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You are hereLaboratory for Investigative Neurophysiology > People > Micah M. Murray

Micah M. Murray

| Research Interests | Representative Publications

MicahMurray_photo1.jpgAssociate Professor
Departments of Clinical Neurosciences and Department of Radiology,
Centre Hospitalier Universitaire Vaudois (CHUV)
BH 08.078, rue du Bugnon, 46, 1011 Lausanne

EEG Brain Mapping Core CIBM-CHUV
Centre Hospitalier Universitaire Vaudois (CHUV)
BH 08.078, rue du Bugnon, 46, 1011 Lausanne

Adjunct Professor
Ophthalmology Service
University of Lausanne, Switzerland

Adjunct Professor
Department of Hearing and Speech Sciences
Vanderbilt University, Nashville, TN, USA

email: Micah.Murray@chuv.ch

Research Interests

Since my arrival in Switzerland ~15 years ago, I have played a central role in bringing several domains of research to the forefront; a sampling of which is summarised here. These domains have direct and broad-reaching implications not only in basic research, but also in generating innovative technologies and in advancing clinical applications.

Multisensory Interactions. Our research has helped establish a new schema of the functional organization of the human brain. Information from the different senses interacts almost immediately and within primary cortices. These interactions directly shape perception and behavior, affecting stimulus detection as well as memory formation and retrieval (e.g. Murray et al., 2016 TiNS, Murray et al. 2016 Neuropsychologia; van Atteveldt et al., 2014 Neuron; Thelen et al., 2014 Curr Biol). This new model bears tremendous impact on both our understanding of the healthy brain, including its development and mechanisms of learning, as well as on the understanding of neuropsychiatric and neurological disorders and their diagnosis/rehabilitation. This extends not only to the neurobiological mechanisms and behavioral relevance of multisensory interactions, but also to their utility in clinical and engineering settings, including in the rehabilitation of neurodevelopmental and neurological disorders as well as in the implementation of sensory-substitution and neuroprosthetic devices (Murray et al., 2015 Curr Biol; Perruchoud et al., 2014 Front Neurosci).

Development of Electrical Neuroimaging Methods. As Director of the EEG Brain Mapping Core CHUV of the Center for Biomedical Imaging (CIBM), we have developed analysis methods permitting EEG to be used as a cost-effective and accessible non-invasive brain imaging technique (EEG is reliably recorded from newborns and the elderly and from patients at their bedside or while individuals perform tasks in virtual and real-world environments) (e.g. Michel and Murray 2012 Neuroimage; Brunet al., 2011 Comp Intell Neurosci; Murray et al., 2008 Brain Topogr). Most recently, we devised single-trial classification methods to account for the trial-to-trial variability in perception, decisions, and treatment/training efficacy in individual subjects/patients (Tzovara et al., 2013 Brain; Tzovara et al., 2012 Dev Neuropsychol; Tzovara et al., 2012 Neuroimage; De Lucia et al., 2012 Neuroimage; Bernasconi et al. 2011 J Neurosci). Such developments are necessary for neuroscientific and medical communities to effectuate a shift from studies of groups of subjects to studies of individuals that can furthermore establish generative models accounting for inter-individual heterogeneity. These tools have been made available to the wider scientific community via our freeware, CarTool, and additional graphical user interfaces. There are currently more than 3000 registered users worldwide. Ongoing efforts are focusing on connectivity and tracking of oscillatory features within electrophysiological signals as well as computational modeling of dynamical systems (Lefebvre et al., 2015 J Neurosci; Herrmann et al., 2016 J Neurosci).

Brain dynamics from sensation to perception and decision-making. One longstanding debate concerns the manner in which sensory information is processed to engender perceptions and actions upon them. One conception is that the brain is a largely passive receptor/collector of sensory information. Another contends that the brain actively senses the environment in a directed fashion. Non-invasive brain mapping, imaging, and stimulation has allowed us to disambiguate effects that are largely sequential/hierarchical from those reflecting iterative and parallel processes including mixtures of both feedforward and feedback volleys of neural activity. In the visual modality we have detailed the constructionist nature of perception, relying on the dynamic interplay across brain regions (Murray & Herrmann 2013 TiCS; Anken et al. 2016 Neuroimage). In the auditory modality we have detailed the functional organization of parallel, but interacting pathways for processing the semantic, spatial, and temporal features of environmental sounds. We have likewise delineated spatio-temporal dynamics of specific processes (e.g. object recognition) and their susceptibility to learning and plasticity (e.g. De Lucia et al., 2010 J Neurosci; De Meo et al., 2015 Neuroimage; De Meo et al., 2016 Current Biology). Finally, our work is showing these processes are impacted in clinical populations, such as individuals with learning disorders, psychosis or brain lesions and can be rehabilitated through training protocols and neuropharmacological interventions (e.g. Lavoie et al., 2008 Neuropsychopharmacology; Yoder et al., 2013 Dev Neuropsychol).

Representative Publications

Past five years only, click here for full list

Exemplar Reviews

  • Matusz PJ, Wallace MT, Murray MM (2017) A Multisensory Perspective on Object Memory. Neuropsychologia, in press.
  • Murray MM, Lewkowicz DJ, Amedi A, Wallace MT (2016) Multisensory Processes: A Balancing Act across the Lifespan. Trends in Neurosciences, 39(8): 567-79.
  • Murray MM, Thelen A, Thut G, Romei V, Martuzzi R, Matusz PJ (2016) The multisensory function of the human primary visual cortex. Neuropsychologia, 83C: 161-169.
  • Murray MM, Matusz PJ, Amedi A (2015) Neuroplasticitiy: unexpected consequences of early blindness. Current Biology, 25(20): R998-R1001.
  • van Atteveldt N, Murray MM, Thut G, Schroeder CE (2014) Multisensory integration: flexible use of general operations. Neuron 81: 1240-53.
  • Perruchoud D, Murray MM, Lefebvre J, Ionta S. (2014) Focal dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE). Front Hum Neurosci. 8:458.
  • Murray MM, Herrmann CS. (2013) Illusory contours: a window onto the neurophysiology of constructing perception. Trends in Cognitive Sciences 17: 471-81.
  • Thelen A, Murray MM. (2013) The efficacy of single-trial multisensory memories. Multisensory Research 26(5).
  • Michel CM, Murray MM. (2012). Towards the utilization of EEG as a brain imaging tool. Neuroimage, 61: 371-385.
  • Murray MM, Spierer L (2011). Multisensory Integration: What you see is where you hear. Current Biology, 21: R229-31.

Exemplar Research Articles

  • Maitre NL, Key AP, Chorna O, Slaughter JC, Matusz PJ, Wallace MT*, Murray MM* (2017) The dual nature of early-life experience on somatosensory processing in the human infant brain. Current Biology, 27, 1048-1054.
  • Shrem T, Murray MM, Deouell LY (2017) Auditory-visual integration modulates location-specific repetition suppression of auditory responses. Psychophysiology, in press.
  • Carda S, Biasiucci A, Maesani A, Ionta S, Moncharmont J, Clarke S, Murray MM*, del Millan J* (2017) Electrically assisted movement therapy in chronic stroke patients with severe upper limb paresis: A pilot, single blind, randomized crossover study. Archives of Physical Medicine and Rehabilitation, in press.
  • Anken J, Knebel JF, Crottaz-Herbette s, Matusz PJ, Lefebvre J, Murray MM (2016) Cue-dependent circuits for illusory contours in humans. Neuroimage, 129: 335-44.
  • Matusz PJ, Retsa C, Murray MM (2016) The context-contingent nature of cross-modal activations of the visual cortex. Neuroimage, 125: 996-1004.
  • Sarmiento BR*, Matusz PJ*, Sanabria D, Murray MM (2016) Contextual factors multiplex to control multisensory processes. Human Brain Mapping, 37(1): 273–288.
  • Lefebvre J, Hutt A, Knebel JF, Whittingstall K, Murray MM. (2015) Stimulus statistics shape oscillations in non-linear recurrent neural networks. Journal of Neuroscience, 35: 2895-903.
  • Toepel U, Murray MM (2015) Human gustation: when the brain has taste. Current Biology 25(9): R381-R383.
  • Matusz, PJ*, Thelen A*, Amrein S, Geiser E, Anken J, Murray MM (2015) The role of auditory cortices in the retrieval of single-trial auditory-visual object memories. European Journal of Neuroscience.
  • Thelen A*, Matusz PJ*, Murray MM (2014) Multisensory context portends object memory. Current Biology 24(16):R734-5.
  • Toepel U, Ohla K, Hudry J, le Coutre J, Murray MM. (2014) Verbal labels selectively bias brain responses to high-energy foods. Neuroimage 87:154-63.
  • Rossetti AO, Tzovara A, Murray MM, De Lucia M, Oddo M. (2014) Automated auditory mismatch negativity paradigm improves coma prognostic accuracy after cardiac arrest and therapeutic hypothermia. J Clin Neurophysiol. 31(4):356-61.
  • Yoder PJ, Molfese D, Murray MM, Key AP. (2013) Normative topographic ERP analyses of speed of speech processing and grammar before and after grammatical treatment. Dev Neuropsychol. 38(8):514-33.
  • Spierer L, Manuel A, Bueti D, Murray MM. (2013) Contributions of pitch and bandwidth to sound-induced enhancement of visual cortex excitability in humans. Cortex, 49(10):2728-34.
  • Salvioni P, Murray MM, Kalmbach L, Bueti D. (2013) How the visual brain encodes and keeps track of time. Journal of Neuroscience 33(30), 12423-12429.
  • Van Zaen J, Murray MM, Meuli RA, Vesin JM. (2013) Adaptive filtering methods for identifying cross-frequency couplings in human EEG. PLoS One. 8(4):e60513.
  • Toepel U, Knebel JF, Hudry J, Le Coutre J, Murray MM. (2012) Gender and weight shape brain dynamics during food viewing. PLoS One, 7:e36778.
  • De Lucia M, Tzovara A, Bernasconi F, Spierer L, Murray MM. (2012) Auditory perceptual decision-making based on semantic categorization of environmental sounds. Neuroimage, 60: 1704-15.
  • Zalesky A, Cocchi L, Fornito A, Murray MM, Bullmore E. (2012). Connectivity differences in brain networks. Neuroimage, 60:1055-1062.
  • Cappe C, Thelen A, Romei V, Thut G, Murray MM. (2012) Looming signals reveal synergistic principles of multisensory interactions. Journal of Neuroscience 32, 1171-82.
  • Brunet D, Murray MM, Michel CM. (2011). Spatio-temporal analysis of multichannel EEG: CARTOOL. Computational Intelligence and Neuroscience doi:10.1155/2011/813870.



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