Microstate ERP Analyses to Pinpoint the Articulatory Onset in Speech Production

The use of electroencephalography (EEG) to study overt speech production has increased substantially in the past 15 years and the alignment of evoked potential (ERPs) on the response onset has become an extremely useful method to target “latest” stages of speech production. Yet, response-locked ERPs raise a methodological issue: on which event should the point of alignment be placed? Response-locked ERPs are usually aligned to the vocal (acoustic) onset, although it is well known that articulatory movements may start up to a hundred milliseconds prior to the acoustic onset and that this “articulatory onset to acoustic onset interval” (AAI) depends on the phoneme properties. Given the previously reported difficulties to measure the AAI, the purpose of this study was to determine if the AAI could be reliably detected with EEG-microstates. High-density EEG was recorded during delayed speech production of monosyllabic pseudowords with four different onset consonants. Whereas the acoustic response onsets varied depending on the onset consonant, the response-locked spatiotemporal EEG analysis revealed a clear asynchrony of the same sequence of microstates across onset consonants. A specific microstate, the latest observed in the ERPs locked to the vocal onset, presented longer duration for phonemes with longer acoustic response onsets. Converging evidences seemed to confirm that this microstate may be related to the articulatory onset of motor execution: its scalp topography corresponded to those previously associated with muscle activity and source localization highlighted the involvement of motor areas. Finally, the analyses on the duration of such microstate in single trials further fit with the AAI intervals for specific phonemes reported in previous studies. These results thus suggest that a particular ERP-microstate is a reliable index of articulation onset and of the AAI.

Timing of response onset and offset in macaque V4: stimulus and task dependence

In the primate visual cortex, both the magnitude of the neuronal response and its timing can carry important information about the visual world, but studies typically focus only on response magnitude. Here, we examine the onset and offset latency of the responses of neurons in area V4 of awake, behaving macaques across several experiments, in the context of a variety of stimuli and task paradigms. Our results highlight distinct contributions of stimuli and tasks to V4 response latency. We found that response onset latencies are shorter than typically cited (median = 75.5 ms), supporting a role for V4 neurons in rapid object and scene recognition functions. Moreover, onset latencies are longer for smaller stimuli and stimulus outlines, consistent with the hypothesis that longer latencies are associated with higher spatial frequency content. Strikingly, we found that onset latencies showed no significant dependence on stimulus occlusion, unlike in inferotemporal cortex, nor on task demands. Across the V4 population, onset latencies had a broad distribution, reflecting the diversity of feedforward, recurrent and feedback connections that inform the responses of individual neurons. Response offset latencies, on the other hand, displayed the opposite tendency in their relationship to stimulus and task attributes: they are less influenced by stimulus appearance, but are shorter in guided saccade tasks compared to fixation tasks. The observation that response latency is influenced by stimulus- and task-associated factors emphasizes a need to examine response timing alongside firing rate in determining the functional role of area V4.

Response nonlinearities in networks of spiking neurons

ABSTRACTCombining information from multiple sources is a fundamental operation performed by networks of neurons in the brain, whose general principles are still largely unknown. Experimental evidence suggests that combination of inputs in cortex relies on nonlinear summation. Such nonlinearities are thought to be fundamental to perform complex computations. However, these non-linearities contradict the balanced-state model, one of the most popular models of cortical dynamics, which predicts networks have a linear response. This linearity is obtained in the limit of very large recurrent coupling strength. We investigate the stationary response of networks of spiking neurons as a function of coupling strength. We show that, while a linear transfer function emerges at strong coupling, nonlinearities are prominent at finite coupling, both at response onset and close to saturation. We derive a general framework to classify nonlinear responses in these networks and discuss which of them can be captured by rate models. This framework could help to understand the observed diversity of non-linearities observed in cortical networks.AUTHOR SUMMARYModels of cortical networks are often studied in the strong coupling limit, where the so-called balanced state emerges. In this strong coupling limit, networks exhibit without fine tuning, a number of ubiquitous properties of cortex, such as the irregular nature of neuronal firing. However, it fails to account for nonlinear summation of inputs, since the strong coupling limit leads to a linear network transfer function. We show that, in networks of spiking neurons, nonlinearities at response-onset and saturation emerge at finite coupling. Critically, for realistic parameter values, both types of nonlinearities are observed at experimentally observed rates. Thus, we propose that these models could explain experimentally observed nonlinearities.

A Key Role for Prefrontocortical Small Conductance Calcium-Activated Potassium Channels in Stress Adaptation and Rapid Antidepressant Response

The muscarinic acetylcholine receptor antagonist scopolamine elicits rapid antidepressant activity, but its underlying mechanism is not fully understood. In a chronic stress model, a single low-dose administration of scopolamine reversed depressive-like reactivity. This antidepressant-like effect was mediated via a muscarinic M1 receptor–SKC pathway because it was mimicked by intra-medial prefrontal cortex (intra-mPFC) infusions of scopolamine, of the M1 antagonist pirenzepine or of the SKC antagonist apamin, but not by the selective serotonin reuptake inhibitor (SSRI) antidepressant fluoxetine. Extracellular and whole-cell recordings revealed that scopolamine and ketamine attenuate the SKC-mediated action potential hyperpolarization current and rapidly enhance mPFC neuronal excitability within the therapeutically relevant time window. The SKC agonist 1-EBIO abrogated scopolamine-induced antidepressant activity at a dose that completely suppressed burst firing activity. Scopolamine also induced a slow-onset activation of raphe serotonergic neurons, which in turn was dependent on mPFC-induced neuroplasticity or excitatory input, since mPFC transection abolished this effect. These early behavioral and mPFC activational effects of scopolamine did not appear to depend on prefrontocortical brain-derived neurotrophic factor and serotonin-1A activity, classically linked to SSRIs, and suggest a novel mechanism associated with antidepressant response onset through SKC-mediated regulation of activity-dependent plasticity.

Time-to-target simplifies optimal control of visuomotor feedback responses

Visuomotor feedback responses vary in intensity throughout a reach, commonly explained by optimal control. Here we show that the optimal control for a range of movements with the same goal can be simplified to a time-to-target dependent control scheme. We measure participants’ visuomotor responses in five reaching conditions, each with different hand or cursor kinematics. Participants only produced different feedback responses when these kinematic changes resulted in different times-to-target. We complement our experimental data with a range of finite and non-finite horizon optimal feedback control models, finding that only the model with time-to-target as one of the input parameters can successfully replicate the experimental data. Overall, this suggests that time-to-target is a critical control parameter in online feedback control. Moreover, we propose that for a specific task and known dynamics, humans can instantly produce a control signal without any computation allowing rapid response onset and close to optimal control.

Dynamic changes in large-scale functional connectivity predict performance in a multisensory task

Complex and variable behavior requires fast changes of functional connectivity in large-scale cortical networks. Here, we report on the cortical dynamics of functional coupling across visual, auditory and parietal areas during a lateralized detection task in the ferret. We hypothesized that fluctuations in coupling, indicative of dynamic variations in the network state, might predict the animals’ performance. While power for hit and miss trials showed significant differences only around stimulus and response onset, phase coupling already differed before stimulus onset. Principal component analysis of directed coupling at the single-trial level during this period revealed subnetworks that most strongly related to behavior. While higher global phase coupling of visual and auditory regions to parietal cortex was predictive of task performance, a second component showed that a reduction in coupling between subnetworks of sensory modalities was also necessary, probably to allow a better detection of the unimodal signals. Furthermore, we observed that long-range coupling became more predominant during the task period compared to the pre-stimulus baseline. Taken together, these results suggest that fluctuations in the network state, particular with respect to long-range connectivity, are key determinants of the animals’ behavior.

The Scope of Planning Serial Actions during Typing

Human activities consisting of multiple component actions require the generation of ordered sequences. This study investigated the scope of response planning in highly serial task, typing, by means of ERPs indexing motor response preparation. Specifically, we compared motor-related ERPs yielded by words typed using a single hand against words that had all keystrokes typed with a single hand, except for a deviant one, typed with the opposite hand. The deviant keystroke occurred either early in the typed sequence, corresponding to the second or third letters, or late, corresponding to the penultimate or last letter. Motor-related ERPs detected before response onset were affected only by deviant keystrokes located at the beginning of the sequence, whereas deviant keystrokes located at the end yielded ERPs that were undistinguishable from unimanual responses. These results impose some constraints on the notion of parallel processing of component actions.

Modeling the Electro-chemical Properties of Microbial Opsin ChrimsonR for Application to Optogenetics-based Vision Restoration

Optogenetic activation of neurons [1] have greatly contributed to our understanding of how neural circuits operate, and holds huge promise in the field of neural prosthetics, particularly in sensory restoration. The discovery of new channelrhodopsins, Chrimson — which is 45 nm more red-shifted than any previously discovered or engineered channelrhodopsin — and its mutant ChrimsonR with faster kinetics [2] made this technology available for medical applications. However, a detailed model that would be able to accurately reproduce the membrane potential dynamics in cells transfected with ChrimsonR under light stimulation is missing. We address this issue by developing the first model for the electrochemical behavior of ChrimsonR that predicts its conductance in response to arbitrary light stimulation. Our model captures ON and OFF dynamics of the protein for stimuli with frequencies up to 100 Hz and their relationship with the brightness, as well as its activation curve, the steady-state amplitude of the response as a function of light intensity. Additionally, we capture a slow adaptation mechanism at a timescale at the order of minutes. Our model holds for light intensities covering the whole dynamic range of the channel (from response onset to saturation) and for timescales in the order of up to several minutes. This model is a new step towards modeling the spiking activity of ChrimsonR-expressing neurons, required for the precise control of information transmission in optogenetics-based Brain-Computer Interfaces, and will inform future applications of ChrimsonR based optogenetics.

The illusory benefit of cognates: Lexical facilitation followed by sublexical interference in a word typing task

Cognate facilitation and cognate interference in word production have been elicited separately, in different paradigms. In our experiment, we created conditions for facilitation and interference to occur sequentially, and identified the levels at which the two processes manifested. Bilinguals translated cognates and noncognates from L2 to L1 and typed the translations. Response-onset latencies were shorter for cognates (cognate-facilitation) but execution latencies were longer, and cross-language orthographic errors were more frequent for cognates than for noncognates (cognate-interference). Facilitation at onset followed by interference during word execution suggests that the language-selection mechanism operated efficiently at the lexical level but inefficiently at the sublexical level. It also suggests that language selection is not an event with irreversible outcome, but selection at one level may not guarantee language-selectivity at subsequent levels. We propose that a model of bilingual language production that specifies multiple language-selection processes at multiple loci of selection can accommodate this phenomenon.