Contribution of area MT to stereoscopic depth perception: choice-related response modulations reflect task strategy

Due to the diversity of tuning properties in sensory cortex, only a fraction of neurons are engaged in a particular task. Characterizing the tuning properties of neurons that are functionally linked to behavior is essential for understanding how activity is "read out" from sensory maps to guide decisions. We recorded from middle temporal (MT) neurons while monkeys performed a depth discrimination task, and we characterized the linkage between MT responses and behavioral choices. Trial-to-trial response fluctuations of MT neurons with odd-symmetric ("Near," "Far") disparity tuning were predictive of monkeys' choices, whereas responses of neurons with even-symmetric tuning were not. This result cannot be explained by neuronal sensitivity or any other response property of MT neurons that we examined but is simply explained by the task strategy that monkeys learned during training. We suggest that this approach provides a physiological means to explore how task strategies are implemented in the brain.     

Sparse representation of sounds in the unanesthetized auditory cortex

How do neuronal populations in the auditory cortex represent acoustic stimuli? Although sound-evoked neural responses in the anesthetized auditory cortex are mainly transient, recent experiments in the unanesthetized preparation have emphasized subpopulations with other response properties. To quantify the relative contributions of these different subpopulations in the awake preparation, we have estimated the representation of sounds across the neuronal population using a representative ensemble of stimuli. We used cell-attached recording with a glass electrode, a method for which single-unit isolation does not depend on neuronal activity, to quantify the fraction of neurons engaged by acoustic stimuli (tones, frequency modulated sweeps, white-noise bursts, and natural stimuli) in the primary auditory cortex of awake head-fixed rats. We find that the population response is sparse, with stimuli typically eliciting high firing rates (>20 spikes/second) in less than 5% of neurons at any instant. Some neurons had very low spontaneous firing rates (<0.01 spikes/second). At the other extreme, some neurons had driven rates in excess of 50 spikes/second. Interestingly, the overall population response was well described by a lognormal distribution, rather than the exponential distribution that is often reported. Our results represent, to our knowledge, the first quantitative evidence for sparse representations of sounds in the unanesthetized auditory cortex. Our results are compatible with a model in which most neurons are silent much of the time, and in which representations are composed of small dynamic subsets of highly active neurons.     

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 extracellularly 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.     

Dynamics of population code for working memory in the prefrontal cortex

Some neurons (delay cells) in the prefrontal cortex elevate their activities throughout the time period during which the animal is required to remember past events and prepare future behavior, suggesting that working memory is mediated by continuous neural activity. It is unknown, however, how working memory is represented within a population of prefrontal cortical neurons. We recorded from neuronal ensembles in the prefrontal cortex as rats learned a new delayed alternation task. Ensemble activities changed in parallel with behavioral learning so that they increasingly allowed correct decoding of previous and future goal choices. In well-trained rats, considerable decoding was possible based on only a few neurons and after removing continuously active delay cells. These results show that neural activity in the prefrontal cortex changes dynamically during new task learning so that working memory is robustly represented and that working memory can be mediated by sequential activation of different neural populations.     

Patterns of spatio-temporal correlations in the neural activity of the cat motor cortex during trained forelimb movements

In order to study how neurons in the primary motor cortex (MI) are dynamically linked together during skilled movement, we recorded simultaneously from many cortical neurons in cats trained to perform a reaching and retrieval task using their forelimbs. Analysis of task-related spike activity in the MI of the hemisphere contralateral to the reaching forelimb (in identified forelimb or hindlimb representations) recorded through chronically implanted microwires, was followed by pairwise evaluation of temporally correlated activity in these neurons during task performance using shuffle corrected cross-correlograms. Over many months of recording, a variety of task-related modulations of neural activities were observed in individual efferent zones. Positively correlated activity (mainly narrow peaks at zero or short latencies) was seen during task performance frequently between neurons recorded within the forelimb representation of MI, rarely within the hindlimb area of MI, and never between forelimb and hindlimb areas. Correlated activity was frequently observed between neurons with different patterns of task-related activity or preferential activity during different task elements (reaching, feeding, etc.), and located in efferent zones with dissimilar representation as defined by intracortical microstimulation. The observed synchronization of action potentials among selected but functionally varied groups of MI neurons possibly reflects dynamic recruitment of network connections between efferent zones during skilled movement.     

Short-latency unit responses of the lateral geniculate body to electrical stimulation of the optic tract in rats

Short-latency responses of single relay neurons of the lateral geniculate body to electrical stimulation of the optic tract were studied. The response of many neurons was complex and could consist of a series of (1–3) spikes with fixed latent periods. Each spike of such a response can be recorded on the EPSP in the absence of other spikes, preserving its latent period. The fixed latent periods of different relay neurons may vary from one to another. In the intervals between spikes with these latent periods active inhibition (IPSP) takes place. The series of spikes, EPSP, and IPSP is completed, as a rule, by a long IPSP.M. V. Lomonosov Moscow State University. Translated from Neirofiziologiya, Vol. 5, No. 1, pp. 28–32, January–February, 1973.     

Rates and rhythms: a synergistic view of frequency and temporal coding in neuronal networks

In the CNS, activity of individual neurons has a small but quantifiable relationship to sensory representations and motor outputs. Coactivation of a few 10s to 100s of neurons can code sensory inputs and behavioral task performance within psychophysical limits. However, in a sea of sensory inputs and demand for complex motor outputs how is the activity of such small subpopulations of neurons organized? Two theories dominate in this respect: increases in spike rate (rate coding) and sharpening of the coincidence of spiking in active neurons (temporal coding). Both have computational advantages and are far from mutually exclusive. Here, we review evidence for a bias in neuronal circuits toward temporal coding and the coexistence of rate and temporal coding during population rhythm generation. The coincident expression of multiple types of gamma rhythm in sensory cortex suggests a mechanistic substrate for combining rate and temporal codes?on the basis of stimulus strength.     

Timing Precision in Population Coding of Natural Scenes in the Early Visual System

The timing of spiking activity across neurons is a fundamental aspect of the neural population code. Individual neurons in the retina, thalamus, and cortex can have very precise and repeatable responses but exhibit degraded temporal precision in response to suboptimal stimuli. To investigate the functional implications for neural populations in natural conditions, we recorded in vivo the simultaneous responses, to movies of natural scenes, of multiple thalamic neurons likely converging to a common neuronal target in primary visual cortex. We show that the response of individual neurons is less precise at lower contrast, but that spike timing precision across neurons is relatively insensitive to global changes in visual contrast. Overall, spike timing precision within and across cells is on the order of 10 ms. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary to represent the more slowly varying natural environment, we argue that preserving relative spike timing at a ~10-ms resolution is a crucial property of the neural code entering cortex.     

Pyramidal unit activity in unanesthetized cats

Pyramidal unit activity in unanesthetized cats at rest and during voluntary movement was recorded by a microelectrode technique from the motor cortex for the forelimb. Some pyramidal neurons were not spontaneously active. The conduction velocity along the axon of these neurons was sometimes high (up to 71.5 m/sec), sometimes low (up to 11.2 m/sec). The remaining pyramidal neurons had spontaneous activity with a mean frequency of 1.29 to 43 spikes/sec. Analysis of interspike interval histograms of spontaneous activity and of autocorrelation histograms showed grouping of the spikes into volleys in most pyramidal neurons (irrespective of the conduction velocity). During voluntary movements the change in the activity of many pyramidal units correlated with changes in the EMG. The firing rate of the pyramidal neurons under these circumstances began to rise at least 50 msec before the increase in amplitude of the EMG and it remained high throughout the movement. The firing rate of most neurons during movement was 40–60/sec. The results are compared with those obtained by other workers who studied pyramidal unit activity of monkeys during voluntary movement.     

The role of attention in visual processing

Attention to a visual stimulus typically increases the responses of cortical neurons to that stimulus. Because many studies have shown a close relationship between the performance of individual neurons and behavioural performance of animal subjects, it is important to consider how attention affects this relationship. Measurements of behavioural and neuronal performance taken from rhesus monkeys while they performed a motion detection task with two attentional states show that attention alters the relationship between behaviour and neuronal response. Notably, attention affects the relationship differently in different cortical visual areas. This indicates that a close relationship between neuronal and behavioural performance on a given task persists over changes in attentional state only within limited regions of visual cortex.     

The chronotron: a neuron that learns to fire temporally precise spike patterns

In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons), one that provides high memory capacity (E-learning), and one that has a higher biological plausibility (I-learning). With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm.     

Functional characteristics of visual cortical neurons of the cat

The characteristics of neurons in Area 17 of the visual cortex in cats were investigated by extracellular recording of their activity. Unit responses to flashes modulated by intensity and duration (100 µsec-1 sec) were recorded. Of 80 neurons tested, 67.6% were spontaneously active and 32.4% were silent. The threshold responses of the neurons to flashes varied by 7 logarithmic units. The distribution curve of the cells by response thresholds had one maximum corresponding to an energy of the order of 1–10 lm·sec. The time during which the cells could summate excitation did not exceed a mean value of 34 msec. Depending on the latent periods of the visual cortical neurons they can be divided into three groups. The first group includes neurons responding 20–40 msec after stimulation, the second and third neurons responding after 100–120 and 160–180 msec, respectively. Photic stimulation considerably altered the ratio between the numbers of cells generating spikes with high and low frequency. No correlation was found between the sensitivity of the visual cortical cells to light, the latent period of their response, and the critical time of summation. This shows that the cortex contains many duplicate units which are grouped together on the basis of only one of the functional characteristics of their spike response.Institute of Higher Nervous Activity and Neurophysiology, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 2, No. 2, pp. 173–179, March–April, 1970.     

Different levels of the homeodomain protein cut regulate distinct dendrite branching patterns of Drosophila multidendritic neurons

Functionally similar neurons can share common dendrite morphology, but how different neurons are directed into similar forms is not understood. Here, we show in embryonic and larval development that the level of Cut immunoreactivity in individual dendritic arborization (da) sensory neurons correlates with distinct patterns of terminal dendrites: high Cut in neurons with extensive unbranched terminal protrusions (dendritic spikes), medium levels in neurons with expansive and complex arbors, and low or nondetectable Cut in neurons with simple dendrites. Loss of Cut reduced dendrite growth and class-specific terminal branching, whereas overexpression of Cut or a mammalian homolog in lower-level neurons resulted in transformations toward the branch morphology of high-Cut neurons. Thus, different levels of a homeoprotein can regulate distinct patterns of dendrite branching.     

Evidence for Synchronous Activation of Neurons Located in Different Layers of Primary Somatosensory Cortex

Although many studies have examined the columnar organization of primary somatosensory (SI) cortex, the functional relationship among neurons in different layers remains unclear. To understand how activity is coordinated among different cortical layers, the present investigation tested the hypothesis that the initial part of a peripheral stimulus produces a serial pattern of laminar activation in SI cortex. Extracellular discharges of 334 histologically recovered neurons were recorded from the medial bank of the coronal sulcus in nine anesthetized cats during electrical or cutaneous stimulation of the distal forelimb. Mean responses during the initial 50-msec period following stimulus onset were largest in layers IIIb or IV for both types of stimulation, but laminar differences in the magnitude of onset responses were not statistically significant. Among 175 neurons with responses exceeding 0.5 spikes per stimulus, electrical Stimulation consistently produced shorter response latencies than mechanical indentation in the extragranular (II, IIIa, V, VI), but not in the middle (IIIb, IV), cortical layers. The average minimum latencies for different cortical layers ranged from 7.4 to 10.1 msec for responses to electrical stimulation and from 10.3 to 11.6 msec for responses to mechanical indentations, but these laminar differences were not statistically significant. In some experiments, neurons in different layers of a cortical column were recorded simultaneously with dual-electrode assemblies; among 37 neuron pairs in which both neurons responded with more than 0.5 spikes per stimulus, response latencies were similar, even though the neurons were separated by several hundred microns. Cross-correlation analysis of the onset responses for neurons recorded simultaneously from different layers also indicated that many cells throughout a cortical column were activated nearly simultaneously by the initial phase of a peripheral stimulus. Results from the present study are compared with previous reports examining laminar patterns of activation.     

Inhibitory neurons exhibit high controlling ability in the cortical microconnectome

The brain is a network system in which excitatory and inhibitory neurons keep activity balanced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons in the cortex. So, in general, how inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the relatively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and controlling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibitory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimulate E/I imbalanced disease states.     

Synaptic integration in dendritic trees

Most neurons have elaborate dendritic trees that receive tens of thousands of synaptic inputs. Because postsynaptic responses to individual synaptic events are usually small and transient, the integration of many synaptic responses is needed to depolarize most neurons to action potential threshold. Over the past decade, advances in electrical and optical recording techniques have led to new insights into how synaptic responses propagate and interact within dendritic trees. In addition to their passive electrical and morphological properties, dendrites express active conductances that shape individual synaptic responses and influence synaptic integration locally within dendrites. Dendritic voltage-gated Na(+) and Ca(2+) channels support action potential backpropagation into the dendritic tree and local initiation of dendritic spikes, whereas K(+) conductances act to dampen dendritic excitability. While all dendrites investigated to date express active conductances, different neuronal types show specific patterns of dendritic channel expression leading to cell-specific differences in the way synaptic responses are integrated within dendritic trees. This review explores the way active and passive dendritic properties shape synaptic responses in the dendrites of central neurons, and emphasizes their role in synaptic integration.     

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

Sensory neurons encode natural stimuli by changes in firing rate or by generating specific firing patterns, such as bursts. Many neural computations rely on the fact that neurons can be tuned to specific stimulus frequencies. It is thus important to understand the mechanisms underlying frequency tuning. In the electrosensory system of the weakly electric fish, Apteronotus leptorhynchus, the primary processing of behaviourally relevant sensory signals occurs in pyramidal neurons of the electrosensory lateral line lobe (ELL). These cells encode low frequency prey stimuli with bursts of spikes and high frequency communication signals with single spikes. We describe here how bursting in pyramidal neurons can be regulated by intrinsic conductances in a cell subtype specific fashion across the sensory maps found within the ELL, thereby regulating their frequency tuning. Further, the neuromodulatory regulation of such conductances within individual cells and the consequences to frequency tuning are highlighted. Such alterations in the tuning of the pyramidal neurons may allow weakly electric fish to preferentially select for certain stimuli under various behaviourally relevant circumstances.     

Time Course of Functional Connectivity in Primate Dorsolateral Prefrontal and Posterior Parietal Cortex during Working Memory

The dorsolateral prefrontal and posterior parietal cortex play critical roles in mediating attention, working memory, and executive function. Despite proposed dynamic modulation of connectivity strength within each area according to task demands, scant empirical data exist about the time course of the strength of effective connectivity, particularly in tasks requiring information to be sustained in working memory. We investigated this question by performing time-resolved cross-correlation analysis for pairs of neurons recorded simultaneously at distances of 0.2–1.5 mm apart of each other while monkeys were engaged in working memory tasks. The strength of effective connectivity determined in this manner was higher throughout the trial in the posterior parietal cortex than the dorsolateral prefrontal cortex. Significantly higher levels of parietal effective connectivity were observed specifically during the delay period of the task. These differences could not be accounted for by differences in firing rate, or electrode distance in the samples recorded in the posterior parietal and prefrontal cortex. Differences were present when we restricted our analysis to only neurons with significant delay period activity and overlapping receptive fields. Our results indicate that dynamic changes in connectivity strength are present but area-specific intrinsic organization is the predominant factor that determines the strength of connections between neurons in each of the two areas.