Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome.

BACKGROUND: In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. METHODS: AEPs were recorded to simple 100 Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. RESULTS: Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. CONCLUSIONS: To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.

Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome.

Background: In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. Methods: AEPs were recorded to simple 100Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. Results: Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. Conclusions: To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.

Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome.

Background In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is "stationarity" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary. Methods AEPs were recorded to simple 100Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures. Results Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a "neural unreliability" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident. Conclusions To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.

Do we all synch alike? Brain-body-environment interactions in ASD.

Autism Spectrum Disorder (ASD) is characterized by rigidity of routines and restricted interests, and atypical social communication and interaction. Recent evidence for altered synchronization of neuro-oscillatory brain activity with regularities in the environment and of altered peripheral nervous system function in ASD present promising novel directions for studying pathophysiology and its relationship to ASD clinical phenotype. Human cognition and action are significantly influenced by physiological rhythmic processes that are generated by both the central nervous system (CNS) and the autonomic nervous system (ANS). Normally, perception occurs in a dynamic context, where brain oscillations and autonomic signals synchronize with external events to optimally receive temporally predictable rhythmic information, leading to improved performance. The recent findings on the time-sensitive coupling between the brain and the periphery in effective perception and successful social interactions in typically developed highlight studying the interactions within the brain-body-environment triad as a critical direction in the study of ASD. Here we offer a novel perspective of autism as a case where the temporal dynamics of brain-body-environment coupling is impaired. We present evidence from the literature to support the idea that in autism the nervous system fails to operate in an adaptive manner to synchronize with temporally predictable events in the environment to optimize perception and behavior. This framework could potentially lead to novel biomarkers of hallmark deficits in ASD such as cognitive rigidity and altered social interaction.

Looking for consistency in an uncertain world: test-retest reliability of neurophysiological and behavioral readouts in autism.

BACKGROUND: Autism spectrum disorders (ASD) are associated with altered sensory processing and perception. Scalp recordings of electrical brain activity time-locked to sensory events (event-related potentials; ERPs) provide precise information on the time-course of related altered neural activity, and can be used to model the cortical loci of the underlying neural networks. Establishing the test-retest reliability of these sensory brain responses in ASD is critical to their use as biomarkers of neural dysfunction in this population. METHODS: EEG and behavioral data were acquired from 33 children diagnosed with ASD aged 6-9.4 years old, while they performed a child-friendly task at two different time-points, separated by an average of 5.2 months. In two blocked conditions, participants responded to the occurrence of an auditory target that was either preceded or not by repeating visual stimuli. Intraclass correlation coefficients (ICCs) were used to assess test-retest reliability of measures of sensory (auditory and visual) ERPs and performance, for the two experimental conditions. To assess the degree of reliability of the variability of responses within individuals, this analysis was performed on the variance of the measurements, in addition to their means. This yielded a total of 24 measures for which ICCs were calculated. RESULTS: The data yielded significant good ICC values for 10 of the 24 measurements. These spanned across behavioral and ERPs data, experimental conditions, and mean as well as variance measures. Measures of the visual evoked responses accounted for a disproportionately large number of the significant ICCs; follow-up analyses suggested that the contribution of a greater number of trials to the visual compared to the auditory ERP partially accounted for this. CONCLUSIONS: This analysis reveals that sensory ERPs and related behavior can be highly reliable across multiple measurement time-points in ASD. The data further suggest that the inter-trial and inter-participant variability reported in the ASD literature likely represents replicable individual participant neural processing differences. The stability of these neuronal readouts supports their use as biomarkers in clinical and translational studies on ASD. Given the minimum interval between test/retest sessions across our cohort, we also conclude that for the tested age-range of ~ 6 to 9.4 years, these reliability measures are valid for at least a 3-month interval. Limitations related to EEG task demands and study length in the context of a clinical trial are considered.

Oscillatory entrainment mechanisms and anticipatory predictive processes in children with autism spectrum disorder.

Anticipating near-future events is fundamental to adaptive behavior, whereby neural processing of predictable stimuli is significantly facilitated relative to nonpredictable events. Neural oscillations appear to be a key anticipatory mechanism by which processing of upcoming stimuli is modified, and they often entrain to rhythmic environmental sequences. Clinical and anecdotal observations have led to the hypothesis that people with autism spectrum disorder (ASD) may have deficits in generating predictions, and as such, a candidate neural mechanism may be failure to adequately entrain neural activity to repetitive environmental patterns, to facilitate temporal predictions. We tested this hypothesis by interrogating temporal predictions and rhythmic entrainment using behavioral and electrophysiological approaches. We recorded high-density electroencephalography in children with ASD and typically developing (TD) age- and IQ-matched controls, while they reacted to an auditory target as quickly as possible. This auditory event was either preceded by predictive rhythmic visual cues or was not preceded by any cue. Both ASD and control groups presented comparable behavioral facilitation in response to the Cue versus No-Cue condition, challenging the hypothesis that children with ASD have deficits in generating temporal predictions. Analyses of the electrophysiological data, in contrast, revealed significantly reduced neural entrainment to the visual cues and altered anticipatory processes in the ASD group. This was the case despite intact stimulus-evoked visual responses. These results support intact behavioral temporal prediction in response to a cue in ASD, in the face of altered neural entrainment and anticipatory processes.NEW & NOTEWORTHY We examined behavioral and EEG indices of predictive processing in children with ASD to rhythmically predictable stimuli. Although behavioral measures of predictive processing and evoked neural responses were intact in the ASD group, neurophysiological measures of preparatory activity and entrainment were impaired. When sensory events are presented in a predictable temporal pattern, performance and neuronal responses in ASD may be governed more by the occurrence of the events themselves and less by their anticipated timing.

Ripe for solution: Delayed development of multisensory processing in autism and its remediation.

Difficulty integrating inputs from different sensory sources is commonly reported in individuals with Autism Spectrum Disorder (ASD). Accumulating evidence consistently points to altered patterns of behavioral reactions and neural activity when individuals with ASD observe or act upon information arriving through multiple sensory systems. For example, impairments in the integration of seen and heard speech appear to be particularly acute, with obvious implications for interpersonal communication. Here, we explore the literature on multisensory processing in autism with a focus on developmental trajectories. While much remains to be understood, some consistent observations emerge. Broadly, sensory integration deficits are found in children with an ASD whereas these appear to be much ameliorated, or even fully recovered, in older teenagers and adults on the spectrum. This protracted delay in the development of multisensory processing raises the possibility of applying early intervention strategies focused on multisensory integration, to accelerate resolution of these functions. We also consider how dysfunctional cross-sensory oscillatory neural communication may be one key pathway to impaired multisensory processing in ASD.

Learning to classify neural activity from a mouse model of Alzheimer's disease amyloidosis versus controls.

The mechanisms underlying Alzheimer's disease (AD) onset and progression are not yet elucidated. The extent to which alterations in the activity of individual neurons of an AD model are significant, and the phase at which they can be captured, point to the intensity of the pathology and imply the stage at which it can be detected. Using a machine-learning algorithm, we present a successful cell-by-cell classification of intracellularly recorded neurons from the B6C3 APPswe/PS1dE9 AD model, versus wildtypes controls, at both a late stage and at an early stage, when the plaque pathology and behavioral deficits are absent or rare. These results suggest that the deficits present in neuronal networks of both old and young transgenic animals are large enough to be apparent at the level of individual neurons, and that the pathology could be detected in nearly any given sample, even before pathologic signs.

Amyloid-ß disrupts ongoing spontaneous activity in sensory cortex.

UNLABELLED: The effect of Alzheimer's disease pathology on activity of individual neocortical neurons in the intact neural network remains obscure. Ongoing spontaneous activity, which constitutes most of neocortical activity, is the background template on which further evoked-activity is superimposed. We compared in vivo intracellular recordings and local field potentials (LFP) of ongoing activity in the barrel cortex of APP/PS1 transgenic mice and age-matched littermate CONTROLS, following significant amyloid-ß (Aß) accumulation and aggregation. We found that membrane potential dynamics of neurons in Aß-burdened cortex significantly differed from those of nontransgenic CONTROLS: durations of the depolarized state were considerably shorter, and transitions to that state frequently failed. The spiking properties of APP/PS1 neurons showed alterations from those of CONTROLS: both firing patterns and spike shape were changed in the APP/PS1 group. At the population level, LFP recordings indicated reduced coherence within neuronal assemblies of APP/PS1 mice. In addition to the physiological effects, we show that morphology of neurites within the barrel cortex of the APP/PS1 model is altered compared to CONTROLS. These results are consistent with a process where the effect of Aß on spontaneous activity of individual neurons amplifies into a network effect, reducing network integrity and leading to a wide cortical dysfunction.

Amyloid-ß alters ongoing neuronal activity and excitability in the frontal cortex.

The effects of amyloid-ß on the activity and excitability of individual neurons in the early and advanced stages of the pathological progression of Alzheimer's disease remain unknown. We used in vivo intracellular recordings to measure the ongoing and evoked activity of pyramidal neurons in the frontal cortex of APPswe/PS1dE9 transgenic mice and age-matched nontransgenic littermate controls. Evoked excitability was altered in both transgenic groups: neurons in young transgenic mice displayed hypoexcitability, whereas those in older transgenic mice displayed hyperexcitability, suggesting changes in intrinsic electrical properties of the neurons. However, the ongoing activity of neurons in both young and old transgenic groups showed signs of hyperexcitability in the depolarized state of the membrane potential. The membrane potential of neurons in old transgenic mice had an increased tendency to fail to transition to the depolarized state, and the depolarized states had shorter durations on average than did controls. This suggests a combination of both intrinsic electrical and synaptic dysfunctions as mechanisms for activity changes at later stages of the neuropathological progression.

Interaction between amyloid-ß pathology and cortical functional columnar organization.

Amyloid-ß plaques are one of the major neuropathological features in Alzheimer's disease (AD). Plaques are found in the extracellular space of telencephalic structures, and have been shown to disrupt neuronal connectivity. Since the disruption of connectivity may underlie a number of the symptoms of AD, understanding the distribution of plaques in the neuropil in relation to the connectivity pattern of the neuronal network is crucial. We measured the distribution and clustering patterns of plaques in the vibrissae-receptive primary sensory cortex (barrel cortex), in which the cortical columnar structure is anatomically demarcated by boundaries in Layer IV. We found that the plaques are not distributed randomly with respect to the barrel structures in Layer IV; rather, they are more concentrated in the septal areas than in the barrels. This difference was not preserved in the supragranular extensions of the functional columns. When comparing the degree of clustering of plaques between primary sensory cortices, we found that the degree of plaques clustering is significantly higher in somatosensory cortex than in visual cortex, and these differences are preserved in Layers II/III. The degree of areal discontinuity is therefore correlated with the patterns of neuropathological deposits. The discontinuous anatomical structure of this area allows us to make predictions about the functional effects of plaques on specific patterns of computational disruption in the AD brain.