Decoding imagined speech with delay differential analysis.

Speech decoding from non-invasive EEG signals can achieve relatively high accuracy (70-80%) for strictly delimited classification tasks, but for more complex tasks non-invasive speech decoding typically yields a 20-50% classification accuracy. However, decoder generalization, or how well algorithms perform objectively across datasets, is complicated by the small size and heterogeneity of existing EEG datasets. Furthermore, the limited availability of open access code hampers a comparison between methods. This study explores the application of a novel non-linear method for signal processing, delay differential analysis (DDA), to speech decoding. We provide a systematic evaluation of its performance on two public imagined speech decoding datasets relative to all publicly available deep learning methods. The results support DDA as a compelling alternative or complementary approach to deep learning methods for speech decoding. DDA is a fast and efficient time-domain open-source method that fits data using only few strong features and does not require extensive preprocessing.

Automated detection of auditory response: non-detection stopping criterion and repeatability studies for multichannel EEG.

An Auditory Steady-State Response (ASSR) is a valuable tool for determining auditory thresholds in individuals who are either unable or unwilling to cooperate with conventional behavioral testing methods. This study proposes a sequential test technique for automatic detection of ASSRs, incorporating a non-detection stopping criterion. The electrophysiological thresholds of a normal hearing volunteer were established using data collected from multichannel EEG signals. The detection probabilities and critical values were obtained via Monte Carlo simulations. Remarkably, application of the non-detection stopping criterion resulted in a 60% reduction in exam time in the absence of a response. These findings clearly demonstrate the significant potential of the sequential test in enhancing the performance of automatic audiometry.

Dealing with correlations in the multichannel EEG using bipolar derivations and Monte Carlo simulations: application to the detection of auditory steady-state responses.

The multichannel objective response detection (MORD) techniques are statistical methods, which use information from more than one electroencephalography (EEG) channel, to infer the presence of evoked potential. However, the correlation level between the channels can lead to a decrease in MORD performance, such as an increase in the false positive (FP) rate and/or a decrease in the detection rate (DR). The present study aims to propose a method to deal with the correlations in the multichannel EEG. The method consists of making an adjustment in the Monte Carlo simulation, considering the information between channels. The MORD techniques with and without the new method were applied to an auditory steady-state response (ASSR) database, composed of the EEG multichannel of eleven volunteers during multifrequency stimulation. The proposed method kept the FP rate at values equal to or less than the significance level of the test and led to an increase of 8.51% in the DR in relation to non-application of the method. Results of this study indicate that the proposed method is an alternative to deal with the effect of the correlation between channels in situations where MORD techniques are applied.

Automatic audiometry using auditory steady-state response and sequential test strategy applied to volunteers with normal hearing.

PURPOSE: In the present study, a new procedure to perform automatic audiometry using multifrequency Auditory Steady-State Response (ASSR) is proposed. METHODS: The automatic audiometry procedure consists of detecting the presence of multifrequency ASSR in real-time using the sequential test strategy and by adjusting the stimulus intensity independently. The ASSR audiometric thresholds of 18 adult volunteers with normal hearing were determined by automatically (four simultaneous frequencies per ear) at modulation frequencies in the 80 Hz range. The exam time and the difference between ASSR thresholds and pure-tone behavioural hearing thresholds were estimated as performance measures. RESULTS: The results showed that automatic audiometry can reduce the number of intensity levels used to obtain the ASSR threshold by up to 58% when compared to audiometry without using the techniques applied in automatic audiometry. In addition, the average of the difference between ASSR thresholds and Pure-Tone Behavioural Hearing thresholds was around 19 dB, which is similar to the results reported in similar studies. CONCLUSIONS: The audiometric procedure proposed in this study is fully automatic, i.e., does not require any human supervision throughout the exam, and is able to significantly reduce the conventional exam time.

Active probing to highlight approaching transitions to ictal states in coupled neural mass models.

The extraction of electrophysiological features that reliably forecast the occurrence of seizures is one of the most challenging goals in epilepsy research. Among possible approaches to tackle this problem is the use of active probing paradigms in which responses to stimuli are used to detect underlying system changes leading up to seizures. This work evaluates the theoretical and mechanistic underpinnings of this strategy using two coupled populations of the well-studied Wendling neural mass model. Different model settings are evaluated, shifting parameters (excitability, slow inhibition, or inter-population coupling gains) from normal towards ictal states while probing stimuli are applied every 2 seconds to the input of either one or both populations. The correlation between the extracted features and the ictogenic parameter shifting indicates if the impending transition to the ictal state may be identified in advance. Results show that not only can the response to the probing stimuli forecast seizures but this is true regardless of the altered ictogenic parameter. That is, similar feature changes are highlighted by probing stimuli responses in advance of the seizure including: increased response variance and lag-1 autocorrelation, decreased skewness, and increased mutual information between the outputs of both model subsets. These changes were mostly restricted to the stimulated population, showing a local effect of this perturbational approach. The transition latencies from normal activity to sustained discharges of spikes were not affected, suggesting that stimuli had no pro-ictal effects. However, stimuli were found to elicit interictal-like spikes just before the transition to the ictal state. Furthermore, the observed feature changes highlighted by probing the neuronal populations may reflect the phenomenon of critical slowing down, where increased recovery times from perturbations may signal the loss of a systems' resilience and are common hallmarks of an impending critical transition. These results provide more evidence that active probing approaches highlight information about underlying system changes involved in ictogenesis and may be able to play a role in assisting seizure forecasting methods which can be incorporated into early-warning systems that ultimately enable closing the loop for targeted seizure-controlling interventions.

A Fully Adapted Headstage With Custom Electrode Arrays Designed for Electrophysiological Experiments.

Electrophysiological recordings lead amongst the techniques that aim to investigate the dynamics of neural activity sampled from large neural ensembles. However, the financial costs associated with the state-of-the-art technology used to manufacture probes and multi-channel recording systems make these experiments virtually inaccessible to small laboratories, especially if located in developing countries. Here, we describe a new method for implanting several tungsten electrode arrays, widely distributed over the brain. Moreover, we designed a headstage system, using the Intan® RHD2000 chipset, associated with a connector (replacing the expensive commercial Omnetics connector), that allows the usage of disposable and inexpensive cranial implants. Our results showed high-quality multichannel recording in freely moving animals (detecting local field, evoked responses and unit activities) and robust mechanical connections ensuring long-term continuous recordings. Our project represents an open source and inexpensive alternative to develop customized extracellular records from multiple brain regions.

Seizure Susceptibility Corrupts Inferior Colliculus Acoustic Integration.

Evidence suggests that the pathophysiology associated with epileptic susceptibility may disturb the functional connectivity of neural circuits and compromise the brain functions, even when seizures are absent. Although memory impairment is a common comorbidity found in patients with epilepsy, it is still unclear whether more caudal structures may play a role in cognitive deficits, particularly in those cases where there is no evidence of hippocampal sclerosis. This work used a genetically selected rat strain for seizure susceptibility (Wistar audiogenic rat, WAR) and distinct behavioral (motor and memory-related tasks) and electrophysiological (inferior colliculus, IC) approaches to access acoustic primary integrative network properties. The IC neural assemblies' response was evaluated by auditory transient (focusing on bottom-up processing) and steady-state evoked response (ASSR, centering on feedforward and feedback forces over neural circuitry). The results show that WAR displayed no disturbance in motor performance or hippocampus-dependent memory tasks. Nonetheless, WAR animals exhibited significative impairment for auditory fear conditioning (AFC) along with no indicative of IC plastic changes between the pre-conditioning and test phases (ASSR coherence analysis). Furthermore, WAR's IC response to transient stimuli presented shorter latency and higher amplitude compared with Wistar; and the ASSR analysis showed similar results for WAR and Wistar animals under subthreshold dose of pentylenetetrazol (pro-convulsive drug) for seizure-induction. Our work demonstrated alterations at WAR IC neural network processing, which may explain the associated disturbance on AFC memory.

Improving the power of objective response detection of evoked responses in noise by using average and product of magnitude-squared coherence of two different signals.

Objective response detection (ORD) techniques such as the magnitude-squared coherence (MSC) are mathematical methods tailored to detect potentials evoked by an external periodic stimulation. The performance of the MSC is directly proportional to the signal-to-noise ratio (SNR) of the recorded signal and the time spent for collecting data. An alternative to increasing the performance of detection techniques without increasing data recording time is to use the information from more than one signal simultaneously. In this context, this work proposes two new detection techniques based on the average and on the product of MSCs of two different signals. The critical values and detection probabilities were obtained theoretically and using a Monte Carlo simulation. The performances of the new detectors were evaluated using synthetic data and electroencephalogram (EEG) signals during photo and auditory stimulation. For the synthetic signals, the two proposed detectors exhibited a higher detection rate when compared to the rate of the traditional MSC technique. When applied to EEG signals, these detectors resulted in an increase of the mean detection rate in relation to MSC for visual and auditory stimulation of at least 25% and 13.21%, respectively. The proposed detectors may be considered as promising tools for clinical applications. Graphical Abstract.

Deep brain stimulation probing performance is enhanced by pairing stimulus with epileptic seizure.

The unpredictability of spontaneous and recurrent seizures significantly impairs the quality of life of patients with epilepsy. Probing neural network excitability with deep brain electrical stimulation (DBS) has shown promising results predicting pathological shifts in brain states. This work presents a proof-of-principal that active electroencephalographic (EEG) probing, as a seizure predictive tool, is enhanced by pairing DBS and the electrographic seizure itself. The ictogenic model used consisted of inducing seizures by continuous intravenous infusion of pentylenetetrazol (PTZ - 2.5 mg/ml/min) while a probing DBS was delivered to the thalamus (TH) or amygdaloid complex to detect changes prior to seizure onset. Cortical electrophysiological recordings were performed before, during, and after PTZ infusion. Thalamic DBS probing, but not amygdaloid, was able to predict seizure onset without any observable proconvulsant effects. However, previously pairing amygdaloid DBS and epileptic polyspike discharges (day-1) elicited distinct preictal cortically recorded evoked response (CRER) (day-2) when compared with control groups that received the same amount of electrical pulses at different moments of the ictogenic progress at day-1. In conclusion, our results have demonstrated that the pairing strategy potentiated the detection of an altered brain state prior to the seizure onset. The EEG probing enhancement method opens many possibilities for both diagnosis and treatment of epilepsy.

Multivariate approach for estimating the local spectral F-test and its application to the EEG during photic stimulation.

BACKGROUND AND OBJECTIVE: The local spectral F-test (SFT) corresponds to a statistical way of assessing whether the spectrum of a signal is flat in the vicinity of a specific frequency. The power of this univariate test (comparing one frequency component  against its neighbours using only one signal) depends on the signal-to-noise ratio, which is fixed in the case of electroencephalogram (EEG) analysis. However, this limitation could be overcome by considering more signals in the analysis. Thus, this work presents an alternative multivariate approach for estimating the local SFT. METHODS: Probabilities of detection and false alarm studies were performed for this new detector using Monte Carlo simulations and theoretically whenever possible. The application was illustrated in recorded EEG data collected during photic stimulation. RESULTS: The results showed that it is worth using more channels if available, since the probability of detecting a response tends to increase with increasing number of signals. In the application to the EEG during photic stimulation, the best results were obtained by using N > 2 signals (around 30% more accurate when compared with the univariate case. The false positive levels were maintained below 5%). CONCLUSION: Consequently, it is conjectured that it is always better to apply the proposed method if more than one EEG signal with the same signal-to-noise ratio (SNR) is available. For the case where the SNRs are different, a guideline has been given to improve the detection.

Home-cage odors spatial cues elicit theta phase/gamma amplitude coupling between olfactory bulb and dorsal hippocampus.

The brain oscillations may play a critical role in synchronizing neuronal assemblies in order to establish appropriate sensory-motor integration. In fact, studies have demonstrated phase-amplitude coupling of distinct oscillatory rhythms during cognitive processes. Here we investigated whether olfacto-hippocampal coupling occurs when mice are detecting familiar odors located in a spatially restricted area of a new context. The spatial olfactory task (SOT) was designed to expose mice to a new environment in which only one quadrant (target) contains odors provided by its own home-cage bedding. As predicted, mice showed a significant higher exploration preference to the target quadrant; which was impaired by olfactory epithelium lesion (ZnSO4). Furthermore, mice were able to discriminate odors from a different cage and avoided the quadrant with predator odor 2,4,5-trimethylthiazoline (TMT), reinforcing the specificity of the SOT. The local field potential (LFP) analysis of non-lesioned mice revealed higher gamma activity (35-100Hz) in the main olfactory bulb (MOB) and a significant theta phase/gamma amplitude coupling between MOB and dorsal hippocampus, only during exploration of home-cage odors (i.e. in the target quadrant). Our results suggest that exploration of familiar odors in a new context involves dynamic coupling between the olfactory bulb and dorsal hippocampus.

Improving the detection of evoked responses to periodic stimulation by using bivariate local spectral F-test - Application to EEG during photic stimulation.

The spectral local F-test has been applied for detecting evoked responses to rhythmic stimulation that are embedded in the ongoing electroencephalogram (EEG). Based on the sampling distribution of a flat spectrum at the neighbourhood of the stimulation frequency, spectral peaks in an EEG signal that are due to the stimulation may be readily assessed. Nevertheless, the performance of the technique is strongly affected by both the signal-to-noise ratio (SNR) of the responses and the number of data segments used in the estimation. The present work aims at both deriving and evaluating a multivariate extension of local F-test by including the EEG collected at a second distinct derivation. The detection rate with this multivariate detector was found to be greater than that using a single channel in case of equal SNR in both signals. Monte Carlo simulation results showed that the probability of detection with this new detector saturates for signal-to-noise ratios above 12 dB and indicated a greater detection rate in practical situations, even when smaller SNR-values are found in the added signal (e.g. 5 dB for 16 neighbouring frequencies used in the estimation). The technique was next applied to the EEG from 12 subjects during intermittent, photic stimulation leading to superior performance in comparison with the univariate local F-test. Since a higher detection rate with the proposed technique is achieved without the need of increasing the number of data segments, it allows evoked responses to be detected faster, once the same detection rate may be accomplished with less segments. This might be useful in clinical practice.

Auditory processing assessment suggests that Wistar audiogenic rat neural networks are prone to entrainment.

Epilepsy is a neurological disease related to the occurrence of pathological oscillatory activity, but the basic physiological mechanisms of seizure remain to be understood. Our working hypothesis is that specific sensory processing circuits may present abnormally enhanced predisposition for coordinated firing in the dysfunctional brain. Such facilitated entrainment could share a similar mechanistic process as those expediting the propagation of epileptiform activity throughout the brain. To test this hypothesis, we employed the Wistar audiogenic rat (WAR) reflex animal model, which is characterized by having seizures triggered reliably by sound. Sound stimulation was modulated in amplitude to produce an auditory steady-state-evoked response (ASSR; -53.71Hz) that covers bottom-up and top-down processing in a time scale compatible with the dynamics of the epileptic condition. Data from inferior colliculus (IC) c-Fos immunohistochemistry and electrographic recordings were gathered for both the control Wistar group and WARs. Under 85-dB SLP auditory stimulation, compared to controls, the WARs presented higher number of Fos-positive cells (at IC and auditory temporal lobe) and a significant increase in ASSR-normalized energy. Similarly, the 110-dB SLP sound stimulation also statistically increased ASSR-normalized energy during ictal and post-ictal periods. However, at the transition from the physiological to pathological state (pre-ictal period), the WAR ASSR analysis demonstrated a decline in normalized energy and a significant increase in circular variance values compared to that of controls. These results indicate an enhanced coordinated firing state for WARs, except immediately before seizure onset (suggesting pre-ictal neuronal desynchronization with external sensory drive). These results suggest a competing myriad of interferences among different networks that after seizure onset converge to a massive oscillatory circuit.

Temporal rearrangement of pre-ictal PTZ induced spike discharges by low frequency electrical stimulation to the amygdaloid complex.

BACKGROUND: Epilepsy is a common neurological disease affecting over 40 million people worldwide. The foremost important challenge of epileptologists has been to control and predict the recurrent and spontaneous seizures of epileptic patients. The application of low frequency electrical stimulation (LFS) in deep brain structures has shown promising results in seizure control. However, the use of LFS as a probing strategy for seizure prediction, thus contributing to a closed loop solution, is still poorly explored. OBJECTIVE: To improve seizure prediction by producing gradually increasing phase-locked pre-ictal electrographical responses, due to the short-term plastic changes in epileptogenic neural networks, thus behaving as a "programmed" surrogate marker. METHODS: Urethane anesthetized rats were divided into 3 groups: the PTZ-noES group was injected with pentylenetetrazole (PTZ 4 mg/ml/min flow rate) i.v. without electrical stimulation (ES); the ES-noPTZ group received ES (0.5 Hz, 0.1 ms pulse width and 0.6 mA) to the amygdaloid complex and the PTZ + ES group received simultaneously i.v. PTZ infusion and ES. After each condition, electrographical parameters and c-Fos expression of regions of interest were evaluated. RESULTS: Although the PTZ + ES group had no evident change in the sustained electrographic seizure onset, duration and/or frequency spectrum; c-Fos labeling showed a different expression pattern when compared to the PTZ-noES and ES-noPTZ. Also, PTZ + ES formed a gradually increasing evoked potential; confirming the strong coupling of reverberant neural networks induced by ES - phase locked to stimuli. CONCLUSION: ES induces a detectable temporal rearrangement of pre-ictal activity, which has suggestive applicability to seizure prediction.

Post-processing of auditory steady-state responses to correct spectral leakage.

Auditory steady-state responses (ASSRs) are electrical manifestations of brain due to high rate sound stimulation. These evoked responses can be used to assess the hearing capabilities of a subject in an objective, automatic fashion. Usually, the detection protocol is accomplished by frequency-domain techniques, such as magnitude-squared coherence, whose estimation is based on the fast Fourier transform (FFT) of several data segments. In practice, the FFT-based spectrum may spread out the energy of a given frequency to its side bins and this escape of energy in the spectrum is called spectral leakage. The distortion of the spectrum due to leakage may severely compromise statistical significance of objective detection. This work presents an offline, a posteriori method for spectral leakage minimization in the frequency-domain analysis of ASSRs using coherent sampling criterion and interpolation in time. The technique was applied to the local field potentials of 10 Wistar rats and the results, together with those from simulated data, indicate that a leakage-free analysis of ASSRs is possible for any dataset if the methods showed in this paper were followed.