Project description:The brain processes sensory information in a context- and learning-dependent manner for adaptive behavior. Through reward-based learning, relevant sensory stimuli can become linked to execution of specific actions associated with positive outcomes. The neuronal circuits involved in such goal-directed sensory-to-motor transformations remain to be precisely determined. Studying simple learned sensorimotor transformations in head-restrained mice offers the opportunity for detailed measurements of cellular activity during task performance. Here, we trained mice to lick a reward spout in response to a whisker deflection and an auditory tone. Through two-photon calcium imaging of retrogradely labeled neurons, we found that neurons located in primary whisker somatosensory barrel cortex projecting to secondary whisker somatosensory cortex had larger calcium signals than neighboring neurons projecting to primary whisker motor cortex in response to whisker deflection and auditory stimulation, as well as before spontaneous licking. Longitudinal imaging of the same neurons revealed that these projection-specific responses were relatively stable across 3 days. In addition, the activity of neurons projecting to secondary whisker somatosensory cortex was more highly correlated than for neurons projecting to primary whisker motor cortex. The large and correlated activity of neurons projecting to secondary whisker somatosensory cortex might enhance the pathway-specific signaling of important sensory information contributing to task execution. Our data support the hypothesis that communication between primary and secondary somatosensory cortex might be an early critical step in whisker sensory perception. More generally, our data suggest the importance of investigating projection-specific neuronal activity in distinct populations of intermingled excitatory neocortical neurons during task performance.
Project description:Neocortical lamina 6B (L6B) is a largely unexplored layer with a very heterogeneous cellular composition. To date, only little is known about L6B neurons on a systematic and quantitative basis. We investigated the morphological and electrophysiological properties of excitatory L6B neurons in the rat somatosensory barrel cortex using whole-cell patch-clamp recordings and simultaneous biocytin fillings. Subsequent histological processing and computer-assisted 3D reconstructions provided the basis for a classification of excitatory L6B neurons according to their structural and functional characteristics. Three distinct clusters of excitatory L6B neurons were identified: (C1) pyramidal neurons with an apical dendrite pointing towards the pial surface, (C2) neurons with a prominent, "apical"-like dendrite not oriented towards the pia, and (C3) multipolar spiny neurons without any preferential dendritic orientation. The second group could be further subdivided into three categories termed inverted, "tangentially" oriented and "horizontally" oriented neurons. Furthermore, based on the axonal domain two subcategories of L6B pyramidal cells were identified that had either a more barrel-column confined or an extended axonal field. The classification of excitatory L6B neurons provided here may serve as a basis for future studies on the structure, function, and synaptic connectivity of L6B neurons.
Project description:Since its first experimental signatures, the so called "critical brain hypothesis" has been extensively studied. Yet, its actual foundations remain elusive. According to a widely accepted teleological reasoning, the brain would be poised to a critical state to optimize the mapping of the noisy and ever changing real-world inputs, thus suggesting that primary sensory cortical areas should be critical. We investigated whether a single barrel column of the somatosensory cortex of the anesthetized rat displays a critical behavior. Neuronal avalanches were recorded across all cortical layers in terms of both multi-unit activities and population local field potentials, and their behavior during spontaneous activity compared to the one evoked by a controlled single whisker deflection. By applying a maximum likelihood statistical method based on timeseries undersampling to fit the avalanches distributions, we show that neuronal avalanches are power law distributed for both multi-unit activities and local field potentials during spontaneous activity, with exponents that are spread along a scaling line. Instead, after the tactile stimulus, activity switches to a transient across-layers synchronization mode that appears to dominate the cortical representation of the single sensory input.
Project description:Spike-based neuromorphic hardware has great potential for low-energy brain-machine interfaces, leading to a novel paradigm for neuroprosthetics where spiking neurons in silicon read out and control activity of brain circuits. Neuromorphic processors can receive rich information about brain activity from both spikes and local field potentials (LFPs) recorded by implanted neural probes. However, it was unclear whether spiking neural networks (SNNs) implemented on such devices can effectively process that information. Here, we demonstrate that SNNs can be trained to classify whisker deflections of different amplitudes from evoked responses in a single barrel of the rat somatosensory cortex. We show that the classification performance is comparable or even superior to state-of-the-art machine learning approaches. We find that SNNs are rather insensitive to recorded signal type: both multi-unit spiking activity and LFPs yield similar results, where LFPs from cortical layers III and IV seem better suited than those of deep layers. In addition, no hand-crafted features need to be extracted from the data-multi-unit activity can directly be fed into these networks and a simple event-encoding of LFPs is sufficient for good performance. Furthermore, we find that the performance of SNNs is insensitive to the network state-their performance is similar during UP and DOWN states.
Project description:Mammalian neocortex is important for conscious processing of sensory information with balanced glutamatergic and GABAergic signaling fundamental to this function. Yet little is known about how this interaction arises despite increasing insight into early GABAergic interneuron (IN) circuits. To study this, we assessed the contribution of specific INs to the development of sensory processing in the mouse whisker barrel cortex, specifically the role of INs in early speed coding and sensory adaptation. In wild-type animals, both speed processing and adaptation were present as early as the layer 4 critical period of plasticity and showed refinement over the period leading to active whisking onset. To test the contribution of IN subtypes, we conditionally silenced action-potential-dependent GABA release in either somatostatin (SST) or vasoactive intestinal peptide (VIP) INs. These genetic manipulations influenced both spontaneous and sensory-evoked cortical activity in an age- and layer-dependent manner. Silencing SST + INs reduced early spontaneous activity and abolished facilitation in sensory adaptation observed in control pups. In contrast, VIP + IN silencing had an effect towards the onset of active whisking. Silencing either IN subtype had no effect on speed coding. Our results show that these IN subtypes contribute to early sensory processing over the first few postnatal weeks.
Project description:Understanding the basic neuronal building blocks of the neocortex is a necessary first step toward comprehending the composition of cortical circuits. Neocortical layer VI is the most morphologically diverse layer and plays a pivotal role in gating information to the cortex via its feedback connection to the thalamus and other ipsilateral and callosal corticocortical connections. The heterogeneity of function within this layer is presumably linked to its varied morphological composition. However, so far, very few studies have attempted to define cell classes in this layer using unbiased quantitative methodologies. Utilizing the Golgi staining technique along with the Neurolucida software, we recontructed 222 cortical neurons from layer VI of mouse barrel cortex. Morphological analyses were performed by quantifying somatic and dendritic parameters, and, by using principal component and cluster analyses, we quantitatively categorized neurons into six distinct morphological groups. Additional systematic replication on a separate population of neurons yielded similar results, demonstrating the consistency and reliability of our categorization methodology. Subsequent post hoc analyses of dendritic parameters supported our neuronal classification scheme. Characterizing neuronal elements with unbiased quantitative techniques provides a framework for better understanding structure-function relationships within neocortical circuits in general.
Project description:Sparse population activity is a well-known feature of supragranular sensory neurons in neocortex. The mechanisms underlying sparseness are not well understood because a direct link between the neurons activated in vivo, and their cellular properties investigated in vitro has been missing. We used two-photon calcium imaging to identify a subset of neurons in layer L2/3 (L2/3) of mouse primary somatosensory cortex that are highly active following principal whisker vibrotactile stimulation. These high responders (HRs) were then tagged using photoconvertible green fluorescent protein for subsequent targeting in the brain slice using intracellular patch-clamp recordings and biocytin staining. This approach allowed us to investigate the structural and functional properties of HRs that distinguish them from less active control cells. Compared to less responsive L2/3 neurons, HRs displayed increased levels of stimulus-evoked and spontaneous activity, elevated noise and spontaneous pairwise correlations, and stronger coupling to the population response. Intrinsic excitability was reduced in HRs, while we found no evidence for differences in other electrophysiological and morphological parameters. Thus, the choice of which neurons participate in stimulus encoding may be determined largely by network connectivity rather than by cellular structure and function.
Project description:How the somatosensory cortex (S1) encodes complex patterns of touch, such as those that occur during tactile exploration, is poorly understood. In the mouse whisker S1, temporally dense stimulation of local whisker pairs revealed that most neurons are not classical single-whisker feature detectors, but instead are strongly tuned to two-whisker sequences that involve the columnar whisker (CW) and one specific surround whisker (SW), usually in a SW-leading-CW order. Tuning was spatiotemporally precise and diverse across cells, generating a rate code for local motion vectors defined by SW-CW combinations. Spatially asymmetric, sublinear suppression for suboptimal combinations and near-linearity for preferred combinations sharpened combination tuning relative to linearly predicted tuning. This resembles computation of motion direction selectivity in vision. SW-tuned neurons, misplaced in the classical whisker map, had the strongest combination tuning. Thus, each S1 column contains a rate code for local motion sequences involving the CW, thus providing a basis for higher-order feature extraction.
Project description:In the barrel field of the rodent primary somatosensory cortex (S1bf), excitatory cells in layer 2/3 (L2/3) display sparse firing but reliable subthreshold response during whisker stimulation. Subthreshold responses encode specific features of the sensory stimulus, for example, the direction of whisker deflection. According to the canonical model for the flow of sensory information across cortical layers, activity in L2/3 is driven by layer 4 (L4). However, L2/3 cells receive excitatory inputs from other regions, raising the possibility that L4 partially drives L2/3 during whisker stimulation. To test this hypothesis, we combined patch-clamp recordings from L2/3 pyramidal neurons in S1bf with selective optogenetic inhibition of L4 during passive whisker stimulation in both anesthetized and awake head-restrained mice. We found that L4 optogenetic inhibition did not abolish the subthreshold whisker-evoked response nor it affected spontaneous membrane potential fluctuations of L2/3 neurons. However, L4 optogenetic inhibition decreased L2/3 subthreshold responses to whisker deflections in the preferred direction, and it increased L2/3 responses to stimuli in the nonpreferred direction, leading to a change in the direction tuning. Our results contribute to reveal the circuit mechanisms underlying the processing of sensory information in the rodent S1bf.
Project description:Neocortical neurons can increasingly be divided into well-defined classes, but their activity patterns during quantified behavior remain to be fully determined. Here, we obtained membrane potential recordings from various classes of excitatory and inhibitory neurons located across different cortical depths in the primary whisker somatosensory barrel cortex of awake head-restrained mice during quiet wakefulness, free whisking and active touch. Excitatory neurons, especially those located superficially, were hyperpolarized with low action potential firing rates relative to inhibitory neurons. Parvalbumin-expressing inhibitory neurons on average fired at the highest rates, responding strongly and rapidly to whisker touch. Vasoactive intestinal peptide-expressing inhibitory neurons were excited during whisking, but responded to active touch only after a delay. Somatostatin-expressing inhibitory neurons had the smallest membrane potential fluctuations and exhibited hyperpolarising responses at whisking onset for superficial, but not deep, neurons. Interestingly, rapid repetitive whisker touch evoked excitatory responses in somatostatin-expressing inhibitory neurons, but not when the intercontact interval was long. Our analyses suggest that distinct genetically-defined classes of neurons at different subpial depths have differential activity patterns depending upon behavioral state providing a basis for constraining future computational models of neocortical function.