Inferring synaptic inputs from spikes with a conductance-based neural encoding model
- University of Washington, United States
- Princeton University, United States
Abstract
Descriptive statistical models of neural responses generally aim to characterize the mapping from stimuli to spike responses while ignoring biophysical details of the encoding process. Here, we introduce an alternative approach, the conductance-based encoding model (CBEM), which describes amapping fromstimuli to excitatory and inhibitory synaptic conductances governing the dynamics of sub-threshold membrane potential. Remarkably, we show that the CBEM can be fit to extracellular spike train data and then used to predict excitatory and inhibitory synaptic currents. We validate these predictions with intracellular recordings from macaque retinal ganglion cells. Moreover, we offer a novel quasi-biophysical interpretation of the Poisson generalized linear model (GLM) as a special case of the CBEM in which excitation and inhibition are perfectly balanced. This work forges a new link between statistical and biophysical models of neural encoding and sheds new light on the biophysical variables that underlie spiking in the early visual pathway.
Data availability
All modeling tools have been made publicly available at https://github.com/pillowlab/CBEM. The datasets analyzed in this paper have been previously published as the following:1. Conductance and cell-attached spike recordings: Philipp Khuc Trong & Fred Rieke (2008). "Origin of correlated activity between parasol retinal ganglion cells." https://doi.org/10.1038/nn.2199. Dataset available via figshare https://figshare.com/articles/ON-Parasol_RGCs_for_the_conductance-based_encoding_model/9636854.2. Full-field extracellular recordings (including multiple contrasts): V. J. Uzzell & E. J. Chichilnisky (2004). "Precision of Spike Trains in Primate Retinal Ganglion Cells." https://doi.org/10.1152/jn.01171.2003. Dataset can be accessed through a response to the corresponding author.3. Spatio-temporal stimuli: Jonathan W. Pillow, Jonathon Shlens, Liam Paninski, Alexander Sher, Alan M. Litke, E. J. Chichilnisky & Eero P. Simoncelli (2008). "Spatio-temporal correlations and visual signalling in a complete neuronal population." https://doi.org/10.1038/nature07140. Dataset can be accessed through a response to the corresponding author.
Article and author information
Author details
Funding
McKnight Foundation
- Jonathan W Pillow
Simons Foundation (SCGB AWD1004351)
- Jonathan W Pillow
National Science Foundation (IIS-1150186)
- Jonathan W Pillow
National Institute of Mental Health (MH099611)
- Jonathan W Pillow
Howard Hughes Medical Institute
- Fred Rieke
National Institutes of Health (EY011850)
- Fred Rieke
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: Tissue was obtained via the tissue distribution program at the Washington National Primate Research Center. All animal procedures were performed in accordance with IACUC protocols at the University of Washington (IACUC protocol number 4277-01).
Copyright
© 2019, Latimer 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
-
- 2,350
- views
-
- 362
- downloads
-
- 23
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
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)
Inferring synaptic inputs from spikes with a conductance-based neural encoding model
eLife 8:e47012.
https://doi.org/10.7554/eLife.47012
Further reading
-
- Neuroscience
This study examines whether auditory cortex anatomy reflects multilingual experience, specifically individuals’ phonological repertoire. Using data from over 200 participants exposed to 1–7 languages across 36 languages, we analyzed the role of language experience and typological distances between languages they spoke in shaping neural signatures of multilingualism. Our findings reveal a negative relationship between the thickness of the left and right second transverse temporal gyrus (TTG) and participants’ degree of multilingualism. Models incorporating phoneme-level information in the language experience index explained the most variance in TTG thickness, suggesting that a more extensive and more phonologically diverse language experience is associated with thinner cortices in the second TTG. This pattern, consistent across two datasets, supports the idea of experience-driven pruning and neural efficiency. Our findings indicate that experience with typologically distant languages appear to impact the brain differently than those with similar languages. Moreover, they suggest that early auditory regions seem to represent phoneme-level cross-linguistic information, contrary to the most established models of language processing in the brain, which suggest that phonological processing happens in more lateral posterior superior temporal gyrus (STG) and superior temporal sulcus (STS).
-
- Neuroscience
The brain is organized into systems and networks of interacting components. The functional connections among these components give insight into the brain's organization and may underlie some cognitive effects of aging. Examining the relationship between individual differences in brain organization and cognitive function in older adults who have reached oldest old ages with healthy cognition can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry. We found that the segregation of the association system and the individual networks within the association system [the fronto-parietal network (FPN), cingulo-opercular network (CON) and default mode network (DMN)], has strong associations with overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals representing successful cognitive aging.
