Kengo Takahashi1,2, Filip Sobczak1,2, Patricia Pais-Roldán3, and Xin Yu1,4
1High-field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2Graduate Training Centre of Neuroscience, Tübingen, Germany, 3Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich, Jülich, Germany, 4Athinoula A. Martinos Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
Synopsis
The lateral hypothalamus (LH) is known
to mediate different vigilance states and modulate pupil dilation through
various neural populations. However, measuring subcortical neuronal activity
non-invasively while assessing the brain state has remained challenging.
Recently, it has been shown that the coupling between fMRI brain signals and
pupil size fluctuations depends on the underlying brain state. In this work, we
suggest that the synchronization of LH fMRI signals with pupil fluctuations may
indicate modulation of the vigilance level of the brain.
Introduction
Animals under anesthesia show altered brain states mimicking different
stages of sleep. The lateral hypothalamus (LH) plays an important role in alternating
brain states, in particular, mediating vigilance levels during rapid eye
movement (REM)1 or non-REM (NREM)2 sleep and wakefulness3.
Meanwhile, pupil dynamics have been often used as an arousal index to tract
brain state changes in both anesthetized4 or awake animals5
and humans6. The noradrenergic projection circuit from the locus
coeruleus (LC) to the anterior cingulate cortex (ACC) has been mostly
investigated to interpret the brain state-dependent pupil dynamics7,8,9.
Lately, we have detected that the neuronal oscillation of ACC shows both
positive and negative correlation to pupil dynamics in anesthetized rats, which
cannot be explained solely by the noradrenergic neuromodulation. The
subcortical regulation of the opposite correlation features of ACC remains unknown.
The LH has been reported to mediate both brain state changes10 and autonomic
activity11, both of which could contribute to regulating pupil
dynamics. We hypothesize that the LH interacts with the ACC to modulate the brain
state-dependent pupil dynamics, presenting different correlation patterns. Here, we performed electrophysiological
recordings in both LH and ACC and simultaneous fMRI and fiber photometry-based
neuronal Ca2+ in the ACC to elucidate the neuronal basis of the
opposite correlations to pupil dynamics in varied brain statesMethods
LFPs recording and pupil size detection
Resting state
electrophysiology signals were recorded from the LH and ACC simultaneously with
pupil size detection in 15-min trials from nine rats anesthetized with
alpha-chloralose (n= 89) (Fig 1a).
fMRI with concurrent pupil size detection and optical fiber
calcium signal recording
Resting state whole-brain fMRI and optical
fiber calcium signal (GCaMP) recording from the ACC and pupil size detection
were acquired in 15-min trials simultaneously from nine rats anesthetized with alpha-chloralose
(n= 61) with a 14.1 T/26 cm magnet (Magnex), as previously described4
(Fig 3a).Results
Electrophysiological recordings demonstrated that LFP delta (1-4Hz)
power in both of the LH and ACC exhibited a positive or negative correlation with
pupil size fluctuation (Fig 1b and 1c).
When pupil dynamics and LH-delta power were anti-correlated (state #1), the
correlation between pupil dynamics and ACC-delta power was always negative (Fig 1d). Under this state, the LH and
ACC exhibited their highest coherence at 2Hz (Fig 2b). In contrast, when LH-delta power was positively correlated
with the pupil dynamics (state #2), the highest coherence between the LH and
ACC occurred at 3Hz (Fig 2b). In
addition, phase-amplitude coupling at the ACC between the phase of delta and the
amplitude of all other LFP frequency bands was observed to be higher in state #1
(Fig 2c). Thus, LH delta power
presents a robust indicator to differentiate brain state-dependent correlation
features to pupil dynamics. Similar to the electrophysiological signals in the
ACC, 1-4Hz calcium power fluctuations in the ACC also showed positive or
negative correlations with the pupil dynamics (Fig 3b). Interestingly, during the negative correlation state, ACC
1-4Hz calcium power was also negatively correlated with the fMRI signal in the
LH (Fig 3c). Previous study also suggested
a potential negative correlation of BOLD fMRI with delta power fluctuation in the
subcortical region, e.g. striatum12. It is possible that the BOLD
fMRI signal is negatively correlated with the delta power fluctuation in LH too.
To examine whether the fMRI signal in the LH could differentiate brain-state
dependent pupil dynamics similar to the electrophysiological signals, we
correlated the pupil dynamics with the whole-brain fMRI, showing both positive
and negative correlation in LH region (Fig
4a). Importantly, when categorizing trials showing positive correlation
between pupil dynamics and LH fMRI signal (Fig
4a), we detected robust negative correlations between ACC 1-4Hz calcium
power and pupil dynamics (Fig 4b), which
is similar to the electrophysiological results (Fig 1d). This result indicates that the LH fMRI signal can also be
used to differentiate brain states, presenting opposite correlation with pupil
dynamics to delta power in the LH.Discussion and Conclusion
We analyzed the electrophysiological signal (in
particular, the delta power) and fMRI signal in the LH together with pupil
dynamics, showing a strong indicator of different brain states represented by
positive and negative correlations of ACC activity and pupil dynamics. Interestingly, when
LH delta power is negatively correlated with pupil dynamics, a 2Hz dominant
brain state is observed, which is consistent with the NERM condition13.
In contrast, when the LH delta power is positively correlated with pupil
dynamics, a 3Hz dominant state is more correlated with a REM state during sleep14.
Meanwhile, besides the electrical signals recorded from the LH, we could use
the fMRI signal from the LH to determine the different brain state, but showing the opposite correlation pattern with electrophysiology.Acknowledgements
This work was supported by Max Planck Society and the Graduate Training Center of Neuroscience, International Max Planck Research School.References
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