Transient Increases in Neural Oscillations and Motor Deficits in a Mouse Model of Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms like tremors and bradykinesia. PD's pathology involves the aggregation of α-synuclein and loss of dopaminergic neurons, leading to altered neural oscillations in the cortico-basal ganglia-thalamic network. Despite extensive research, the relationship between the motor symptoms of PD and transient changes in brain oscillations before and after motor tasks in different brain regions remain unclear. This study aimed to investigate neural oscillations in both healthy and PD model mice using local field potential (LFP) recordings from multiple brain regions during rest and locomotion. The histological evaluation confirmed the significant dopaminergic neuron loss in the injection side in 6-OHDA lesioned mice. Behavioral tests showed motor deficits in these mice, including impaired coordination and increased forelimb asymmetry. The LFP analysis revealed increased delta, theta, alpha, beta, and gamma band activity in 6-OHDA lesioned mice during movement, with significant increases in multiple brain regions, including the primary motor cortex (M1), caudate-putamen (CPu), subthalamic nucleus (STN), substantia nigra pars compacta (SNc), and pedunculopontine nucleus (PPN). Taken together, these results show that the motor symptoms of PD are accompanied by significant transient increases in brain oscillations, especially in the gamma band. This study provides potential biomarkers for early diagnosis and therapeutic evaluation by elucidating the relationship between specific neural oscillations and motor deficits in PD.

Mapping cognitive activity from electrocorticography field potentials in humans performing NBack task.

Objective. Advancements in data science and assistive technologies have made invasive brain-computer interfaces (iBCIs) increasingly viable for enhancing the quality of life in physically disabled individuals. Intracortical microelectrode implants are a common choice for such a communication system due to their fine temporal and spatial resolution. The small size of these implants makes the implantation plan critical for the successful exfiltration of information, particularly when targeting representations of task goals that lack robust anatomical correlates.Approach. Working memory processes including encoding, retrieval, and maintenance are observed in many areas of the brain. Using human electrocorticography (ECoG) recordings during a working memory experiment, we provide proof that it is possible to localize cognitive activity associated with the task and to identify key locations involved with executive memory functions.Results.From the analysis, we could propose an optimal iBCI implant location with the desired features. The general approach is not limited to working memory but could also be used to map other goal-encoding factors such as movement intentions, decision-making, and visual-spatial attention.Significance. Deciphering the intended action of a BCI user is a complex challenge that involves the extraction and integration of cognitive factors such as movement planning, working memory, visual-spatial attention, and the decision state. Examining field potentials from ECoG electrodes while participants engaged in tailored cognitive tasks can pinpoint location with valuable information related to anticipated actions. This manuscript demonstrates the feasibility of identifying electrodes involved in cognitive activity related to working memory during user engagement in the NBack task. Devoting time in meticulous preparation to identify the optimal brain regions for BCI implant locations will increase the likelihood of rich signal outcomes, thereby improving the overall BCI user experience.

Case report: Improvement of gait with adaptive deep brain stimulation in a patient with Parkinson's disease.

Gait disturbance is a common and severe symptom of Parkinson's disease that severely impairs quality of life. Current treatments provide only partial benefits with wide variability in outcomes. Also, deep brain stimulation of the subthalamic nucleus (STN-DBS), a mainstay treatment for bradykinetic-rigid symptoms and parkinsonian tremor, is poorly effective on gait. We applied a novel DBS paradigm, adjusting the current amplitude linearly with respect to subthalamic beta power (adaptive DBS), in one parkinsonian patient with gait impairment and chronically stimulated with conventional DBS. We studied the kinematics of gait and gait initiation (anticipatory postural adjustments) as well as subthalamic beta oscillations with both conventional and adaptive DBS. With adaptive DBS, the patient showed a consistent and long-lasting improvement in walking while retaining benefits on other disease-related symptoms. We suggest that adaptive DBS can benefit gait in Parkinson's disease possibly by avoiding overstimulation and dysfunctional entrainment of the supraspinal locomotor network.

Cortico-striatal beta oscillations as a reward-related signal.

The value associated with reward is sensitive to external factors, such as the time between the choice and reward delivery as classically manipulated in temporal discounting tasks. Subjective preference for two reward options is dependent on objective variables of reward magnitude and reward delay. Single neuron correlates of reward value have been observed in regions, including ventral striatum, orbital, and medial prefrontal cortex. Brain imaging studies show cortico-striatal-limbic network activity related to subjective preferences. To explore how oscillatory dynamics represent reward processing across brain regions, we measured local field potentials of rats performing a temporal discounting task. Our goal was to use a data-driven approach to identify an electrophysiological marker that correlates with reward preference. We found that reward-locked oscillations at beta frequencies signaled the magnitude of reward and decayed with longer temporal delays. Electrodes in orbitofrontal/medial prefrontal cortex, anterior insula, ventral striatum, and amygdala individually increased power and were functionally connected at beta frequencies during reward outcome. Beta power during reward outcome correlated with subjective value as defined by a computational model fit to the discounting behavior. These data suggest that cortico-striatal beta oscillations are a reward signal correlated, which may represent subjective value and hold potential to serve as a biomarker and potential therapeutic target.

Comparison of alterations in local field potentials and neuronal firing in mouse M1 and CA1 associated with central fatigue induced by high-intensity interval training and moderate-intensity continuous training.

Background: The mechanisms underlying central fatigue (CF) induced by high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) are still not fully understood. Methods: In order to explore the effects of these exercises on the functioning of cortical and subcortical neural networks, this study investigated the effects of HIIT and MICT on local field potential (LFP) and neuronal firing in the mouse primary motor cortex (M1) and hippocampal CA1 areas. HIIT and MICT were performed on C57BL/6 mice, and simultaneous multichannel recordings were conducted in the M1 motor cortex and CA1 hippocampal region. Results: A range of responses were elicited, including a decrease in coherence values of LFP rhythms in both areas, and an increase in slow and a decrease in fast power spectral density (PSD, n = 7-9) respectively. HIIT/MICT also decreased the gravity frequency (GF, n = 7-9) in M1 and CA1. Both exercises decreased overall firing rates, increased time lag of firing, declined burst firing rates and the number of spikes in burst, and reduced burst duration (BD) in M1 and CA1 (n = 7-9). While several neuronal firing properties showed a recovery tendency, the alterations of LFP parameters were more sustained during the 10-min post-HIIT/MICT period. MICT appeared to be more effective than HIIT in affecting LFP parameters, neuronal firing rate, and burst firing properties, particularly in CA1. Both exercises significantly affected neural network activities and local neuronal firing in M1 and CA1, with MICT associated with a more substantial and consistent suppression of functional integration between M1 and CA1. Conclusion: Our study provides valuable insights into the neural mechanisms involved in exercise-induced central fatigue by examining the changes in functional connectivity and coordination between the M1 and CA1 regions. These findings may assist individuals engaged in exercise in optimizing their exercise intensity and timing to enhance performance and prevent excessive fatigue. Additionally, the findings may have clinical implications for the development of interventions aimed at managing conditions related to exercise-induced fatigue.

Spinal Cord Stimulation Modulates Rat Cortico-Basal Ganglia Locomotor Circuit.

OBJECTIVE: The cortico-basal ganglia circuit is crucial to understanding locomotor behavior and movement disorders. Spinal cord stimulation modulates that circuit, which is a promising approach to restoring motor functions. However, the effects of electrical spinal cord stimulation in the healthy brain motor circuit in pre- and postgait are poorly understood. Thus, this report aims to evaluate, through electrophysiological analyses, the dynamic spectral features of motor networks underlying locomotor initiation with spinal cord stimulation. MATERIALS AND METHODS: Wistar male rats underwent spinal cord stimulation (current 30-150 µA, frequency 100, 333, and 500 Hz) with the electrophysiological recording of the caudate and putamen nuclei, primary and secondary motor cortices, and primary somatosensory cortex. Video tracking recorded treadmill locomotion and extracted the motor planning and gait initiation. RESULTS: Spectral analysis of segments of gait initiation (pre- and postgait), with stimulation off, showed increased low-frequency activity. Postgait initiation showed increased alpha and beta rhythms and decreased delta rhythm with the stimulation off. Overall, the stimulation frequencies reduced alpha and beta rhythms in all brain areas during movement initiation. Regarding movement planning, such an effect was observed in the sensorimotor area, comprising the delta and alpha rhythms. CONCLUSION: This study showed a short-term effect of spinal cord stimulation on the brain areas of the motor circuit, suggesting possible facilitation of movement planning and starting through neuromodulation. Thus, the electrophysiological characterization of this study may contribute to understanding basal ganglia networks and developing new approaches to treat movement disorders in the gait initiation phase.

Coupled oscillations orchestrate selective information transmission in visual cortex.

Performing visually guided behavior involves flexible routing of sensory information towards associative areas. We hypothesize that in visual cortical areas, this routing is shaped by a gating influence of the local neuronal population on the activity of the same population's single neurons. We analyzed beta frequencies (representing local population activity), high-gamma frequencies (representative of the activity of local clusters of neurons), and the firing of single neurons in the medial temporal (MT) area of behaving rhesus monkeys. Our results show an influence of beta activity on single neurons, predictive of behavioral performance. Similarly, the temporal dependence of high-gamma on beta predicts behavioral performance. These demonstrate a unidirectional influence of network-level neural dynamics on single-neuron activity, preferentially routing relevant information. This demonstration of a local top-down influence unveils a previously unexplored perspective onto a core feature of cortical information processing: the selective transmission of sensory information to downstream areas based on behavioral relevance.

Subthalamic nucleus local field potential stability in patients with Parkinson's disease.

BACKGROUND: Despite the large body of work on local field potentials (LFPs), a measure of oscillatory activity in patients with Parkinson's disease (PD), the longitudinal evolution of LFPs is less explored. OBJECTIVE: To determine LFP fluctuations collected in clinical settings in patients with PD and STN deep brain stimulation (DBS). METHODS: Twenty-two STN-DBS patients (age: 67.6 ± 8.3 years; 9 females; disease duration: 10.3 ± 4.5 years) completed bilateral LFP recordings over three visits in the OFF-stimulation setting. Peak and band power measures were calculated from each recording. RESULTS: After bilateral LFP recordings, at least one peak was detected in 18 (81.8%), 20 (90.9%), and 22 (100%) patients at visit 1, 2, and 3, respectively. No significant differences were seen in primary peak amplitude (F = 2.91, p = 0.060) over time. Amplitude of the second largest peak (F = 5.49, p = 0.006) and low-beta (F = 6.89, p = 0.002), high-beta (F = 13.23, p < 0.001), and gamma (F = 12.71, p < 0.001) band power demonstrated a significant effect of time. Post hoc comparisons determined low-beta power (Visit 1-Visit 2: t = 3.59, p = 0.002; Visit 1-Visit 3: t = 2.61, p = 0.031), high-beta (Visit 1-Visit 2: t = 4.64, p < 0.001; Visit 1-Visit 3: t = 4.23, p < 0.001) and gamma band power (Visit 1-Visit 2: t = 4.65, p < 0.001; Visit 1-Visit 3: t = 4.00, p < 0.001) were significantly increased from visit 1 recordings to both follow-up visits. CONCLUSION: Our results provide substantial evidence that LFP can reliably be detected across multiple real-world clinical visits in patients with STN-DBS for PD. Moreover, it provides insights on the evolution of these LFPs.

Cholinergic and behavior-dependent beta and gamma waves are coupled between olfactory bulb and hippocampus.

Olfactory oscillations may enhance cognitive processing through coupling with beta (ß, 15-30 Hz) and gamma (γ, 30-160 Hz) activity in the hippocampus (HPC). We hypothesize that coupling between olfactory bulb (OB) and HPC oscillations is increased by cholinergic activation in control rats and is reduced in kainic-acid-treated epileptic rats, a model of temporal lobe epilepsy. OB γ2 (63-100 Hz) power was higher during walking and immobility-awake (IMM) compared to sleep, while γ1 (30-57 Hz) power was higher during grooming than other behavioral states. Muscarinic cholinergic agonist pilocarpine (25 mg/kg ip) with peripheral muscarinic blockade increased OB power and OB-HPC coherence at ß and γ1 frequency bands. A similar effect was found after physostigmine (0.5 mg/kg ip) but not scopolamine (10 mg/kg ip). Pilocarpine increased bicoherence and cross-frequency coherence (CFC) between OB slow waves (SW, 1-5 Hz) and hippocampal ß, γ1 and γ2 waves, with stronger coherence at CA1 alveus and CA3c than CA1 stratum radiatum. Bicoherence further revealed a nonlinear interaction of ß waves in OB with ß waves at the CA1-alveus. Beta and γ1 waves in OB or HPC were segregated at one phase of the OB-SW, opposite to the phase of γ2 and γ3 (100-160 Hz) waves, suggesting independent temporal processing of ß/γ1 versus γ2/γ3 waves. At CA1 radiatum, kainic-acid-treated epileptic rats compared to control rats showed decreased theta power, theta-ß and theta-γ2 CFC during baseline walking, decreased CFC of HPC SW with γ2 and γ3 waves during baseline IMM, and decreased coupling of OB SW with ß and γ2 waves at CA1 alveus after pilocarpine. It is concluded that ß and γ waves in the OB and HPC are modulated by a slow respiratory rhythm, in a cholinergic and behavior-dependent manner, and OB-HPC functional connectivity at ß and γ frequencies may enhance cognitive functions.

Development of neuronal timescales in human cortical organoids and rat hippocampus dissociated cultures.

To support complex cognition, neuronal circuits must integrate information across multiple temporal scales, ranging from milliseconds to decades. Neuronal timescales describe the duration over which activity within a network persists, posing a putative explanatory mechanism for how information might be integrated over multiple temporal scales. Little is known about how timescales develop in human neural circuits or other model systems, limiting insight into how the functional dynamics necessary for cognition emerge. In our work, we show that neuronal timescales develop in a nonlinear fashion in human cortical organoids, which is partially replicated in dissociated rat hippocampus cultures. We use spectral parameterization of spiking activity to extract an estimate of neuronal timescale that is unbiased by coevolving oscillations. Cortical organoid timescales begin to increase around month 6 postdifferentiation. In rodent hippocampal dissociated cultures, we see that timescales decrease from in vitro days 13-23 before stabilizing. We speculate that cortical organoid development over the duration studied here reflects an earlier stage of a generalized developmental timeline in contrast to the rodent hippocampal cultures, potentially accounting for differences in timescale developmental trajectories. The fluctuation of timescales might be an important developmental feature that reflects the changing complexity and information capacity in developing neuronal circuits.NEW & NOTEWORTHY Neuronal timescales describe the persistence of activity within a network of neurons. Timescales were found to fluctuate with development in two model systems. In cortical organoids timescales increased, peaked, and then decreased throughout development; in rat hippocampal dissociated cultures timescales decreased over development. These distinct developmental models overlap to highlight a critical window in which timescales lengthen and contract, potentially indexing changes in the information capacity of neuronal systems.

Spiking Laguerre Volterra networks-predicting neuronal activity from local field potentials.

Objective.Understanding the generative mechanism between local field potentials (LFP) and neuronal spiking activity is a crucial step for understanding information processing in the brain. Up to now, most approaches have relied on simply quantifying the coupling between LFP and spikes. However, very few have managed to predict the exact timing of spike occurrence based on LFP variations.Approach.Here, we fill this gap by proposing novel spiking Laguerre-Volterra network (sLVN) models to describe the dynamic LFP-spike relationship. Compared to conventional artificial neural networks, the sLVNs are interpretable models that provide explainable features of the underlying dynamics.Main results.The proposed networks were applied on extracellular microelectrode recordings of Parkinson's Disease patients during deep brain stimulation (DBS) surgery. Based on the predictability of the LFP-spike pairs, we detected three neuronal populations with unique signal characteristics and sLVN model features.Significance.These clusters were indirectly associated with motor score improvement following DBS surgery, warranting further investigation into the potential of spiking activity predictability as an intraoperative biomarker for optimal DBS lead placement.

Deep learning based decoding of single local field potential events.

How is information processed in the cerebral cortex? In most cases, recorded brain activity is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. However, the brain is obviously a single-trial processor. Thus, we here demonstrate that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial basis. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both extra-cellular neural recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.

Asymmetries of the subthalamic activity in Parkinson's disease: phase-amplitude coupling among local field potentials.

The role of brain asymmetries of dopaminergic neurons in motor symptoms of Parkinson's disease is still undefined. Local field recordings from the subthalamic nucleus revealed some neurophysiological biomarkers of the disease: increased beta activity, increased low-frequency activity and high-frequency oscillations. Phase-amplitude coupling coordinates the timing of neuronal activity and allows determining the mechanism for communication within distinct regions of the brain. In this study, we discuss the use of phase-amplitude coupling to assess the differences between the two hemispheres in a cohort of 24 patients with Parkinson's disease before and after levodopa administration. Subthalamic low- (12-20 Hz) and high-beta (20-30 Hz) oscillations were compared with low- (30-45 Hz), medium- (70-100 Hz) and high-frequency (260-360 Hz) bands. We found a significant beta-phase-amplitude coupling asymmetry between left and right and an opposite-side-dependent effect of the pharmacological treatment, which is associated with the reduction of motor symptoms. In particular, high coupling between high frequencies and high-beta oscillations was found during the OFF condition (P < 0.01) and a low coupling during the ON state (P < 0.0001) when the right subthalamus was assessed; exactly the opposite happened when the left subthalamus was considered in the analysis, showing a lower coupling between high frequencies and high-beta oscillations during the OFF condition (P < 0.01), followed by a higher one during the ON state (P < 0.01). Interestingly, these asymmetries are independent of the motor onset side, either left or right. These findings have important implications for neural signals that may be used to trigger adaptive deep brain stimulation in Parkinson's and could provide more exhaustive insights into subthalamic dynamics.

Modulation of neuronal activity in human centromedian nucleus during an auditory attention and working memory task.

Centromedian nucleus (CM) is one of several intralaminar nuclei of the thalamus and is thought to be involved in consciousness, arousal, and attention. CM has been suggested to play a key role in the control of attention, by regulating the flow of information to different brain regions such as the ascending reticular system, basal ganglia, and cortex. While the neurophysiology of attention in visual and auditory systems has been studied in animal models, combined single unit and LFP recordings in human have not, to our knowledge, been reported. Here, we recorded neuronal activity in the CM nucleus in 11 patients prior to insertion of deep brain stimulation electrodes for the treatment of epilepsy while subjects performed an auditory attention task. Patients were requested to attend and count the infrequent (p = 0.2) odd or "deviant" tones, ignore the frequent standard tones and report the total number of deviant tones at trial completion. Spikes were discriminated, and LFPs were band pass filtered (5-45 Hz). Average peri­stimulus time histograms and spectra were constructed by aligning on tone onsets and statistically compared. The firing rate of CM neurons showed selective, multi-phasic responses to deviant tones in 81% of the tested neurons. Local field potential analysis showed selective beta and low gamma (13-45 Hz) modulations in response to deviant tones, also in a multi-phasic pattern. The current study demonstrates that CM neurons are under top-down control and participate in the selective processing during auditory attention and working memory. These results, taken together, implicate the CM in selective auditory attention and working memory and support a role of beta and low gamma oscillatory activity in cognitive processes. It also has potential implications for DBS therapy for epilepsy and non-motor symptoms of PD, such as apathy and other disorders of attention.

Subthalamic control of impulsive actions: insights from deep brain stimulation in Parkinson's disease.

Control of actions allows adaptive, goal-directed behaviour. The basal ganglia, including the subthalamic nucleus, are thought to play a central role in dynamically controlling actions through recurrent negative feedback loops with the cerebral cortex. Here, we summarize recent translational studies that used deep brain stimulation to record neural activity from and apply electrical stimulation to the subthalamic nucleus in people with Parkinson's disease. These studies have elucidated spatial, spectral and temporal features of the neural mechanisms underlying the controlled delay of actions in cortico-subthalamic networks and demonstrated their causal effects on behaviour in distinct processing windows. While these mechanisms have been conceptualized as control signals for suppressing impulsive response tendencies in conflict tasks and as decision threshold adjustments in value-based and perceptual decisions, we propose a common framework linking decision-making, cognition and movement. Within this framework subthalamic deep brain stimulation can lead to suboptimal choices by reducing the time that patients take for deliberation before committing to an action. However, clinical studies have consistently shown that the occurrence of impulse control disorders is reduced, not increased, after subthalamic deep brain stimulation surgery. This apparent contradiction can be reconciled when recognizing the multifaceted nature of impulsivity, its underlying mechanisms and modulation by treatment. While subthalamic deep brain stimulation renders patients susceptible to making decisions without proper forethought, this can be disentangled from effects related to dopamine comprising sensitivity to benefits vs. costs, reward delay aversion and learning from outcomes. Alterations in these dopamine-mediated mechanisms are thought to underlie the development of impulse control disorders, and can be relatively spared with reduced dopaminergic medication after subthalamic deep brain stimulation. Together, results from studies using deep brain stimulation as an experimental tool have improved our understanding of action control in the human brain and have important implications for treatment of patients with Neurological disorders.

Insula uses overlapping codes for emotion in self and others.

In daily life, we must recognize others' emotions so we can respond appropriately. This ability may rely, at least in part, on neural responses similar to those associated with our own emotions. We hypothesized that the insula, a cortical region near the junction of the temporal, parietal, and frontal lobes, may play a key role in this process. We recorded local field potential (LFP) activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one on identifying facial emotional responses in others. We found matching patterns of gamma- and high-gamma band activity for the two tasks in the insula. Three other regions (MTL, ACC, and OFC) clearly encoded both self- and other-emotions, but used orthogonal activity patterns to do so. These results support the hypothesis that the insula plays a particularly important role in mediating between experienced vs. observed emotions.

Beta Oscillations in the Sensory Thalamus During Severe Facial Neuropathic Pain Using Novel Sensing Deep Brain Stimulation.

OBJECTIVE: Advancements in deep brain stimulation (DBS) devices provide a unique opportunity to record local field potentials longitudinally to improve the efficacy of treatment for intractable facial pain. We aimed to identify potential electrophysiological biomarkers of pain in the ventral posteromedial nucleus (VPM) of the thalamus and periaqueductal gray (PAG) using a long-term sensing DBS system. MATERIALS AND METHODS: We analyzed power spectra of ambulatory pain-related events from one patient implanted with a long-term sensing generator, representing different pain intensities (pain >7, pain >9) and pain qualities (no pain, burning, stabbing, and shocking pain). Power spectra were parametrized to separate oscillatory and aperiodic features and compared across the different pain states. RESULTS: Overall, 96 events were marked during a 16-month follow-up. Parameterization of spectra revealed a total of 62 oscillatory peaks with most in the VPM (77.4%). The pain-free condition did not show any oscillations. In contrast, ß peaks were observed in the VPM during all episodes (100%) associated with pain >9, 56% of episodes with pain >7, and 50% of burning pain events (center frequencies: 28.4 Hz, 17.8 Hz, and 20.7 Hz, respectively). Episodes of pain >9 indicated the highest relative ß band power in the VPM and decreased aperiodic exponents (denoting the slope of the power spectra) in both the VPM and PAG. CONCLUSIONS: For this patient, an increase in ß band activity in the sensory thalamus was associated with severe facial pain, opening the possibility for closed-loop DBS in facial pain.

Neurometric amplitude modulation detection in the inferior colliculus of Young and Aged rats.

Amplitude modulation is an important acoustic cue for sound discrimination, and humans and animals are able to detect small modulation depths behaviorally. In the inferior colliculus (IC), both firing rate and phase-locking may be used to detect amplitude modulation. How neural representations that detect modulation change with age are poorly understood, including the extent to which age-related changes may be attributed to the inherited properties of ascending inputs to IC neurons. Here, simultaneous measures of local field potentials (LFPs) and single-unit responses were made from the inferior colliculus of Young and Aged rats using both noise and tone carriers in response to sinusoidally amplitude-modulated sounds of varying depths. We found that Young units had higher firing rates than Aged for noise carriers, whereas Aged units had higher phase-locking (vector strength), especially for tone carriers. Sustained LFPs were larger in Young animals for modulation frequencies 8-16 Hz and comparable at higher modulation frequencies. Onset LFP amplitudes were much larger in Young animals and were correlated with the evoked firing rates, while LFP onset latencies were shorter in Aged animals. Unit neurometric thresholds by synchrony or firing rate measures did not differ significantly across age and were comparable to behavioral thresholds in previous studies whereas LFP thresholds were lower than behavior.

Electrophysiological Correlates of Dentate Nucleus Deep Brain Stimulation for Poststroke Motor Recovery.

While ipsilesional cortical electroencephalography has been associated with poststroke recovery mechanisms and outcomes, the role of the cerebellum and its interaction with the ipsilesional cortex is still largely unknown. We have previously shown that poststroke motor control relies on increased corticocerebellar coherence (CCC) in the low beta band to maintain motor task accuracy and to compensate for decreased excitability of the ipsilesional cortex. We now extend our work to investigate corticocerebellar network changes associated with chronic stimulation of the dentato-thalamo-cortical pathway aimed at promoting poststroke motor rehabilitation. We investigated the excitability of the ipsilesional cortex, the dentate (DN), and their interaction as a function of treatment outcome measures. Relative to baseline, 10 human participants (two women) at the end of 4-8 months of DN deep brain stimulation (DBS) showed (1) significantly improved motor control indexed by computerized motor tasks; (2) significant increase in ipsilesional premotor cortex event-related desynchronization that correlated with improvements in motor function; and (3) significant decrease in CCC, including causal interactions between the DN and ipsilesional cortex, which also correlated with motor function improvements. Furthermore, we show that the functional state of the DN in the poststroke state and its connectivity with the ipsilesional cortex were predictive of motor outcomes associated with DN-DBS. The findings suggest that as participants recovered, the ipsilesional cortex became more involved in motor control, with less demand on the cerebellum to support task planning and execution. Our data provide unique mechanistic insights into the functional state of corticocerebellar-cortical network after stroke and its modulation by DN-DBS.

Paradoxical Boosting of Weak and Strong Spatial Memories by Hippocampal Dopamine Uncaging.

The ability to remember changes in the surroundings is fundamental for daily life. It has been proposed that novel events producing dopamine release in the hippocampal CA1 region could modulate spatial memory formation. However, the role of hippocampal dopamine increase on weak or strong spatial memories remains unclear. We show that male mice exploring two objects located in a familiar environment for 5 min created a short-term memory (weak) that cannot be retrieved 1 d later, whereas 10 min exploration created a long-term memory (strong) that can be retrieved 1 d later. Remarkably, hippocampal dopamine elevation during the encoding of weak object location memories (OLMs) allowed their retrieval 1 d later but dopamine elevation during the encoding of strong OLMs promoted the preference for a familiar object location over a novel object location after 24 h. Moreover, dopamine uncaging after the encoding of OLMs did not have effect on weak memories whereas on strong memories diminished the exploration of the novel object location. Additionally, hippocampal dopamine elevation during the retrieval of OLMs did not allow the recovery of weak memories and did not affect the retrieval of strong memory traces. Finally, dopamine elevation increased hippocampal theta oscillations, indicating that dopamine promotes the recurrent activation of specific groups of neurons. Our experiments demonstrate that hippocampal dopaminergic modulation during the encoding of OLMs depends on memory strength indicating that hyperdopaminergic levels that enhance weak experiences could compromise the normal storage of strong memories.