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Brain Systems

Overview

Historically, brain science has focused on how distinct brain regions carry out specialised functions such as sensation, motor control and cognition. This approach has led to a 'compartmentalised' map of thebrain, whereby nerve cells (neurons) with shared morphology and function, located in the same area, correspond to discrete information processing modules. However, it is now recognised that the real challenge is to understand how activity is coordinated across brain areas, in real time. Such coordination is crucial for virtually all brain functions.

For example, when you cross the street, the sight and sound of an oncoming car are coordinated to yield a coherent, multi-sensory perception. Brain centres for movement planning are coordinated with the ones that produce goal-directed actions (initiating movements to ensure safe crossing). At the same time, sensory feedback from the environment is used to refine ongoing movement. These principles also apply to high-level functions such as language, where activity in many areas is coordinated to extract meaning and generate speech. In sum, the brain needs to be understood in terms of the interaction of its parts, not by considering each part in isolation.

Recent developments in brain imaging and brain stimulation allow, more than ever, functional study of the living human brain. Despite this advance, there are still only tenuous connections between the results of human studies and those of experimental studies in other mammals, which can provide the most detailed information about the cellular processes and neural circuits of the brain.

The Brain Systems research theme addresses this problem by conducting parallel investigations in rodents, monkeys and humans. A key strategy is to develop measures of simple behaviours (e.g. shifting of visual attention, prediction of movement trajectories, and perceptual decisions on discrete sensory events). In humans, these tasks are performed in brain imaging and stimulation experiments; in rodents and nonhuman primates, they are done during electrode-array recordings from brain cells.

Brain Systems – imaging

In humans, combining brain stimulation and imaging allows us to target specific brain areas and trace their system-wide influence on neural activity. For example, we can stimulate primary sensory areas and measure propagation of neural activity to other areas while the brain is at 'rest' and during action. In other experiments we are stimulating high-level 'executive' areas critical for integrative functions, and trace the effects on lower level sensory and motor areas. In rodents and monkeys parallel investigations are being undertaken by micro-stimulation of local circuits via implanted electrodes and by using the new method of optogenetic modulation, in which light sensitive molecules are incorporated into brain cells, allowing neural activation by laser stimulation. Concurrent recordings or neuronal activity are being made via electrode arrays implanted in both sensory and executive cortical areas, allowing us to examine how activity in networks of neurons underlies integrative functions.

Brain Systems – analytic measures

The Brain Systems research theme takes advantage of new analytic measures of human brain function, and apply these to non-human mammalian brains. For example, the traditional approach to analysis of brain imaging data is to subtract activity in control conditions from activity associated with a task. This approach however biases outcomes toward localised function in specialised areas. To address this challenge, our investigators adopt and further develop analysis methods that can point to the physiological interactions within brain networks that underlie integrative functions. We use new 'decoding' techniques to reveal patterns of network activity that are invisible to conventional analyses. Most importantly, we apply these methods to recordings from connected nerve cell groups and MRI experiments in animals, revealing how the network components are built up at a local (neuronal circuit) level.

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Research Themes

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2014 Publications

In our establishment year (2014), we produced more than 30 peer reviewed journal articles.

1. Aquino KM, Robinson PA, Drysdale PM. Spatiotemporal hemodynamic response functions derived from physiology. J Theor Biol. 2014;347:118-36. doi:10.1016/j.jtbi.2013.12.027.
2. Aquino KM, Robinson PA, Schira MM, Breakspear M. Deconvolution of neural dynamics from fMRI data using a spatiotemporal hemodynamic response function. Neuroimage. 2014;94:203-15. doi:10.1016/j.neuroimage.2014.03.001.
3. Arabzadeh E, Clifford CW, Harris JA, Mahns DA, Macefield VG, Birznieks I. Single tactile afferents outperform human subjects in a vibrotactile intensity discrimination task. J Neurophysiol. 2014;112(10):2382-7. doi:10.1152/jn.00482.2014.
4. Bhagavatula PS, Claudianos C, Ibbotson MR, Srinivasan MV. Behavioral lateralization and optimal route choice in flying budgerigars. PLoS Comput Biol. 2014;10(3):e1003473. doi:10.1371/journal.pcbi.1003473.
5. Burman KJ, Bakola S, Richardson KE, Reser DH, Rosa MG. Patterns of afferent input to the caudal and rostral areas of the dorsal premotor cortex (6DC and 6DR) in the marmoset monkey. J Comp Neurol. 2014;522(16):3683-716. doi:10.1002/cne.23633.
6. Cooray G, Garrido MI, Hyllienmark L, Brismar T. A mechanistic model of mismatch negativity in the ageing brain. Clin Neurophysiol. 2014;125(9):1774-82. doi:10.1016/j.clinph.2014.01.015.
7. Dietz MJ, Friston KJ, Mattingley JB, Roepstorff A, Garrido MI. Effective connectivity reveals right-hemisphere dominance in audiospatial perception: implications for models of spatial neglect. J Neurosci. 2014;34(14):5003-11. doi:10.1523/JNEUROSCI.3765-13.2014.
8. Filmer HL, Dux PE, Mattingley JB. Applications of transcranial direct current stimulation for understanding brain function. Trends Neurosci. 2014;37(12):742-53. doi:10.1016/j.tins.2014.08.003.
9. Fulcher BD, Phillips AJ, Postnova S, Robinson PA. A physiologically based model of orexinergic stabilization of sleep and wake. PLoS One. 2014;9(3):e91982. doi:10.1371/journal.pone.0091982.
10. Fung PK, Robinson PA. Neural field theory of synaptic metaplasticity with applications to theta burst stimulation. J Theor Biol. 2014;340:164-76. doi:10.1016/j.jtbi.2013.09.021.
11. Goscinski WJ, McIntosh P, Felzmann UC, Maksimenko A, Hall CJ, Gureyev T, Thompson D, Janke A, Galloway G, Killeen NE, Raniga P, Kaluza O, Ng A, Poudel G, Barnes DG, Nguyen T, Bonnington P, Egan GF. The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research. Front Neuroinform. 2014;8:30. doi:10.3389/fninf.2014.00030.
12. Henderson JA, Robinson PA. Relations between the geometry of cortical gyrification and white-matter network architecture. Brain Connect. 2014;4(2):112-30. doi:10.1089/brain.2013.0183.
13. Henke H, Robinson PA, Drysdale PM. Spatiotemporally varying visual hallucinations: II. Spectral classification and comparison with theory. J Theor Biol. 2014;357:210-9. doi:10.1016/j.jtbi.2014.05.024.
14. Hohwy J. Elusive phenomenology, counterfactual awareness, and presence without mastery. Cogn Neurosci. 2014;5(2):127-8. doi:10.1080/17588928.2014.906399.
15. Hohwy J, Palmer C. Social cognition as causal inference: implications for common knowledge and autism. In: Gallotti M, Michael J, editors. Perspectvies on Social Ontology and Social Cognition. London: Springer; 2014.
16. Hughes NJ, Hunt JJ, Cloherty SL, Ibbotson MR, Sengpiel F, Goodhill GJ. Stripe-rearing changes multiple aspects of the structure of primary visual cortex. Neuroimage. 2014;95:305-19. doi:10.1016/j.neuroimage.2014.03.031.
17. Hung YS, Ibbotson MR. Ocellar structure and neural innervation in the honeybee. Front Neuroanat. 2014;8:6. doi:10.3389/fnana.2014.00006.
18. Liang H, Bácskai T, Watson C, Paxinos G. Projections from the lateral vestibular nucleus to the spinal cord in the mouse. Brain Struct Funct. 2014;219(3):805-15. doi:10.1007/s00429-013-0536-4.
19. Marshak DW, Martin PR. Short wavelength-sensitive cones and the processing of their signals. Vis Neurosci. 2014;31(2):111-3. doi:10.1017/S0952523813000655.
20. Martin PR. Neuroscience: who needs a parasol at night? Curr Biol. 2014;24(24):R1164-6. doi:10.1016/j.cub.2014.10.075.
21. Martin PR, Lee BB. Distribution and specificity of S-cone (“blue cone”) signals in subcortical visual pathways. Vis Neurosci. 2014;31(2):177-87. doi:org/10.1017/S0952523813000631.
22. Miyagishima KJ, Grunert U, Li W. Processing of S-cone signals in the inner plexiform layer of the mammalian retina. Vis Neurosci. 2014;31(2):153-63. doi:10.1017/S0952523813000308.
23. Palmer JH, Gong P. Associative learning of classical conditioning as an emergent property of spatially extended spiking neural circuits with synaptic plasticity. Front Comput Neurosci. 2014;8:79. doi:10.3389/fncom.2014.00079.
24. Percival KA, Koizumi A, Masri RA, Buzas P, Martin PR, Grunert U. Identification of a pathway from the retina to koniocellular layer K1 in the lateral geniculate nucleus of marmoset. J Neurosci. 2014;34(11):3821-5. doi:10.1523/JNEUROSCI.4491-13.2014.
25. Pietersen ANJ, Cheong SK, Solomon SG, Tailby C, Martin PR. Temporal response properties of koniocellular (blue-on and blue-off) cells in marmoset lateral geniculate nucleus. J Neurophysiol. 2014;112(6):1421-38. doi:10.1152/jn.00077.2014.
26. Postnova S, Postnov DD, Seneviratne M, Robinson PA. Effects of rotation interval on sleepiness and circadian dynamics on forward rotating 3-shift systems. J Biol Rhythms. 2014;29(1):60-70. doi:10.1177/0748730413516837.
27. Reser DH, Richardson KE, Montibeller MO, Zhao S, Chan JM, Soares JG, Chaplin TA, Gattass R, Rosa MG. Claustrum projections to prefrontal cortex in the capuchin monkey (Cebus apella). Front Syst Neurosci. 2014;8:123. doi:10.3389/fnsys.2014.00123.
28. Richards K, Calamante F, Tournier JD, Kurniawan ND, Sadeghian F, Retchford AR, Jones GD, Reid CA, Reutens DC, Ordidge R, Connelly A, Petrou S. Mapping somatosensory connectivity in adult mice using diffusion MRI tractography and super-resolution track density imaging. Neuroimage. 2014;102(2):381-92. doi:10.1016/j.neuroimage.2014.07.048.
29. Robinson PA, Sarkar S, Pandejee GM, Henderson JA. Determination of effective brain connectivity from functional connectivity with application to resting state connectivities. Phys Rev E Stat Nonlin Soft Matter Phys. 2014;90(1):012707. doi:10.1103/PhysRevE.90.012707.
30. Sarkar S, Dong A, Henderson JA, Robinson PA. Spectral characterization of hierarchical modularity in product architectures. J Mech Des N Y. 2014;136(1):0110061-1100612. doi:10.1115/1.4025490.
31. Sefton AJ, Dreher B, Harvey AR, Martin PR. Visual System. In: Paxinos G, editor. The rat nervous system San Diego: Elsevier Academic Press; 2014.
32. Skafidas E, Testa R, Zantomio D, Chana G, Everall IP, Pantelis C. Response to Belgard et al. Mol Psychiatry. 2014;19:407-9. doi:10.1038/mp.2013.186.
33. Solomon SG, Rosa MG. A simpler primate brain: the visual system of the marmoset monkey. Front Neural Circuits. 2014;8. doi:10.3389/fncir.2014.00096.
34. Van Doorn G, Hohwy J, Symmons M. Can you tickle yourself if you swap bodies with someone else? Conscious Cogn. 2014;23:1-11. doi:10.1016/j.concog.2013.10.009.
35. Weltzien F, Dimarco S, Protti DA, Daraio T, Martin PR, Grunert U. Characterization of secretagogin-immunoreactive amacrine cells in marmoset retina. J Comp Neurol. 2014;522(2):435-55. doi:10.1002/cne.23420.
36. Wong RC, Garrett DJ, Grayden DB, Ibbotson MR, Cloherty SL. Efficacy of electrical stimulation of retinal ganglion cells with temporal patterns resembling light-evoked spike trains. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:1707-10. doi:10.1109/EMBC.2014.6943936.
37. Zhao X, Kim JW, Robinson PA, Rennie CJ. Low dimensional model of bursting neurons. J Comput Neurosci. 2014;36(1):81-95. doi:10.1007/s10827-013-0468-2.

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2015 Publications

Books

1. Paxinos G, Watson C, Calabrese E, Badea A, Johnson GA. An MRI/DTI Atlas of the Rat Brain. San Diego: Academic Press/ Elsevier; 2015.

 Book Chapters

2. Robinson PA, Postnova S, Abeysuriya RG, Kim JW, McKenzie-Sell L, Karanjai A, Kerr CC, Fung F, Anderson A, Breakspear MJ, Drysdale PM, Fulcher BD, Phillips AJK, Rennie CJ, Yin G. A Multiscale "Working Brain" Model. In: Bhattacharya, Sen B, Chowdhury, N F, editors. Validating Neuro-Computational Models of Neurological and Psychiatric Disorders. Switzerland: Springer International; 2015. p. 107-40.

Conference papers

3. Maturana MI, Apollo NV, Garrett DJ, Kameneva T, Meffin H, Ibbotson MR, Cloherty SL, Grayden DB. The effects of temperature changes on retinal ganglion cell responses to electrical stimulation: Conf Proc IEE Eng Med Biol Soc. 2015; 7320128

Journal Articles

4. Abeysuriya RG, Rennie CJ, Robinson PA. Physiologically based arousal state estimation and dynamics. J Neurosci Meth. 2015;253:55-69.

5. Apollo NV, Maturana M, Tong W, Zamani A, Turnley A, Foroughi J, Wallace G, Prawer S, Ibbotson MR, Garrett D. Soft, Flexible Freestanding Neural Stimulation Electrodes Fabricated from Reduced Graphene Oxide. Adv Funct Mater. 2015;25:3551-9.

6. Baumann O, Borra RJ, Bower JM, Cullen KE, Habas C, Ivry RB, Leggio M, Mattingley JB, Molinari M, Moulton EA, Paulin MG, Pavlova MA, Schmahmann JD, Sokolov AA. Consensus paper: the role of the cerebellum in perceptual processes. Cerebellum. 2015;14(2):197-220.

7. Burman KJ, Bakola S, Richardson KE, Yu H-H, Reser DH, Rosa MGP. Cortical and thalamic projections to cytoarchitectural areas 6Va and 8C of the marmoset monkey: Connectionally distinct subdivisions of the lateral premotor cortex. J Comp Neurol. 2015;523(8):1222-47.

8. Chen SC, Morley JW, Solomon SG. Spatial precision of population activity in primate area MT J Neurophysiol. 2015;114(2):869-78.

9. Cloherty SL, Crowder NA, Mustari MJ, Ibbotson MR. Saccade-induced image motion cannot account for post-saccadic enhancement of visual processing in primate MST. Front Syst Neurosci 2015;9(1):122.

10. Cloherty SL, Ibbotson MR. Contrast-dependent phase sensitivity in V1 but not V2 of macaque visual cortex. J Neurophysiol. 2015;113(2):434-44.

11. Cocchi L, Sale MV, Lord A, Zalesky A, Breakspear M, Mattingley JB. Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics J Neurophysiol. 2015;113(9):3375-85.

12. Fam J, Westbrook F, Arabzadeh E. Dynamics of pre- and post-choice behaviour: rats approximate optimal strategy in a discrete-trial decision task. Proc R Soc B: Biol Sci. 2015;282(1803):20142963.

13. Fam J, Westbrook F, Arabzadeh E. Behavioral correlates of the decision process in a dynamic environment: post-choice latencies reflect relative value and choice evaluation. Front Behav Neurosci. 2015;9(261).

14. Filmer HL, Dux PE, Mattingley JB. Dissociable effects of anodal and cathodal tDCS reveal distinct functional roles for right parietal cortex in the detection of single and competing stimuli Neuropsychologia 2015;74:120-6.

15. Filmer HL, Mattingley JB, Dux PE. Object substitution masking for an attended and foveated target. J Exp Psychol: Hum Percept Perform. 2015;41:6-10.

16. FitzGibbon T, Eriköz B, Grünert U, Martin PR. Analysis of the lateral geniculate nucleus in dichromatic and trichromatic marmosets. J Comp Neurol. 2015;523(13):1948-66.

17. Fu Y, Yu  Y, Paxinos G, Watson C, Rusznak Z. Ageing-dependent changes in the cellular composition of the mouse brain and spinal cord. Neuroscience. 2015;290:406-20.

18. Garrido MI, Barnes GR, Kumaran D, Maquire EA, Dolan RJ. Ventromedial prefrontal cortex drives hippocampal theta oscillations induced by mismatch computations. Neuroimage. 2015;120:362-70.

19. Hadjinicolaou AE, Meffin H, Maturana MI, Cloherty SL, Ibbotson MR. Prosthetic vision: devices, patient outcomes and retinal research. Clin Exp Optom. 2015;98(5):395-410.

20. Hadjinicolaou AE, Savage CO, Garrett DJ, Apollo NV, Cloherty SL, Ibbotson MR, O’Brien BJ. Optimal electrical stimulation of retinal ganglion cells. Trans Neural Syst Rehabil Eng. 2015;23(2):169-78.

21. Hall MG, Mattingley JB, Dux PE. Distinct contributions of attention and working memory to visual statistical learning and ensemble processing J Exp Psychol: Hum Percept Perform. 2015;41(4):1112-23.

22. He W, Garrido MI, Sowman PF, Brock J, Johnson BW. Development of effective connectivity in the core network for face perception Hum Brain Mapp. 2015;36:2161-73.

23. Hearne L, Cocchi L, Zalesky A, Mattingley JB. Interactions between default mode and control networks as a function of increasing cognitive reasoning complexity Hum Brain Mapp. 2015;36(7):2719-31.

24. Jamadar S, Johnson B, Clough M, Egan GF, Fielding J. Behavioural and neural plasticity of ocular motor control: changes in performance and fMRI activity following antisaccade training. Front Hum Neurosci. 2015;9:653.

25. Keane A, Gong P. Propagating waves can explain irregular neural dynamics. J Neurosci. 2015;35(4):1591-605.

26. Liang H, Bácskai T, Paxinos G. Termination of vestibulospinal fibers arising from the spinal vestibular nucleus in the mouse spinal cord. Neuroscience. 2015;294:206-14.

27. Liang H, Wang S, Francis R, Whan R, Watson C, Paxinos G. Distribution of raphespinal fibers in the mouse spinal cord. Mol Pain. 2015;11(1):42.

28. Liang H, Watson C, Paxinos G. Projections from the oral pontine reticular nucleus to the spinal cord of the mouse. Neurosci Lett. 2015;584:113-8.

29. Litvak V, Garrido MI, Zeidman P, Friston K. Empirical Bayes for group (DCM) studies: a reproducibility study. Front Hum Neurosci. 2015;9:670.

30. Lui LL, Mokri Y, Reser DH, Rosa MGP, Rajan R. Responses of neurons in the marmoset primary auditory cortex to interaural level differences: Comparison of pure tones and vocalizations. Front Neurosci. 2015;9:132.

31. Meffin H, Hietanen MA, Cloherty SL, Ibbotson MR. Spatial phase sensitivity of complex cells in primary visual cortex depends on stimulus contrast. J Neurophysiol. 2015;114(6):3326-38.

32. Painter DR, Dux PE, Mattingley JB. Distinct roles of the intraparietal sulcus and temporoparietal junction in attentional capture from distractor features: an individual differences approach Neuropsychologia. 2015;74:50-62.

33. Painter DR, Dux PE, Mattingley JB. Casual involvement of visual area MT in global feature-based enhancement but not contingent attentional capture Neuroimage. 2015;118:90-102.

34. Pasternak T, Lui LL, Spinelli PM. Unilateral prefrontal lesions impair memory-guided comparisons of contralateral visual motion. J Neurosci. 2015;35(18):7095-105.

35. Perry A, Wen W, Lord A, Thalamuthu A, Roberts G, Mitchell PB, Sachdev PS, Breakspear M. The organisation of the elderly connectome. Neuroimage. 2015;114:414-26.

36. Poch C, Garrido MI, Igoa JM, Belichon M, Garcia-Morales I, Campo P. Time-varying effective connectivity during visual object naming as a function of semantic demands. J Neurosci. 2015;35:8768-76.

37. Poudel G, Stout JC, Dominguez DF, Churchyard A, Chua P, Egan GF, Georgiou-Karistianis N. Longitudinal change in white matter microstructure in Huntington’s disease: The IMAGE-HD study. Neurobiol Dis. 2015;74(1):406-12.

38. Robinson AK, Reinhard J, Mattingley JB. Olfaction modulates early neural responses to matching visual objects J Cogn Neurosci. 2015;27(4):832-41.

39. Robinson PA, Roy N. Neural field theory of nonlinear wave-wave and wave-neuron processes. Phys Rev E Stat Nonlin Soft Matter Phys. 2015;91:062719.

40. Rosa MJ, Portugal L, Hahn T, Fallgatter AJ, Garrido MI, Shawe-Taylor J, Mourao-Miranda J. Sparse network-based models for patient classification using fMRI Neuroimage 2015;105:493-506.

41. Strobel C, Marek R, Gooch HM, Sullivan RK, Sah P. Prefrontal and auditory input to intercalated neurons of the amygdala Cell Rep. 2015;10:1435-42.

42. Stronks HC, Nau AC, Ibbotson MR, Barnes N. The role of visual deprivation and experience on the performance of sensory substitution devices. Brain Res. 2015;1624:140-52.

43.  Townsend RG, Solomon SS, Chen SC, Pietersen AN, Martin PR, Solomon SG, Gong P. Emergence of complex wave patterns in primate cerebral cortex. J Neurosci. 2015;35(11):4657-62.

44. Weltzien F, Percival KA, Martin PR, Grünert U. Analysis of bipolar and amacrine populations in marmoset retina. J Comp Neurol. 2015;523(2):313-34.

45. Wimmer VC, Harty RC, Richards KL, Phillips AM, Miyazaki H, Nukina N, Petrou S. Sodium channel β1 subunit localizes to axon initial segments of excitatory and inhibitory neurons and shows regional heterogeneity in mouse brain. J Comp Neurol. 2015;532(5):814-30.

46. Zeater N, Cheong SK, Solomon SG, Dreher B, Martin PR. Binocular Visual Responses in the Primate Lateral Geniculate Nucleus. Curr Biol. 2015;25:3190-5.

47. Zhao X, Kim JW, Robinson PA. Slow-wave oscillations in a corticothalamic model of sleep and wake. J Theor Biol 2015;370:93-102.

48. Zhao X, Robinson PA. Generalized seizures in a neural field model with bursting dynamics. J Comput Neurosci. 2015;39(2):197-216.

Review papers

49. Angelucci A, Rosa MG. Resolving the organization of the third tier visual cortex in primates: a hypothesis-based approach. Vis Neurosci. 2015;32:e010.

50. Bakola S, Burman KJ, Rosa MGP. The cortical motor system of the marmoset monkey (Callithrix jacchus). Neurosci Res. 2015;93:72-81.

51.  Lui LL, Rosa MGP. Structure and function of the middle temporal visual area (MT) in the marmoset: Comparisons with the macaque monkey. Neurosci Res. 2015;93:62-71.

52. Mansouri FA, Rosa MG, Atapour N. Working Memory in the Service of Executive Control Functions. Front Syst Neurosci. 2015;9:166.

53. Sale MV, Mattingley JB, Zalesky A, Cocchi L. Imaging human brain networks to improve the clinical efficacy of non-invasive brain stimulation Neurosci Biobehav Rev. 2015;57:187-98.

54.  Stuart GJ, Spruston N. Dendritic integration: 60 years of progress. Nat Neurosci. 2015;18:1713-21.

55. Yu H-H, Chaplin TA, Rosa MGP. Representation of central and peripheral vision in the primate cerebral cortex: Insights from studies of the marmoset brain. Neurosci Res. 2015;93:47-61.

56. Zantomio D, Chana G, Laskaris L, Testa R, Everall I, Pantelis C, Skafidas E. Convergent evidence for mGluR5 in synaptic and neuroinflammatory pathways implicated in ASD. Neurosci Biobehav Rev. 2015;52:172-7.

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2016 Publications

Books

1. Mai, J.K., Majtanic, M., Paxinos, G. Atlas of the Human Brain, 4th ed. San Diego: Academic Press; 2016.

2. Stuart, G.J., Spruston, N., Hausser, M. Dendrites, 3rd ed. Oxford: Oxford University Press; 2016.

Book Chapters

3.  Arabzadeh, E., von Heimendahl, M., Diamond, M.E. Vibrissal Texture Coding, in Scholarpedia of Touch, T.J. Prescott, et al., Eds. Paris: Atlantis Press; 2016. p. 737-749.

4.  Hausser, M., Spruston, N., Stuart, G.J. The future of dendritic research, in Dendrites, G.J. Stuart, et al., Eds. Oxford: Oxford University Press; 2016. p. 703-707.

5.  Lowery, A.J., Rosenfeld, J.V., Rosa, M.G.P., Brunton, E., Rajan, R., Mann, C., Armstrong, M., Mohan, A., Josh, H., Kleeman, L., Li, W.H., Pritchard, J. Monash Vision Group’s Gennaris Cortical Implant for Vision Restoration, in Artificial Vision, V.P. Gabel, Ed. Switzerland: Springer International Publishing; 2016. p. 215-225.

6. Spruston, N., Stuart, G.J., Hausser, M. Principles of dendritic intgration, in Dendrites, G.J. Stuart, et al., Eds. Oxford: Oxford University Press; 2016. p. 351-398.

Conference Papers

7. Saker, P., Farrell, M.J., Egan, G.F., McKinley, M.J., Denton, D.A. Overdrinking, swallowing inhibition, and regional brain responses prior to swallowing. Proc Natl Acad Sci USA. 2016; 113(43): 12274-12279.

8.  Mendis, G.D., Morrisroe, E., Reid, C.A., Halgamuge, S., Petrou, S. Use of local field potentials of dissociated cultures grown on multi-electrode arrays for pharmacological assays. Conf Proc IEEE Eng Med Biol Soc. 2016; 2016-October: Art. 7590859.

Journal Articles

9.  Aberyrathne, C.D., Huynh, D.H., Lee, T.T., Mcintire, T.W., Nguyen, T.C., Nasr, B., Zantomio, D., Chana, G., Abbot, I., Choong, P., Catton, M., Skafidis, E. Lab on a chip sensor for rapid detection and antibiotic resistance determination of staphylococcus aureua. Analyst. 2016; 141(6): 1922-1929.

10. Aberyrathne, C.D., Huynh, D.H., Lee, T.T., Nguyen, T.C., Nasr, B., Chana, G., Skafidis, E. GFAP antibody detection using interdigital coplanar waveguide immunosensor. IEEE Sens J. 2016; 16(9): 2898-2905.

11. Amlien, I.K., Fjell, A.M., Tamnes, C.K., Grydeland, H., Krogsrud, S.K., Chaplin, T.A., Rosa, M.G.P., Walhovd, K.B. Organizing principles of human cortical development - thickness and area from 4 to 30 years: Insights from comparative primate neuroanatomy Cereb Cortex. 2016; 26(1): 257-267.

12. Baumann, O., Mattingley, J.B. Functional organization of the parahippocampal cortex: Dissociable roles for context representations and the perception of visual scenes. J Neurosci. 2016; 36(8): 2536-2542.

13. Bock, H.T., Stuart, G.J. Impact of BK channels on cellular excitability depends on their subcellular location. Front. Cell. Neurosci. 2016; 10: Art. 206.

14. Bock, T., Stuart, G.J. Impact of calcium-activated potassium channels on NMDA spikes in cortical layer 5 pyramidal neurons. J Neurophysiol. 2016; 115(3): 1740-1748.

15. Boonstra, T.W., Farmer, S.F., Breakspear, M. Using computational neuroscience to define common input to spinal motor neurons. Front Hum Neurosci. 2016; 10: Art. 313.

16. Cloherty, S.L., Hughes, N.J., Hietenan, M.A., Bhagavatula, P., Goodhill, G.J., Ibbotson, M.R. Sensory experience modifies feature map relationships in visual cortex. eLife. 2016; 5: e13911.

17. Cocchi, L., Sale, M.V., Gollo, L.L., Bell, P.T., Nguyen, V.T., Zalesky, A., Breakspear, M., Mattingley, J.B. A hierarchy of timescales explains distinct effects of local inhibition of primary visual cortex and frontal eye fields. eLife. 2016; 5(Se): e15252.

18. Cooray, G.K., Garrido, M.I., Brismar, T., Hyllienmark, L. The maturation of mismatch negativity networks in normal adolescence. Clin Neurophysiol. 2016; 127(1): 520-529.

19. Davies, A.J., Chaplin, T.A., Rosa, M.G.P., Yu, H.-H. Natural motion trajectory enhances the coding of speed in primate extrastriate cortex. Sci Rep. 2016; 6: Art. 19739.

20. Dürschmid, S., Zaehle, T., Hinrichs, H., Heinze, H.-J., Voges, J., Garrido, M.I., Dolan, R., Knight, R. Sensory deviancy detection measured directly within the human nucleus accumbens. Cereb Cortex. 2016; 26(3): 1168-1175.

21. Fam, J., Westbrook, R.F., Arabzadeh, E. Temporal dynamics of choice behavior in rats and humans: An examination of pre- and post-choice latencies. Sci Rep. 2016; 6: Art. 20583.

22. Fazlali, Z., Ranjbar-Slamloo, Y., Adibi, M., Arabzadeh, E. Correlation between cortical state and locus coeruleus activity: Implications for sensory coding in rat barrel cortex. Front Neural Circuit. 2016; 10: Art. 14.

23. Fu, Y., Hsiao, J.H., Paxinos, G., Halliday, G.M., Kim, W.S. ABCA7 mediates phagocytic clearance of Amyloid-β in the brain. J Alzheimers Dis. 2016; 54(2): 569-584.

24.  Fu, Y., Paxinos, G., Watson, C., Halliday, G.M. The substantia nigra and ventral tegmental dopaminergic neurons from development to degeneration. J Chem Neuroanat. 2016; 76(Pt B): 98-107.

25.  Gamberini, M., Bakola, S., Passarelli, L., Burman, K., Rosa, M.G.P., Fattori, P., Galletti, C. Thalamic projections to visual and visuomotor areas (V6 and V6A) in the Rostral Bank of the parieto-occipital sulcus of the Macaque. Brain Struct Funct. 2016; 221(3): 1573-1589.

26. Garrido, M.I., Teng, C.L.J., Taylor, J.A., Rowe, E.G., Mattingley, J.B. Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand. npj Sci Learn. 2016; 1: Art 16006.

27.  Ghodrati, M., Alwis, D.S., Price, N.S.C., Foxe, J. Orientation selectivity in rat primary visual cortex emerges earlier with low-contrast and high-luminance stimuli. Eur J Neurosci. 2016; 44(10): 2759-2773.

28. Gu, Y., Gong, P. The dynamics of memory retrieval in hierarchical networks. J Comput Neurosci. 2016; 40(3): 247-268.

29. Hearne, L., Mattingley, J.B., Cocchi, L. Functional brain networks related to individual differences in human intelligence at rest. Sci Rep. 2016; 6: Art. 32328.

30. Hohwy, J., Paton, B., Palmer, C. Distrusting the present. Phenomenol Cogn Sci. 2016; 15(3): 315-335.

31. Jamadar, S.D., Egan, G.F., Calhoun, V.D., Johnson, B., Fielding, J. Intrinsic connectivity provides the baseline framework for variability in motor performance: A multivariate fusion analysis of low-and high-frequency resting-state oscillations and antisaccade performance. Brain Connect. 2016; 6(6): 505-517.

32. Kameneva, T., Maturana, M.I., Hadjinicolaou, A.E., Cloherty, S.L., Ibbotson, M.R., Grayden, D.B., Burkitt, A.N., Meffin, H. Retinal ganglion cells: mechanisms underlying depolarization block and differential responses to high frequency electrical stimulation of ON and OFF cells. J Neural Eng. 2016; 13(1): Art. 016017.

33. Kamke, M.R., Nydam, A.S., Sale, M.V., Mattingley, J.B. Associative plasticity in the human motor cortex is enhanced by concurrently targetingseparate muscle representations with excitatory and inhibitory protocols. J Neurophysiol. 2016; 115(4): 2191-2198.

34. Lee, C., Diamond, M.E., Arabzadeh, E. Sensory prioritization in rats: behavioural performance and neuronal correlates. J Neurosci. 2016; 36(11): 3243-3253.

35. Lee, S.C., Weltzien, F., Madigan, M., Martin, P.R., Grünert, U. Identification of aII amacrine, displaced amacrine and bistratified ganglion cell types in human retina with antibodies against calretinin. J Comp Neurol. 2016; 524(1): 39-53.

36. Liang, H., Schofield, E., Paxinos, G. Imaging serotonergic fibers in the mouse spinal cord using the CLARITY/CUBIC technique. J Vis Exp. 2016; 108: Art. 53673.

37.  Liang, H., Watson, C., Paxinos, G. Terminations of reticulospinal fibers originating from the gigantocellular reticular formation in the mouse spinal cord. Brain Struct Funct. 2016; 221(3): 1623-1633.

38. Liu, X., Xie, B., Qi, Y., Du, X., Wang, S., Zhang, Y., Paxinos, G., Yang, H., Liang, H. The expression of SEIPIN in the mouse central nervous system. Brain Struct Funct. 2016; 221(8): 4111-4127.

39. Majka, P., Chaplin, T.A., Yu, H.-H., Tolpygo, A., Mitra, P.P., Wójcik, D.K., Rosa, M.G.P. Towards a comprehensive atlas of cortical connections in a primate brain: Mapping tracer injection studies of the common marmoset into a reference digital template. J Comp Neurol. 2016; 524(11): 2161-2181.

40.  Mansouri, F.A., Fehring, D.J., Feizpour, A., Gaillard, A., Rosa, M.G.P., Rajan, R., Jaberzadeh, S., Thut, G. Direct current stimulation of prefrontal cortex modulates error-induced behavioral adjustments. Eur J Neurosci. 2016; 44(2): 1856-1869.

41. Mansouri, F.A., Fehring, D.J., Gaillard, A., Jaberzadeh, S., Parkington, H. Sex dependency of inhibitory control functions. Biol Sex Differ. 2016; 7(11): 1-13.

42. Masri, R.A., Percival, K.A., Koizumi, A., Martin, P.R., Grünert, U. Connectivity between the OFF bipolar type DB3a and six types of ganglion cell in the marmoset retina. J Comp Neurol. 2016; 524(9): 1839-1858.

43. Maturana, M.I., Apollo, N.V., Hadjinicoloaou, A.E., Garrett, D.J., Cloherty, S.L., Kameneva, T., Grayden, D.B., Ibbotson, M.R., Meffin, H. A simple and accurate model to predict responses to multi-electrode stimulation in the retina. PLoS Comput Biol. 2016; 12(4): e1004849.

44. Naughtin, C., Mattingley, J.B., Dux, P. Early information processing contributions to object individuation revealed by perception of illusory figures. J Neurophysiol. 2016; 116(6): 2513-2522.

45. Naughtin, C.K., Mattingley, J.B., Dux, P.E. Distributed and overlapping neural substrates for object individuation and identification in visual short-term memory. Cereb Cortex. 2016; 26(2): 566-275.

46. Pang, J.C., Robinson, P.A., Aquino, K.M. Response-mode decomposition of spatio-temporal haemodynamics. J R Soc Interface. 2016; 13(118): pii: 20160253.

47. Puckett, A.M., Aquino, K.M., Robinson, P.A., Breakspear, M., Schira, M.M. The spatiotemporal hemodynamic response function for depth-dependent functional imaging of human cortex. NeuroImage. 2016; 139: 240-248.

48.  Richards, L.R., Michie, P.T., Badcock, D.R., Bartlett, P.F., Bekkers, J.M., Bourne, J.A., Castles, A., Egan, G.F., Fornito, A., Hannan, A.J., Hickie, I.B., Mattingley, J.B., Schofield, P.R., Shum, D.H.K., Stuart, G.J., Vickers, J.C., Vissel, B. Australian Brain Alliance. Neuron. 2016; 92(3): 597-600.

49. Roberts, J.A., Perry, A., Lord, A.R., Roberts, G., Mitchell, P.B., Smith, R.E., Calamante, F., Breakspear, M. The contribution of geometry to the human connectome. NeuroImage. 2016; 124: 379-393.

50. Robinson, A.K., Laning, J., Reinhard, J., Mattingley, J.B. Odours reduce the magnitude of object substitution masking for matching visual targets in females. Atten Percept Psycho. 2016; 78(6): 1702-1711.

51. Robinson, P.A., Zhao, X., Aquino, K.M., Griffiths, J.D., Sarkar, S., Mehta-Pandejee, G. Eigenmodes of brain activity: Neural field theory predictions and comparison with experiment. NeuroImage. 2016; 142: 79-98.

52. Rusznák, Z., Henskens, W., Schofield, E., Kim, W.S., Fu, Y. Adult neurogenesis and gliogenesis: Possible mechanisms for neurorestoration. Exp Neurobiol. 2016; 25(3): 103-112.

53. Rusznák, Z., Kim, W.S., Hsiao, J.H., Halliday, G.M., Paxinos, G., Fu, Y. Early in vivo effects of the human mutant Amyloid-β protein precursor (hAβPPSwInd) on the mouse olfactory bulb. J Alzheimers Dis. 2016; 49(2): 443-457.

54. Sabri, M., Adibi, M., Arabzadeh, E. Dynamics of population activity in rat sensory cortex: Network correlations predict anatomical arrangement and information content. Front Neural Circuit. 2016; 10: Art. 49.

55. Sarkar, S., Chawla, S., Robinson, P.A., Fortunato, S. Eigenvector dynamics under perturbation of modular networks. Phys Rev E. 2016; 93(6): Art. 062312.

56. Spampanato, J., Sullivan, R.K.P., Perumal, M.B., Sah, P. Development and physiology of GABAergic feedback excitation in parvalbumin expressing interneurons of the mouse basolateral amygdala. Physiol Rep. 2016; 4: e12664.

57. Verghese, A., Garner , K.G., Mattingley, J.B., Dux, P. Prefrontal cortex structure predicts training - induced improvements in multitasking performance. J Neurosci. 2016; 36(9): 2638-2645.

58. Wilson, M.T., Fung, P.K., Robinson, P.A., Shemmell, J., Reynolds, J.N. Calcium dependent plasticity applied to repetitive transcranial magnetic stimulation with a neural field model. J Comput Neurosci. 2016; 41(1): 107-125.

59. Windels, F., Yan, S., Stratton, P.G., Sullivan, R., Crane, J.W., Sah, P. Auditory tones and foot-shock recapitulate spontaneous sub-threshold activity in basolateral amygdala principal neurons and interneurons. PLoS One. 2016; 11(5): e0155192.

60. Yang, D.P., McKenzie-Sell, L., Karanjai, A., Robinson, P.A. Wake-sleep transition as a noisy bifurcation. Phys Rev E. 2016; 94(2): Art. 022412.

61. Zalesky, A., Fornito, A., Cocchi, L., Gollo, L.L., van den Heuvel, M.P., Breakspear, M. Connectome sensitivity or specificity: which is more important? NeuroImage. 2016; 142: 407-420.

62. Zarei, P., Kameneva, T., Ibbotson, M.R., Grayden, D.L. A possible role for end-stopped V1 neurons in the perception of motion: a computational model. PLoS One. 2016; 11(10): e0164813.

63. Zavitz, E., Yu, H.-H., Rowe, E.G., Rosa, M.G.P., Price, N.S.C. Rapid adaptation induces persistent biases in population codes for visual motion. J Neurosci. 2016; 36(16): 4579-4590.

Review Articles

64. Lewis, P.M., Ayton, L.N., Guymer, R.H., Lowery, A.J., Blamey, P.J., Allen, P.J., Luu, C.D., Rosenfeld, J.V. Advances in implantable bionic devices for blindness: a review. ANZ J Surg. 2016; 86(9): 654-659.

65. Molenberghs, P., Johnson, H., Henry , J., Mattingley, J.B. Understanding the minds of others: A neuroimaging meta-analysis. Neurosci Biobehav Rev. 2016; 65: 276-291.

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Neuroethics

Ethical challenges raised

Rapid advances in neuroscience are transforming our understanding of human cognition and behaviour. The secrets of our brains are being unlocked and many of these discoveries present ethical challenges for society.

Sophisticated imaging methods, brain-based technologies and drug development are provoking questions around cognitive enhancement, criminal behaviour and human rights. Neurobiological profiling could lead to unintended consequences, and how interventions to ameliorate cognitive decline and diminished brain health are being examined.

Our Neuroethics program explores the social, ethical, legal and policy implications raised through our growing knowledge of the brain. By doing so, we hope to translate our brain research into effective and ethical interventions, treatments and policies.

Australian Neuroethics Network

The Australian Neuroethics Network is an interdisciplinary collaboration that brings together leading Australian practitioners in neuroscience, law, ethics, philosophy, policy-making, clinical practice, patient populations, the public and other end-users to examine the ethical and social implications of neuroscience research.

We host interdisciplinary workshops and events that produce outcomes such as recommendations, guidelines and policy briefs for government, regulators and business.

Through conference presentations, the media and online communications, we are improving awareness of neuroethical issues associated with recent advances in brain research. Read more about the Australian Neuroethics Network.

Neuroethics Program Coordinator - Associate Professor Adrian Carter

Associate Professor Adrian Carter is a neuroscientist and ethicist conducting interdisciplinary research on the impact of neuroscience on our understanding and treatment of addictive behaviours.

Besides directing the Centre's Neuroethics Program, Associate Professor Carter leads the Neuroethics and Public Policy group at the Monash Institute of Cognitive and Clinical Neurosciences. This group examines the implications of neuroscience research on free will, identity, and moral responsibility; drug use and self-efficacy (people’s belief in their ability to control their drug use and their motivation to enter treatment); stigma and discrimination; coercion; and the use of emerging technologies, such as brain stimulation and brain imaging, to treat addiction.

Associate Professor Carter has been an advisor to the World Health Organization, the European Monitoring Centre for Drugs and Drug Addiction, the Australian Ministerial Council on Drugs Strategy and United Nations Office on Drugs and Crime and is a member of the International Neuroethics Society’s Response Action Task Force.

He is an ARC DECRA Fellow, and deputy chair of executive committee of the Australian Academy of Science Early and Mid Career Researcher Forum.

Associate Professor Carter’s book Addiction Neuroethics: The Promises and Perils of Neuroscience Research on Addiction is available in paper or hardback from Cambridge University Press, and for Amazon kindle.

He also co-ordinates the Australian Neuroethics Network, which can be contacted on Twitter: @NeuroethicsAU

The Ethics of Neuroscience, a mini documentary featuring Dr Carter and produced by Monash University, examines the fundamental questions being raised by our growing understanding of the human brain.

New technologies are allowing us to have control over the human brain like never before. As we push the possibilities we must ask ourselves, what is neuroscience today and how far is too far?

The world’s best neurosurgeons can now provide treatments for things that were previously untreatable, such as Parkinson’s and clinical depression. Many patients are cured, while others develop side effects such as erratic behaviour and changes in their personality.

Not only do we have greater understanding of clinical psychology, forensic psychology and criminal psychology, we also have more control. Professional athletes and gamers are now using this technology – some of it untested – to improve performance. However, with these amazing possibilities come great ethical concerns.

This manipulation of the brain has far-reaching effects, impacting the law, marketing, health industries and beyond. We need to investigate the capabilities of neuroscience and ask the ethical questions that will determine how far we can push the science of mind and behaviour.

 

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Research

How does the brain interact with the world?

Perhaps the greatest scientific challenge of our time is to understand the link between brain activity and human behaviour. By elucidating the core principles of brain activity underlying perceptual and cognitive functions in our everyday lives, we aim to understand how the brain interacts with the world. Detailed knowledge gained over the last century may soon lead to mechanistic explanations of our experiences, actions and thoughts.

However, this level of deep understanding of different aspects of brain structure and function requires coordinated, multi-scale, multidisciplinary investigations, which are beyond the reach of any single laboratory.

Opening a world of possibilities

Knowing how the activity of brain cells mediates the way we interact with the world unlocks tremendous possibilities. Take a moment to imagine:

• practical vehicles controlled by thought
• machine-brain interfaces to enhance our natural senses
• technologies for accelerated learning
• portable instruments for diagnosing brain diseases
• biomimetic robots.

Such developments will require much deeper knowledge of brain anatomy and physiology than we currently possess, which is why we have created a critical mass of leading Australian brain researchers to work together.

Integrating research

The ARC Centre of Excellence for Integrative Brain Function aims to further the understanding of the brain mechanisms underlying attention, prediction and decision, via research projects that cross two or more of the Centre's Research Themes:

1. Cells and Synapses
2. Neural Circuits
3. Brain Systems
4. Models and Technologies

Our research plan increasingly emphasises studies applying multi-scale integrative approaches in human and animal models.

Recent research highlights include discovering:

• the brain’s ability to detect subtle irregularities in the environment when attention is focused elsewhere
• highly connected brain regions that send and receive large volumes of messages share similar patterns of gene activity
• how the parahippocampal cortex performs both recognition of visual scenes and assigns context to objects, with each function having its own sub-region
• the development of a new 3D imaging method to trace individual nerve cell projections between the brain and spinal cord of mice.

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Annual Reports

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Collaborators and Partners

Collaborating Institutions

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Partner Institutions

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Affiliate Organisations

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Our Team

Chief Investigators

Chief Investigators (CI) are responsible for leading our research. Each CI is listed below, along with their role within the Centre and their host institution.

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Management and Administration

Our extensive research program is supported by a team of management and administrative personnel located at each of our collaborating organisations throughout Australia.

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Program Coordinators

Apart from our scientific research, our Program Coordinators lead specialised programs that address societal, education, computational and industry issues raised by brain research.

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Partner Investigators

Partner Investigators support the Centre’s research and are based at the partner organisations in Australia, Europe and the USA.

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Associate Investigators

Associate Investigators support the Centre’s Chief Investigators at their various collaborating institutions.

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