How to Build Bridges between Computational Neuroscience and Cognitive Psychology // Melanie Pincus

Tuesday, March 24, 2015

Dieter Jaeger and Phillip Wolff

In the first CMBC Faculty Lunch Discussion of the Spring 2015 semester, titled ‘How to Build Bridges between Computational Neuroscience and Cognitive Psychology?’ Dr. Phillip Wolff (Department of Psychology, Emory University) and Dr. Dieter Jaeger (Department of Biology, Emory University) conversed about the ways in which cognitive psychology and neuroscience can develop more meaningful cross-disciplinary collaborations. The two fields address overlapping research questions and use some of the same modeling tools, but, historically, have been relatively isolated from one another. Drs. Wolf and Jaeger emphasized the benefits that can come from greater collaboration between the two disciplines, and acknowledged the challenges that make collaboration inherently difficult. The lunch discussion itself provided a starting-point for bringing faculty and researchers from both disciplines together, encouraging dialogue about the advantages of building a stronger alliance between the two disciplines.

Collaboration between cognitive psychology and computational neuroscience has the potential to be mutually beneficial, as research findings from one discipline help constrain and guide research in the other. Cognitive psychology research delineates how human minds represent information and perform computations in different contexts. Through subtle manipulations of task design, cognitive psychologists can identify whether information can be represented in different ways and which representation is most likely, given the particular context, learning-related changes, and individual cognitive biases. For example, cognitive psychology research has found that the spatial relationship between objects can be represented in multiple ways by the human mind, and that different cultures have biases toward particular representations. A ball sitting on the ground in proximity to a chair could be described as being to the north of the chair, in front of the chair, or to the right of the chair. The first description captures allocentric properties of the scene, the second reflects the position of the objects relative to each other, and the third corresponds to an egocentric perspective. By asking participants to describe the scenes, cognitive psychologists can discern which type of spatial representation participants are using. These varied representations likely map on to different neural processes, so it would be important for a neuroscientist to identify which representation is being used in a particular task, in order to test a more constrained hypothesis about neural pathways of activity. In this way, research findings from cognitive psychology provide top-down guidance to neuroscientists, allowing them to make more precise predictions about the location and type of neural activity they expect to see.

Neuroscientists examine neural processes at varying spatial levels, from subcellular processes taking place in individual neurons, at one end of the continuum, to interactions between functional brain networks at the other end of the continuum. Just as cognitive psychology findings can be used to provide top-down guidance in constraining the hypotheses of neuroscientists, the corpus of neuroscience research can provide bottom-up information about the flow of activity in neural pathways and help psychologists make more refined predictions about cognition, perception, and behavior. For example, lesion and neuroimaging research has provided evidence that there are distinct learning and memory systems in the brain—a hippocampal-based system and a striatal-based one–and that these systems competitively and cooperatively interact, depending on the context. Neuroscience research can help cognitive psychologists refine predictions and build more accurate models to capture how people learn new skills and remember information.

Despite the advantages to be had from greater communication between the disciplines, there are a number of challenges that make collaboration difficult. Some attendees raised the point that between the cellular processes that computational neuroscientists study, and the higher-level cognitive phenomena that cognitive psychologists research, exist multiple layers of neurobiological complexity that are challenging to traverse. A single neuron itself is very complex, receiving inputs from thousands of other neurons and responding to diffuse neuromodulators in a variety of different ways.  Thousands of neurons organize into well-structured networks, which themselves give rise to larger-scale maps, such as the somatotopic map in the somatosensory cortex. At a larger spatial scale, brain regions with well-studied functions come into view, and these regions interact with one another in coordinated ways, defining systems (e.g., the limbic system). Because there are many intermediary steps between the level of neurons and the level of functional systems, and each level is itself defined by profoundly complex interactions, it is inherently challenging to model how activity in individual neurons, or even neuronal networks, map on to higher-level phenomena like language and perception. Despite these challenges, neuroimaging is a promising tool for bridging the gap between nervous system activity at different spatial levels and human cognition. Neuroimaging detects functional activity at the systems level in the brain as humans perform cognitive and perceptual tasks. Thanks to research being carried out by investigators like Shella Keilholz in the Wallace H. Coulter Department of Biomedical Engineering at Emory University and Georgia Institute of Technology, we are gaining insight into how systems-level activity detected by neuroimaging corresponds to the coordinated neural activity occurring on a much finer spatial scale. Hence, neuroimaging provides an important link between how activity at smaller spatial scales in the brain generates higher-level cognitive processes.

 

Another challenge that has proven to be problematic historically for the two disciplines is the dearth of models and theories that make clear and testable predictions. In the early 1990s, the two disciplines temporarily came together to experiment with a new generation of connectionist network models. However, neuroscientists quickly soured on these models because they failed to make clear predictions about neural activity, and psychologists found that they modeled cognition and behavior in ways that were very different from how human minds appear to work. As a result, the two disciplines drifted apart and made less effort to coordinate conferences and meetings together. Recently, new and exciting machine learning algorithms have emerged that may encourage the disciplines to work together more closely again, by providing the means to design and test more promising models. In addition, efforts made by centers like CMBC and other cross-disciplinary institutes and national meetings can facilitate greater communication between the researchers in these fields. As a case in point, the CMBC Faculty Lunch Discussion was successful in bringing together Emory researchers from computational neuroscience and cognitive psychology, some of whom had never met before, and creating a space for the two fields to consider how they can benefit from greater collaboration.

— Melanie Pincus

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