Publications using the RZ2

Auditory areas on the superior temporal plane and lateral convexity are key initial stages of speech processing in the human cortex, representing acoustic and phonetic attributes in a temporally precise manner. More complex representations in auditory-related cortex along the ventral and dorsal processing streams and prefrontal cortex are associated with perception and action. In this study, we used intracranial electroencephalography (iEEG) to clarify where and how activity leading to perceptually driven behavioral events emerges. Participants were patients undergoing iEEG monitoring for medically intractable epilepsy. Stimuli were monosyllabic words, and participants pressed a button in response to a semantic target category. Significant high gamma activity after stimulus onset and immediately prior to motor response defined stimulus- and behavior-related activity patterns, respectively. The stimulus-related pattern was more common than behavior-related throughout the cortical auditory hierarchy as well as sensorimotor cortex. Behavior-related activity was sparsely represented, with the highest prevalence in the prefrontal cortex and a more limited representation in anterior temporal and parieto-occipital cortex. Hemispheric asymmetries included a higher prevalence of stimulus-related activity in the right sensorimotor cortex and a higher prevalence of the behavior-related pattern in the left prefrontal cortex. Faster behavioral responses were associated with greater stimulus-locked high gamma power in non-core auditory, prefrontal, and premotor cortex. Results reveal the cortical distribution of sensory stimulus-driven responses and activity time-locked to behavior and provide insights into neural substrates of speech perception.

Stimulation of sensory vagal pathways is typically delivered via invasive, cervical vagus nerve stimulation (cVNS) or noninvasive, trans-auricular nerve stimulation (taNS). While both methods are investigated therapeutically, their effects on brain physiology remain poorly understood, hindering mechanistic insights and stimulus optimization. In 6 awake nonhuman primates, we recorded cortical vagal-evoked potentials (VEPs) from subdural electrodes placed in prefrontal, sensorimotor and parietal cortical areas, in response to cVNS or taNS. Across 478 different taNS and cVNS protocols, we varied stimulation side, intensity, frequency, pulse count, and pulse width and assessed independent effects on amplitude and latency of early (EC; 30-100 ms), intermediate (IC; 101-200 ms) and late components (LC; 201-500 ms) of VEPs. Fixed and random effects of stimulation parameters and subjects, respectively, on VEPs were assessed using a linear mixed-effects model. Overall, cVNS elicits more robust VEPs than taNS, with larger EC, IC and LC amplitudes, in both hemispheres. cVNS-elicited ECs and LCs are largest in PFC and PC areas, whereas ICs are largest in SM areas. On the other hand, taNS generally does not elicit area-specific responses. cVNS-elicited ECs have slower latency than ta-NS elicited ECs. Higher stimulation frequencies and intensities and a longer pulse width elicit larger ECs and ICs for cVNS, and to some extent for taNS. Both short and long cVNS trains elicit stronger ECs, and long trains elicit slower ICs. Earlobe stimulation elicits VEPs that partially overlap with those from taNS. In conclusion, cVNS and taNS elicit cortical VEPs in a manner consistent with distinct engagement of ascending vagal pathways, with both similarities and differences in the effects of stimulation parameters on evoked responses.

S ummary Although somatosensation is known to be important for precise hand control, how coordinated activity across sensory and motor cortical areas supports hand movements and object interactions is unclear. We simultaneously recorded neural activity from dorsal premotor cortex (PMd) and Area 2 of the primary somatosensory cortex in three rhesus macaques performing a reach-to-grasp task during recovery from a primary motor cortex (M1) lesion. Using dual-area latent factor analysis, we decomposed population activity into cross-area factors (CFs) shared between PMd and Area 2 and within-area factors (WFs) local to each region. Shared CFs tracked hand kinematics closely despite explaining less overall variance. Strikingly, the emergence of long-timescale, stereotyped sensory–motor cross-area dynamics was correlated with recovery of prehension and object grasping, whereas changes in within-area dynamics were not correlated with recovery. These findings suggest that restoration of coordinated sensory–motor population dynamics is important for recovery of skilled hand function after injury.

Humans and other animals can solve new problems, even on the first attempt. This capacity to generate novel problem-solving behavior has been hypothesized to depend on brain mechanisms for recombining units of knowledge using systems of procedural rules, or grammars . Yet, whether and how the brain represents and implements grammars remains unclear, in large part due to the lack of neural recordings (typically performed in animal models) during grammar-based problem solving (typically studied in humans). Here, we address that gap, and in turn identify an underlying neural basis of grammatical behavior. We designed a visual–motor construction task in which macaque monkeys trace complex, often novel, geometric figures by generating a sequence of strokes, each a distinct shape, like a circle, dash, or chevron (action symbols 1 ). Critically, sequencing was guided by a learned hierarchical action grammar A n B m C k , meaning “repeat shape A, then repeat shape B, then repeat shape C”, where the number of repetitions (n, m, and k) varied across problems. Behavior was internally generated (no cues guiding stroke order), problem-directed (to construct a specific image), and exhibited zero-shot generalization (successful on the first trial for novel problems, including harder ones)--key hallmarks of grammar use. To identify underlying neural substrates, we recorded from multiple frontal cortical areas previously implicated in rule use or action sequencing. Activity during drawing encoded key structural properties of the action grammar: (i) shape index (A, B, C), (ii) abstract role (e.g., the role A independent of the specific shape), and (iii) ordinal position within a shape repeat. Moreover, all three properties were strongest in a single region, the pre-supplementary motor area (preSMA). We suggest the possibility that this conjunction of representations is a signature of an implementation of an iterative algorithm resembling a “for-loop” program: internally tracking how many repetitions remain for each shape index and switching to the next when complete. Our study establishes a paradigm for studying the neural basis of grammar-guided novel behavior and identifies in preSMA a dynamic representation of grammatical structure supporting such behavior.

Psychedelics lead to profound changes in subjective experience and behaviour, which are typically conceptualised in psychological terms rather than corresponding to an altered brain state or a distinct state of vigilance. Here, we performed chronic electrophysiological recordings from the neocortex concomitant with pupillometry in freely moving adult male mice following an injection of a short-acting psychedelic 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT). We report an acute induction of a dissociated state, characterised by prominent slow oscillations in the cortex and marked pupil dilation in behaviourally awake, moving animals. REM sleep was initially markedly suppressed, but was overcompensated in the subsequent 48 hours, while administration of 5-MeO-DMT immediately after sleep deprivation attenuated the subsequent rebound of sleep slow-wave activity. We argue that the occurrence of a dissociated state combining features of waking and sleep may fundamentally underpin the known and hypothesised effects of psychedelics — from dream-like hallucinations to reopening of the critical period for plasticity.

Parvalbumin-expressing inhibitory neurons (PVNs) stabilize cortical network activity, generate gamma rhythms, and regulate experience-dependent plasticity. We found that PVNs act like a volume knob in the mouse auditory cortex (ACtx), bi-directionally adjusting neural and perceptual sensitivity to sound level over a 20 dB range. PVN-based gain adjustments were "sticky," such that a single bout of PVN activation at 40 Hz-but not at 1 or 70 Hz-sustainably dampened ACtx sound responsiveness, enhanced feedforward inhibition, and behaviorally desensitized mice to loudness. We then developed a mouse model of adult-onset hyperacusis by demonstrating ACtx hyperactivity, PVN hypofunction, and loudness hypersensitivity following a restricted noise-induced cochlear lesion. We found that several minutes of 40-Hz PVN stimulation in noise-exposed mice sustainably dampened ACtx hyperactivity and restored normal loudness sensitivity for 1 week. These findings demonstrate that sensory disorders caused by permanent peripheral injuries can be reversed by patterned stimulation of cortical circuits that directly regulate perception.

Basal forebrain cholinergic neurons (BFCNs) densely innervate auditory cortex (ACtx), conveying signals linked to internal brain states and external sensory cues. Acetylcholine (ACh) is known to rapidly modulate cortical circuits through nicotinic ACh receptor (nAChR)-mediated activation of layer 1 inhibitory neurons (L1-INs). However, BFCN terminals are also abundant in deeper layers, where their functional impact has received less attention. Using multi-plex in situ labeling across cortical layers and cell types, we found that layer 6 pyramidal neurons (L6-PNs) are highly enriched in diverse transcripts for nAChR subunits and muscarinic ACh receptors (mAChRs). In vivo optogenetic activation of BFCN axons revealed persistent modulation of regular spiking units in L2-6 but a rapid phasic activation only in L6. In acute slices, optogenetic activation of BFCN axons elicited fast nAChR-mediated excitatory post-synaptic potentials in L6-PNs, comparable to responses in L1-INs, and slower mAChR-mediated inhibitory responses. These findings identify L1-INs and excitatory L6-PNs as two major hubs for BFCN modulation of cortical circuits. By recruiting distinct receptor mechanisms and circuit motifs in L1 and L6, BFCNs may engage parallel pathways of cholinergic control that couple fast, transient modulation with slower, sustained regulation to shape cortical perception and plasticity.

Speech production entails several processing steps that encode linguistic and articulatory structure, but whether these computations correspond to spatiotemporally discrete patterns of neural activity is unclear. To address this issue, we use electrocorticography to directly measure the brains of neurosurgical participants performing an interactive speech paradigm. We observe a broad range of cortical modulation profiles, and subsequent clustering analyses establish that responses comprised distinct classes associated with sensory perception, planning, motor execution, and task-related suppression. These activity classes are also localized to separate neural substrates, indicating their status as specialized networks. We then parse dynamics in the planning and motor networks using unsupervised dimensionality reduction, which reveals subnetworks that are sequentially active throughout preparation and articulation. These results therefore support and extend a localizationist model of speech production where cortical activity "flows" within and across discrete pathways during language use.

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.

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.

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.

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.

The hypothalamus is critical for regulating behaviors essential for survival and locomotion, but how it integrates internal needs and transmits locomotion commands to the spinal cord (SC) remains unclear. We found that glutamatergic neurons in lateral hypothalamic area (LHA) are essential for regulating motivated locomotor activity. Using single-neuron projectome analysis, trans-synaptic tracing, and optogenetic manipulation, we showed that LHA facilitates motivated locomotion during food seeking via pontine reticular nucleus, oral part (PnO) projection neurons, rather than direct SC projections or indirect stress signaling via medial septum and diagonal band. Activating PnO-SC projection neurons also initiated locomotion. Importantly, LHA-PnO projection neurons were crucial for regulating locomotor recovery following mouse spinal cord injury (SCI). Motor cortex signals gated LHA deep brain stimulation treatment markedly promoted long-term restoration of hindlimb motor functions after severe SCI. Thus, we have identified a hypothalamic-pontine-spinal pathway and the stimulation paradigm for potential therapeutic intervention after SCI.

Memory consolidation enables animals to draw on past experiences to guide future behavior. This process involves system- and synaptic-level changes and predominantly occurs during sleep. While hippocampal-cortical circuits are well studied in this context, the contributions of other systems, including dopaminergic circuits—key players in learning-related processes—remain poorly understood. Ventral tegmental area dopaminergic (VTA DA ) neurons are active during sleep and suggested to participate in memory consolidation processes; however, causal evidence for this is lacking. Using calcium-dependent fiber photometry, electrophysiology, and chemogenetic and optogenetic manipulations across learning paradigms, we explore the functions of VTA DA neuronal activity during sleep. We show that VTA DA activity during nonrapid eye movement sleep is experience dependent, is enhanced by motor skill and associative learning, facilitates motor skill memory consolidation, and exhibits a motor learning–dependent increase in temporal coordination with cortical spindle oscillations. Our findings uncover a previously unidentified function for VTA DA neurons in consolidating memories during sleep, advancing understanding of this central neuromodulator’s functions in regulating fundamental biological processes.

Objective. Infrared neural stimulation (INS) has emerged as a potent neuromodulation technology, offering safe and focal stimulation with superior spatial recruitment profiles compared to conventional electrical methods. However, the neural dynamics induced by INS stimulation remain poorly understood. Elucidating these dynamics will help develop new INS stimulation paradigms and advance its clinical application. Approach. In this study, we assessed the local network dynamics of INS entrainment in the auditory thalamocortical circuit using the chronically implanted rat model. Our approach focused on measuring INS energy-based local field potential (LFP) recruitment induced by focal thalamocortical stimulation. We further characterized linear and nonlinear oscillatory LFP activity in response to single-pulse and periodic INS and performed spectral decomposition to uncover specific LFP band entrainment to INS. Finally, we examined spike-field transformations across the thalamocortical synapse using spike-LFP coherence coupling measures. Main results. We found that INS significantly increases LFP amplitude as a log-linear function of INS energy per pulse, primarily entraining to LFP β and γ bands with synchrony extending to 200 Hz in some cases. A subset of neurons demonstrated nonlinear, chaotic oscillations linked to information transfer across cortical circuits. Finally, we utilized spike-field coherences to correlate spike coupling to LFP frequency band activity and suggest an energy-dependent model of network activation resulting from INS stimulation. Significance. We show that INS reliably drives robust network activity and can potently modulate cortical field potentials across a wide range of frequencies in a stimulus parameter-dependent manner. Based on these results, we propose design principles for developing full coverage, all-optical thalamocortical auditory neuroprostheses.

Context‐dependent sensory processing within the predictive coding framework relies on detecting mismatches between incoming stimuli and internal predictive models. Sensory deviants elicit prediction errors, seen as enhanced neural responses, that update these models and influence attention and behaviour. Although prediction errors have been widely observed across brain regions, the downstream processes remain poorly understood. In this study, we recorded electrocorticography in five urethane‐anaesthetised rats and identified cortical slow oscillations, characterised by spontaneous transitions between ‘Up’ and ‘Down’ states. Deviant stimuli in an auditory oddball paradigm evoked an initial positive prediction error, followed by a prolonged, all‐or‐nothing response which spread in a travelling wave across the cortex. Identified as putative evoked cortical Up states, these responses were not evoked by standards, omissions or a many‐standards control. Up states following deviants occurred more recently after a previous Up state when compared to spontaneous Up states. In preliminary data from an awake rat, long‐latency Up states were not present spontaneously or evoked. In a different rat, anaesthetic depth was key to spontaneous and evoked Up states, with more robust Up/Down states and more reliable triggering of Up states under deeper anaesthesia. These results suggest that sensory deviants may cause shifts in cortical state under anaesthesia, explaining the long‐latency mismatch response under anaesthesia and sleep.

As part of a deep brain stimulation (DBS) procedure, direct electrophysiological recordings from thalamic and basal ganglia circuits were obtained from a pediatric participant with secondary dystonia to examine the neural mechanisms of motor timing. The participant performed a two-phase repetitive timing task that began with synchronization to a series of externally presented auditory cues, followed by a continuation phase in which the participant maintained the movement rhythm without external guidance. Simultaneous recordings from stereoelectroencephalography (sEEG) leads implanted in the globus pallidus internus (GPi), subthalamic nucleus (STN), ventral oralis (Vo), centromedian nucleus (CM), and thalamic nuclei receiving projections from the cerebellum (ventral intermediate nucleus (VIM) and centrolateral nucleus (CL)) revealed behaviorally relevant neural dynamics. Local field potentials (LFPs) from recorded nuclei exhibited strong, time-locked responses during the synchronization phase, with reduced amplitudes during the continuation phase. Time-frequency analysis showed consistent power increases around the corresponding mean of the inter-response intervals (IRIs) in both behavioral output and neural signals, suggesting frequency-specific entrainment across circuits. These findings suggest of cerebellar-thalamic and basal ganglia contributions to temporal coordination.

Purpose: We aim to develop a robust method to improve the estimation accuracy of motor-evoked potential (MEP) recruitment curves (RCs), including motor threshold, in small-sample settings which typically involve fewer than 40 stimuli. Methods: We present a hierarchical Bayesian (HB) method to model MEP size as a rectified-logistic function of stimulation intensity. This method is designed to account for small samples, handle outliers without discarding data, quantify estimation uncertainty, and simulate synthetic data that closely matches real observations, useful for optimizing experimental design. We validate its performance on transcranial magnetic stimulation (TMS), epidural spinal cord stimulation (SCS), and synthetic TMS datasets, and provide an open-source library for Python, called hbMEP, for diverse applications. Results: The rectified-logistic outperformed sigmoidal functions in predictive accuracy on TMS and SCS datasets, as demonstrated through cross-validation. A mixture extension of the HB model improved robustness to outliers by further increasing its predictive accuracy. The HB model reduced threshold estimation error by up to 70% on sparse synthetic TMS data compared to non-hierarchical models. Bayesian estimation with the HB model reduced the required number of participants by at least 23% to detect a shift in threshold with 80% power, compared to frequentist testing. Empirical results on human SCS data further validated its applicability to real data. Conclusion: By improving accuracy on sparse data, our method minimizes the number of stimuli needed to probe each individual's neuromuscular parameters across multiple muscles simultaneously, thereby reducing session duration and the risk of inadvertent neuromodulation. Our approach provides a more statistically powerful and conclusive framework for inferring changes in threshold, and therefore corticospinal excitability. The hbMEP library streamlines and unifies the analysis of RCs across stimulation modalities and experimental paradigms.

Neuronal synchronization refers to the temporal coordination of activity across populations of neurons, a process that underlies coherent information processing, supports the encoding of diverse sensory stimuli, and facilitates adaptive behavior in dynamic environments. Previous studies of synchronization have predominantly emphasized rate coding and pairwise interactions between neurons, which have provided valuable insights into emergent network phenomena but remain insufficient for capturing the full complexity of temporal dynamics in spike trains, particularly the interspike interval. To address this limitation, we performed in vivo neural ensemble recording in the primary olfactory center—the antennal lobe (AL) of the hawk moth Manduca sexta —by stimulating with floral odor blends and systematically varying the concentration of an individual odorant within one of the mixtures. We then applied machine learning methods integrating modern attention mechanisms and generative normalizing flows, enabling the extraction of semi-interpretable attention weights that characterize dynamic neuronal interactions. These learned weights not only recapitulated the established principles of neuronal synchronization but also facilitated the functional classification of two major cell types in the antennal lobe (AL) [local interneurons (LNs) and projection neurons (PNs)]. Furthermore, by experimentally manipulating the excitation/inhibition balance within the circuit, our approach revealed the relationships between synchronization strength and odorant composition, providing new insight into the principles by which olfactory networks encode and integrate complex sensory inputs.

Cerebral cortex and cerebellum are essential for sensorimotor control, but the dynamics of their interactions remain unclear. Here, we investigated which pathways prevail during preparation and execution of spontaneous whisker movements in mice. During preparation, neuronal activity of primary motor (M1) and somatosensory (S1) cortex precede that of cerebellar crus regions, with a lead that is consistent with relaying a copy of motor commands. After movement onset, the phase of the signal inverts, indicating a dominant vector signaling from cerebellum to cerebrum. At this stage, Purkinje cell activity correlates more with S1 than M1, generating a prediction of sensory consequences during motor actions. A computational cerebello-cortical model could replicate the changes in dynamics and directionality. Optogenetic manipulations of pons and thalamus confirm the modeled predictions on stage-dependent dynamics. Together our data point towards a swap in direction of information flow between cerebrum and cerebellum when motor preparation switches to execution.