Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons

Branco, Tiago; Clark, Beverley A.; Häusser, Michael

doi:10.1126/science.1189664

Cited by 413 publications

(432 citation statements)

References 33 publications

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“…The results of our analysis of the electrical activity in basal ganglia GPe, GPi, STN and ZI of monkeys reaching to seen targets is consistent with the idea that GPe is implicated in prospectively guiding the ρ of a movement using the prospective neural-power function, ρ G ; that STN is implicated in the perceptual monitoring of the movement; and that ZI is implicated in integrating (Sherrington 1961, Branco et al 2010, 2012) the ρ of prospective neural-power from GPe and the ρ of perceptual neural-power from STN to create the ρ of enacting neural-power at ZI. The ρ of the enacting neural-power both informationally and physically (after amplification, e.g., with ATP) powers the ρ of muscular-power (the rate of flow of energy into the muscles) and this powers the ρ of the actionpower of the movement.…”

Section: Discussionsupporting

confidence: 67%

Function of basal ganglia in tauG-guiding action

Lee

Georgopoulos

Pepping

2017

Preprint

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Nervous systems control purposeful movement, both within and outside the body, which is essential for the survival of an animal. The movement control functions of globus pallidus (GP), subthalamic nucleus (STN) and zona incerta (ZI) were analyzed in monkeys reaching for seen targets. Temporal profiles of the hand movements of monkeys and the synchronized flow of electrochemical energy through these basal ganglia were analyzed in terms of a theory of goal-directed movement. Theoretical and empirical analysis indicated: (i) the neural information for controlling movement is the relative-rate-of-change of flow of electrochemical energy in neurons rather than the flow itself; (ii) GP is involved in creating prospective electrochemical flow to guide movement; (iii) STN is involved in registering the perceptual electrochemical flow monitoring the movement; (iv) ZI is involved in integrating the prospective and perceptual electrochemical flows to power the muscles and thence the movement. Possible implications for PD are discussed.

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Section: Discussionsupporting

confidence: 67%

Function of basal ganglia in tauG-guiding action

Lee

Georgopoulos

Pepping

2017

Preprint

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“…Furthermore, an interesting consequence of minimizing wiring to target synapses is that synapses that are close together are more likely to be linked by the same stretch of dendrite and therefore involved in a local computation (31)(32)(33), such that geometry is a key determinant of information processing. There is increasing evidence that such sophisticated local processing may be carried out within the dendritic tree (34,35), with nonlinear interactions between synaptic inputs shaping the output of the neuron (36)(37)(38)(39). We therefore predict it will be fruitful to study how the scaling laws of wiring and branching place constraints on the overall computational power of single neurons.…”

Section: Discussionmentioning

confidence: 99%

A scaling law derived from optimal dendritic wiring

Cuntz

Mathy

Häusser

2012

Proc. Natl. Acad. Sci. U.S.A.

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111

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The wide diversity of dendritic trees is one of the most striking features of neural circuits. Here we develop a general quantitative theory relating the total length of dendritic wiring to the number of branch points and synapses. We show that optimal wiring predicts a 2/3 power law between these measures. We demonstrate that the theory is consistent with data from a wide variety of neurons across many different species and helps define the computational compartments in dendritic trees. Our results imply fundamentally distinct design principles for dendritic arbors compared with vascular, bronchial, and botanical trees.computational neuroscience | branching | dendrite | morphology | minimum spanning tree O ne of the main roles of dendrites is to connect a neuron to its synaptic inputs. To interpret neural connectivity from morphological data, it is important to understand the relationship between dendrite shape and synaptic input distribution (1-4). As early as the end of the 19th century (5), it was suggested that dendrites optimize connectivity in terms of cable length and conduction time costs, and a number of recent studies have supported the idea that optimal wiring explains dendritic branching patterns using simulations (6-8) or by reasoning from first principles (1, 2, 9, 10). However, although dendrite length is the most common measure for molecular studies of dendritic growth (11), its relationship to dendritic branching and the number of synaptic contacts has not been elucidated. Understanding this relationship should provide crucial constraints for circuit structure and function. Here we directly test the hypothesis that neurons wire up a space in an optimal way by studying the consequences for dendrite length and branching complexity. We derive a simple equation that directly relates dendrite length with the number of branch points, dendrite spanning volume, and number of synapses. ResultsRelating Total Dendritic Length to Optimal Wiring. We assume that a dendritic tree of total length L connects n target points distributed over a volume V (Fig. 1A). Each target point occupies an average volume V =n. A tree that optimizes wiring will tend to connect points to their nearest neighbors, which are on average located at distances proportional to ðV =nÞ 1=3 . We need at least n such dendritic sections to make up the tree. The total length L of these sections sums up toThis result shows that a 2/3 power law relationship between L and n (12) provides a lower bound for the total dendritic length, where c is a proportionality constant. Approximating the volume around each target point by a sphere, then c ¼ ð3=4πÞ 1=3 , and each dendritic section corresponds to the radius of a sphere, giving(SI Text and Fig. S1). Importantly, assuming a constant ratio between the number of branch points, bp and the number of target points (which is addressed later), this assumption also results in a 2/3 power law between wiring length and the number of branch points. Supporting these intuitive derivations of power laws, there ...

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“…While Branco et al 38 recently used focal glutamate uncaging at multiple sites along one dendrite to generate sequence-dependent intracellular responses, this mechanism presumably operates primarily through rapid cell-autonomous mechanisms. By contrast, the dentate gyrus circuits activated in the present study reliably encoded temporal sequences with substantially longer time intervals and could be decoded accurately only by comparing activity across multiple simultaneously-recorded hilar cells.…”

Section: Information Representation In the Dentate Gyrus In Vitromentioning

confidence: 99%

Mnemonic representations of transient stimuli and temporal sequences in the rodent hippocampus in vitro

Hyde

Strowbridge

2012

Nat Neurosci

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A primary function of the brain is to store and retrieve information. Except for working memory, where extracellular recordings demonstrate persistent discharges during delay-response tasks, it has been difficult to link memories with changes in individual neurons or specific synaptic connections. Here, we demonstrate that transient stimuli are reliably encoded in the ongoing activity of brain tissue in vitro. We found that the patterns of synaptic input onto dentate hilar neurons predict which of four pathways were stimulated with an accuracy of 76% and performed significantly better than chance for >15 s. Dentate gyrus neurons also could accurately encode temporal sequences using population representations that were robust to variation in sequence interval. These results demonstrate direct neural encoding of temporal sequences in the spontaneous activity of brain tissue and suggest a novel local circuit mechanism that may contribute to diverse forms of short-term memory.A fundamental property of the central nervous system is the ability to encode and retrieve information. In mammals, declarative memory function is typically divided into behavioral tasks that promote short-or long-term storage of items such as names, places and specific temporal sequences 1,2 . While the specific cellular origin of individual long-term declarative memories has remained elusive, a large literature highlights the importance of several critical brain regions, including the prefrontal cortex 3 and the hippocampal formation 4 for encoding short-term, or working, memories. Extracellular unit recordings in these brain areas often display periods of persistent spiking activity at elevated frequencies when animals are required to retain transiently presented sensory information. This "delay-period activity" typically lasts for seconds and is extinguished when the animal initiates a behavioral response to indicate whether it correctly remembered the correct transient stimulus 3,5 . The reduction in persistent spiking during error trials-trials in which the animal made an incorrect behavioral response following the delay period-argues that delay-period activity in those specific neurons reflects activity in neural circuits encoding that short-term memory, rather than a response to the cue stimulus or a motor plan Users may view, print, copy, download and text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

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Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons

Cited by 413 publications

References 33 publications

Function of basal ganglia in tauG-guiding action

Function of basal ganglia in tauG-guiding action

A scaling law derived from optimal dendritic wiring

Mnemonic representations of transient stimuli and temporal sequences in the rodent hippocampus in vitro

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