Clock genes control cortical critical period timing

Circadian rhythms control a variety of physiological processes, but whether they may also time brain development remains largely unknown. Here, we show that circadian clock genes control the onset of critical period plasticity in the neocortex. Within visual cortex of Clock-deficient mice, the emergence of circadian gene expression was dampened, and the maturation of inhibitory parvalbumin (PV) cell networks slowed. Loss of visual acuity in response to brief monocular deprivation was concomitantly delayed and rescued by direct enhancement of GABAergic transmission. Conditional deletion of Clock or Bmal1 only within PV cells recapitulated the results of total Clock-deficient mice. Unique downstream gene sets controlling synaptic events and cellular homeostasis for proper maturation and maintenance were found to be mis-regulated by Clock deletion specifically within PV cells. These data demonstrate a developmental role for circadian clock genes outside the suprachiasmatic nucleus, which may contribute mis-timed brain plasticity in associated mental disorders.

Identifying and tracking simulated synaptic inputs from neuronal firing: insights from in vitro experiments

Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes.

Holistic neural coding of Chinese character forms in bilateral ventral visual system

How are Chinese characters recognized and represented in the brain of skilled readers? Functional MRI fast adaptation technique was used to address this question. We found that neural adaptation effects were limited to identical characters in bilateral ventral visual system while no activation reduction was observed for partially overlapping characters regardless of the spatial location of the shared sub-character components, suggesting highly selective neuronal tuning to whole characters. The consistent neural profile across the entire ventral visual cortex indicates that Chinese characters are represented as mutually distinctive wholes rather than combinations of sub-character components, which presents a salient contrast to the left-lateralized, simple-to-complex neural representations of alphabetic words. Our findings thus revealed the cultural modulation effect on both local neuronal activity patterns and functional anatomical regions associated with written symbol recognition. Moreover, the cross-language discrepancy in written symbol recognition mechanism might stem from the language-specific early-stage learning experience.

Multimap formation in visual cortex

An extrastriate visual area such as V2 or V4 contains neurons selective for a multitude of complex shapes, all sharing a common topographic organization. Simultaneously developing multiple interdigitated maps--hereafter a "multimap"--is challenging in that neurons must compete to generate a diversity of response types locally, while cooperating with their dispersed same-type neighbors to achieve uniform visual field coverage for their response type at all orientations, scales, etc. Previously proposed map development schemes have relied on smooth spatial interaction functions to establish both topography and columnar organization, but by locally homogenizing cells' response properties, local smoothing mechanisms effectively rule out multimap formation. We found in computer simulations that the key requirements for multimap development are that neurons are enabled for plasticity only within highly active regions of cortex designated "learning eligibility regions" (LERs), but within an LER, each cell's learning rate is determined only by its activity level with no dependence on location. We show that a hybrid developmental rule that combines spatial and activity-dependent learning criteria in this way successfully produces multimaps when the input stream contains multiple distinct feature types, or in the degenerate case of a single feature type, produces a V1-like map with "salt-and-pepper" structure. Our results support the hypothesis that cortical maps containing a fine mixture of different response types, whether in monkey extrastriate cortex, mouse V1 or elsewhere in the cortex, rather than signaling a breakdown of map formation mechanisms at the fine scale, are a product of a generic cortical developmental scheme designed to map cells with a diversity of response properties across a shared topographic space.

Distribution of orientation selectivity in recurrent networks of spiking neurons with different random topologies

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.

Variance predicts salience in central sensory processing

Information processing in the sensory periphery is shaped by natural stimulus statistics. In the periphery, a transmission bottleneck constrains performance; thus efficient coding implies that natural signal components with a predictably wider range should be compressed. In a different regime--when sampling limitations constrain performance--efficient coding implies that more resources should be allocated to informative features that are more variable. We propose that this regime is relevant for sensory cortex when it extracts complex features from limited numbers of sensory samples. To test this prediction, we use central visual processing as a model: we show that visual sensitivity for local multi-point spatial correlations, described by dozens of independently-measured parameters, can be quantitatively predicted from the structure of natural images. This suggests that efficient coding applies centrally, where it extends to higher-order sensory features and operates in a regime in which sensitivity increases with feature variability.

Focal cortical lesions induce bidirectional changes in the excitability of fast spiking and non fast spiking cortical interneurons

A physiological brain function requires neuronal networks to operate within a well-defined range of activity. Indeed, alterations in neuronal excitability have been associated with several pathological conditions, ranging from epilepsy to neuropsychiatric disorders. Changes in inhibitory transmission are known to play a key role in the development of hyperexcitability. However it is largely unknown whether specific interneuronal subpopulations contribute differentially to such pathological condition. In the present study we investigated functional alterations of inhibitory interneurons embedded in a hyperexcitable cortical circuit at the border of chronically induced focal lesions in mouse visual cortex. Interestingly, we found opposite alterations in the excitability of non fast-spiking (Non Fs) and fast-spiking (Fs) interneurons in acute cortical slices from injured animals. Non Fs interneurons displayed a depolarized membrane potential and a higher frequency of spontaneous excitatory postsynaptic currents (sEPSCs). In contrast, Fs interneurons showed a reduced sEPSCs amplitude. The observed downscaling of excitatory synapses targeting Fs interneurons may prevent the recruitment of this specific population of interneurons to the hyperexcitable network. This mechanism is likely to seriously affect neuronal network function and to exacerbate hyperexcitability but it may be important to protect this particular vulnerable population of GABAegic neurons from excitotoxicity.

Moving sensory adaptation beyond suppressive effects in single neurons

How an object is perceived depends on the temporal context in which it is encountered. Sensory signals in the brain also depend on temporal context, a phenomenon often referred to as adaptation. Traditional descriptions of adaptation effects emphasize various forms of response fatigue in single neurons, which grow in strength with exposure to a stimulus. Recent work on vision, and other sensory modalities, has shown that this description has substantial shortcomings. Here we review our emerging understanding of how adaptation alters the balance between excitatory and suppressive signals, how effects depend on adaptation duration, and how adaptation influences representations that are distributed within and across multiple brain structures. This work points to a sophisticated set of mechanisms for adjusting to recent sensory experience, and suggests new avenues for understanding their function.

Thy1-GCaMP6 transgenic mice for neuronal population imaging in vivo

Genetically-encoded calcium indicators (GECIs) facilitate imaging activity of genetically defined neuronal populations in vivo. The high intracellular GECI concentrations required for in vivo imaging are usually achieved by viral gene transfer using adeno-associated viruses. Transgenic expression of GECIs promises important advantages, including homogeneous, repeatable, and stable expression without the need for invasive virus injections. Here we present the generation and characterization of transgenic mice expressing the GECIs GCaMP6s or GCaMP6f under the Thy1 promoter. We quantified GCaMP6 expression across brain regions and neurons and compared to other transgenic mice and AAV-mediated expression. We tested three mouse lines for imaging in the visual cortex in vivo and compared their performance to mice injected with AAV expressing GCaMP6. Furthermore, we show that GCaMP6 Thy1 transgenic mice are useful for long-term, high-sensitivity imaging in behaving mice.

Formation of excitation-inhibition balance: inhibition listens and changes its tune

Recently, Xue, Atallah, and Scanziani reported that excitation/inhibition ratios across cortical pyramidal neurons are equalized by activity-dependent modulations of parvalbumin-neuron mediated feedforward inhibition. Their results raise questions about the developmental formation of this excitation-inhibition balance and the potential activity-dependent synaptic plasticity rules that mediate this process.

Experience-dependent plasticity of visual cortical microcircuits

The recent decade testified a tremendous increase in our knowledge on how cell-type-specific microcircuits process sensory information in the neocortex and on how such circuitry reacts to manipulations of the sensory environment. Experience-dependent plasticity has now been investigated with techniques endowed with cell resolution during both postnatal development and in adult animals. This review recapitulates the main recent findings in the field using mainly the primary visual cortex as a model system to highlight the more important questions and physiological principles (such as the role of non-competitive mechanisms, the role of inhibition in excitatory cell plasticity, the functional importance of spine and axonal plasticity on a microscale level). I will also discuss on which scientific problems the debate and controversies are more pronounced. New technologies that allow to perturbate cell-type-specific subcircuits will certainly shine new light in the years to come at least on some of the still open questions.

The effects of short-term synaptic depression at thalamocortical synapses on orientation tuning in cat V1

We examine the effects of short-term synaptic depression on the orientation tuning of the LGN input to simple cells in cat primary visual cortex (V1). The total LGN input has an untuned component as well as a tuned component, both of which grow with stimulus contrast. The untuned component is not visible in the firing rate responses of the simple cells. The suppression of the contribution of the untuned input component to firing rate responses is key to establishing orientation selectivity and its invariance with stimulus contrast. It has been argued that synaptic depression of LGN inputs could contribute to the selective suppression of the untuned component and thus contribute to the tuning observed in simple cells. We examine this using a model fit to the depression observed at thalamocortical synapses in-vivo, and compare this to an earlier model fit based on in-vitro observations. We examine the tuning of both the conductance and the firing rate induced in simple cells by the net LGN input. We find that depression causes minimal suppression of the untuned component. The primary effect of depression is to cause the contrast response curve to saturate at lower contrasts without differentially affecting the tuned vs. untuned components. This effect is slightly weaker for in-vivo vs. in-vitro parameters. Thus, synaptic depression of LGN inputs does not appreciably contribute to the orientation tuning of V1 simple cells.

Pyramidal cells make specific connections onto smooth (GABAergic) neurons in mouse visual cortex

Light and electron microscopy of the primary visual cortex of mice indicates that pyramidal neurons connect preferentially to inhibitory neurons.

One of the hallmarks of neocortical circuits is the predominance of recurrent excitation between pyramidal neurons, which is balanced by recurrent inhibition from smooth GABAergic neurons. It has been previously described that in layer 2/3 of primary visual cortex (V1) of cat and monkey, pyramidal cells filled with horseradish peroxidase connect approximately in proportion to the spiny (excitatory, 95% and 81%, respectively) and smooth (GABAergic, 5% and 19%, respectively) dendrites found in the neuropil. By contrast, a recent ultrastructural study of V1 in a single mouse found that smooth neurons formed 51% of the targets of the superficial layer pyramidal cells. This suggests that either the neuropil of this particular mouse V1 had a dramatically different composition to that of V1 in cat and monkey, or that smooth neurons were specifically targeted by the pyramidal cells in that mouse. We tested these hypotheses by examining similar cells filled with biocytin in a sample of five mice. We found that the average composition of the neuropil in V1 of these mice was similar to that described for cat and monkey V1, but that the superficial layer pyramidal cells do form proportionately more synapses with smooth dendrites than the equivalent neurons in cat or monkey. These distributions may underlie the distinct differences in functional architecture of V1 between rodent and higher mammals.

The mammalian visual cortex, which is part of the cerebral cortex, contains 50 to 100 thousands of neurons per cubic millimetre, most of which are excitatory (85%) and the minority, inhibitory (15%). Unlike neurons in the retina, neurons in the visual cortex are preferentially activated by lines or edges of a particular orientation. This is termed a neuron's “orientation preference.” In the visual cortex of higher mammals like cats and monkeys, neurons that share an orientation preference are clustered in functional columns. However, in rodents like mice, orientation preferences are randomly distributed. In this study, we investigate whether the differences between columnar and non-columnar cortex is correlated with differences in the connectivity patterns between excitatory and inhibitory neurons. Using light and electron microscopy, we mapped the connectivity of pyramidal neurons—the primary excitatory neurons—in the superficial layers of the primary visual cortex (V1) of mice. Our results show that the ratio of excitatory-inhibitory neurons in mouse V1 is similar to that of cat or monkey V1, but in mouse V1 local pyramidal neurons target proportionately many more inhibitory neurons compared to what other studies found in cat or monkey. This difference may indicate the significance of inhibition in maintaining orientation selectivity in the non-columnar visual cortex of rodents like mice and is a distinct difference in the architecture of V1 between mice and higher mammals.

The disorganized visual cortex in reelin-deficient mice is functional and allows for enhanced plasticity

A hallmark of neocortical circuits is the segregation of processing streams into six distinct layers. The importance of this layered organization for cortical processing and plasticity is little understood. We investigated the structure, function and plasticity of primary visual cortex (V1) of adult mice deficient for the glycoprotein reelin and their wild-type littermates. In V1 of rl-/- mice, cells with different laminar fates are present at all cortical depths. Surprisingly, the (vertically) disorganized cortex maintains a precise retinotopic (horizontal) organization. Rl-/- mice have normal basic visual capabilities, but are compromised in more challenging perceptual tasks, such as orientation discrimination. Additionally, rl-/- animals learn and memorize a visual task as well as their wild-type littermates. Interestingly, reelin deficiency enhances visual cortical plasticity: juvenile-like ocular dominance plasticity is preserved into late adulthood. The present data offer an important insight into the capabilities of a disorganized cortical system to maintain basic functional properties.

Auditory-prefrontal axonal connectivity in the macaque cortex: quantitative assessment of processing streams

Primate sensory systems subserve complex neurocomputational functions. Consequently, these systems are organised anatomically in a distributed fashion, commonly linking areas to form specialised processing streams. Each stream is related to a specific function, as evidenced from studies of the visual cortex, which features rather prominent segregation into spatial and non-spatial domains. It has been hypothesised that other sensory systems, including auditory, are organised in a similar way on the cortical level. Recent studies offer rich qualitative evidence for the dual stream hypothesis. Here we provide a new paradigm to quantitatively uncover these patterns in the auditory system, based on an analysis of multiple anatomical studies using multivariate techniques. As a test case, we also apply our assessment techniques to more ubiquitously-explored visual system. Importantly, the introduced framework opens the possibility for these techniques to be applied to other neural systems featuring a dichotomised organisation, such as language or music perception.

[Local synchronized activity of neurons of different classes in cat primary visual cortex]

The goal of the present study was to investigate the local synchronized neuronal activity in the cat visual cortex and the role of different classes of neurons in neural synchrony. Four classes of neurons were identified on the basis of electrophysiological properties of extracellular recorded cells: RS, FS, IB and FRB. It was revealed that neurons with short spikes and FRB type of activity were first engaged in synchronization. The model study revealed that neurons with the short action potential had more stable synchronized activity.

Snx14 regulates neuronal excitability, promotes synaptic transmission, and is imprinted in the brain of mice

Genomic imprinting describes an epigenetic process through which genes can be expressed in a parent-of-origin-specific manner. The monoallelic expression of imprinted genes renders them particularly susceptible to disease causing mutations. A large proportion of imprinted genes are expressed in the brain, but little is known about their functions. Indeed, it has proven difficult to identify cell type-specific imprinted genes due to the heterogeneity of cell types within the brain. Here we used laser capture microdissection of visual cortical neurons and found evidence that sorting nexin 14 (Snx14) is a neuronally imprinted gene in mice. SNX14 protein levels are high in the brain and progressively increase during neuronal development and maturation. Snx14 knockdown reduces intrinsic excitability and severely impairs both excitatory and inhibitory synaptic transmission. These data reveal a role for monoallelic Snx14 expression in maintaining normal neuronal excitability and synaptic transmission.

Distinct profiles of myelin distribution along single axons of pyramidal neurons in the neocortex

Myelin is a defining feature of the vertebrate nervous system. Variability in the thickness of the myelin envelope is a structural feature affecting the conduction of neuronal signals. Conversely, the distribution of myelinated tracts along the length of axons has been assumed to be uniform. Here, we traced high-throughput electron microscopy reconstructions of single axons of pyramidal neurons in the mouse neocortex and built high-resolution maps of myelination. We find that individual neurons have distinct longitudinal distribution of myelin. Neurons in the superficial layers displayed the most diversified profiles, including a new pattern where myelinated segments are interspersed with long, unmyelinated tracts. Our data indicate that the profile of longitudinal distribution of myelin is an integral feature of neuronal identity and may have evolved as a strategy to modulate long-distance communication in the neocortex.

Neuronal and perceptual differences in the temporal processing of darks and lights

Visual information is mediated by two major thalamic pathways that signal light decrements (OFF) and increments (ON) in visual scenes, the OFF pathway being faster than the ON. Here, we demonstrate that this OFF temporal advantage is transferred to visual cortex and has a correlate in human perception. OFF-dominated cortical neurons in cats responded ∼3 ms faster to visual stimuli than ON-dominated cortical neurons, and dark-mediated suppression in ON-dominated neurons peaked ∼14 ms faster than light-mediated suppression in OFF-dominated neurons. Consistent with the neuronal differences, human observers were 6-14 ms faster at detecting darks than lights and better at discriminating dark than light flickers. Neuronal and perceptual differences both vanished if backgrounds were biased toward darks. Our results suggest that the cortical OFF pathway is faster than the ON pathway at increasing and suppressing visual responses, and these differences have parallels in the human visual perception of lights and darks.

Expression of m1-type muscarinic acetylcholine receptors by parvalbumin-immunoreactive neurons in the primary visual cortex: a comparative study of rat, guinea pig, ferret, macaque, and human

Cholinergic neuromodulation is a candidate mechanism for aspects of arousal and attention in mammals. We have reported previously that cholinergic modulation in the primary visual cortex (V1) of the macaque monkey is strongly targeted toward GABAergic interneurons, and in particular that the vast majority of parvalbumin-immunoreactive (PV) neurons in macaque V1 express the m1-type (pirenzepine-sensitive, Gq-coupled) muscarinic ACh receptor (m1AChR). In contrast, previous physiological data indicates that PV neurons in rats rarely express pirenzepine-sensitive muscarinic AChRs. To examine further this apparent species difference in the cholinergic effectors for the primary visual cortex, we have conducted a comparative study of the expression of m1AChRs by PV neurons in V1 of rats, guinea pigs, ferrets, macaques, and humans. We visualize PV- and mAChR-immunoreactive somata by dual-immunofluorescence confocal microscopy and find that the species differences are profound; the vast majority (>75%) of PV-ir neurons in macaques, humans, and guinea pigs express m1AChRs. In contrast, in rats only ∼25% of the PV population is immunoreactive for m1AChRs. Our data reveal that while they do so much less frequently than in primates, PV neurons in rats do express Gq-coupled muscarinic AChRs, which appear to have gone undetected in the previous in vitro studies. Data such as these are critical in determining the species that represent adequate models for the capacity of the cholinergic system to modulate inhibition in the primate cortex.

Cortico-cortical connections of areas 44 and 45B in the macaque monkey

In the human brain, areas 44 and 45 constitute Broca's region, the ventrolateral frontal region critical for language production. The homologues of these areas in the macaque monkey brain have been established by direct cytoarchitectonic comparison with the human brain. The cortical areas that project monosynaptically to areas 44 and 45B in the macaque monkey brain require clarification. Fluorescent retrograde tracers were placed in cytoarchitectonic areas 44 and 45B of the macaque monkey, as well as in the anterior part of the inferior parietal lobule and the superior temporal gyrus. The results demonstrate that ipsilateral afferent connections of area 44 arise from local frontal areas, including rostral premotor cortical area 6, from secondary somatosensory cortex, the caudal insula, and the cingulate motor region. Area 44 is strongly linked with the anterior inferior parietal lobule (particularly area PFG and the adjacent anterior intraparietal sulcus). Input from the temporal lobe is limited to the fundus of the superior temporal sulcus extending caudal to the central sulcus. There is also input from the sulcal part of area Tpt in the upper bank of the superior temporal sulcus. Area 45B shares some of the connections of area 44, but can be distinguished from area 44 by input from the caudal inferior parietal lobule (area PG) and significant input from the part of the superior temporal sulcus that extends anterior to the central sulcus. Area 45B also receives input from visual association cortex that is not observed in area 44. The results have provided a clarification of the relative connections of areas 44 and 45B of the ventrolateral frontal region which, in the human brain, subserves certain aspects of language processing.

A dedicated circuit links direction-selective retinal ganglion cells to the primary visual cortex

How specific features in the environment are represented within the brain is an important unanswered question in neuroscience. A subset of retinal neurons, called direction-selective ganglion cells (DSGCs), are specialized for detecting motion along specific axes of the visual field. Despite extensive study of the retinal circuitry that endows DSGCs with their unique tuning properties, their downstream circuitry in the brain and thus their contribution to visual processing has remained unclear. In mice, several different types of DSGCs connect to the dorsal lateral geniculate nucleus (dLGN), the visual thalamic structure that harbours cortical relay neurons. Whether direction-selective information computed at the level of the retina is routed to cortical circuits and integrated with other visual channels, however, is unknown. Here we show that there is a di-synaptic circuit linking DSGCs with the superficial layers of the primary visual cortex (V1) by using viral trans-synaptic circuit mapping and functional imaging of visually driven calcium signals in thalamocortical axons. This circuit pools information from several types of DSGCs, converges in a specialized subdivision of the dLGN, and delivers direction-tuned and orientation-tuned signals to superficial V1. Notably, this circuit is anatomically segregated from the retino-geniculo-cortical pathway carrying non-direction-tuned visual information to deeper layers of V1, such as layer 4. Thus, the mouse harbours several functionally specialized, parallel retino-geniculo-cortical pathways, one of which originates with retinal DSGCs and delivers direction- and orientation-tuned information specifically to the superficial layers of the primary visual cortex. These data provide evidence that direction and orientation selectivity of some V1 neurons may be influenced by the activation of DSGCs.

Responses to orientation discontinuities in V1 and V2: physiological dissociations and functional implications

Segmenting the visual image into objects is a crucial stage of visual processing. Object boundaries are typically associated with differences in luminance, but discontinuities in texture also play an important role. We showed previously that a subpopulation of neurons in V2 in anesthetized macaques responds to orientation discontinuities parallel to their receptive field orientation. Such single-cell responses could be a neurophysiological correlate of texture boundary detection. Neurons in V1, on the other hand, are known to have contextual response modulations such as iso-orientation surround suppression, which also produce responses to orientation discontinuities. Here, we use pseudorandom multiregion grating stimuli of two frame durations (20 and 40 ms) to probe and compare texture boundary responses in V1 and V2 in anesthetized macaque monkeys. In V1, responses to texture boundaries were observed for only the 40 ms frame duration and were independent of the orientation of the texture boundary. However, in transient V2 neurons, responses to such texture boundaries were robust for both frame durations and were stronger for boundaries parallel to the neuron's preferred orientation. The dependence of these processes on stimulus duration and orientation indicates that responses to texture boundaries in V2 arise independently of contextual modulations in V1. In addition, because the responses in transient V2 neurons are sensitive to the orientation of the texture boundary but those of V1 neurons are not, we suggest that V2 responses are the correlate of texture boundary detection, whereas contextual modulation in V1 serves other purposes, possibly related to orientation "pop-out."

ER stress-induced eIF2-alpha phosphorylation underlies sensitivity of striatal neurons to pathogenic huntingtin

A hallmark of Huntington's disease is the pronounced sensitivity of striatal neurons to polyglutamine-expanded huntingtin expression. Here we show that cultured striatal cells and murine brain striatum have remarkably low levels of phosphorylation of translation initiation factor eIF2α, a stress-induced process that interferes with general protein synthesis and also induces differential translation of pro-apoptotic factors. EIF2α phosphorylation was elevated in a striatal cell line stably expressing pathogenic huntingtin, as well as in brain sections of Huntington's disease model mice. Pathogenic huntingtin caused endoplasmic reticulum (ER) stress and increased eIF2α phosphorylation by increasing the activity of PKR-like ER-localized eIF2α kinase (PERK). Importantly, striatal neurons exhibited special sensitivity to ER stress-inducing agents, which was potentiated by pathogenic huntingtin. We could strongly reduce huntingtin toxicity by inhibiting PERK. Therefore, alteration of protein homeostasis and eIF2α phosphorylation status by pathogenic huntingtin appears to be an important cause of striatal cell death. A dephosphorylated state of eIF2α has been linked to cognition, which suggests that the effect of pathogenic huntingtin might also be a source of the early cognitive impairment seen in patients.

Cannabinoid neuromodulation in the adult early visual cortex

Sensory processing is an active process involving the interaction of ongoing cortical activity with incoming stimulus information. However, the modulators and circuits involved in this interaction are incompletely understood. One potential candidate is the cannabinoid-signaling system, which is known to modulate the dynamics of cortical networks. Here, we show that in the primate primary and secondary visual cortices, the cannabinoid CP55940 modulates not only population dynamics but also influences the dynamics of the stimulus-response relationship of individual neurons. At the population level, CP55940 decreases EEG power, LFP power, and LFP coherence. At the single-neuron level, intrinsic spike train dynamics appear relatively unchanged, but visual receptive fields are altered: CP55940 induced an overall delay and broadening of the temporal component of V1 and V2 spatiotemporal receptive fields. Our findings provide neurophysiologic evidence for a link between cannabinoid-signaling, network dynamics and the function of a canonical cortical circuit.

Distal connectivity causes summation and division across mouse visual cortex

Neurons in different locations across the cortex are connected through polysynaptic networks involving both excitation and inhibition. To probe the functional effect of such networks, we used optogenetic stimulation to trigger antidromic spikes in a local region of primary visual cortex (V1). This local activity had two effects at distal V1 locations: summation and division. The balance between the two depended on visual contrast, and a normalization model precisely captured these effects.

[Development of Meynert cells in cat visual cortex under the conditions of flickering light stimulation]

To examine the effect of rhythmical light stimulation on postnatal development of the visual system, the formation of Meynert cells was studied in area 17 and posteromedial suprasylvian area (PMLS) of kittens reared under the conditions of flickering light stimulation (15 Hz frequency). Profile area of neuronal cell bodies and cytochrome oxidase (CO) activity level were measured in frontal sections of the visual cortex in control (n = 6) and stimulated (n = 6) kittens. Meynert cells located in area 17 and PMLS demonstrated an approximately 37% increase in CO activity in the stimulated animals. At the same time, the profile area of Meynert cell bodies in PMLS was decreased by 20% as compared to that in normal animals. The presence of functional disturbances of Y-conducting visual channel and the possibility of binocular vision suppression in the stimulated animals are discussed.

Role of electrical activity in horizontal axon growth in the developing cortex: a time-lapse study using optogenetic stimulation

During development, layer 2/3 neurons in the neocortex extend their axons horizontally, within the same layers, and stop growing at appropriate locations to form branches and synaptic connections. Firing and synaptic activity are thought to be involved in this process, but how neuronal activity regulates axonal growth is not clear. Here, we studied axonal growth of layer 2/3 neurons by exciting cell bodies or axonal processes in organotypic slice cultures of the rat cortex. For neuronal stimulation and morphological observation, plasmids encoding channelrhodopsin-2 (ChR2) and DsRed were coelectroporated into a small number of layer 2/3 cells. Firing activity induced by photostimulation (475 nm) was confirmed by whole-cell patch recording. Axonal growth was observed by time-lapse confocal microscopy, using a different excitation wavelength (560 nm), at 10–20-min intervals for several hours. During the first week in vitro, when spontaneous neuronal activity is low, DsRed- and ChR2-expressing axons grew at a constant rate. When high-frequency photostimulation (4 or 10 Hz) for 1 min was applied to the soma or axon, most axons paused in their growth. In contrast, lower-frequency stimulation did not elicit this pause behavior. Moreover, in the presence of tetrodotoxin, even high-frequency stimulation did not cause axonal growth to pause. These results indicate that increasing firing activity during development suppresses axon growth, suggesting the importance of neuronal activity for the formation of horizontal connections.

Spatial and feature-based attention in a layered cortical microcircuit model

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception.

[Effects of ketamine and urethane on stimulation-induced c-fos expression in neurons of cat visual cortex]

The effects of ketamine and urethane on neuronal activities remain in debate. As a member of immediate early genes family, the expression of c-fos is stimulation dependent and could be treated as an index to evaluate the strength of neural activities. In this study, SABC immunohistochemical techniques were applied to compare the c-fos expression in neurons of the primary visual cortex (V1) of cats and therefore, to evaluate the effects of acute anesthesia with ketamine HCl and uethane on inhibiting neural activities. Our results showed that compared with control cats, there were no significant differences with the average densities of Nissl-stained V1 neurons in each cortical layers of either urethane or ketamine anesthetized cats. In urethane anesthetized cats, neither the average densities nor the immunoreactive intensities of c-fos positive V1 neurons showed significant difference with that of control ones. However, both the average densities and immunoreactive intensities of c-fos positive V1 neurons in ketamine anesthetized cats decreased significantly compared with that of control and urethane anesthetized cats. These results suggested that ketamine has strong inhibitory effects on the activities of visual cortical neurons, whereas urethane did not.

Linking assumptions in amblyopia

Over the last 35 years or so, there has been substantial progress in revealing and characterizing the many interesting and sometimes mysterious sensory abnormalities that accompany amblyopia. A goal of many of the studies has been to try to make the link between the sensory losses and the underlying neural losses, resulting in several hypotheses about the site, nature, and cause of amblyopia. This article reviews some of these hypotheses, and the assumptions that link the sensory losses to specific physiological alterations in the brain. Despite intensive study, it turns out to be quite difficult to make a simple linking hypothesis, at least at the level of single neurons, and the locus of the sensory loss remains elusive. It is now clear that the simplest notion-that reduced contrast sensitivity of neurons in cortical area V1 explains the reduction in contrast sensitivity-is too simplistic. Considerations of noise, noise correlations, pooling, and the weighting of information also play a critically important role in making perceptual decisions, and our current models of amblyopia do not adequately take these into account. Indeed, although the reduction of contrast sensitivity is generally considered to reflect "early" neural changes, it seems plausible that it reflects changes at many stages of visual processing.

A simple rule for dendritic spine and axonal bouton formation can account for cortical reorganization after focal retinal lesions

Lasting alterations in sensory input trigger massive structural and functional adaptations in cortical networks. The principles governing these experience-dependent changes are, however, poorly understood. Here, we examine whether a simple rule based on the neurons' need for homeostasis in electrical activity may serve as driving force for cortical reorganization. According to this rule, a neuron creates new spines and boutons when its level of electrical activity is below a homeostatic set-point and decreases the number of spines and boutons when its activity exceeds this set-point. In addition, neurons need a minimum level of activity to form spines and boutons. Spine and bouton formation depends solely on the neuron's own activity level, and synapses are formed by merging spines and boutons independently of activity. Using a novel computational model, we show that this simple growth rule produces neuron and network changes as observed in the visual cortex after focal retinal lesions. In the model, as in the cortex, the turnover of dendritic spines was increased strongest in the center of the lesion projection zone, while axonal boutons displayed a marked overshoot followed by pruning. Moreover, the decrease in external input was compensated for by the formation of new horizontal connections, which caused a retinotopic remapping. Homeostatic regulation may provide a unifying framework for understanding cortical reorganization, including network repair in degenerative diseases or following focal stroke.

The adult brain is less hard-wired than traditionally thought. About ten percent of synapses in the mature visual cortex is continually replaced by new ones (structural plasticity). This percentage greatly increases after lasting changes in visual input. Due to the topographically organized nerve connections from the retina in the eye to the primary visual cortex in the brain, a small circumscribed lesion in the retina leads to a defined area in the cortex that is deprived of input. Recent experimental studies have revealed that axonal sprouting and dendritic spine turnover are massively increased in and around the cortical area that is deprived of input. However, the driving forces for this structural plasticity remain unclear. Using a novel computational model, we examine whether the need for activity homeostasis of individual neurons may drive cortical reorganization after lasting changes in input activity. We show that homeostatic growth rules indeed give rise to structural and functional reorganization of neuronal networks similar to the cortical reorganization observed experimentally. Understanding the principles of structural plasticity may eventually lead to novel treatment strategies for stimulating functional reorganization after brain damage and neurodegeneration.

The fine structure of shape tuning in area V4

Previous studies have shown that neurons in area V4 are involved in the processing of shapes of intermediate complexity and are sensitive to curvature. These studies also suggest that curvature-tuned neurons are position invariant. We sought to examine the mechanisms that endow V4 neurons with these properties. Consistent with previous studies, we found that response rank order to the most- and least-preferred stimuli was preserved throughout the receptive field. However, a fine-grained analysis of shape tuning revealed a surprising result: V4 neurons tuned to highly curved shapes exhibit very limited translation invariance. At a fine spatial scale, these neurons exhibit local variation in orientation. In contrast, neurons that prefer straight contours exhibit spatially invariant orientation-tuning and homogenous fine-scale orientation maps. Both of these patterns are consistent with a simple orientation-pooling model, with tuning for straight or curved shapes resulting, respectively, from pooling of homogenous or heterogeneous orientation signals inherited from early visual areas.

Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system

Extensive electrophysiology studies have shown that many V1 simple cells have nonlinear response properties to stimuli within their classical receptive field (CRF) and receive contextual influence from stimuli outside the CRF modulating the cell's response. Models seeking to explain these non-classical receptive field (nCRF) effects in terms of circuit mechanisms, input-output descriptions, or individual visual tasks provide limited insight into the functional significance of these response properties, because they do not connect the full range of nCRF effects to optimal sensory coding strategies. The (population) sparse coding hypothesis conjectures an optimal sensory coding approach where a neural population uses as few active units as possible to represent a stimulus. We demonstrate that a wide variety of nCRF effects are emergent properties of a single sparse coding model implemented in a neurally plausible network structure (requiring no parameter tuning to produce different effects). Specifically, we replicate a wide variety of nCRF electrophysiology experiments (e.g., end-stopping, surround suppression, contrast invariance of orientation tuning, cross-orientation suppression, etc.) on a dynamical system implementing sparse coding, showing that this model produces individual units that reproduce the canonical nCRF effects. Furthermore, when the population diversity of an nCRF effect has also been reported in the literature, we show that this model produces many of the same population characteristics. These results show that the sparse coding hypothesis, when coupled with a biophysically plausible implementation, can provide a unified high-level functional interpretation to many response properties that have generally been viewed through distinct mechanistic or phenomenological models.

Simple cells in the primary visual cortex (V1) demonstrate many response properties that are either nonlinear or involve response modulations (i.e., stimuli that do not cause a response in isolation alter the cell's response to other stimuli). These non-classical receptive field (nCRF) effects are generally modeled individually and their collective role in biological vision is not well understood. Previous work has shown that classical receptive field (CRF) properties of V1 cells (i.e., the spatial structure of the visual field responsive to stimuli) could be explained by the sparse coding hypothesis, which is an optimal coding model that conjectures a neural population should use the fewest number of cells simultaneously to represent each stimulus. In this paper, we have performed extensive simulated physiology experiments to show that many nCRF response properties are simply emergent effects of a dynamical system implementing this same sparse coding model. These results suggest that rather than representing disparate information processing operations themselves, these nCRF effects could be consequences of an optimal sensory coding strategy that attempts to represent each stimulus most efficiently. This interpretation provides a potentially unifying high-level functional interpretation to many response properties that have generally been viewed through distinct models.

Simulating cortical development as a self constructing process: a novel multi-scale approach combining molecular and physical aspects

Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

The proper operation of the brain depends on the correct developmental wiring of billions of neurons. Understanding this process of living self-construction is crucial not only for biological explanation and medical therapy, but could also provide an entirely new approach to industrial fabrication. We are approaching this problem through detailed simulation of cortical development. We have previously presented a software package that allows for simulation of cellular growth in a 3D space that respects physical forces and diffusion of substances, as well as an instruction language for specifying biologically plausible ‘genetic codes’. Here we apply this novel formalism to understanding the principles of cortical development in the context of multiple, spatially distributed agents that communicate only by local metabolic messages.

A functional and perceptual signature of the second visual area in primates

There is no generally accepted account of the function of the second visual cortical area (V2), partly because no simple response properties robustly distinguish V2 neurons from those in primary visual cortex (V1). We constructed synthetic stimuli replicating the higher-order statistical dependencies found in natural texture images and used them to stimulate macaque V1 and V2 neurons. Most V2 cells responded more vigorously to these textures than to control stimuli lacking naturalistic structure; V1 cells did not. Functional magnetic resonance imaging (fMRI) measurements in humans revealed differences between V1 and V2 that paralleled the neuronal measurements. The ability of human observers to detect naturalistic structure in different types of texture was well predicted by the strength of neuronal and fMRI responses in V2 but not in V1. Together, these results reveal a particular functional role for V2 in the representation of natural image structure.

Are v1 simple cells optimized for visual occlusions? A comparative study

Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of 'globular' receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of 'globular' fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of 'globular' fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of 'globular' fields well. Our computational study, therefore, suggests that 'globular' fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.

Binocular integration and disparity selectivity in mouse primary visual cortex

Signals from the two eyes are first integrated in primary visual cortex (V1). In many mammals, this binocular integration is an important first step in the development of stereopsis, the perception of depth from disparity. Neurons in the binocular zone of mouse V1 receive inputs from both eyes, but it is unclear how that binocular information is integrated and whether this integration has a function similar to that found in other mammals. Using extracellular recordings, we demonstrate that mouse V1 neurons are tuned for binocular disparities, or spatial differences, between the inputs from each eye, thus extracting signals potentially useful for estimating depth. The disparities encoded by mouse V1 are significantly larger than those encoded by cat and primate. Interestingly, these larger disparities correspond to distances that are likely to be ecologically relevant in natural viewing, given the stereo-geometry of the mouse visual system. Across mammalian species, it appears that binocular integration is a common cortical computation used to extract information relevant for estimating depth. As such, it is a prime example of how the integration of multiple sensory signals is used to generate accurate estimates of properties in our environment.

Adaptation to visual stimulation modifies the burst firing property of V1 neurons

The mean firing rate of visual cortical neurons is reduced after prolonged visual stimulation, but the underlying process by which this occurs as well as the biological significance of this phenomenon remains unknown. Computational neuroscience studies indicate that high-frequency bursts in stimulus-driven responses can be transmitted across synapses more reliably than isolated spikes, and thus may carry accurate stimulus-related information. Our research examined whether or not adaptation affects the burst firing property of visual cortical neurons by examining changes in the burst firing changes of V1 neurons during adaptation to the preferred visual stimulus. The results show that adaptation to prolonged visual stimulation significantly decreased burst frequency (bursts/s) and burst length (spikes/burst), but increased burst duration and the interspike interval within bursts. These results suggest that the adaptation of V1 neurons to visual stimulation may result in a decrease of feedforward response gain but an increase of functional activities from lateral and/or feedback connections, which could lead to a reduction in the effectiveness of adapted neurons in transmitting information to its driven neurons.

Sparse coding can predict primary visual cortex receptive field changes induced by abnormal visual input

Receptive fields acquired through unsupervised learning of sparse representations of natural scenes have similar properties to primary visual cortex (V1) simple cell receptive fields. However, what drives in vivo development of receptive fields remains controversial. The strongest evidence for the importance of sensory experience in visual development comes from receptive field changes in animals reared with abnormal visual input. However, most sparse coding accounts have considered only normal visual input and the development of monocular receptive fields. Here, we applied three sparse coding models to binocular receptive field development across six abnormal rearing conditions. In every condition, the changes in receptive field properties previously observed experimentally were matched to a similar and highly faithful degree by all the models, suggesting that early sensory development can indeed be understood in terms of an impetus towards sparsity. As previously predicted in the literature, we found that asymmetries in inter-ocular correlation across orientations lead to orientation-specific binocular receptive fields. Finally we used our models to design a novel stimulus that, if present during rearing, is predicted by the sparsity principle to lead robustly to radically abnormal receptive fields.

The responses of neurons in the primary visual cortex (V1), a region of the brain involved in encoding visual input, are modified by the visual experience of the animal during development. For example, most neurons in animals reared viewing stripes of a particular orientation only respond to the orientation that the animal experienced. The responses of V1 cells in normal animals are similar to responses that simple optimisation algorithms can learn when trained on images. However, whether the similarity between these algorithms and V1 responses is merely coincidental has been unclear. Here, we used the results of a number of experiments where animals were reared with modified visual experience to test the explanatory power of three related optimisation algorithms. We did this by filtering the images for the algorithms in ways that mimicked the visual experience of the animals. This allowed us to show that the changes in V1 responses in experiment were consistent with the algorithms. This is evidence that the precepts of the algorithms, notably sparsity, can be used to understand the development of V1 responses. Further, we used our model to propose a novel rearing condition which we expect to have a dramatic effect on development.

Top-down influences on visual processing

Re-entrant or feedback pathways between cortical areas carry rich and varied information about behavioural context, including attention, expectation, perceptual tasks, working memory and motor commands. Neurons receiving such inputs effectively function as adaptive processors that are able to assume different functional states according to the task being executed. Recent data suggest that the selection of particular inputs, representing different components of an association field, enable neurons to take on different functional roles. In this Review, we discuss the various top-down influences exerted on the visual cortical pathways and highlight the dynamic nature of the receptive field, which allows neurons to carry information that is relevant to the current perceptual demands.

A modulatory effect of the feedback from higher visual areas to V1 in the mouse

Using a mouse brain slice preparation, we studied the modulatory effects of a feedback projection from higher visual cortical areas, mostly or exclusively area LM (or V2), on two inputs to layer 4 cells in the first visual area (V1). The two inputs to these cells were geniculocortical and an unspecified intracortical input, possibly involving layer 6 cells. We found that activation of metabotropic glutamate receptors (mGluRs) from stimulation of the feedback projection reduced the evoked excitatory postsynaptic currents of both of these inputs to layer 4 but that this modulation acts in an input-specific way. Reducing the strength of the geniculocortical input in adults involved both presynaptic and postsynaptic group I mGluRs (although in younger animals presynaptic group II mGluRs were also involved), whereas modulation of the intracortical input acted entirely via postsynaptic group II mGluRs. These results demonstrate that one of the effects of this feedback pathway is to control the gain of geniculocortical transmission.

Cortical projections to the superior colliculus in tree shrews (Tupaia belangeri)

The visuomotor functions of the superior colliculus depend not only on direct inputs from the retina, but also on inputs from neocortex. As mammals vary in the areal organization of neocortex, and in the organization of the number of visual and visuomotor areas, patterns of corticotectal projections vary. Primates in particular have a large number of visual areas projecting to the superior colliculus. As tree shrews are close relatives of primates, and they are also highly visual, we studied the distribution of cortical neurons projecting to the superior colliculus by injecting anatomical tracers into the colliculus. Since projections from visuotopically organized visual areas are expected to match the visuotopy of the superior colliculus, injections at different retinotopic locations in the superior colliculus provide information about the locations and organization of topographic areas in extrastriate cortex. Small injections in the superior colliculus labeled neurons in locations within areas 17 (V1) and 18 (V2) that are consistent with the known topography of these areas and the superior colliculus. In addition, the separate locations of clusters of labeled cells in temporal visual cortex provide evidence for five or more topographically organized areas. Injections that included deeper layers of the superior colliculus also labeled neurons in medial frontal cortex, likely in premotor cortex. Only occasional labeled neurons were observed in somatosensory or auditory cortex. Regardless of tracer injection location, we found that, unlike primates, a substantial projection to the superior colliculus from posterior parietal cortex is not a characteristic of tree shrews.

Suppression of spontaneous activity before visual response in the primate V1 neurons during a visually guided saccade task

Visually guided saccadic eye movements are thought to involve multiple stages of processing in diverse brain structures including the primary visual cortex (V1). The variability of neural activity in each of these structures may present ambiguities for downstream stages in identifying sensory and motor signals among spontaneous discharges. The response time of saccadic eye movements made toward a visual target is correlated with the time of the first spikes in V1 that are evoked by the target (Lee et al., 2010). This suggests that downstream neurons receiving the output of V1 are faced with a challenging task of discriminating first spikes of visual response against spontaneous discharge. Here we report a novel response property of the macaque V1 neurons. Immediately before neurons discharge a burst of activity to a visual saccade target, spontaneous discharges were transiently suppressed. This suppression was maximal ∼18 ms after target onset. Based on simulations of artificial spike trains, we propose that the transient suppression enhances temporal contrast for identifying the onset of visual response by increasing the reliability of detection of response onset by downstream neurons, thereby facilitating visually guided behavioral responses.

Cytoarchitectonic mapping of the human dorsal extrastriate cortex

The dorsal visual stream consists of several functionally specialized areas, but most of their cytoarchitectonic correlates have not yet been identified in the human brain. The cortex adjacent to Brodmann area 18/V2 was therefore analyzed in serial sections of ten human post-mortem brains using morphometrical and multivariate statistical analyses for the definition of areal borders. Two previously unknown cytoarchitectonic areas (hOc3d, hOc4d) were detected. They occupy the medial and, to a smaller extent, lateral surface of the occipital lobe. The larger area, hOc3d, is located dorso-lateral to area V2 in the region of superior and transverse occipital, as well as parieto-occipital sulci. Area hOc4d was identified rostral to hOc3d; it differed from the latter by larger pyramidal cells in lower layer III, thinner layers V and VI, and a sharp cortex-white-matter borderline. The delineated areas were superimposed in the anatomical MNI space, and probabilistic maps were calculated. They show a relatively high intersubject variability in volume and position. Based on their location and neighborhood relationship, areas hOc3d and hOc4d are putative anatomical substrates of functionally defined areas V3d and V3a, a hypothesis that can now be tested by comparing probabilistic cytoarchitectonic maps and activation studies of the living human brain.

Genetic evidence that brain-derived neurotrophic factor mediates competitive interactions between individual cortical neurons

Brain-derived neurotrophic factor (BDNF) is a secreted protein important for development and function of neocortical circuitry. Although it is well established that BDNF contributes to the sculpting of dendrite structure and modulation of synapse strength, the range and directionality of BDNF signaling underlying these functions are incompletely understood. To gain insights into the role of BDNF at the level of individual neurons, we tested the cell-autonomous requirements for Bdnf in visual cortical layer 2/3 neurons. We found that the number of functional Bdnf alleles a neuron carries relative to the prevailing genotype determines its density of dendritic spines, the structures at which most excitatory synapses are made. This requirement for Bdnf exists both during postnatal development and in adulthood, suggesting that the amount of BDNF a neuron is capable of producing determines its success in ongoing competition in the environment of the neocortex. Our results suggest that BDNF may perform a long-sought function for a secreted growth factor in mediating the competitive events that shape individual neurons and their circuits.

Image sequence reactivation in awake V4 networks

In the absence of sensory input, neuronal networks are far from being silent. Whether spontaneous changes in ongoing activity reflect previous sensory experience or stochastic fluctuations in brain activity is not well understood. Here we describe reactivation of stimulus-evoked activity in awake visual cortical networks. We found that continuous exposure to randomly flashed image sequences induces reactivation in macaque V4 cortical networks in the absence of visual stimulation. This reactivation of previously evoked activity is stimulus-specific, occurs only in the same temporal order as the original response, and strengthens with increased stimulus exposures. Importantly, cells exhibiting significant reactivation carry more information about the stimulus than cells that do not reactivate. These results demonstrate a surprising degree of experience-dependent plasticity in visual cortical networks as a result of repeated exposure to unattended information. We suggest that awake reactivation in visual cortex may underlie perceptual learning by passive stimulus exposure.

Implicit and explicit contributions to object recognition: evidence from rapid perceptual learning

The present study investigated implicit and explicit recognition processes of rapidly perceptually learned objects by means of steady-state visual evoked potentials (SSVEP). Participants were initially exposed to object pictures within an incidental learning task (living/non-living categorization). Subsequently, degraded versions of some of these learned pictures were presented together with degraded versions of unlearned pictures and participants had to judge, whether they recognized an object or not. During this test phase, stimuli were presented at 15 Hz eliciting an SSVEP at the same frequency. Source localizations of SSVEP effects revealed for implicit and explicit processes overlapping activations in orbito-frontal and temporal regions. Correlates of explicit object recognition were additionally found in the superior parietal lobe. These findings are discussed to reflect facilitation of object-specific processing areas within the temporal lobe by an orbito-frontal top-down signal as proposed by bi-directional accounts of object recognition.

Determining the role of correlated firing in large populations of neurons using white noise and natural scene stimuli

The role of correlated firing in representing information has been a subject of much discussion. Several studies in retina, visual cortex, somatosensory cortex, and motor cortex, have suggested that it plays only a minor role, carrying <10% of the total information carried by the neurons (Gawne & Richmond, 1993; Nirenberg et al., 2001; Oram et al., 2001; Petersen, Panzeri, & Diamond, 2001; Rolls et al., 2003). A limiting factor of these studies, however, is that they were carried out using pairs of neurons; how the results extend to large populations was not clear. Recently, new methods for modeling network firing patterns have been developed (Nirenberg & Pandarinath, 2012; Pillow et al., 2008), opening the door to answering this question for more complete populations. One study, Pillow et al. (2008), showed that including correlations increased information by a modest amount, ~20%; however, this work used only a single retina (primate) and a white noise stimulus. Here we performed the analysis using several retinas (mouse) and both white noise and natural scene stimuli. The results showed that correlations added little information when white noise stimuli were used (~13%), similar to Pillow et al.'s findings, and essentially no information when natural scene stimuli were used. Further, the results showed that ignoring correlations did not change the quality of the information carried by the population (as measured by comparing the full pattern of decoding errors). These results suggest generalization: the pairwise analysis in several species show that correlations account for very little of the total information. Now, the analysis with large populations in two species show a similar result, that correlations still account for only a small fraction of the total information, and, most significantly, the amount is not statistically significant when natural stimuli are used, making rapid advances in the study of population coding possible.

Characterizing responses of translation-invariant neurons to natural stimuli: maximally informative invariant dimensions

The human visual system is capable of recognizing complex objects even when their appearances change drastically under various viewing conditions. Especially in the higher cortical areas, the sensory neurons reflect such functional capacity in their selectivity for complex visual features and invariance to certain object transformations, such as image translation. Due to the strong nonlinearities necessary to achieve both the selectivity and invariance, characterizing and predicting the response patterns of these neurons represents a formidable computational challenge. A related problem is that such neurons are poorly driven by randomized inputs, such as white noise, and respond strongly only to stimuli with complex high-order correlations, such as natural stimuli. Here we describe a novel two-step optimization technique that can characterize both the shape selectivity and the range and coarseness of position invariance from neural responses to natural stimuli. One step in the optimization is finding the template as the maximally informative dimension given the estimated spatial location where the response could have been triggered within each image. The estimates of the locations that triggered the response are updated in the next step. Under the assumption of a monotonic relationship between the firing rate and stimulus projections on the template at a given position, the most likely location is the one that has the largest projection on the estimate of the template. The algorithm shows quick convergence during optimization, and the estimation results are reliable even in the regime of small signal-to-noise ratios. When we apply the algorithm to responses of complex cells in the primary visual cortex (V1) to natural movies, we find that responses of the majority of cells were significantly better described by translation-invariant models based on one template compared with position-specific models with several relevant features.