Electrophysiology publications

The mammillary body (MB) has traditionally been regarded as a relay station for the hippocampus and plays a pivotal role in the Papez circuit. However, its molecular and cellular organization remains inadequately characterized. This study focuses on the horizontally symmetrically distributed neurotensin (Nts)-expressing and nitric oxide synthase 1 (Nos1)-expressing neurons in the MB, demonstrating that Grik4 (encoding a high-affinity kainate receptor subunit) underlies their distinct electrophysiological properties. Within neural circuits, Nts and Nos1 neurons receive excitatory inputs from the ventral subiculum and send parallel excitatory projections to the dorsomedial and ventrolateral subdivisions of the anteroventral thalamus (AV). These 2 cell type-specific circuits are essential for working memory and exhibit selective activation during the maintenance phase with a marked temporal difference. Together, our findings establish a direct link from molecular identity to circuit architecture and cognitive processing by demonstrating that molecularly distinct Nts and Nos1 neurons constitute differential circuits with convergent inputs, divergent outputs, and dissociable roles in working memory maintenance. This work thus reveals a fundamental cross-scale organizational principle—molecule, cell, circuit, function—within the MB.

The mismatch response (MMR) is a critical neural indicator of the discrimination of speech contrasts. Previous research has demonstrated that language experience can affect MMRs: speech contrasts in one’s native language differ from nonnative speech contrasts. This effect is observed as early as 11–12 months, but not at 6–7 months, reflective of early learning of speech sounds. Yet, many challenges remain when using MMRs to study speech learning in infants, including prolonged recording time, inefficient use of data, and a lack of reconciliation of MMR recorded using different technologies (i.e., EEG vs. magnetoencephalography [MEG]). Using an improved recording paradigm and analysis approach, the current study addressed these challenges by examining (1) whether MEG-MMR is linked to the well-established EEG-MMR in the same adults and (2) whether our methods capture the difference in MEG-MMR between native and nonnative speech contrasts in adults and (3) in older infants. Results from 18 adults with simultaneous M/EEG demonstrated a high correlation between the MEG-MMR and the EEG-MMR. Additionally, MEG-MMRs to native speech contrasts were different from ones to nonnative speech contrasts, replicating spatiotemporal patterns documented in the existing literature. Finally, we replicated this effect in the MEG-MMR in 14 infants aged between 9 and 14 months using the same methods. These findings validate our new methodologies with less than 15 mins of recording time for acquiring and analyzing speech-related MMRs across ages, paving the way for studying early language development, and improving early detection of language-related disorders.

Physical exercise acutely improves hippocampus-dependent memory. Whereas animal studies have offered cellular- and synaptic-level accounts of these effects, human neuroimaging studies show that exercise improves hippocampal-cortical connectivity at the macroscale level. However, the neurophysiological basis of exercise-induced effects on hippocampal-cortical circuits remains unknown. Experimental evidence supports the idea that hippocampal sharp wave-ripples (SWR) play a critical role in learning and memory. Coupling between SWRs in the hippocampus and neocortex may reflect modulations in inter-regional connectivity required by mnemonic processes. Here, we examine the hypothesis that exercise modulates hippocampal-cortical ripple dynamics in the human brain. We performed intracranial recordings in epilepsy patients undergoing pre-surgical evaluation, during awake resting state, before and after an exercise session. Exercise increased ripple rate in the hippocampus. Exercise also enhanced the coupling and phase-synchrony between cortical ripples in the limbic and the default mode (DM) cortical networks and hippocampal SWRs. Further, a higher heart rate during exercise, reflecting exercise intensity, was related to a subsequent increase in resting state ripples across specific cortical networks, including the DM network. These results offer the first direct evidence that a single exercise session elicits changes in ripple events, a well-established neurophysiological marker of mnemonic processing. The characterisation and anatomical distribution of the described modulation points to hippocampal ripples as a potential mechanism by which exercise elicits its reported short-term effects in cognition.

In everyday settings, information processing depends on attentional focus, available cognitive resources, and stimulus characteristics such as its valence. Despite insights from laboratory studies, multisensory information processing in complex, realistic environments remains poorly understood. Using whole-head magnetoencephalography and eye tracking in a driving simulation, we addressed two research questions: (1) What are the distinct signatures of (socio-)emotional speech processing and visuo-spatial cognition in the dual task of driving and listening and (2) is information processing co-modulated by valence of speech and workload? We hypothesised two antagonistic processing modes: A top-down guided mode for (socio-)emotional speech processing and a bottom-up stimulus-driven mode for visuo-spatial cognition under high workload. A third mode was proposed to regulate emotional interference during driving under high visuo-spatial load and limited cognitive capacity. Its involvement is hypothesised to be co-modulated by valence and workload. Spatial clustering of oscillatory source activity supported the hypotheses: During emotional compared with neutral speech, parietal beta-band power increased, which likely supported processes related to predictive listening and socio-emotional cognition. In this top-down guided mode, driving-related activity decreased, as indicated by greater parietal alpha- and reduced gamma-band power. During high visuo-spatial workload, linked to the bottom-up stimulus-driven mode, gamma-band power increased in motor and orbitofrontal cortices, whereas beta-band power decreased in motor and temporo-parietal regions. Moreover, increased pupil dilation and decreased gaze dispersion were associated with this bottom-up stimulus-driven mode and visuo-spatial cognitive demands. Multivariate pattern analyses identified the third regulatory mode reflected in fronto-temporal gamma-band oscillations. It was co-modulated by valence and workload: Under low workload drives, gamma-band activity increased for negative compared with positive speech, pointing to the recruitment of inhibitory control processes. Under high workload drives with heightened visuo-spatial demands, gamma-band activity increased for positive speech, but decreased for negative speech, suggesting reduced cognitive resources and impaired control. To conclude, we found converging evidence of distinct signatures for (socio-)emotional speech, visuo-spatial cognition, and interference regulation in naturalistic multisensory environments. We propose that the top-down guided mode represents anticipatory listening and socio-emotional cognition, whereas the bottom-up stimulus-driven mode reflects the allocation of resources to driving-related spatial and sensorimotor processing but also cognitive strain under heightened task demands. Fronto-temporal gamma oscillations likely enable flexible up- and down-regulation of emotional speech processing in response to potential interference in complex, naturalistic environments.

The non-rapid-eye movement (NREM) sleep power spectrum is composed of rhythmic and arrhythmic components, respectively associated with brain rhythms and scale-free dynamics. Both components are hypothesized to represent distinct processes underlying sleep-dependent memory consolidation as well as other brain complex processes. Recent advancements in spectral parametrization techniques and the use of multifractal models have enabled new insights into these components and their connection to brain networks. Aging impacts NREM sleep oscillations, but no animal studies considered the impact of age on rhythmic and arrhythmic components. In this study, we assessed the effects of age on the power spectrum and its two components using local field potential recordings in mice. We recorded across the cerebral cortex and within the hippocampus—a central brain hub involved in NREM sleep-dependent cognitive processing. Ten younger (7.6 months) and eleven older (15.7 months) C57BL/6 J male and female mice were continuously recorded over a 24-hour period. We extracted the NREM sleep standard and rhythmic spectra, controlled for scale-free activity, and estimated multifractal arrhythmic properties during NREM sleep using the Wavelet Leader and Bootstrap based MultiFractal analysis toolbox. Older mice showed specific alterations in both components compared to younger animals: reduced rhythmic gamma power in the anterior cortex, greater regional differentiation of scaling exponents, and higher multifractal dispersion of the arrhythmic component in the hippocampus. These findings demonstrate that aging alters rhythmic and arrhythmic properties of NREM sleep in distinct brain regions, suggesting that both contribute to age-related changes in sleep-dependent cognition.

The clinical use of alternating current stimulation (ACS) has been confounded by heterogeneity in patient responses. Optimization of this treatment requires understanding the dependence of neuronal responses on ACS parameters. We sought to characterize neuronal responses across varying ACS frequencies and amplitudes and assess the extent to which changes in neuronal activity persist beyond the cessation of the stimulation, thereby informing ACS optimization pathways and evaluating the potential for sustained neuromodulation. We delivered subcutaneous ACS while recording intracortical electrophysiological activity in adult rats. We applied ACS for 1 or 20 minutes and analyzed ensuing spiking activity, power spectra, and low-frequency to high-frequency phase–amplitude coupling (LF-HF PAC). Both durations of ACS elicited a modulation of firing patterns (either in rate or entrainment) in most neurons, in a stimulation frequency- and amplitude-dependent manner. Changes in firing rate were more frequent, albeit modest, whereas changes in entrainment were rarer, but pronounced. Increasing ACS amplitude or frequency increased the degree of entrainment. Further, entrainment changes persisted beyond the 20-minute ACS, at half their online level. Neuronal power and LF-HF PAC increased proximal to excited, but decreased near suppressed neurons. Neuronal entrainment was observed alongside decreased power and LF-HF PAC. The prominent entrainment response to prolonged high-frequency ACS observed here supports the potential of ACS for facilitating signal integration and promoting functional reorganization via spike timing-dependent plasticity. In turn, we found broader temporal windows of excitation under low ACS frequencies engendered greater variability in spike timing, which may be utilized to reduce hypersynchronous or task-irrelevant activity.

Background: Electrical stimulation targeting the motor thalamus (Mthal) represents an emerging strategy for regulating motor cortical activity patterns, however the fundamental mechanisms and optimal stimulation configurations are not well established. Objective: To characterize how burst Mthal stimulation modulates cortical activity and to identify stimulation parameters that maximize cortical co-firing via thalamocortical rebound mechanisms. Methods: We conducted acute electrophysiological experiments in anesthetized rats using Mthal stimulation with systematically manipulated burst stimulation parameters (i.e., number of pulses and pulse width) in the low-frequency band (1-8 Hz) modulation cycle. Cortical responses across large areas covering primary and secondary motor cortex were recorded. Additionally, intracortical recordings were performed for detailed spike activity monitoring during stimulation. Cortical activity patterns in local field potentials and spike activity were analyzed to quantify the effects of Mthal stimulation on motor cortex. Computational thalamocortical circuit models were employed to explore the mechanistic basis of frequency-selective modulation effects. Results: Burst Mthal stimulation elicited tunable cortical excitation, with optimal modulation achieved at 3-4 Hz. This preferred frequency corresponded to the natural rebound timing of thalamocortical (TC) cells and generated maximal cortical co-firing and synchronization. Higher stimulation frequencies (e.g., 8 Hz) resulted in suppressed and diminished responses. Computational modeling further validated that the cellular mechanism of the TC cell rebound excitation leads to frequency-dependent cortical modulation. Conclusion: Burst Mthal stimulation demonstrates frequency-selective modulation of cortical network excitability, with 3-4 Hz protocols providing optimal enhancement of synchronized activity through exploitation of thalamocortical rebound dynamics. These results establish motor thalamic stimulation as a promising and efficient methodology for precise cortical network control and offer mechanistic foundations for developing therapeutic neuromodulation interventions aimed at motor system rehabilitation.

Transcranial Focused Ultrasound Stimulation (tFUS) is a promising non-invasive technique capable of modulating brain activity with high spatial precision. However, its efficacy for seizure suppression requires further exploration. This study aims to address whether tFUS of white matter can suppress seizures non-invasively. Repeated injections of a 4-Aminopyridine (4-AP) cocktail into the right somatosensory cortex (S1) induced cortical seizures in male rats under anesthesia with recording of both EEG and intracranial signals. Approximately one hour of tFUS was applied to the corpus callosum (CC) using a 128-element random-array transducer with 20 ms pulse duration, 1 Hz pulse repetition frequency, 2% duty cycle, and ~127 kPa pressure. Another 2-3 hours were used to assess post-stimulation effects. Seizure duration, seizure count, percent time in seizure, and inter-seizure interval were compared to a sham control for quantifying efficacy. The absolute frequency power, asymmetry index (AI), and phase lag index (PLI) were calculated to analyze brain activity changes induced by tFUS. CC tFUS can significantly reduce percent time in seizure, seizure duration, and seizure count, as well as increase inter-seizure interval. These effects extended up to 2 hours post-stimulation. We also observed a decrease in absolute power of the beta band and changes in the brain network, as evidenced by a decrease in synchronization and an improvement in interhemispheric balance. Our study is the first to show that white matter tFUS can significantly suppress seizures with a lasting post stimulation effect, potentially providing a safer alternative for drug-resistant epilepsy patients.

Large language models (LLMs) capture long-range contextual structure in natural language and have recently been shown to align with the human brain’s contextualized linguistic encoding. This makes them a promising computational probe for studying how context-dependent linguistic information is represented during natural speech perception. Speech perception often occurs in multi-talker environments, where attention must dynamically select among competing streams, yet how contextual information from attended and unattended speech is neurally encoded remains underexplored. Here, we investigate how auditory attention modulates neural tracking of context-dependent linguistic representations using electrocorticography (ECoG) and stereoelectroencephalography (sEEG) recordings from three epilepsy patients engaged in a two-conversation “cocktail party” paradigm. To model neural responses to attended and unattended speech streams, we used contextual word embeddings generated by large language models. We find that LLM-derived features reliably predict brain activity for the attended stream and that contextual information from the unattended stream also contributes to neural prediction. Importantly, these contributions extend beyond low-level acoustic features and shallow syntactic information, and depend on the surrounding linguistic context. Moreover, neural tracking of the unattended stream reflects shorter-range contextual integration than that of the attended stream. Together, these findings indicate that neural responses to speech reflect context-dependent linguistic representations from multiple concurrent speech streams, with attention modulating the depth and timescale of contextual integration. Our results highlight the utility of LLMs for probing higher-level linguistic representations in complex, naturalistic listening environments.

Objectives: Cisplatin is an effective anticancer drug that can induce cochleotoxicity in up to 50 to 60% of treated patients. However, the vestibulotoxic potential of cisplatin remains unclear. Our lab previously developed a multicycle model of cisplatin administration in mice that results in hearing loss similar to that observed clinically. The purpose of this study was to comprehensively characterize the functional and morphological consequences of cisplatin on the vestibular periphery in this mouse model. Design: Twenty-nine adult CBA/CaJ mice were assigned to control or cisplatin-treated groups. Cisplatin-treated mice received three consecutive cycles of once-daily cisplatin for 4 days followed by a 10-day recovery period. Mice underwent vestibular sensory evoked potential testing before cisplatin administration, after the final cycle of cisplatin, and 6 mo after treatment cessation. Mice also underwent vestibulo-ocular reflex testing and vestibular afferent single-unit recordings 6 mo after treatment cessation. Following testing, utricles, saccules, and horizontal semicircular canals were microdissected, and vestibular morphology was examined. To examine whether our data in mice were consistent with reports of cisplatin-induced vestibulotoxicity in patients, histopathology reports of human temporal bones were examined for evidence of cisplatin-induced vestibulotoxicity. Results: Vestibular sensory evoked potential thresholds were significantly elevated in cisplatin-treated mice immediately after cessation of cisplatin administration and progressively worsened 6 mo later. Rotational and translational vestibulo-ocular reflexes were generally unaffected by cisplatin. Cisplatin did not cause statistically significant changes in the spontaneous firing rates of semicircular canal afferents but did cause significant decreases in their overall regularity. No statistically significant differences in the spontaneous firing rates or regularity of otolith afferents were observed. However, cisplatin-treated mice exhibited statistically significant decreases in the percentage of low-distortion otolith afferents, indicating that responses of these afferents to head translations were more variable and less precise. Cisplatin-treated mice showed significantly decreased hair cell numbers in the saccule but not in the utricle or horizontal semicircular canal. One temporal bone histopathology report from an individual treated with high cumulative cisplatin was consistent with the results of our study, showing only saccular degeneration with normal utricle and semicircular canal morphology. Conclusions: Our study demonstrates cisplatin’s potential to affect the vestibular end organs adversely and differentially. The saccule was uniquely susceptible in our mouse model, suggesting that it may be possible to screen for cisplatin-induced vestibulotoxicity by testing saccular function. While very little is known about the potential for progression of cisplatin-induced vestibulotoxicity, our results suggest vestibular dysfunction may continue to worsen after cessation of cisplatin treatment. We recommend that ongoing and future efforts at evaluating vestibular function in patients treated with cisplatin include monitoring and evaluation of otolith function.

Selective activation of small versus large diameter nerve fibers represents a broad challenge in the electrical modulation of neural activity for clinical applications. For example, off-target activation of motor nerve fibers was implicated in several failed vagus nerve stimulation (VNS) clinical trials by effectively limiting maximum applicable current amplitudes, thereby preventing robust activation of smaller diameter fibers responsible for therapeutic effects. Kilohertz high-frequency (HF) block is one of several strategies proposed to overcome this gap, but has yet to be thoroughly investigated in large, multifascicular, mixed nerves comparable in scale to humans. Here, we evaluated effects of HF block on the neural, muscular, and cardiac responses evoked by traditional low-frequency (LF) VNS in a large animal (swine) model. We found that HF selectively blocks neural fibers, and their associated physiological responses, in a size dependent manner with a high degree of specificity and establish initial thresholds for achieving block in large multifascicular nerves. Critically, we demonstrate that appropriately titrating HF amplitude can eliminate off-target LF-evoked motor responses while preserving activation of smaller diameter fibers targeted by clinical VNS. Beyond VNS, these data establish HF as a potentially viable strategy in any neuromodulation therapies where off-target activation of large diameter fibers limits therapeutic efficacy.

The hippocampus is classically linked to memory, yet increasing evidence points to a broader role in perceptual inference and deviance detection. Predictive coding theories propose that perception minimizes mismatches between expected and actual sensory input, expressed in neural signatures such as mismatch negativity (MMN) and P300. Although MMN arises mainly from sensory and prefrontal cortices, the hippocampus is anatomically interconnected with both and may also contribute to prediction error processing. We recorded single- and multi-unit activity and local field potentials (LFPs) from DG and CA1 in urethane-anesthetized rats during an auditory oddball paradigm and a no-repetition control sequence to dissociate prediction error from repetition suppression. Approximately 20% of hippocampal neurons were sound responsive, and a subset showed deviant selectivity. Spiking activity predominantly reflected prediction errors, while LFPs revealed complementary contributions from repetition suppression and prediction error. Early LFP components were enhanced for randomly presented deviants, whereas later components within the P300 latency range were stronger for predictable deviants, indicating temporally distinct phases of error signaling and top-down modulation. These findings identify the hippocampus as an active contributor to auditory deviance detection and support a hierarchical model in which hippocampal circuits participate in predictive sensory processing beyond memory.

The axon initial segment (AIS) is the site of action potential generation and exhibits structural and functional plasticity upon adaptation of neuronal excitability and disease. Performing in vivo longitudinal two-photon imaging of AIS in the medial prefrontal cortex of male mice, we reveal dynamic AIS remodeling during associative fear learning and extinction. These results demonstrate that AIS plasticity is not only crucial for homeostatic adaptation but also a hallmark of memory formation.

Primate societies rely on the production and interpretation of social signals, in particular those displayed by the face. Facial movements are controlled, according to the dominant neuropsychological schema, by two separate circuits, one originating in medial frontal cortex controlling emotional expressions, and a second one originating in lateral motor and premotor areas controlling voluntary facial movements. Despite this functional dichotomy, cortical anatomy suggests that medial and lateral areas are directly connected and may thus operate as a single network. Here, we test these contrasting hypotheses through structural and functional MRI (fMRI) guided electrical stimulation and simultaneous multichannel recordings from key facial motor areas in the macaque monkey brain. These areas include medial facial motor area M3 (located in the anterior cingulate cortex); two lateral face-related motor areas: M1 (primary motor) and PMv (ventrolateral premotor); and S1 (primary somatosensory cortex). Cortical responses evoked by intracortical stimulation revealed that medial and lateral areas can exert significant functional impact on each other. Simultaneous recordings of local field potentials in all facial motor areas further confirm that during facial expressions, medial and lateral facial motor areas significantly interact, primarily in the alpha and beta frequency ranges, whereas during voluntary chewing, coupling occurs at lower frequencies. These functional interactions varied across facial movement types. Thus, at the cortical level, the control of facial movements is not mediated through independent (medial/lateral) functional streams, but results from an interacting sensorimotor network.

Vasomotion, vascular oscillations at ~ 0.1 Hz, may serve as a biomarker and therapeutic target for neurodegenerative diseases, but its origins, structure across brain vasculature, and correlation with neural activity remain unclear. This study examined the spatiotemporal characteristics of cerebral vasomotion and its relationship to neural activity in anaesthetised Hooded Lister rats using simultaneous recordings of neuronal activity and haemodynamics in motor and whisker barrel cortices. In a subset of rats, tissue oxygen was also measured. Blood pressure was pharmacologically modulated to alter vascular oscillations. We found that vasomotion was driven by the arterial tree. Two prominent activity patterns emerged: fast vasomotion across the entire hemisphere and slow vasomotion seen as a travelling wave running through the surface arteries. Moreover, vasomotion was associated with low tissue oxygen and was largely independent of spontaneous neural activity and therefore not a product of neurovascular coupling.

Understanding how the brain rapidly processes neural information through large-scale network dynamics is fundamental to neuroscience. Resting-state fMRI (rsfMRI) captures networks by probing spontaneous neural activity fluctuations, yet whether these networks can accommodate fast, sensitive information processing remains unknown. Here, we reveal brain-wide rsfMRI network dynamics (i.e., states and their transitions) that enable fast information processing through rapid activity-triggered network reconfiguration in male rats. Following activation of a single optogenetically evoked somatosensory thalamic input, states and transitions associated with internally-oriented information processing are quickly suppressed and diverted through basal forebrain and hypothalamus to strengthen externally-oriented (i.e., sensory) processes. Simultaneous rsfMRI and electrophysiology measurements in somatosensory and cingulate cortices demonstrate that intra-regional wide-band and inter-regional narrow-band (i.e., slow-oscillations) neural activity synchronizations directly drive rsfMRI network dynamics and reconfiguration to support fast processing of single thalamic input. Our study uncovers fast interactions between neural activity and rsfMRI networks in processing single neural input.

Purpose Although human temporal bones suggest that cochlear synapse numbers decline with age and noise exposure, no validated diagnostic method exists. In animal models, cochlear synaptopathy is associated with reduced auditory brainstem response (ABR) wave 1 amplitude and envelope following response (EFR) magnitude for a sinusoidally amplitude modulated (SAM) tone. However, measuring SAM EFR at the optimal modulation frequency (1000 Hz) is difficult in humans. A rectangular amplitude modulated (RAM) tone may be more sensitive to synaptopathy, but this has not been validated in animals. In addition, because synaptopathy likely co-occurs with outer hair cell dysfunction (OHC), a diagnostic assay needs to be robust to abnormal auditory thresholds. The objective of this study was to evaluate the relative ability of ABR and EFR measures to predict synapse numbers in mice with varying degrees of synaptopathy and OHC dysfunction. Methods Distortion product otoacoustic emissions (DPOAEs), ABR, SAM EFR, and RAM EFR were recorded from 57 mice with a range of auditory thresholds and degrees of synaptopathy. Cross-validation was used to compare the relative ability of linear regression models incorporating different measures to predict synapse numbers. Predictions were confirmed histologically. Results RAM EFR modulated at 1000 Hz was the single best predictor of synapse numbers for broad synapse loss across frequency, while combining RAM EFR with ABR further improved predictions. In contrast, ABR best predicted focal synaptopathy. Incorporating DPOAEs improved predictions for EFR, but not ABR. Conclusion RAM EFR, ABR, and DPOAEs should be used in the future when predicting synapse numbers.