Dr. Dorval applies the tools of engineering to study the nervous system and design ways to improve the health and quality of life for persons with neural disorders. Dorval's research activities include: engineering novel treatments to alleviate the symptoms of neurological diseases; quantifying information processing in the brain and interpreting informational changes induced by disease and treatment states; and elucidating the relationships between the structural elements of neurons and neural tissue, their physiological dynamics and their behavioral responses.  Pursuing these interests, Dorval performs experimental studies, recording and stimulating neurons and neural tissue while assessing symptom severity in computational systems, animal models and human participants with neurological disorders.

I conduct research in the field of neural engineering, oriented toward designing devices that will alleviate the symptoms of neurological diseases and disorders by modulating neural activity.  In most cases, intelligent construction of neuromodulatory devices requires a more complete understanding of how neural activity relates to behavior than exists currently.  Hence the goals of my specific research projects are often two stage: first, to better understand how neural activity corresponds to behavior and symptoms, and second to engineer interventions that will modify neural activity to improve function.

Projects

Variable yet Reliable Neuronal Responses to Natural and Artificial Input.  A neuron transmits information by firing spikes of membrane potential along its axon as a signal to downstream neurons.  The information a neuron can transmit is limited by the spike rate, the variability of the membrane potential waveform, and the fidelity with which inputs are reliably transformed into outputs.  In this project we elucidate fundamental constraints on how rate, variability and reliability limit the processing of synaptic and externally applied information.  We quantify those concepts with a measure of firing pattern entropy, and explore methods to best estimate that entropy.  We also examine how various neuronal elements (e.g., ion channels, dendritic spines) and electrical stimulation affect rate, variability, reliability and the information to which they give rise.  For this project thus far, we have used computational neuronal  models and in vitro rodent neurons.

Random Fluctuations in Ion Channel States Enables Rhythmic Activity.  The mammalian brain is rife with rhythmic activity at many frequencies and across various brain regions.  In the hippocampus in particular, periodic activity in the 4-12 Hz range is highly correlated with active exploration and location identification.  While there may be several mechanisms contributing to the generation of this oscillatory activity, we focus on contributions provided by the random (i.e., thermal noise driven) openings and closings of membrane spanning proteins that, when open, channel Na+ ions across the neuronal membrane.  The small number of these so called persistent Na+ channels suggests that neurons may control their oscillatory activity by increasing or decreasing the pool of available channels over time.

Controlling Abstract Properties of Neuronal Behavior, In Vitro.  Electrophysiologists have traditionally relied upon two techniques to assa the membrane and response properties of neurons: current and voltage clamp, which control the current through an intracellular electrode and the voltage across the neuronal membrane, respectively.  The modern technique of dynamic clamp supercedes those more traditional methods, enabling: the addition or subtraction of less straighforward quantities including conductance or capacitance; the control of more abstract qualities including firing rate and membrane potential variability; and the generation of arbitrarily complicated hybrid networks in which living neurons are connected to entirely artificial constructs.  This technique harbors great potential for future scientific discovery.

Education

• Postdoctoral studies, Biomedical Engineering, Duke University, Durham NC, 2008.  Research: Examining the relationships between neuronal firing patterns, deep brain stimulation (DBS) and Parkinson's disease.
  
• Marine Biological Laboratory, Woods Hole, 2001.  Course: Methods in Computational Neuroscience.
• Ph.D., Biomedical Engineering, Boston University, Boston MA, 2004. Dissertation: Probing the role of noise in the superficial medial entorhinal cortex.
• B.S., Biomedical Engineering, Rensselaer Polytechnic Institute, Troy NY, 1997.  Senior Research: Constructed software tool for the statistical analysis of functional magnetic resonance imaging (fMRI) data.

Employment

• 2009-present USTAR Assistant Professor.
  Department of Bioengineering, Program in Neurosciences, Brain Institute, University of Utah, Salt Lake City, UT
  
• 2004-2008 Reseach Associate with Dr. Warren Grill.
  Department of Biomedical Engineering, Duke University, Durham NC
• 1997-2004 Research Assistant & Graduate Student Fellow with Dr. John White.
  Department of Biomedical Engineering & Center for BioDynamics, Boston University, Boston MA.
• 1996-1997 Research Assistant with Dr. T. J. Holmes.
  AutoQuant Imaging, Inc., Watervliet NY.

Teaching Experience

Professor/Instructor:

• Bioengineering Senior Project I & II (2009, 2010) University of Utah, Salt Lake City UT.
  

Teaching Assistant/Fellow (TA/TF)

• Post-graduate student courses
• Neural Systems and Behavior (TA-2004) Marine Biological Laboratories, Woods Hole MA.
• Methods in Computational Neuroscience (TA-2003) Marine Biological Laboratories, Woods Hole MA.
• Graduate student courses
• Quantitative Studies of Excitable Membranes (TF-1998, TA-2000, TA-2002) Boston University, Boston MA.
• Advanced Signals and Systems (TF-1999) Boston Universtiy, Boston MA.
• Biomedical Instrumentation (TF-1999) Boston University, Boston MA.
• Quantitative Studies of Cardiovascular & Respiratory Systems (TF-1998) Boston University, Boston MA.
• Undergraduate student courses
• Physics I (TA-1997) Rensselaer Polytechnic Institute, Troy NY.

Professional Activities

• Ad hoc reviewer for:
• Annals of Biomedical Engineering
• Journal of Neural Engineering
  
• Journal of Neurophysiology
  
• Journal of Neuroscience Methods
• Neural Computation
• Open Neuroscience Journal
  
• Service
• National Postdoctoral Association, Advocacy Committee & Meetings Committee, 2008-2009
  
• Duke University Postdoctal Association, Board of Chairs: 2006-2008, President 2008
  
• Boston University, Student Association of Graduate Engineers, Officers' Committee: 1998 - 2003
• Societies
• since 2000  Society for Neuroscience, Member
• since 2003  BioMedical Engineering Society, Member
• since 2009  IEEE Engineering in Medicine and Biology Society, Member
  
• 2008-2007  National Postdoctoral Association, Member
  

Publications

• Dorval AD, Kuncel AM, Birdno MJ, Turner D, Grill WM. “Deep brain stimulation that regularizes activity in the basal ganglia thalamic circuit alleviates parkinsonian bradykinesia." (submitted, January 2010)
• Birdno MJ, Kuncel AM, Dorval AD, Turner DA, Gross RE, Grill WM. "Stimulus features underlying reduced tremor suppression during deep brain stimulation (DBS) with temporally irregular patterns." (submitted, January 2010)
• Dorval AD, Panjwani N, Qi R, Grill WM. "Deep brain stimulation that abolishes parkinsonian activity in the basal ganglia improves thalamic relay fidelity in a computational circuit." Proc IEEE Eng Med Biol Soc, 31(1):4230-4233, 2009. [abstract] [pdf]
• Dorval AD, Russo GS, Hashimoto T, Xu W, Grill WM, Vitek JL. "Deep brain stimulation reduces neuronal entropy in the MPTP-primate model of Parkinson's disease." Journal of Neurophysiology, 100(5):2807-2818, 2008. [abstract] [pdf]
• Dorval AD. "Probability distribtutions of the logarithm of inter-spike intervals yield accurate entropy estimates from small datasets." Journal of Neuroscience Methods, 173(1), 2008. [abstract] [pdf] [supplement]
• Birdno MJ, Kuncel AM, Dorval AD, Turner DA, Grill WM. “Tremor varies as a function of the temporal regularity of deep brain stimulation." NeuroReport, 19(5):599-602, 2008. [abstract] [pdf]
• Haas JS, Dorval AD, White JA. “Contributions of I_h to feature selectivity in layer II stellate cells of the entorhinal cortex.” Journal of Computational Neuroscience, 22(2):161-171, 2007. [abstract] [pdf]
• Dorval AD, Bettencourt JB, Netoff TI, White JA. “Hybrid Neuronal Network Studies Under Dynamic Clamp.” Methods in Molecular Biology: Applied Patch Clamp, Humana Press, Totowa, NJ, 2007. [abstract]
• Dorval AD. “The rhythmic consequences of ion channel stochasticity.” The Neuroscientist 12(5):442-448, 2006. [abstract] [pdf]
• Dorval AD, White JA. “Synaptic input statistics tune the variability and reproducibility of neuronal responses.” Chaos, 16(2):26105, 2006. **selected as highlight publication 7/1/2006: Virtual Journal of Biological Physics Research. [abstract] [pdf]
• Dorval AD, White JA. “Channel noise is essential for perithreshold oscillations in entorhinal stellate neurons.” J ournal of Neuroscience, 25(43):10025-10028, 2005. [abstract] [pdf]
• White JA, Dorval AD. “Neuro-electric principles.” The Electrical Engineering Handbook, 3^rd edition. Dorf RC (Ed.), CRC Press, Boca Raton, 2005.
• Netoff TI, Banks MI, Dorval AD, Acker CD, Haas JS, Kopell N, White JA. “Synchronization in hybrid neuronal networks of the hippocampal formation.”Journal of Neurophysiology, 93(3):1197-1208, 2005. [abstract] [pdf]
• Dorval AD, Netoff TI, White JA. “Real-time experimental control in cellular neurophysiology.” Proc IEEE Eng Med Biol Soc Neural Eng, 1:71-74, 2003. [pdf]
• White JA, Netoff TI, Dorval AD, Banks MI. “Assessing neuronal synchronization properties using spike time response methods.” Proc IEEE Eng Med Biol Soc, 25:2235-2238, 2003.
• White JA, Netoff TI, Acker CD, Dorval AD, Haas JS. “The biophysical bases of synchronous activity in the hippocampal formation.” Proc IEEE Eng Med Biol Soc, 24:1958-1959, 2002.
• Dorval AD, Christini DJ, White JA. “Real-time linux dynamic clamp: a fast and flexible way to construct virtual ion channels in living cells.” Annals of Biomedical Engineering, 29(10): 897-907, 2001. [abstract] [pdf]
• White JA, Haas JS, Dorval AD. “Stochastic dynamic clamping as a method for studying the effects of biological noise sources.” Proc IEEE Eng Med Biol Soc, 21:880, 1999.