The Faculty

Focus

Observational and theoretical approaches to how the brain encodes and stores information

Education

PhD, University of Manitoba

Research Interests

  • Cellular & Molecular
  • Computational & Theoretical
  • Development & Plasticity
  • Systems / Behavior / Cognitive

Neurons do not work in isolation but rather operate together, within local interconnected circuits. Our lab uses the latest technology in microscopy to allow us to examine the long standing questions of how information is encoded and stored in the neocortex, at the level of the functional neuronal circuit. Other techniques are limited to the examination of either large brain regions, missing the resolution needed to analyze the underlying mechanisms, or to single neurons, missing the activity of the circuit in which the neurons are embedded. Experiments at the circuit level are essential to answering these questions because studies in which single or even a few cells are monitored fundamentally miss the emergent properties of these circuits.

Select Publications

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks.
Bojanek K, Zhu Y, MacLean J. Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks. PLoS Comput Biol. 2020 09; 16(9):e1007409.
PMID: 32997658

Network Analysis of Murine Cortical Dynamics Implicates Untuned Neurons in Visual Stimulus Coding.
Levy M, Sporns O, MacLean JN. Network Analysis of Murine Cortical Dynamics Implicates Untuned Neurons in Visual Stimulus Coding. Cell Rep. 2020 04 14; 31(2):107483.
PMID: 32294431

A platform for semiautomated voluntary training of common marmosets for behavioral neuroscience.
Walker JD, Pirschel F, Gidmark N, MacLean JN, Hatsopoulos NG. A platform for semiautomated voluntary training of common marmosets for behavioral neuroscience. J Neurophysiol. 2020 04 01; 123(4):1420-1426.
PMID: 32130092

Recurrent interactions can explain the variance in single trial responses.
Kotekal S, MacLean JN. Recurrent interactions can explain the variance in single trial responses. PLoS Comput Biol. 2020 01; 16(1):e1007591.
PMID: 31999693

Functional triplet motifs underlie accurate predictions of single-trial responses in populations of tuned and untuned V1 neurons.
Dechery JB, MacLean JN. Functional triplet motifs underlie accurate predictions of single-trial responses in populations of tuned and untuned V1 neurons. PLoS Comput Biol. 2018 05; 14(5):e1006153.
PMID: 29727448

Editorial: Spontaneous Activity in Sensory Systems.
Imaizumi K, Ruthazer ES, MacLean JN, Lee CC. Editorial: Spontaneous Activity in Sensory Systems. Front Neural Circuits. 2018; 12:27.
PMID: 29651239

Ensemble stacking mitigates biases in inference of synaptic connectivity.
Chambers B, Levy M, Dechery JB, MacLean JN. Ensemble stacking mitigates biases in inference of synaptic connectivity. Netw Neurosci. 2018; 2(1):60-85.
PMID: 29911678

Learning to make external sensory stimulus predictions using internal correlations in populations of neurons.
Sederberg AJ, MacLean JN, Palmer SE. Learning to make external sensory stimulus predictions using internal correlations in populations of neurons. Proc Natl Acad Sci U S A. 2018 01 30; 115(5):1105-1110.
PMID: 29348208

Emergent cortical circuit dynamics contain dense, interwoven ensembles of spike sequences.
Dechery JB, MacLean JN. Emergent cortical circuit dynamics contain dense, interwoven ensembles of spike sequences. J Neurophysiol. 2017 09 01; 118(3):1914-1925.
PMID: 28724786

The marmoset as a model system for studying voluntary motor control.
Walker J, MacLean J, Hatsopoulos NG. The marmoset as a model system for studying voluntary motor control. Dev Neurobiol. 2017 03; 77(3):273-285.
PMID: 27739220