From the connectome to brain function
Abstract
In this Historical Perspective, we ask what information is needed beyond connectivity diagrams to understand the function of nervous systems. Informed by invertebrate circuits whose connectivities are known, we highlight the importance of neuronal dynamics and neuromodulation, and the existence of parallel circuits. The vertebrate retina has these features in common with invertebrate circuits, suggesting that they are general across animals. Comparisons across these systems suggest approaches to study the functional organization of large circuits based on existing knowledge of small circuits.
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The model used naive estimates of synaptic weights from the simple measure of number of synapses, simplified linear rate model neuron treatment of cell morphology, synaptic and intrinsic cellular biophysics, and neglected possible neuromodulatory effects.
“This is especially so given our naive estimates of synaptic weights from the simple measure of number of synapses, simplified linear rate model neuron treatment of cell morphology, synaptic and intrinsic cellular biophysics and neglect of possible neuromodulatory effects64.”
From Predicting modular functions and neural coding of behavior from a synaptic wiring diagram (2024) · cites this paper as [64]
Studies of the connectomes of C. elegans and the crustacean stomatogastric ganglion demonstrate that connectivity knowledge constrains, but does not dictate, a particular circuit mechanism.
“Moreover, studies of the connectomes of C. elegans and the crustacean stomatogastric ganglion demonstrate that connectivity knowledge constrains, but does not dictate, a particular circuit mechanism56–58.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [58]
The same neuron or circuit can exhibit different input-output responses and plasticity depending on a global circuit state, as reflected by the concentrations of various neuromodulators.
“The same neuron or circuit can exhibit different input-output responses and plasticity depending on a global circuit state, as reflected by the concentrations of various neuromodulators like dopamine, serotonin, norepinephrine, acetylcholine, and hundreds of different neuropeptides such as opiods (Bargmann, 2012; Bargmann and Marder, 2013).”
From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Bargmann and Marder, 2013
A single neural circuit can be thought of as multiple overlapping circuits with modulation switching between them.
“Furthermore, it has been argued that a single neural circuit can be thought of as multiple overlapping circuits with modulation switching between them (Bargmann, 2012; Bargmann and Marder, 2013).”
From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Bargmann and Marder, 2013
These modulators interact in complex and cell-type-specific ways to influence circuit function.
“These modulators interact in complex and cell-type-specific ways to influence circuit function.”
From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Bargmann and Marder, 2013
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- Authors
- Bargmann, C. I., & Marder, E.
- Affiliations
- Howard Hughes Medical Institute (US)
- Brandeis University (US)
- Corresponding author
- Bargmann, Cornelia I
- Venue
- Nature Methods
- Published
- 2013-05-30
- Volume
- 10
- Issue
- 6
- Pages
- 483-490
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2139919351
- Semantic Scholar
- 12bc9f173f17e9eb5bd31e9a1c3d24761eda2d09
- Cited by
- 561
- References
- 50
- Citations by year
- 2026: 22 · 2025: 44 · 2024: 55 · 2023: 50 · 2022: 33 · 2021: 46 · 2020: 47 · 2019: 54 · 2018: 48 · 2017: 52 · 2016: 37 · 2015: 29 · 2014: 37 · 2013: 7
- FWCI
- 3.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health
- National Institute of Mental Health (MH 46742)
- National Institute of Neurological Disorders and Stroke (R01NS081013, NS81013, NS17813)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Keywords
- connectome, brain function, neural dynamics, neuromodulation, parallel circuits, vertebrate retina, comparative neuroscience
- MeSH terms
- Animals, Brain, Brachyura, Humans, Nerve Net, Neurons, Retina, Synapses, Caenorhabditis elegans, Connectome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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