Lisa Saksida


Scientific Director, BrainsCAN

Why I Became a Scientist

I have broad  training in psychology and cognitive neuroscience, with specific and extensive expertise on the neurobiological mechanisms of cognition including memory and perception. We are working toward a better understanding of the psychological processes underlying memory and perception through a programme of theoretically-driven experimental research using both healthy subjects and brain-damaged populations.

We utilize computational models and animal models to investigate both the healthy brain and what can go wrong after damage or neurodegeneration, with a major goal being the successful translation of findings to humans and, eventually, to the clinic. A key part of our research program has been the development of novel cognitive testing methods to achieve this goal.  

Research in our lab spans across several species and techniques (lesion studies, pharmacology, computational modelling, genetically modified mouse models, patient studies), in each case using the appropriate species and technique for the specific question at hand.

Research Questions

I co-direct the Translational Cognitive Neuroscience Lab (TCNLab) with Timothy Bussey, PhD. I'm interested in cognition in the healthy brain, what goes wrong in neurodegenerative and neuropsychiatric disease such as Alzheimer’s and Schizophrenia, and identifying targets for therapy.

Alzheimer’s Disease

Because the loss of memory is the most common symptom lamented by affected patients, the disease is often regarded simply as a memory disorder. In the majority of individuals with Alzheimer's disease, however, multiple cognitive domains are compromised including attention and response control; indeed such impairments can occur early in the disease and precede language and spatial impairments. Our work in this area mainly involves developing and validating assays for phenotyping murine models of this disease across all of these domains of cognition.


Current anti-psychotics do quite a good job suppressing these psychotic symptoms. However, they do not do very much to address the cognitive symptoms, and so the cognitive symptoms – impairments in learning, memory, perception, reasoning, etc. – persist. We work on the development of assays for understanding cognition in models of schizophrenia. Our work focuses on developing new animal models and the use of brain recording and behavioural tests to identify innovative and effective drugs for schizophrenia.

Cognitive Task Development

A major difficulty in moving research from the bench to the clinic is the translational gap between animal studies and clinical trials. For example, although many medications for Alzheimer’s disease have been successful in animal tests, they have failed to lead to functional improvement in human clinical trials (Gravitz, 2011, Cummings, 2010, Bezprozvanny, 2010). One of the factors that may have contributed to these failures is differences between how efficacy of compounds is assessed in animals and humans, which in diseases affecting cognition usually means cognitive and behavioural tests.

A major thrust of the TCNLab is to improve translation to the clinic, mainly through scientific and technological innovation. Most people in the lab are working in one way or another on the development of a touchscreen-based cognitive assessment system for rodents. The system enables us to utilize very similar, and in many cases identical, cognitive assays in mice and humans. This method has the tremendous advantage of eliminating numerous confounds, in addition to maximizing the likelihood that the same underlying cognitive processes are being probed in both mice and humans. Thus, the effects of manipulations at multiple levels on cognition can be evaluated in mouse and rat models of neurodegenerative and neuropsychiatric disease, and then directly compared to the cognitive profiles of human patients.

Modularity of Function in the Medial Temporal Lobe

The work that has formed the backbone of our research over the past 10 years has involved the development of a novel theory of the organization of cognition in the medial temporal lobe and ventral visual stream. The main idea behind this 'representational-hierarchical' view is that, rather than confining ourselves to the prevailing paradigm of assuming modularity of cognitive processes within anatomically-defined cognitive boxes in the brain, we would do better to consider the representations maintained in differing brain circuits, which can subserve a variety of cognitive functions.

These organizational principles have been instantiated in computational models, which have in turn been used to drive empirical work. Initial experiments tested the implications of this framework for memory in the healthy brain; however, over the past five years we have been applying it to the understanding of cognitive function in the dysfunctional brain, in conditions such as amnesia and dementia. Recent work, for example, has explored the prediction of this model that memory impairment in cases of medial temporal lobe amnesia and Alzheimer’s Disease may be due in large part to abnormal susceptibility to perceptual interference.

We believe that novel thinking can lead to novel therapies and indeed, in these experiments treatments suggested by the predictions of the model were found to ameliorate memory impairments resulting from brain damage and Alzheimer’s pathology.

Pattern Separation

For most people, memory is about time. It is easier to remember a set of items in a memory test if they are presented a few seconds before memory retrieval, than if they are presented several hours before. When memory fails, as it does normally in old age, or under pathological conditions such as Alzheimer’s disease, this failure is reflected in the inability to remember over an extended period of time – although the ability to remember over a few seconds may remain intact. Increasingly, however, memory researchers are becoming interested in the ability not to remember over time, but to keep memories distinct and resistant to confusion. If asked to remember where you parked your car this morning, yesterday morning and the day before, the task is difficult not because you need to remember over a long period – you can easily remember many things that happened three days ago – but because the similar memories of your car in that same parking lot are so easily confused.

The ability to separate the components of memories into distinct complex memory representations that are unique and less easily confused has been simulated by computational models of memory and has been referred to as ‘pattern separation’.

The psychological and neurobiological mechanisms underlying pattern separation are a particular interest of this lab.


  • Ph.D. Neural Basis of Cognition and Robotics, Carnegie Mellon University
  • M.Sc. Articifical Intelligence, University of Edinburgh
  • M.A. Biopsychology, University of British Columbia
  • B.Sc. Psychology, Western University


  • Fogarty International Research Fellow – Elisabeth Murray, National Institute of Mental Health


  • Professional Fellow, Newnham College Cambridge, 2015
  • Canadian Institute for Advanced Research Senior Fellow, 2014-2019
  • Pinsent Darwin Fellow, 2000-2004
  • Sir James Lougheed Award of Distinction, 1998-1999
  • Carnegie Mellon Robotics Institute Full Scholarship, 1994-1999
  • Natural Sciences and Engineering Research Council of Canada (NSERC), PGS-B Award, 1993-1995
  • NATO Advanced Study Institute Scholarship, 1993
  • Natural Sciences and Engineering Research Council of Canada (NSERC), Undergraduate Research Award, 1991
  • Dow Chemical Full Tuition Scholarship, 1987-1991
  • Western University, Admission Scholarship, 1987-1988
  • Ontario Scholar Award, 1987-1999


My work to date has resulted in over 115 publications which have been highly cited and published in high impact journals including Science, Neuron, Nature Neuroscience, Nature Protocols, Cell Reports, PNAS, and Brain.

View all PubMed publications

Contact Info

Lisa Saksida, PhD
Scientist and Scientific Director, BrainsCAN
Rm. 3228, Robarts Research Institute
Western University
London, Ontario
N6A 5B7

Phone: 519-931-5777 ext. 83604
Twitter: @TCNLab