Spike-timing-dependent synaptic modification induced by natural spike trains

The strength of the connection between two neurons can be modified by activity, in a way that depends on the timing of neuronal firing on either side of the synapse. This spike-timing-dependent plasticity (STDP) has been studied by systematically varying the intervals between pre- and postsynaptic spikes. Here we studied how STDP operates in the context of more natural spike trains. We found that in visual cortical slices the contribution of each pre-/postsynaptic spike pair to synaptic modification depends not only on the interval between the pair, but also on the timing of preceding spikes. The efficacy of each spike in synaptic modification was suppressed by the preceding spike in the same neuron, occurring within several tens of milliseconds. The direction and magnitude of synaptic modifications induced by spike patterns recorded in vivo in response to natural visual stimuli were well predicted by incorporating the suppressive inter-spike interaction within each neuron. Thus, activity-induced synaptic modification depends not only on the relative spike timing between the neurons, but also on the spiking pattern within each neuron. For natural spike trains, the timing of the first spike in each burst is dominant in synaptic modification.     

Oscillation and noise determine signal transduction in shark multimodal sensory cells

Oscillating membrane potentials that generate rhythmic impulse patterns are considered to be of particular significance for neuronal information processing. In contrast, noise is usually seen as a disturbance which limits the accuracy of information transfer. We show here, however, that noise in combination with intrinsic oscillations can provide neurons with particular encoding properties, a discovery we made when recording from single electro-sensory afferents of a fish. The temporal sequence of the impulse trains indicates oscillations that operate near the spike-triggering threshold. The oscillation frequency determines the basic rhythm of impulse generation, but whether or not an impulse is actually triggered essentially depends on superimposed noise. The probability of impulse generation can be altered considerably by minor modifications of oscillation baseline and amplitude, which may underlie the exquisite sensitivity of these receptors to thermal and electrical stimuli. Additionally, thermal, but not electrical, stimuli alter the oscillation frequency, allowing dual sensory messages to be conveyed in a single spike train. These findings demonstrate novel properties of sensory transduction which may be relevant for neuronal signalling in general.     

Attention modulates synchronized neuronal firing in primate somatosensory cortex

A potentially powerful information processing strategy in the brain is to take advantage of the temporal structure of neuronal spike trains. An increase in synchrony within the neural representation of an object or location increases the efficacy of that neural representation at the next synaptic stage in the brain; thus, increasing synchrony is a candidate for the neural correlate of attentional selection. We investigated the synchronous firing of pairs of neurons in the secondary somatosensory cortex (SII) of three monkeys trained to switch attention between a visual task and a tactile discrimination task. We found that most neuron pairs in SII cortex fired synchronously and, furthermore, that the degree of synchrony was affected by the monkey's attentional state. In the monkey performing the most difficult task, 35% of neuron pairs that fired synchronously changed their degree of synchrony when the monkey switched attention between the tactile and visual tasks. Synchrony increased in 80% and decreased in 20% of neuron pairs affected by attention.     

Voice-selective areas in human auditory cortex

The human voice contains in its acoustic structure a wealth of information on the speaker's identity and emotional state which we perceive with remarkable ease and accuracy. Although the perception of speaker-related features of voice plays a major role in human communication, little is known about its neural basis. Here we show, using functional magnetic resonance imaging in human volunteers, that voice-selective regions can be found bilaterally along the upper bank of the superior temporal sulcus (STS). These regions showed greater neuronal activity when subjects listened passively to vocal sounds, whether speech or non-speech, than to non-vocal environmental sounds. Central STS regions also displayed a high degree of selectivity by responding significantly more to vocal sounds than to matched control stimuli, including scrambled voices and amplitude-modulated noise. Moreover, their response to stimuli degraded by frequency filtering paralleled the subjects' behavioural performance in voice-perception tasks that used these stimuli. The voice-selective areas in the STS may represent the counterpart of the face-selective areas in human visual cortex; their existence sheds new light on the functional architecture of the human auditory cortex.     

Motor learning in a recurrent network model based on the vestibulo-ocular reflex.

Most models of neural networks have assumed that neurons process information on a timescale of milliseconds and that the long-term modification of synaptic strengths underlies learning and memory. But neurons also have cellular mechanisms that operate on a timescale of tens or hundreds of milliseconds, such as a gradual rise in firing rate in response to injection of constant current or a rapid rise followed by a slower adaptation. These dynamic properties of neuronal responses are mediated by ion channels that are subject to modulation. We demonstrate here how a neural network with recurrent feedback connections can convert long-term modulation of neural responses that occur over these intermediate timescales into changes in the amplitude of the steady output from the system. This general principle may be relevant to many feedback systems in the brain. Here it is applied to the vestibulo-ocular reflex, whose amplitude is subject to long-term adaptive modification by visual inputs. The model reconciles apparently contradictory data on the neural locus of the cellular mechanisms that mediate this simple form of learning and memory.     

Spatio-temporal correlations and visual signalling in a complete neuronal population

Statistical dependencies in the responses of sensory neurons govern both the amount of stimulus information conveyed and the means by which downstream neurons can extract it. Although a variety of measurements indicate the existence of such dependencies, their origin and importance for neural coding are poorly understood. Here we analyse the functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells using a model of multi-neuron spike responses. The model, with parameters fit directly to physiological data, simultaneously captures both the stimulus dependence and detailed spatio-temporal correlations in population responses, and provides two insights into the structure of the neural code. First, neural encoding at the population level is less noisy than one would expect from the variability of individual neurons: spike times are more precise, and can be predicted more accurately when the spiking of neighbouring neurons is taken into account. Second, correlations provide additional sensory information: optimal, model-based decoding that exploits the response correlation structure extracts 20% more information about the visual scene than decoding under the assumption of independence, and preserves 40% more visual information than optimal linear decoding. This model-based approach reveals the role of correlated activity in the retinal coding of visual stimuli, and provides a general framework for understanding the importance of correlated activity in populations of neurons.     

Gamma-band synchronization in visual cortex predicts speed of change detection

Our capacity to process and respond behaviourally to multiple incoming stimuli is very limited. To optimize the use of this limited capacity, attentional mechanisms give priority to behaviourally relevant stimuli at the expense of irrelevant distractors. In visual areas, attended stimuli induce enhanced responses and an improved synchronization of rhythmic neuronal activity in the gamma frequency band (40-70 Hz). Both effects probably improve the neuronal signalling of attended stimuli within and among brain areas. Attention also results in improved behavioural performance and shortened reaction times. However, it is not known how reaction times are related to either response strength or gamma-band synchronization in visual areas. Here we show that behavioural response times to a stimulus change can be predicted specifically by the degree of gamma-band synchronization among those neurons in monkey visual area V4 that are activated by the behaviourally relevant stimulus. When there are two visual stimuli and monkeys have to detect a change in one stimulus while ignoring the other, their reactions are fastest when the relevant stimulus induces strong gamma-band synchronization before and after the change in stimulus. This enhanced gamma-band synchronization is also followed by shorter neuronal response latencies on the fast trials. Conversely, the monkeys' reactions are slowest when gamma-band synchronization is high in response to the irrelevant distractor. Thus, enhanced neuronal gamma-band synchronization and shortened neuronal response latencies to an attended stimulus seem to have direct effects on visually triggered behaviour, reflecting an early neuronal correlate of efficient visuo-motor integration.     

Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with physiological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgment. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.     

Visual categorization shapes feature selectivity in the primate temporal cortex.

The way that we perceive and interact with objects depends on our previous experience with them. For example, a bird expert is more likely to recognize a bird as a sparrow, a sandpiper or a cockatiel than a non-expert. Neurons in the inferior temporal cortex have been shown to be important in the representation of visual objects; however, it is unknown which object features are represented and how these representations are affected by categorization training. Here we show that feature selectivity in the macaque inferior temporal cortex is shaped by categorization of objects on the basis of their visual features. Specifically, we recorded from single neurons while monkeys performed a categorization task with two sets of parametric stimuli. Each stimulus set consisted of four varying features, but only two of the four were important for the categorization task (diagnostic features). We found enhanced neuronal representation of the diagnostic features relative to the non-diagnostic ones. These findings demonstrate that stimulus features important for categorization are instantiated in the activity of single units (neurons) in the primate inferior temporal cortex.     

Temporal response properties to second-order visual stimuli in the LGN of cats

Visual stimuli occurring naturally are rich in instances of objects delineated from the backgrounds only by differences in luminance,which is called first-order stimuli,as well as those defined by differences of contrast or texture,referred to as second-order stimuli. The neuronal mechanism for processing second-order stimuli is still unclear. In this study,we compared the responses of cat LGN (lateral geniculate nucleus) cells to second-order stimuli at five temporal frequencies to their responses to first-order stimuli. Our results showed that most LGN cells can be evoked by second-order stimuli,and their firing rates to second-order stimuli decreased relative to first-order stimuli as temporal frequency increased from 0.5 to 8 Hz; moreover the ratio of a nonlinear to linear factor had a higher value in the responses to second-order stimuli than to first-order stimuli. We also found that the responses of Y-cells to second-order stimuli were significantly higher than the responses of X-cells,suggesting the Y-cells have a more important role in the processing of second-order stimuli. All these results reveal that first-order and second-order signals might be processed in separate 'streams' of the visual sys-tem.     

Feature-based attention influences motion processing gain in macaque visual cortex.

Changes in neural responses based on spatial attention have been demonstrated in many areas of visual cortex, indicating that the neural correlate of attention is an enhanced response to stimuli at an attended location and reduced responses to stimuli elsewhere. Here we demonstrate non-spatial, feature-based attentional modulation of visual motion processing, and show that attention increases the gain of direction-selective neurons in visual cortical area MT without narrowing the direction-tuning curves. These findings place important constraints on the neural mechanisms of attention and we propose to unify the effects of spatial location, direction of motion and other features of the attended stimuli in a 'feature similarity gain model' of attention.     

视知觉训练与初级视皮层神经元信息及其表征容量

通过分析猕猴初级视皮层（V1）神经元的群体活动在轮廓线检测训练过程中的变化发现：知觉训练可以降低V1神经元响应在不同试次之间的变异性，促使V1神经元对相同刺激的响应更加稳定；训练还可降低V1神经元群体中神经元活动之间的相关性，使V1神经元之间的活动更加独立；增加了神经活动的维度，提高了神经元表征信息的容量，减少了冗余的神经活动，进而提升了感知能力.     

The primate amygdala represents the positive and negative value of visual stimuli during learning

Visual stimuli can acquire positive or negative value through their association with rewards and punishments, a process called reinforcement learning. Although we now know a great deal about how the brain analyses visual information, we know little about how visual representations become linked with values. To study this process, we turned to the amygdala, a brain structure implicated in reinforcement learning. We recorded the activity of individual amygdala neurons in monkeys while abstract images acquired either positive or negative value through conditioning. After monkeys had learned the initial associations, we reversed image value assignments. We examined neural responses in relation to these reversals in order to estimate the relative contribution to neural activity of the sensory properties of images and their conditioned values. Here we show that changes in the values of images modulate neural activity, and that this modulation occurs rapidly enough to account for, and correlates with, monkeys' learning. Furthermore, distinct populations of neurons encode the positive and negative values of visual stimuli. Behavioural and physiological responses to visual stimuli may therefore be based in part on the plastic representation of value provided by the amygdala.     

Neuronal filtering of multiplexed odour representations

Neuronal activity patterns contain information in their temporal structure, indicating that information transfer between neurons may be optimized by temporal filtering. In the zebrafish olfactory bulb, subsets of output neurons (mitral cells) engage in synchronized oscillations during odour responses, but information about odour identity is contained mostly in non-oscillatory firing rate patterns. Using optogenetic manipulations and odour stimulation, we found that firing rate responses of neurons in the posterior zone of the dorsal telencephalon (Dp), a target area homologous to olfactory cortex, were largely insensitive to oscillatory synchrony of mitral cells because passive membrane properties and synaptic currents act as low-pass filters. Nevertheless, synchrony influenced spike timing. Moreover, Dp neurons responded primarily during the decorrelated steady state of mitral cell activity patterns. Temporal filtering therefore tunes Dp neurons to components of mitral cell activity patterns that are particularly informative about precise odour identity. These results demonstrate how temporal filtering can extract specific information from multiplexed neuronal codes.     

基于多元线性逆滤波器的视顶盖神经元集群亮度信息解码研究

通过解码鸽子视顶盖(the optic tectum,OT)神经元集群亮度信息的方法,研究了OT区神经元集群编码亮度信息的神经机制。首先设计了具有瞬态闪变特性的亮度视觉刺激模式,采用微电极阵列记录了多通道的锋电位(spike)发放序列;然后提取了神经元集群的spike发放率特征,构造多元线性逆滤波器解码视觉刺激亮度;最后采用互相关和信息论的方法对解码结果进行了分析。结果表明:采用的多元线性逆滤波器有效解码了OT区神经元集群编码的亮度信息。通过对解码参数变化与解码精度的分析可知神经元集群数目13个、bin的宽度5 ms、刺激后15 ms、刺激后持续时间35 ms具有最高的解码精度。通过神经元集群中逆滤波器形态的分析发现,单神经元在亮度信息的编码过程中受周围神经元的动态调制。通过对解码精度与刺激闪变频率关系的分析,发现在刺激闪变频率19 Hz到53 Hz的范围内,重建质量较好,在刺激闪变频率为33.5 Hz时,重建质量达到最优。     

Correlation between neural spike trains increases with firing rate

Populations of neurons in the retina, olfactory system, visual and somatosensory thalamus, and several cortical regions show temporal correlation between the discharge times of their action potentials (spike trains). Correlated firing has been linked to stimulus encoding, attention, stimulus discrimination, and motor behaviour. Nevertheless, the mechanisms underlying correlated spiking are poorly understood, and its coding implications are still debated. It is not clear, for instance, whether correlations between the discharges of two neurons are determined solely by the correlation between their afferent currents, or whether they also depend on the mean and variance of the input. We addressed this question by computing the spike train correlation coefficient of unconnected pairs of in vitro cortical neurons receiving correlated inputs. Notably, even when the input correlation remained fixed, the spike train output correlation increased with the firing rate, but was largely independent of spike train variability. With a combination of analytical techniques and numerical simulations using 'integrate-and-fire' neuron models we show that this relationship between output correlation and firing rate is robust to input heterogeneities. Finally, this overlooked relationship is replicated by a standard threshold-linear model, demonstrating the universality of the result. This connection between the rate and correlation of spiking activity links two fundamental features of the neural code.     

Entrained rhythmic activities of neuronal ensembles as perceptual memory of time interval

The ability to process temporal information is fundamental to sensory perception, cognitive processing and motor behaviour of all living organisms, from amoebae to humans. Neural circuit mechanisms based on neuronal and synaptic properties have been shown to process temporal information over the range of tens of microseconds to hundreds of milliseconds. How neural circuits process temporal information in the range of seconds to minutes is much less understood. Studies of working memory in monkeys and rats have shown that neurons in the prefrontal cortex, the parietal cortex and the thalamus exhibit ramping activities that linearly correlate with the lapse of time until the end of a specific time interval of several seconds that the animal is trained to memorize. Many organisms can also memorize the time interval of rhythmic sensory stimuli in the timescale of seconds and can coordinate motor behaviour accordingly, for example, by keeping the rhythm after exposure to the beat of music. Here we report a form of rhythmic activity among specific neuronal ensembles in the zebrafish optic tectum, which retains the memory of the time interval (in the order of seconds) of repetitive sensory stimuli for a duration of up to approximately 20 s. After repetitive visual conditioning stimulation (CS) of zebrafish larvae, we observed rhythmic post-CS activities among specific tectal neuronal ensembles, with a regular interval that closely matched the CS. Visuomotor behaviour of the zebrafish larvae also showed regular post-CS repetitions at the entrained time interval that correlated with rhythmic neuronal ensemble activities in the tectum. Thus, rhythmic activities among specific neuronal ensembles may act as an adjustable 'metronome' for time intervals in the order of seconds, and serve as a mechanism for the short-term perceptual memory of rhythmic sensory experience.     

Short-term memory in olfactory network dynamics

Neural assemblies in a number of animal species display self-organized, synchronized oscillations in response to sensory stimuli in a variety of brain areas. In the olfactory system of insects, odour-evoked oscillatory synchronization of antennal lobe projection neurons (PNs) is superimposed on slower and stimulus-specific temporal activity patterns. Hence, each odour activates a specific and dynamic projection neuron assembly whose evolution during a stimulus is locked to the oscillation clock. Here we examine, using locusts, the changes in population dynamics of projection-neuron assemblies over repeated odour stimulations, as would occur when an animal first encounters and then repeatedly samples an odour for identification or localization. We find that the responses of these assemblies rapidly decrease in intensity, while they show a marked increase in spike time precision and inter-neuronal oscillatory coherence. Once established, this enhanced precision in the representation endures for several minutes. This change is stimulus-specific, and depends on events within the antennal lobe circuits, independent of olfactory receptor adaptation: it may thus constitute a form of sensory memory. Our results suggest that this progressive change in olfactory network dynamics serves to converge, over repeated odour samplings, on a more precise and readily classifiable odour representation, using relational information contained across neural assemblies.     

Experience-dependent representation of visual categories in parietal cortex

Categorization is a process by which the brain assigns meaning to sensory stimuli. Through experience, we learn to group stimuli into categories, such as 'chair', 'table' and 'vehicle', which are critical for rapidly and appropriately selecting behavioural responses. Although much is known about the neural representation of simple visual stimulus features (for example, orientation, direction and colour), relatively little is known about how the brain learns and encodes the meaning of stimuli. We trained monkeys to classify 360 degrees of visual motion directions into two discrete categories, and compared neuronal activity in the lateral intraparietal (LIP) and middle temporal (MT) areas, two interconnected brain regions known to be involved in visual motion processing. Here we show that neurons in LIP--an area known to be centrally involved in visuo-spatial attention, motor planning and decision-making-robustly reflect the category of motion direction as a result of learning. The activity of LIP neurons encoded directions of motion according to their category membership, and that encoding shifted after the monkeys were retrained to group the same stimuli into two new categories. In contrast, neurons in area MT were strongly direction selective but carried little, if any, explicit category information. This indicates that LIP might be an important nexus for the transformation of visual direction selectivity to more abstract representations that encode the behavioural relevance, or meaning, of stimuli.     

Adaptive coding of visual information in neural populations

Our perception of the environment relies on the capacity of neural networks to adapt rapidly to changes in incoming stimuli. It is increasingly being realized that the neural code is adaptive, that is, sensory neurons change their responses and selectivity in a dynamic manner to match the changes in input stimuli. Understanding how rapid exposure, or adaptation, to a stimulus of fixed structure changes information processing by cortical networks is essential for understanding the relationship between sensory coding and behaviour. Physiological investigations of adaptation have contributed greatly to our understanding of how individual sensory neurons change their responses to influence stimulus coding, yet whether and how adaptation affects information coding in neural populations is unknown. Here we examine how brief adaptation (on the timescale of visual fixation) influences the structure of interneuronal correlations and the accuracy of population coding in the macaque (Macaca mulatta) primary visual cortex (V1). We find that brief adaptation to a stimulus of fixed structure reorganizes the distribution of correlations across the entire network by selectively reducing their mean and variability. The post-adaptation changes in neuronal correlations are associated with specific, stimulus-dependent changes in the efficiency of the population code, and are consistent with changes in perceptual performance after adaptation. Our results have implications beyond the predictions of current theories of sensory coding, suggesting that brief adaptation improves the accuracy of population coding to optimize neuronal performance during natural viewing.