Post-stimulus Time Research Articles

Mutual oligosynaptic inhibition of group Ia afferents between the anterior and posterior parts of the deltoid in humans.

The anterior (DA) and posterior parts of the deltoid (DP) show alternating contraction during shoulder flexion and extension movements. It is expected that an inhibitory spinal reflex between the DA and DP exists. In this study, spinal reflexes between the DA and DP were examined in healthy human subjects using post-stimulus time histogram (PSTH) and electromyogram averaging (EMG-A). Electrical conditioning stimulation was delivered to the axillary nerve branch that innervates the DA (DA nerve) and DP (DP nerve) with the intensity below the motor threshold. In the PSTH study, the stimulation to the DA and DP nerves inhibited (decrease in the firing probability) 31 of 54 DA motor units and 31 of 51 DP motor units. The inhibition was not provoked by cutaneous stimulation. The central synaptic delay of the inhibition between the DA and DP nerves was 1.5 ± 0.5ms and 1.4 ± 0.4ms (mean ± SD) longer than those of the homonymous facilitation of the DA and DP, respectively. In the EMG-A study, conditioning stimulation to the DA and DP nerves inhibited the rectified and averaged EMG of the DP and DA, respectively. The inhibition diminished with tonic vibration stimulation to the DA and DP and recovered 20-30min after vibration removal. These findings suggest that oligo(di or tri)-synaptic inhibition mediated by group Ia afferents between the DA and DP exists in humans.

Contact Heat in Magnetoencephalography: A Systematic Review.

Contact heat is commonly used in experimental research to evoke brain activity, most frequently acquired with electroencephalography (EEG). Although magnetoencephalography (MEG) improves spatial resolution, using some contact heat stimulators with MEG can present methodological challenges. This systematic review assesses studies that utilise contact heat in MEG, their findings and possible directions for further research. Eight electronic databases were searched for relevant studies, in addition to the selected papers' reference lists, citations and ConnectedPapers maps. Best practice recommendations for systematic reviews were followed. Papers met inclusion criteria if they used MEG to record brain activity in conjunction with contact heat, regardless of stimulator equipment or paradigm. Of 646 search results, seven studies met the inclusion criteria. Studies demonstrated effective electromagnetic artefact removal from MEG data, the ability to elicit affective anticipation and differences in deep brain stimulation responders. We identify contact heat stimulus parameters that should be reported in publications to ensure comparisons between data outcomes are consistent. Contact heat is a viable alternative to laser or electrical stimulation in experimental research, and methods exist to successfully mitigate any electromagnetic noise generated by PATHWAY CHEPS equipment - though there is a dearth of literature exploring the post-stimulus time window.

EEG is better left alone

Automated preprocessing methods are critically needed to process the large publicly-available EEG databases, but the optimal approach remains unknown because we lack data quality metrics to compare them. Here, we designed a simple yet robust EEG data quality metric assessing the percentage of significant channels between two experimental conditions within a 100 ms post-stimulus time range. Because of volume conduction in EEG, given no noise, most brain-evoked related potentials (ERP) should be visible on every single channel. Using three publicly available collections of EEG data, we showed that, with the exceptions of high-pass filtering and bad channel interpolation, automated data corrections had no effect on or significantly decreased the percentage of significant channels. Referencing and advanced baseline removal methods were significantly detrimental to performance. Rejecting bad data segments or trials could not compensate for the loss in statistical power. Automated Independent Component Analysis rejection of eyes and muscles failed to increase performance reliably. We compared optimized pipelines for preprocessing EEG data maximizing ERP significance using the leading open-source EEG software: EEGLAB, FieldTrip, MNE, and Brainstorm. Only one pipeline performed significantly better than high-pass filtering the data.

Modeling temporal information encoding by the population of fibers in the healthy and synaptopathic auditory nerve

We report a theoretical study aimed at investigating the impact of cochlear synapse loss (synaptopathy) on the encoding of the envelope (ENV) and temporal fine structure (TFS) of sounds by the population of auditory nerve fibers. A computational model was used to simulate auditory-nerve spike trains evoked by sinusoidally amplitude-modulated (AM) tones at 10 Hz with various carrier frequencies and levels. The model included 16 cochlear channels with characteristic frequencies (CFs) from 250 Hz to 8 kHz. Each channel was innervated by 3, 4 and 10 fibers with low (LSR), medium (MSR), and high spontaneous rates (HSR), respectively. For each channel, spike trains were collapsed into three separate ‘population’ post-stimulus time histograms (PSTHs), one per fiber type. Information theory was applied to reconstruct the stimulus waveform, ENV, and TFS from one or more PSTHs in a mathematically optimal way. The quality of the reconstruction was regarded as an estimate of the information present in the used PSTHs. Various synaptopathy scenarios were simulated by removing fibers of specific types and/or cochlear regions before stimulus reconstruction. We found that the TFS was predominantly encoded by HSR fibers at all stimulus carrier frequencies and levels. The encoding of the ENV was more complex. At lower levels, the ENV was predominantly encoded by HSR fibers with CFs near the stimulus carrier frequency. At higher levels, the ENV was equally well or better encoded by HSR fibers with CFs different from the AM carrier frequency as by LSR fibers with CFs at the carrier frequency. Altogether, findings suggest that a healthy population of HSR fibers (i.e., including fibers with CFs around and remote from the AM carrier frequency) might be sufficient to encode the ENV and TFS over a wide range of stimulus levels. Findings are discussed regarding their relevance for diagnosing synaptopathy using non-invasive ENV- and TFS-based measures.

Auditory response patterns of mouse primary auditory cortex to sound stimuli

To investigate the auditory response patterns of mouse primary auditory cortex (A1) neurons. In vivo cell-attached recordings and neural network modeling were performed to detect the changes in response patterns of A1 neurons of awake C57BL/6J mice to sound stimulation with varying lengths. A1 neuron signals were recorded for 216 neurons in 20 awake mice using a target sound stimulation sequence, and the classification and response characteristics of A1 neuron response patterns were examined using post-stimulus spike time histograms. To simulate the diversity of the A1 neuron response patterns, an A1 neuron model was established based on the Wilson-Cowan model and integral-firing model. The neuron connection weight parameters in the model were calculated by examining the micro loop structure of the pyramidal neurons, parvalbumin neurons, and somatostatin neurons in the A1 region, and the A1 neural network information coding model was constructed. The Onset response neurons only had fast spike response within 10 to 40 ms after the beginning of noise stimulation (122 neurons). The Sustained response neurons had spike response continuously during the noise stimulation (26 neurons). The On-off response neurons had fast spike response after the beginning and the end of noise stimulation (40 neurons). The Offset response neurons only had fast spike response within 10 to 40 ms after the end of noise stimulation (22 neurons). In the neural network model, the Onset peak neural activities of A1 pyramidal neurons, parvalbumin neurons, and somatostatin neurons were 0.7483, 0.5236 and 0.9427, respectively, and their response half peak widths were 18.5 ms, 12 ms and 31 ms during the 100 ms noise stimulation, respectively. By changing the feedforward excitation and synaptic inhibition time constants in the model, the neurons generated numerous different types of spike train. The auditory response of mouse A1 neurons to sound stimuli shows mainly the Onset, Sustained, On-off, and Offset response patterns.

An Entropy-Based Prospective Randomized Controlled Trial to Evaluate the Analgesic and Hypnotic Effects of Equipotent Doses of Sevoflurane and Isoflurane in Patients Presenting for Spine Surgeries.

Objectives Minimal alveolar concentration (MAC) of anesthetic agents has been considered a suitable measure of the potency of inhalational anesthetics. Furthermore, it is assumed that equi-MAC concentrations of different anesthetic agents have a similar potency in suppressing responses to painful stimuli. Isoflurane and sevoflurane are two commonly used volatile anesthetic agents in spine surgeries. Therefore, these agents' hypnotic and analgesic potencies should be distinguished and comprehended for the optimal administration of anesthesia. Consequently, we undertook this study to compare the analgesic and hypnotic potencies between these agents at equi-MAC concentrations, using the entropy monitor. Materials and Methods Forty patients undergoing lumbar spine surgery were randomly assigned to two groups receiving either isoflurane ( n = 20) or sevoflurane ( n = 20). After induction, maintenance of anesthesia was done with age-corrected 1.0 MAC of either isoflurane or sevoflurane. A standardized noxious stimulus was provided to all the patients after achieving a steady state of 1.0 MAC. The state entropy (SE), response entropy (RE), and RE–SE were recorded at baseline, prestimulus, and poststimulus time points in both groups. Statistical Analyses Data are presented as frequency and percentages for categorical variables and mean ± standard deviation for continuous variables. The comparison of categorical variables between the two groups was made using the Fisher's exact test, and the Student's t -test was used for continuous variables. A p -value of < 0.05 was considered to be statistically significant. Results At age-corrected 1.0 MAC, there was no significant difference in the SE, RE, and RE–SE in both the groups at any time point. Conclusion Our study shows that during a steady state of age-corrected 1.0 MAC single-agent anesthesia, sevoflurane and isoflurane have comparable analgesic and hypnotic potencies as measured by entropy indices when a standardized nociceptive stimulus is provided.

Enumeration takes time: Accuracy improves even after stimuli disappear

Numerical cognition is widespread among animal species and present from birth in humans. Laboratory studies show that longer stimulus duration improves numerical discrimination accuracy (Inglis & Gilmore, 2013; Wood & Spelke, 2005). Inglis and Gilmore (2013) suggested that longer durations allow subjects to resample the stimulus image multiple times, resulting in a more accurate final estimate. The current study tested this “multiple sampling” model alongside two competing models – “serial foveal accumulator” (Cheyette & Piantadosi, 2019) and “longer processing time” – to determine how stimulus duration relates to accuracy. Adult subjects completed a fully within-subject, 2AFC task in which they judged which of two arrays had more dots; accuracy was the dependent measure. Experiment 1 revealed higher accuracy in the 500 ms stimulus duration condition compared to the 100 ms condition, replicating previous results. Experiments 2 and 4 extended this finding. When stimulus duration was held constant at 100 ms, adding a 400 ms delay between stimulus offset and mask onset improved accuracy. Accuracy was similar in the 500 ms stimulus duration condition (E1) and the 100 ms duration + 400 ms mask delay conditions (E2 and E4), indicating that post-stimulus processing time improves accuracy, rather than stimulus duration per se. This contrasts with both the multiple sampling model and the serial foveal model, although we cannot exclude the possibility that sampling continues in iconic memory. Numerosity was a significant factor in all four experiments, suggesting a serial component in the enumeration process. These findings shed light on the cognitive processes underlying nonverbal number representation in humans.

Differences in dogs' event-related potentials in response to human and dog vocal stimuli; a non-invasive study.

Recent advances in the field of canine neuro-cognition allow for the non-invasive research of brain mechanisms in family dogs. Considering the striking similarities between dog's and human (infant)'s socio-cognition at the behavioural level, both similarities and differences in neural background can be of particular relevance. The current study investigates brain responses of n = 17 family dogs to human and conspecific emotional vocalizations using a fully non-invasive event-related potential (ERP) paradigm. We found that similarly to humans, dogs show a differential ERP response depending on the species of the caller, demonstrated by a more positive ERP response to human vocalizations compared to dog vocalizations in a time window between 250 and 650 ms after stimulus onset. A later time window between 800 and 900 ms also revealed a valence-sensitive ERP response in interaction with the species of the caller. Our results are, to our knowledge, the first ERP evidence to show the species sensitivity of vocal neural processing in dogs along with indications of valence sensitive processes in later post-stimulus time periods.

Similarities Between Somatosensory Cortical Responses Induced via Natural Touch and Microstimulation in the Ventral Posterior Lateral Thalamus in Macaques.

Lost sensations, such as touch, could be restored by microstimulation (MiSt) along the sensory neural substrate. Such neuroprosthetic sensory information can be used as feedback from an invasive brain-machine interface (BMI) to control a robotic arm/hand, such that tactile and proprioceptive feedback from the sensorized robotic arm/hand is directly given to the BMI user. Microstimulation in the human somatosensory thalamus (Vc) has been shown to produce somatosensory perceptions. However, until recently, systematic methods for using thalamic stimulation to evoke naturalistic touch perceptions were lacking. We have recently presented rigorous methods for determining a mapping between ventral posterior lateral thalamus (VPL) MiSt, and neural responses in the somatosensory cortex (S1), in a rodent model (Choi et al., 2016; Choi and Francis, 2018). Our technique minimizes the difference between S1 neural responses induced by natural sensory stimuli and those generated via VPL MiSt. Our goal is to develop systems that know what neural response a given MiSt will produce and possibly allow the development of natural “sensation.” To date, our optimization has been conducted in the rodent model and simulations. Here, we present data from simple non-optimized thalamic MiSt during peri-operative experiments, where we used MiSt in the VPL of macaques, which have a somatosensory system more like humans, as compared to our previous rat work (Li et al., 2014; Choi et al., 2016). We implanted arrays of microelectrodes across the hand area of the macaque S1 cortex as well as in the VPL. Multi and single-unit recordings were used to compare cortical responses to natural touch and thalamic MiSt in the anesthetized state. Post-stimulus time histograms were highly correlated between the VPL MiSt and natural touch modalities, adding support to the use of VPL MiSt toward producing a somatosensory neuroprosthesis in humans.

The Implicit Aesthetic Preference for Mobile Marketing Interface Layout-An ERP Study.

Businesses and scholars have been trying to improve marketing effect by optimizing mobile marketing interfaces aesthetically as users browse freely and aimlessly through mobile marketing interfaces. Although the layout is an important design factor that affects interface aesthetics, whether it can trigger customer's aesthetic preferences in mobile marketing remains unexplored. To address this issue, we employ an empirical methodology of event-related potentials (EPR) in this study from the perspective of cognitive neuroscience and psychology. Subjects are presented with a series of mobile marketing interface images of different layouts with identical marketing content. Their EEG waves were recorded as they were required to distinguish a target stimulus from the others. After the experiment, each of the subjects chose five stimuli interfaces they like and five they dislike. By analyzing the ERP data derived from the EEG data and the behavioral data, we find significant differences between the disliked interfaces and the other interfaces in the ERP component of P2 from the frontal-central area in the 200–400 ms post-stimulus onset time window and LPP from both the frontal-central and parietal-occipital area in the 400–600 ms time window. The results support the hypothesis that humans do make rapid implicit aesthetic preferences for interface layouts and suggest that even under a free browsing context like the mobile marketing context, interface layouts that raise high emotional arousal can still attract more user attention and induce users' implicit aesthetic preference.

Sensorimotor contributions to working memory differ between the discrimination of Same and Different syllable pairs

Sensorimotor activity during speech perception is both pervasive and highly variable, changing as a function of the cognitive demands imposed by the task. The purpose of the current study was to evaluate whether the discrimination of Same (matched) and Different (unmatched) syllable pairs elicit different patterns of sensorimotor activity as stimuli are processed in working memory. Raw EEG data recorded from 42 participants were decomposed with independent component analysis to identify bilateral sensorimotor mu rhythms from 36 subjects. Time frequency decomposition of mu rhythms revealed concurrent event related desynchronization (ERD) in alpha and beta frequency bands across the peri- and post-stimulus time periods, which were interpreted as evidence of sensorimotor contributions to working memory encoding and maintenance. Left hemisphere alpha/beta ERD was stronger in Different trials than Same trials during the post-stimulus period, while right hemisphere alpha/beta ERD was stronger in Same trials than Different trials. A between-hemispheres contrast revealed no differences during Same trials, while post-stimulus alpha/beta ERD was stronger in the left hemisphere than the right during Different trials. Results were interpreted to suggest that predictive coding mechanisms lead to repetition suppression effects in Same trials. Mismatches arising from predictive coding mechanisms in Different trials shift subsequent working memory processing to the speech-dominant left hemisphere. Findings clarify how sensorimotor activity differentially supports working memory encoding and maintenance stages during speech discrimination tasks and have potential to inform sensorimotor models of speech perception and working memory.

Differential Influence of Ventromedial Prefrontal Cortex Lesions on Neural Representations of Schema and Semantic Category Knowledge.

Prior knowledge, such as schemas or semantic categories, influences our interpretation of stimulus information. For this to transpire, prior knowledge must first be reinstated and then instantiated by being applied to incoming stimuli. Previous neuropsychological models implicate the ventromedial prefrontal cortex (vmPFC) in mediating these functions for schemas and the anterior/lateral temporal lobes and related structures for categories. vmPFC, however, may also affect processing of semantic category information. Here, the putative differential role of the vmPFC in the reinstatement and instantiation of schemas and semantic categories was examined by probing network-level oscillatory dynamics. Patients with vmPFC damage (n = 11) and healthy controls (n = 13) were instructed to classify words according to a given schema or category, while electroencephalography was recorded. As reinstatement is a preparatory process, we focused on oscillations occurring 500 msec prior to stimulus presentation. As instantiation occurs at stimulus presentation, we focused on oscillations occurring between stimulus presentation and 1000 msec poststimulus. We found that reinstatement was associated with prestimulus, theta and alpha desynchrony between vmPFC and the posterior parietal cortex for schemas, and between lateral temporal lobe and inferotemporal cortex for categories. Damage to the vmPFC influenced both schemas and categories, but patients with damage to the subcallosal vmPFC showed schema-specific deficits. Instantiation showed similar oscillatory patterns in the poststimulus time frame, but in the alpha and beta frequency bands. Taken together, these findings highlight distinct but partially overlapping neural mechanisms implicated in schema- and category-mediated processing.

The correspondence between EMG and EEG measures of changes in cortical excitability following transcranial magnetic stimulation.

TMS is commonly used to study excitatory/inhibitory neurotransmission in cortical circuits. Changes in cortical excitability following TMS are typically measured from hand (using EMG; limited to motor cortex) or scalp (using EEG); however, it is unclear whether these two measures represent the same activity when assessing motor cortex. We found that TMS-EMG and TMS-EEG measures of motor cortex excitability are differentially affected by sensory confounds at different time points, masking any actual relationship between them in the time domain. In the frequency domain, local high-frequency oscillations in EEG recordings were minimally confounded by sensory artefacts and demonstrated strong correlations with EMG measures of cortical excitability across time, regardless of TMS intensity or waveform. Therefore, despite the effects of sensory artefacts, the two measures of motor cortex excitability share a response component, suggesting that they index a similar cortical activity and perhaps the same neuronal population. Transcranial magnetic stimulation (TMS) is a powerful tool for investigating cortical circuits. Changes in cortical excitability following TMS are typically assessed by measuring changes in either conditioned motor-evoked potentials (MEPs) following paired-pulse TMS over motor cortex or evoked potentials measured with electroencephalography following single-pulse TMS (TEPs). However, it is unclear whether these two measures of cortical excitability index the same cortical response. Twenty-four healthy participants received local and interhemispheric paired-pulse TMS over motor cortex with eight inter-pulse intervals, sub- and suprathreshold conditioning intensities, and two different pulse waveforms, while MEPs were recorded from a hand muscle. TEPs were also recorded in response to single-pulse TMS using the conditioning pulse alone. The relationships between TEPs and conditioned-MEPs were evaluated using metrics sensitive to both their magnitude at each time point and their overall shape across time. The impacts of undesired sensory potentials resulting from TMS pulse and muscle contractions were also assessed on both measures. Both conditioned-MEPs and TEPs were sensitive to re-afferent somatosensory activity following motor-evoked responses, but over different post-stimulus time points. Moreover, the amplitude of low-frequency oscillations in TEPs was strongly correlated with the sensory potentials, whereas early and local high-frequency responses showed minimal relationships. Accordingly, conditioned-MEPs did not correlate with TEPs in the time domain but showed high shape similarity with the amplitude of high-frequency oscillations in TEPs. Therefore, despite the effects of sensory confounds, the TEP and MEP measures share a response component, suggesting that they index a similar cortical response and perhaps the same neuronal populations.

Susceptibility to Residual Inhibition Is Associated With Hearing Loss and Tinnitus Chronicity.

Residual inhibition, that is, the temporary suppression of tinnitus loudness after acoustic stimulation, is a frequently observed phenomenon that may have prognostic value for clinical applications. However, it is unclear in which subjects residual inhibition is more likely and how stable the effect of inhibition is over multiple repetitions. The primary aim of this work was to evaluate the effect of hearing loss and tinnitus chronicity on residual inhibition susceptibility. The secondary aim was to investigate the short-term repeatability of residual inhibition. Residual inhibition was assessed in 74 tinnitus subjects with 60-second narrow-band noise stimuli in 10 consecutive trials. The subjects were assigned to groups according to their depth of suppression (substantial residual inhibition vs. comparator group). In addition, a categorization in normal hearing and hearing loss groups, related to the degree of hearing loss at the frequency corresponding to the tinnitus pitch, was made. Logistic regression was used to identify factors associated with susceptibility to residual inhibition. Repeatability of residual inhibition was assessed using mixed-effects ordinal regression including poststimulus time and repetitions as factors. Tinnitus chronicity was not associated with residual inhibition for subjects with hearing loss, while a statistically significant negative association between tinnitus chronicity and residual inhibition susceptibility was observed in normal hearing subjects (odds ratio: 0.63; p = .0076). Moreover, repeated states of suppression can be stably induced, reinforcing the use of residual inhibition for within-subject comparison studies.

Epileptogenesis-induced changes of hippocampal-piriform connectivity

ObjectiveTissue remodeling has been described in brain circuits that are involved in the generation and propagation of epileptic seizures. Human and animal studies suggest that the anterior piriform cortex (aPC) is crucial for seizure expression in focal epilepsies. Here, we investigate the effect of kainic-acid (KA)-induced seizures on the effective connectivity of the aPC with bilateral hippocampal CA3 regions using cerebro-cerebral evoked potentials (CCEPs). MethodsAdult male Sprague-Dawley rats were implanted with a tripolar electrode in the left aPC for stimulation and recording, and with unipolar recording electrodes in bilateral CA3 regions. Single pulse stimulations were given to the aPC and CCEPs were averaged before KA injections and after the emergence of spontaneous recurrent seizures (SRS). Similar recordings at equivalent time intervals were obtained from animals that received saline injections instead of KA (controls). ResultsIn the experimental group, the percentage change of increased amplitude of the contralateral (but not ipsilateral) CA3 CCEPs between pre-KA injection and after the emergence of SRS was significantly greater than in controls. No significant single-pulse-induced spectral change responses were observed in either epileptic or control rats when comparing pre- and post-stimulus time intervals. Also, we found no correlation between seizure frequency and the extent of amplitude changes in the CCEPs. ConclusionsIn the KA model, epileptogenesis results in plastic changes that manifest as an amplification of evoked potential amplitudes recorded in the contralateral hippocampus in response to single-pulse stimulation of the aPC. These results suggest epileptogenesis-induced facilitation of interhemispheric connectivity between the aPC and the hippocampus. Since the amplitude increase of the contralateral CCEP is a possible in vivo biomarker of epilepsy, any intervention (e.g. neuromodulatory) that can reverse this phenomenon may hold a potential antiepileptic efficacy.

Three dimensional rendering of auditory neuronal responses: A novel illustration of receptive field across frequency, intensity & time domains

BackgroundNeural coding of sound information is often studied through frequency tuning curve (FTC), spectro-temporal receptive field (STRF), post-stimulus time histogram (PSTH), and other methods such as rate functions. These methods, despite providing a robust characterization of auditory responses in their specific domains, lack a complete description in terms of three sound fundamentals: frequency, amplitude, and time. New MethodUsing the techniques of electrophysiology, neural signal processing and medical image processing, a standalone method is created to illustrate the neural processing of three sound fundamentals in one representation. ResultsThe new method comprehensively showed frequency tuning, intensity tuning, time tuning as well as a novel representation of frequency and time dependent intensity coding. It provides most of the necessary parameters that are used to quantify neural response properties, such as minimum threshold (MT), frequency tuning, latency, best frequency (BF), characteristic frequency (CF), bandwidth (BW), etc. Comparison with Existing MethodsOur method shows neural responses as a function of all three sound fundamentals in a single representation that was not possible in previous methods. It covers many functions of conventional methods and allow extracting novel information such as the intensity coding as the function of the spectrotemporal response area of auditory neurons. ConclusionThis method can be used as a standalone package to study auditory neural responses and evaluate the performance of different hearing related devices such as cochlear implants and hearing aids in animal models as well as study and compare auditory processing in aged and hearing impaired animal models.

Statistical Significance Assessment of Phase Synchrony in the Presence of Background Couplings: An ECoG Study.

Statistical significance testing is a necessary step in connectivity analysis. Several statistical test methods have been employed to assess the significance of functional connectivity, but the performance of these methods has not been thoroughly evaluated. In addition, the effects of the intrinsic brain connectivity and background couplings on performance of statistical test methods in task-based studies have not been investigated yet. The background couplings may exist independent of cognitive state and can be observed on both pre- and post-stimulus time intervals. The background couplings may be falsely detected by a statistical test as task-related connections, which can mislead interpretations of the task-related functional networks. The aim of this study was to investigate the relative performance of four commonly used non-parametric statistical test methods-surrogate, demeaned surrogate, bootstrap resampling, and Monte Carlo permutation methods-in the presence of background couplings and noise, with different signal-to-noise ratios (SNRs). Using simulated electrocorticographic (ECoG) datasets and phase locking value (PLV) as a measure of functional connectivity, we evaluated the performances of the statistical test methods utilizing sensitivity, specificity, accuracy, and receiver operating curve (ROC) analysis. Furthermore, we calculated optimal p values for each statistical test method using the ROC analysis, and found that the optimal p values were increased by decreasing the SNR. We also found that the optimal p value of the bootstrap resampling was greater than that of other methods. Our results from the simulation datasets and a real ECoG dataset, as an illustrative case report, revealed that the bootstrap resampling is the most efficient non-parametric statistical test for identifying the significant PLV of ECoG data, especially in the presence of background couplings.

Frequency variation analysis in neuronal cultures for stimulus response characterization

In vitro neuronal cultures embodied in a closed-loop control system have been used recently to study neuronal dynamics. This allows the development of neurons in a controlled environment with the purpose of exploring the computational capabilities of such biological neural networks. Due to the intrinsic properties of in vitro neuronal cultures and how the neuronal tissue grows in them, the ways in which signals are transmitted and generated within and throughout the culture can be difficult to characterize. The neural code is formed by patterns of spikes whose properties are in essence nonlinear and non-stationary. The usual approach for this characterization has been the use of the post-stimulus time histogram (PSTH). PSTH is calculated by counting the spikes detected in each neuronal culture electrode during some time windows after a stimulus in one of the electrodes. The objective is to find pairs of electrodes where stimulation in one of the pairs produces a response in the other but not in the rest of the electrodes in other pairs. The aim of this work is to explore possible ways of extracting relevant information from the global response to culture stimulus by studying the patterns of variation over time for the firing rate, estimated from inverse inter-spike intervals, in each electrode. Machine learning methods can then be applied to distinguish the electrode being stimulated from the whole culture response, in order to obtain a better characterization of the culture and its computational capabilities so it can be useful for robotic applications.

Predicting responses to inhibitory synaptic input in substantia nigra pars reticulata neurons.

The changes in firing probability produced by a synaptic input are usually visualized using the poststimulus time histogram (PSTH). It would be useful if postsynaptic firing patterns could be predicted from patterns of afferent synaptic activation, but attempts to predict the PSTH from synaptic potential waveforms using reasoning based on voltage trajectory and spike threshold have not been successful, especially for inhibitory inputs. We measured PSTHs for substantia nigra pars reticulata (SNr) neurons inhibited by optogenetic stimulation of striato-nigral inputs or by matching artificial inhibitory conductances applied by dynamic clamp. The PSTH was predicted by a model based on each SNr cell's phase-resetting curve (PRC). Optogenetic activation of striato-nigral input or artificial synaptic inhibition produced a PSTH consisting of an initial depression of firing followed by oscillatory increases and decreases repeating at the SNr cell's baseline firing rate. The phase resetting model produced PSTHs closely resembling the cell data, including the primary pause in firing and the oscillation. Key features of the PSTH, including the onset rate and duration of the initial inhibitory phase, and the subsequent increase in firing probability could be explained from the characteristic shape of the SNr cell's PRC. The rate of damping of the late oscillation was explained by the influence of asynchronous phase perturbations producing firing rate jitter and wander. Our results demonstrate the utility of phase-resetting models as a general method for predicting firing in spontaneously active neurons and their value in interpretation of the striato-nigral PSTH. NEW & NOTEWORTHY The coupling of patterned presynaptic input to sequences of postsynaptic firing is a Gordian knot, complicated by the multidimensionality of neuronal state and the diversity of potential initial states. Even so, it is fundamental for even the simplest understanding of network dynamics. We show that a simple phase-resetting model constructed from experimental measurements can explain and predict the sequence of spike rate changes following synaptic inhibition of an oscillating basal ganglia output neuron.

Perceptual facilitation of word recognition through motor activation during sentence comprehension

Despite the growing literature on anticipatory language processing, the brain dynamics of this high-level predictive process are still unclear. In the present MEG study, we analyzed pre- and post-stimulus oscillatory activity time-locked to the reading of a target word. We experimentally contrasted the processing of the same target word following two highly constraining sentence contexts, in which the constraint was driven either by the semantic content or by the lexical association between words. Previous research suggests the presence of sensory facilitation for expected words in the latter condition but not in the former. We observed a dissociation between beta (∼20 Hz) and gamma (>50 Hz) band activity in pre- and post-stimulus time intervals respectively. Both the beta and gamma effects were evident in occipital brain regions, and only the pre-stimulus beta effect additionally involved left pre-articulatory motor regions. Lexically constrained (vs. semantically constrained) words elicited reduced beta power around 400 msec before the target word in motor regions and a functionally related gamma enhancement in occipital regions around 200 msec post-target. The present findings highlight the role of the motor network in word-form prediction and support proposals claiming that low-level perceptual representations can be pre-activated during language prediction.