Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits

  1. Balazs B Ujfalussy  Is a corresponding author
  2. Judit K Makara
  3. Tiago Branco
  4. Máté Lengyel
  1. University of Cambridge, United Kingdom
  2. Institute of Experimental Medicine, Hungary
  3. MRC Laboratory of Molecular Biology, United Kingdom

Abstract

Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalises how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems-level properties of cortical circuits.

Article and author information

Author details

  1. Balazs B Ujfalussy

    Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
    For correspondence
    balazs.ujfalussy@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
  2. Judit K Makara

    Lendület Laboratory of Neuronal Signaling, Institute of Experimental Medicine, Budapest, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  3. Tiago Branco

    MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Máté Lengyel

    Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

Ethics

Animal experimentation: Hippocampal experiments were conducted according to methods approved by the Janelia Farm Institutional Animal Care and Use Committee and 26 the Animal Care and Use Committee (ACUC) of the Institute of Experimental Medicine, Hungarian Academy of 27 Sciences, and in accordance with 86/609/EEC/2 and DIRECTIVE 2010/63/EU Directives of the EU. Neocortical experiments were performed in strict accordance with guidelines of the Wolfson Institute for Biomedical Research and with the national guidelines.

Reviewing Editor

  1. Frances K Skinner, University Health Network, Canada

Publication history

  1. Received: July 14, 2015
  2. Accepted: December 23, 2015
  3. Accepted Manuscript published: December 24, 2015 (version 1)
  4. Version of Record published: March 31, 2016 (version 2)

Copyright

© 2015, Ujfalussy et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,651
    Page views
  • 825
    Downloads
  • 21
    Citations

Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Balazs B Ujfalussy
  2. Judit K Makara
  3. Tiago Branco
  4. Máté Lengyel
(2015)
Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits
eLife 4:e10056.
https://doi.org/10.7554/eLife.10056

Further reading

    1. Computational and Systems Biology
    2. Neuroscience
    Vasileios Dimakopoulos et al.
    Research Article

    The maintenance of items in working memory (WM) relies on a widespread network of cortical areas and hippocampus where synchronization between electrophysiological recordings reflects functional coupling. We investigated the direction of information flow between auditory cortex and hippocampus while participants heard and then mentally replayed strings of letters in WM by activating their phonological loop. We recorded local field potentials from the hippocampus, reconstructed beamforming sources of scalp EEG, and – additionally in four participants – recorded from subdural cortical electrodes. When analyzing Granger causality, the information flow was from auditory cortex to hippocampus with a peak in the [4 8] Hz range while participants heard the letters. This flow was subsequently reversed during maintenance while participants maintained the letters in memory. The functional interaction between hippocampus and the cortex and the reversal of information flow provide a physiological basis for the encoding of memory items and their active replay during maintenance.

    1. Computational and Systems Biology
    2. Neuroscience
    Raymond Doudlah et al.
    Research Advance

    Visually guided behaviors require the brain to transform ambiguous retinal images into object-level spatial representations and implement sensorimotor transformations. These processes are supported by the dorsal 'where' pathway. However, the specific functional contributions of areas along this pathway remain elusive due in part to methodological differences across studies. We previously showed that macaque caudal intraparietal (CIP) area neurons possess robust three-dimensional (3D) visual representations, carry choice- and saccade-related activity, and exhibit experience-dependent sensorimotor associations (Chang et al., 2020b). Here, we used a common experimental design to reveal parallel processing, hierarchical transformations, and the formation of sensorimotor associations along the 'where' pathway by extending the investigation to V3A, a major feedforward input to CIP. Higher-level 3D representations and choice-related activity were more prevalent in CIP than V3A. Both areas contained saccade-related activity that predicted the direction/timing of eye movements. Intriguingly, the time-course of saccade-related activity in CIP aligned with the temporally integrated V3A output. Sensorimotor associations between 3D orientation and saccade direction preferences were stronger in CIP than V3A, and moderated by choice signals in both areas. Together, the results explicate parallel representations, hierarchical transformations, and functional associations of visual and saccade-related signals at a key juncture in the 'where' pathway.