Sound-driven synaptic inhibition in primary visual cortex

Multimodal objects and events activate many sensory cortical areas simultaneously. This is possibly reflected in reciprocal modulations of neuronal activity, even at the level of primary cortical areas. However, the synaptic character of these interareal interactions, and their impact on synaptic and behavioral sensory responses are unclear. Here, we found that activation of auditory cortex by a noise burst drove local GABAergic inhibition on supragranular pyramids of the mouse primary visual cortex, via cortico-cortical connections. This inhibition was generated by sound-driven excitation of a limited number of cells in infragranular visual cortical neurons. Consequently, visually driven synaptic and spike responses were reduced upon bimodal stimulation. Also, acoustic stimulation suppressed conditioned behavioral responses to a dim flash, an effect that was prevented by acute blockade of GABAergic transmission in visual cortex. Thus, auditory cortex activation by salient stimuli degrades potentially distracting sensory processing in visual cortex by recruiting local, translaminar, inhibitory circuits.     

Organization of the Connections between the Parietal Associative Zone and the Primary Sensory Zones in the Cat Neocortex

In acute experiments on cats, we studied the impulse activity of 262 neurons of the parietal associative zone (PAZ, field 5). Among them, 129 cells [100 silent units and 29 units generating background activity (BA)] were identified as output neurons, while 133 cells with the BA were interneurons of the intrinsic cortical neuronal circuits. Electrical stimulation of the primary visual, auditory, or somatosensory cortices evoked no impulse responses in silent output PAZ neurons, while output neurons with the BA and interneurons (more than 65 and 80% of the cell units, respectively) generated clear responses (more frequently, phasic). Stimulation of the auditory and visual cortices exerted mostly inhibitory effects, while stimulation of the somatosensory cortex provided mostly excitatory influences. The ratios of neurons generating primary excitatory and inhibitory responses to stimulation of the visual, auditory, and somatic cortices were 0.3:1, 0.6:1, and 3.2:1, respectively. More than 95% of the field-5 neurons were influenced from the primary sensory zones via di- and/or polysynaptic pathways. Monosynaptic excitatory inputs from the visual cortex were identified for 3.8% of interneurons and 6.9% of output PAZ neurons; for the auditory cortical inputs, the respective figures were 1.7 and 3.5%. Monosynaptic connections with the somatic cortex were found only for 4% of the interneurons under study. It has been concluded that interaction of heteromodal signals coming to the PAZ via the corticopetal and associative inputs occurs on neurons of all the cortical layers.     

Auditory cortex mapmaking: principles, projections, and plasticity

Maps of sensory receptor epithelia and computed features of the sensory environment are common elements of auditory, visual, and somatic sensory representations from the periphery to the cerebral cortex. Maps enhance the understanding of normal neural organization and its modification by pathology and experience. They underlie the derivation of the computational principles that govern sensory processing and the generation of perception. Despite their intuitive explanatory power, the functions of and rules for organizing maps and their plasticity are not well understood. Some puzzles of auditory cortical map organization are that few complete receptor maps are available and that even fewer computational maps are known beyond primary cortical areas. Neuroanatomical evidence suggests equally organized connectional patterns throughout the cortical hierarchy that might underlie map stability. Here, we consider the implications of auditory cortical map organization and its plasticity and evaluate the complementary role of maps in representation and computation from an auditory perspective.     

Long-range, pattern-dependent contextual effects in early human visual cortex

The standard view of neurons in early visual cortex is that they behave like localized feature detectors. Here we demonstrate that processing in early visual areas goes beyond feature detection by showing that neural responses are greater when a feature deviates from its context compared to when it does not deviate from its context. Using psychophysics, fMRI, and electroencephalography methodologies, we measured neural responses to an oriented Gabor ("target") embedded in various visual patterns as defined by the relative orientation of flanking stimuli. We first show using psychophysical contrast adaptation and fMRI that a target that differs from its context results in more neural activity compared to a target that is contained within an alternating sequence, suggesting that neurons in early visual cortex are sensitive to large-scale orientation patterns. Next, we use event-related potentials to show that orientation deviations affect the earliest sensory components of the target response. Finally, we use forced-choice classification of "noise" stimuli to show that we are more likely to "see" orientations that deviate from the context. Our results suggest that early visual cortex is sensitive to global patterns in images in a way that is markedly different from the predictions of standard models of cortical visual processing.     

Negative BOLD differentiates visual imagery and perception

Recent studies emphasize the overlap between the neural substrates of visual perception and visual imagery. However, the subjective experiences of imagining and seeing are clearly different. Here we demonstrate that deactivation of auditory cortex (and to some extent of somatosensory and subcortical visual structures) as measured by BOLD functional magnetic resonance imaging unequivocally differentiates visual imagery from visual perception. During visual imagery, auditory cortex deactivation negatively correlates with activation in visual cortex and with the score in the subjective vividness of visual imagery questionnaire (VVIQ). Perception of the world requires the merging of multisensory information so that, during seeing, information from other sensory systems modifies visual cortical activity and shapes experience. We suggest that pure visual imagery corresponds to the isolated activation of visual cortical areas with concurrent deactivation of "irrelevant" sensory processing that could disrupt the image created by our "mind's eye."     

Integrating information from different senses in the auditory cortex

Multisensory integration was once thought to be the domain of brain areas high in the cortical hierarchy, with early sensory cortical fields devoted to unisensory processing of inputs from their given set of sensory receptors. More recently, a wealth of evidence documenting visual and somatosensory responses in auditory cortex, even as early as the primary fields, has changed this view of cortical processing. These multisensory inputs may serve to enhance responses to sounds that are accompanied by other sensory cues, effectively making them easier to hear, but may also act more selectively to shape the receptive field properties of auditory cortical neurons to the location or identity of these events. We discuss the new, converging evidence that multiplexing of neural signals may play a key role in informatively encoding and integrating signals in auditory cortex across multiple sensory modalities. We highlight some of the many open research questions that exist about the neural mechanisms that give rise to multisensory integration in auditory cortex, which should be addressed in future experimental and theoretical studies.     

Auditory filters, features, and redundant representations

Responses in auditory cortex tend to be weaker, more phasic, and noisier than those of auditory brainstem and midbrain nuclei. Is the activity in cortex therefore merely a "degraded echo" of lower-level neural representations? In this issue of Neuron, Chechik and colleagues show that, while cortical responses indeed convey less sensory information than auditory midbrain neurons, their responses are also much less redundant.     

Response variability in the mammalian auditory cortex: an objection to feature detection?

Research strategy in the auditory system has tended to parallel that in the visual system, where neurons have been shown to respond selectively to specific stimulus parameters. Auditory neurons have been shown to be sensitive to changes in acoustic parameters, but only rarely have neurons been reported that respond exclusively to only one biologically significant sound. Even at higher levels of the auditory system very few cells have been found that could be described as "vocalization detectors." In addition, variability in responses to artificial sounds have been reported for auditory cortical neurons similar to the response variability that has been reported in the visual system. Recent evidence indicates that the responses of auditory cortical neurons to species-specific vocalizations can also be labile, varying in both strength and selectivity. This is especially true of the secondary auditory cortex. This variability, coupled with the lack of extreme specificity in the secondary auditory cortex, suggests that secondary cortical neurons are not well suited for the role of "vocalization detectors."     

AIM: A network model of attention in auditory cortex

Attentional modulation of cortical networks is critical for the cognitive flexibility required to process complex scenes. Current theoretical frameworks for attention are based almost exclusively on studies in visual cortex, where attentional effects are typically modest and excitatory. In contrast, attentional effects in auditory cortex can be large and suppressive. A theoretical framework for explaining attentional effects in auditory cortex is lacking, preventing a broader understanding of cortical mechanisms underlying attention. Here, we present a cortical network model of attention in primary auditory cortex (A1). A key mechanism in our network is attentional inhibitory modulation (AIM) of cortical inhibitory neurons. In this mechanism, top-down inhibitory neurons disinhibit bottom-up cortical circuits, a prominent circuit motif observed in sensory cortex. Our results reveal that the same underlying mechanisms in the AIM network can explain diverse attentional effects on both spatial and frequency tuning in A1. We find that a dominant effect of disinhibition on cortical tuning is suppressive, consistent with experimental observations. Functionally, the AIM network may play a key role in solving the cocktail party problem. We demonstrate how attention can guide the AIM network to monitor an acoustic scene, select a specific target, or switch to a different target, providing flexible outputs for solving the cocktail party problem.     

Constructing Noise-Invariant Representations of Sound in the Auditory Pathway

Identifying behaviorally relevant sounds in the presence of background noise is one of the most important and poorly understood challenges faced by the auditory system. An elegant solution to this problem would be for the auditory system to represent sounds in a noise-invariant fashion. Since a major effect of background noise is to alter the statistics of the sounds reaching the ear, noise-invariant representations could be promoted by neurons adapting to stimulus statistics. Here we investigated the extent of neuronal adaptation to the mean and contrast of auditory stimulation as one ascends the auditory pathway. We measured these forms of adaptation by presenting complex synthetic and natural sounds, recording neuronal responses in the inferior colliculus and primary fields of the auditory cortex of anaesthetized ferrets, and comparing these responses with a sophisticated model of the auditory nerve. We find that the strength of both forms of adaptation increases as one ascends the auditory pathway. To investigate whether this adaptation to stimulus statistics contributes to the construction of noise-invariant sound representations, we also presented complex, natural sounds embedded in stationary noise, and used a decoding approach to assess the noise tolerance of the neuronal population code. We find that the code for complex sounds in the periphery is affected more by the addition of noise than the cortical code. We also find that noise tolerance is correlated with adaptation to stimulus statistics, so that populations that show the strongest adaptation to stimulus statistics are also the most noise-tolerant. This suggests that the increase in adaptation to sound statistics from auditory nerve to midbrain to cortex is an important stage in the construction of noise-invariant sound representations in the higher auditory brain.     

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons'' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.     

Comparison of Neural Responses to Cat Meows and Human Vowels in the Anterior and Posterior Auditory Field of Awake Cats

For humans and animals, the ability to discriminate speech and conspecific vocalizations is an important physiological assignment of the auditory system. To reveal the underlying neural mechanism, many electrophysiological studies have investigated the neural responses of the auditory cortex to conspecific vocalizations in monkeys. The data suggest that vocalizations may be hierarchically processed along an anterior/ventral stream from the primary auditory cortex (A1) to the ventral prefrontal cortex. To date, the organization of vocalization processing has not been well investigated in the auditory cortex of other mammals. In this study, we examined the spike activities of single neurons in two early auditory cortical regions with different anteroposterior locations: anterior auditory field (AAF) and posterior auditory field (PAF) in awake cats, as the animals were passively listening to forward and backward conspecific calls (meows) and human vowels. We found that the neural response patterns in PAF were more complex and had longer latency than those in AAF. The selectivity for different vocalizations based on the mean firing rate was low in both AAF and PAF, and not significantly different between them; however, more vocalization information was transmitted when the temporal response profiles were considered, and the maximum transmitted information by PAF neurons was higher than that by AAF neurons. Discrimination accuracy based on the activities of an ensemble of PAF neurons was also better than that of AAF neurons. Our results suggest that AAF and PAF are similar with regard to which vocalizations they represent but differ in the way they represent these vocalizations, and there may be a complex processing stream between them.     

弱背景噪声对大鼠听皮层神经元频率调谐的影响

在自然环境中,人和动物常在一定的背景噪声下感知信号声刺激,然而,关于低强度的弱背景噪声如何影响听皮层神经元对声刺激频率的编码尚不清楚.本研究以大鼠听皮层神经元的频率反应域为研究对象,测定了阈下背景噪声对79个神经元频率反应域的影响.结果表明,弱背景噪声对大鼠初级听皮层神经元的听反应既有抑制性影响、又有易化性影响.一般来说,抑制性影响使神经元的频率调谐范围和最佳频率反应域缩小,易化性影响使神经元的频率调谐范围和最佳频率反应域增大.对于少数神经元,弱背景噪声并未显著改变其频率调谐范围,但却改变了其最佳频率反应域范围.弱背景噪声对63.64%神经元的特征频率和55.84%神经元的最低阈值无显著影响.神经元频率调谐曲线的尖部比中部更容易受到弱背景噪声的影响.该研究结果有助于我们进一步理解复杂声环境下大脑听皮层对听觉信息的编码机制.     

Prior expectations evoke stimulus-specific activity in the deep layers of the primary visual cortex

The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex.

The way we perceive the world is strongly influenced by our expectations, but the neural circuitry through which the brain achieves this remains unknown. A study using ultra-high field fMRI reveals that prior expectations evoke stimulus-specific signals in the deep layers of the primary visual cortex.     

Separate modulations of human V1 associated with spatial attention and task structure

Functional magnetic resonance imaging (fMRI) was used while normal human volunteers engaged in simple detection and discrimination tasks, revealing separable modulations of early visual cortex associated with spatial attention and task structure. Both modulations occur even when there is no change in sensory stimulation. The modulation due to spatial attention is present throughout the early visual areas V1, V2, V3, and VP, and varies with the attended location. The task structure activations are strongest in V1 and are greater in regions that represent more peripheral parts of the visual field. Control experiments demonstrate that the task structure activations cannot be attributed to visual, auditory, or somatosensory processing, the motor response for the detection/discrimination judgment, or oculomotor responses such as blinks or saccades. These findings demonstrate that early visual areas are modulated by at least two types of endogenous signals, each with distinct cortical distributions.     

A computational framework for topographies of cortical areas

Self-organizing feature maps (SOFMs) represent a dimensionality-reduction algorithm that has been used to replicate feature topographies observed experimentally in primary visual cortex (V1). We used the SOFM algorithm to model possible topographies of generic sensory cortical areas containing up to five arbitrary physiological features. This study explored the conditions under which these multi-feature SOFMs contained two features that were mapped monotonically and aligned orthogonally with one another (i.e., “globally orthogonal”), as well as the conditions under which the map of one feature aligned with the longest anatomical dimension of the modeled cortical area (i.e., “dominant”). In a single SOFM with more than two features, we never observed more than one dominant feature, nor did we observe two globally orthogonal features in the same map in which a dominant feature occurred. Whether dominance or global orthogonality occurred depended upon how heavily weighted the features were relative to one another. The most heavily weighted features are likely to correspond to those physical stimulus properties transduced directly by the sensory epithelium of a particular sensory modality. Our results imply, therefore, that in the primary cortical area of sensory modalities with a two-dimensional sensory epithelium, these two features are likely to be organized globally orthogonally to one another, and neither feature is likely to be dominant. In the primary cortical area of sensory modalities with a one-dimensional sensory epithelium, however, this feature is likely to be dominant, and no two features are likely to be organized globally orthogonally to one another. Because the auditory system transduces a single stimulus feature (i.e., frequency) along the entire length of the cochlea, these findings may have particular relevance for topographic maps of primary auditory cortex. This research was supported by The McDonnell Center for Higher Brain Function, The Wallace H. Coulter Foundation and NIH grant DC008880.     

Failed Stabilization for Long-Term Potentiation in the Auditory Cortex of Fmr1 Knockout Mice

Fragile X syndrome is a developmental disorder that affects sensory systems. A null mutation of the Fragile X Mental Retardation protein 1 (Fmr1) gene in mice has varied effects on developmental plasticity in different sensory systems, including normal barrel cortical plasticity, altered ocular dominance plasticity and grossly impaired auditory frequency map plasticity. The mutation also has different effects on long-term synaptic plasticity in somatosensory and visual cortical neurons, providing insights on how it may differentially affect the sensory systems. Here we present evidence that long-term potentiation (LTP) is impaired in the developing auditory cortex of the Fmr1 knockout (KO) mice. This impairment of synaptic plasticity is consistent with impaired frequency map plasticity in the Fmr1 KO mouse. Together, these results suggest a potential role of LTP in sensory map plasticity during early sensory development.     

Parvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli

The response of cortical neurons to a sensory stimulus is shaped by the network in which they are embedded. Here we establish a role of parvalbumin (PV)-expressing cells, a large class of inhibitory neurons that target the soma and perisomatic compartments of pyramidal cells, in controlling cortical responses. By bidirectionally manipulating PV cell activity in visual cortex we show that these neurons strongly modulate layer 2/3 pyramidal cell spiking responses to visual stimuli while only modestly affecting their tuning properties. PV cells' impact on pyramidal cells is captured by a linear transformation, both additive and multiplicative, with a threshold. These results indicate that PV cells are ideally suited to modulate cortical gain and establish a causal relationship between a select neuron type and specific computations performed by the cortex during sensory processing.     

A Synchrony-Dependent Influence of Sounds on Activity in Visual Cortex Measured Using Functional Near-Infrared Spectroscopy (fNIRS)

Evidence from human neuroimaging and animal electrophysiological studies suggests that signals from different sensory modalities interact early in cortical processing, including in primary sensory cortices. The present study aimed to test whether functional near-infrared spectroscopy (fNIRS), an emerging, non-invasive neuroimaging technique, is capable of measuring such multisensory interactions. Specifically, we tested for a modulatory influence of sounds on activity in visual cortex, while varying the temporal synchrony between trains of transient auditory and visual events. Related fMRI studies have consistently reported enhanced activation in response to synchronous compared to asynchronous audiovisual stimulation. Unexpectedly, we found that synchronous sounds significantly reduced the fNIRS response from visual cortex, compared both to asynchronous sounds and to a visual-only baseline. It is possible that this suppressive effect of synchronous sounds reflects the use of an efficacious visual stimulus, chosen for consistency with previous fNIRS studies. Discrepant results may also be explained by differences between studies in how attention was deployed to the auditory and visual modalities. The presence and relative timing of sounds did not significantly affect performance in a simultaneously conducted behavioral task, although the data were suggestive of a positive relationship between the strength of the fNIRS response from visual cortex and the accuracy of visual target detection. Overall, the present findings indicate that fNIRS is capable of measuring multisensory cortical interactions. In multisensory research, fNIRS can offer complementary information to the more established neuroimaging modalities, and may prove advantageous for testing in naturalistic environments and with infant and clinical populations.     

Primary auditory cortex of cats: feature detection or something else?

Neurons in sensory cortices are often assumed to be feature detectors, computing simple and then successively more complex features out of the incoming sensory stream. These features are somehow integrated into percepts. Despite many years of research, a convincing candidate for such a feature in primary auditory cortex has not been found. We argue that feature detection is actually a secondary issue in understanding the role of primary auditory cortex. Instead, the major contribution of primary auditory cortex to auditory perception is in processing previously derived features on a number of different timescales. We hypothesize that, as a result, neurons in primary auditory cortex represent sounds in terms of auditory objects rather than in terms of feature maps. According to this hypothesis, primary auditory cortex has a pivotal role in the auditory system in that it generates the representation of auditory objects to which higher auditory centers assign properties such as spatial location, source identity, and meaning.Abbreviations A1 primary auditory cortex - MGB medical geniculate body - IC inferior coliculus - STRF spectrotemporal receptive field