Firing Rate Of Neurons Research Articles

Prenatal exposure to MAM impairs mPFC and hippocampal inhibitory function in mice during adolescence and adulthood.

Neurodevelopmental abnormalities are considered to be one of the important causes of schizophrenia. The offspring of methylazoxymethanol acetate (MAM)-exposed mice are recognized for the dysregulation of neurodevelopment and well-characterized with schizophrenia-like phenotypes. However, the inhibition-related properties of the medial prefrontal cortex (mPFC) and hippocampus throughout adolescence and adulthood have not been systematically elucidated. In this study, both 10 mg/kg and 15 mg/kg MAM-exposed mice exhibited schizophrenia-related phenotypes in both adolescence and adulthood, including spontaneous locomotion hyperactivity and deficits in prepulse inhibition (PPI). We observed that there was an obvious parvalbumin (PV) loss in mPFC and hippocampus of MAM-exposed mice, extending from adolescence to adulthood. Moreover, the frequency of sIPSCs in pyramidal neurons at mPFC and hippocampus was significantly dampened in the 10 mg/kg and 15 mg/kg MAM-exposed mice. Furthermore, the firing rate of putative pyramidal neurons in mPFC and hippocampus was increased, while that of putative inhibitory neurons was decreased during both adolescence and adulthood. In conclusion, PV loss in mPFC and hippocampus of MAM-exposed mice may contribute to the impaired inhibitory function leading to the attenuation of inhibition in the brain both in vitro and in vivo.Significance Statement PV neurons could play an important role in maintaining the balance of neural network homeostasis for its ability to provide strong inhibition. PV neurons were reduced in the mPFC and hippocampus in the schizophrenia patients. In this study, we demonstrated that 10 mg/kg and 15 mg/kg MAM exposure causes a loss of PV neurons in the mPFC and hippocampus of mice, which leads to an impaired inhibitory function. Overall, these results provided the significance of PV neurons modulating neural network homeostasis and involving in the pathogenesis of schizophrenia.

Dopamine D4 receptors in the lateral habenula regulate anxiety-related behaviors in a rat model of Parkinson's disease

Although the output of the lateral habenula (LHb) controls the activity of midbrain dopamine (DA) and 5-hydroxytryptamine (5-HT) containing systems, which are implicated in the pathophysiology of anxiety, it is not clear how activation and blockade of LHb D4 receptors affects anxiety-like behaviors, particularly in Parkinson’s disease related anxiety. In this study, unilateral 6-hydroxydopamine lesions of the substantia nigra pars compacta (SNc) in rats induced anxiety-like behaviors, which attribute to hyperactivity of LHb neurons and decrease in the level of DA in the medial prefrontal cortex (mPFC), amygdala and ventral hippocampus (vHip) compared to sham-operated rats. Intra-LHb injection of D4 receptor agonist A412997 induced or increased the expression of anxiety-like behaviors, while injection of D4 receptor antagonist L741742 showed anxiolytic effects in sham-operated and the SNc-lesioned rats. However, the doses producing behavioral effects in the lesioned rats were higher than those of sham-operated rats. Intra-LHb injection of A412997 increased firing rate of LHb neurons, and decreased levels of DA and 5-HT in the mPFC, amygdala and vHip; conversely, L741742 decreased firing rate of LHb neurons, and increased levels of DA and 5-HT in two groups of rats. Compared to sham-operated rats, the duration of A412997 and L741742 action on the firing rate of neurons was markedly shortened in the lesioned rats. Collectively, these findings suggest that D4 receptors in the LHb are involved in the regulation of anxiety-like behaviors, and degeneration of the nigrostriatal pathway down-regulates function and/or expression of these receptors.

Pharmacological characterization of prostaglandin E2 EP2 and EP4 receptors in male rat locus coeruleus neurons ex vivo

The inflammatory mediator prostaglandin E2 (PGE2) binds to Gs-coupled EP2 and EP4 receptors. These receptors are located in the locus coeruleus (LC), the principal noradrenergic nucleus in the brain, but their functional role remains unknown. In this study, the PGE2 EP2 and EP4 receptors in LC cells from male rat brain slices were pharmacologically characterized by single-unit extracellular electrophysiology. The EP2 receptor agonists butaprost (0.01–10 μM) and treprostinil (0.03–10 µM) and the EP4 receptor agonists rivenprost (0.01 nM–1 µM) and TCS2510 (0.20 nM–2 µM) increased the firing rate of LC neurons in a concentration-dependent manner. The EP2 receptor antagonist PF-04418948 (10 nM) hindered the excitatory effect of butaprost and treprostinil while the EP4 receptor antagonist L-161,982 (30 and 300 nM) blocked the excitatory effect caused by rivenprost and TCS2510. The effects of butaprost and rivenprost were prevented by extracellular sodium replacement but were not modified by the protein kinase A (PKA) activator 8-Br-cAMP (1 mM) or the inhibitor H-89 (10 μM). However, the Gβγ subunit blocker gallein (20 μM) hindered the stimulatory effect of butaprost while the Gαs subunit inhibitor NF449 (10 µM) prevented that of rivenprost. Finally, rivenprost-induced stimulation (30 nM) was not occluded by butaprost (1 µM).In conclusion, activation of EP2 and EP4 receptors excites LC noradrenergic neurons through sodium-dependent currents via different G protein subunits in male rat brain slices. EP2 and EP4 in the LC may constitute pharmacological targets for the treatment of pain, fever, drug addiction, anxiety and neuroinflammatory diseases.

Theoretical framework for learning through structural plasticity

A growing body of research indicates that structural plasticity mechanisms are crucial for learning and memory consolidation. Starting from a simple phenomenological model, we exploit a mean-field approach to develop a theoretical framework of learning through this kind of plasticity, capable of taking into account several features of the connectivity and pattern of activity of biological neural networks, including probability distributions of neuron firing rates, selectivity of the responses of single neurons to multiple stimuli, probabilistic connection rules, and noisy stimuli. More importantly, it describes the effects of stabilization, pruning, and reorganization of synaptic connections. This framework is used to compute the values of some relevant quantities used to characterize the learning and memory capabilities of the neuronal network in training and testing procedures as the number of training patterns and other model parameters vary. The results are then compared with those obtained through simulations with firing-rate-based neuronal network models. Published by the American Physical Society 2024

A preserved neural code for temporal order between memory formation and recall in the human medial temporal lobe.

Temporal memory enables us to remember the temporal order of events happening in our life. The human medial temporal lobe (MTL) appears to contain neural representations supporting temporal memory formation, but the cellular mechanisms that preserve temporal order information for recall are largely unknown. Here, we examined whether human MTL neuronal activity represents the temporal position of events during memory formation and recall, using invasive single and multi-unit recordings in human epilepsy patients (n = 19). Participants freely navigated a virtual environment in order to explore and remember locations and temporal positions of objects. During each exploration period, they sequentially encountered two or three different objects, placed in different locations. This allowed us to examine single- and multi-unit neuronal firing rates (FR) as a function of the temporal position the objects were presented in. We found that a significant number of multi-units and single-units in various MTL regions including the hippocampus showed selectivity to the temporal position of objects during the exploration period. During recall, patients were asked to indicate which one of two objects from the same trial was found latter. Neural firing rates during recall showed a selectivity supporting recall of temporal positions. Interestingly, most of the selective single-units that stayed selective during encoding and recall preserved their temporal position preference. Our results thus suggest that neuronal activity in the human MTL contains a preserved neural code for temporal order in memory formation and recall.

S-(+)-mecamylamine increases the firing rate of serotonin neurons and diminishes depressive-like behaviors in an animal model of stress

Mecamylamine, a noncompetitive blocker of nicotinic acetylcholine receptors (nAChRs), is the racemic mixture of two stereoisomers: S-(+)-mecamylamine (S-mec) and R-(−)-mecamylamine (R-mec), with distinct interactions with α4β2 nAChRs. It has been shown that mecamylamine increases glutamate release and excites serotonergic (5-HT) neurons in the dorsal raphe nucleus (DRN). In this study, we separately evaluated the effects of S-mec and R-mec on 5-HT neuron excitability. S-mec (3 μM) increased firing frequency by 40 %, while R-mec (3 μM) raised it by only 22 %. S-mec acts as a positive allosteric modulator on high-sensitivity (HS) α4β2 nAChRs at glutamate terminals, enhancing spontaneous excitatory postsynaptic currents (sEPSCs) in 5-HT neurons. Conversely, R-mec decreased sEPSCs by blocking HS α4β2 nAChRs and reduced GABA-mediated inhibitory currents (sIPSCs) by blocking α7 nAChRs at GABAergic terminals. These mechanisms make S-mec more effective than R-mec in enhancing 5-HT neuron firing. Moreover, combining S-mec with TC-2559, a selective agonist of HS α4β2 nAChRs, increased firing frequency by 65 %, exceeding the effect of S-mec alone. To validate these findings, we evaluated the antidepressant effects of S-mec (1 mg/kg) combined with TC-2559 or RJR-2403, another α4β2 nAChR agonist. This combination successfully reduced depression-like behaviors, suggesting a potential treatment strategy for patients resistant to conventional antidepressants.

Can Residual Inhibition Predict the Success of Sound Enrichment Treatment for Tinnitus?

The objective of this study was to investigate whether residual inhibition (RI), which provides information on the relationship between tinnitus and increased spontaneous activity in the auditory system, is a predictor for the success of sound enrichment treatment. Tinnitus patients were divided into two groups based on whether RI was achieved (RI+) or not (RI-). All participants underwent sound enrichment. Psychosomatic measures (for tinnitus severity, discomfort, attention deficit and sleep difficulties), Tinnitus Handicap Inventory (THI), minimum masking level (MML), and tinnitus loudness level (TLL) results were compared before and at 1, 3, and 6 months after treatment. Sixty-seven chronic tinnitus patients were divided into two groups based on whether RI was achieved (RI+) or not (RI-). There were 38 patients in the RI+ group and 29 in the RI- group. There was a statistically significant difference between the groups in psychosomatic measures, THI, MML and TLL scores at the post-treatment 6 months after treatment (p <.05). There was a statistically significant decrease in psychosomatic measures, THI, MML and TLL scores during the treatment period in the RI+ group, but not in the RI- group. RI may predict the prognosis of tinnitus treatments used in clinics to reduce the spontaneous firing rate of neurons in the central auditory system, and that RI positivity may be a predictor of treatment success in sound enrichment.

Coding Dynamics of the Striatal Networks During Learning.

The rat dorsomedial (DMS) and dorsolateral striatum (DLS), equivalent to caudate nucleus and putamen in primates, are required for goal-directed and habit behaviour, respectively. However, it is still unclear whether and how this functional dichotomy emerges in the course of learning. In this study, we investigated this issue by recording DMS and DLS single neuron activity in rats performing a continuous spatial alternation task, from the acquisition to optimized performance. We first applied a classical analytical approach to identify task-related activity based on the modifications of single neuron firing rate in relation to specific task events or maze trajectories. We then used an innovative approach based on Hawkes process to reconstruct a directed connectivity graph of simultaneously recorded neurons, that was used to decode animal behavior. This approach enabled us to better unravel the role of DMSand DLS neural networks across learning stages. We showed that DMS and DLS display different task-related activity throughout learning stages, and the proportion of coding neurons over time decreases in the DMS and increases in the DLS. Despite these major differences, the decoding power of both networks increases during learning. These results suggest that DMS and DLS neural networks gradually reorganize in different ways in order to progressively increase their control over the behavioral performance.

Sequential Activation of Lateral Hypothalamic Neuronal Populations during Feeding and Their Assembly by Gamma Oscillations.

Neural circuits supporting innate behaviors, such as feeding, exploration, and social interaction, intermingle in the lateral hypothalamus (LH). Although previous studies have shown that individual LH neurons change their firing relative to the baseline during one or more behaviors, the firing rate dynamics of LH populations within behavioral episodes and the coordination of behavior-related LH populations remain largely unknown. Here, using unsupervised graph-based clustering of LH neurons firing rate dynamics in freely behaving male mice, we identified distinct populations of cells whose activity corresponds to feeding, specific times during feeding bouts, or other innate behaviors-social interaction and novel object exploration. Feeding-related cells fired together with a higher probability during slow and fast gamma oscillations (30-60 and 60-90 Hz) than during nonrhythmic epochs. In contrast, the cofiring of neurons signaling other behaviors than feeding was overall similar between slow gamma and nonrhythmic epochs but increased during fast gamma oscillations. These results reveal a neural organization of ethological hierarchies in the LH and point to behavior-specific motivational systems, the dysfunction of which may contribute to mental disorders.

Learning to integrate parts for whole through correlated neural variability.

Neural activity in the cortex exhibits a wide range of firing variability and rich correlation structures. Studies on neural coding indicate that correlated neural variability can influence the quality of neural codes, either beneficially or adversely. However, the mechanisms by which correlated neural variability is transformed and processed across neural populations to achieve meaningful computation remain largely unclear. Here we propose a theory of covariance computation with spiking neurons which offers a unifying perspective on neural representation and computation with correlated noise. We employ a recently proposed computational framework known as the moment neural network to resolve the nonlinear coupling of correlated neural variability with a task-driven approach to constructing neural network models for performing covariance-based perceptual tasks. In particular, we demonstrate how perceptual information initially encoded entirely within the covariance of upstream neurons' spiking activity can be passed, in a near-lossless manner, to the mean firing rate of downstream neurons, which in turn can be used to inform inference. The proposed theory of covariance computation addresses an important question of how the brain extracts perceptual information from noisy sensory stimuli to generate a stable perceptual whole and indicates a more direct role that correlated variability plays in cortical information processing.

Suppression of the Excitability of Nociceptive Secondary Sensory Neurons Following Systemic Administration of Astaxanthin in Rats

Although astaxanthin (AST) has demonstrated a modulatory effect on voltage-gated Ca2+ (Cav) channels and excitatory glutamate neuronal transmission in vitro, particularly on the excitability of nociceptive sensory neurons, its action in vivo remains to be determined. This research sought to determine if an acute intravenous administration of AST in rats reduces the excitability of wide-dynamic range (WDR) spinal trigeminal nucleus caudalis (SpVc) neurons in response to nociceptive and non-nociceptive mechanical stimulation in vivo. In anesthetized rats, extracellular single-unit recordings were carried out on SpVc neurons following mechanical stimulation of the orofacial area. The average firing rate of SpVc WDR neurons in response to both gentle and painful mechanical stimuli significantly and dose-dependently decreased after the application of AST (1–5 mM, i.v.), and maximum suppression of discharge frequency for both non-noxious and nociceptive mechanical stimuli occurred within 10 min. These suppressive effects persisted for about 20 min. These results suggest that acute intravenous AST administration suppresses the SpVc nociceptive transmission, possibly by inhibiting Cav channels and excitatory glutamate neuronal transmission, implicating AST as a potential therapeutic agent for the treatment of trigeminal nociceptive pain without side effects.

Hippocampal storage and recall of neocortical "What"-"Where" representations.

A key question for understanding the function of the hippocampus in memory is how information is recalled from the hippocampus to the neocortex. This was investigated in a neuronal network model of the hippocampal system in which "What" and "Where" neuronal firing rate vectors were applied to separate neocortical modules, which then activated entorhinal cortex "What" and "Where" modules, then the dentate gyrus, then CA3, then CA1, then the entorhinal cortex, and then the backprojections to the neocortex. A rate model showed that the whole system could be trained to recall "Where" in the neocortex from "What" applied as a retrieval cue to the neocortex, and could in principle be trained up towards the theoretical capacity determined largely by the number of synapses onto any one neuron divided by the sparseness of the representation. The trained synaptic weights were then imported into an integrate-and-fire simulation of the same architecture, which showed that the time from presenting a retrieval cue to a neocortex module to recall the whole memory in the neocortex is approximately 100 ms. This is sufficiently fast for the backprojection synapses to be trained onto the still active neocortical neurons during storage of the episodic memory, and this is needed for recall to operate correctly to the neocortex. These simulations also showed that the long loop neocortex-hippocampus-neocortex that operates continuously in time may contribute to complete recall in the neocortex; but that this positive feedback long loop makes the whole dynamical system inherently liable to a pathological increase in neuronal activity. Important factors that contributed to stability included increased inhibition in CA3 and CA1 to keep the firing rates low; and temporal adaptation of the neuronal firing and of active synapses, which are proposed to make an important contribution to stabilizing runaway excitation in cortical circuits in the brain.

Neuronal firing rate diversity lowers the dimension of population covariability.

Populations of neurons produce activity with two central features. First, neuronal responses are very diverse - specific stimuli or behaviors prompt some neurons to emit many action potentials, while other neurons remain relatively silent. Second, the trial-to-trial fluctuations of neuronal response occupy a low dimensional space, owing to significant correlations between the activity of neurons. These two features define the quality of neuronal representation. We link these two aspects of population response using a recurrent circuit model and derive the following relation: the more diverse the firing rates of neurons in a population, the lower the effective dimension of population trial-to-trial covariability. This surprising prediction is tested and validated using simultaneously recorded neuronal populations from numerous brain areas in mice, non-human primates, and in the motor cortex of human participants. Using our relation we present a theory where a more diverse neuronal code leads to better fine discrimination performance from population activity. In line with this theory, we show that neuronal populations across the brain exhibit both more diverse mean responses and lower-dimensional fluctuations when the brain is in more heightened states of information processing. In sum, we present a key organizational principle of neuronal population response that is widely observed across the nervous system and acts to synergistically improve population representation.

Prefrontal working memory signal primarily controls phase-coded information within extrastriate cortex.

In order to understand how prefrontal cortex provides the benefits of working memory (WM) for visual processing we examined the influence of WM on the representation of visual signals in V4 neurons in two macaque monkeys. We found that WM induces strong β oscillations in V4 and that the timing of action potentials relative to this oscillation reflects sensory information- i.e., a phase coding of visual information. Pharmacologically inactivating the Frontal Eye Field part of prefrontal cortex, we confirmed the necessity of prefrontal signals for the WM-driven boost in phase coding of visual information. Indeed, changes in the average firing rate of V4 neurons could be accounted for by WM-induced oscillatory changes. We present a network model to describe how WM signals can recruit sensory areas primarily by inducing oscillations within these areas and discuss the implications of these findings for a sensory recruitment theory of WM through coherence.

Neuronal rhythmicity and cortical arousal in a mouse model of absence epilepsy

Objectives: Absence seizures impair psychosocial function, yet their detailed neuronal basis remains unknown. Recent work in a rat model suggests that cortical arousal state changes prior to seizures and that single neurons show diverse firing patterns during seizures. Our aim was to extend these investigations to a mouse model with studies of neuronal activity and arousal state to facilitate future fundamental investigations of absence epilepsy.Methods: We performed in vivo extracellular single unit recordings on awake head-fixed C3H/HeJ mice. Mice were implanted with tripolar electrodes for cortical electroencephalography (EEG). Extracellular single unit recordings were obtained with glass micropipettes in the somatosensory barrel cortex, while animals ambulated freely on a running wheel. Signals were digitized and analyzed during seizures and at baseline.Results: Neuronal activity was recorded from 36 cortical neurons in 19 mice while EEG showed characteristic 7–8 Hz spike-wave discharges. Different single neurons showed distinct firing patterns during seizures, but the overall mean population neuronal firing rate during seizures was no different from pre-seizure baseline. However, the rhythmicity of neuronal firing during seizures was significantly increased (p < 0.001). In addition, beginning 10s prior to seizure initiation, we observed a progressive decrease in cortical high frequency (>40 Hz) EEG and an increase in lower frequency (1–39 Hz) activity suggesting decreased arousal state.Significance: We found that the awake head-fixed C3H/HeJ mouse model demonstrated rhythmic neuronal firing during seizures, and a decreased cortical arousal state prior to seizure onset. Unlike the rat model we did not observe an overall decrease in neuronal firing during seizures. Similarities and differences across species strengthen the ability to investigate fundamental key mechanisms. Future work in the mouse model will identify the molecular basis of neurons with different firing patterns, their role in seizure initiation and behavioral deficits, with ultimate translation to human absence epilepsy.

The Locus Coeruleus in Chronic Pain.

Pain perception is the consequence of a complex interplay between activation and inhibition. Noradrenergic pain modulation inhibits nociceptive transmission and pain perception. The main source of norepinephrine (NE) in the central nervous system is the Locus Coeruleus (LC), a small but complex cluster of cells in the pons. The aim of this study is to review the literature on the LC-NE inhibitory system, its influence on chronic pain pathways and its frequent comorbidities. The literature research showed that pain perception is the consequence of nociceptive and environmental processing and is modulated by the LC-NE system. If perpetuated in time, nociceptive inputs can generate neuroplastic changes in the central nervous system that reduce the inhibitory effects of the LC-NE complex and facilitate the development of chronic pain and frequent comorbidities, such as anxiety, depression or sleeping disturbances. The exact mechanisms involved in the LC functional shift remain unknown, but there is some evidence that they occur through plastic changes in the medial and lateral pathways and their brain projections. Additionally, there are other influencing factors, like developmental issues, neuroinflammatory glial changes, NE receptor affinity and changes in LC neuronal firing rates.

TE-Spikformer:Temporal-enhanced spiking neural network with transformer

The integration of Spiking Neural Networks (Maass, 1997) and Transformers (Vaswani et al., 2017) has significantly enhanced performance in the field, achieving substantial improvements while ensuring energy efficiency. This amalgamation bears significant exploratory significance. This paper aims to enhance the network’s capacity for extracting temporal information from neuromorphic datasets. By leveraging the Spikformer (Zhou et al., 2023b) architecture, we introduce a novel network named TE-Spikformer. Through thorough analysis, we identified an imbalance in the Average Firing Rates(AFR) of neurons in the layer preceding the classification head across temporal steps. We thoroughly investigate the root cause of this issue, attributing it to the limitations of the network’s use of Batch Normalization (BN) (Ioffe and Szegedy, 2015) layer. To address these challenges, we propose a Batch Group Normalization (BGN) layer. While maintaining the stability of temporal characteristics in the data, we also introduce the Spike Spatio-Temporal Attention(SSTA) module to enhance the network’s ability to capture temporal information. To validate the effectiveness of our approach, we conducted multiple experiments using neuromorphic datasets, including DVS-CIFAR10, DVS128 Gesture, and N-Caltech101. The experimental results demonstrate that our algorithm consistently outperforms baseline methods, achieving accuracy rates of 99.30%, 89.60%, and 87.42%, respectively, thereby attaining state-of-the-art performance in the field.

Dynamic spatial representation of self and others’ actions in the macaque frontal cortex

Modulation of neuronal firing rates by the spatial locations of physical objects is a widespread phenomenon in the brain. However, little is known about how neuronal responses to the actions of biological entities are spatially tuned and whether such spatially tuned responses are affected by social contexts. These issues are of key importance for understanding the neural basis of embodied social cognition, such as imitation and perspective-taking. Here, we show that spatial representation of actions can be dynamically changed depending on others' social relevance and agents of action. Monkeys performed a turn-taking choice task with a real monkey partner sitting face-to-face or a filmed partner in prerecorded videos. Three rectangular buttons (left, center, and right) were positioned in front of the subject and partner as their choice targets. We recorded from single neurons in two frontal nodes in the social brain, the ventral premotor cortex (PMv) and the medial prefrontal cortex (MPFC). When the partner was filmed rather than real, spatial preference for partner-actions was markedly diminished in MPFC, but not PMv, neurons. This social context-dependent modulation in the MPFC was also evident for self-actions. Strikingly, a subset of neurons in both areas switched their spatial preference between self-actions and partner-actions in a diametrically opposite manner. This observation suggests that these cortical areas are associated with coordinate transformation in ways consistent with an actor-centered perspective-taking coding scheme. The PMv may subserve such functions in context-independent manners, whereas the MPFC may do so primarily in social contexts.

Electrophysiological activity pattern of mouse hippocampal CA1 and dentate gyrus under isoflurane anesthesia.

General anesthesia can impact a patient's memory and cognition by influencing hippocampal function. The CA1 and dentate gyrus (DG), serving as the primary efferent and gateway of the hippocampal trisynaptic circuit facilitating cognitive learning and memory functions, exhibit significant differences in cellular composition, molecular makeup, and responses to various stimuli. However, the effects of isoflurane-induced general anesthesia on CA1 and DG neuronal activity in mice are not well understood. In this study, utilizing electrophysiological recordings, we examined neuronal population dynamics and single-unit activity (SUA) of CA1 and DG in freely behaving mice during natural sleep and general anesthesia. Our findings reveal that isoflurane anesthesia shifts local field potential (LFP) to delta frequency and reduces the firing rate of SUA in both CA1 and DG, compared to wakefulness. Additionally, the firing rates of DG neurons are significantly lower than CA1 neurons during isoflurane anesthesia, and the recovery of theta power is slower in DG than in CA1 during the transition from anesthesia to wakefulness, indicating a stronger and more prolonged impact of isoflurane anesthesia on DG. This work presents a suitable approach for studying brain activities during general anesthesia and provides evidence for distinct effects of isoflurane anesthesia on hippocampal subregions.

Initial and corrective submovement encoding differences within primary motor cortex during precision reaching.

Precision reaching often requires corrective submovements to obtain the desired goal. Most studies of reaching have focused on single initial movements, and implied the cortical encoding model was the same for all submovements. However, corrective submovements may show different encoding patterns from the initial submovement with distinct patterns of activation across the population. Two rhesus macaques performed a precision center-out-task with small targets. Neural activity from single units in the primary motor cortex and associated behavioral data were recorded to evaluate movement characteristics. Neural population data and individual neuronal firing rates identified with a peak finding algorithm to identify peaks in hand speed were examined for encoding differences between initial and corrective submovements. Individual neurons were fitted with a regression model that included the reach vector, position, and speed to predict firing rate. For both initial and corrective submovements, the largest effect remained movement direction. We observed a large subset changed their preferred direction greater than 45° between initial and corrective submovements. Neuronal depth of modulation also showed considerable variation when adjusted for movement speed. By using principal component analysis, neural trajectories of initial and corrective submovements progressed through different neural subspaces. These findings all suggest that different neural encoding patterns exist for initial and corrective submovements within the cortex. We hypothesize that this variation in how neurons change to encode small, corrective submovements might allow for a larger portion of the neural space being used to encode a greater range of movements with varying amplitudes and levels of precision.NEW & NOTEWORTHY Neuronal recordings matched with kinematic behavior were collected in a precision center-out task that often required corrective movements. We reveal large differences in preferred direction and depth of modulation between initial and corrective submovements across the neural population. We then present a model of the neural population describing how these shifts in tuning create different subspaces for signaling initial and corrective movements likely to improve motor precision.