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A cortico-hippocampal learning rule shapes inhibitory microcircuit activity to enhance hippocampal information flow.

ABSTRACT: How does coordinated activity between distinct brain regions implement a set of learning rules to sculpt information processing in a given neural circuit? Using interneuron cell-type-specific optical activation and pharmacogenetic silencing in vitro, we show that temporally precise pairing of direct entorhinal perforant path (PP) and hippocampal Schaffer collateral (SC) inputs to CA1 pyramidal cells selectively suppresses SC-associated perisomatic inhibition from cholecystokinin (CCK)-expressing interneurons. The CCK interneurons provide a surprisingly strong feedforward inhibitory drive to effectively control the coincident excitation of CA1 pyramidal neurons by convergent inputs. Thus, in-phase cortico-hippocampal activity provides a powerful heterosynaptic learning rule for long-term gating of information flow through the hippocampal excitatory macrocircuit by the silencing of the CCK inhibitory microcircuit.

SUBMITTER: Basu J

PROVIDER: S-EPMC3836574 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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A cortico-hippocampal learning rule shapes inhibitory microcircuit activity to enhance hippocampal information flow.

Basu Jayeeta J Srinivas Kalyan V KV Cheung Stephanie K SK Taniguchi Hiroki H Huang Z Josh ZJ Siegelbaum Steven A SA

Neuron 20130901 6

How does coordinated activity between distinct brain regions implement a set of learning rules to sculpt information processing in a given neural circuit? Using interneuron cell-type-specific optical activation and pharmacogenetic silencing in vitro, we show that temporally precise pairing of direct entorhinal perforant path (PP) and hippocampal Schaffer collateral (SC) inputs to CA1 pyramidal cells selectively suppresses SC-associated perisomatic inhibition from cholecystokinin (CCK)-expressing ...[more]

PMID: 24050406

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Project description:The impact of a given neuronal pathway depends on the number of synapses it makes with its postsynaptic target, the strength of each individual synapse, and the integrative properties of the postsynaptic dendrites. Here we explore the cellular and synaptic mechanisms responsible for the differential excitatory drive from the entorhinal cortical pathway onto mouse CA2 compared with CA1 pyramidal neurons (PNs). Although both types of neurons receive direct input from entorhinal cortex onto their distal dendrites, these inputs produce a 5- to 6-fold larger EPSP at the soma of CA2 compared with CA1 PNs, which is sufficient to drive action potential output from CA2 but not CA1. Experimental and computational approaches reveal that dendritic propagation is more efficient in CA2 than CA1 as a result of differences in dendritic morphology and dendritic expression of the hyperpolarization-activated cation current (Ih). Furthermore, there are three times as many cortical inputs onto CA2 compared with CA1 PN distal dendrites. Using a computational model, we demonstrate that the differences in dendritic properties of CA2 compared with CA1 PNs are necessary to enable the CA2 PNs to generate their characteristically large EPSPs in response to their cortical inputs; in contrast, CA1 dendritic properties limit the size of the EPSPs they generate, even to a similar number of cortical inputs. Thus, the matching of dendritic integrative properties with the density of innervation is crucial for the differential processing of information from the direct cortical inputs by CA2 compared with CA1 PNs.SIGNIFICANCE STATEMENT Recent discoveries have shown that the long-neglected hippocampal CA2 region has distinct synaptic properties and plays a prominent role in social memory and schizophrenia. This study addresses the puzzling finding that the direct entorhinal cortical inputs to hippocampus, which target the very distal pyramidal neuron dendrites, provide an unusually strong excitatory drive at the soma of CA2 pyramidal neurons, with EPSPs that are 5-6 times larger than those in CA1 pyramidal neurons. We here elucidate synaptic and dendritic mechanisms that account quantitatively for the marked difference in EPSP size. Our findings further demonstrate the general importance of fine-tuning the integrative properties of neuronal dendrites to their density of synaptic innervation.

Project description:Most of the mammalian neocortex is comprised of a highly similar anatomical structure, consisting of a granular cell layer between superficial and deep layers. Even so, different cortical areas process different information. Taken together, this suggests that cortex features a canonical functional microcircuit that supports region-specific information processing. For example, the primate primary visual cortex (V1) combines the two eyes' signals, extracts stimulus orientation, and integrates contextual information such as visual stimulation history. These processes co-occur during the same laminar stimulation sequence that is triggered by the onset of visual stimuli. Yet, we still know little regarding the laminar processing differences that are specific to each of these types of stimulus information. Univariate analysis techniques have provided great insight by examining one electrode at a time or by studying average responses across multiple electrodes. Here we focus on multivariate statistics to examine response patterns across electrodes instead. Specifically, we applied multivariate pattern analysis (MVPA) to linear multielectrode array recordings of laminar spiking responses to decode information regarding the eye-of-origin, stimulus orientation, and stimulus repetition. MVPA differs from conventional univariate approaches in that it examines patterns of neural activity across simultaneously recorded electrode sites. We were curious whether this added dimensionality could reveal neural processes on the population level that are challenging to detect when measuring brain activity without the context of neighboring recording sites. We found that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1. Conversely, orientation information was transient and equally pronounced along all layers. More importantly, using time-resolved MVPA, we were able to evaluate laminar response properties beyond those yielded by univariate analyses. Specifically, we performed a time generalization analysis by training a classifier at one point of the neural response and testing its performance throughout the remaining period of stimulation. Using this technique, we demonstrate repeating (reverberating) patterns of neural activity that have not previously been observed using standard univariate approaches.

Dataset Information

A cortico-hippocampal learning rule shapes inhibitory microcircuit activity to enhance hippocampal information flow.

Publications

A cortico-hippocampal learning rule shapes inhibitory microcircuit activity to enhance hippocampal information flow.

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