Neuronal Populations Research Articles

Jointly efficient encoding and decoding in neural populations.

The efficient coding approach proposes that neural systems represent as much sensory information as biological constraints allow. It aims at formalizing encoding as a constrained optimal process. A different approach, that aims at formalizing decoding, proposes that neural systems instantiate a generative model of the sensory world. Here, we put forth a normative framework that characterizes neural systems as jointly optimizing encoding and decoding. It takes the form of a variational autoencoder: sensory stimuli are encoded in the noisy activity of neurons to be interpreted by a flexible decoder; encoding must allow for an accurate stimulus reconstruction from neural activity. Jointly, neural activity is required to represent the statistics of latent features which are mapped by the decoder into distributions over sensory stimuli; decoding correspondingly optimizes the accuracy of the generative model. This framework yields in a family of encoding-decoding models, which result in equally accurate generative models, indexed by a measure of the stimulus-induced deviation of neural activity from the marginal distribution over neural activity. Each member of this family predicts a specific relation between properties of the sensory neurons-such as the arrangement of the tuning curve means (preferred stimuli) and widths (degrees of selectivity) in the population-as a function of the statistics of the sensory world. Our approach thus generalizes the efficient coding approach. Notably, here, the form of the constraint on the optimization derives from the requirement of an accurate generative model, while it is arbitrary in efficient coding models. Moreover, solutions do not require the knowledge of the stimulus distribution, but are learned on the basis of data samples; the constraint further acts as regularizer, allowing the model to generalize beyond the training data. Finally, we characterize the family of models we obtain through alternate measures of performance, such as the error in stimulus reconstruction. We find that a range of models admits comparable performance; in particular, a population of sensory neurons with broad tuning curves as observed experimentally yields both low reconstruction stimulus error and an accurate generative model that generalizes robustly to unseen data.

Investigating the Impact of Intracerebroventricular Streptozotocin on Female Rats with and without Ovaries: Implications for Alzheimer's Disease.

To contribute to research on female models of Alzheimer's disease (AD), our aim was to study the effect of intracerebroventricular (ICV) injection of streptozotocin (STZ) in female rats, and to evaluate a potential neuroprotective action of ovarian steroids against STZ. Female rats were either ovariectomized (OVX) or kept with ovaries (Sham) two weeks before ICV injections. Animals were injected with either vehicle (artificial cerebrospinal fluid, aCSF) or STZ (3mg/kg) and separated into four experimental groups: Sham + aCSF, Sham + STZ, OVX + aCSF and OVX + STZ. Nineteen days post-injection, we assessed different behavioral aspects: burying, anxiety and exploration, object recognition memory, spatial memory, and depressive-like behavior. Immunohistochemistry and Immunoblot analyses were performed in the hippocampus to examine changes in AD-related proteins and neuronal and microglial populations. STZ affected burying and exploratory behavior depending on ovarian status, and impaired recognition but not spatial memory. STZ and ovariectomy increased depressive-like behavior. Interestingly, STZ did not alter the expression of β-amyloid peptide or Tau phosphorylated forms. STZ affected the neuronal population from the Dentate Gyrus, where immature neurons were more vulnerable to STZ in OVX rats. Regarding microglia, STZ increased reactive cells, and the OVX + STZ group showed an increase in the total cell number. In sum, STZ partially affected female rats, compared to what was previously reported for males. Although AD is more frequent in women, reports about the effect of ICV-STZ in female rats are scarce. Our work highlights the need to deepen into the effects of STZ in the female brain and study possible sex differences.

How to design optimal brain stimulation to modulate phase-amplitude coupling?

Objective. Phase-amplitude coupling (PAC), the coupling of the amplitude of a faster brain rhythm to the phase of a slower brain rhythm, plays a significant role in brain activity and has been implicated in various neurological disorders. For example, in Parkinson’s disease, PAC between the beta (13–30 Hz) and gamma (30–100 Hz) rhythms in the motor cortex is exaggerated, while in Alzheimer’s disease, PAC between the theta (4–8 Hz) and gamma rhythms is diminished. Modulating PAC (i.e. reducing or enhancing PAC) using brain stimulation could therefore open new therapeutic avenues. However, while it has been previously reported that phase-locked stimulation can increase PAC, it is unclear what the optimal stimulation strategy to modulate PAC might be. Here, we provide a theoretical framework to narrow down the experimental optimisation of stimulation aimed at modulating PAC, which would otherwise rely on trial and error. Approach. We make analytical predictions using a Stuart–Landau model, and confirm these predictions in a more realistic model of coupled neural populations. Main results. Our framework specifies the critical Fourier coefficients of the stimulation waveform which should be tuned to optimally modulate PAC. Depending on the characteristics of the amplitude response curve of the fast population, these components may include the slow frequency, the fast frequency, combinations of these, as well as their harmonics. We also show that the optimal balance of energy between these Fourier components depends on the relative strength of the endogenous slow and fast rhythms, and that the alignment of fast components with the fast rhythm should change throughout the slow cycle. Furthermore, we identify the conditions requiring to phase-lock stimulation to the fast and/or slow rhythms. Significance. Together, our theoretical framework lays the foundation for guiding the development of innovative and more effective brain stimulation aimed at modulating PAC for therapeutic benefit.

Neurofeedback training can modulate task-relevant memory replay rate in rats.

Hippocampal replay - the time-compressed, sequential reactivation of ensembles of neurons related to past experience - is a key neural mechanism of memory consolidation. Replay typically coincides with a characteristic pattern of local field potential activity, the sharp-wave ripple (SWR). Reduced SWR rates are associated with cognitive impairment in multiple models of neurodegenerative disease, suggesting that a clinically viable intervention to promote SWRs and replay would prove beneficial. We therefore developed a neurofeedback paradigm for rat subjects in which SWR detection triggered rapid positive feedback in the context of a memory-dependent task. This training protocol increased the prevalence of task-relevant replay during the targeted neurofeedback period by changing the temporal dynamics of SWR occurrence. This increase was also associated with neural and behavioral forms of compensation after the targeted period. These findings reveal short-timescale regulation of SWR generation and demonstrate that neurofeedback is an effective strategy for modulating hippocampal replay.

The mechanics of correlated variability in segregated cortical excitatory subnetworks

Understanding the genesis of shared trial-to-trial variability in neuronal population activity within the sensory cortex is critical to uncovering the biological basis of information processing in the brain. Shared variability is often a reflection of the structure of cortical connectivity since it likely arises, in part, from local circuit inputs. A series of experiments from segregated networks of (excitatory) pyramidal neurons in the mouse primary visual cortex challenge this view. Specifically, the across-network correlations were found to be larger than predicted given the known weak cross-network connectivity. We aim to uncover the circuit mechanisms responsible for these enhanced correlations through biologically motivated cortical circuit models. Our central finding is that coupling each excitatory subpopulation with a specific inhibitory subpopulation provides the most robust network-intrinsic solution in shaping these enhanced correlations. This result argues for the existence of excitatory-inhibitory functional assemblies in early sensory areas which mirror not just response properties but also connectivity between pyramidal cells. Furthermore, our findings provide theoretical support for recent experimental observations showing that cortical inhibition forms structural and functional subnetworks with excitatory cells, in contrast to the classical view that inhibition is a nonspecific blanket suppression of local excitation.

Shifts in attention drive context-dependent subspace encoding in anterior cingulate cortex in mice during decision making

Attention supports decision making by selecting the features that are relevant for decisions. Selective enhancement of the relevant features and inhibition of distractors has been proposed as potential neural mechanisms driving this selection process. Yet, how attention operates when relevance cannot be directly determined, and the attention signal needs to be internally constructed is less understood. Here we recorded from populations of neurons in the anterior cingulate cortex (ACC) of mice in an attention-shifting task where relevance of stimulus modalities changed across blocks of trials. In contrast with V1 recordings, decoding of the irrelevant modality gradually declined in ACC after an initial transient. Our analytical proof and a recurrent neural network model of the task revealed mutually inhibiting connections that produced context-gated suppression as observed in mice. Using this RNN model we predicted a correlation between contextual modulation of individual neurons and their stimulus drive, which we confirmed in ACC but not in V1.

In vivo magnetogenetics for cell-type-specific targeting and modulation of brain circuits.

Neuromodulation technologies are crucial for investigating neuronal connectivity and brain function. Magnetic neuromodulation offers wireless and remote deep brain stimulations that are lacking in optogenetic- and wired-electrode-based tools. However, due to the limited understanding of working principles and poorly designed magnetic operating systems, earlier magnetic approaches have yet to be utilized. Furthermore, despite its importance in neuroscience research, cell-type-specific magnetic neuromodulation has remained elusive. Here we present a nanomaterials-based magnetogenetic toolbox, in conjunction with Cre-loxP technology, to selectively activate genetically encoded Piezo1 ion channels in targeted neuronal populations via torque generated by the nanomagnetic actuators in vitro and in vivo. We demonstrate this cell-type-targeting magnetic approach for remote and spatiotemporal precise control of deep brain neural activity in multiple behavioural models, such as bidirectional feeding control, long-term neuromodulation for weight control in obese mice and wireless modulation of social behaviours in multiple mice in the same physical space. Our study demonstrates the potential of cell-type-specific magnetogenetics as an effective and reliable research tool for life sciences, especially in wireless, long-term and freely behaving animals.

Two Distinct Neuronal Populations in the Rat Parafascicular Nucleus Oppositely Encode the Engagement in Stimulus-driven Reward-seeking

Background:: The thalamus is a phylogenetically well-preserved structure. Known to densely contact cortical regions, its role in the transmission of sensory information to the striatal complex has been widely reconsidered in recent years. Methods:: The parafascicular nucleus of the thalamus (Pf) has been implicated in the orientation of attention toward salient sensory stimuli. In a stimulus-driven reward-seeking task, we sought to characterize the electrophysiological activity of Pf neurons in rats. Results:: We observed a predominance of excitatory over inhibitory responses for all events in the task. Neurons responded more strongly to the stimulus compared to lever-pressing and reward collecting, confirming the strong involvement of the Pf in sensory information processing. The use of long sessions allowed us to compare neuronal responses to stimuli between trials when animals were engaged in action and those when they were not. We distinguished two populations of neurons with opposite responses: MOTIV+ neurons responded more intensely to stimuli followed by a behavioral response than those that were not. Conversely, MOTIV- neurons responded more strongly when the animal did not respond to the stimulus. In addition, the latency of excitation of MOTIV- neurons was shorter than that of MOTIV+ neurons. Conclusion:: Through this encoding, the Pf could perform an early selection of environmental stimuli transmitted to the striatum according to motivational level

Chemogenetic activation ofarcuate nucleus NPY and NPY/AgRP neurons increases feeding behaviour in mice

Neuropeptide Y (NPY) plays a crucial role in controlling energy homeostasis and feeding behaviour. The role of NPY neurons located in the arcuate nucleus of the hypothalamus (Arc) in responding to homeostatic signals has been the focus of much investigation, but most studies have used AgRP promoter-driven models, which do not fully encompass Arc NPY neurons. To directly investigate NPY-expressing versus AgRP-expressing Arc neurons function, we utilised chemogenetic techniques in NPY-Cre and AgRP-Cre animals to activate Arc NPY or AgRP neurons in the presence of food and food-related stimuli. Our findings suggest that chemogenetic activation of the broader population of Arc NPY neurons, including AgRP-positive and AgRP-negative NPY neurons, has equivalent effects on feeding behaviour as activation of Arc AgRP neurons. Our results demonstrate that these Arc NPY neurons respond specifically to caloric signals and do not respond to non-caloric signals, in line with what has been observed in AgRP neurons. Activating Arc NPY neurons significantly increases food consumption and influences macronutrient selection to prefer fat intake.

Neuroimmune Interactions in the Intestine

Recent advances have contributed to a mechanistic understanding of neuroimmune interactions in the intestine and revealed an essential role of this cross talk for gut homeostasis and modulation of inflammatory and infectious intestinal diseases. In this review, we describe the innervation of the intestine by intrinsic and extrinsic neurons and then focus on the bidirectional communication between neurons and immune cells. First, we highlight the contribution of neuronal subtypes to the development of colitis and discuss the different immune and epithelial cell types that are regulated by neurons via the release of neuropeptides and neurotransmitters. Next, we review the role of intestinal inflammation in the development of visceral hypersensitivity and summarize how inflammatory mediators induce peripheral and central sensitization of gut-innervating sensory neurons. Finally, we outline the importance of immune cells and gut microbiota for the survival and function of different neuronal populations at homeostasis and during bacterial and helminth infection.

An Unpredictable Brain Is a Conscious, Responsive Brain.

Severe traumatic brain injuries typically result in loss of consciousness or coma. In deeply comatose patients with traumatic brain injury, cortical dynamics become simple, repetitive, and predictable. We review evidence that this low-complexity, high-predictability state results from a passive cortical state, represented by a stable repetitive attractor, that hinders the flexible formation of neuronal ensembles necessary for conscious experience. Our data and those from other groups support the hypothesis that this cortical passive state is because of the loss of thalamocortical input. We identify the unpredictability and complexity of cortical dynamics captured by local field potential as a sign of recovery from this passive coma attractor. In this perspective article, we discuss how these electrophysiological biomarkers of the recovery of consciousness could inform the design of closed-loop stimulation paradigms to treat disorders of consciousness.

Temporal information in the anterior cingulate cortex relates to accumulated experiences

Anterior cingulate cortex (ACC) activity is important for operations that require the ability to integrate multiple experiences over time, such as rule learning, cognitive flexibility, working memory, and long-term memory recall. To shed light on this, we analyzed neuronal activity while rats repeated the same behaviors during hour-long sessions to investigate how activity changed over time. We recorded neuronal ensembles as rats performed a decision-free operant task with varying reward likelihoods at three different response ports (n= 5). Neuronal state space analysis revealed that each repetition of a behavior was distinct, with more recent behaviors more similar than those further apart in time. ACC activity was dominated by a slow, gradual change in low-dimensional representations of neural state space aligning with the pace of behavior. Temporal progression, or drift, was apparent on the top principal component for every session and was driven by the accumulation of experiences and not an internal clock. Notably, these signals were consistent across subjects, allowing us to accurately predict trial numbers based on a model trained on data from a different animal. We observed that non-continuous ramping firing rates over extended durations (tens of minutes) drove the low-dimensional ensemble representations. 40% of ACC neurons' firing ramped over a range of trial lengths and combinations of shorter duration ramping neurons created ensembles that tracked longer durations. These findings provide valuable insights into how the ACC, at an ensemble level, conveys temporal information by reflecting the accumulation of experiences over extended periods.

Distinct action signals by subregions in nucleus accumbens during STOP-change performance.

Nucleus accumbens (NAc) is thought to contribute to motivated behavior by signaling the value of reward-predicting cues and the delivery of anticipated reward. NAc is subdivided into core and shell, with each region containing different populations of neurons that increase or decrease firing to rewarding events. While there are various and numerous theories of functions pertaining to these subregions and cell types, most are in the context of reward processing, with fewer considering that NAc might serve functions related to action selection more generally. We recorded from single neurons in NAc as rats of both sexes performed a STOP-change task that is commonly used to study motor control and impulsivity. In this task, rats respond quickly to a spatial cue on 80% of trials (GO) and must stop and redirect planned movement on 20% of trials (STOP). We found that the activity of reward-excited neurons signaled accurate response direction on GO, but not STOP trials, and that these neurons exhibited higher pre-cue firing after correct trials resulting in stronger firing during correct GO trials and errant STOP trials, while reward-inhibited neurons significantly represented response direction on STOP trials at the time of the instrumental response. Finally, the proportion of reward-excited to reward-inhibited neurons and the strength of pre-cue firing decreased as the electrode traversed NAc. We conclude that reward-excited cells (more common in core) promote proactive action selection, while reward-inhibited cells (more common in shell) contribute to accurate responding on STOP trials that require reactive suppression and redirection of behavior.Significant Statement The ability to appropriately adapt behavior is an important part of human cognition, and one that is disrupted by many neuropsychiatric disorders. Here we recorded from neurons in the nucleus accumbens (NAc) as rats performed a cognitive control task and found cell type- and subregion-specific firing patterns. Core and reward-excited cells track trial outcome history, proactively driving behavior to the first cue-a strategy that is appropriate for most trials. Conversely, shell and reward-inhibited neurons signal accurate response direction on trials requiring redirection of behavior. Together, these data suggest that NAc neuronal populations differentially contribute to action selection.

Reward prediction error neurons implement an efficient code for reward.

We use efficient coding principles borrowed from sensory neuroscience to derive the optimal neural population to encode a reward distribution. We show that the responses of dopaminergic reward prediction error neurons in mouse and macaque are similar to those of the efficient code in the following ways: the neurons have a broad distribution of midpoints covering the reward distribution; neurons with higher thresholds have higher gains, more convex tuning functions and lower slopes; and their slope is higher when the reward distribution is narrower. Furthermore, we derive learning rules that converge to the efficient code. The learning rule for the position of the neuron on the reward axis closely resembles distributional reinforcement learning. Thus, reward prediction error neuron responses may be optimized to broadcast an efficient reward signal, forming a connection between efficient coding and reinforcement learning, two of the most successful theories in computational neuroscience.

Adult expression of the cell adhesion protein Fasciclin 3 is required for the maintenance of adult olfactory interneurons.

The proper functioning of the nervous system is dependent on the establishment and maintenance of intricate networks of neurons that form functional neural circuits. Once neural circuits are assembled during development, a distinct set of molecular programs is likely required to maintain their connectivity throughout the lifetime of the organism. Here, we demonstrate that Fasciclin 3 (Fas3), an axon guidance cell adhesion protein, is necessary for the maintenance of the olfactory circuit in adult Drosophila. We utilized the TARGET system to spatiotemporally knockdown Fas3 in selected populations of adult neurons. Our findings show that Fas3 knockdown results in the death of olfactory circuit neurons and reduced survival of adults. We also demonstrated that Fas3 knockdown activates caspase-3-mediated cell death in olfactory local interneurons, which can be rescued by overexpressing baculovirus p35, an anti-apoptotic protein. This work adds to the growing set of evidence indicating a crucial role for axon guidance proteins in the maintenance of neuronal circuits in adults.

Molecular and functional mapping of the neuroendocrine hypothalamus: a new era begins.

Recent advances in neuroscience tools for single-cell molecular profiling of brain neurons have revealed an enormous spectrum of neuronal subpopulations within the neuroendocrine hypothalamus, highlighting the remarkable molecular and cellular heterogeneity of this brain area. Neuronal diversity in the hypothalamus reflects the high functional plasticity of this brain area, where multiple neuronal populations flexibly integrate a variety of physiological outputs, including energy balance, stress and fertility, through crosstalk mechanisms with peripheral hormones. Intrinsic functional heterogeneity is also observed within classically 'defined' subpopulations of neuroendocrine neurons, including subtypes with distinct neurochemical signatures, spatial organisation and responsiveness to hormonal cues. The aim of this review is to critically evaluate past and current research on the functional diversity of hypothalamic neuroendocrine neurons and their plasticity. It focuses on how this neuronal plasticity in this brain area relates to metabolic control, feeding regulation and interactions with stress and fertility-related neural circuits. Our analysis provides an original framework for improving our understanding of the hypothalamic regulation of hormone function and the development of neuroendocrine diseases.

EVIDENCE FOR AUDITORY STIMULUS-SPECIFIC ADAPTATION BUT NOT DEVIANCE DETECTION IN LARVAL ZEBRAFISH BRAINS.

Animals receive a constant stream of sensory input, and detecting changes in this sensory landscape is critical to their survival. One signature of change detection in humans is the auditory mismatch negativity (MMN), a neural response to unexpected stimuli that deviate from a predictable sequence. This process requires the auditory system to adapt to specific repeated stimuli while remaining sensitive to novel input (stimulus-specific adaptation). MMN was originally described in humans, and equivalent responses have been found in other mammals and birds, but it is not known to what extent this deviance detection circuitry is evolutionarily conserved. Here we present the first evidence for stimulus-specific adaptation in the brain of a teleost fish, using whole-brain calcium imaging of larval zebrafish at single-neuron resolution with selective plane illumination microscopy. We found frequency-specific responses across the brain with variable response amplitudes for frequencies of the same volume, and created a loudness curve to model this effect. We presented an auditory 'oddball' stimulus in an otherwise predictable train of pure tone stimuli, and did not find a population of neurons with specific responses to deviant tones that were not otherwise explained by stimulus-specific adaptation. Further, we observed no deviance responses to an unexpected omission of a sound in a repetitive sequence of white noise bursts. These findings extend the known scope of auditory adaptation and deviance responses across the evolutionary tree, and lay groundwork for future studies to describe the circuitry underlying auditory adaptation at the level of individual neurons.

Evoked resonant neural activity long-term dynamics can be reproduced by a computational model with vesicle depletion

Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinson's disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. Our results demonstrate that it is possible to reproduce the slow dynamics of ERNA (over hundreds of seconds) with a single neuronal population, and, crucially, with vesicle depletion as one of the key mechanisms behind the ERNA frequency decay in our model. We further validate the proposed model against experimental data from Parkinson's disease patients, where it captures the variations in ERNA frequency and amplitude in response to variable stimulation frequency, amplitude, and to stimulation pulse bursting. We provide a series of predictions from the model that could be the subject of future studies for further validation.

Identification of hypothermia-inducing neurons in the preoptic area and activation of them by isoflurane anesthesia and central injection of adenosine

Hibernation and torpor are not passive responses caused by external temperature drops and fasting but are active brain functions that lower body temperature. A population of neurons in the preoptic area was recently identified as such active torpor-regulating neurons. We hypothesized that the other hypothermia-inducing maneuvers would also activate these neurons. To test our hypothesis, we first refined the previous observations, examined the brain regions explicitly activated during the falling phase of body temperature using c-Fos expression, and confirmed the preoptic area. Next, we observed long-lasting hypothermia by reactivating torpor-tagged Gq-expressing neurons using the activity tagging and DREADD systems. Finally, we found that about 40–60% of torpor-tagged neurons were activated by succeeding isoflurane anesthesia and by icv administration of an adenosine A1 agonist. Isoflurane-induced and central adenosine-induced hypothermia is, at least in part, an active process mediated by the torpor-regulating neurons in the preoptic area.Graphical abstract

Incremental induction of NMDAR-STP and NMDAR-LTP in the CA1 area of ventral hippocampal slices relies on graded activation of discrete NMDA receptors.

N-methyl-d-aspartate receptor (NMDAR)-dependent short- and long-term types of potentiation (STP and LTP, respectively) are frequently studied in the CA1 area of dorsal hippocampal slices (DHS). Far less is known about the NMDAR dependence of STP and LTP in ventral hippocampal slices (VHS), where both types of potentiation are smaller in magnitude than in the DHS. Here, we first briefly review our knowledge about the NMDAR dependence of STP and LTP and some other forms of synaptic plasticity. We then show in new experiments that the decay of NMDAR-STP in VHS, similar to dorsal hippocampal NMDAR-STP, is not time- but activity-dependent. We also demonstrate that the induction of submaximal levels of NMDAR-STP and NMDAR-LTP in VHS differs from the induction of saturated levels of plasticity in terms of their sensitivity to subunit-preferring NMDAR antagonists. These data suggest that activation of distinct NMDAR subtypes in a population of neurons results in an incremental increase in the induction of different phases of potentiation with changing sensitivity to pharmacological agents. Differences in pharmacological sensitivity, which arise due to differences in the levels of agonist-evoked biological response, might explain the disparity of the results concerning NMDAR subunit involvement in the induction of NMDAR-dependent plasticity.This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.