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Ion conductance and ion selectivity of potassium channels in snail neurones (1980)

Reuter, H. ; Stevens, C. F.

Springer

The journal of membrane biology 57 (1980), S. 103-118

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ISSN: 1432-1424

Source: Springer Online Journal Archives 1860-2000

Topics: Biology , Chemistry and Pharmacology

Notes: Summary Delayed potassium channels were studied in internally perfused neurone somata from land snails. Relaxation and fluctuation analysis of this class of ion channels revealed Hodgkin-Huxley type K channels with an average single channel conductance (γ K) of 2.40±0.15 pS. The conductance of open channels is independent of voltage and virtually all K channels seem to be open at maximum K conductance (g K) of the membrane. Voltage dependent time constants of activation ofg K, calculated from K current relaxation and from cut-off frequencies of power spectra, are very similar indicating dominant first-order kinetics. Ion selectivity of K channels was studied by ion substitution in the external medium and exhibited the following sequence: T1+〉K+〉Rb+〉Cs+〉NH 4 + 〉Li+〉Na+. The sequence of the alkali cations does not conform to any of the sequences predicted by Eisenman's theory. However, the data are well accommodated by a new theory assuming a single rate-limiting barrier that governs ion movement through the channel.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1007/BF01868997

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A neural algorithm for a fundamental computing problem (2017)

Dasgupta, S., Stevens, C. F., Navlakha, S.

American Association for the Advancement of Science (AAAS)

In: Science

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Publication Date: 2017-11-10

Description: Similarity search—for example, identifying similar images in a database or similar documents on the web—is a fundamental computing problem faced by large-scale information retrieval systems. We discovered that the fruit fly olfactory circuit solves this problem with a variant of a computer science algorithm (called locality-sensitive hashing). The fly circuit assigns similar neural activity patterns to similar odors, so that behaviors learned from one odor can be applied when a similar odor is experienced. The fly algorithm, however, uses three computational strategies that depart from traditional approaches. These strategies can be translated to improve the performance of computational similarity searches. This perspective helps illuminate the logic supporting an important sensory function and provides a conceptually new algorithm for solving a fundamental computational problem.

Keywords: Computers, Mathematics, Engineering

Print ISSN: 0036-8075

Electronic ISSN: 1095-9203

Topics: Biology , Chemistry and Pharmacology , Geosciences , Computer Science , Medicine , Natural Sciences in General , Physics