Explore This Lab

Overview

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.

Research Projects

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.

Research Positions

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.

Publications

Books

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

Additional publications on PubMed

Our Researchers and Collaborators

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)