a-protocol-for-uncovering-neural-mechanisms-neurotherapeutic-effects

A Protocol For Uncovering Neural Mechanisms Of Neurotherapeutic Effects On Electroencephalography Using The Human Neocortical Neurosolver

Electroencephalography (EEG) and electrophysiological methods provide millisecond-resolution biomarkers for central nervous system disorders and are ...

Brown University

How perception of sensory stimuli emerges from brain activity is a fundamental question of neuroscience. To date, two disparate lines of research have examined this question. On one hand, human neuroimaging studies have helped us understand the large-scale brain dynamics of perception. On the other hand, work in animal models (mice, typically) has led to fundamental insight into the micro-scale neural circuits underlying perception. However, translating such fundamental insight from animal models to humans has been challenging. Here, using biophysical modeling, we show that the auditory awareness negativity (AAN), an evoked response associated with perception of target sounds in noise, can be accounted for by synaptic input to the supragranular layers of auditory cortex (AC) that is present when target sounds are heard but absent when they are missed. This additional input likely arises from cortico-cortical feedback and/or non-lemniscal thalamic projections and targets the apical dendrites of layer-V pyramidal neurons (PNs). In turn, this leads to increased local field potential activity, increased spiking activity in layer-V PNs, and the AAN. The results are consistent with current cellular models of conscious processing and help bridge the gap between the macro and micro levels of perception-related brain activity.

Laminar Specificity of the Auditory Perceptual Awareness Negativity: A Biophysical Modeling Study.

How perception of sensory stimuli emerges from brain activity is a fundamental question of neuroscience. To date, two disparate lines of research have examined this question. On one hand, human neuroimaging studies have helped us understand the large-scale brain dynamics of perception. On the other hand, work in animal models (mice, typically) has led to fundamental insight into the micro-scale neural circuits underlying perception. However, translating such fundamental insight from animal models to humans has been challenging. Here, using biophysical modeling, we show that the auditory awareness negativity (AAN), an evoked response associated with perception of target sounds in noise, can be accounted for by synaptic input to the supragranular layers of auditory cortex (AC) that is present when target sounds are heard but absent when they are missed. This additional input likely arises from cortico-cortical feedback and/or non-lemniscal thalamic projections and targets the apical dendrites of layer-5 (L5) pyramidal neurons. In turn, this leads to increased local field potential activity, increased spiking activity in L5 pyramidal neurons, and the AAN. The results are consistent with current cellular models of conscious processing and help bridge the gap between the macro and micro levels of perception-related brain activity.

Laminar specificity of the auditory perceptual awareness negativity: A biophysical modeling study.

HNN-core is a library for circuit and cellular level interpretation of non-invasive human magneto-/electro-encephalography (MEG/EEG) data. It is based on the Human Neocortical Neurosolver (HNN) software (Neymotin et al., 2020), a modeling tool designed to simulate multiscale neural mechanisms generating current dipoles in a localized patch of neocortex. HNN's foundation is a biophysically detailed neural network representing a canonical neocortical column containing populations of pyramidal and inhibitory neurons together with layer-specific exogenous synaptic drive (Figure 1 left). In addition to simulating network-level interactions, HNN produces the intracellular currents in the long apical dendrites of pyramidal cells across the cortical layers known to be responsible for macroscopic current dipole generation.

HNN-core: A Python software for cellular and circuit-level interpretation of human MEG/EEG.

Our understanding of the neural basis of consciousness is mostly restricted to large-scale brain activity patterns as measured by methods such as functional magnetic resonance imaging (fMRI) and magneto/electro-encephalography (M/EEG). In contrast, we lack even basic understanding of circuit-level mechanisms supporting consciousness - particularly in humans - despite the fundamental role that such mechanisms likely play in instantiating larger-scale brain activity patterns supporting conscious states and contents. Here, we review what progress has been made on circuit-level theories of consciousness (e.g., apical amplification theory, dendritic integration theory) and argue that such theories can be tested in humans using recently developed, state-of-the-art methods. Doing so will further facilitate translation of consciousness science into clinical settings and strengthen the bridge between circuit- and network-level theories of consciousness.

Testing circuit-level theories of consciousness in humans.

The mismatch negativity, or MMN, is a ubiquitous evoked brain response elicited by any discriminable change of an otherwise regular stimulus sequence. Despite its potential clinical relevance - the MMN is known to be affected by brain state, lesions, and neurologic/psychiatric disorders - and a growing body of animal work, the underlying neurophysiology of the MMN is not well understood. This hinders translation of circuit-level animal findings and mitigates the utility of the MMN as a neurologic/psychiatric biomarker. Here, we used biophysical modeling to examine the neurophysiological basis of the MMN as measured in a canonical auditory oddball paradigm with frequency deviants (i.e., tones whose frequency was shifted slightly with respect to standard tones). The response to standards was successfully modeled by a typical feedforward-followed-by-feedback input sequence. The response to deviants required additional, prolonged input to supragranular layers, consistent with input from the non-lemniscal thalamus. This additional input resulted in downward-going pyramidal-neuron currents in both layer 2/3 (via indirect somatic inhibition) , critically, layer 5 (via direct apical excitation), which together generated the MMN. The results suggest that current circuit-level models of MMN generation derived from animal models are incomplete, and that further work is required to characterize the underlying neurophysiology of the MMN.

Neurophysiology of mismatch negativity generation: a biophysical modeling study.

Electroencephalography (EEG) and electrophysiology methods provide millisecond resolution biomarkers for central nervous system disorders and are used to assess treatment-related effects. However, lack of understanding about the neural mechanisms generating such biomarkers impedes the development of diagnostics and therapeutics based on these signals. The Human Neocortical Neurosolver (HNN) is an open-source biophysical modeling software that connects localized EEG biomarkers to their multi-scale neural generators. This protocol demonstrates a hypothesis-driven workflow using HNN to test possible neural mechanisms of neurotherapy-induced EEG biomarkers by optimizing parameters to achieve a fit between simulated and empirical current source waveforms. Corresponding multi-scale cell- and circuit-level activity can then be visualized and quantified, providing validation targets for model predictions in follow up empirical studies. An example is provided which shows how to examine the generating mechanisms of the early event-related potential (ERP) components of an auditory evoked response (P1, N1 and P2) and to assess changes following neural circuit modification due to neurotherapeutic administration. This protocol demonstration enables scientists to design simulation experiments to develop testable predictions on how EEG biomarkers reflect neural circuit mechanisms of example therapeutics. A similar protocol can be applied to study disease mechanisms or other therapies.

Article	Year
Laminar Specificity of the Auditory Perceptual Awareness Negativity: A Biophysical Modeling Study. bioRxiv : the preprint server for biology\| PubMed ID: 36945469	2023
Laminar specificity of the auditory perceptual awareness negativity: A biophysical modeling study. PLoS computational biology\| PubMed ID: 37384802	2023
HNN-core: A Python software for cellular and circuit-level interpretation of human MEG/EEG. Journal of open source software\| PubMed ID: 38939123	2023
Testing circuit-level theories of consciousness in humans. Trends in cognitive sciences\| PubMed ID: 40976753	2026
Neurophysiology of mismatch negativity generation: a biophysical modeling study. bioRxiv : the preprint server for biology\| PubMed ID: 41279217	2025
Uncovering putative neural mechanisms of neurotherapeutic impacts on EEG using the Human Neocortical Neurosolver. bioRxiv : the preprint server for biology\| PubMed ID: 42039506	2026

Carolina Fernandez Pujol

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