Computational Neuroscience

Research Description

Neurons in the spinal cord provide the neural interface for sensation and movement. Our lab focuses on the mechanisms of motor output in both normal and disease states (spinal injury, amyotrophic lateral sclerosis). We use a broad range of techniques including intracellular recordings, array recordings of firing patterns, 2-photon imaging, pharmacological manipulations, and behavioral testing. These techniques are applied in in vitro and in vivo animal preparations. In addition we have extensive collaborations with colleagues who study motor output in human subjects.

For lab information and more, see Dr. Heckman's faculty profile.

Publications

See Dr. Heckman's publications on PubMed.

Contact

Contact Dr. Heckman at 312-503-2164.

Research Faculty: Matthieu Chardon, Mingchen Jiang, Michael Johnson, Thomas Sandercock

Postdoctoral Fellows: Amr Mahrous, Jack Miller, Gregory Pearcey

Graduate Students: Seoan Huh, Edward Kim, Emily Reedich, Theeradej Thaweerattanasinp, Jessica Wilson

Technical Staff: Rebecca Cranmer

Research Description

The primary goal of the research in my lab is to understand the nature of the somatosensory and motor signals within the brain that are used to control arm movements. Most of the experiments in my laboratory rely on multi-electrode arrays that are surgically implanted in the brains of monkeys. These “neural interfaces” allow us to record simultaneously from roughly 100 individual neurons in the somatosensory and motor cortices and thereby study the brain’s own control signals as the monkey makes reaching and grasping movements. We can also pass tiny electrical currents through the electrodes to manipulate the natural neural activity and study their effect on neural activity and the monkey’s behavior.

Current projects seek to understand:

1. How motor cortical activity leads to the complex patterns of muscle contractions needed to produce movement
2. How movement of the limb and forces exerted by the hand are “encoded” in the activity of neurons in the somatosensory cortex

We also study how these relations are affected by behavioral context: the magnitude and dynamics of exerted forces, the varied requirements for sensory discrimination, and the quality of the visual feedback that is provided to the monkey to guide its movements.

Along with this basic research, we can use these neural interfaces to bypass the peripheral nervous system, in order to connect the monkey’s brain directly to the outside world. We are developing neural interfaces that ultimately will use signals recorded from the brain to allow patients who have lost a limb to operate a prosthetic limb. The interface may also be used to bypass a patient’s injured spinal cord in order to restore voluntary control of their paralyzed muscles. Conversely, electrical stimulation of the brain will restore the sense of touch and limb movement to patients with limb amputation or spinal cord injury. This highly interdisciplinary work is enabled by numerous collaborations at Northwestern University and other institutions.

For lab information and more, see Dr. Miller's faculty profile and lab website.

Publications

See. Dr. Miller's publications on PubMed.

Contact

Contact Dr. Miller at 312-503-8677.

Postdoctoral Fellows: Xuan Ma, Fabio Rizzoglio

Technical Staff: Kevin Bodkin, Henry Powell

Research Description

We want to understand how neural circuits across many brain areas interact to support decision making. In particular, how are these interactions flexibly reconfigured when animals make decisions that use different underlying computations? To do this we combine high-throughput mouse behavior in virtual reality, optical and genetic tools to measure and manipulate the dynamics of single neurons and neuronal populations, and computational approaches to understand both the behavior and its relationship to neural activity.

• Decision-making and its different underlying computations: There is much evidence to suggest that decision-making computations happen across widespread brain areas, including many in the cerebral cortex. But how do these areas interact to make a single decision? And how can the brain perform different computations using the same pool of neural circuits? Decisions that require different combinations of underlying computations appear to be associated with distinct patterns of large-scale activity across the cerebral cortex. We want to understand how neuromodulatory mechanisms potentially control these different dynamic configurations of neural activity, and how they map onto different cognitive operations.
• Neuromodulatory mechanisms of the reorganization of large-scale cortical dynamics: We study the brain circuits that switch between, and maintain, the different dynamic configurations of large-scale cortical activity that support different types of decisions. A particular focus is on the role of neuromodulators such as acetylcholine. This line of inquiry is also of potential clinical interest, as it may help us understand how neurodegenerative diseases such as Alzheimer’s lead to decision-making deficits.
• Functional organization of large-scale cortical dynamics: Another crucial question is whether there is actually a logic to the way large-scale cortical dynamics change according to the behaviors they support. To put it another way, are there core computations performed by each cortical area that explain why activity across the cortex looks the way it does during different tasks? We believe answering this will help us provide parsimonious explanations of cortical function using general computational principles.

For lab information and more, see Dr. Pinto's faculty profile and laboratory website.

Publications

See Dr. Pinto's publications on PubMed.

Contact

Contact Dr. Pinto at 312-503-7928.

Research Faculty: Julia Cox

Postdoctoral Fellows: Jose Ernesto Canton-Josh, Renan Costa, Jiaqi Keith Luo, Matthew Rynes

Graduate Students: Lyn Ackert-Smith, Junhua Tan

Technical Staff: Camey Calzolano, Erin Myhre

Research Description

The goal of our research is to understand information processing in the brain. We use mathematical models based on specific hypothesis about encoding and decoding aspects of neural activity, and use analytical and numerical techniques to investigate the implications of these hypothesis so that they can be validated, modified, or discarded as dictated by experimental data.

Our purpose is to understand the computational implications of neural dynamics. Our work relies on conceptual frameworks and mathematical tools from statistical physics, information theory, nonlinear dynamics, probability theory, and machine learning, and aims at formulating data driven models that illuminate specific aspects of information processing by networks of neurons.

Specific topics of interest include input-output characteristics of single cell and network models, encoding and decoding of information through neural activity, early stages of sensory processing, and the neural control of movement. We work in close collaboration with experimental groups, both at Northwestern University and at other institutions. Recently, we have focused on the interplay between neural connectivity, network dynamics, and computation, and on brain-machine interfaces for the decoding of neural activity in motor cortex and the encoding of sensory information via stimulation of somatosensory cortex. Our work on brain-machine interfaces is funded by NINDS, the National Institute of Neurological Disorders and Strokes within the NIH. 

For lab information and more, see Dr. Solla’s faculty profile.

Publications

See Dr. Solla's publications on PubMed.

Contact

Contact Dr. Solla at 312-503-1408 or the lab at 312-503-1408.

Research Description

Our group has five research topics. The first topic area is what drives Parkinson’s disease (PD). Using a combination of optical, electrophysiological and molecular approaches, we are examining the factors governing neurodegeneration in PD and its network consequences, primarily in the striatum. This work has led to a Phase III neuroprotection clinical trial for early stage PD and a drug development program targeting a sub-class of calcium channels. The second topic area is network dysfunction in Huntington’s disease (HD). Using the same set of approaches, we are exploring striatal and pallidal dysfunction in genetic models of HD, again with the aim of identifying novel drug targets. The third topic area is striatal dysfunction in schizophrenia, with a particular interest in striatal adaptations to neuroleptic treatment. The fourth topic area is post-traumatic stress disorder and the role played by neurons in the locus ceruleus in its manifestations. The last topic area is chronic pain states and the impact these have on the circuitry of the ventral striatum.

For lab information and more, see Dr. Surmeier's faculty profile.

Publications

See Dr. Surmeier's publications on PubMed.

Contact

Contact Dr. Surmeier at 312-503-4904.

Lab Manager and Research Associate: Sasha Ulrich

Research Faculty: Vernon Clarke, Qiaoling Cui, Michelle Day, Jaime Guzman-Lucero, Ema Ilijic, David Wokosin, Weixing Shen, Tatiana Tkatch, Jun Ueda, Zhong Xie, Enrico Zampese, Shenyu Zhai

Postdoctoral Fellows: Marziyeh Belal, Martin Henrich, James Moran, DeNard Simmons, Yichen Wu, Enrico Zampese, Shenyu Zhai

Research Staff: Tamara Perez-Rosello

Technical Staff: Marisha Alicea, Kang Chen, Yu Chen, Bonnie Erjavec, Daniel Galtieri, Christine Kamide, Danielle Schowalter, Marisol Serrano

Visiting Scholar: Fanni Geibl