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.

Network-motif delay differential analysis of brain activity during seizures.

Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions.

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.

A Custom Microcontrolled and Wireless-Operated Chamber for Auditory Fear Conditioning.

Animal behavioral paradigms, such as classical conditioning and operant conditioning, are an important tool to study the neural basis of cognition and behavior. These paradigms involve manipulating sensory stimuli in a way that learning processes are induced under controlled experimental conditions. However, the majority of the commercially available equipment did not offer flexibility to manipulate stimuli. Therefore, the development of most versatile devices would allow the study of more complex cognitive functions. The purpose of this work is to present a low-cost, customized and wireless-operated chamber for animal behavior conditioning, based on the joint operation of two microcontroller modules: Arduino Due and ESP8266-12E. Our results showed that the auditory stimulation system allows setting the carrier frequency in the range of 1 Hz up to more than 100 kHz and the sound stimulus can be modulated in amplitude, also over a wide range of frequencies. Likewise, foot-shock could be precisely manipulated regarding its amplitude (from ∼200 µA to ∼1500 µA) and frequency (up to 20 pulses per second). Finally, adult rats exposed to a protocol of cued fear conditioning in our device showed consistent behavioral response and electrophysiological evoked responses in the midbrain auditory pathway. Furthermore, the device developed in the current study represents an open source alternative to develop customized protocols to study fear memory under conditions of varied sensory stimuli.

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.

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.

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.

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.