2378319
Fractured tonotopy of functional neural clusters in mouse auditory cortex
The degree of order versus randomness in mammalian cortical circuits has been the subject of much discussion. Previous reports showed that at a large scale there is smooth tonotopy in mouse auditory cortex, while at the single neuron level the representation is the traditional “salt and pepper” configuration attributed to rodent cortex. Here we show that at the micro columnar scale we find a large variety of response profiles, but neurons tend to share similar preference in terms of frequency, bandwidth and latency. However, this smooth representation was fractured and large differences were possible between neighbouring neurons. Despite the tendency of most groups of neurons to operate redundantly, high information gains were achieved between cells that had a high signal correlation. Connectivity between neurons was highly non-random, in agreement with a previous in-vitro report from layer five. Our results suggest the existence of functional clusters, connecting neighbouring mini-columns. This supports the idea of a “salt and pepper” configuration at the level of functional clusters of neurons rather than single units.
14666307
Functional organization and population dynamics in the mouse primary auditory cortex
Cortical processing of auditory stimuli involves large populations of neurons with distinct individual response profiles. However, the functional organization and dynamics of local populations in the auditory cortex have remained largely unknown. Using in vivo two-photon calcium imaging, we examined the response profiles and network dynamics of layer 2/3 neurons in the primary auditory cortex (A1) of mice in response to pure tones. We found that local populations in A1 were highly heterogeneous in the large-scale tonotopic organization. Despite the spatial heterogeneity, the tendency of neurons to respond together (measured as noise correlation) was high on average. This functional organization and high levels of noise correlations are consistent with the existence of partially overlapping cortical subnetworks. Our findings may account for apparent discrepancies between ordered large-scale organization and local heterogeneity.
12121513
Dichotomy of functional organization in the mouse auditory cortex
The sensory areas of the cerebral cortex possess multiple topographic representations of sensory dimensions. The gradient of frequency selectivity (tonotopy) is the dominant organizational feature in the primary auditory cortex, whereas other feature-based organizations are less well established. We probed the topographic organization of the mouse auditory cortex at the single-cell level using in vivo two-photon Ca2+ imaging. Tonotopy was present on a large scale but was fractured on a fine scale. Intensity tuning, which is important in level-invariant representation, was observed in individual cells, but was not topographically organized. The presence or near absence of putative subthreshold responses revealed a dichotomy in topographic organization. Inclusion of subthreshold responses revealed a topographic clustering of neurons with similar response properties, whereas such clustering was absent in supra-threshold responses. This dichotomy indicates that groups of nearby neurons with locally shared inputs can perform independent parallel computations in the auditory cortex.
21023700
Universality in the Evolution of Orientation Columns in the Visual Cortex
Orientation Columns In the brain's visual cortex, certain neurons respond to vertical lines and others to horizontal lines, with a range in between. Such orientation of neurons tends to be organized in columns reflecting similar responses, and the columns are organized in pinwheels representing the range of responses. Kaschube et al. (p. 1113, published online 4 November; see the Perspective by Miller) looked at the organization of orientation columns in diverse placental mammals and discovered a similarity of organizational principles. Analysis of evolutionarily divergent species highlights constraint on brain structure imposed by self-organizing neural networks. The brain’s visual cortex processes information concerning form, pattern, and motion within functional maps that reflect the layout of neuronal circuits. We analyzed functional maps of orientation preference in the ferret, tree shrew, and galago—three species separated since the basal radiation of placental mammals more than 65 million years ago—and found a common organizing principle. A symmetry-based class of models for the self-organization of cortical networks predicts all essential features of the layout of these neuronal circuits, but only if suppressive long-range interactions dominate development. We show mathematically that orientation-selective long-range connectivity can mediate the required interactions. Our results suggest that self-organization has canalized the evolution of the neuronal circuitry underlying orientation preference maps into a single common design.
17631760
Synaptic Connections between Layer 5B Pyramidal Neurons in Mouse Somatosensory Cortex Are Independent of Apical Dendrite Bundling
Rodent somatosensory barrel cortex is organized both physiologically and anatomically in columns with a cross-sectional diameter of 100–400 μm. The underlying anatomical correlate of physiologically defined, much narrower minicolumns (20–60 μm in diameter) remains unclear. The minicolumn has been proposed to be a fundamental functional unit in the cortex, and one anatomical component of a minicolumn is thought to be a cluster of pyramidal cells in layer 5B (L5B) that contribute their apical dendrite to distinct bundles. In transgenic mice with fluorescently labeled L5B pyramidal cells, which project to the pons and thalamus, we investigated whether the pyramidal cells of a cluster also share functional properties. We found that apical dendrite bundles in the transgenic mice were anatomically similar to apical dendrite bundles previously proposed to be part of minicolumns. We made targeted whole-cell recordings in acute brain slices from pairs of fluorescently labeled L5B pyramidal cells that were located either in the same cluster or in adjacent clusters and subsequently reconstructed their dendritic arbors. Pyramids within the same cluster had larger common dendritic domains compared with pyramids in adjacent clusters but did not receive more correlated synaptic inputs. L5B pyramids within and between clusters have similar connection probabilities and unitary EPSP amplitudes. Furthermore, intrinsically bursting and regular spiking pyramidal cells were both present within the same cluster. In conclusion, intrinsic electrical excitability and the properties of synaptic connections between this subtype of L5B pyramidal cells are independent of the cell clusters defined by bundling of their apical dendrites.
4409952
Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex
Neurons in the cerebral cortex are organized into anatomical columns, with ensembles of cells arranged from the surface to the white matter. Within a column, neurons often share functional properties, such as selectivity for stimulus orientation; columns with distinct properties, such as different preferred orientations, tile the cortical surface in orderly patterns. This functional architecture was discovered with the relatively sparse sampling of microelectrode recordings. Optical imaging of membrane voltage or metabolic activity elucidated the overall geometry of functional maps, but is averaged over many cells (resolution >100 µm). Consequently, the purity of functional domains and the precision of the borders between them could not be resolved. Here, we labelled thousands of neurons of the visual cortex with a calcium-sensitive indicator in vivo. We then imaged the activity of neuronal populations at single-cell resolution with two-photon microscopy up to a depth of 400 µm. In rat primary visual cortex, neurons had robust orientation selectivity but there was no discernible local structure; neighbouring neurons often responded to different orientations. In area 18 of cat visual cortex, functional maps were organized at a fine scale. Neurons with opposite preferences for stimulus direction were segregated with extraordinary spatial precision in three dimensions, with columnar borders one to two cells wide. These results indicate that cortical maps can be built with single-cell precision.
18957366
Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity
Excitatory cortical neurons form fine-scale networks of precisely interconnected neurons. Here we tested whether inhibitory cortical neurons in rat visual cortex might also be connected with fine-scale specificity. Using paired intracellular recordings and cross-correlation analyses of photostimulation-evoked synaptic currents, we found that fast-spiking interneurons preferentially connected to neighboring pyramids that provided them with reciprocal excitation. Furthermore, they shared common fine-scale excitatory input with neighboring pyramidal neurons only when the two cells were reciprocally connected, and not when there was no connection or a one-way, inhibitory-to-excitatory connection. Adapting inhibitory neurons shared little or no common input with neighboring pyramids, regardless of their direct connectivity. We conclude that inhibitory connections and also excitatory connections to inhibitory neurons can both be precise on a fine scale. Furthermore, fine-scale specificity depends on the type of inhibitory neuron and on direct connectivity between neighboring pyramidal-inhibitory neuron pairs.
7877826
Localising and classifying neurons from high density MEA recordings
Neuronal microcircuits are formed of a myriad of spatially and functionally specific cell classes. Despite the importance of the spatial component in the characterisation of neural circuits, it has not received the attention it deserves. While multi-electrodes are widely used in the study of microcircuits, the spatial information available from them remains largely unexploited for analysis beyond spike sorting. Here we show how the spatial pattern of the extracellular signal is determined by both the electrophysiology and morphology of neurons. Starting from known current source models for the generation of the extracellular potential, we use the spatial pattern observed across a multi-electrode array to localise and classify neurons into putative morphological classes. We evaluated the localisation and classification models with low fitting errors in simulated data. When applying them to recorded data we found correspondence between localisation statistics and expected recording radius and found evidence to support the separation into putative morphological classes. While existing localisation methods do not hold for the recording distances expected on multi-electrode recordings (under 60μm), classification methods have been limited to the temporal component by either characterising spike shape or firing patterns. We show here how the information available from extracellular recordings can be used to localise and classify neurons based on the spatial pattern seen by multi-electrode arrays. Together they can improve current characterisation and classification of neurons based on complementary criteria such us firing pattern and functional characterisation.
13938365
High-Dimensional Cluster Analysis with the Masked EM Algorithm
Cluster analysis faces two problems in high dimensions: the “curse of dimensionality” that can lead to overfitting and poor generalization performance and the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of spike sorting for next-generation, high-channel-count neural probes. In this problem, only a small subset of features provides information about the cluster membership of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a “masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data and to real-world high-channel-count spike sorting data.
1530808
Responses of neurons in primary auditory cortex (A1) to pure tones in the halothane-anesthetized cat.
The responses of primary auditory cortex (A1) neurons to pure tones in anesthetized animals are usually described as having mostly narrow, unimodal frequency tuning and phasic responses. Thus A1 neurons are believed not to carry much information about pure tones beyond sound onset. In awake cats, however, tuning may be wider and responses may have substantially longer duration. Here we analyze frequency-response areas (FRAs) and temporal-response patterns of 1,828 units in A1 of halothane-anesthetized cats. Tuning was generally wide: the total bandwidth at 40 dB above threshold was 4 octaves on average. FRA shapes were highly variable and many were diffuse, not fitting into standard classification schemes. Analyzing the temporal patterns of the largest responses of each unit revealed that only 9% of the units had pure onset responses. About 40% of the units had sustained responses throughout stimulus duration (115 ms) and 13% of the units had significant and informative responses lasting 300 ms and more after stimulus offset. We conclude that under halothane anesthesia, neural responses show many of the characteristics of awake responses. Furthermore, A1 units maintain sensory information in their activity not only throughout sound presentation but also for hundreds of milliseconds after stimulus offset, thus possibly playing a role in sensory memory.
6831069
Measuring and interpreting neuronal correlations
Mounting evidence suggests that understanding how the brain encodes information and performs computations will require studying the correlations between neurons. The recent advent of recording techniques such as multielectrode arrays and two-photon imaging has made it easier to measure correlations, opening the door for detailed exploration of their properties and contributions to cortical processing. However, studies have reported discrepant findings, providing a confusing picture. Here we briefly review these studies and conduct simulations to explore the influence of several experimental and physiological factors on correlation measurements. Differences in response strength, the time window over which spikes are counted, spike sorting conventions and internal states can all markedly affect measured correlations and systematically bias estimates. Given these complicating factors, we offer guidelines for interpreting correlation data and a discussion of how best to evaluate the effect of correlations on cortical processing.
17679134
Evidence for Hierarchical Processing in Cat Auditory Cortex: Nonreciprocal Influence of Primary Auditory Cortex on the Posterior Auditory Field
The auditory cortex of the cat is composed of 13 distinct fields that have been defined on the basis of anatomy, physiology, and behavior. Although an anatomically based hierarchical processing scheme has been proposed in auditory cortex, few functional studies have examined how these areas influence one another. The purpose of the present study was to examine the bidirectional processing contributions between primary auditory cortex (A1) and the nonprimary posterior auditory field (PAF). Multiunit acute recording techniques in eight mature cats were used to measure neuronal responses to tonal stimuli in A1 or PAF while synaptic activity from PAF or A1 was suppressed with reversible cooling deactivation techniques. Specifically, in four animals, electrophysiological recordings in A1 were conducted before, during, and after deactivation of PAF. Similarly, in the other four animals, PAF activity was measured before, during, and after deactivation of A1. The characteristic frequency, bandwidth, and neuronal threshold were calculated at each receptive field collected and the response strength and response latency measures were calculated from cumulative peristimulus time histograms. Two major changes in PAF response properties were observed during A1 deactivation: a decrease in response strength and a reduction in receptive field bandwidths. In comparison, we did not identify any significant changes in A1 neuronal responses during deactivation of PAF neurons. These findings support proposed models of hierarchal processing in cat auditory cortex.
6104253
Functional organization of ferret auditory cortex.
We characterized the functional organization of different fields within the auditory cortex of anaesthetized ferrets. As previously reported, the primary auditory cortex, A1, and the anterior auditory field, AAF, are located on the middle ectosylvian gyrus. These areas exhibited a similar tonotopic organization, with high frequencies represented at the dorsal tip of the gyrus and low frequencies more ventrally, but differed in that AAF neurons had shorter response latencies than those in A1. On the basis of differences in frequency selectivity, temporal response properties and thresholds, we identified four more, previously undescribed fields. Two of these are located on the posterior ectosylvian gyrus and were tonotopically organized. Neurons in these areas responded robustly to tones, but had longer latencies, more sustained responses and a higher incidence of non-monotonic rate-level functions than those in the primary fields. Two further auditory fields, which were not tonotopically organized, were found on the anterior ectosylvian gyrus. Neurons in the more dorsal anterior area gave short-latency, transient responses to tones and were generally broadly tuned with a preference for high (>8 kHz) frequencies. Neurons in the other anterior area were frequently unresponsive to tones, but often responded vigorously to broadband noise. The presence of both tonotopic and non-tonotopic auditory cortical fields indicates that the organization of ferret auditory cortex is comparable to that seen in other mammals.
1596086
Laminar Structure of Spontaneous and Sensory-Evoked Population Activity in Auditory Cortex
Spontaneous activity plays an important role in the function of neural circuits. Although many similarities between spontaneous and sensory-evoked neocortical activity have been reported, little is known about consistent differences between them. Here, using simultaneously recorded cortical populations and morphologically identified pyramidal cells, we compare the laminar structure of spontaneous and sensory-evoked population activity in rat auditory cortex. Spontaneous and evoked patterns both exhibited sparse, spatially localized activity in layer 2/3 pyramidal cells, with densely distributed activity in larger layer 5 pyramidal cells and putative interneurons. However, the propagation of spontaneous and evoked activity differed, with spontaneous activity spreading upward from deep layers and slowly across columns, but sensory responses initiating in presumptive thalamorecipient layers, spreading rapidly across columns. The similarity of sparseness patterns for both neural events and distinct spread of activity may reflect similarity of local processing and differences in the flow of information through cortical circuits, respectively.
15014876
Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes
The understanding of brain computations requires methods that read out neural activity on different spatial and temporal scales. Following signal propagation and integration across a neuron and recording the concerted activity of hundreds of neurons pose distinct challenges, and the design of imaging systems has been mostly focused on tackling one of the two operations. We developed a high-resolution, acousto-optic two-photon microscope with continuous three-dimensional (3D) trajectory and random-access scanning modes that reaches near-cubic-millimeter scan range and can be adapted to imaging different spatial scales. We performed 3D calcium imaging of action potential backpropagation and dendritic spike forward propagation at sub-millisecond temporal resolution in mouse brain slices. We also performed volumetric random-access scanning calcium imaging of spontaneous and visual stimulation–evoked activity in hundreds of neurons of the mouse visual cortex in vivo. These experiments demonstrate the subcellular and network-scale imaging capabilities of our system.
41951793
Response properties of inferior colliculus neurons in young and very old CBA/J mice
Extracellular recordings were obtained from inferior colliculus (IC) neurons on young (2-month) and very old (greater than 2-year) CBA/J mice in response to contralateral tone and noise stimuli. The old mice had a small loss of spiral ganglion cells throughout the cochlea and moderate hearing loss, manifested as an elevation of neuronal thresholds throughout the IC. There was an age-related increase (3% to 22%) in 'sluggish' neurons (auditory, but poorly driven by sound); however, most neurons responded robustly to sound. Nine response types were derived from post-stimulus time histograms (PSTHs); all types were found in both age groups with no difference in their relative incidence. Sustained responses remained vigorous in old neurons, as indicated by spike counts and temporal discharge patterns. The percentage of neurons that were spontaneously active increased with age in the ventral IC (the area most sensitive to high frequencies, including most of the central nucleus) and decreased in the dorsal IC (the area most sensitive to lower frequencies, including much of the dorsal cortex). Parameters of response areas (range, upper frequency cutoff, best frequency, and rate-best frequency) showed modest age differences, while rate-level functions showed little age-related change. While a significant correlate of old age was attrition of IC neurons from the population capable of responding robustly to sounds, the majority of individual neurons demonstrated a remarkable degree of normalcy in their responses.
819980
Stimulus Dependence of Neuronal Correlation in Primary Visual Cortex of the Macaque
Nearby cortical neurons often have correlated trial-to-trial response variability, and a significant fraction of their spikes occur synchronously. These two forms of correlation are both believed to arise from common synaptic input, but the origin of this input is unclear. We investigated the source of correlated responsivity by recording from pairs of single neurons in primary visual cortex of anesthetized macaque monkeys and comparing correlated variability and synchrony for spontaneous activity and activity evoked by stimuli of different orientations and contrasts. These two stimulus manipulations would be expected to have different effects on the cortical pool providing input to the recorded pair: changing stimulus orientation should recruit different populations of cells, whereas changing stimulus contrast affects primarily the relative strength of sensory drive and ongoing cortical activity. Consistent with this predicted difference, we found that correlation was affected by these stimulus manipulations in different ways. Synchrony was significantly stronger for orientations that drove both neurons well than for those that did not, but correlation on longer time scales was orientation independent. Reducing stimulus contrast resulted in a decrease in the temporal precision of synchronous firing and an enhancement of correlated response variability on longer time scales. Our results thus suggest that correlated responsivity arises from mechanisms operating at two distinct timescales: one that is orientation tuned and that determines the strength of temporally precise synchrony, and a second that is contrast sensitive, of low temporal frequency, and present in ongoing cortical activity.
9373156
Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior
We studied the simultaneous activity of pairs of neurons recorded with a single electrode in visual cortical area MT while monkeys performed a direction discrimination task. Previously, we reported the strength of interneuronal correlation of spike count on the time scale of the behavioral epoch (2 sec) and noted its potential impact on signal pooling (Zohary et al., 1994). We have now examined correlation at longer and shorter time scales and found that pair-wise cross-correlation was predominantly short term (10–100 msec). Narrow, central peaks in the spike train cross-correlograms were largely responsible for correlated spike counts on the time scale of the behavioral epoch. Longer-term (many seconds to minutes) changes in the responsiveness of single neurons were observed in auto-correlations; however, these slow changes in time were on average uncorrelated between neurons. Knowledge of the limited time scale of correlation allowed the derivation of a more efficient metric for spike count correlation based on spike timing information, and it also revealed a potential relative advantage of larger neuronal pools for shorter integration times. Finally, correlation did not depend on the presence of the visual stimulus or the behavioral choice of the animal. It varied little with stimulus condition but was stronger between neurons with similar direction tuning curves. Taken together, our results strengthen the view that common input, common stimulus selectivity, and common noise are tightly linked in functioning cortical circuits.
2596287
Python for Information Theoretic Analysis of Neural Data
Information theory, the mathematical theory of communication in the presence of noise, is playing an increasingly important role in modern quantitative neuroscience. It makes it possible to treat neural systems as stochastic communication channels and gain valuable, quantitative insights into their sensory coding function. These techniques provide results on how neurons encode stimuli in a way which is independent of any specific assumptions on which part of the neuronal response is signal and which is noise, and they can be usefully applied even to highly non-linear systems where traditional techniques fail. In this article, we describe our work and experiences using Python for information theoretic analysis. We outline some of the algorithmic, statistical and numerical challenges in the computation of information theoretic quantities from neural data. In particular, we consider the problems arising from limited sampling bias and from calculation of maximum entropy distributions in the presence of constraints representing the effects of different orders of interaction in the system. We explain how and why using Python has allowed us to significantly improve the speed and domain of applicability of the information theoretic algorithms, allowing analysis of data sets characterized by larger numbers of variables. We also discuss how our use of Python is facilitating integration with collaborative databases and centralised computational resources.
1674228
Entropy and Inference, Revisited
We study properties of popular near–uniform (Dirichlet) priors for learning undersampled probability distributions on discrete nonmetric spaces and show that they lead to disastrous results. However, an Occam–style phase space argument expands the priors into their infinite mixture and resolves most of the observed problems. This leads to a surprisingly good estimator of entropies of discrete distributions.
205507595
The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes
Neuronal activity in the brain gives rise to transmembrane currents that can be measured in the extracellular medium. Although the major contributor of the extracellular signal is the synaptic transmembrane current, other sources — including Na+ and Ca2+ spikes, ionic fluxes through voltage- and ligand-gated channels, and intrinsic membrane oscillations — can substantially shape the extracellular field. High-density recordings of field activity in animals and subdural grid recordings in humans, combined with recently developed data processing tools and computational modelling, can provide insight into the cooperative behaviour of neurons, their average synaptic input and their spiking output, and can increase our understanding of how these processes contribute to the extracellular signal.
16898669
Comparison of LFP-Based and Spike-Based Spectro-Temporal Receptive Fields and Cross-Correlation in Cat Primary Auditory Cortex
Multi-electrode array recordings of spike and local field potential (LFP) activity were made from primary auditory cortex of 12 normal hearing, ketamine-anesthetized cats. We evaluated 259 spectro-temporal receptive fields (STRFs) and 492 frequency-tuning curves (FTCs) based on LFPs and spikes simultaneously recorded on the same electrode. We compared their characteristic frequency (CF) gradients and their cross-correlation distances. The CF gradient for spike-based FTCs was about twice that for 2–40 Hz-filtered LFP-based FTCs, indicating greatly reduced frequency selectivity for LFPs. We also present comparisons for LFPs band-pass filtered between 4–8 Hz, 8–16 Hz and 16–40 Hz, with spike-based STRFs, on the basis of their marginal frequency distributions. We find on average a significantly larger correlation between the spike based marginal frequency distributions and those based on the 16–40 Hz filtered LFP, compared to those based on the 4–8 Hz, 8–16 Hz and 2–40 Hz filtered LFP. This suggests greater frequency specificity for the 16–40 Hz LFPs compared to those of lower frequency content. For spontaneous LFP and spike activity we evaluated 1373 pair correlations for pairs with >200 spikes in 900 s per electrode. Peak correlation-coefficient space constants were similar for the 2–40 Hz filtered LFP (5.5 mm) and the 16–40 Hz LFP (7.4 mm), whereas for spike-pair correlations it was about half that, at 3.2 mm. Comparing spike-pairs with 2–40 Hz (and 16–40 Hz) LFP-pair correlations showed that about 16% (9%) of the variance in the spike-pair correlations could be explained from LFP-pair correlations recorded on the same electrodes within the same electrode array. This larger correlation distance combined with the reduced CF gradient and much broader frequency selectivity suggests that LFPs are not a substitute for spike activity in primary auditory cortex.
15854180
Sparse Representation of Sounds in the Unanesthetized Auditory Cortex
How do neuronal populations in the auditory cortex represent acoustic stimuli? Although sound-evoked neural responses in the anesthetized auditory cortex are mainly transient, recent experiments in the unanesthetized preparation have emphasized subpopulations with other response properties. To quantify the relative contributions of these different subpopulations in the awake preparation, we have estimated the representation of sounds across the neuronal population using a representative ensemble of stimuli. We used cell-attached recording with a glass electrode, a method for which single-unit isolation does not depend on neuronal activity, to quantify the fraction of neurons engaged by acoustic stimuli (tones, frequency modulated sweeps, white-noise bursts, and natural stimuli) in the primary auditory cortex of awake head-fixed rats. We find that the population response is sparse, with stimuli typically eliciting high firing rates (>20 spikes/second) in less than 5% of neurons at any instant. Some neurons had very low spontaneous firing rates (<0.01 spikes/second). At the other extreme, some neurons had driven rates in excess of 50 spikes/second. Interestingly, the overall population response was well described by a lognormal distribution, rather than the exponential distribution that is often reported. Our results represent, to our knowledge, the first quantitative evidence for sparse representations of sounds in the unanesthetized auditory cortex. Our results are compatible with a model in which most neurons are silent much of the time, and in which representations are composed of small dynamic subsets of highly active neurons.
3044807
Correlations and the encoding of information in the nervous system
Is the information transmitted by an ensemble of neurons determined solely by the number of spikes fired by each cell, or do correlations in the emission of action potentials also play a significant role? We derive a simple formula which enables this question to be answered rigorously for short time–scales. The formula quantifies the corrections to the instantaneous information rate which result from correlations in spike emission between pairs of neurons. The mutual information that the ensemble of neurons conveys about external stimuli can thus be broken down into firing rate and correlation components. This analysis provides fundamental constraints upon the nature of information coding, showing that over short time–scales, correlations cannot dominate information representation, that stimulus–independent correlations may lead to synergy (where the neurons together convey more information than they would if they were considered independently), but that only certain combinations of the different sources of correlation result in significant synergy rather than in redundancy or in negligible effects. This analysis leads to a new quantification procedure which is directly applicable to simultaneous multiple neuron recordings.
18684597
The Role of Correlations in Direction and Contrast Coding in the Primary Visual Cortex
The spiking activity of nearby cortical neurons is not independent. Numerous studies have explored the importance of this correlated responsivity for visual coding and perception, often by comparing the information conveyed by pairs of simultaneously recorded neurons with the sum of information provided by the respective individual cells. Pairwise responses typically provide slightly more information so that encoding is weakly synergistic. The simple comparison between pairwise and summed individual responses conflates several forms of correlation, however, making it impossible to judge the relative importance of synchronous spiking, basic tuning properties, and stimulus-independent and stimulus-dependent correlation. We have applied an information theoretic approach to this question, using the responses of pairs of neurons to drifting sinusoidal gratings of different directions and contrasts that have been recorded in the primary visual cortex of anesthetized macaque monkeys. Our approach allows us to break down the information provided by pairs of neurons into a number of components. This analysis reveals that, although synchrony is prevalent and informative, the additional information it provides frequently is offset by the redundancy arising from the similar tuning properties of the two cells. Thus coding is approximately independent with weak synergy or redundancy arising, depending on the similarity in tuning and the temporal precision of the analysis. We suggest that this would allow cortical circuits to enjoy the stability provided by having similarly tuned neurons without suffering the penalty of redundancy, because the associated information transmission deficit is compensated for by stimulus-dependent synchrony.
24643558
GABA immunoreactive neurons in rat visual cortex
An antiserum to γ‐aminobutyric acid (GABA) was used in a light and electron microscopic immunocytochemical study to determine the morphology and distribution of GABA‐containing neurons in the rat visual cortex and to ascertain whether all classes of nonpyramidal neurons in this cortex are GABAergic. The visual cortex used for light microscopy was prepared in such a way that the antibody penetrated completely through tissue sections, and in these sections large numbers of GABA immunoreactive neurons were apparent. The labeled neurons could be identified as being either multipolar, bitufted, bipolar, or horizontal neurons. In layers II through Via, GABA immunostained cells were distributed uniformly and accounted for approximately 15% of all neurons, but in layer I all neurons appeared to be immunostained.
6702912
Immunochemical characterization of inhibitory mouse cortical neurons: Three chemically distinct classes of inhibitory cells
The cerebral cortex has diverse types of inhibitory neurons. In rat cortex, past research has shown that parvalbumin (PV), somatostatin (SOM), calretinin (CR), and cholecystokinin (CCK) label four distinct chemical classes of GABAergic interneurons. However, in contrast to rat cortex, previous studies indicate that there is significant colocalization of SOM and CR in mouse cortical inhibitory neurons. In the present study we further characterized immunochemical distinctions among mouse inhibitory cortical neurons by double immunochemical labeling with chemical markers. We found that, PV, SOM, and vasointenstinal peptide (VIP) reliably identify three nonoverlapping distinct subpopulations, as there was no overlap of immunoreactivity between PV and all the other chemical markers tested, and SOM and VIP did not show any overlap in labeled neurons in all the cortical areas. In comparison, there was significant overlap in combinations of other chemical markers. With some laminar and regional variations, the average overlap of SOM/CR (percentage of SOM+ cells expressing CR) and SOM/neuropeptide tyrosine (NPY) across all examined layers and cortical regions was 21.6% and 7.1%, respectively. The average overlap of VIP/CR, VIP/NPY, and CR/NPY was 34.2%, 9.5%, and 10%, respectively. We quantified and assessed the percentages of marker‐positive GABAergic cells, and showed that the nonoverlapping subpopulations (i.e., PV+, SOM+ and VIP+ cells) accounted for about 60% of the GABAergic cell population. Taken together, our data reveal important chemical distinctions between mouse inhibitory cortical neurons and indicate that PV, SOM, and VIP can differentially label a majority of mouse inhibitory cortical neurons. J. Comp. Neurol. 518:389–404, 2010. © 2009 Wiley‐Liss, Inc.
15307279
Two populations of layer v pyramidal cells of the mouse neocortex: development and sensitivity to anesthetics.
Previous studies have shown that layer V pyramidal neurons projecting either to subcortical structures or the contralateral cortex undergo different morphological and electrophysiological patterns of development during the first three postnatal weeks. To isolate the determinants of this differential maturation, we analyzed the gene expression and intrinsic membrane properties of layer V pyramidal neurons projecting either to the superior colliculus (SC cells) or the contralateral cortex (CC cells) by combining whole cell recordings and single-cell RT-PCR in acute slices prepared from postnatal day (P) 5-7 or P21-30 old mice. Among the 24 genes tested, the calcium channel subunits alpha1B and alpha1C, the protease Nexin 1, and the calcium-binding protein calbindin were differentially expressed in adult SC and CC cells and the potassium channel subunit Kv4.3 was expressed preferentially in CC cells at both stages of development. Intrinsic membrane properties, including input resistance, amplitude of the hyperpolarization-activated current, and action potential threshold, differed quantitatively between the two populations as early as from the first postnatal week and persisted throughout adulthood. However, the two cell types had similar regular action potential firing behaviors at all developmental stages. Surprisingly, when we increased the duration of anesthesia with ketamine-xylazine or pentobarbital before decapitation, a proportion of mature SC cells, but not CC cells, fired bursts of action potentials. Together these results indicate that the two populations of layer V pyramidal neurons already start to differ during the first postnatal week and exhibit different firing capabilities after anesthesia.
8070423
Functional Maps of Neocortical Local Circuitry
This review aims to summarize data obtained with different techniques to provide a functional map of the local circuit connections made by neocortical neurones, a reference for those interested in cortical circuitry and the numerical information required by those wishing to model the circuit. A brief description of the main techniques used to study circuitry is followed by outline descriptions of the major classes of neocortical excitatory and inhibitory neurones and the connections that each layer makes with other cortical and subcortical regions. Maps summarizing the projection patterns of each class of neurone within the local circuit and tables of the properties of these local circuit connections are provided. This review relies primarily on anatomical studies that have identified the classes of neurones and their local and long distance connections and on paired intracellular and whole-cell recordings which have documented the properties of the connections between them. A large number of different types of synaptic connections have been described, but for some there are only a few published examples and for others the details that can only be obtained with paired recordings and dye-filling are lacking. A further complication is provided by the range of species, technical approaches and age groups used in these studies. Wherever possible the range of available data are summarised and compared. To fill some of the more obvious gaps for the less well-documented cases, data obtained with other methods are also summarized.
19892282
Characterization of neocortical principal cells and interneurons by network interactions and extracellular features.
Most neuronal interactions in the cortex occur within local circuits. Because principal cells and GABAergic interneurons contribute differently to cortical operations, their experimental identification and separation is of utmost important. We used 64-site two-dimensional silicon probes for high-density recording of local neurons in layer 5 of the somatosensory and prefrontal cortices of the rat. Multiple-site monitoring of units allowed for the determination of their two-dimensional spatial position in the brain. Of the approximately 60,000 cell pairs recorded, 0.2% showed robust short-term interactions. Units with significant, short-latency (<3 ms) peaks following their action potentials in their cross-correlograms were characterized as putative excitatory (pyramidal) cells. Units with significant suppression of spiking of their partners were regarded as putative GABAergic interneurons. A portion of the putative interneurons was reciprocally connected with pyramidal cells. Neurons physiologically identified as inhibitory and excitatory cells were used as templates for classification of all recorded neurons. Of the several parameters tested, the duration of the unfiltered (1 Hz to 5 kHz) spike provided the most reliable clustering of the population. High-density parallel recordings of neuronal activity, determination of their physical location and their classification into pyramidal and interneuron classes provide the necessary tools for local circuit analysis.
2680991
Spatial Profile of Excitatory and Inhibitory Synaptic Connectivity in Mouse Primary Auditory Cortex
The role of local cortical activity in shaping neuronal responses is controversial. Among other questions, it is unknown how the diverse response patterns reported in vivo—lateral inhibition in some cases, approximately balanced excitation and inhibition (co-tuning) in others—compare to the local spread of synaptic connectivity. Excitatory and inhibitory activity might cancel each other out, or, whether one outweighs the other, receptive field properties might be substantially affected. As a step toward addressing this question, we used multiple intracellular recording in mouse primary auditory cortical slices to map synaptic connectivity among excitatory pyramidal cells and the two broad classes of inhibitory cells, fast-spiking (FS) and non-FS cells in the principal input layer. Connection probability was distance-dependent; the spread of connectivity, parameterized by Gaussian fits to the data, was comparable for all cell types, ranging from 85 to 114 μm. With brief stimulus trains, unitary synapses formed by FS interneurons were stronger than other classes of synapses; synapse strength did not correlate with distance between cells. The physiological data were qualitatively consistent with predictions derived from anatomical reconstruction. We also analyzed the truncation of neuronal processes due to slicing; overall connectivity was reduced but the spatial pattern was unaffected. The comparable spatial patterns of connectivity and relatively strong excitatory-inhibitory interconnectivity are consistent with a theoretical model where either lateral inhibition or co-tuning can predominate, depending on the structure of the input.
6698567
Auditory Cortical Detection and Discrimination Correlates with Communicative Significance
Plasticity studies suggest that behavioral relevance can change the cortical processing of trained or conditioned sensory stimuli. However, whether this occurs in the context of natural communication, where stimulus significance is acquired through social interaction, has not been well investigated, perhaps because neural responses to species-specific vocalizations can be difficult to interpret within a systematic framework. The ultrasonic communication system between isolated mouse pups and adult females that either do or do not recognize the calls' significance provides an opportunity to explore this issue. We applied an information-based analysis to multi- and single unit data collected from anesthetized mothers and pup-naïve females to quantify how the communicative significance of pup calls affects their encoding in the auditory cortex. The timing and magnitude of information that cortical responses convey (at a 2-ms resolution) for pup call detection and discrimination was significantly improved in mothers compared to naïve females, most likely because of changes in call frequency encoding. This was not the case for a non-natural sound ensemble outside the mouse vocalization repertoire. The results demonstrate that a sensory cortical change in the timing code for communication sounds is correlated with the vocalizations' behavioral relevance, potentially enhancing functional processing by improving its signal to noise ratio.
17980162
Neural Codes Formed by Small and Temporally Precise Populations in Auditory Cortex
The encoding of sensory information by populations of cortical neurons forms the basis for perception but remains poorly understood. To understand the constraints of cortical population coding we analyzed neural responses to natural sounds recorded in auditory cortex of primates (Macaca mulatta). We estimated stimulus information while varying the composition and size of the considered population. Consistent with previous reports we found that when choosing subpopulations randomly from the recorded ensemble, the average population information increases steadily with population size. This scaling was explained by a model assuming that each neuron carried equal amounts of information, and that any overlap between the information carried by each neuron arises purely from random sampling within the stimulus space. However, when studying subpopulations selected to optimize information for each given population size, the scaling of information was strikingly different: a small fraction of temporally precise cells carried the vast majority of information. This scaling could be explained by an extended model, assuming that the amount of information carried by individual neurons was highly nonuniform, with few neurons carrying large amounts of information. Importantly, these optimal populations can be determined by a single biophysical marker—the neuron's encoding time scale—allowing their detection and readout within biologically realistic circuits. These results show that extrapolations of population information based on random ensembles may overestimate the population size required for stimulus encoding, and that sensory cortical circuits may process information using small but highly informative ensembles.
11878416
Reduction of Information Redundancy in the Ascending Auditory Pathway
Information processing by a sensory system is reflected in the changes in stimulus representation along its successive processing stages. We measured information content and stimulus-induced redundancy in the neural responses to a set of natural sounds in three successive stations of the auditory pathway-inferior colliculus (IC), auditory thalamus (MGB), and primary auditory cortex (A1). Information about stimulus identity was somewhat reduced in single A1 and MGB neurons relative to single IC neurons, when information is measured using spike counts, latency, or temporal spiking patterns. However, most of this difference was due to differences in firing rates. On the other hand, IC neurons were substantially more redundant than A1 and MGB neurons. IC redundancy was largely related to frequency selectivity. Redundancy reduction may be a generic organization principle of neural systems, allowing for easier readout of the identity of complex stimuli in A1 relative to IC.