bioRxiv Science⌕ Search

bioRxiv · 10.1101/286369

Weak and equally balanced synaptic inputs to interneurons in the CA1 hippocampus characterize in vivo rhythmic states

Abstract

Brain coding strategies are enabled by the balance of synaptic inputs that individual neurons receive as determined by the networks in which they reside. Inhibitory cell types contribute to brain function in distinct ways but recording from specific, inhibitory cell types during behaviour to determine their contributions is difficult. In particular, the in vivo activities of vasoactive intestinal peptide-expressing interneuron specific 3 (IS3) cells in the hippocampus that only target other inhibitory cells are unknown at present. We perform a massive, computational exploration of possible synaptic inputs to IS3 cells using multi-compartment models and optimized synaptic parameters. We find that asynchronous in vivo-like states that are sensitive to additional theta-timed inputs exist when excitatory and inhibitory synaptic conductances are equally balanced and there are low amounts of correlated inputs. Thus, using a generally applicable computational approach we predict the existence of balanced states in hippocampal circuits during rhythmic activities.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Guet-McCreight, A., Skinner, F. K.. 2018-03-22. Weak and equally balanced synaptic inputs to interneurons in the CA1 hippocampus characterize in vivo rhythmic states. https://doi.org/10.1101/286369

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Human iEEG recordings during audiovisual speech violations support and extend predictive routing models

Rather than constantly reconstructing the world solely through sensory input, predictive processing theories posit that the brain utilizes predictions maintained as internal representations to guide sensory processing. An emerging model, predictive routing, proposes that an interplay between neuronal gamma (40-150 Hz) and alpha-beta (10-30 Hz) rhythms implements a dynamic mechanism for predictive processing. Namely, predictions enhance alpha-beta oscillations that suppress gamma activity during the processing of predicted inputs. While this model is supported by animal studies, its validity has not been fully explored within the human brain. The present study addresses this by leveraging human intracranial EEG (iEEG) recordings across superior temporal and prefrontal/premotor areas of seven presurgical epilepsy patients during an audiovisual speech paradigm. We calculated iEEG power in the theta, alpha-beta, and high gamma bands during simple auditory deviance, multisensory integration, and a condition where an incongruent visual cue (lip movements) clashed with an auditory stimulus (a syllable), creating audiovisual incongruence that can elicit the McGurk illusion. Results revealed increased high-gamma and decreased alpha-beta power in the superior temporal cortex in response to auditory deviance and the McGurk condition, while frontal areas, despite reflecting a similar decrease in alpha-beta power, did not present this high gamma prediction error signal. Instead, the theta band revealed a strong prediction error signal in the McGurk condition, consistent with theories on the role of theta in reorganizing cortical networks. These results both support and extend existing predictive routing models for human-specific forms of predictive processing.

neuroscience↗

A Unified World Model in Human Posterior Parietal Cortex

How does the brain understand the physical world, predict future events, and plan actions? Are these problems solved by a unified world model, as hypothesized by cognitive scientists and artificial intelligence researchers? Posterior parietal cortex has been implicated in all these functions, but whether the same neurons support each of them is unknown. We recorded from the superior parietal lobule (SPL) of two tetraplegic participants implanted with microelectrode arrays. SPL units preferentially engaged by intuitive physics, judging block-tower stability and viewing naturalistic physical events, also predicted whether moving objects would collide hundreds of milliseconds before contact, generalizing between different physical scenarios. These populations also encoded which hand action the participant intended to perform. These findings identify SPL as a substrate for physical world modeling.

neuroscience↗

Cortical long-range dynamics track excitation-inhibition balance across cognitive states and organizational principles

A fundamental question in systems neuroscience is how the brain's excitation-inhibition (E/I) balance shapes the temporal structure of neural activity and whether we can non-invasively recover this relationship from neural scaling properties. We show that MRS-derived E/I balance is expressed in long-range temporal dynamics and constrained by cytoarchitecture. The laminar organisation of inhibitory circuits, spanning agranular to granular cortex, determines how faithfully regional dynamics reflect E/I balance. This neurochemical signature is state-dependent: its relationship with cortical dynamics reverses during task engagement, consistent with traversal of dynamical regimes around a critical point. It extends beyond fMRI to arousal-linked dynamics, indexed by pupil diameter and microsaccades, indicating a global mode of cortical state rather than a regionally isolated property. The imprint of E/I balance on long-range dynamics follows the sensory-association axis at rest, and is reconfigured during task engagement. These findings establish E/I balance as a neurochemical quantity with structured, scalable signatures across the temporal and spatial organization of the human cortex.

neuroscience↗