Dendrites are where neurons do most of their heavy electrical lifting, yet textbooks often flatten that complexity into a few cable-theory pages. Electrical Dynamics Of The Dendritic Space breaks that mold. Written by Sergiy M. Korogod and Suzanne Tyč-Dumont and published by Cambridge University Press in 2010, the book carves out a 200-page deep dive into how dendritic geometry and membrane kinetics shape neural computation. Below is an SEO-tuned, human-readable review to help you decide if this specialised volume belongs on your lab shelf.
Table of Contents
Book at a Glance
| Full Title | Electrical Dynamics Of The Dendritic Space |
| Authors | Sergiy M. Korogod & Suzanne Tyč-Dumont |
| Publisher / Year | Cambridge University Press • 2009 (print) |
| Print ISBN | 978-0521896771 |
| Length | 204 pp. |
| Format / Price | Hardcover ≈ US $75–81 depending on retailer |
| Audience | Neuroscientists, computational modellers, advanced grad students |
Why Electrical Dynamics Of The Dendritic Space Matters
- Whole-arbor perspective – Instead of treating dendrites as passive cables, the authors analyse full three-dimensional arborisations and show how local voltage and current transfer interact across branches.
- Functional “dendritic space” concept – A fresh modelling framework maps electrical states throughout the arbor, revealing how geometry influences spike timing and pattern generation.
- Simulation companion tools – The text references an accompanying NeuronViewer program, letting readers visualise the models in action.
- Bridges micro and macro – Chapters connect single-branch biophysics to network-level coding implications, making the material useful for both cellular electrophysiologists and systems modellers.
Chapter Highlights
| Ch. | Focus | Key Take-aways |
|---|---|---|
| 1 | Neuron definition | Distills why dendrites, not somas, dominate integrative properties. |
| 2 | 3-D geometry | Quantitative measures of branch length, taper and bifurcation angle. |
| 3 | Bioelectricity basics | Membrane equations refreshed for non-physicists. |
| 4–6 | Cable theory redux | Voltage & current transfer analyses updated with spatial mapping. |
| 7–9 | Artificial paths & geography | How simplified geometries predict real-arbor behavior. |
| 10–12 | Biological case studies | Motoneuron, Purkinje and pyramidal dendrites dissected electrically. |
| 13 | Coding output patterns | Shows how dendritic space shapes spike trains and bursting. |
| 14 | Concluding remarks | Open questions and software resources. |
Strengths That Stand Out
- Data-driven visuals – Dozens of colour heat-maps and 3-D renders make complex transfer functions intuitively clear.
- Interdisciplinary readability – Math is rigorous yet step-wise, easing entry for experimentalists wary of differential equations.
- Endorsements from field leaders – Praise by Matthew Larkum, Rodolfo Llinás and Gordon Shepherd underscores the book’s authority.
Limitations to Consider
| Limitation | Impact | Work-around |
|---|---|---|
| Pre-2010 ion-channel datasets | Some parameters need updating for latest Hodgkin-Huxley fits | Cross-check with recent NEURON modelDB files |
| Niche focus | Limited coverage of glial or axonal dynamics | Pair with a general cellular neurophysiology text |
| Software link rot | Original NeuronViewer URL may require archive access | Search GitHub forks or email the authors |
Who Should Read Electrical Dynamics Of The Dendritic Space?
- Computational neuroscientists – Gain ready-made algorithms for spatially resolved dendritic modelling.
- Patch-clamp electrophysiologists – Translate local dendritic recordings into whole-cell behaviour predictions.
- Advanced neuroscience students – Build intuition for how shape and ion channels co-define neural codes.
- Systems modellers – Inform network simulations with realistic dendritic filtering and delay parameters.
FAQ
Is the math approachable for non-engineers?
Yes. The authors recap cable theory step-by-step before scaling to 3-D arbors, making equations digestible with high-quality diagrams.
Does the book provide software examples?
A NeuronViewer tool accompanies the text, illustrating the simulations discussed in later chapters.
How current is the content?
The theoretical framework remains timeless, but readers may want to update channel kinetics and membrane constants with post-2015 literature.
