Neurology of Vision Lab
Neurology of Vision Lab
175 Cambridge Street
Boston, MA 02114
Explore This Lab
The adult brain constantly adapts to changes in stimuli, and this plasticity is manifest not only as learning and memory but also as dynamic changes in information transmission and processing. Using interactively multimodal imaging (fMRI, MEG) and psychophysics, the Neurology of Vision Laboratory's (NOVI) goal is to understand the mechanisms mediating visual perception in healthy and damaged human brains, and long-term plasticity and short-term dynamics in networks of the adult normal and stroke-damaged cortex.
Our research is translational, conducted hand in hand with several neurologists, physiatrists, and other clinicians. We are developing psychophysical tests for the diagnosis of cognitive and higher visual function deficits, and use fMRI, MEG and behavioral tasks to develop a physiological marker for prognosis of recovery of such deficits in stroke patients, and for determining programs of targeted rehabilitation of such deficits.
Dynamic Granger Causality Applied to Perception of a Complex Visual Motion Search Task
Perception and perceptual decisions arise from the spatiotemporal orchestration of activity distributed across brain networks. In an MEG study, we used dynamic Granger Causality and corresponding summary network measures to understand the critical cortical interactions involved in solving a complex visual-motion search task (VS).
Cortical dynamics of perception and decision in sensory tasks: An MEG study
Perception and perceptual decisions arise from the spatiotemporal orchestration of activity distributed across brain networks. Functional MRI (fMRI) studies have shown that discrete networks mediate the sensory processing and the representation of visual search task (VSS2011 C&V). However, fMRI does not have the temporal precision required for revealing the neuronal mechanisms that integrate sensory information and coordinate the decision-making process during perceptual tasks. View poster.
Deficit of temporal dynamics of detection of a moving object during egomotion in a stroke patient: An MEG study
Using anatomically constrained MEG in conjunction with Granger causality in the time domain (DGC)1 and PLV in the frequency domain and bands) we compared in a patient and 6 healthy controls the direction and dynamics of connectivity between the functional areas involved in detection of a moving object by a moving observer in two experimental conditions: visual only (unimodal) and cross-modal, visual augmented by an auditory cue co-localized and congruent to the moving object. Our previous psychophysical study of these tasks demonstrated that in healthy observers, this specific auditory cue significantly enhanced task performance. View poster.
Detection of object motion during self-motion: Psychophysics and neuronal substrate
During self-motion, the separation of the motion flow field into self- and object-motion components is critical to safe navigation. “Flow-parsing”, a visual-only implementation, has been proposed based on the subtraction of induced selfmotion from the perceived flow field1,2. Is object detection during forward observer translation consistent with the low-parsing hypothesis? What brain networks mediate the detection of object motion by a moving observer? View poster.
Direction of motion in depth: dissociation of perception 114 of self-motion and object motion
Accurately estimating direction of self-motion through the environment (heading) and detecting possibility of collision with a moving object (collision detection) are fundamental tasks of visually guided navigation. Do heading estimation and collision with a moving object share the same motion mechanisms? Is performance on collision detection affected differently by a static or moving observer? Why? What do fMRI studies tell us about the neural substrate of the collision detection task (static observer)? View poster.
Functional Stealing: Reorganization of the Retinotopic Map After Occipital Lobe Infarction
While neuroplasticity after stroke has been amply demonstrated using functional magnetic resonance imaging (fMRI) in the motor (1-4) and language (5) systems, there is a dearth of human studies examining neuroplasticity in the cortical visual system. This is in stark contrast with the extensive knowledge of visual mechanisms and their neural substrate in non-human primates and humans. View poster.
Medical Student Research Project Opportunities
The signature of brain networks after ischemic stroke in humans
In order to understand pathological states after stroke, the projects involves using fMRI data, both from rest states and from quantitative computerized psychophysical tasks, to determine changes in functional brain networks in patients compared with healthy subjects. Students will learn fMRI data analysis (Free Surfer), and models of brain connectivity analysis and graph theory concepts that are used to quantitatively characterize the human connectome at the behavioral level. The projects may be done as a mini-project, in a few months, or as a full projects over a few years.
The project can be split into 3-4 related subprojects to be carried out by multiple students. All projects are carried out at Mass General Neurology Department and the Martinos Center for Biomedical Imaging, under the supervision of Dr. Vaina.
Prerequisites (desired but not obligatory): Matlab, fluent in basic statistics and signal processing, good with computers, good knowledge of human brain anatomy. But most important, energy and enthusiasm!
Professional Research Opportunities
All applicants should register with the Mass General Careers website.
Vaina LM, Hintikka J, Eds. (1984). Cognitive Constraints on Communication: Representations and Processes, Reidel-Dordrecht, Holland.
Vaina LM, Ed. (1987). Matters of Intelligence, Reidel-Dordrecht, Holland.
Vaina LM, Ed. (1991). From the Retina to the Neocortex: Selected Papers of David Marr (with an Introduction and Commentaries), Birkhauser Publishing House, Boston.
Vaina LM, Beardsley SA, Rushton S (2004). Optic Flow and Beyond, Kluwer Academic Press.
Vaina LM, Passingham RE. (2017). Computational Theories and their Implementation in the Brain: The Legacy of David Marr, Oxford University Press, The United Kingdom.
Selected Peer Reviewed Articles
Vaina L.M (1996). Akinetopsia, Achromatopsia and Blindsight: Recent Studies on Perception Without Awareness. Synthese,105: 1-19
Vaina LM, Rushton SK (2000). What Neurological Patients Tell Us About the Use of Optic Flow. In: Lappe M (Ed.) International Review of Neurobiology, 44: 293-314
Vaina LM, Cowey A, Eskew RT, LeMay M, Kemper T (2001). Anatomical Correlates Of Global Motion Perception: Evidence From Unilateral Cortical Brain Damage. Brain, 124: 310-321.
Vaina LM, Cowey A, LeMay M, Bienfang D, Kikinis R (2002). Visual Deficits in a Patient with “Kaleidoscopic Disintegration of the Visual World.” European Journal of Neurology, 9: 463-477
Vaina LM, Gross CG (2004). Perceptual Deficits in Patients with Impaired Recognition of Biological Motion After Temporal Lobe Lesions. Proc. Natl. Acad. Sci (USA), 101(48): 16947-16951
Vaina, LM, Sikoglu, EM, Sloviev S, LeMay, M, Squatrito, S, Cowey, A. (2010). Functional and Anatomical Profile of Visual Motion Impairments in Stroke Patients Correlated with fMRI in Normal Subjects. Journal of Neuropsychology 4, 121-145
Rana KD, Caldwell B, Vaina LM. (2011). A Method for Selecting an Efficient Diagnostic Protocol for Classification of Perceptive and Cognitive Impairments in Neurological Patients. Conference Proceedings: IEEE Engineering in Medicine and Biology Society, 2011:1129-1132
Calabro FJ, Vaina LM. (2011). A Computerized Perimeter for Assessing Modality-Specific Visual Field Loss. Conference Proceedings: IEEE Engineering in Medicine and Biology Society, 2011:2025-2028
Vaina LM, Soloviev S, Calabro FJ, Buonanno F, Passingham R, Cowey A. (2014). Reorganization of Retinotopic Maps after Occipital Lobe Infarction. J Cogn Neurosci. 26(6):1266-82
Ben-Assa E, Rengifo-Moreno P, Al-Bawardy R, Kolte D, Cigarroa R, Cruz-Gonzalez I, Sakhuja R, Elmariah S, Pomerantsev E, Vaina LM, Ning MM, Buonanno FS, Hung JW, Inglessis I, and Palacios IF. Effect of Residual Interatrial Shunt on Migraine Burden After Transcatheter Closure of Patent Foramen Ovale. JACC: Cardiovascular Interventions. 2020; Volume 13, Issue 3, February 2020 13
Rana, KD, Kahn, S, Hamalainen MS, Vaina, LM (2020). A Computational Paradigm for Real-Time MEG Neurofeedback for Dynamic Allocation of Spatial Attention. Biomedical Engineering OnLine
Kozhemiako, N, Nunes, A, Samal, A, Rana, KD, Hamalinen MS, Kahn, S, Vaina, LM (2020). Neural Activity Underlying the Detection of an Object Movement by an Observer During Forward Self-motion: Dynamic Decoding and Temporal Evolution of Directional Cortical Connectivity. Progress in Neurobiology, Vol 195; doi: 10.1016/j.pneurobio.2020.101824
Vaina, LM, Calabro, F, Samal, A, Mamashli, F, Khan, S, Hamalainen, M, Alford, S, Ahvenien, J (2021). Auditory Cues Facilitate Object Movement Processing in Human Extrastriate Visual Cortex During Simulated Self-motion: a Pilot Study. Brain Research Vol. 175
Our Researchers and Collaborators
- Medical Director, Stroke Program, Spaulding Rehabilitation Hospital
- Professor of Radiology, Harvard Medical School
- Director, David Cohen MEG Laboratory
- Martinos Center for Biomedical Imaging
- Assistant Professor of Radiology, Massachusetts General Hospital & Massachusetts Institute of Technology
- MGH Physical Medicine and Rehabilitation Service
- Assistant Professor of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital
- Interventional Cardiologist
- Professor of Cardiology, Massachusetts General Hospital
- Director, Knight Catheterization Laboratory
- Vascular Neurologist
- Vice Chair, Department of Neurology
- Director, MGH Comprehensive Stroke Center
- Associate Professor of Neurology, Brigham & Women's Hospital
Lucia Vaina, MD, PhD
- Director, Neurology of Vision Lab
- Lecturer in Neurology, Harvard Medical School
- Professor of Biomedical Engineering and Neuroscience, Boston University
- Martinos Center for Biomedical Imaging
Consultants & Affiliates
Fernandino Buonnano, MD
Assistant Professor of Neurology Emeritus, Harvard Medical School
Michael E. Goldberg, MD
David Mahoney Professor of Brain and Behavior in Neuroscience and Neurology in Psychiatry and Ophthalmology; Principal Investigator, Zuckerman Institute, Columbia University
Kunjan Dinesh Rana, PhD
Postdoctoral Researcher, National Institute of Mental Health (NIMH)