Representation of visual stimuli in inferior temporal cortex.

In primates, inferior temporal (IT) cortex is crucial for the processing and storage of visual information about form and colour. This article reviews the properties of IT neurons and considers how these properties may underlie the perceptual and mnemonic functions of IT cortex. The available evidence suggests that the processing of the facial image by IT cortex is similar to its processing of other visual patterns. Faces and other complex visual stimuli appear to be represented by the pattern of responses over a population of IT neurons rather than by the responses of specific 'feature detectors' or 'grandmother' cells. IT neurons with adult-like stimulus properties are present in monkeys as young as six weeks old.     

Active maintenance of associative mnemonic signal in monkey inferior temporal cortex

We investigated the contribution of the inferior temporal (IT) cortical neurons to the active maintenance of internal representations. The activity of single neurons in the IT cortex was recorded while the monkeys performed a sequential-type associative memory task in which distractor stimuli interrupted the delay epoch between the cue and target (paired-associate) stimuli. For each neuron, information about each stimulus conveyed by the delay activity was estimated as a coefficient of multiple regression analysis. We found that target information derived from long-term memory (LTM) persisted despite the distractors. By contrast, cue information derived from the visual system was attenuated and frequently replaced by distractor information. These results suggest that LTM-derived information required for upcoming behavior is actively maintained in the IT neurons, whereas visually derived information tends to be updated irrespective of behavioral relevance.     

Neurophysiological mechanisms underlying face processing within and beyond the temporal cortical visual areas.

The ways in which information about faces is represented and stored in the temporal lobe visual areas of primates, as shown by recordings from single neurons in macaques, are considered. Some neurons that respond primarily to faces are found in the cortex in the anterior part of the superior temporal sulcus (in which neurons are especially likely to be tuned to facial expression and to face movement involved in gesture), and in the TE areas more ventrally forming the inferior temporal gyrus (in which neurons are more likely to have responses related to the identity of faces). Quantitative studies of the responses of the neurons that respond differently to the faces of different individuals show that information about the identity of the individual is represented by the responses of a population of neurons, that is, ensemble encoding rather than 'grandmother cell' encoding is used. It is argued that this type of tuning is a delicate compromise between very fine tuning, which has the advantage of low interference in neuronal network operations but the disadvantage of losing the useful properties (such as generalization, completion and graceful degradation) of storage in neuronal networks, and broad tuning, which has the advantage of allowing these properties of neuronal networks to be realized but the disadvantage of leading to interference between the different memories stored in an associative network. There is evidence that the responses of some of these neurons are altered by experience so that new stimuli become incorporated in the network. It is shown that the representation that is built in temporal cortical areas shows considerable invariance for size, contrast, spatial frequency and translation. Thus the representation is in a form which is particularly useful for storage and as an output from the visual system. It is also shown that one of the representations that is built is object based, which is suitable for recognition and as an input to associative memory, and that another is viewer centred, which is appropriate for conveying information about gesture. Ways are considered in which such cortical representations might be built by competitive self-organization aided by back projections in the multi-stage cortical processing hierarchy which has convergence from stage to stage.     

The role of the posterior parietal cortex in coordinate transformations for visual-motor integration

Lesion to the posterior parietal cortex in monkeys and humans produces spatial deficits in movement and perception. In recording experiments from area 7a, a cortical subdivision in the posterior parietal cortex in monkeys, we have found neurons whose responses are a function of both the retinal location of visual stimuli and the position of the eyes in the orbits. By combining these signals area 7 a neurons code the location of visual stimuli with respect to the head. However, these cells respond over only limited ranges of eye positions (eye-position-dependent coding). To code location in craniotopic space at all eye positions (eye-position-independent coding) an additional step in neural processing is required that uses information distributed across populations of area 7a neurons. We describe here a neural network model, based on back-propagation learning, that both demonstrates how spatial location could be derived from the population response of area 7a neurons and accurately accounts for the observed response properties of these neurons.     

Bayesian inference in populations of cortical neurons: a model of motion integration and segmentation in area MT

A major issue in cortical physiology and computational neuroscience is understanding the interaction between extrinsic signals from feedforward connections and intracortical signals from lateral connections. We propose here a computational model for motion perception based on the assumption that the local cortical circuits in the medio-temporal area (area MT) implement a Bayesian inference principle. This approach establishes a functional balance between feedforward and lateral, excitatory and inhibitory, inputs. The model reproduces most of the known properties of the neurons in area MT in response to moving stimuli. It accounts for important motion perception phenomena including motion transparency, spatial and temporal integration/segmentation. While integrating several properties of previously proposed models, it makes specific testable predictions concerning, in particular, temporal properties of neurons and the architecture of lateral connections in area MT. In addition, the proposed mechanism is consistent with the known properties of local cortical circuits in area V1. This suggests that Bayesian inference may be a general feature of information processing in cortical neuron populations. Received: 3 December 1997 / Accepted in revised form: 21 July 1998     

The neuropsychology of face perception: beyond simple dissociations and functional selectivity

Face processing relies on a distributed, patchy network of cortical regions in the temporal and frontal lobes that respond disproportionately to face stimuli, other cortical regions that are not even primarily visual (such as somatosensory cortex), and subcortical structures such as the amygdala. Higher-level face perception abilities, such as judging identity, emotion and trustworthiness, appear to rely on an intact face-processing network that includes the occipital face area (OFA), whereas lower-level face categorization abilities, such as discriminating faces from objects, can be achieved without OFA, perhaps via the direct connections to the fusiform face area (FFA) from several extrastriate cortical areas. Some lesion, transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) findings argue against a strict feed-forward hierarchical model of face perception, in which the OFA is the principal and common source of input for other visual and non-visual cortical regions involved in face perception, including the FFA, face-selective superior temporal sulcus and somatosensory cortex. Instead, these findings point to a more interactive model in which higher-level face perception abilities depend on the interplay between several functionally and anatomically distinct neural regions. Furthermore, the nature of these interactions may depend on the particular demands of the task. We review the lesion and TMS literature on this topic and highlight the dynamic and distributed nature of face processing.     

Parallel processing in the honeybee olfactory pathway: structure, function, and evolution

Animals face highly complex and dynamic olfactory stimuli in their natural environments, which require fast and reliable olfactory processing. Parallel processing is a common principle of sensory systems supporting this task, for example in visual and auditory systems, but its role in olfaction remained unclear. Studies in the honeybee focused on a dual olfactory pathway. Two sets of projection neurons connect glomeruli in two antennal-lobe hemilobes via lateral and medial tracts in opposite sequence with the mushroom bodies and lateral horn. Comparative studies suggest that this dual-tract circuit represents a unique adaptation in Hymenoptera. Imaging studies indicate that glomeruli in both hemilobes receive redundant sensory input. Recent simultaneous multi-unit recordings from projection neurons of both tracts revealed widely overlapping response profiles strongly indicating parallel olfactory processing. Whereas lateral-tract neurons respond fast with broad (generalistic) profiles, medial-tract neurons are odorant specific and respond slower. In analogy to “what-” and “where” subsystems in visual pathways, this suggests two parallel olfactory subsystems providing “what-” (quality) and “when” (temporal) information. Temporal response properties may support across-tract coincidence coding in higher centers. Parallel olfactory processing likely enhances perception of complex odorant mixtures to decode the diverse and dynamic olfactory world of a social insect.     

The inferior temporal cortex: Architecture, computation, and representation

Neurons in the inferior temporal cortex (IT), an area crucially involved in visual object recognition in monkeys, show the visual response properties and anatomical/chemical nature which are distinct from those in the cortical areas that feed visual inputs to the IT. Earlier physiological studies showed that IT neurons have large receptive fields covering the center and contralateral (often bilateral) visual fields, stimulus selectivity for images of complex objects or shapes, and translation invariance of the stimulus selectivity. Recent studies have revealed new aspects of their properties such as invariant selectivity for shapes despite drastic changes in various physical attributes of stimuli, latent excitatory inputs masked by stimulus-specific GABAergic inhibition, selectivity for binocular disparity and 3-dimensional surface structures, profound effects of learning on the stimulus selectivity, and columnar clustering of neurons with similarstimulus selectivity for shapes and other object features. Another line of research using histological techniques have revealed that pyramidal neurons in the IT are larger in the size of dendritic arbors, in the number of dendritic branches and spines, and in the size and distribution of horizontal axonal arbors than those in the earlier areas, allowing them to integrate a larger population of afferents and process more diverse inputs. The concentration of several neurochemicals including those related to synaptic transmission or plasticity changes systematically towards the IT along the occipitotemporal pathway. Many of the characteristics of IT neurons parallel or explain certain aspects of visual object perception, although the behavioral relevance has yet to be addressed experimentally.     

A multi-stage model for fundamental functional properties in primary visual cortex

Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. We here define a model that accounts for many of the empirical observations concerning direction selectivity. The model describes a single column of cat primary visual cortex and comprises a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small (～4 ms) interval, and it is this difference that confers direction selectivity on model neurons. We show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex.     

Information in the Neuronal Representation of Individual Stimuli in the Primate Temporal Visual Cortex

To analyze the information provided about individual visual stimuliin the responses of single neurons in the primate temporal lobevisual cortex, neuronal responses to a set of 65 visual stimuli wererecorded in macaques performing a visual fixation task and analyzedusing information theoretical measures. The population of neuronsanalyzed responded primarily to faces. The stimuli included 23 facesand 42 nonface images of real-world scenes, so that the function ofthis brain region could be analyzed when it was processing relativelynatural scenes.It was found that for the majority of the neurons significantamounts of information were reflected about which of several of the23 faces had been seen. Thus the representation was not local, forin a local representation almost all the information available canbe obtained when the single stimulus to which the neuron respondsbest is shown. It is shown that the information available about anyone stimulus depended on how different (for example, how manystandard deviations) the response to that stimulus was from theaverage response to all stimuli. This was the case for responsesbelow the average response as well as above.It is shown that the fraction of information carried by the lowfiring rates of a cell was large—much larger than that carried bythe high firing rates. Part of the reason for this is that theprobability distribution of different firing rates is biased towardlow values (though with fewer very low values than would bepredicted by an exponential distribution). Another factor is thatthe variability of the response is large at intermediate and highfiring rates.Another finding is that at short sampling intervals (such as 20 ms)the neurons code information efficiently, by effectively acting asbinary variables and behaving less noisily than would be expectedof a Poisson process.     

Multiple topological representation self-organized by spike-timing-dependent synaptic learning rule

Position-and-scale-free representations of shapes are acquired by neurons in the inferior temporal (IT) cortex. So each neuron receives information from the whole visual field. Familiar shapes are extremely restricted from all the possible shapes on the whole visual field. So they must be clustered in the shape space to have mixed structure of continuity and discreteness. We demonstrate that multiple representation can be acquired in a spike-based model for topological maps based on the spike-timing-dependent synaptic plasticity (STDP), subjected to a set of inputs on multiple rings, which is a simple example of mixed structure. In this representation, the position on each ring is represented by a center of active neurons and the difference of rings is represented by a detailed pattern of active neurons. Neurons in the same region exhibit high activities for an input on the other ring. The result is consistent with the fact observed in IT cortex that neighboring neurons exhibit different preferences while the region of active neurons is continuously shifted for continuous changes of object.     

综述: 初级视皮层的亮度信息加工

亮度(luminance)是最基本的视觉信息.与其他视觉特征相比,由于视神经元对亮度刺激的反应较弱,并且许多神经元对均匀亮度无反应,对亮度信息编码的神经机制知之甚少.初级视皮层部分神经元对亮度的反应要慢于对比度反应,被认为是由边界对比度诱导的亮度知觉(brightness)的神经基础.我们的研究表明,初级视皮层许多神经元的亮度反应要快于对比度反应,并且这些神经元偏好低的空间频率、高的时间频率和高的运动速度,提示皮层下具有低空间频率和高运动速度通路的信息输入对产生初级视皮层神经元的亮度反应有贡献.已经知道初级视皮层神经元对空间频率反应的时间过程是从低空间频率到高空间频率,我们发现的早期亮度反应是对极低空间频率的反应,与这一时间过程是一致的,是这一从粗到细的视觉信息加工过程的第一步,揭示了处理最早的粗的视觉信息的神经基础.另外,初级视皮层含有偏好亮度下降和高运动速度的神经元,这群神经元的活动有助于在光照差的环境中检测高速运动的低亮度物体.     

Imagine Jane and identify John: face identity aftereffects induced by imagined faces

It is not known whether prolonged exposure to perceived and imagined complex visual images produces similar shifts in subsequent perception through selective adaptation. This question is important because a positive finding would suggest that perception and imagery of visual stimuli are mediated by shared neural networks. In this study, we used a selective adaptation procedure designed to induce high-level face-identity aftereffects--a phenomenon in which extended exposure to a particular face facilitates recognition of subsequent faces with opposite features while impairing recognition of all other faces. We report here that adaptation to either real or imagined faces produces a similar shift in perception and that identity boundaries represented in real and imagined faces are equivalent. Together, our results show that identity information contained in imagined and real faces produce similar behavioral outcomes. Our findings of high-level visual aftereffects induced by imagined stimuli can be taken as evidence for the involvement of shared neural networks that mediate perception and imagery of complex visual stimuli.     

Columnar Connectivity and Laminar Processing in Cat Primary Auditory Cortex

Background

Radial intra- and interlaminar connections form a basic microcircuit in primary auditory cortex (AI) that extracts acoustic information and distributes it to cortical and subcortical networks. Though the structure of this microcircuit is known, we do not know how the functional connectivity between layers relates to laminar processing.

Methodology/Principal Findings

We studied the relationships between functional connectivity and receptive field properties in this columnar microcircuit by simultaneously recording from single neurons in cat AI in response to broadband dynamic moving ripple stimuli. We used spectrotemporal receptive fields (STRFs) to estimate the relationship between receptive field parameters and the functional connectivity between pairs of neurons. Interlaminar connectivity obtained through cross-covariance analysis reflected a consistent pattern of information flow from thalamic input layers to cortical output layers. Connection strength and STRF similarity were greatest for intralaminar neuron pairs and in supragranular layers and weaker for interlaminar projections. Interlaminar connection strength co-varied with several STRF parameters: feature selectivity, phase locking to the stimulus envelope, best temporal modulation frequency, and best spectral modulation frequency. Connectivity properties and receptive field relationships differed for vertical and horizontal connections.

Conclusions/Significance

Thus, the mode of local processing in supragranular layers differs from that in infragranular layers. Therefore, specific connectivity patterns in the auditory cortex shape the flow of information and constrain how spectrotemporal processing transformations progress in the canonical columnar auditory microcircuit.     

Backward signal from medial temporal lobe in neural circuit reorganization of primate inferotemporal cortex

Neuropsychological theories proposed a critical role of the interaction between the medial temporal lobe and neocortex in the formation of long-term memory for facts and events, which has often been tested by learning of a series of paired words or figures in humans. We identify neural mechanisms of this long-term memory formation process by single-unit recording and molecular biological methods in an animal model of visual pair-association task in monkeys. In our previous studies, we found a group of neurons that manifested selective responses to both of the paired associates (pair-coding neuron) in the anterior inferior temporal (IT) cortex. It provides strong evidence that single IT neurons acquire the response-selectivity through associative learning, and suggests that the reorganized neural circuits for the pair-coding neurons serve as the memory engram of the pair-association learning. In this article, we investigated further mechanisms of the neural circuit reorganization. First, we tested the role of the backward connections from the medial temporal lobe to IT cortex. lbotenic acid was injected unilaterally into the entorhinal and perirhinal cortex which provided massive backward projections ipsilaterally to IT cortex. We found that the limbic lesion disrupted the associative code of the IT neurons between the paired associates, without impairing the visual response to each stimulus. Second, we ask why the limbic-neocortical interactions are so important. We hypothesize that limbic neurons would undergo rapid modification of synaptic connectivity and provide backward signals that guide reorganization of neocortical neural circuits. We then investigated the molecular basis of such rapid synaptic modifiability by detecting the expression of immediate-early genes. We found strong expression of zif268 during the learning of a new set of paired associates, most intensively in area 36 of the perirhinal cortex. All these results with visual pair-association task support our hypothesis, and demonstrate that the ‘consolidation’ process, which was first proposed on the basis of clinico-psychological evidence, can now be examined in the primate with neurophysiolocical and molecular biological approaches.     

Decoding Face Information in Time,Frequency and Space from Direct Intracranial Recordings of the Human Brain

Faces are processed by a neural system with distributed anatomical components, but the roles of these components remain unclear. A dominant theory of face perception postulates independent representations of invariant aspects of faces (e.g., identity) in ventral temporal cortex including the fusiform gyrus, and changeable aspects of faces (e.g., emotion) in lateral temporal cortex including the superior temporal sulcus. Here we recorded neuronal activity directly from the cortical surface in 9 neurosurgical subjects undergoing epilepsy monitoring while they viewed static and dynamic facial expressions. Applying novel decoding analyses to the power spectrogram of electrocorticograms (ECoG) from over 100 contacts in ventral and lateral temporal cortex, we found better representation of both invariant and changeable aspects of faces in ventral than lateral temporal cortex. Critical information for discriminating faces from geometric patterns was carried by power modulations between 50 to 150 Hz. For both static and dynamic face stimuli, we obtained a higher decoding performance in ventral than lateral temporal cortex. For discriminating fearful from happy expressions, critical information was carried by power modulation between 60–150 Hz and below 30 Hz, and again better decoded in ventral than lateral temporal cortex. Task-relevant attention improved decoding accuracy more than10% across a wide frequency range in ventral but not at all in lateral temporal cortex. Spatial searchlight decoding showed that decoding performance was highest around the middle fusiform gyrus. Finally, we found that the right hemisphere, in general, showed superior decoding to the left hemisphere. Taken together, our results challenge the dominant model for independent face representation of invariant and changeable aspects: information about both face attributes was better decoded from a single region in the middle fusiform gyrus.     

Dynamic Spatial Organization of Receptive Fields of Neurons in the 21a Cortical Area

We studied changes in the spatial parameters of receptive fields (RFs) of visually sensitive neurons in the associative area 21a of the cat cortex under conditions of presentation of moving visual stimuli. The results of experiments demonstrated that these parameters are dynamic and depend, from many aspects, on the pattern of the stimulus used for their estimation. Angular lengths of the horizontal and vertical axes of the RFs measured in the case of movement of the visual stimuli exceeded many times those determined by presentation of stationary blinking stimuli. As is supposed, a visual stimulus, when moving along the field of vision, activates a certain number of the neurons synaptically connected with the examined cell and possessing RFs localized along the movement trajectory. As a result, such integrated activity of the neuronal group can change the excitation threshold and discharge frequency of the studied neuron. It seems probable that correlated directed activation of the neuronal groups represents a significant neurophysiological mechanism providing dynamic modifications of the RF parameters of visually sensitive neurons in the course of processes of visual perception and identification of moving objects within the field of vision.     

Nonlinear visuoauditory integration in the mouse superior colliculus

Sensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.     

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 Network Model of Motion Processing in Area MT of Primates

A simple and biologically plausible model is proposed to simulatethe visual motion processing taking place in the middle temporal (MT) areaof the visual cortex in the primate brain. The model is ahierarchical neural network composed of multiple competitive learninglayers. The input layer of the network simulates the neurons in the primaryvisual cortex (V1), which are sensitive to the orientation and motionvelocity of the visual stimuli, and the middle and output layers of thenetwork simulate the component MT and pattern MT neurons, which areselectively responsive to local and global motions, respectively. Thenetwork model was tested with various simulated motion patterns (random dotsof different direction correlations, transparent motion, grating and plaidpatterns, and so on). The response properties of the model closely resemblemany of the known features of the MT neurons found neurophysiologically.These results show that the sophisticated response behaviors of the MTneurons can emerge naturally from some very simple models, such as acompetitive learning network.