EEG/ECoG/EMG publications

Objective: Spasmodic dysphonia (SD) is a debilitating voice/speech disorder without an effective cure. To obtain a better understanding of the underlying cortical neural mechanism of the disease we analyzed electroencephalographic (EEG) signals of people with SD during voice production. Method: Ten SD individuals and 10 healthy volunteers produced 50 vowel vocalization epochs of 2500 ms duration. Two EEG features were derived: (1) event-related change in spectral power during vocalization relative to rest, (2) inter-regional spectral coherence. Results: During early vocalization (500-1000 ms) the SD group showed significantly larger alpha band spectral power over the left motor cortex. During late vocalization (1000-2500 ms) SD patients showed a significantly larger gamma band coherence between left somatosensory and premotor cortical areas. Conclusions: Two atypical patterns of cortical activity characterize the pathophysiology of spasmodic dysphonia during voice production: (1) a reduced movement-related desynchronization of motor cortical networks, (2) an excessively large synchronization between left somatosensory and premotor cortical areas. Significance: The pathophysiology of SD is characterized by an abnormally high synchronous activity within and across cortical neural networks involved in voice production that is mainly lateralized in the left hemisphere.

Background: Cervical vestibular evoked myogenic potential (cVEMP) testing is a strong tool that enables objective determination of balance functions in humans. However, it remains unknown whether cVEMP correctly expresses vestibular disorder in mice. Objective: In this study, correlations of cVEMP with scores for balance-related behavior tests including rotarod, beam, and air-righting reflex tests were determined in ICR mice with vestibular disorder induced by 3,3'-iminodipropiontrile (IDPN) as a mouse model of vestibular disorder. Methods: Male ICR mice at 4 weeks of age were orally administered IDPN in saline (28 mmol/kg body weight) once. Rotarod, beam crossing, and air-righting reflex tests were performed before and 3-4 days after oral exposure one time to IDPN to determine balance functions. The saccule and utricles were labeled with fluorescein phalloidin. cVEMP measurements were performed for mice in the control and IDPN groups. Finally, the correlations between the scores of behavior tests and the amplitude or latency of cVEMP were determined with Spearman's rank correlation coefficient. Two-tailed Student's t test and Welch's t test were used to determine a significant difference between the two groups. A difference with p < 0.05 was considered to indicate statistical significance. Results: After oral administration of IDPN at 28 mmol/kg, scores of the rotarod, beam, and air-righting reflex tests in the IDPN group were significantly lower than those in the control group. The numbers of hair cells in the saccule, utricle, and cupula were decreased in the IDPN group. cVEMP in the IDPN group was significantly decreased in amplitude and increased in latency compared to those in the control group. cVEMP amplitude had significant correlations with the numbers of hair cells as well as scores for all of the behavior tests in mice. Conclusions: This study demonstrated impaired cVEMP and correlations of cVEMP with imbalance determined by behavior tests in a mouse model of vestibular disorder.

To effectively interact with their environment, humans must often select actions from multiple incompatible options. Existing theories propose that during motoric response-conflict, inappropriate motor activity is actively (and perhaps non-selectively) suppressed by an inhibitory fronto-basal ganglia mechanism. We here tested this theory across three experiments. First, using scalp-EEG, we found that both outright action-stopping and response-conflict during action-selection invoke low-frequency activity of a common fronto-central source, whose activity relates to trial-by-trial behavioral indices of inhibition in both tasks. Second, using simultaneous intracranial recordings from the basal ganglia and motor cortex, we found that response-conflict increases the influence of the subthalamic nucleus on M1-representations of incorrect response-tendencies. Finally, using transcranial magnetic stimulation, we found that during the same time period when conflict-related STN-to-M1 communication is increased, cortico-spinal excitability is broadly suppressed. Together, these findings demonstrate that fronto-basal ganglia networks buttress action-selection under response-conflict by rapidly and non-selectively net-inhibiting inappropriate motor tendencies.

Objectives: The aims of this study were to systematically explore the effects of stimulus duration, background (quiet versus noise), and three consonant–vowels on speech-auditory brainstem responses (ABRs). Additionally, the minimum number of epochs required to record speech-ABRs with clearly identifiable waveform components was assessed. The purpose was to evaluate whether shorter duration stimuli could be reliably used to record speech-ABRs both in quiet and in background noise to the three consonant–vowels, as opposed to longer duration stimuli that are commonly used in the literature. Shorter duration stimuli and a smaller number of epochs would require shorter test sessions and thus encourage the transition of the speech-ABR from research to clinical practice. Design: Speech-ABRs in response to 40 msec [da], 50 msec [ba] [da] [ga], and 170 msec [ba] [da] [ga] stimuli were collected from 12 normal-hearing adults with confirmed normal click-ABRs. Monaural (right-ear) speech-ABRs were recorded to all stimuli in quiet and to 40 msec [da], 50 msec [ba] [da] [ga], and 170 msec [da] in a background of two-talker babble at +10 dB signal to noise ratio using a 2-channel electrode montage (Cz-Active, A1 and A2-reference, Fz-ground). Twelve thousand epochs (6000 per polarity) were collected for each stimulus and background from all participants. Latencies and amplitudes of speech-ABR peaks (V, A, D, E, F, O) were compared across backgrounds (quiet and noise) for all stimulus durations, across stimulus durations (50 and 170 msec) and across consonant–vowels ([ba], [da], and [ga]). Additionally, degree of phase locking to the stimulus fundamental frequency (in quiet versus noise) was evaluated for the frequency following response in speech-ABRs to the 170 msec [da]. Finally, the number of epochs required for a robust response was evaluated using F sp statistic and bootstrap analysis at different epoch iterations. Results: Background effect: the addition of background noise resulted in speech-ABRs with longer peak latencies and smaller peak amplitudes compared with speech-ABRs in quiet, irrespective of stimulus duration. However, there was no effect of background noise on the degree of phase locking of the frequency following response to the stimulus fundamental frequency in speech-ABRs to the 170 msec [da]. Duration effect: speech-ABR peak latencies and amplitudes did not differ in response to the 50 and 170 msec stimuli. Consonant–vowel effect: different consonant–vowels did not have an effect on speech-ABR peak latencies regardless of stimulus duration. Number of epochs: a larger number of epochs was required to record speech-ABRs in noise compared with in quiet, and a smaller number of epochs was required to record speech-ABRs to the 40 msec [da] compared with the 170 msec [da]. Conclusions: This is the first study that systematically investigated the clinical feasibility of speech-ABRs in terms of stimulus duration, background noise, and number of epochs. Speech-ABRs can be reliably recorded to the 40 msec [da] without compromising response quality even when presented in background noise. Because fewer epochs were needed for the 40 msec [da], this would be the optimal stimulus for clinical use. Finally, given that there was no effect of consonant–vowel on speech-ABR peak latencies, there is no evidence that speech-ABRs are suitable for assessing auditory discrimination of the stimuli used.

Prominent 7-12 Hz oscillations in frontal cortical networks in rats have been reported. However, the mechanism of generation and the physiological function of this brain rhythm have not yet been clarified. Multichannel extracellular field potentials of the ACC were recorded and analyzed using the current source density method in halothane-anesthetized rats. Spontaneous high-current spikes (HCSs) were localized in the deep part of layer II/III and upper part of layer V of the ACC. The frequency of HCSs in the ACC was 7-12 Hz, with an amplitude of 6.5 ± 0.76 mV/mm2 and duration of 55.24 ± 2.43 ms. The power density significantly decreased (84.56 ± 6.93%, p < 0.05, t test) after pinching the hindpaw and significantly increased (149.28 ± 15.96%) after treatment with morphine. The suppressive effect of pinching was reversed by naloxone (0.7 mg/kg, i.p.). HCSs coincided with initiation of the depolarization of cingulate neurons and remained in a depolarized upstate. The occurrence of cingulate HCSs was persistently preceded by a hyperpolarization phase and a burst of multiunit spike activity in the medial dorsal thalamic nucleus. Spontaneous field-potential oscillations changed from 10 Hz to a lower band (i.e., ∼7.5 Hz) when a central poststroke pain condition was induced. The central poststroke pain group had a higher average coherence coefficient compared with the control group. Our results indicate that spontaneous cingulate cortical HCSs could be initiated by thalamocortical synaptic inputs from the medial dorsal thalamic nucleus and maintained by intracortical neuronal upstate mechanisms in physiological and pathological pain states.SIGNIFICANCE STATEMENT This study elucidated the mechanism of generation and physiological function of prominent 7-12 Hz frequency oscillations in frontal cortical networks in rats. Spontaneous cingulate cortical high-current spikes in anesthetized rats could be initiated by thalamocortical synaptic inputs from the medial dorsal thalamic nucleus and maintained by intracortical neuronal upstate mechanisms. Suppression of the anterior cingulate cortex-filtered EEG during noxious stimulation may have resulted from the desynchronization of high-current spikes in the ACC. The enhancement of fast Fourier transform power after a systemic morphine injection suggested that the opioid system may play an important role in synchronizing cingulate cortical neuronal networks. Spontaneous cingulate high-current spikes may also play an important role in thalamocortical dysrhythmia in central poststroke pain.

Technology that translates neural activity into speech would be transformative for people who are unable to communicate as a result of neurological impairments. Decoding speech from neural activity is challenging because speaking requires very precise and rapid multi-dimensional control of vocal tract articulators. Here we designed a neural decoder that explicitly leverages kinematic and sound representations encoded in human cortical activity to synthesize audible speech. Recurrent neural networks first decoded directly recorded cortical activity into representations of articulatory movement, and then transformed these representations into speech acoustics. In closed vocabulary tests, listeners could readily identify and transcribe speech synthesized from cortical activity. Intermediate articulatory dynamics enhanced performance even with limited data. Decoded articulatory representations were highly conserved across speakers, enabling a component of the decoder to be transferrable across participants. Furthermore, the decoder could synthesize speech when a participant silently mimed sentences. These findings advance the clinical viability of using speech neuroprosthetic technology to restore spoken communication.

Despite extensive research on primate cognitive function, understanding how anatomical connectivity at a neural circuit level relates to information transformation across different cortical areas remains primitive. New technology is needed to visualize inter-areal anatomical connectivity in living monkeys and to tie this directly to neurophysiological function. Here, we developed a novel method to investigate this structure-function relationship, by combining optical intrinsic signal imaging (OISI) with optogenetic stimulation in living monkeys (opto-OISI). The method involves expressing channelrhodophsin-2 in one area (source) followed by optical imaging of optogenetic activations in the other area (target). We successfully demonstrated the potential of the method with interhemispheric columnar projection patterns between V1/V2 border regions. Unlike the combination of optogenetics and functional magnetic resonance imaging (opto-fMRI), opto-OISI has the advantage of enabling us to detect responses of small clusters of neurons, even if the clusters are sparsely distributed. We suggest that opto-OISI can be a powerful approach to understanding cognitive function at the neural circuit level, directly linking inter-areal circuitry to fine-scale structure and function.

The medial septum implements cortical theta oscillations, a 5-12 Hz rhythm associated with locomotion and paradoxical sleep reflecting synchronization of neuronal assemblies such as place cell sequence coding. Highly rhythmic burst-firing parvalbumin-positive GABAergic medial septal neurons are strongly coupled to theta oscillations and target cortical GABAergic interneurons, contributing to coordination within one or several cortical regions. However, a large population of medial septal neurons of unidentified neurotransmitter phenotype and with unknown axonal target areas fire with a low degree of rhythmicity. We investigated whether low-rhythmic-firing neurons (LRNs) innervated similar or different cortical regions to high-rhythmic-firing neurons (HRNs) and assessed their temporal dynamics in awake male mice. The majority of LRNs were GABAergic and parvalbumin-immunonegative, some expressing calbindin; they innervated interneurons mostly in the dentate gyrus (DG) and CA3. Individual LRNs showed several distinct firing patterns during immobility and locomotion, forming a parallel inhibitory stream for the modulation of cortical interneurons. Despite their fluctuating firing rates, the preferred firing phase of LRNs during theta oscillations matched the highest firing probability phase of principal cells in the DG and CA3. In addition, as a population, LRNs were markedly suppressed during hippocampal sharp-wave ripples, had a low burst incidence, and several of them did not fire on all theta cycles. Therefore, CA3 receives GABAergic input from both HRNs and LRNs, but the DG receives mainly LRN input. We propose that distinct GABAergic LRNs contribute to changing the excitability of the DG and CA3 during memory discrimination via transient disinhibition of principal cells.SIGNIFICANCE STATEMENT For the encoding and recall of episodic memories, nerve cells in the cerebral cortex are activated in precisely timed sequences. Rhythmicity facilitates the coordination of neuronal activity and these rhythms are detected as oscillations of different frequencies such as 5-12 Hz theta oscillations. Degradation of these rhythms, such as through neurodegeneration, causes memory deficits. The medial septum, a part of the basal forebrain that innervates the hippocampal formation, contains high- and low-rhythmic-firing neurons (HRNs and LRNs, respectively), which may contribute differentially to cortical neuronal coordination. We discovered that GABAergic LRNs preferentially innervate the dentate gyrus and the CA3 area of the hippocampus, regions important for episodic memory. These neurons act in parallel with the HRNs mostly via transient inhibition of inhibitory neurons.

Direct cortical stimulation (DCS) of primary somatosensory cortex (S1) could help restore sensation and provide task-relevant feedback in a neuroprosthesis. However, the psychophysics of S1 DCS is poorly studied, including any comparison to cutaneous haptic stimulation. We compare the response times to DCS of human hand somatosensory cortex through electrocorticographic grids with response times to haptic stimuli delivered to the hand in four subjects. We found that subjects respond significantly slower to S1 DCS than to natural, haptic stimuli for a range of DCS train durations. Median response times for haptic stimulation varied from 198 ms to 313 ms, while median responses to reliably perceived DCS ranged from 254 ms for one subject, all the way to 528 ms for another. We discern no significant impact of learning or habituation through the analysis of blocked trials, and find no significant impact of cortical stimulation train duration on response times. Our results provide a realistic set of expectations for latencies with somatosensory DCS feedback for future neuroprosthetic applications and motivate the study of neural mechanisms underlying human perception of somatosensation via DCS.

A common method for measuring changes in temporal processing sensitivity in both humans and animals makes use of GaP-induced Inhibition of the Acoustic Startle (GPIAS). It is also the basis of a common method for detecting tinnitus in rodents. However, the link to tinnitus has not been properly established because GPIAS has not yet been used to objectively demonstrate tinnitus in humans. In guinea pigs, the Preyer (ear flick) myogenic reflex is an established method for measuring the acoustic startle for the GPIAS test, while in humans, it is the eye-blink reflex. Yet, humans have a vestigial remnant of the Preyer reflex, which can be detected by measuring skin surface potentials associated with the Post-Auricular Muscle Response (PAMR). A similar electrical potential can be measured in guinea pigs and we aimed to show that the PAMR could be used to demonstrate GPIAS in both species. In guinea pigs, we compare the GPIAS measured using the pinna movement of the Preyer reflex and the electrical potential of the PAMR to demonstrate that the two are at least equivalent. In humans, we establish for the first time that the PAMR provides a reliable way of measuring GPIAS that is a pure acoustic alternative to the multimodal eye-blink reflex. Further exploratory tests showed that while eye gaze position influenced the size of the PAMR response, it did not change the degree of GPIAS. Our findings confirm that the PAMR is a sensitive method for measuring GPIAS and suggest that it may allow direct comparison of temporal processing between humans and animals and may provide a basis for an objective test of tinnitus.

Predictive coding is a theoretical framework that provides a functional interpretation of top-down and bottom-up interactions in sensory processing. The theory suggests there are differences in message passing up versus down the cortical hierarchy. These differences result from the linear feedforward of prediction errors, and the nonlinear feedback of predictions. This implies that cross-frequency interactions should predominate top-down. But it remains unknown whether these differences are expressed in cross-frequency interactions in the brain. Here we examined bidirectional cross-frequency coupling across four sectors of the auditory hierarchy in the macaque. We computed two measures of cross-frequency coupling, phase–amplitude coupling (PAC) and amplitude–amplitude coupling (AAC). Our findings revealed distinct patterns for bottom-up and top-down information processing among cross-frequency interactions. Both top-down and bottom-up interactions made prominent use of low frequencies: low-to-low-frequency (theta, alpha, beta) and low-frequency-to-high- gamma couplings were predominant top-down, while low-frequency-to-low-gamma couplings were predominant bottom-up. These patterns were largely preserved across coupling types (PAC and AAC) and across stimulus types (natural and synthetic auditory stimuli), suggesting that they are a general feature of information processing in auditory cortex. Our findings suggest the modulatory effect of low frequencies on gamma-rhythms in distant regions is important for bidirectional information transfer. The finding of low-frequency-to-low-gamma interactions in the bottom-up direction suggest that nonlinearities may also play a role in feedforward message passing. Altogether, the patterns of cross-frequency interaction we observed across the auditory hierarchy are largely consistent with the predictive coding framework.

With the advent of recent genetic technologies for mice, it is now feasible to investigate the circuit mechanisms of brain functions in an unprecedented manner. Although transgenic mice are commonly used on C57BL/6J (C57) background, hearing research has typically relied on different genetic backgrounds, such as CBA/Ca or CBA due to the genetic defect of C57 mice for early age-related hearing loss. This limits the utilization of available genetic resources for hearing research. Here we report congenic (>F10) Cre-dependent channelrhodopsin2 (ChR2) mice on CBA/Ca background. By crossing this line with Cre-driver mice on C57 background, F1 hybrids restored the hearing deficit of C57 mice. We also found a linear relationship between aging and hearing loss, with progression rates varied depending on genetic backgrounds (3.39 dB/month for C57; 0.82 dB/month for F1 hybrid). We further demonstrate that this approach allows to express ChR2 in a specific type of inhibitory neurons in the auditory cortex and that they can be identified within a simultaneously recorded population of neurons in awake mice. Thus, our Cre-dependent optogenetic transgenic mice on CBA/Ca background are a valuable tool to investigate the circuit mechanisms of hearing across lifespan.

Objective Manual detection of spike‐wave discharges (SWDs) from electroencephalography (EEG) records is time intensive, costly, and subject to inconsistencies/biases. In addition, manual scoring often omits information on SWD confidence/intensity, which may be important for the investigation of mechanistic‐based research questions. Our objective is to develop an automated method for the detection of SWDs in a mouse model of absence epilepsy that is focused on the characteristics of human scoring of preselected events to establish a confidence‐based, continuous‐valued scoring. Methods We develop a support vector machine (SVM)–based algorithm for the automated detection of SWDs in the γ2R43Q mouse model of absence epilepsy. The algorithm first identifies putative SWD events using frequency‐ and amplitude‐based peak detection. Four humans scored a set of 2500 putative events identified by the algorithm. Then, using predictors calculated from the wavelet transform of each event and the labels from human scoring, we trained an SVM to classify (SWD/nonSWD) and assign confidence scores to each event identified from 60, 24‐hour EEG records. We provide a detailed assessment of intra‐ and interrater scoring that demonstrates advantages of automated scoring. Results The algorithm scored SWDs along a continuum that is highly correlated with human confidence and that allows us to more effectively characterize ambiguous events. We demonstrate that events along our scoring continuum are temporally and proportionately correlated with abrupt changes in spectral power bands relevant to normal behavioral states including sleep. Significance Although there are automated and semi‐automated methods for the detection of SWDs in humans and rats, we contribute to the need for continued development of SWD detection in mice. Our results demonstrate the value of viewing detection of SWDs as a continuous classification problem to better understand “ground truth” in SWD detection (ie, the most reliable features agreed upon by humans that also correlate with objective physiologic measures).

Fragile X Syndrome (FXS) is a leading genetic cause of autism and intellectual disabilities. Sensory-processing deficits are common in humans with FXS and an animal model, the Fmr1 knockout (KO) mouse, manifesting in the auditory system as debilitating hypersensitivity and abnormal electroencephalographic (EEG) and event-related potential (ERP) phenotypes. FXS is a neurodevelopmental disorder, but how EEG/ERP phenotypes change during development is unclear. Therefore, we characterized baseline and stimulus-evoked EEG in auditory and frontal cortex of developing (postnatal day (P) 21 and P30) and adult (P60) wildtype (WT) and Fmr1 KO mice with the FVB genetic background. We found that baseline gamma-band power and N1 amplitude of auditory ERP were increased in frontal cortex of Fmr1 KO mice during development and in adults. Baseline gamma power was increased in auditory cortex at P30. Genotype differences in stimulus-evoked gamma power were present in both cortical regions, but the direction and strength of the changes were age-dependent. These findings suggest that cortical deficits are present during early development and may contribute to sensory-processing deficits in FXS, which in turn may lead to anxiety and delayed language. Developmental changes in EEG measures indicate that observations at a single time-point during development are not reflective of FXS disease progression and highlight the need to identify developmental trajectories and optimal windows for treatment.

Auditory stimulus reconstruction is a technique that finds the best approximation of the acoustic stimulus from the population of evoked neural activity. Reconstructing speech from the human auditory cortex creates the possibility of a speech neuroprosthetic to establish a direct communication with the brain and has been shown to be possible in both overt and covert conditions. However, the low quality of the reconstructed speech has severely limited the utility of this method for brain-computer interface (BCI) applications. To advance the state-of-the-art in speech neuroprosthesis, we combined the recent advances in deep learning with the latest innovations in speech synthesis technologies to reconstruct closed-set intelligible speech from the human auditory cortex. We investigated the dependence of reconstruction accuracy on linear and nonlinear (deep neural network) regression methods and the acoustic representation that is used as the target of reconstruction, including auditory spectrogram and speech synthesis parameters. In addition, we compared the reconstruction accuracy from low and high neural frequency ranges. Our results show that a deep neural network model that directly estimates the parameters of a speech synthesizer from all neural frequencies achieves the highest subjective and objective scores on a digit recognition task, improving the intelligibility by 65% over the baseline method which used linear regression to reconstruct the auditory spectrogram. These results demonstrate the efficacy of deep learning and speech synthesis algorithms for designing the next generation of speech BCI systems, which not only can restore communications for paralyzed patients but also have the potential to transform human-computer interaction technologies.

Active listening involves dynamically switching attention between competing talkers and is essential to following conversations in everyday environments. Previous investigations in human listeners have examined the neural mechanisms that support switching auditory attention within the acoustic featural cues of pitch and auditory space. Here, we explored the cortical circuitry underlying endogenous switching of auditory attention between pitch and spatial cues necessary to discern target from masker words. Because these tasks are of unequal difficulty, we expected an asymmetry in behavioral switch costs for hard-to-easy versus easy-to-hard switches, mirroring prior evidence from vision-based cognitive task-switching paradigms. We investigated the neural correlates of this behavioral switch asymmetry and associated cognitive control operations in the present auditory paradigm. Behaviorally, we observed no switch-cost asymmetry, i.e., no performance difference for switching from the more difficult attend-pitch to the easier attend-space condition (P→S) versus switching from easy-to-hard (S→P). However, left lateral prefrontal cortex activity, correlated with improved performance, was observed during a silent gap period when listeners switched attention from P→S, relative to switching within pitch cues. No such differential activity was seen for the analogous easy-to-hard switch. We hypothesize that this neural switch asymmetry reflects proactive cognitive control mechanisms that successfully reconfigured neurally-specified task parameters and resolved competition from other such "task sets," thereby obviating the expected behavioral switch-cost asymmetry. The neural switch activity observed was generally consistent with that seen in cognitive paradigms, suggesting that established cognitive models of attention switching may be productively applied to better understand similar processes in audition.

This paper describes a technique to assess the correspondence between patterns of similarity in the brain's response to speech sounds and the patterns of similarity encoded in phonological feature systems, by quantifying the recoverability of phonological features from the neural data using supervised learning. The technique is applied to EEG recordings collected during passive listening to consonant-vowel syllables. Three published phonological feature systems are compared, and are shown to differ in their ability to recover certain speech sound contrasts from the neural data. For the phonological feature system that best reflects patterns of similarity in the neural data, a leave-one-out analysis indicates some consistency across subjects in which features have greatest impact on the fit, but considerable across-subject heterogeneity remains in the rank ordering of features in this regard.

Neurovascular coupling, cerebrovascular remodeling and hemodynamic changes are critical to brain function, and dysregulated in neuropathologies such as brain tumors. Interrogating these phenomena in freely behaving animals requires a portable microscope with multiple optical contrast mechanisms. Therefore, we developed a miniaturized microscope with: a fluorescence (FL) channel for imaging neural activity (e.g., GCaMP) or fluorescent cancer cells (e.g., 9L-GFP); an intrinsic optical signal (IOS) channel for imaging hemoglobin absorption (i.e., cerebral blood volume); and a laser speckle contrast (LSC) channel for imaging perfusion (i.e., cerebral blood flow). Following extensive validation, we demonstrate the microscope’s capabilities via experiments in unanesthetized murine brains that include: (i) multi-contrast imaging of neurovascular changes following auditory stimulation; (ii) wide-area tonotopic mapping; (iii) EEG-synchronized imaging during anesthesia recovery; and (iv) microvascular connectivity mapping over the life-cycle of a brain tumor. This affordable, flexible, plug-and-play microscope heralds a new era in functional imaging of freely behaving animals.

How does the human brain rapidly process incoming information in working memory? In growing divergence from a single-region focus on the prefrontal cortex (PFC), recent work argues for emphasis on how distributed neural networks are rapidly coordinated in support of this central neurocognitive function. Previously, we showed that working memory for everyday "what," "where," and "when" associations depends on multiplexed oscillatory systems, in which signals of different frequencies simultaneously link the PFC to parieto-occipital and medial temporal regions, pointing to a complex web of sub-second, bidirectional interactions. Here, we used direct brain recordings to delineate the frontoparietal oscillatory correlates of working memory with high spatiotemporal precision. Seven intracranial patients with electrodes simultaneously localized to prefrontal and parietal cortices performed a visuospatial working memory task that operationalizes the types of identity and spatiotemporal information we encounter every day. First, task-induced oscillations in the same delta-theta (2-7 Hz) and alpha-beta (9-24 Hz) frequency ranges previously identified using scalp electroencephalography (EEG) carried information about the contents of working memory. Second, maintenance was linked to directional connectivity from the parietal cortex to the PFC. However, presentation of the test prompt to cue identity, spatial, or temporal information changed delta-theta coordination from a unidirectional, parietal-led system to a bidirectional, frontoparietal system. Third, the processing of spatiotemporal information was more bidirectional in the delta-theta range than was the processing of identity information, where alpha-beta connectivity did not exhibit sensitivity to the contents of working memory. These findings implicate a bidirectional delta-theta mechanism for frontoparietal control over the contents of working memory.

Evidence shows that selective attention to visual stimuli modulates the gain of cochlear responses, probably through auditory-cortex descending pathways. At the cerebral cortex level, amplitude and phase changes of neural oscillations have been proposed as a correlate of selective attention. However, whether sensory receptors are also influenced by the oscillatory network during attention tasks remains unknown. Here, we searched for oscillatory attention-related activity at the cochlear receptor level in humans. We used an alternating visual/auditory selective attention task and measured electroencephalographic activity simultaneously to distortion product otoacoustic emissions (a measure of cochlear receptor-cell activity). In order to search for cochlear oscillatory activity, the otoacoustic emission signal, was included as an additional channel in the electroencephalogram analyses. This method allowed us to evaluate dynamic changes in cochlear oscillations within the same range of frequencies (1-35 Hz) in which cognitive effects are commonly observed in electroencephalogram works. We found the presence of low frequency (<10 Hz) brain and cochlear amplifier oscillations during selective attention to visual and auditory stimuli. Notably, switching between auditory and visual attention modulates the amplitude and the temporal order of brain and inner ear oscillations. These results extend the role of the oscillatory activity network during cognition in neural systems to the receptor level.