Cognitive functions of intracellular mechanisms for contextual amplification

Phillips, William A.

doi:10.1016/j.bandc.2015.09.005

Cited by 45 publications

(94 citation statements)

References 152 publications

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“…However, fast 2D and 3D imaging of large spine assemblies and spiny dendritic segments in awake, running, and behaving animals has remained an important challenge because locomotion can more than double firing rate in most neurons (Niell and Stryker, 2010, Fu et al., 2014). Moreover, the majority of the top-down and bottom-up input integration occurs in complex, distant apical and basal dendritic segments separated by distances of several hundred micrometers in 3D (Schiller et al., 2000, Magee and Johnston, 2005, Larkum et al., 2009, Smith et al., 2013, Phillips, 2015). The maximal, over 1,000 μm z-scanning range of AO microscopy (Katona et al., 2012), which was limited during in vivo measurements with GECIs to about 650 μm by the maximal power of the currently available lasers, already permitted the simultaneous measurement of these apical and basal dendritic segments of layer II/III neurons and dendritic segments of layer V neurons in a range of over 500 μm during running periods, or in different behavioral experiments (Harvey et al., 2012, Hangya et al., 2015) where motion-induced fluorescence transients had similar amplitude and kinetics as behavior-related Ca 2+ transients without motion compensation.…”

Section: Discussionmentioning

confidence: 99%

Fast 3D Imaging of Spine, Dendritic, and Neuronal Assemblies in Behaving Animals

Szalay

Judák

Katona

et al. 2016

Neuron

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SummaryUnderstanding neural computation requires methods such as 3D acousto-optical (AO) scanning that can simultaneously read out neural activity on both the somatic and dendritic scales. AO point scanning can increase measurement speed and signal-to-noise ratio (SNR) by several orders of magnitude, but high optical resolution requires long point-to-point switching time, which limits imaging capability. Here we present a novel technology, 3D DRIFT AO scanning, which can extend each scanning point to small 3D lines, surfaces, or volume elements for flexible and fast imaging of complex structures simultaneously in multiple locations. Our method was demonstrated by fast 3D recording of over 150 dendritic spines with 3D lines, over 100 somata with squares and cubes, or multiple spiny dendritic segments with surface and volume elements, including in behaving animals. Finally, a 4-fold improvement in total excitation efficiency resulted in about 500 × 500 × 650 μm scanning volume with genetically encoded calcium indicators (GECIs).

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Section: Discussionmentioning

confidence: 99%

Fast 3D Imaging of Spine, Dendritic, and Neuronal Assemblies in Behaving Animals

Szalay

Judák

Katona

et al. 2016

Neuron

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“…We consider this an acceptable restriction for some purposes in neuroscience as it seems to map well to the properties of cortical neurons; for example, the pyramidal neurons of the neocortex keep exactly two classes of inputs separate via their apical and basal dendrites (see [17,38,39] and references therein). In addition, as long as one is only interested in the computations performed by a neuron based on its own history and all its inputs considered together as one (vector-valued) input variable, this framework is sufficient (see, for example, the treatment of this case in the theoretical study presented in [17]).…”

Section: Which Definition Of Synergistic Mutual Information To Use?mentioning

confidence: 99%

Quantifying Information Modification in Developing Neural Networks via Partial Information Decomposition

Wibral

Finn²,

Wollstadt³

et al. 2017

Entropy

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Information processing performed by any system can be conceptually decomposed into the transfer, storage and modification of information-an idea dating all the way back to the work of Alan Turing. However, formal information theoretic definitions until very recently were only available for information transfer and storage, not for modification. This has changed with the extension of Shannon information theory via the decomposition of the mutual information between inputs to and the output of a process into unique, shared and synergistic contributions from the inputs, called a partial information decomposition (PID). The synergistic contribution in particular has been identified as the basis for a definition of information modification. We here review the requirements for a functional definition of information modification in neuroscience, and apply a recently proposed measure of information modification to investigate the developmental trajectory of information modification in a culture of neurons vitro, using partial information decomposition. We found that modification rose with maturation, but ultimately collapsed when redundant information among neurons took over. This indicates that this particular developing neural system initially developed intricate processing capabilities, but ultimately displayed information processing that was highly similar across neurons, possibly due to a lack of external inputs. We close by pointing out the enormous promise PID and the analysis of information modification hold for the understanding of neural systems.

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“…We have described how bursting in axon inputs to the distal segment of apical dendrites of layer 2/3 pyramidal neurons could increase the tonic level of voltage at the soma so that only a small increase in current from a basal dendrite is required to produce a discharge into the axon This amplification effect at the soma resulting from facilitating basal dendritic input has been recently described as the Apical Amplification (AA) hypothesis by Phillips (2017). The dendritic tuft apparently represents a separate segment of the apical dendrite that functions as a subthreshold integrator of tuft inputs which has an augmenting effect on synaptic inputs located on basal dendrites.…”

Section: Two Tuning Neuronsmentioning

confidence: 99%

Neuroelectric Tuning of Cortical Oscillations by Apical Dendrites in Loop Circuits

LaBerge

Kasevich

2017

Front. Syst. Neurosci.

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Bundles of relatively long apical dendrites dominate the neurons that make up the thickness of the cerebral cortex. It is proposed that a major function of the apical dendrite is to produce sustained oscillations at a specific frequency that can serve as a common timing unit for the processing of information in circuits connected to that apical dendrite. Many layer 5 and 6 pyramidal neurons are connected to thalamic neurons in loop circuits. A model of the apical dendrites of these pyramidal neurons has been used to simulate the electric activity of the apical dendrite. The results of that simulation demonstrated that subthreshold electric pulses in these apical dendrites can be tuned to specific frequencies and also can be fine-tuned to narrow bandwidths of less than one Hertz (1 Hz). Synchronous pulse outputs from the circuit loops containing apical dendrites can tune subthreshold membrane oscillations of neurons they contact. When the pulse outputs are finely tuned, they function as a local “clock,” which enables the contacted neurons to synchronously communicate with each other. Thus, a shared tuning frequency can select neurons for membership in a circuit. Unlike layer 6 apical dendrites, layer 5 apical dendrites can produce burst firing in many of their neurons, which increases the amplitude of signals in the neurons they contact. This difference in amplitude of signals serves as basis of selecting a sub-circuit for specialized processing (e.g., sustained attention) within the typically larger layer 6-based circuit. After examining the sustaining of oscillations in loop circuits and the processing of spikes in network circuits, we propose that cortical functioning can be globally viewed as two systems: a loop system and a network system. The loop system oscillations influence the network system’s timing and amplitude of pulse signals, both of which can select circuits that are momentarily dominant in cortical activity.

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Cognitive functions of intracellular mechanisms for contextual amplification

Cited by 45 publications

References 152 publications

Fast 3D Imaging of Spine, Dendritic, and Neuronal Assemblies in Behaving Animals

Fast 3D Imaging of Spine, Dendritic, and Neuronal Assemblies in Behaving Animals

Quantifying Information Modification in Developing Neural Networks via Partial Information Decomposition

Neuroelectric Tuning of Cortical Oscillations by Apical Dendrites in Loop Circuits

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