Azevedo, E. P. et al. A role of Drd2 hippocampal neurons in context-dependent food intake. Neuron 102, 873–886 (2019).
Herzog, L. E. et al. Interaction of taste and place coding in the hippocampus. J. Neurosci. 39, 3057–3069 (2019).
Davidson, T. L. & Jarrard, L. E. A role for hippocampus in the utilization of hunger signals. Behav. Neural Biol. 59, 167–171 (1993).
Davidson, T. L., Kanoski, S. E., Schier, L. A., Clegg, D. J. & Benoit, S. C. A potential role for the hippocampus in energy intake and body weight regulation. Curr. Opin. Pharmacol. 7, 613–616 (2007).
Noble, E. E. et al. Hypothalamus–hippocampus circuitry regulates impulsivity via melanin-concentrating hormone. Nat. Commun. 10, 4923 (2019).
Hsu, T. M. et al. Hippocampus ghrelin signaling mediates appetite through lateral hypothalamic orexin pathways. eLife 4, e11190 (2015).
Sternson, S. M. & Eiselt, A.-K. Three pillars for the neural control of appetite. Annu. Rev. Physiol. 79, 401–423 (2017).
Dalley, J. W. & Robbins, T. W. Fractionating impulsivity: neuropsychiatric implications. Nat. Rev. Neurosci. 18, 158–171 (2017).
Sunkin, S. M. et al. Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system. Nucleic Acids Res. 41, D996–D1008 (2013).
Ludwig, D. S. et al. Melanin-concentrating hormone overexpression in transgenic mice leads to obesity and insulin resistance. J. Clin. Invest. 107, 379–386 (2001).
Alon, T. & Friedman, J. M. Late-onset leanness in mice with targeted ablation of melanin concentrating hormone neurons. J. Neurosci. 26, 389–397 (2006).
Huang, Y. et al. The insulo-opercular cortex encodes food-specific content under controlled and naturalistic conditions. Nat. Commun. 12, 3609 (2021).
Fries, P. A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn. Sci. 9, 474–480 (2005).
Yassa, M. A. & Stark, C. E. L. Pattern separation in the hippocampus. Trends Neurosci. 34, 515–525 (2011).
Bakker, A., Kirwan, C. B., Miller, M. & Stark, C. E. L. Pattern separation in the human hippocampal CA3 and dentate gyrus. Science 319, 1640–1642 (2008).
Kim, K., Hsieh, L.-T., Parvizi, J. & Ranganath, C. Neural repetition suppression effects in the human hippocampus. Neurobiol. Learn. Mem. 173, 107269 (2020).
Knutson, B., Adams, C. M., Fong, G. W. & Hommer, D. Anticipation of increasing monetary reward selectively recruits nucleus accumbens. J. Neurosci. 21, RC159 (2001).
Leuze, C. et al. Comparison of diffusion MRI and CLARITY fiber orientation estimates in both gray and white matter regions of human and primate brain. NeuroImage 228, 117692 (2021).
Matsumoto, R. et al. Functional connectivity in the human language system: a cortico-cortical evoked potential study. Brain 127, 2316–2330 (2004).
Miller, K. J., Müller, K.-R. & Hermes, D. Basis profile curve identification to understand electrical stimulation effects in human brain networks. PLoS Comput. Biol. 17, e1008710 (2021).
Miller, K. J. et al. Canonical response parameterization: quantifying the structure of responses to single-pulse intracranial electrical brain stimulation. PLoS Comput. Biol. 19, e1011105 (2023).
Renier, N. et al. iDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging. Cell 159, 896–910 (2014).
Shivacharan, R. S. et al. Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating. Nat. Med. 28, 1791–1796 (2022).
Barbosa, D. A. N. et al. Aberrant impulse control circuitry in obesity. Mol. Psychiatry 27, 3374–3384 (2022).
Kanoski, S. E. & Grill, H. J. Hippocampus contributions to food intake control: mnemonic, neuroanatomical, and endocrine mechanisms. Biol. Psychiatry 81, 748–756 (2017).
Franken, I. H. A., Huijding, J., Nijs, I. M. T. & van Strien, J. W. Electrophysiology of appetitive taste and appetitive taste conditioning in humans. Biol. Psychol. 86, 273–278 (2011).
Chao, A. M. et al. Sex/gender differences in neural correlates of food stimuli: a systematic review of functional neuroimaging studies. Obes. Rev. 18, 687–699 (2017).
Conturo, T. E. et al. Tracking neuronal fiber pathways in the living human brain. Proc. Natl Acad. Sci. USA 96, 10422–10427 (1999).
Grisot, G., Haber, S. N. & Yendiki, A. Diffusion MRI and anatomic tracing in the same brain reveal common failure modes of tractography. NeuroImage 239, 118300 (2021).
Keller, C. J. et al. Mapping human brain networks with cortico-cortical evoked potentials. Philos. Trans. R. Soc. B 369, 20130528 (2014).
Fanselow, M. S. & Dong, H.-W. Are the dorsal and ventral hippocampus functionally distinct structures? Neuron 65, 7–19 (2010).
Miocinovic, S. et al. Cortical potentials evoked by subthalamic stimulation demonstrate a short latency hyperdirect pathway in humans. J. Neurosci. 38, 9129–9141 (2018).
Chen, W. et al. Prefrontal-subthalamic hyperdirect pathway modulates movement inhibition in humans. Neuron 106, 579–588 (2020).
Suarez, A. N., Liu, C. M., Cortella, A. M., Noble, E. E. & Kanoski, S. E. Ghrelin and orexin interact to increase meal size through a descending hippocampus to hindbrain signaling pathway. Biol. Psychiatry 87, 1001–1011 (2020).
Stice, E., Burger, K. & Yokum, S. Caloric deprivation increases responsivity of attention and reward brain regions to intake, anticipated intake, and images of palatable foods. NeuroImage 67, 322–330 (2013).
Guthoff, M. et al. Insulin modulates food-related activity in the central nervous system. J. Clin. Endocrinol. Metab. 95, 748–755 (2010).
Buzsáki, G. Theta rhythm of navigation: link between path integration and landmark navigation, episodic and semantic memory. Hippocampus 15, 827–840 (2005).
Nyhus, E. & Curran, T. Functional role of gamma and theta oscillations in episodic memory. Neurosci. Biobehav. Rev. 34, 1023–1035 (2010).
Cavanagh, J. F. & Frank, M. J. Frontal theta as a mechanism for cognitive control. Trends Cogn. Sci. 18, 414–421 (2014).
Mitchell, D. J., McNaughton, N., Flanagan, D. & Kirk, I. J. Frontal-midline theta from the perspective of hippocampal ‘theta’. Prog. Neurobiol. 86, 156–185 (2008).
Samerphob, N., Cheaha, D., Chatpun, S. & Kumarnsit, E. Hippocampal CA1 local field potential oscillations induced by olfactory cue of liked food. Neurobiol. Learn. Mem. 142, 173–181 (2017).
Smith, K. E., Luo, S. & Mason, T. B. A systematic review of neural correlates of dysregulated eating associated with obesity risk in youth. Neurosci. Biobehav. Rev. 124, 245–266 (2021).
Mestre, Z. L. et al. Hippocampal atrophy and altered brain responses to pleasant tastes among obese compared with healthy weight children. Int. J. Obes. 41, 1496–1502 (2017).
Wang, G.-J. et al. Evidence of gender differences in the ability to inhibit brain activation elicited by food stimulation. Proc. Natl Acad. Sci. USA 106, 1249–1254 (2009).
Lyu, Z. & Jackson, T. Acute stressors reduce neural inhibition to food cues and increase eating among binge eating disorder symptomatic women. Front. Behav. Neurosci. 10, 188 (2016).
Cyr, M. et al. Reward-based spatial learning in teens with bulimia nervosa. J. Am. Acad. Child Adolesc. Psychiatry 55, 962–971 (2016).
Bond, D. J. et al. Diagnosis and body mass index effects on hippocampal volumes and neurochemistry in bipolar disorder. Transl. Psychiatry 7, e1071 (2017).
Lock, J., Garrett, A., Beenhakker, J. & Reiss, A. L. Aberrant brain activation during a response inhibition task in adolescent eating disorder subtypes. Am. J. Psychiatry 168, 55–64 (2011).
Martín-Pérez, C., Contreras-Rodríguez, O., Vilar-López, R. & Verdejo-García, A. Hypothalamic networks in adolescents with excess weight: stress-related connectivity and associations with emotional eating. J. Am. Acad. Child Adolesc. Psychiatry 58, 211–220 (2019).
Liu, S. & Parvizi, J. Cognitive refractory state caused by spontaneous epileptic high-frequency oscillations in the human brain. Sci. Transl. Med. 11, eaax7830 (2019).
Van Essen, D. C. et al. The Human Connectome Project: a data acquisition perspective. NeuroImage 62, 2222–2231 (2012).
Glasser, M. F. et al. The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage 80, 105–124 (2013).
Sotiropoulos, S. N. et al. Advances in diffusion MRI acquisition and processing in the Human Connectome Project. NeuroImage 80, 125–143 (2013).
Esteban, O. et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat. Methods 16, 111–116 (2019).
Pruim, R. H. R. et al. ICA-AROMA: a robust ICA-based strategy for removing motion artifacts from fMRI data. NeuroImage 112, 267–277 (2015).
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L. & Petersen, S. E. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 59, 2142–2154 (2012).
Power, J. D. et al. Methods to detect, characterize, and remove motion artifact in resting state fMRI. NeuroImage 84, 320–341 (2014).
Parkes, L., Fulcher, B., Yücel, M. & Fornito, A. An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI. NeuroImage 171, 415–436 (2018).
Ciric, R. et al. Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity. NeuroImage 154, 174–187 (2017).
Smith, S. M. et al. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23, S208–S219 (2004).
Andersson, J. L. R., Skare, S. & Ashburner, J. How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. NeuroImage 20, 870–888 (2003).
Pauli, W. M., Nili, A. N. & Tyszka, J. M. A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei. Sci. Data 5, 180063 (2018).
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S. & Woolrich, M. W. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? NeuroImage 34, 144–155 (2007).
Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. NeuroImage 62, 782–790 (2012).
Tschentscher, N., Ruisinger, A., Blank, H., Díaz, B. & Kriegstein, Kvon Reduced structural connectivity between left auditory thalamus and the motion-sensitive planum temporale in developmental dyslexia. J. Neurosci. 39, 1720–1732 (2019).
Royston, P. Approximating the Shapiro-Wilk W-test for non-normality. Stat. Comput. 2, 117–119 (1992).
Stice, E., Spoor, S., Bohon, C. & Small, D. M. Relation between obesity and blunted striatal response to food is moderated by TaqIA A1 allele. Science 322, 449–452 (2008).
Kakusa, B. et al. Anticipatory human subthalamic area beta-band power responses to dissociable tastes correlate with weight gain. Neurobiol. Dis. 154, 105348 (2021).
Cohen, M. X. Analyzing Neural Time Series Data: Theory and Practice (MIT Press, 2019).
Shine, J. M. et al. Distinct patterns of temporal and directional connectivity among intrinsic networks in the human brain. J. Neurosci. 37, 9667–9674 (2017).
Prime, D., Woolfe, M., Rowlands, D., O’Keefe, S. & Dionisio, S. Comparing connectivity metrics in cortico-cortical evoked potentials using synthetic cortical response patterns. J. Neurosci. Methods 334, 108559 (2020).
Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 2013); https://doi.org/10.1176/appi.books.9780890425596.
Fairburn, C. G. & Cooper, Z. in Binge eating: Nature, Assessment, and Treatment (eds Fairburn, C. G. & Wilson, G. T.) 317–360 (Guilford Press, 1993).
Beck, A. T., Ward, C. H., Mendelson, M., Mock, J. & Erbaugh, J. An inventory for measuring depression. Arch. Gen. Psychiatry 4, 561–571 (1961).
Beck, A. T., Epstein, N., Brown, G. & Steer, R. A. An inventory for measuring clinical anxiety: psychometric properties. J. Consult. Clin. Psychol. 56, 893–897 (1988).
Gratz, K. L. & Roemer, L. Multidimensional assessment of emotion regulation and dysregulation: development, factor structure, and initial validation of the difficulties in emotion regulation scale. J. Psychopathol. Behav. Assess. 26, 41–54 (2004).
Yan, C.-G., Wang, X.-D., Zuo, X.-N. & Zang, Y.-F. DPABI: data processing & analysis for (resting-state) brain imaging. Neuroinformatics 14, 339–351 (2016).
Johnston, R., Jones, K. & Manley, D. Confounding and collinearity in regression analysis: a cautionary tale and an alternative procedure, illustrated by studies of British voting behaviour. Qual. Quant. 52, 1957–1976 (2018).