Steven Middleton

From Yasunori Hayashi Laboratory
Revision as of 15:49, 8 June 2023 by Yasunori Hayashi (talk | contribs) (Created page with "== Bibliography == *2002 Graduated with a degree in Biochemistry, Biological Sciences Department, Lancaster University (UK) *2005 Ph.D. Neuroscience, School of Biomedical Sciences, University of Leeds (UK) *2005-2009 Post-doc, School of Neurology, Neurobiology & Psychiatry, University of Newcastle. (Prof. Miles. A. Whittington) *2009-2011 Post-doc, Brain Science Institute, RIKEN (Dr. Thomas Knopfel) *2011-2023 Research Scientist, Center for Brain Science, RIKEN (Dr. Tho...")
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Bibliography

  • 2002 Graduated with a degree in Biochemistry, Biological Sciences Department, Lancaster University (UK)
  • 2005 Ph.D. Neuroscience, School of Biomedical Sciences, University of Leeds (UK)
  • 2005-2009 Post-doc, School of Neurology, Neurobiology & Psychiatry, University of Newcastle. (Prof. Miles. A. Whittington)
  • 2009-2011 Post-doc, Brain Science Institute, RIKEN (Dr. Thomas Knopfel)
  • 2011-2023 Research Scientist, Center for Brain Science, RIKEN (Dr. Thomas. J. McHugh)
  • 2023-present Assistant Professor. Dept. Pharmacology, Graduate School of Medicine, Kyoto University. (Prof. Yasunori Hayashi)

Research topics

Hippocampal memory processing

Behavioural episodes comprising the multimodal sensory information that make up memories occur over prolonged timescales (>minutes), yet for the brain to effectively retain this information, synaptic plasticity must occur, which requires neurons to fire in close temporal proximity. One method the hippocampus overcomes this disparity is via the temporal compression of neuronal activity into theta (8Hz) frequency packets. Specifically, during spatial navigation tasks, place representations during a single theta cycle (approx. 125ms) code for not only an animal’s current location, but contain information coding both past and upcoming trajectory information occurring over a much wider timescale. To understand how this theta frequency compression of information (termed ‘theta sequences’) was generated and what implications it has for information coding, I used a transgenic mouse model which allows for the specific and temporally controlled silencing of hippocampal area CA3. By recording from these mice which display deficits in rapid one-trial contextual learning, pattern completion-based memory recall, and poorer spatial tuning of CA1 neurons, we were able to demonstrate that theta sequences were absent in area CA1, when output from upstream CA3 was blocked. These data demonstrate that while the activity of individual neurons in CA1 remains largely unchanged, i.e. they still produce a stable spatial map and exhibit phase precession, their organization into a larger coherent ensemble capable of generating theta sequences is directed by CA3.

Animal models of neural dysfunction

Modelling of disease outcomes and severity have become more advanced with the introduction of transgenic models of disease, which allow for a more detailed understanding of what neurological changes may underlie the behavioural changes observed. The SCN2A gene is mutated in multiple disorders which include autism, with the SCN2A+/- heterozygote mouse line displaying similar learning impairments to those observed in patients. To understand the underlying cause of these deficits I used high density neural recordings while animals performed a spatial working memory task. In control animals during learning, place cells replay whole behavioural sequences depicting the subjects previous experiences. These replayed events occur during activity called sharp-wave ripples, which occur repeatedly during sleep and act to strengthen synapses, leading to the formation of robust memories which can support learning and lead to enhanced task performance. In SCN2A+/- mice, although replays still occurred, the behavioural sequences that they replayed were shorter than controls, meaning that only partial memories were being formed explaining the poorer task performance.

Exploring the mechanisms of neuronal oscillations and their modulation for the treatment of diseases

Neuronal oscillations are the electrical activity commonly recorded in EEG, that result from the coordinated activity of large populations of neurons. This activity occurs in many different frequency bands and is observed ubiquitously across almost all regions of the brain. The behavioural state of an animal and current cognitive demand determines which frequency of activity dominates at any given time. To understand the mechanisms responsible for generating hippocampal oscillations I recorded intracellularly from both excitatory and inhibitory neurons in vitro, whilst oscillations were pharmacologically induced in brain slices. The results demonstrated that inhibitory interneurons drive oscillations, firing in a phase locked manner and are responsible for restricting the firing window of excitatory neurons to specific phases of the ongoing oscillation. Moreover, using the recreational drug ketamine, I was able to demonstrate that endogenous gamma frequency oscillations in the entorhinal cortex (EC) become disrupted, which influences the pathway for information transfer between the EC and hippocampus. More recently, in collaboration with Prof. Li-Huei Tsai’s laboratory (MIT) we investigated how artificial modulation of oscillations may be used a method to reverse/slow the pathologies associated with Alzheimer's disease (AD) in transgenic disease models. Endogenous gamma frequency oscillations were evoked by the presentation of visual stimuli at gamma frequencies for prolonged periods in AD model mice. We found that oscillations were not only generated in visual cortical areas (V1), but propagated to multiple regions including the hippocampus and prefrontal cortex, acting to bind and engage large areas of the brain simultaneously. Compared with control mice, light receiving AD mice showed a marked decrease in amyloid deposition and the neuronal and synaptic loss associated with AD in multiple regions, together with a corresponding increase in performance in memory dependent tasks.

Publications

  1. Adaikkan, C., Wang, J., Abdelaal, K., Middleton, S.J., Bozzelli, P.L., Wickersham, I.R., McHugh, T.J., & Tsai, L.H. (2022).
    Alterations in a cross-hemispheric circuit associates with novelty discrimination deficits in mouse models of neurodegeneration. Neuron, 110(19), 3091-3105.e9. [PubMed:35987206] [PMC] [WorldCat] [DOI]
  2. Guan, H., Middleton, S.J., Inoue, T., & McHugh, T.J. (2021).
    Lateralization of CA1 assemblies in the absence of CA3 input. Nature communications, 12(1), 6114. [PubMed:34671042] [PMC] [WorldCat] [DOI]
  3. Chen, S., He, L., Huang, A.J.Y., Boehringer, R., Robert, V., Wintzer, M.E., Polygalov, D., Weitemier, A.Z., Tao, Y., Gu, M., Middleton, S.J., Namiki, K., Hama, H., Therreau, L., Chevaleyre, V., Hioki, H., Miyawaki, A., Piskorowski, R.A., & McHugh, T.J. (2020).
    A hypothalamic novelty signal modulates hippocampal memory. Nature, 586(7828), 270-274. [PubMed:32999460] [WorldCat] [DOI]
  4. Middleton, S.J., & McHugh, T.J. (2020).
    CA2: A Highly Connected Intrahippocampal Relay. Annual review of neuroscience, 43, 55-72. [PubMed:31874067] [WorldCat] [DOI]
  5. Adaikkan, C., Middleton, S.J., Marco, A., Pao, P.C., Mathys, H., Kim, D.N., Gao, F., Young, J.Z., Suk, H.J., Boyden, E.S., McHugh, T.J., & Tsai, L.H. (2019).
    Gamma Entrainment Binds Higher-Order Brain Regions and Offers Neuroprotection. Neuron, 102(5), 929-943.e8. [PubMed:31076275] [PMC] [WorldCat] [DOI]
  6. Middleton, S.J., & McHugh, T.J. (2019).
    Memory: Sequences Take Time. Current biology : CB, 29(5), R158-R160. [PubMed:30836085] [WorldCat] [DOI]
  7. Middleton, S.J., Kneller, E.M., Chen, S., Ogiwara, I., Montal, M., Yamakawa, K., & McHugh, T.J. (2018).
    Altered hippocampal replay is associated with memory impairment in mice heterozygous for the Scn2a gene. Nature neuroscience, 21(7), 996-1003. [PubMed:29867081] [PMC] [WorldCat] [DOI]
  8. Boehringer, R., Polygalov, D., Huang, A.J.Y., Middleton, S.J., Robert, V., Wintzer, M.E., Piskorowski, R.A., Chevaleyre, V., & McHugh, T.J. (2017).
    Chronic Loss of CA2 Transmission Leads to Hippocampal Hyperexcitability. Neuron, 94(3), 642-655.e9. [PubMed:28472661] [WorldCat] [DOI]
  9. Middleton, S.J., & McHugh, T.J. (2016).
    Silencing CA3 disrupts temporal coding in the CA1 ensemble. Nature neuroscience, 19(7), 945-51. [PubMed:27239937] [WorldCat] [DOI]
  10. Meng, L., Kramer, M.A., Middleton, S.J., Whittington, M.A., & Eden, U.T. (2014).
    A unified approach to linking experimental, statistical and computational analysis of spike train data. PloS one, 9(1), e85269. [PubMed:24465520] [PMC] [WorldCat] [DOI]
  11. Akemann, W., Middleton, S.J., & Knöpfel, T. (2009).
    Optical imaging as a link between cellular neurophysiology and circuit modeling. Frontiers in cellular neuroscience, 3, 5. [PubMed:19649169] [PMC] [WorldCat] [DOI]
  12. Middleton, S., Jalics, J., Kispersky, T., Lebeau, F.E., Roopun, A.K., Kopell, N.J., Whittington, M.A., & Cunningham, M.O. (2008).
    NMDA receptor-dependent switching between different gamma rhythm-generating microcircuits in entorhinal cortex. Proceedings of the National Academy of Sciences of the United States of America, 105(47), 18572-7. [PubMed:18997013] [PMC] [WorldCat] [DOI]
  13. Traub, R.D., Middleton, S.J., Knöpfel, T., & Whittington, M.A. (2008).
    Model of very fast (> 75 Hz) network oscillations generated by electrical coupling between the proximal axons of cerebellar Purkinje cells. The European journal of neuroscience, 28(8), 1603-16. [PubMed:18973579] [PMC] [WorldCat] [DOI]
  14. Middleton, S.J., Racca, C., Cunningham, M.O., Traub, R.D., Monyer, H., Knöpfel, T., Schofield, I.S., Jenkins, A., & Whittington, M.A. (2008).
    High-frequency network oscillations in cerebellar cortex. Neuron, 58(5), 763-74. [PubMed:18549787] [PMC] [WorldCat] [DOI]
  15. Fuchs, E.C., Zivkovic, A.R., Cunningham, M.O., Middleton, S., Lebeau, F.E., Bannerman, D.M., Rozov, A., Whittington, M.A., Traub, R.D., Rawlins, J.N., & Monyer, H. (2007).
    Recruitment of parvalbumin-positive interneurons determines hippocampal function and associated behavior. Neuron, 53(4), 591-604. [PubMed:17296559] [WorldCat] [DOI]
  16. Bibbig, A., Middleton, S., Racca, C., Gillies, M.J., Garner, H., Lebeau, F.E., Davies, C.H., & Whittington, M.A. (2007).
    Beta rhythms (15-20 Hz) generated by nonreciprocal communication in hippocampus. Journal of neurophysiology, 97(4), 2812-23. [PubMed:17287437] [WorldCat] [DOI]
  17. Roopun, A.K., Middleton, S.J., Cunningham, M.O., LeBeau, F.E., Bibbig, A., Whittington, M.A., & Traub, R.D. (2006).
    A beta2-frequency (20-30 Hz) oscillation in nonsynaptic networks of somatosensory cortex. Proceedings of the National Academy of Sciences of the United States of America, 103(42), 15646-50. [PubMed:17030821] [PMC] [WorldCat] [DOI]
  18. Cunningham, M.O., Hunt, J., Middleton, S., LeBeau, F.E., Gillies, M.J., Davies, C.H., Maycox, P.R., Whittington, M.A., & Racca, C. (2006).
    Region-specific reduction in entorhinal gamma oscillations and parvalbumin-immunoreactive neurons in animal models of psychiatric illness. The Journal of neuroscience : the official journal of the Society for Neuroscience, 26(10), 2767-76. [PubMed:16525056] [PMC] [WorldCat] [DOI]

Funding & Awards

2014-2016 Grant-in-Aid for Young Scientists (B)
2019-2022 Grant-in-Aid for Scientific Research (B)
2019 MEXT Commendation for Science and Technology young researchers’ prize

Teaching Experience

B11b Pharmacology practical class

Academic Society

Society for Neuroscience
Japanese Society for Neuroscience

Personal Interests

Gardening (growing vegetables), exploring nature and cooking.

Contact Address

Department of Pharmacology
Kyoto University Graduate School of Medicine
Room 403, Building A
Kyoto 606-8501 Japan

E-mail: middleton.steven.8p@ms.c.kyoto-u.ac.jp

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