S. M. Sternson, J. Nicholas-betley, and Z. F. Cao, Neural circuits and motivational processes for hunger, Current opinion in neurobiology, vol.23, pp.353-360, 2013.

P. J. Kennedy and M. L. Shapiro, Motivational states activate distinct hippocampal representations to guide goal-directed behaviors, Proc Natl Acad Sci, vol.106, pp.10805-10810, 2009.

M. Shojaie, F. Ghanbari, and N. Shojaie, Intermittent fasting could ameliorate cognitive function against distress by regulation of inflammatory response pathway, Journal of advanced research, vol.8, pp.697-701, 2017.

T. L. Jensen, M. K. Kiersgaard, D. B. Sorensen, and L. F. Mikkelsen, Fasting of mice: a review, Laboratory animals, vol.47, pp.225-240, 2013.

T. M. Hsu, A. N. Suarez, and S. E. Kanoski, Ghrelin: A link between memory and ingestive behavior, Physiol Behav, vol.162, pp.10-17, 2016.

T. Eichele, Prediction of human errors by maladaptive changes in event-related brain networks, Proc Natl Acad Sci, vol.105, pp.6173-6178, 2008.

Q. Li, Resting-state functional MRI reveals altered brain connectivity and its correlation with motor dysfunction in a mouse model of Huntington's disease, 2017.

V. Zerbi, Resting-state functional connectivity changes in aging apoE4 and apoE-KO mice, J Neurosci, vol.34, pp.13963-13975, 2014.
DOI : 10.1523/jneurosci.0684-14.2014

URL : http://www.jneurosci.org/content/34/42/13963.full.pdf

M. P. Van-den-heuvel and H. E. Hulshoff-pol, Exploring the brain network: a review on resting-state fMRI functional connectivity, European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology, vol.20, pp.519-534, 2010.

A. Uematsu, A. Kitamura, K. Iwatsuki, H. Uneyama, and T. Tsurugizawa, Correlation Between Activation of the Prelimbic Cortex, Basolateral Amygdala, and Agranular Insular Cortex During Taste Memory Formation, Cereb Cortex, vol.25, pp.2719-2728, 2015.

T. Tsurugizawa, A. Uematsu, H. Uneyama, and K. Torii, Different BOLD responses to intragastric load of L-glutamate and inosine monophosphate in conscious rats, Chem Senses, vol.36, pp.169-176, 2011.

H. Lu, Rat brains also have a default mode network, Proc Natl Acad Sci, vol.109, pp.3979-3984, 2012.
DOI : 10.1073/pnas.1200506109

URL : http://www.pnas.org/content/109/10/3979.full.pdf

J. A. Ash, Functional connectivity with the retrosplenial cortex predicts cognitive aging in rats, Proc Natl Acad Sci, vol.113, pp.12286-12291, 2016.
DOI : 10.1073/pnas.1525309113

URL : https://www.pnas.org/content/pnas/113/43/12286.full.pdf

R. W. Chan, Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity, Proc Natl Acad Sci, vol.114, pp.6972-6981, 2017.
DOI : 10.1073/pnas.1703309114

URL : https://www.pnas.org/content/pnas/114/33/E6972.full.pdf

S. M. Huang, Inter-Strain Differences in Default ModeNetwork: A Resting State fMRI Study on Spontaneously Hypertensive Rat and Wistar Kyoto Rat, Scientific reports, vol.6, 2016.
DOI : 10.1038/srep21697

URL : https://www.nature.com/articles/srep21697.pdf

S. Orfanos, Investigating the impact of overnight fasting on intrinsic functional connectivity: a double-blind fMRI study, Brain imaging and behavior, 2017.

A. M. Van-opstal, Brain activity and connectivity changes in response to glucose ingestion, Nutritional neuroscience, pp.1-8, 2018.

A. Zalesky, A. Fornito, and E. T. Bullmore, Network-based statistic: identifying differences in brain networks, Neuroimage, vol.53, pp.1197-1207, 2010.
DOI : 10.1016/j.neuroimage.2010.06.041

Y. Ma, Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons, Proc Natl Acad Sci, vol.113, pp.8463-8471, 2016.
DOI : 10.1073/pnas.1525369113

URL : http://europepmc.org/articles/pmc5206542?pdf=render

Q. H. Zou, An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF, J Neurosci Methods, vol.172, pp.137-141, 2008.

K. J. Kovacs, Measurement of immediate-early gene activation-c-fos and beyond, J Neuroendocrinol, vol.20, pp.665-672, 2008.

Y. Abe, T. Tsurugizawa, and D. Le-bihan, Water diffusion closely reveals neural activity status in rat brain loci affected by anesthesia, PLoS biology, vol.15, 2017.
DOI : 10.1371/journal.pbio.2001494

URL : https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.2001494&type=printable

T. Tsurugizawa, L. Ciobanu, and D. Le-bihan, Water diffusion in brain cortex closely tracks underlying neuronal activity, Proc Natl Acad Sci, vol.110, pp.11636-11641, 2013.
DOI : 10.1073/pnas.1303178110

URL : http://www.pnas.org/content/110/28/11636.full.pdf

T. Tsurugizawa, Y. Abe, and D. Le-bihan, Water apparent diffusion coefficient correlates with gamma oscillation of local field potentials in the rat brain nucleus accumbens following alcohol injection, J Cereb Blood Flow Metab, vol.37, pp.3193-3202, 2017.

M. A. Mintun, A. G. Vlassenko, M. M. Rundle, and M. E. Raichle, Increased lactate/pyruvate ratio augments blood flow in physiologically activated human brain, Proc Natl Acad Sci, vol.101, pp.659-664, 2004.
DOI : 10.1073/pnas.0307457100

URL : http://www.pnas.org/content/101/2/659.full.pdf

L. Mazuel, A neuronal MCT2 knockdown in the rat somatosensory cortex reduces both the NMR lactate signal and the BOLD response during whisker stimulation, PLos One, vol.12, 2017.

R. Gruetter, K. Ugurbil, and E. R. Seaquist, Effect of acute hyperglycemia on visual cortical activation as measured by functional MRI, Journal of neuroscience research, vol.62, pp.279-285, 2000.

D. Burdakov, S. M. Luckman, and A. Verkhratsky, Glucose-sensing neurons of the hypothalamus, Philosophical transactions of the Royal Society of London. Series B, Biological sciences, vol.360, pp.2227-2235, 2005.

T. Tsurugizawa, Neuroimaging of gut nutrient perception, Current pharmaceutical design, vol.20, pp.2738-2744, 2014.

T. Tsurugizawa, Mechanisms of neural response to gastrointestinal nutritive stimuli: the gut-brain axis, Gastroenterology, vol.137, pp.262-273, 2009.

T. Tsurugizawa and H. Uneyama, Differences in BOLD responses to intragastrically infused glucose and saccharin in rats, Chem Senses, vol.39, pp.683-691, 2014.

Q. Wu, The temporal pattern of cfos activation in hypothalamic, cortical, and brainstem nuclei in response to fasting and refeeding in male mice, Endocrinology, vol.155, pp.840-853, 2014.

Y. Oomura, Feeding regulation by endogenous sugar acids through hypothalamic chemosensitive neurons, Brain Res Bull, vol.17, pp.551-562, 1986.

B. C. Small and B. C. Peterson, Establishment of a time-resolved fluoroimmunoassay for measuring plasma insulin-like growth factor I (IGF-I) in fish: effect of fasting on plasma concentrations and tissue mRNA expression of IGF-I and growth hormone (GH) in channel catfish (Ictalurus punctatus), Domestic animal endocrinology, vol.28, pp.202-215, 2005.

G. J. Crystal, Isoflurane-induced coronary vasodilation, Anesthesiology, vol.81, pp.778-779, 1994.

T. Tsurugizawa, Y. Takahashi, and F. Kato, Distinct effects of isoflurane on basal BOLD signals in tissue/vascular microstructures in rats, Scientific reports, vol.6, 2016.

M. G. Sommers, J. Van-egmond, L. H. Booij, and A. Heerschap, Isoflurane anesthesia is a valuable alternative for alpha-chloralose anesthesia in the forepaw stimulation model in rats, NMR Biomed, vol.22, pp.414-418, 2009.

J. Schummers, H. Yu, and M. Sur, Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex, Science, vol.320, pp.1638-1643, 2008.

Z. Wang, W. Luo, P. Li, J. Qiu, and Q. Luo, Acute hyperglycemia compromises cerebral blood flow following cortical spreading depression in rats monitored by laser speckle imaging, Journal of biomedical optics, vol.13, 2008.

F. F. Horber, Isoflurane and whole body leucine, glucose, and fatty acid metabolism in dogs, Anesthesiology, vol.73, pp.82-92, 1990.

Q. Bukhari, A. Schroeter, D. M. Cole, and M. Rudin, Resting State fMRI in Mice Reveals Anesthesia Specific Signatures of Brain Functional Networks and Their Interactions, Frontiers in neural circuits, vol.11, 2017.

M. Carus-cadavieco, Gamma oscillations organize top-down signalling to hypothalamus and enable food seeking, Nature, vol.542, pp.232-236, 2017.

B. R. Noga, LFP Oscillations in the Mesencephalic Locomotor Region during Voluntary Locomotion, Frontiers in neural circuits, vol.11, 2017.

A. Shmuel and D. A. Leopold, Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest, Human brain mapping, vol.29, pp.751-761, 2008.

S. Jaime, Delta Rhythm Orchestrates the Neural Activity Underlying the Resting State BOLD Signal via Phase-amplitude Coupling, Cereb Cortex, pp.1-15, 2017.

R. M. Hutchison, N. Hashemi, J. S. Gati, R. S. Menon, and S. Everling, Electrophysiological signatures of spontaneous BOLD fluctuations in macaque prefrontal cortex, Neuroimage, vol.113, pp.257-267, 2015.

C. R. Burgess, Hunger-Dependent Enhancement of Food Cue Responses in Mouse Postrhinal Cortex and Lateral Amygdala, Neuron, vol.91, pp.1154-1169, 2016.

A. J. Nelson, E. L. Hindley, J. E. Haddon, S. D. Vann, and J. P. Aggleton, A novel role for the rat retrosplenial cortex in cognitive control, Learning & memory, vol.21, pp.90-97, 2014.

K. L. Ellacott, G. J. Morton, S. C. Woods, P. Tso, and M. W. Schwartz, Assessment of feeding behavior in laboratory mice, Cell Metab, vol.12, pp.10-17, 2010.

Y. Xue and P. Bogdan, Reliable Multi-Fractal Characterization of Weighted ComplexNetworks: Algorithms and Implications, Scientific reports, vol.7, 2017.

J. Hutsler and R. A. Galuske, Hemispheric asymmetries in cerebral cortical networks, Trends in neurosciences, vol.26, pp.429-435, 2003.

G. Ehret, Left hemisphere advantage in the mouse brain for recognizing ultrasonic communication calls, Nature, vol.325, pp.249-251, 1987.

B. Kolb, R. J. Sutherland, A. J. Nonneman, and I. Q. Whishaw, Asymmetry in the cerebral hemispheres of the rat, mouse, rabbit, and cat: the right hemisphere is larger, Exp Neurol, vol.78, pp.348-359, 1982.

Q. Zou, C. W. Wu, E. A. Stein, Y. Zang, and Y. Yang, Static and dynamic characteristics of cerebral blood flow during the resting state, Neuroimage, vol.48, pp.515-524, 2009.

Y. Komaki, Functional brain mapping using specific sensory-circuit stimulation and a theoretical graph network analysis in mice with neuropathic allodynia, Scientific reports, vol.6, 2016.

K. Yoshida, Physiological effects of a habituation procedure for functional MRI in awake mice using a cryogenic radiofrequency probe, J Neurosci Methods, vol.274, pp.38-48, 2016.

A. Kitamura, Ingested d-Aspartate Facilitates the Functional Connectivity and Modifies Dendritic Spine Morphology in Rat Hippocampus, Cereb Cortex, 2018.

A. Zalesky, Whole-brain anatomical networks: does the choice of nodes matter?, Neuroimage, vol.50, pp.970-983, 2010.

G. Paxinos and C. Watson, The Rat Brain in Stereotaxic Coodinates, 1998.

O. Sporns and R. F. Betzel, Modular Brain Networks, Annu Rev Psychol, vol.67, pp.613-640, 2016.

, Scientific RepoRts |, vol.9, p.2976, 2019.

V. D. Blondel, J. L. Guillaume, R. Lambiotte, and E. Lefebvre, Fast unfolding communities in large networks, J. Stat. Mech, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01146070

A. Lancichinetti and S. Fortunato, Consensus clustering in complex networks, Scientific reports, vol.2, 2012.

B. H. Good, Y. A. De-montjoye, and A. Clauset, Performance of modularity maximization in practical contexts. Physical review. E, Statistical, nonlinear, and soft matter physics 81, vol.046106, 2010.

M. E. Newman, Analysis of weighted networks. Physical review. E, Statistical, nonlinear, and soft matter physics 70, p.56131, 2004.

M. Rubinov and O. Sporns, Weight-conserving characterization of complex functional brain networks, Neuroimage, vol.56, pp.2068-2079, 2011.

G. J. Thompson, Neural correlates of time-varying functional connectivity in the rat, Neuroimage, vol.83, pp.826-836, 2013.