sensory cortex
Latest
sensorimotor control, mouvement, touch, EEG
Traditionally, touch is associated with exteroception and is rarely considered a relevant sensory cue for controlling movements in space, unlike vision. We developed a technique to isolate and measure tactile involvement in controlling sliding finger movements over a surface. Young adults traced a 2D shape with their index finger under direct or mirror-reversed visual feedback to create a conflict between visual and somatosensory inputs. In this context, increased reliance on somatosensory input compromises movement accuracy. Based on the hypothesis that tactile cues contribute to guiding hand movements when in contact with a surface, we predicted poorer performance when the participants traced with their bare finger compared to when their tactile sensation was dampened by a smooth, rigid finger splint. The results supported this prediction. EEG source analyses revealed smaller current in the source-localized somatosensory cortex during sensory conflict when the finger directly touched the surface. This finding supports the hypothesis that, in response to mirror-reversed visual feedback, the central nervous system selectively gated task-irrelevant somatosensory inputs, thereby mitigating, though not entirely resolving, the visuo-somatosensory conflict. Together, our results emphasize touch’s involvement in movement control over a surface, challenging the notion that vision predominantly governs goal-directed hand or finger movements.
Chandelier cells shine a light on the emergence of GABAergic circuits in the cortex
GABAergic interneurons are chiefly responsible for controlling the activity of local circuits in the cortex. Chandelier cells (ChCs) are a type of GABAergic interneuron that control the output of hundreds of neighbouring pyramidal cells through axo-axonic synapses which target the axon initial segment (AIS). Despite their importance in modulating circuit activity, our knowledge of the development and function of axo-axonic synapses remains elusive. We have investigated the emergence and plasticity of axo-axonic synapses in layer 2/3 of the somatosensory cortex (S1) and found that ChCs follow what appear to be homeostatic rules when forming synapses with pyramidal neurons. We are currently implementing in vivo techniques to image the process of axo-axonic synapse formation during development and uncover the dynamics of synaptogenesis and pruning at the AIS. In addition, we are using an all-optical approach to both activate and measure the activity of chandelier cells and their postsynaptic partners in the primary visual cortex (V1) and somatosensory cortex (S1) in mice, also during development. We aim to provide a structural and functional description of the emergence and plasticity of a GABAergic synapse type in the cortex.
How neural circuits organize and learn during development
To generate brain circuits that are both flexible and stable requires the coordination of powerful developmental mechanisms acting at different scales, including activity-dependent synaptic plasticity and changes in single neuron properties. The brain prepares to efficiently compute information and reliably generate behavior during early development without any prior sensory experience but through patterned spontaneous activity. After the onset of sensory experience, ongoing activity continues to modify sensory circuits, and plays an important functional role in the mature brain. Using quantitative data analysis, experiment-driven theory and computational modeling, I will present a framework for how neural circuits are built and organized during early postnatal development into functional units, and how they are modified by intact and perturbed sensory-evoked activity. Inspired by experimental data from sensory cortex, I will then show how neural circuits use the resulting non-random connectivity to flexibly gate a network’s response, providing a mechanism for routing information.
Input and target-selective plasticity in sensory neocortex during learning
Behavioral experience shapes neural circuits, adding and subtracting connections between neurons that will ultimately control sensation and perception. We are using natural sensory experience to uncover basic principles of information processing in the cerebral cortex, with a focus on how sensory learning can selectively alter synaptic strength. I will discuss recent findings that differentiate reinforcement learning from sensory experience, showing rapid and selective plasticity of thalamic and inhibitory synapses within primary sensory cortex.
How does seeing help listening? Audiovisual integration in Auditory Cortex
Multisensory responses are ubiquitous in so-called unisensory cortex. However, despite their prevalence, we have very little understanding of what – if anything - they contribute to perception. In this talk I will focus on audio-visual integration in auditory cortex. Anatomical tracing studies highlight visual cortex as one source of visual input to auditory cortex. Using cortical cooling we test the hypothesis that these inputs support audiovisual integration in ferret auditory cortex. Behavioural studies in humans support the idea that visual stimuli can help listeners to parse an auditory scene. This effect is paralleled in single units in auditory cortex, where responses to a sound mixture can be determined by the timing of a visual stimulus such that sounds that are temporally coherent with a visual stimulus are preferentially represented. Our recent data therefore support the idea that one role for the early integration of auditory and visual signals in auditory cortex is to support auditory scene analysis, and that visual cortex plays a key role in this process.
Spontaneous activity competes with externally evoked responses in sensory cortex
The interaction between spontaneously and externally evoked neuronal activity is fundamental for a functional brain. Increasing evidence suggests that bursts of high-power oscillations in the 15-30 Hz beta-band represent activation of resting state networks and can mask perception of external cues. Yet demonstration of the effect of beta power modulation on perception in real-time is missing, and little is known about the underlying mechanism. In this talk I will present the methods we developed to fill this gap together with our recent results. We used a closed-loop stimulus-intensity adjustment system based on online burst-occupancy analyses in rats involved in a forepaw vibrotactile detection task. We found that the masking influence of burst-occupancy on perception can be counterbalanced in real-time by adjusting the vibration amplitude. Offline analysis of firing-rates and local field potentials across cortical layers and frequency bands confirmed that beta-power in the somatosensory cortex anticorrelated with sensory evoked responses. Mechanistically, bursts in all bands were accompanied by transient synchronization of cell assemblies, but only beta-bursts were followed by a reduction of firing-rate. Our closed loop approach reveals that spontaneous beta-bursts reflect a dynamic state that competes with external stimuli.
Imaging neuronal morphology and activity pattern in developing cerebral cortex layer 4
Establishment of precise neuronal connectivity in the neocortex relies on activity-dependent circuit reorganization during postnatal development. In the mouse somatosensory cortex layer 4, barrels are arranged in one-to-one correspondence to whiskers on the face. Thalamocortical axon termini are clustered in the center of each barrel. The layer 4 spiny stellate neurons are located around the barrel edge, extend their dendrites primarily toward the barrel center, and make synapses with thalamocortical axons corresponding to a single whisker. These organized circuits are established during the first postnatal week through activity-dependent refinement processes. However, activity pattern regulating the circuit formation is still elusive. Using two-photon calcium imaging in living neonatal mice, we found that layer 4 neurons within the same barrel fire synchronously in the absence of peripheral stimulation, creating a ''patchwork'' pattern of spontaneous activity corresponding to the barrel map. We also found that disruption of GluN1, an obligatory subunit of the N-methyl-D-aspartate (NMDA) receptor, in a sparse population of layer 4 neurons reduced activity correlation between GluN1 knockout neuron pairs within a barrel. Our results provide evidence for the involvement of layer 4 neuron NMDA receptors in spatial organization of the spontaneous firing activity of layer 4 neurons in the neonatal barrel cortex. In the talk I will introduce our strategy to analyze the role of NMDA receptor-dependent correlated activity in the layer 4 circuit formation.
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A recent formulation of predictive coding theory proposes that a subset of neurons in each cortical area encodes sensory prediction errors, the difference between predictions relayed from higher cortex and the sensory input. Here, we test for evidence of prediction error responses in spiking responses and local field potentials (LFP) recorded in primary visual cortex and area V4 of macaque monkeys, and in complementary electroencephalographic (EEG) scalp recordings in human participants. We presented a fixed sequence of visual stimuli on most trials, and violated the expected ordering on a small subset of trials. Under predictive coding theory, pattern-violating stimuli should trigger robust prediction errors, but we found that spiking, LFP and EEG responses to expected and pattern-violating stimuli were nearly identical. Our results challenge the assertion that a fundamental computational motif in sensory cortex is to signal prediction errors, at least those based on predictions derived from temporal patterns of visual stimulation.
Distinctive computational features of a sensory cortex and their role in perception
Interpreting the Mechanisms and Meaning of Sensorimotor Beta Rhythms with the Human Neocortical Neurosolver (HNN) Neural Modeling Software
Electro- and magneto-encephalography (EEG/MEG) are the leading methods to non-invasively record human neural dynamics with millisecond temporal resolution. However, it can be extremely difficult to infer the underlying cellular and circuit level origins of these macro-scale signals without simultaneous invasive recordings. This limits the translation of E/MEG into novel principles of information processing, or into new treatment modalities for neural pathologies. To address this need, we developed the Human Neocortical Neurosolver (HNN: https://hnn.brown/edu ), a new user-friendly neural modeling tool designed to help researchers and clinicians interpret human imaging data. A unique feature of HNN’s model is that it accounts for the biophysics generating the primary electric currents underlying such data, so simulation results are directly comparable to source localized data. HNN is being constructed with workflows of use to study some of the most commonly measured E/MEG signals including event related potentials, and low frequency brain rhythms. In this talk, I will give an overview of this new tool and describe an application to study the origin and meaning of 15-29Hz beta frequency oscillations, known to be important for sensory and motor function. Our data showed that in primary somatosensory cortex these oscillations emerge as transient high power ‘events’. Functionally relevant differences in averaged power reflected a difference in the number of high-power beta events per trial (“rate”), as opposed to changes in event amplitude or duration. These findings were consistent across detection and attention tasks in human MEG, and in local field potentials from mice performing a detection task. HNN modeling led to a new theory on the circuit origin of such beta events and suggested beta causally impacts perception through layer specific recruitment of cortical inhibition, with support from invasive recordings in animal models and high-resolution MEG in humans. In total, HNN provides an unpresented biophysically principled tool to link mechanism to meaning of human E/MEG signals.
An in-silico framework to study the cholinergic modulation of the neocortex
Neuromodulators control information processing in cortical microcircuits by regulating the cellular and synaptic physiology of neurons. Computational models and detailed simulations of neocortical microcircuitry offer a unifying framework to analyze the role of neuromodulators on network activity. In the present study, to get a deeper insight in the organization of the cortical neuropil for modeling purposes, we quantify the fiber length per cortical volume and the density of varicosities for catecholaminergic, serotonergic and cholinergic systems using immunocytochemical staining and stereological techniques. The data obtained are integrated into a biologically detailed digital reconstruction of the rodent neocortex (Markram et al, 2015) in order to model the influence of modulatory systems on the activity of the somatosensory cortex neocortical column. Simulations of ascending modulation of network activity in our model predict the effects of increasing levels of neuromodulators on diverse neuron types and synapses and reveal a spectrum of activity states. Low levels of neuromodulation drive microcircuit activity into slow oscillations and network synchrony, whereas high neuromodulator concentrations govern fast oscillations and network asynchrony. The models and simulations thus provide a unifying in silico framework to study the role of neuromodulators in reconfiguring network activity.
Meta-analytic evidence of differential prefrontal and early sensory cortex activity during non-social sensory perception in autism
To date, neuroimaging research has had a limited focus on non-social features of autism. As a result, neurobiological explanations for atypical sensory perception in autism are lacking. To address this, we quantitively condensed findings from the non-social autism fMRI literature in line with the current best practices for neuroimaging meta-analyses. Using activation likelihood estimation (ALE), we conducted a series of robust meta-analyses across 83 experiments from 52 fMRI studies investigating differences between autistic (n = 891) and typical (n = 967) participants. We found that typical controls, compared to autistic people, show greater activity in the prefrontal cortex (BA9, BA10) during perception tasks. More refined analyses revealed that, when compared to typical controls, autistic people show greater recruitment of the extrastriate V2 cortex (BA18) during visual processing. Taken together, these findings contribute to our understanding of current theories of autistic perception, and highlight some of the challenges of cognitive neuroscience research in autism.
Circuit mechanisms for synaptic plasticity in the rodent somatosensory cortex
Sensory experience and perceptual learning changes receptive field properties of cortical pyramidal neurons possibly mediated by long-term potentiation (LTP) of synapses. We have previously shown in the mouse somatosensory cortex (S1) that sensory-driven LTP in layer (L) 2/3 pyramidal neurons is dependent on higher order thalamic feedback from the posteromedial nucleus (POm), which is thought to convey contextual information from various cortical regions integrated with sensory input. We have followed up on this work by dissecting the cortical microcircuitry that underlies this form of LTP. We found that repeated pairing of Pom thalamocortical and intracortical pathway activity in brain slices induces NMDAr-dependent LTP of the L2/3 synapses that are driven by the intracortical pathway. Repeated pairing also recruits activity of vasoactive intestinal peptide (VIP) interneurons, whereas it reduces the activity of somatostatin (SST) interneurons. VIP interneuron-mediated inhibition of SST interneurons has been established as a motif for the disinhibition of pyramidal neurons. By chemogenetic interrogation we found that activation of this disinhibitory microcircuit motif by higher-order thalamic feedback is indispensable for eliciting LTP. Preliminary results in vivo suggest that VIP neuron activity also increases during sensory-evoked LTP. Together, this suggests that the higherorder thalamocortical feedback may help modifying the strength of synaptic circuits that process first-order sensory information in S1. To start characterizing the relationship between higher-order feedback and cortical plasticity during learning in vivo, we adapted a perceptual learning paradigm in which head-fixed mice have to discriminate two types of textures in order to obtain a reward. POm axons or L2/3 pyramidal neurons labeled with the genetically encoded calcium indicator GCaMP6s were imaged during the acquisition of this task as well as the subsequent learning of a new discrimination rule. We found that a subpopulation of the POm axons and L2/3 neurons dynamically represent textures. Moreover, upon a change in reward contingencies, a fraction of the L2/3 neurons re-tune their selectivity to the texture that is newly associated with the reward. Altogether, our data indicates that higher-order thalamic feedback can facilitate synaptic plasticity and may be implicated in dynamic sensory stimulus representations in S1, which depends on higher-order features that are associated with the stimuli.
Sensory-motor control, cognition and brain evolution: exploring the links
Drawing on recent findings from evolutionary anthropology and neuroscience, professor Barton will lead us through the amazing story of the evolution of human cognition. Usingstatistical, phylogenetic analyses that tease apart the variation associated with different neural systems and due to different selection pressures, he will be addressing intriguing questions like ‘Why are there so many neurons in the cerebellum?’, ‘Is the neocortex the ‘intelligent’ bit of the brain?’, and ‘What explains that the recognition by humans of emotional expressions is disrupted by trancranial magnetic stimulation of the somatosensory cortex?’ Could, as professor Barton suggests, the cerebellum -modestly concealed beneath the volumetrically dominating neocortex and largely ignored- turn out to be the Cinderella of the study of brain evolution?
How the immune system shapes synaptic functions
The synapse is the core component of the nervous system and synapse formation is the critical step in the assembly of neuronal circuits. The assembly and maturation of synapses requires the contribution of secreted and membrane-associated proteins, with neuronal activity playing crucial roles in regulating synaptic strength, neuronal membrane properties, and neural circuit refinement. The molecular mechanisms of synapse assembly and refinement have been so far largely examined on a gene-by-gene basis and with a perspective fully centered on neuronal cells. However, in the last years, the involvement of non-neuronal cells has emerged. Among these, microglia, the resident immune cells of the central nervous system, have been shown to play a key role in synapse formation and elimination. Contacts of microglia with dendrites in the somatosensory cortex were found to induce filopodia and dendritic spines via Ca2+ and actin-dependent processes, while microglia-derived BDNF was shown to promote learning-dependent synapse formation. Microglia is also recognized to have a central role in the widespread elimination (or pruning) of exuberant synaptic connections during development. Clarifying the processes by which microglia control synapse homeostasis is essential to advance our current understanding of brain functions. Clear answers to these questions will have important implications for our understanding of brain diseases, as the fact that many psychiatric and neurological disorders are synaptopathies (i.e. diseases of the synapse) is now widely recognized. In the last years, my group has identified TREM2, an innate immune receptor with phagocytic and antiinflammatory properties expressed in brain exclusively by microglia, as essential for microglia-mediated synaptic refinement during the early stages of brain development. The talk will describe the role of TREM2 in synapse elimination and introduce the molecular actors involved. I will also describe additional pathways by which the immune system may affect the formation and homeostasis of synaptic contacts.
A Cortical Circuit for Audio-Visual Predictions
Team work makes sensory streams work: our senses work together, learn from each other, and stand in for one another, the result of which is perception and understanding. Learned associations between stimuli in different sensory modalities can shape the way we perceive these stimuli (Mcgurk and Macdonald, 1976). During audio-visual associative learning, auditory cortex is thought to underlie multi-modal plasticity in visual cortex (McIntosh et al., 1998; Mishra et al., 2007; Zangenehpour and Zatorre, 2010). However, it is not well understood how processing in visual cortex is altered by an auditory stimulus that is predictive of a visual stimulus and what the mechanisms are that mediate such experience-dependent, audio-visual associations in sensory cortex. Here we describe a neural mechanism by which an auditory input can shape visual representations of behaviorally relevant stimuli through direct interactions between auditory and visual cortices. We show that the association of an auditory stimulus with a visual stimulus in a behaviorally relevant context leads to an experience-dependent suppression of visual responses in primary visual cortex (V1). Auditory cortex axons carry a mixture of auditory and retinotopically-matched visual input to V1, and optogenetic stimulation of these axons selectively suppresses V1 neurons responsive to the associated visual stimulus after, but not before, learning. Our results suggest that cross-modal associations can be stored in long-range cortical connections and that with learning these cross-modal connections function to suppress the responses to predictable input.
Mechanisms of cortical communication during decision-making
Regulation of information flow in the brain is critical for many forms of behavior. In the process of sensory based decision-making, decisions about future actions are held in memory until enacted, making them potentially vulnerable to distracting sensory input. Therefore, gating of information flow from sensory to motor areas could protect memory from interference during decision-making, but the underlying network mechanisms are not understood. I will present our recent experimental and modeling work describing how information flow from the sensory cortex can be gated by state-dependent frontal cortex dynamics during decision-making in mice. Our results show that communication between brain regions can be regulated via attractor dynamics, which control the degree of commitment to an action, and reveal a novel mechanism of gating of neural information.
Sensory and metasensory responses during sequence learning in the mouse somatosensory cortex
Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. Touch is one sensory modality where temporal patterning carries key information, and the rodent whisker system is a prominent model for understanding neuronal coding and plasticity underlying touch sensation. Neurons in this system are precise encoders of fluctuations in whisker dynamics down to a timescale of milliseconds, but it is not clear whether they can refine their encoding abilities as a result of learning patterned stimuli. For example, can they enhance temporal integration to become better at distinguishing sequences? To explore how cortical coding plasticity underpins sequence discrimination, we developed a task in which mice distinguished between tactile ‘word’ sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory “barrel” cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal’s action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal’s learnt action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were already found in naïve mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf sequence learning results in neurons whose activity reflects the learnt association between target sequence and licking, rather than a refined representation of sensory features. Taken together with results from other laboratories, our findings suggest that neurons in sensory cortex are involved in task-specific processing and that an animal does not sense the world independently of what it needs to feel in order to guide behaviour.
Slow global population dynamics propagating through the medial entorhinal cortex
The medial entorhinal cortex (MEC) supports the brain’s representation of space with distinct cell types whose firing is tuned to features of the environment (grid, border, and object-vector cells) or navigation (head-direction and speed cells). While the firing properties of these functionally-distinct cell types are well characterized, how they interact with one another remains unknown. To determine how activity self-organizes in the MEC network, we tested mice in a spontaneous locomotion task under sensory-deprived conditions. Using 2-photon calcium imaging, we monitored the activity of large populations of MEC neurons in head-fixed mice running on a wheel in darkness, in the absence of external sensory feedback tuned to navigation. We unveiled the presence of motifs that involve the sequential activation of cells in layer II of MEC (MEC-L2). We call these motifs waves. Waves lasted tens of seconds to minutes, were robust, swept through the entire network of active cells and did not exhibit any anatomical organization. Furthermore, waves did not map the position of the mouse on the wheel and were not restricted to running epochs. The majority of MEC-L2 neurons participate in this global sequential dynamics, that ties all functional cell types together. We found the waves in the most lateral region of MEC, but not in adjacent areas such as PaS or in a sensory cortex such as V1.
Global AND Scale-Free? Spontaneous cortical dynamics between functional networks and cortico-hippocampal communication
Recent advancements in anatomical and functional imaging emphasize the presence of whole-brain networks organized according to functional and connectivity gradients, but how such structure shapes activity propagation and memory processes still lacks asatisfactory model. We analyse the fine-grained spatiotemporal dynamics of spontaneous activity in the entire dorsal cortex. through simultaneous recordings of wide-field voltage sensitive dye transients (VS), cortical ECoG, and hippocampal LFP in anesthetized mice. Both VS and ECoG show cortical avalanches. When measuring avalanches from the VS signal, we find a major deviation of the size scaling from the power-law distribution predicted by the criticality hypothesis and well approximated by the results from the ECoG. Breaking from scale-invariance, avalanches can thus be grouped in two regimes. Small avalanches consists of a limited number of co-activation modes involving a sub-set of cortical networks (related to the Default Mode Network), while larger avalanches involve a substantial portion of the cortical surface and can be clustered into two families: one immediately preceded by Retrosplenial Cortex activation and mostly involving medial-posterior networks, the other initiated by Somatosensory Cortex and extending preferentially along the lateral-anterior region. Rather than only differing in terms of size, these two set of events appear to be associated with markedly different brain-wide dynamical states: they are accompaniedby a shift in the hippocampal LFP, from the ripple band (smaller) to the gamma band (larger avalanches), and correspond to opposite directionality in the cortex-to-hippocampus causal relationship. These results provide a concrete description of global cortical dynamics, and shows how cortex in its entirety is involved in bi-directional communication in the hippocampus even in sleep-like states.
Distinct synaptic plasticity mechanisms determine the diversity of cortical responses during behavior
Spike trains recorded from the cortex of behaving animals can be complex, highly variable from trial to trial, and therefore challenging to interpret. A fraction of cells exhibit trial-averaged responses with obvious task-related features such as pure tone frequency tuning in auditory cortex. However, a substantial number of cells (including cells in primary sensory cortex) do not appear to fire in a task-related manner and are often neglected from analysis. We recently used a novel single-trial, spike-timing-based analysis to show that both classically responsive and non-classically responsive cortical neurons contain significant information about sensory stimuli and behavioral decisions suggesting that non-classically responsive cells may play an underappreciated role in perception and behavior. We now expand this investigation to explore the synaptic origins and potential contribution of these cells to network function. To do so, we trained a novel spiking recurrent neural network model that incorporates spike-timing-dependent plasticity (STDP) mechanisms to perform the same task as behaving animals. By leveraging excitatory and inhibitory plasticity rules this model reproduces neurons with response profiles that are consistent with previously published experimental data, including classically responsive and non-classically responsive neurons. We found that both classically responsive and non-classically responsive neurons encode behavioral variables in their spike times as seen in vivo. Interestingly, plasticity in excitatory-to-excitatory synapses increased the proportion of non-classically responsive neurons and may play a significant role in determining response profiles. Finally, our model also makes predictions about the synaptic origins of classically and non-classically responsive neurons which we can compare to in vivo whole-cell recordings taken from the auditory cortex of behaving animals. This approach successfully recapitulates heterogeneous response profiles measured from behaving animals and provides a powerful lens for exploring large-scale neuronal dynamics and the plasticity rules that shape them.
Neural circuit redundancy, stability, and variability in developmental brain disorders
Despite the consistency of symptoms at the cognitive level, we now know that brain disorders like Autism and Schizophrenia can each arise from mutations in >100 different genes. Presumably there is a convergence of “symptoms” at the level of neural circuits in diagnosed individuals. In this talk I will argue that redundancy in neural circuit parameters implies that we should take a circuit-function rather that circuit-component approach to understanding these disorders. Then I will present our recent empirical work testing a circuit-function theory for Autism: the idea that neural circuits show excess trial-to-trial variability in response to sensory stimuli, and instability in the representations across a timescale of days. For this we analysed in vivo neural population activity data recorded from somatosensory cortex of mouse models of Fragile-X syndrome, a disorder related to autism. Work with Beatriz Mizusaki (Univ of Bristol), Nazim Kourdougli, Anand Suresh, and Carlos Portera-Cailliau (Univ of California, Los Angeles).
High precision coding in visual cortex
Single neurons in visual cortex provide unreliable measurements of visual features due to their high trial-to-trial variability. It is not known if this “noise” extends its effects over large neural populations to impair the global encoding of stimuli. We recorded simultaneously from ∼20,000 neurons in mouse primary visual cortex (V1) and found that the neural populations had discrimination thresholds of ∼0.34° in an orientation decoding task. These thresholds were nearly 100 times smaller than those reported behaviourally in mice. The discrepancy between neural and behavioural discrimination could not be explained by the types of stimuli we used, by behavioural states or by the sequential nature of perceptual learning tasks. Furthermore, higher-order visual areas lateral to V1 could be decoded equally well. These results imply that the limits of sensory perception in mice are not set by neural noise in sensory cortex, but by the limitations of downstream decoders.
The operating regime of primate sensory cortex
COSYNE 2022
The operating regime of primate sensory cortex
COSYNE 2022
Beyond perception: the sensory cortex as an associative engine during goal-directed learning
COSYNE 2023
Population activity in sensory cortex informs confidence in a perceptual decision
COSYNE 2023
Integration of corollary discharge and sensory feedback signals in somatosensory cortex
COSYNE 2025
Rapid emergence of latent knowledge in the sensory cortex drives learning
COSYNE 2025
Representational drift in primary vibrissal somatosensory cortex is receptive field dependent
COSYNE 2025
Activation of L2/3 neurons in the primary somatosensory cortex during motor output
FENS Forum 2024
Adenosine and astrocytes determine the developmental dynamics of spike timing-dependent plasticity in the somatosensory cortex
FENS Forum 2024
All-optical mapping of feedback and sensory-evoked synaptic inputs to pyramidal neurons in the mouse primary somatosensory cortex
FENS Forum 2024
Astrocyte activity triggers adaptive myelin plasticity and increased neuronal excitability in the somatosensory cortex following sensory deprivation
FENS Forum 2024
Astrocytic calcium response to locomotion in mouse somatosensory cortex: Heterogeneity, reproducibility, and subcellular integration
FENS Forum 2024
Barrel-septa response identity in the somatosensory cortex of mice is regulated by progressive engagement of SST+ interneurons via ELFN1
FENS Forum 2024
Coding of whisker touch and movement in dysgranular somatosensory cortex
FENS Forum 2024
Elucidating the impact of demyelination and remyelination on inhibitory synaptic transmission in the somatosensory cortex of a mouse model of cuprizone
FENS Forum 2024
Excitatory-inhibitory balance assessed by aperiodic component and its correlation with paired-pulse inhibition in the primary somatosensory cortex: An MEG study
FENS Forum 2024
Functional heterogeneity of astrocytes in the somatosensory cortex and its role in the processing of different sensory modalities
FENS Forum 2024
Functional and morphological alterations of parvalbumin-positive interneurons in the somatosensory cortex of mice in the early phase after traumatic brain injury
FENS Forum 2024
Multimodal signal complexity in somatosensory cortex revealed through high-dimensional representations
FENS Forum 2024
Network plasticity and GABAergic cellular dynamics in the different layers of the somatosensory cortex after a spinal cord injury
FENS Forum 2024
Neuronal encoding of forelimb proprioception in the mouse somatosensory cortex and cerebellum
FENS Forum 2024
TRPV1 enhances encoding of sensory information in mouse primary somatosensory cortex
FENS Forum 2024
Information flows from primary motor to primary somatosensory cortex in humans during motor preparation
Neuromatch 5
sensory cortex coverage
46 items