head-fixed awake mice in future studies.

Interestingly, vibrissa stimulation also led to robust VRA activation in awake mice (Radwanska et al., 2010). VRA serves as one of the major nodes of the default mode network across different species (Lu et al., 2012; Andrews-Hanna et al., 2010; Vincent et al., 2007; Rilling et al., 2007; Raichle et al., 2001). The vibrissa stimulation-evoked VRA activation suggests the higher-level cortical function contribute to vibrissa sensory processing in awake mice.

There are extensive studies investigating brain activation responsible for anticipation with fMRI and electrophysiological recordings (Zhao et al., 2019; Martin et al., 2009; Zhao et al., 2022; Ploghaus et al., 2003; Sirotin and Das, 2009). In contrast to the reward anticipation or audiovisual anticipation of naturalistic music and movie clips that demand more complex cognitive processing (Pezzulo et al., 2007; McRobert et al., 2011; Burton et al., 2009; Ciesielski et al., 2012), the repetitive air-puff stimulation delivered during head-fixed training for fMRI studies could serve as a simple paradigm to process the anticipatory responses in awake mice. Based on cross-correlation analysis with evoked VRA BOLD responses, the strongest correlation with the BC was detected from 6 s lag-time-based correlation maps, showing a positive BOLD signal at a time point 2 s prior to stimulus onset (Figure 5). This anticipatory BC response was not detected when the air-puff stimulation paradigm was randomized in another group of mice. VRA is known to be involved in prediction (Smith et al., 2018; Miller et al., 2019; Auger and Maguire, 2013) and has been coupled with temporal prediction in rodents (Miller et al., 2019; Wyass and Van Groen, 1992), as well as navigation efficiency involving spatial reference cues (Miller et al., 2019; Auger and Maguire, 2013; Wyass and Van Groen, 1992). Additionally, external somatosensory cues (e.g. the air-puff or brushing of whiskers) are an important factor when investigating prediction processing (Taube, 2007; Valerio and Taube, 2012; Todd et al., 2019; Cooper et al., 2001; Keene and Bucci, 2021). Previous work has shown that prediction of external stimulation will cause a hemodynamic response even in the absence of a stimulus (Sirotin and Das, 2009; Yu et al., 2019). In our study, we show that after continued regularly spaced stimulation, early somatosensory hemodynamic responses begin to have a significant impact seen in the averaged BOLD response time course. These anticipatory hemodynamic responses are a result of the continuous training for mice experiencing months of repetitive stimulation. The increased BOLD signal in the BC before the stimulus onset shows strong cross-correlation to the VRA activation, but VRA activation is not dependent on the pre-stimulus activation in the BC. This can be seen through the comparable VRA BOLD responses between repetitive and randomized air-puff stimulation paradigms (Figure 5C). This result indicates that VRA response mediates external sensory perception and may serve as a key association cortical area for the processing of the anticipated vibrissa signals but is not solely dependent on the prediction of incoming stimulus.