ABSTRACT
The mismatch negativity (MMN) component of the human event-related potential (ERP) is frequently interpreted as a sensory prediction-error signal. However, there is ambiguity concerning the neurophysiology underlying hypothetical prediction and prediction-error signalling components, and whether these can be dissociated from overlapping obligatory components of the ERP that are sensitive to physical properties of sounds. In the present study, a hierarchical recurrent neural network (RNN) was fitted to ERP data from 38 subjects. After training the model to reproduce ERP waveforms evoked by 80 dB standard and 70 dB deviant stimuli, it was used to simulate a response to 90 dB deviant stimuli. Internal states of the RNN effectively combined to generate synthetic ERPs, where individual hidden units are loosely analogous to population-level sources. Model behaviour was characterised using principal component analysis of stimulus condition, layer, and individual unit responses. Hidden units were categorised according to their temporal response fields, and statistically significant differences among stimulus conditions were observed for amplitudes of units peaking in the 0-75 ms (P50), 75-125 ms (N1), and 250-400 ms (N3) latency ranges, surprisingly not including the measurement window of MMN. The model demonstrated opposite polarity changes in MMN amplitude produced by falling (70 dB) and rising (90 dB) intensity deviant stimuli, consistent with loudness dependence of sensory ERP components. This modelling study suggests that loudness dependence is a principal driver of intensity MMN, and future studies ought to clarify the distinction between loudness dependence, adaptation and prediction-error signalling.
Subject(s)
Evoked Potentials, Auditory , Evoked Potentials , Humans , Evoked Potentials, Auditory/physiology , Evoked Potentials/physiology , Principal Component Analysis , Neural Networks, Computer , Acoustic Stimulation , ElectroencephalographyABSTRACT
Objective.Understanding neurophysiological changes that accompany transitions between anaesthetized and conscious states is a key objective of anesthesiology and consciousness science. This study aimed to characterize the dynamics of auditory-evoked potential morphology in mice along a continuum of consciousness.Approach.Epidural field potentials were recorded from above the primary auditory cortices of two groups of laboratory mice: urethane-anaesthetized (A,n= 14) and conscious (C,n= 17). Both groups received auditory stimulation in the form of a repeated pure-tone stimulus, before and after receiving 10 mg kg-1i.p. ketamine (AK and CK). Evoked responses were then ordered by ascending sample entropy into AK, A, CK, and C, considered to reflect physiological correlates of awareness. These data were used to train a recurrent neural network (RNN) with an input parameter encoding state. Model outputs were compared with grand-average event-related potential (ERP) waveforms. Subsequently, the state parameter was varied to simulate changes in the ERP that occur during transitions between states, and relationships with dominant peak amplitudes were quantified.Main results.The RNN synthesized output waveforms that were in close agreement with grand-average ERPs for each group (r2> 0.9,p< 0.0001). Varying the input state parameter generated model outputs reflecting changes in ERP morphology predicted to occur between states. Positive peak amplitudes within 25-50 ms, and negative peak amplitudes within 50-75 ms post-stimulus-onset, were found to display a sigmoidal characteristic during the transition from anaesthetized to conscious states. In contrast, negative peak amplitudes within 0-25 ms displayed greater linearity.Significance.This study demonstrates a method for modelling changes in ERP morphology that accompany transitions between states of consciousness using an RNN. In future studies, this approach may be applied to human data to support the clinical use of ERPs to predict transition to consciousness.
Subject(s)
Auditory Cortex , Ketamine , Acoustic Stimulation , Animals , Consciousness/physiology , Electroencephalography/methods , Evoked Potentials, Auditory/physiology , Humans , Mice , Neural Networks, Computer , UrethaneABSTRACT
Neurophysiology research using animals is often necessary to further our understanding of particular areas of medical interest. Human mismatch negativity (MMN) is one such area, where animal models are used to explore underlying mechanisms more invasively and with greater precision than typically possible with human subjects. Computational models can supplement these efforts by providing abstractions that lead to new insights and drive hypotheses. This study aims to establish whether a mouse mismatch response (MMR) analogous to human MMN can be modelled using electric circuit theory. Input to the auditory cortex was modelled as a step function multiplied by a frequency-dependent weighting designed to reflect spectral hearing sensitivity. Afferent sensory responses were modelled using a resistor-capacitor (RC) network, while bidirectional (bottom-up and top-down) responses were modelled using a resistor-inductor-capacitor (RLC) network. Synthetic EEG was combined with RC and RLC circuit currents in response to simulated sequences of auditory input, which comprised duration and frequency oddball paradigms. Two different states of awareness were considered: i) anaesthetized, including only the RC circuit, and ii) conscious, including both RC and RLC circuits. Event-related potential waveforms were obtained from ten simulated experiments for each oddball paradigm and state. These were qualitatively and quantitatively compared with data from a previous in-vivo study, and the model was deemed to successfully replicate low-level features of the mouse central auditory response. Clinical Relevance - Abnormal MMN is believed to reflect pathological changes associated with psychiatric disease. Maximizing the effectiveness of this biomarker will require a greater understanding of the specific cause(s) of these abnormalities. This study presents a computational model that can account for differences between responses to duration and frequency oddball paradigms, which is particularly significant for clinical MMN research.
Subject(s)
Auditory Cortex , Evoked Potentials, Auditory , Acoustic Stimulation , Animals , Auditory Cortex/physiology , Auditory Perception/physiology , Electroencephalography , Evoked Potentials, Auditory/physiology , Humans , MiceABSTRACT
Mismatch negativity (MMN) elicited by decrements in sound pressure level has been asserted as evidence for its dependence upon general deviance detection, while refuting the proposition that it is simply caused by modulating the intrinsic sensory response with different physical properties of sound. However, reports of intensity-decrement MMN are sparse compared with MMN to stimulus frequency or duration changes, and verifying the mechanisms that shape difference waveform morphology is essential for their responsible use as clinical biomarkers. In the present study, open-access EEG data from 40 healthy young adults recorded during an intensity-decrement oddball paradigm was analyzed to establish the effects of transitions between different level stimuli on the auditory evoked response. Standard stimuli were 80 dB and deviant stimuli were 70 dB. Event-related potentials were extracted from standards after standards (sS), deviants after standards (sD), and standards after deviants (dS). Mean amplitude across a recommended measurement window for MMN (125 to 225 ms) was calculated for each ERP waveform. This revealed statistically significant negative amplitude shift elicited by lower-intensity deviant stimuli, as expected, and an opposite direction, positive amplitude shift elicited by higher-intensity standard stimuli that followed lower-intensity deviants, relative to standard stimuli presented consecutively. These findings indicate that intensity-modulation of the auditory response influences cortical activity measured during the latency range of MMN. To what extent the hypothesized deviance detection mechanisms may also contribute is uncertain and remains to be elucidated.
Subject(s)
Auditory Perception/physiology , Evoked Potentials, Auditory/physiology , Reaction Time/physiology , Acoustic Stimulation/methods , Electroencephalography , Healthy Volunteers , Humans , Sound , Young AdultABSTRACT
Long-latency mismatch responses to oddball stimuli have recently been observed from anaesthetised rodents. This electrophysiological activity is viewed through 200 to 700 ms post-stimulus; a window that is typically obstructed from analysis by the response to subsequent stimuli in the auditory paradigm. A novel difference waveform computation using two adjoining evoked responses has enabled visualisation of this activity over a longer window than previously available. In the present study, this technique was retroactively applied to data from 13 urethane-anaesthetised mice. Oddball paradigm waveforms were compared with those of a many-standards control sequence, confirming that oddball stimuli evoked long-latency potentials that did not arise from standard or control stimuli. Statistical tests were performed to identify regions of significant difference. Oddball-induced mismatch responses were found to display significantly greater long-latency potentials than identical stimuli presented in an equal-probability context. As such, it may be concluded that long-latency potentials were evoked by the oddball condition. How this feature of the anaesthetised rodent mismatch response relates to human mismatch negativity is unclear, although it may be tentatively linked to the human P3a component, which emerges downstream from mismatch negativity under certain conditions. These results demonstrate that the time dynamics of mismatch responses from anaesthetised rodents are more extensive than previously considered.
Subject(s)
Evoked Potentials, Auditory , Acoustic Stimulation , Animals , Electroencephalography , Mice , Reaction Time , Urethane/toxicityABSTRACT
Human mismatch negativity (MMN) is modelled in rodents and other non-human species to examine its underlying neurological mechanisms, primarily described in terms of deviance-detection and adaptation. Using the mouse model, we aim to elucidate subtle dependencies between the mismatch response (MMR) and different physical properties of sound. Epidural field potentials were recorded from urethane-anaesthetised and conscious mice during oddball and many-standards control paradigms with stimuli varying in duration, frequency, intensity and inter-stimulus interval. Resulting auditory evoked potentials, classical MMR (oddball - standard), and controlled MMR (oddball - control) waveforms were analysed. Stimulus duration correlated with stimulus-off response peak latency, whereas frequency, intensity and inter-stimulus interval correlated with stimulus-on N1 and P1 (conscious only) peak amplitudes. These relationships were instrumental in shaping classical MMR morphology in both anaesthetised and conscious animals, suggesting these waveforms reflect modification of normal auditory processing by different physical properties of sound. Controlled MMR waveforms appeared to exhibit habituation to auditory stimulation over time, which was equally observed in response to oddball and standard stimuli. These findings are inconsistent with the mechanisms thought to underlie human MMN, which currently do not address differences due to specific physical features of sound. Thus, no evidence was found to objectively support the deviance-detection or adaptation hypotheses of MMN in relation to anaesthetised or conscious mice. These findings highlight the potential risk of mischaracterising difference waveform components that are principally influenced by physical sensitivities and habituation of the auditory system.