"Neural Noise" in Auditory Responses in Young Autistic and Neurotypical Children

Elevated "neural noise" has been advanced as an explanation of autism and autistic sensory experiences. However, functional neuroimaging measures of neural noise may be vulnerable to contamination by recording noise. This study explored variability of electrophysiological responses to tones of different intensities in 127 autistic and 79 typically-developing children aged 2-5 years old. A rigorous data processing pipeline, including advanced visualizations of different signal sources that were maximally independent across different time lags, was used to identify and eliminate putative recording noise. Inter-trial variability was measured using median absolute deviations (MADs) of EEG amplitudes across trials and inter-trial phase coherence (ITPC). ITPC was elevated in autism in the 50 and 60 dB intensity conditions, suggesting diminished (rather than elevated) neural noise in autism, although reduced ITPC to soft 50 dB sounds was associated with increased loudness discomfort. Autistic and non-autistic participants did not differ in MADs, and indeed, the vast majority of the statistical tests examined in this study yielded no significant effects. These results appear inconsistent with the neural noise account.

Associations between age-related differences in occipital alpha power and the broadband parameters of the EEG power spectrum: A cross-sectional cohort study

In adulthood, neurological structure and function are often affected by aging, with negative implications for daily life as well as laboratory-based tasks. Some of these changes include decreased efficiency modulating cortical activity and lower signal-to-noise ratios in neural processing (as inferred from surface electroencephalography). To better understand mechanisms influencing age-related changes in cortical activity, we explored the effects of aging on narrow-band alpha power (7.5-12.5 Hz) and broadband/aperiodic components that span a wider range (1.5-30.5 Hz) over the occipital region during eyes-open and eyes-closed wakeful rest in 19 healthy young adults (18-35 years) and 21 community-dwelling older adults (59+ years). Older adults exhibited a smaller change in alpha power across conditions compared to younger adults. Older adults also showed flatter aperiodic slopes in both conditions. These changes in narrow-band alpha are consistent with previous work and suggest that older adults may have a reduced ability to modulate state-specific activity. Differences in the aperiodic slope suggest age-related changes in the signal-noise-ratio in cortical oscillations. However, the relationship between narrow-band alpha modulation and the aperiodic slope was unclear, warranting further investigation into how these variables relate to each other in the aging process. In summary, aging is associated with a broadband flattening of the EEG power spectrum and reduced state-specific modulation of narrow-band alpha power, but these changes appear to be (at least partially) independent of each other. The present findings suggest that separate mechanisms may underlie age-related differences in aperiodic power and narrow-band oscillations.

Increased Aperiodic Neural Activity During Sleep in Major Depressive Disorder

Background

In major depressive disorder (MDD), patients often express subjective sleep complaints, while polysomnographic studies report only subtle alterations of the electroencephalographic signal. We hypothesize that differentiating the signal into its oscillatory and aperiodic components may bring new insights into our understanding of sleep abnormalities in MDD. Specifically, we investigated aperiodic neural activity during sleep and its relationships with sleep architecture, depression severity, and responsivity to antidepressant treatment.

Methods

Polysomnography was recorded in 38 patients with MDD (in unmedicated and 7-day-medicated states) and 38 age-matched healthy control subjects (N= 76). The aperiodic power component was calculated using irregularly resampled auto-spectral analysis. Depression severity was assessed with the Hamilton Depression Rating Scale. We replicated the analysis using 2 independently collected datasets of medicated patients and control subjects (N = 60 and N = 80, respectively).

Results

Unmedicated patients showed flatter aperiodic slopes compared with control subjects during non-rapid eye movement (non-REM) stage 2 sleep (p = .009). Medicated patients showed flatter aperiodic slopes compared with their earlier unmedicated state (p values < .001) and control subjects during all sleep stages (p values < .03). In medicated patients, flatter aperiodic slopes during non-REM sleep were linked to the higher proportion of N1, lower proportion of REM, delayed onset of N3 and REM, and shorter total sleep time.

Conclusions

Flatter slopes of aperiodic electroencephalographic power may reflect noisier neural activity due to increased excitation-to-inhibition balance, representing a new disease-relevant feature of sleep in MDD.

Aperiodic neural activity reflects metacontrol

Higher-level cognitive functions are mediated via complex oscillatory activity patterns and its analysis is dominating cognitive neuroscience research. However, besides oscillatory (period) activity, also aperiodic activity constitutes neural dynamics, but its relevance for higher-level cognitive functions is only beginning to be understood. The present study examined whether the broadband EEG aperiodic activity reflects principles of metacontrol. Metacontrol conceptualizes whether it is more useful to engage in more flexible processing of incoming information or to shield cognitive processes from incoming information (persistence-heavy processing). We examined EEG and behavioral data from a sample of n = 191 healthy participants performing a Simon Go/NoGo task that can be assumed to induce different metacontrol states (persistence-biased vs. flexibility-biased). Aperiodic activity was estimated using the FOOOF toolbox in the EEG power spectrum. There was a higher aperiodic exponent and offset in NoGo trials compared with Go trials, in incongruent (Go) trials compared with congruent (Go) trials. Thus, aperiodic activity increases during persistence-heavy processing, but decreases during flexibility-heavy processing. These findings link aperiodic features of the EEG signal and concepts describing the dynamics of how cognitive control modes are applied. Therefore, the study substantially extends the importance of aperiodic activity in understanding cognitive functions.

Eye stabilization

This chapter summarizes how visual feedback could be used to stabilize the line of sight and optimize vision during attempted fixation of a stationary target. Quantitative features of oculomotor noise that causes drifts of the eye away from the target are analyzed. The sources of such noise, including the ripples in eye position due to muscle fiber twitches, and drifts of the eye away from the visual target due to vestibular imbalance, are examined. Evidence for a promptly responding stabilization system, distinct from optokinetic or pursuit eye movements is reviewed. Smooth eye movements that negate drifts of the eyes, which are discussed here, are distinct from microsaccades, which are discussed in chapter "Behavior of the saccadic system: Metrics of timing and accuracy" by Robinson.

Neural noise and cortical inhibition in schizophrenia

BACKGROUND

Neural information processing is subject to noise and this leads to variability in neural firing and behavior. Schizophrenia has been associated with both more variable motor control and impaired cortical inhibition, which is crucial for excitatory/inhibitory balance in neural commands.

HYPOTHESIS

In this study, we hypothesized that impaired intracortical inhibition in motor cortex would contribute to task-related motor noise in schizophrenia.

METHODS

We measured variability of force and of electromyographic (EMG) activity in upper limb and hand muscles during a visuomotor grip force-tracking paradigm in patients with schizophrenia (N = 25), in unaffected siblings (N = 17) and in healthy control participants (N = 25). Task-dependent primary motor cortex (M1) excitability and inhibition were assessed using transcranial magnetic stimulation (TMS).

RESULTS

During force maintenance patients with schizophrenia showed increased variability in force and EMG, despite similar mean force and EMG magnitudes. Compared to healthy controls, patients with schizophrenia also showed increased M1 excitability and reduced cortical inhibition during grip-force tracking. EMG variability and force variability correlated negatively to cortical inhibition in patients with schizophrenia. EMG variability also correlated positively to negative symptoms. Siblings had similar variability and cortical inhibition compared to controls. Increased EMG and force variability indicate enhanced motor noise in schizophrenia, which relates to reduced motor cortex inhibition.

CONCLUSION

The findings suggest that excessive motor noise in schizophrenia may arise from an imbalance of M1 excitation/inhibition of GABAergic origin. Thus, higher motor noise may provide a useful marker of impaired cortical inhibition in schizophrenia.

Augmenting Global Coherence in EEG Signals with Binaural or Monaural Noises

Internal stochastic resonance (internal SR) is a phenomenon of non-linear systems in which the addition of a non-zero level of noise produces an enhancement in the coherence between two or more signals. In a previous study, we found that the simultaneous administration of multisensory visual and auditory noise augments global coherence in electroencephalographic (EEG) signals via this phenomenon. Here, we examined whether such global coherence can also be augmented with at least one noisy acoustic source. We performed experiments on healthy subjects and applied the following binaural and monaural noise-stimulation protocols. First, we administered to the left ear Gaussian noise of fixed intensity, while we delivered to the right ear a second Gaussian noise of variable intensity levels (binaural protocol). Second, we applied the Gaussian noise of the same variable intensity levels but only to one ear (monaural protocol). We performed a permutation test analysis, finding that during both noise protocols there was a significant enhancement in the global coherence in EEG signals via the occurrence of internal SR within central pathways of the auditory system.

The Modulation of Neural Noise Underlies the Effectiveness of Methylphenidate Treatment in Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Various lines of research suggest that the stability of neural processes is low in attention-deficit/hyperactivity disorder (ADHD). Considering overarching neural principles, this lack of stability relates to increased levels of neural noise. However, no study has directly examined neural noise in ADHD. Likewise, it is unknown whether the modulation of neural noise reflects a mechanistic link as to why methylphenidate (MPH) is effective in treating impulsivity in ADHD.

METHODS

We compared neural noise between 29 juvenile patients with ADHD and 32 healthy control subjects and examined the effects of MPH. We examined 1/f neural noise of electroencephalogram data collected while participants performed a response inhibition (Go/NoGo) task.

RESULTS

Specific during NoGo trials, children with ADHD showed more neural noise than healthy control subjects. This was especially the case with regard to the theta frequency band, which is very closely related to cognitive control. MPH treatment reduced neural noise in ADHD to the level of healthy control subjects. Correlational analyses showed a direct relationship between decreases in neural noise and increases in behavioral performance. Mechanistically, this can be explained by the MPH-induced increase in dopaminergic neurotransmission that enhances the signal-to-noise ratio in neural networks and thus reduces neural noise.

CONCLUSIONS

This study is the first to demonstrate increased (pink) neural noise in patients with ADHD and its reduction through MPH treatment. The study reveals an important mechanistic link as to why MPH is effective in treating impulsivity in ADHD.

1/f neural noise and electrophysiological indices of contextual prediction in aging

Prediction of upcoming words during reading has been suggested to enhance the efficiency of discourse processing. Emerging models have postulated that predictive mechanisms require synchronous firing of neural networks, but to date, this relationship has been investigated primarily through oscillatory activity in narrow frequency bands. A recently-developed measure proposed to reflect broadband neural activity - and thereby synchronous neuronal firing - is 1/f neural noise extracted from EEG spectral power. Previous research has indicated that this measure of 1/f neural noise changes across the lifespan, and these neural changes predict age-related behavioral impairments in visual working memory. Using a cross-sectional sample of young and older adults, we examined age-related changes in 1/f neural noise and whether this measure predicted ERP correlates of successful lexical prediction during discourse comprehension. 1/f neural noise across two different language tasks revealed high within-subject correlations, indicating that this measure can provide a reliable index of individualized patterns of neural activation. In addition to age, 1/f noise was a significant predictor of N400 effects of successful lexical prediction; however, noise did not mediate age-related declines in other ERP effects. We discuss broader implications of these findings for theories of predictive processing, as well as potential applications of 1/f noise across research populations.

Theoretical connections between mathematical neuronal models corresponding to different expressions of noise

Identifying the right tools to express the stochastic aspects of neural activity has proven to be one of the biggest challenges in computational neuroscience. Even if there is no definitive answer to this issue, the most common procedure to express this randomness is the use of stochastic models. In accordance with the origin of variability, the sources of randomness are classified as intrinsic or extrinsic and give rise to distinct mathematical frameworks to track down the dynamics of the cell. While the external variability is generally treated by the use of a Wiener process in models such as the Integrate-and-Fire model, the internal variability is mostly expressed via a random firing process. In this paper, we investigate how those distinct expressions of variability can be related. To do so, we examine the probability density functions to the corresponding stochastic models and investigate in what way they can be mapped one to another via integral transforms. Our theoretical findings offer a new insight view into the particular categories of variability and it confirms that, despite their contrasting nature, the mathematical formalization of internal and external variability is strikingly similar.

The psychosis-like effects of Δ(9)-tetrahydrocannabinol are associated with increased cortical noise in healthy humans

BACKGROUND

Drugs that induce psychosis may do so by increasing the level of task-irrelevant random neural activity or neural noise. Increased levels of neural noise have been demonstrated in psychotic disorders. We tested the hypothesis that neural noise could also be involved in the psychotomimetic effects of delta-9-tetrahydrocannabinol (Δ(9)-THC), the principal active constituent of cannabis.

METHODS

Neural noise was indexed by measuring the level of randomness in the electroencephalogram during the prestimulus baseline period of an oddball task using Lempel-Ziv complexity, a nonlinear measure of signal randomness. The acute, dose-related effects of Δ(9)-THC on Lempel-Ziv complexity and signal power were studied in humans (n = 24) who completed 3 test days during which they received intravenous Δ(9)-THC (placebo, .015 and .03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design.

RESULTS

Δ(9)-THC increased neural noise in a dose-related manner. Furthermore, there was a strong positive relationship between neural noise and the psychosis-like positive and disorganization symptoms induced by Δ(9)-THC, which was independent of total signal power. Instead, there was no relationship between noise and negative-like symptoms. In addition, Δ(9)-THC reduced total signal power during both active drug conditions compared with placebo, but no relationship was detected between signal power and psychosis-like symptoms.

CONCLUSIONS

At doses that produced psychosis-like effects, Δ(9)-THC increased neural noise in humans in a dose-dependent manner. Furthermore, increases in neural noise were related with increases in Δ(9)-THC-induced psychosis-like symptoms but not negative-like symptoms. These findings suggest that increases in neural noise may contribute to the psychotomimetic effects of Δ(9)-THC.

Low-contrast response deficits and increased neural noise in children with autism spectrum disorder

A battery of short-duration neurophysiological tests were designed and implemented using visual evoked potentials (VEPs) to examine specific neural mechanisms in children with and without autism spectrum disorder (ASD). Contrast-sweep conditions (bright or dark isolated-checks) were used to elicit steady-state VEPs to examine the integrity of ON/OFF pathways. Children with ASD displayed deficits in low-contrast responses at the stimulus frequency of 12.5 Hz, notably under conditions that emphasized activity in the magnocellular pathway. Signal-to-noise ratios were weaker in the ASD group, particularly for the OFF pathway. There were no group differences in the amplitude of responses. In addition, the ASD group displayed significantly higher levels of neural noise than controls. For the response at the stimulus frequency, the ASD group produced a relatively constant level of noise across the contrast range tested, with higher levels than controls at low contrasts and approximately equal levels of noise at moderate to high contrasts.