Modulation Of Neural Activity Research Articles

Brain Neuroplasticity Leveraging Virtual Reality and Brain-Computer Interface Technologies.

This study explores neuroplasticity through the use of virtual reality (VR) and brain-computer interfaces (BCIs). Neuroplasticity is the brain's ability to reorganize itself by forming new neural connections in response to learning, experience, and injury. VR offers a controlled environment to manipulate sensory inputs, while BCIs facilitate real-time monitoring and modulation of neural activity. By combining VR and BCI, researchers can stimulate specific brain regions, trigger neurochemical changes, and influence cognitive functions such as memory, perception, and motor skills. Key findings indicate that VR and BCI interventions are promising for rehabilitation therapies, treatment of phobias and anxiety disorders, and cognitive enhancement. Personalized VR experiences, adapted based on BCI feedback, enhance the efficacy of these interventions. This study underscores the potential for integrating VR and BCI technologies to understand and harness neuroplasticity for cognitive and therapeutic applications. The researchers utilized the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method to conduct a comprehensive and systematic review of the existing literature on neuroplasticity, VR, and BCI. This involved identifying relevant studies through database searches, screening for eligibility, and assessing the quality of the included studies. Data extraction focused on the effects of VR and BCI on neuroplasticity and cognitive functions. The PRISMA method ensured a rigorous and transparent approach to synthesizing evidence, allowing the researchers to draw robust conclusions about the potential of VR and BCI technologies in promoting neuroplasticity and cognitive enhancement.

Modulus self-adaptive hydrogel optical fiber for long-term modulation of neural activity

Modulus self-adaptive hydrogel optical fiber for long-term modulation of neural activity

Relevance of pre-stimulus oscillatory activity for the perceived valence of emotional facial expressions

The interpretation of emotional facial expressions is crucial in everyday social interactions, and rapid processing of these expressions is necessary. Although extensive research has shed light on the mechanisms involved in facial expression processing, there is limited research on the potential role of the state of neural activity that directly precedes the occurrence of a face. Here, we investigated the potential modulatory role of pre-stimulus oscillatory activity in emotional facial expression processing. We tested emotional facial processing in two experiments, one utilizing artificial and the other natural facial expressions. The participants had to evaluate the emotional valence of the presented ambiguous facial expressions. In a univariate analysis, differences in the oscillation activity of the later rated valence of the faces were observed in both experiments, and these differences were observed even before the presentation of the facial expressions. Importantly, two different multivariate approaches directly supported the relevance of pre-stimulus oscillatory activity by exclusively using pre-stimulus oscillatory data to predict the perceived valence of the latter rated facial expression across the two experiments within as well as across subjects. The behavioral data shows the often observed negativity bias, i.e. ambiguous faces resulted in the tendency to rate them as negative. This negativity bias was related to neural activity modulations in the pre-stimulus period and also within post-stimulus processing related activity. These findings underscore the significance of pre-stimulus oscillatory activity in facial expression processing, indicating a functional role of ongoing neural states that affects the processing of facial expressions and constitute a basis for the well described negativity bias.

Applications of 2D Nanomaterials in Neural Interface.

Neural interfaces are crucial conduits between neural tissues and external devices, enabling the recording and modulation of neural activity. However, with increasing demand, simple neural interfaces are no longer adequate to meet the requirements for precision, functionality, and safety. There are three main challenges in fabricating advanced neural interfaces: sensitivity, heat management, and biocompatibility. The electrical, chemical, and optical properties of 2D nanomaterials enhance the sensitivity of various types of neural interfaces, while the newly developed interfaces do not exhibit adverse reactions in terms of heat management and biocompatibility. Additionally, 2D nanomaterials can further improve the functionality of these interfaces, including magnetic resonance imaging (MRI) compatibility, stretchability, and drug delivery. In this review, we examine the recent applications of 2D nanomaterials in neural interfaces, focusing on their contributions to enhancing performance and functionality. Finally, we summarize the advantages and disadvantages of these nanomaterials, analyze the importance of biocompatibility testing for 2D nanomaterials, and propose that improving and developing composite material structures to enhance interface performance will continue to lead the forefront of this field.

Volitional modulation of neuronal activity in the external globus pallidus by engagement of the cortical-basal ganglia circuit.

Volitional modulation of neural activity is not confined to the cortex but extends to various brain regions. Yet, it remains unclear whether neurons in the basal ganglia structure, the external globus pallidus (GPe), can be volitionally controlled. Here, we employed a volitional conditioning task to compare the volitional modulation of GPe and primary motor cortex (M1) neurons as well as the underlying circuits and control mechanisms. The results revealed that the volitional modulation of GPe neuronal activity engaged both M1 and substantia nigra pars reticulata (SNr) neurons, indicating the involvement of the cortex-GPe-SNr loop. In contrast, the volitional modulation of M1 neurons primarily occurred through the engagement of M1 local circuitry. Furthermore, lesioning M1 neurons did not affect the volitional learning or volitional control signal in GPe, whereas lesioning of GPe neurons impaired the learning process for the volitional modulation of M1 neuronal activity at the intermediate stage. Additionally, lesion of GPe neurons enhanced M1 neuronal activity when performing the volitional control task without reward delivery and a random reward test. Taken together, our findings demonstrated that GPe neurons could be volitionally controlled by engagement of the cortical-basal ganglia circuit and inhibit learning process for the volitional modulation of M1 neuronal activity by regulating M1 neuronal activity. Thus, GPe neurons can be effectively harnessed for independent volitional modulation for neurorehabilitation in patients with cortical damage. KEY POINTS: The cortical-basal ganglia circuit contributes to the volitional modulation of GPe neurons. Volitional modulation of M1 neuronal activity mainly engages M1 local circuitry. Bilateral GPe lesioning impedes volitional learning at the intermediate stages. Lesioning of GPe neurons inhibits volitional learning process by regulating M1 neuronal activity.

Graphdiyne as a Highly Efficient and Neuron-Targeted Photothermal Transducer for in Vivo Neuromodulation.

Photothermal modulation of neural activity offers a promising approach for understanding brain circuits and developing therapies for neurological disorders. However, the low neuron selectivity and inefficient light-to-heat conversion of existing photothermal nanomaterials significantly limit their potential for neuromodulation. Here, we report that graphdiyne (GDY) can be developed into an efficient neuron-targeted photothermal transducer for in vivo modulation of neuronal activity through rational surface functionalization. We functionalize GDY with polyethylene glycol (PEG) through noncovalent hydrophobic interactions, followed by antibody conjugation to specifically target the temperature-sensitive transient receptor potential cation channel subfamily V member 1 (TRPV1) on the surface of neural cells. The nanotransducer not only exhibits high photothermal conversion efficiency in the near-infrared region but also shows great TRPV1-targeting capability. This enables photothermal activation of TRPV1, leading to neurotransmitter release in cells and modulation of neural firing in living mice. With its precision and selectivity, the GDY-based transducer provides an innovative avenue for understanding brain function and developing therapeutic strategies for neurodegenerative diseases.

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited a recently developed non-invasive deep brain stimulation technique called transcranial temporal interference stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomized, sham-controlled, double-blind study. Striatal tTIS applied at 80 Hz, but not at 20 Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80 Hz, but not 20 Hz, tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, expanding our tools for the study of causal relationships between deep brain structures and human behaviour.

Modulation of neural activity in response to dance training in Parkinson’s: A case study

Modulation of neural activity in response to dance training in Parkinson’s: A case study

Modulatory Effects on Laminar Neural Activity Induced by Near-Infrared Light Stimulation with a Continuous Waveform to the Mouse Inferior Colliculus In Vivo.

Infrared neural stimulation (INS) is a promising area of interest for the clinical application of a neuromodulation method. This is in part because of its low invasiveness, whereby INS modulates the activity of the neural tissue mainly through temperature changes. Additionally, INS may provide localized brain stimulation with less tissue damage. The inferior colliculus (IC) is a crucial auditory relay nucleus and a potential target for clinical application of INS to treat auditory diseases and develop artificial hearing devices. Here, using continuous INS with low to high-power density, we demonstrate the laminar modulation of neural activity in the mouse IC in the presence and absence of sound. We investigated stimulation parameters of INS to effectively modulate the neural activity in a facilitatory or inhibitory manner. A mathematical model of INS-driven brain tissue was first simulated, temperature distributions were numerically estimated, and stimulus parameters were selected from the simulation results. Subsequently, INS was administered to the IC of anesthetized mice, and the modulation effect on the neural activity was measured using an electrophysiological approach. We found that the modulatory effect of INS on the spontaneous neural activity was bidirectional between facilitatory and inhibitory effects. The modulatory effect on sound-evoked responses produced only an inhibitory effect to all examined stimulus intensities. Thus, this study provides important physiological evidence on the response properties of IC neurons to INS. Overall, INS can be used for the development of new therapies for neurological disorders and functional support devices for auditory central processing.

Stress increases hepatic release of lipocalin 2 which contributes to anxiety-like behavior in mice.

Chronic stress induces anxiety disorders via both neural pathways and circulating factors. Although many studies have elucidated the neural circuits involved in stress-coping behaviors, the origin and regulatory mechanism of peripheral cytokines in behavioural regulation under stress conditions are not fully understood. Here, we identified a serum cytokine, lipocalin 2 (LCN2), that was upregulated in participants with anxiety disorders. Using a mouse model of chronic restraint stress (CRS), circulating LCN2 was found to be related to stress-induced anxiety-like behaviour via modulation of neural activity in the medial prefrontal cortex (mPFC). These results suggest that stress increases hepatic LCN2 via a neural pathway, leading to disrupted cortical functions and behaviour.

Modulatory effects of low-intensity retinal ultrasound stimulation on rapid and non-rapid eye movement sleep.

Prior investigations have established that the manipulation of neural activity has the potential to influence both rapid eye movement and non-rapid eye movement sleep. Low-intensity retinal ultrasound stimulation has shown effectiveness in the modulation of neural activity. Nevertheless, the specific effects of retinal ultrasound stimulation on rapid eye movement and non-rapid eye movement sleep, as well as its potential to enhance overall sleep quality, remain to be elucidated. Here, we found that: In healthy mice, retinal ultrasound stimulation: (i) reduced total sleep time and non-rapid eye movement sleep ratio; (ii) changed relative power and sample entropy of the delta (0.5-4Hz) in non-rapid eye movement sleep; and (iii) enhanced relative power of the theta (4-8Hz) and reduced theta-gamma coupling strength in rapid eye movement sleep. In Alzheimer's disease mice with sleep disturbances, retinal ultrasound stimulation: (i) reduced the total sleep time; (ii) altered the relative power of the gamma band during rapid eye movement sleep; and (iii) enhanced the coupling strength of delta-gamma in non-rapid eye movement sleep and weakened the coupling strength of theta-fast gamma. The results indicate that retinal ultrasound stimulation can modulate rapid eye movement and non-rapid eye movement-related neural activity; however, it is not beneficial to the sleep quality of healthy and Alzheimer's disease mice.

Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes

Objective. The controlled delivery of potassium is an interesting neuromodulation modality, being potassium ions involved in shaping neuron excitability, synaptic transmission, network synchronization, and playing a key role in pathological conditions like epilepsy and spreading depression. Despite many successful examples of pre-clinical devices able to influence the extracellular potassium concentration, computational frameworks capturing the corresponding impact on neuronal activity are still missing. Approach. We present a finite-element model describing a PEDOT:PSS-coated microelectrode (herein, simply ionic actuator) able to release potassium and thus modulate the activity of a cortical neuron in an in-vitro-like setting. The dynamics of ions in the ionic actuator, the neural membrane, and the cellular fluids are solved self-consistently. Main results. We showcase the capability of the model to describe on a physical basis the modulation of the intrinsic excitability of the cell and of the synaptic transmission following the electro-ionic stimulation produced by the actuator. We consider three case studies for the ionic actuator with different levels of selectivity to potassium: ideal selectivity, no selectivity, and selectivity achieved by embedding ionophores in the polymer. Significance. This work is the first step toward a comprehensive computational framework aimed to investigate novel neuromodulation devices targeting specific ionic species, as well as to optimize their design and performance, in terms of the induced modulation of neural activity.

Commit to your putting stroke: exploring the impact of quiet eye duration and neural activity on golf putting performance.

There is a growing interest in characterizing the cognitive-motor processes that underlie superior performance in highly skilled athletes. The aim of this study was to explore neural markers of putting performance in highly skilled golfers by recording mobile EEG (electroencephalogram) during the pre-shot period. Twenty-eight right-handed participants (20 males) with a mean age of 24.2 years (± 6.4) and an average handicap of +1.7 (± 6.4) completed a testing session. Following the warm-up, participants completed 140 putts from a distance of 8ft (2.4m), with putts taken from 5 different positions. While putting, participants wore an eye tracker and a gel-based EEG system with 32 electrodes. Time and frequency domain features of the EEG signals were extracted to characterize Movement-Related Cortical Potentials (MRCP) and rhythmic modulations of neural activity in theta, alpha, sensorimotor and beta frequency bands associated with putting performance. Eye-tracking data demonstrate that mean Quiet Eye durations are not a reliable marker of expertise as the same duration was found for both successful and unsuccessful putts. Following rigorous data processing data from 12 participants (8 males, mean age 21.6 years ± 5.4, average handicap +1.5 ± 4.4) were included in the EEG analysis. MRCP analysis revealed performance-based differences, with unsuccessful putts having a greater negative amplitude in comparison to successful putts. Time frequency analysis of the EEG data revealed that successful putts exhibit distinct neural activity profiles compared to unsuccessful ones. For successful putts, greater suppression of beta was present in the central region prior to the putt. By contrast, increased frontal theta power was present for unsuccessful putts immediately before the putt (consistent with hesitation and the need for motor plan adjustments prior to execution). We propose that neural activity may provide plausible insights into the mechanisms behind why identical QE durations can lead to both success and failure. From an applied perspective, this study highlights the merits of a multi-measure approach to gain further insights into performance differences within highly skilled golfers. We discuss considerations for future research and solutions to address the challenges related to the complexities of collecting clean EEG signals within naturalistic sporting contexts.

Development and application of implantable electrical neural electrodes

Implantable nerve electrodes are a crucial neuro-engineering device that can play a pivotal role in the treatment of various neurological disorders. As the fundamental unit of the nervous system, neurons possess the capability to generate electrical signals, which serve as the primary means of information transmission. Implantable neural electrodes have the capacity to intercept and record these electrical signals, thereby providing invaluable insights into understanding nervous system functionality. Furthermore, these electrodes enable precise modulation of neural activity through targeted delivery of pulses to neurons. Surgical implantation of these electrodes within the nervous system allows for simulation or inhibition of neural signals with therapeutic objectives in mind. This article comprehensively reviews the significance and application of implantable neural electrodes in neuro-engineering while highlighting their immense potential in enhancing patients quality of life across diverse neurological conditions With further research and technological improvements, we can expect implantable neural electrodes to play an even greater role in improving the quality of life of patients, treating neurological diseases, and advancing neuroscience.

Bursting activity in the reduced mean-field model of neuron-glial interaction

The study of neural activity synchronization in the brain is a central focus of modern neurobiology and neurodynamics. In a healthy brain, cognitive functions necessitate the accurate integration of neural activity at specific spatiotemporal scales. Some neurological and psychiatric disorders exhibit observable variations in patterns of synchronous population activity. One of the most significant and compelling synchronous population activity patterns is the bursting activity that participates in various informational and physiological processes, including epilepsy. Several mathematical models have been proposed to explain the mechanisms of formation of the bursting activity. The most intriguing and scientifically sound models enable incorporation of astrocytic modulation of neural activity [1]. In this paper, we present a novel phenomenological model for accurately replicating the bursting neural population activity. Our model builds upon the Tsodyks-Markram [2] model and incorporates vital aspects of neuron-glial interaction through a tripartite synapse. The presented model is a simplified version of the previously proposed model [3]. During astrocyte activity (which lasts seconds), we can set the probability of neurotransmitter release, u, which is determined in fractions of a second. This enables the proposed model to be written in the following manner: r=–E+α ln(1+exp((Ju(Y)xE+I0)/α)), =(1–x)/τD–u(Y)xE, =–y/τY+βσy(X). Here, E(t) represents the average neuronal activity of the excitatory population, while x(t) denotes the quantity of available neurotransmitter. Additionally, y(t) describes the concentration of gliotransmitters, which are released as a result of biochemical reactions during neuron-astrocyte interactions. The function describes the alteration in the likelihood of neurotransmitter release when gliotransmitters are present u(y)=u0+(∆u0)/(1+exp(–50(y–ythr)). Here u0 represents the probability of neurotransmitter release without astrocytic influence; ∆u0 indicates the change in the probability of neurotransmitter release caused by the interaction of the gliotransmitter with the presynaptic terminal, and ythr represents the threshold value that determines the change in the probability of neurotransmitter release due to the effect of a gliotransmitter. The function describes the influence of neurotransmitter on the concentration of the gliotransmitter σy(x)=1/(1+exp(–20(x–xthr)), where xthr is the astrocyte activation threshold. Note that the proposed model does not account for synaptic depression’s mechanism. Therefore, various dynamical regimes’ formation in the model is solely controlled by astrocytic dynamics. In the study, control parameters I0 and u0 were selected while the remaining parameters were held constant. Specifically, τ=0.013, τD=0.08, α=1.58, J=3.07. Changes in the concentration of neurotransmitters and gliotransmitters were characterized by parameters ∆u0=0.305, τν=3.3, β=0.3, xxthr=0.75, ythr=0.4. The research was conducted using computer modeling and numerical methods in nonlinear dynamics. The proposed model exhibits a diverse range of population activity patterns, such as spiking and bursting regular and chaotic activity. Chaotic dynamics zones are identified in the control parameter plane. An account is given of the mechanisms behind the emergence of these activity patterns through bifurcation analysis. It is shown that the occurrence of chaotic activity in the system can be associated both with the cascade of period doubling bifurcations and with the further development of chaos, as a result of which a homoclinic attractor appears in the system according to the Shilnikov scenario. It was also shown that multistability is observed in the system in a certain range of parameters. Note that the emergence of multistability and bursting activity in the model is independent of the intricacy of neuron and glial cell dynamics. These dynamics are instead influenced by the feedback loop between the presynaptic neuron and the glial cell. The effects of neuron-like dynamics and neural-glial interaction demonstrated are generally applicable, without specifying particular characteristics of neural-glial interaction, network architecture, or single-cell neuron dynamics. It should be noted that our proposed model solely concerns the potentiation of synaptic transmission by astrocytes. In summary, the proposed phenomenological model for population activity can replicate various patterns of neuron activity found in a wide range of dynamic memory and information processing studies. This research can potentially lead to the development of new, effective treatment methods for neurological diseases that involve neuron-glial interaction. Another potential application for these results is in the development of an optimized live chip that has preset functions. This requires a deeper understanding of rhythmogenesis in neural networks and brain function.

Research Progress on Effects of Ginsenoside Rg2 and Rh1 on Nervous System and Related Mechanisms

Neurological-related disorders are diseases that affect the body’s neurons or peripheral nerve tissue, such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). The development of neurological disorders can cause serious harm to the quality of life and functioning of the patient. The use of traditional therapeutic agents such as dopamine-promoting drugs, anticholinergic drugs, cholinesterase inhibitors, and NMDA receptor antagonists is often accompanied by a series of side effects such as drug resistance, cardiac arrhythmia, liver function abnormalities, and blurred vision. Therefore, there is an urgent need to find a therapeutic drug with a high safety profile and few side effects. Herbal medicines are rich in active ingredients that are natural macromolecules. Ginsenoside is the main active ingredient of ginseng, which has a variety of pharmacological effects and is considered to have potential value in the treatment of human diseases. Modern pharmacological studies have shown that ginsenosides Rg2 and Rh1 have strong pharmacological activities in the nervous system, with protective effects on nerve cells, improved resistance to neuronal injury, modulation of neural activity, resistance to cerebral ischemia/reperfusion injury, improvement of brain damage after eclampsia hemorrhage, improvement of memory and cognitive deficits, treatment of AD and vascular dementia, alleviation of anxiety, pain, and inhibition of ionic-like behavior. In this article, we searched the pharmacological research literature of Rg2 and Rh1 in the field of neurological diseases, summarized the latest research progress of the two ginsenosides, and reviewed the pharmacological effects and mechanisms of Rg2 and Rh1, which provided a new way of thinking for the research of the active ingredients in ginseng anti-neurological diseases and the development of new drugs.

Functional Magnetic Resonance Imaging Signatures of Pavlovian and Instrumental Valuation Systems during a Modified Orthogonalized Go/No-go Task.

Motivational (i.e., Pavlovian) values interfere with instrumental responding and can lead to suboptimal decision-making. In humans, task-based neuroimaging studies have only recently started illuminating the functional neuroanatomy of Pavlovian biasing of instrumental control. To provide a mechanistic understanding of the neural dynamics underlying the Pavlovian and instrumental valuation systems, analysis of neuroimaging data has been informed by computational modeling of conditioned behavior. Nonetheless, because of collinearities in Pavlovian and instrumental predictions, previous research failed to tease out hemodynamic activity that is parametrically and dynamically modulated by coexistent Pavlovian and instrumental value expectations. Moreover, neural correlates of Pavlovian to instrumental transfer effects have so far only been identified in extinction (i.e., in the absence of learning). In this study, we devised a modified version of the orthogonalized go/no-go paradigm, which introduced Pavlovian-only catch trials to better disambiguate trial-by-trial Pavlovian and instrumental predictions in both sexes. We found that hemodynamic activity in the ventromedial pFC covaried uniquely with the model-derived Pavlovian value expectations. Notably, modulation of neural activity encoding for instrumental predictions in the supplementary motor cortex was linked to successful action selection in conflict conditions. Furthermore, hemodynamic activity in regions pertaining to the limbic system and medial pFC was correlated with synergistic Pavlovian and instrumental predictions and improved conditioned behavior during congruent trials. Altogether, our results provide new insights into the functional neuroanatomy of decision-making and corroborate the validity of our variant of the orthogonalized go/no-go task as a behavioral assay of the Pavlovian and instrumental valuation systems.

Closed‐Loop Optogenetic Modulation of Neural Activities in Freely Moving Mice with Multimodal Fibers

AbstractThe precise manipulation of neural activity is of great significance to reveal the function of complex neural circuits in brain, especially the mechanism of neurological disorders such as epilepsy, Parkinson's, and Alzheimer's disease. In the past decades, optogenetics has become a powerful tool to investigate the function of neural circuits due to its unique advantages of cell specificity and high spatiotemporal resolution. However, to date, most optogenetic manipulation has been conducted in an open‐loop fashion. The closed‐loop neural modulation is still an important task. Here, a closed‐loop optogenetic modulation system is developed for ultra‐fast, ‐accurate, and ‐stable manipulation of neural activities in behaving mice. Specifically, this system is mediated by a functional fiber probe with excellent low optical loss (0.052 dB cm−1 at 589 nm) and electrical impedance (5.40 MΩ µm−2 at 1 kHz). In vivo electrophysiology and behavioral experiments demonstrated that the system can be successfully applied for the identification and intervention of seizures in epilepsy mice with high efficiency. It is envision that the closed‐loop manipulation system has promising applications in brain science, neuroscience, and neuromodulation therapies.

Editorial: 90th anniversary of the Sherrington and Adrian Nobel Prize: brain rhythms and oscillations in neural activity modulation, brain function and dysfunction

Editorial: 90th anniversary of the Sherrington and Adrian Nobel Prize: brain rhythms and oscillations in neural activity modulation, brain function and dysfunction

Computational assessment of visual coding across mouse brain areas and behavioural states.

Our brain is bombarded by a diverse range of visual stimuli, which are converted into corresponding neuronal responses and processed throughout the visual system. The neural activity patterns that result from these external stimuli vary depending on the object or scene being observed, but they also change as a result of internal or behavioural states. This raises the question of to what extent it is possible to predict the presented visual stimuli from neural activity across behavioural states, and how this varies in different brain regions. To address this question, we assessed the computational capacity of decoders to extract visual information in awake behaving mice, by analysing publicly available standardised datasets from the Allen Brain Institute. We evaluated how natural movie frames can be distinguished based on the activity of units recorded in distinct brain regions and under different behavioural states. This analysis revealed the spectrum of visual information present in different brain regions in response to binary and multiclass classification tasks. Visual cortical areas showed highest classification accuracies, followed by thalamic and midbrain regions, with hippocampal regions showing close to chance accuracy. In addition, we found that behavioural variability led to a decrease in decoding accuracy, whereby large behavioural changes between train and test sessions reduced the classification performance of the decoders. A generalised linear model analysis suggested that this deterioration in classification might be due to an independent modulation of neural activity by stimulus and behaviour. Finally, we reconstructed the natural movie frames from optimal linear classifiers, and observed a strong similarity between reconstructed and actual movie frames. However, the similarity was significantly higher when the decoders were trained and tested on sessions with similar behavioural states. Our analysis provides a systematic assessment of visual coding in the mouse brain, and sheds light on the spectrum of visual information present across brain areas and behavioural states.