Adaptive switches in midbrain circuits

In this issue of Neuron, Mysore and Knudsen (2012) describe a simple, anatomically supported circuit that can categorize stimuli into "strongest" and "others," regardless of their absolute strength. Such flexible categorization cannot be achieved by lateral inhibition alone but also requires that the inhibitory neurons reciprocally inhibit each other.     

Spatially Reciprocal Inhibition of Inhibition within a Stimulus Selection Network in the Avian Midbrain

Reciprocal inhibition between inhibitory projection neurons has been proposed as the most efficient circuit motif to achieve the flexible selection of one stimulus among competing alternatives. However, whether such a motif exists in networks that mediate selection is unclear. Here, we study the connectivity within the nucleus isthmi pars magnocellularis (Imc), a GABAergic nucleus that mediates competitive selection in the midbrain stimulus selection network. Using laser photostimulation of caged glutamate, we find that feedback inhibitory connectivity is global within the Imc. Unlike typical lateral inhibition in other circuits, intra-Imc inhibition remains functionally powerful over long distances. Anatomically, we observed long-range axonal projections and retrograde somatic labeling from focal injections of bi-directional tracers in the Imc, consistent with spatial reciprocity of intra-Imc inhibition. Together, the data indicate that spatially reciprocal inhibition of inhibition occurs throughout the Imc. Thus, the midbrain selection circuit possesses the most efficient circuit motif possible for fast, reliable, and flexible selection.     

The role of a midbrain network in competitive stimulus selection

A midbrain network interacts with the well-known frontoparietal forebrain network to select stimuli for gaze and spatial attention. The midbrain network, containing the superior colliculus (SC; optic tectum, OT, in non-mammalian vertebrates) and the isthmic nuclei, helps evaluate the relative priorities of competing stimuli and encodes them in a topographic map of space. Behavioral experiments in monkeys demonstrate an essential contribution of the SC to stimulus selection when the relative priorities of competing stimuli are similar. Neurophysiological results from the owl OT demonstrate a neural correlate of this essential contribution of the SC/OT. The multi-layered, spatiotopic organization of the midbrain network lends itself to the analysis and modeling of the mechanisms underlying stimulus selection for gaze and spatial attention.     

Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.     

The Emotional Gatekeeper: A Computational Model of Attentional Selection and Suppression through the Pathway from the Amygdala to the Inhibitory Thalamic Reticular Nucleus

In a complex environment that contains both opportunities and threats, it is important for an organism to flexibly direct attention based on current events and prior plans. The amygdala, the hub of the brain''s emotional system, is involved in forming and signaling affective associations between stimuli and their consequences. The inhibitory thalamic reticular nucleus (TRN) is a hub of the attentional system that gates thalamo-cortical signaling. In the primate brain, a recently discovered pathway from the amygdala sends robust projections to TRN. Here we used computational modeling to demonstrate how the amygdala-TRN pathway, embedded in a wider neural circuit, can mediate selective attention guided by emotions. Our Emotional Gatekeeper model demonstrates how this circuit enables focused top-down, and flexible bottom-up, allocation of attention. The model suggests that the amygdala-TRN projection can serve as a unique mechanism for emotion-guided selection of signals sent to cortex for further processing. This inhibitory selection mechanism can mediate a powerful affective ‘framing’ effect that may lead to biased decision-making in highly charged emotional situations. The model also supports the idea that the amygdala can serve as a relevance detection system. Further, the model demonstrates how abnormal top-down drive and dysregulated local inhibition in the amygdala and in the cortex can contribute to the attentional symptoms that accompany several neuropsychiatric disorders.     

Representation of lateral line and electrosensory systems in the midbrain of the axolotl,Ambystoma mexicanum

Summary The study focussed on the representation of the electrosensory and lateral line units in the midbrain of the axolotl Ambystoma mexicanum. In addition, the responses to photic and acoustic/vibrational stimuli were determined. Unit properties were characterized with respect to baseline activity, sensitivity, latency, directional specificity and number of input modalities. The anatomical arrangement of the units was determined using stereotactic and histological measurements of the electrode positions.Of 106 units recorded, 29 units were unimodal, 77 units responded to more than one modality. Most units discharged only in response to stimuli. Thresholds of electrosensory units were about 100 V/cm field strength; lateral line units had thresholds below 5 m pp amplitude. The shortest latencies (8–17 ms) were found for responses to visual stimuli. Lateral line and vestibular units responded after 35–58 ms, electroreceptive units after 79–150 ms. All electrosensory and about 50% of the lateral line units were sharply tuned to definite stimulus directions.Electrosensory and lateral line units formed topographical maps in the tectum. The map in each tectal hemisphere contained information about the contralateral surroundings. The electrosensory, lateral line and visual representations were only partly in register; especially in the caudal areas of the midbrain the alignment was poor.     

Stimulus-dependent adjustment of reward prediction error in the midbrain

Previous reports have described that neural activities in midbrain dopamine areas are sensitive to unexpected reward delivery and omission. These activities are correlated with reward prediction error in reinforcement learning models, the difference between predicted reward values and the obtained reward outcome. These findings suggest that the reward prediction error signal in the brain updates reward prediction through stimulus-reward experiences. It remains unknown, however, how sensory processing of reward-predicting stimuli contributes to the computation of reward prediction error. To elucidate this issue, we examined the relation between stimulus discriminability of the reward-predicting stimuli and the reward prediction error signal in the brain using functional magnetic resonance imaging (fMRI). Before main experiments, subjects learned an association between the orientation of a perceptually salient (high-contrast) Gabor patch and a juice reward. The subjects were then presented with lower-contrast Gabor patch stimuli to predict a reward. We calculated the correlation between fMRI signals and reward prediction error in two reinforcement learning models: a model including the modulation of reward prediction by stimulus discriminability and a model excluding this modulation. Results showed that fMRI signals in the midbrain are more highly correlated with reward prediction error in the model that includes stimulus discriminability than in the model that excludes stimulus discriminability. No regions showed higher correlation with the model that excludes stimulus discriminability. Moreover, results show that the difference in correlation between the two models was significant from the first session of the experiment, suggesting that the reward computation in the midbrain was modulated based on stimulus discriminability before learning a new contingency between perceptually ambiguous stimuli and a reward. These results suggest that the human reward system can incorporate the level of the stimulus discriminability flexibly into reward computations by modulating previously acquired reward values for a typical stimulus.     

A neural representation of categorization uncertainty in the human brain

The ability to classify visual objects into discrete categories ("friend" versus "foe"; "edible" versus "poisonous") is essential for survival and is a fundamental cognitive function. The cortical substrates that mediate this function, however, have not been identified in humans. To identify brain regions involved in stimulus categorization, we developed a task in which subjects classified stimuli according to a variable categorical boundary. Psychophysical functions were used to define a decision variable, categorization uncertainty, which was systematically manipulated. Using event-related functional MRI, we discovered that activity in a fronto-striatal-thalamic network, consisting of the medial frontal gyrus, anterior insula, ventral striatum, and dorsomedial thalamus, was modulated by categorization uncertainty. We found this network to be distinct from the frontoparietal attention network, consisting of the frontal and parietal eye fields, where activity was not correlated with categorization uncertainty.     

Variable synaptic strengths controls the firing rate distribution in feedforward neural networks

Heterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integrate-and-fire neurons with random recurrent coupling. Inspired by our experimental data, we extend these theoretical results to a delayed feedforward spiking network that qualitatively capture the changes of firing rate heterogeneity observed in in-vivo recordings. We demonstrate how heterogeneous neural attributes alter firing rate heterogeneity, accounting for the effect with various sensory stimuli. The model predicts how the strength of the effective network connectivity is related to intrinsic heterogeneity in such delayed feedforward networks: the strength of the feedforward input is positively correlated with excitability (threshold value for spiking) when firing rate heterogeneity is low and is negatively correlated with excitability with high firing rate heterogeneity. We also show how our theory can be used to predict effective neural architecture. We demonstrate that neural attributes do not interact in a simple manner but rather in a complex stimulus-dependent fashion to control neural heterogeneity and discuss how it can ultimately shape population codes.     

Stimulus detection after interruption of the feedforward response in a backward masking paradigm

In backward masking, a target stimulus is rendered invisible by the presentation of a second stimulus, the mask. When the mask is effective, neural responses to the target are suppressed. Nevertheless, weak target responses sometimes may produce a behavioural response. It remains unclear whether the reduced target response is a purely feedforward response or that it includes recurrent activity. Using a feedforward neural network of biological plausible spiking neurons, we tested whether a transient spike burst is sufficient for face categorization. After training the network, the system achieved face/non-face categorization for sets of grayscale images. In a backward masking paradigm, the transient burst response was cut off thereby reducing the feedforward target response. Despite the suppressed feedforward responses stimulus classification remained robust. Thus according to our model data stimulus detection is possible with purely, suppressed feedforward responses.     

Dynamic perceptual changes in audiovisual simultaneity

Background

The timing at which sensory input reaches the level of conscious perception is an intriguing question still awaiting an answer. It is often assumed that both visual and auditory percepts have a modality specific processing delay and their difference determines perceptual temporal offset.

Methodology/Principal Findings

Here, we show that the perception of audiovisual simultaneity can change flexibly and fluctuates over a short period of time while subjects observe a constant stimulus. We investigated the mechanisms underlying the spontaneous alternations in this audiovisual illusion and found that attention plays a crucial role. When attention was distracted from the stimulus, the perceptual transitions disappeared. When attention was directed to a visual event, the perceived timing of an auditory event was attracted towards that event.

Conclusions/Significance

This multistable display illustrates how flexible perceived timing can be, and at the same time offers a paradigm to dissociate perceptual from stimulus-driven factors in crossmodal feature binding. Our findings suggest that the perception of crossmodal synchrony depends on perceptual binding of audiovisual stimuli as a common event.     

Context-dependent changes in functional circuitry in visual area MT

Animals can flexibly change their behavior in response to a particular sensory stimulus; the mapping between sensory and motor representations in the brain must therefore be flexible as well. Changes in the correlated firing of pairs of neurons may provide a metric of changes in functional circuitry during behavior. We studied dynamic changes in functional circuitry by analyzing the noise correlations of simultaneously recorded MT neurons in two behavioral contexts: one that promotes cooperative interactions between the two neurons and another that promotes competitive interactions. We found that identical visual stimuli give rise to differences in noise correlation in the two contexts, suggesting that MT neurons receive inputs of central origin whose strength changes with the task structure. The data are consistent with a mixed feature-based attentional strategy model in which the animal sometimes alternates attention between opposite directions of motion and sometimes attends to the two directions simultaneously.     

Conditions for noise reduction and stable encoding of spatial structure by cortical neural networks

Cortical circuits have been proposed to encode information by forming stable spatially structured attractors. Experimentally in the primary somatosensory cortex of the monkey, temporally invariant stimuli lead to spatially structured activity patterns. The purpose of this work is to study a recurrent cortical neural network model with lateral inhibition and examine what effect additive random noise has on the networks' ability to form stable spatially structured representations of the stimulus pattern. We show numerically that this network performs edge enhancement and forms statistically stationary, spatially structured responses when the lateral inhibition is of moderate strength. We then derive analytical conditions on the connectivity matrix that ensure stochasticly stable encoding of the stimulus spatial structure by the network. For stimuli whose strength falls in the near linear region of the sigmoid, we are able to give explicit conditions on the eigenvalues of the connection matrix. Finally, we prove that a network with a connection matrix, where the total excitation and inhibition impinging upon a neural unit are nearly balanced, will yield stable spatial attractor responses. Received: 16 October 1998 / Accepted in revised form: 25 November 1999     

Tuned normalization explains the size of attention modulations

The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron's receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the nonpreferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention.     

Dual mechanism of neuronal ensemble inhibition in primary auditory cortex

Inhibition plays an essential role in shaping and refining the brain's representation of sensory stimulus attributes. In primary auditory cortex (A1), so-called "sideband" inhibition helps to sharpen the tuning of local neuronal responses. Several distinct types of anatomical circuitry could underlie sideband inhibition, including direct thalamocortical (TC) afferents, as well as indirect intracortical mechanisms. The goal of the present study was to characterize sideband inhibition in A1 and to determine its mechanism by analyzing laminar profiles of neuronal ensemble activity. Our results indicate that both lemniscal and nonlemniscal TC afferents play a role in inhibitory responses via feedforward inhibition and oscillatory phase reset, respectively. We propose that the dynamic modulation of excitability in A1 due to the phase reset of ongoing oscillations may alter the tuning of local neuronal ensembles and can be regarded as a flexible overlay on the more obligatory system of lemniscal feedforward type responses.     

Selectivity of visual cortical neurons of rabbits to magnitude of moving stimuli

Unit responses of the rabbit visual cortex were investigated in relation to size of visual stimuli moving in their receptive field. With an increase in size of the stimulus in a direction perpendicular to the direction of movement ("width" of the stimulus) an initial increase in the intensity of the unit response through spatial summation of excitory effects is followed by a decrease through lateral inhibition. This inhibition is observed between zones of the receptive field which behave as activating when tested by a stimulus of small size. Each neuron has its own "preferred" size of stimuli evoking its maximal activation. No direct correlation is found between the "preferred" stimulus size and the size of the receptive field. With a change in stimulus size in the direction of movement ("length" of the stimulus) the responses to stimuli of optimal size may be potentiated through mutual facilitation of the effects evoked by the leading and trailing edges of the stimulus and weakened in response to stimuli of large size. The selective behavior of the neurons with respect to stimulus size is intensified in the case of coordinated changes in their length and width. It is postulated that the series of neurons responding to stimuli of different "preferred" dimensions may constitute a system classifying stimuli by their size.A. N. Severtsov Institute of Evolutionary Morphology and Ecology of Animals, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 4, No. 6, pp. 636–644, November–December, 1972.     

Lesions of the Fasciculus Retroflexus Alter Footshock-Induced cFos Expression in the Mesopontine Rostromedial Tegmental Area of Rats

Midbrain dopamine neurons are an essential part of the circuitry underlying motivation and reinforcement. They are activated by rewards or reward-predicting cues and inhibited by reward omission. The lateral habenula (lHb), an epithalamic structure that forms reciprocal connections with midbrain dopamine neurons, shows the opposite response being activated by reward omission or aversive stimuli and inhibited by reward-predicting cues. It has been hypothesized that habenular input to midbrain dopamine neurons is conveyed via a feedforward inhibitory pathway involving the GABAergic mesopontine rostromedial tegmental area. Here, we show that exposing rats to low-intensity footshock (four, 0.5 mA shocks over 20 min) induces cFos expression in the rostromedial tegmental area and that this effect is prevented by lesions of the fasciculus retroflexus, the principal output pathway of the habenula. cFos expression is also observed in the medial portion of the lateral habenula, an area that receives dense DA innervation via the fr and the paraventricular nucleus of the thalamus, a stress sensitive area that also receives dopaminergic input. High-intensity footshock (120, 0.8 mA shocks over 40 min) also elevates cFos expression in the rostromedial tegmental area, medial and lateral aspects of the lateral habenula and the paraventricular thalamus. In contrast to low-intensity footshock, increases in cFos expression within the rostromedial tegmental area are not altered by fr lesions suggesting a role for non-habenular inputs during exposure to highly aversive stimuli. These data confirm the involvement of the lateral habenula in modulating the activity of rostromedial tegmental area neurons in response to mild aversive stimuli and suggest that dopamine input may contribute to footshock- induced activation of cFos expression in the lateral habenula.     

Biased competition through variations in amplitude of <Emphasis Type="Italic">γ</Emphasis>-oscillations

Experiments in visual cortex have shown that the firing rate of a neuron in response to the simultaneous presentation of a preferred and non-preferred stimulus within the receptive field is intermediate between that for the two stimuli alone (stimulus competition). Attention directed to one of the stimuli drives the response towards the response induced by the attended stimulus alone (selective attention). This study shows that a simple feedforward model with fixed synaptic conductance values can reproduce these two phenomena using synchronization in the gamma-frequency range to increase the effective synaptic gain for the responses to the attended stimulus. The performance of the model is robust to changes in the parameter values. The model predicts that the phase locking between presynaptic input and output spikes increases with attention.     

Categorization training results in shape- and category-selective human neural plasticity

Object category learning is a fundamental ability, requiring the combination of "bottom-up" stimulus-driven with "top-down" task-specific information. It therefore may be a fruitful domain for study of the general neural mechanisms underlying cortical plasticity. A simple model predicts that category learning involves the formation of a task-independent shape-selective representation that provides input to circuits learning the categorization task, with the computationally appealing prediction of facilitated learning of additional, novel tasks over the same stimuli. Using fMRI rapid-adaptation techniques, we find that categorization training (on morphed "cars") induced a significant release from adaptation for small shape changes in lateral occipital cortex irrespective of category membership, compatible with the sharpening of a representation coding for physical appearance. In contrast, an area in lateral prefrontal cortex, selectively activated during categorization, showed sensitivity posttraining to explicit changes in category membership. Further supporting the model, categorization training also improved discrimination performance on the trained stimuli.     

Convergence between influences from midbrain and bulbar locomotor sites and from an inhibitory site in neurons of the medulla

Synaptic response to regular stimulation of midbrain and bulbar locomotor sites (LS) and a pontine inhibitory site (IS) was recorded in medial and lateral bulbar neurons in cats (mesencephalic decerebellate preparation). Excitatory post-synaptic potentials (PSP) and discharges were usually noted in medial neurons; mixed PSP also occurred when stimulating the IS. Almost 50% of lateral and over 25% of medial neurons showed a change in background firing rate, failing to generate response time-locked to stimulus. Medial neurons producing a response time-locked to the stimulus showed equal sensitivity to stimulation of midbrain and bulbar LT and very little reaction to IS stimulation. Medial neurons with a response not time-locked to stimuli together with lateral neurons were most receptive to input from the bulbar LS, less sensitive to stimulation of the midbrain LS, and least responsive of all to IS stimulation. Convergence between influences from midbrain and bulbar LS was the same in neurons of all populations. The part played by different neuronal populations in initiation and cessation of locomotion is discussed.Institute for Research into Information Transmission, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 23, No. 3, pp. 297–306, May–June, 1991.