Gain modulation in the central nervous system: where behavior, neurophysiology, and computation meet

Cortical region interactions and the functional role of apical dendrites

The basal and distal apical dendrites of pyramidal cells occupy distinct cortical layers and are targeted by axons originating in different cortical regions. Hence, apical and basal dendrites receive information from distinct sources. Physiological evidence suggests that this anatomically observed segregation of input sources may have functional significance. This possibility has been explored in various connectionist models that employ neurons with functionally distinct apical and basal compartments. A neuron in which separate sets of inputs can be integrated independently has the potential to operate in a variety of ways not possible for the conventional neuron model, in which all inputs are treated equally. This article thus considers how functionally distinct apical and basal dendrites can contribute to the information-processing capacities of single neurons and, in particular, how information from different cortical regions could have disparate effects on neural activity and learning.

Enhancement of visual responsiveness by spontaneous local network activity in vivo

Spontaneous activity within local circuits affects the integrative properties of neurons and networks. We have previously shown that neocortical network activity exhibits a balance between excitatory and inhibitory synaptic potentials, and such activity has significant effects on synaptic transmission, action potential generation, and spike timing. However, whether such activity facilitates or reduces sensory responses has yet to be clearly determined. We examined this hypothesis in the primary visual cortex in vivo during slow oscillations in ketamine-xylazine anesthetized cats. We measured network activity (Up states) with extracellular recording, while simultaneously recording postsynaptic potentials (PSPs) and action potentials in nearby cells. Stimulating the receptive field revealed that spiking responses of both simple and complex cells were significantly enhanced (>2-fold) during network activity, as were spiking responses to intracellular injection of varying amplitude artificial conductance stimuli. Visually evoked PSPs were not significantly different in amplitude during network activity or quiescence; instead, spontaneous depolarization caused by network activity brought these evoked PSPs closer to firing threshold. Further examination revealed that visual responsiveness was gradually enhanced by progressive membrane potential depolarization. These spontaneous depolarizations enhanced responsiveness to stimuli of varying contrasts, resulting in an upward (multiplicative) scaling of the contrast response function. Our results suggest that small increases in ongoing balanced network activity that result in depolarization may provide a rapid and generalized mechanism to control the responsiveness (gain) of cortical neurons, such as occurs during shifts in spatial attention.

Close coordination between recognition and action: Really two separate streams?

Somewhat in contrast to their proposal of two separate somatosensory streams, Dijkerman & de Haan (D&dH) propose that tactile recognition involves active manual exploration, and therefore involves parietal cortex. I argue that interactions from perception for action to object recognition can be found also in vision. Furthermore, there is evidence that perception for action and perception for recognition rely on similar processing principles.

fMRI reveals a preference for near viewing in the human parieto-occipital cortex

Posterior parietal cortex in primates contains several functional areas associated with visual control of body effectors (e.g., arm, hand and head) which contain neurons tuned to specific depth ranges appropriate for the effector. For example, the macaque ventral intraparietal area (VIP) is involved in head movements and is selective for motion in near-space around the head. We used functional magnetic resonance imaging to examine activation in the putative human VIP homologue (pVIP), as well as parietal and occipital cortex, as a function of viewing distance when multiple cues to target depth were available (Expt 1) and when only oculomotor cues were available (Expt 2). In Experiment 1, subjects viewed stationary or moving disks presented at three distances (with equal retinal sizes). Although activation in pVIP showed no preference for any particular spatial range, the dorsal parieto-occipital sulcus (dPOS) demonstrated a near-space preference, with activation highest for near viewing, moderate for arm's length viewing, and lowest for far viewing. In Experiment 2, we investigated whether the near response alone (convergence of the eyes, accommodation of the lens and pupillary constriction) was sufficient to elicit this same activation pattern. Subjects fixated lights presented at three distances which were illuminated singly (with luminance and visual angle equated across distances). dPOS displayed the same gradient of activation (Near>Medium>Far) as that seen in Experiment 1, even with reduced cues to depth. dPOS seems to reflect the status of the near response (perhaps driven largely by vergence angle) and may provide areas in the dorsal visual stream with spatial information useful for guiding actions toward targets in depth.

Gating information by two-state membrane potential fluctuations

Two-state voltage fluctuations between a hyperpolarized down-state and a depolarized up-state have been observed experimentally in a wide variety of neurons across brain regions. Using a biophysical model, we show that synaptic input by NMDA receptors can cause such membrane potential fluctuations. In this model, when a neuron is driven by two input pathways with different AMPA/NMDA receptor content, the NMDA-rich input causes up-state transitions, whereas the AMPA-rich input generates spikes only in the up-state. Therefore the NMDA-rich pathway can gate input from an AMPA pathway in an all-or-none fashion by switching between different membrane potential states. Furthermore, once in the up-state, the NMDA-rich pathway multiplicatively increases the gain of a neuron responding to AMPA-rich input. This proposed mechanism for two-state fluctuations directly suggests specific computations, such as gating and gain modulation based on the distinct receptor composition of different neuronal pathways. The dynamic gating of input by up- and down-states may be an elementary operation for the selective routing of signals in neural circuits, which may explain the ubiquity of two-state fluctuations across brain regions.

Multiplicative computation in the vestibulo-ocular reflex (VOR)

Multiplicative computation is a basic operation that is crucial for neural information processing, but examples of multiplication by neural pathways that perform well-defined sensorimotor transformations are scarce. Here in behaving monkeys, we identified a multiplication of vestibular and eye position signals in the vestibulo-ocular reflex (VOR). Monkeys were trained to maintain fixation on visual targets at different horizontal locations and received brief unilateral acoustic clicks (1 ms, rarefaction, 85 approximately 110 db NHL) that were delivered into one of their external ear canals. We found that both the click-evoked horizontal eye movement responses and the click-evoked neuronal responses of the abducens neurons exhibited linear dependencies on horizontal conjugate eye position, indicating that the interaction of vestibular and horizontal conjugate eye position was multiplicative. Latency analysis further indicated that the site of the multiplication was within the direct VOR pathways. Based on these results, we propose a novel neural mechanism that implements the VOR gain modulation by fixation distance and gaze eccentricity. In this mechanism, the vestibular signal from a single labyrinth interacts multiplicatively with the position signals of each eye (Principle of Multiplication). These effects, however, interact additively with the other labyrinth (Principle of Addition). Our analysis suggests that the new mechanism can implement the VOR gain modulation by fixation distance and gaze eccentricity within the direct VOR pathways.

Does the brain have a baseline? Why we should be resisting a rest

In the last few years, the notion that the brain has a default or intrinsic mode of functioning has received increasing attention. The idea derives from observations that a consistent network of brain regions shows high levels of activity when no explicit task is performed and participants are asked simply to rest. The importance of this putative "default mode" is asserted on the basis of the substantial energy demand associated with such a resting state and of the suggestion that rest entails a finely tuned balance between metabolic demand and regionally regulated blood supply. These observations, together with the fact that the default network is more active at rest than it is in a range of explicit tasks, have led some to suggest that it reflects an absolute baseline, one that must be understood and used if we are to develop a comprehensive picture of brain functioning. Here, we examine the assumptions that are generally made in accepting the importance of the "default mode". We question the value, and indeed the interpretability, of the study of the resting state and suggest that observations made under resting conditions have no privileged status as a fundamental metric of brain functioning. In doing so, we challenge the utility of studies of the resting state in a number of important domains of research.

Effects of spatial attention on contrast response functions in macaque area V4

Previous single-unit studies of visual cortex have reported that spatial attention modulates responses to different orientations and directions proportionally, such that it does not change the width of tuning functions for these properties. Other studies have suggested that spatial attention causes a leftward shift in contrast response functions, such that its effects on responses to stimuli of different contrasts are not proportional. We have further explored the effects of attention on stimulus-response functions by measuring the responses of 131 individual V4 neurons in two monkeys while they did a task that controlled their spatial attention. Each neuron was tested with a set of stimuli that spanned complete ranges of orientation and contrast during different states of attention. Consistent with earlier reports, attention scaled responses to preferred and nonpreferred orientations proportionally. However, we did not find compelling evidence that the effects were best described by a leftward shift of the contrast response function. The modulation of neuronal responses by attention was well described by either a leftward shift or proportional scaling of the contrast response function. Consideration of differences in experimental design and analysis that may have contributed to this discrepancy suggests that it was premature to exclude a proportional scaling of responses to different contrasts by attention in favor of a leftward shift of contrast response functions. The current results reopen the possibility that the effects of attention on stimulus-response functions are well described by a single proportional increase in a neuron's response to all stimuli.

The role of action representations in visual object recognition

It is typically assumed that perception for action and object recognition are subserved by functionally and neuroanatomically distinct processing streams in the brain. However, recent evidence challenges this classical view and suggests an interaction between both visual processing streams. While previous studies showed an influence of object perception on action-related tasks, we investigated whether action representations facilitate visual object recognition. In order to address this question, two briefly displayed masked objects were sequentially presented, either affording congruent or incongruent motor interactions. We found superior naming accuracy for object pairs with congruent as compared to incongruent motor interactions (Experiment 1). This action priming effect indicates that action representations can facilitate object recognition. We further investigated the nature of the representations underlying this action priming effect. The effect was absent when the prime stimulus was presented as a word (Experiment 2). Thus, the action priming effect seems to rely on action representations specified by visual object information. Our findings suggest that processes of object-directed action influence object recognition.

A model that integrates eye velocity commands to keep track of smooth eye displacements

Past results have reported conflicting findings on the oculomotor system's ability to keep track of smooth eye movements in darkness. Whereas some results indicate that saccades cannot compensate for smooth eye displacements, others report that memory-guided saccades during smooth pursuit are spatially correct. Recently, it was shown that the amount of time before the saccade made a difference: short-latency saccades were retinotopically coded, whereas long-latency saccades were spatially coded. Here, we propose a model of the saccadic system that can explain the available experimental data. The novel part of this model consists of a delayed integration of efferent smooth eye velocity commands. Two alternative physiologically realistic neural mechanisms for this integration stage are proposed. Model simulations accurately reproduced prior findings. Thus, this model reconciles the earlier contradictory reports from the literature about compensation for smooth eye movements before saccades because it involves a slow integration process.

Correlates of measures of voluntary force with the functional state of the motor system

Oscillation spectra were analyzed for prolonged isometric force recorded in healthy subjects of three age groups. Changes in the distributions of spectral components of the oscillations in force were noted, along with differences in the distributions of spectral density as exhaustion developed in the age groups. The amplitude-frequency ranges of changes in the spectral densities of oscillations in force characterized the activity at the suprasegmental and segmental levels of the motor system which support the voluntary control and automatic regulation of posture during the performance of movements. Correlates of the functional state of the motor system are discussed in terms of the voluntary and involuntary components of control. A significant increase in activity in the central structures of the movement control system was seen with the development of exhaustion, along with decreases in the frequency range of the activity of subcortical structures with age.

Rapid reshaping of human motor generalization

People routinely learn how to manipulate new tools or make new movements. This learning requires the transformation of sensed movement error into updates of predictive neural control. Here, we demonstrate that the richness of motor training determines not only what we learn but how we learn. Human subjects made reaching movements while holding a robotic arm whose perturbing forces changed directions at the same rate, twice as fast, or four times as fast as the direction of movement, therefore exposing subjects to environments of increasing complexity across movement space. Subjects learned all three environments and learned the low- and medium-complexity environments equally well. We found that subjects lessened their movement-by-movement adaptation and narrowed the spatial extent of generalization to match the environmental complexity. This result demonstrated that people can rapidly reshape the transformation of sense into motor prediction to best learn a new movement task. We then modeled this adaptation using a neural network and found that, to mimic human behavior, the modeled neuronal tuning of movement space needed to narrow and reduce gain with increased environmental complexity. Prominent theories of neural computation have hypothesized that neuronal tuning of space, which determines generalization, should remained fixed during learning so that a combination of neuronal outputs can underlie adaptation simply and flexibly. Here, we challenge those theories with evidence that the neuronal tuning of movement space changed within minutes of training.

Deterministic multiplicative gain control with active dendrites

Multiplicative gain control is a vital component of many theoretical analyses of neural computations, conferring the ability to scale neuronal firing rate in response to synaptic inputs. Many theories of gain control in single cells have used precisely balanced noisy inputs. Such noisy inputs can degrade signal processing. We demonstrate a deterministic method for the control of gain without the use of noise. We show that a depolarizing afterpotential (DAP), arising from active dendritic spike backpropagation, leads to a multiplicative increase in gain. Reduction of DAP amplitude by dendritic inhibition dilutes the multiplicative effect, allowing for divisive scaling of the firing rate. In contrast, somatic inhibition acts in a subtractive manner, allowing spatially distinct inhibitory inputs to perform distinct computations. The simplicity of this mechanism and the ubiquity of its elementary components suggest that many cell types have the potential to display a dendritic division of neuronal output.

Motor-maps, navigation and implicit space representation in the hippocampus

Multiple sensory-motor maps located in the brainstem and the cortex are involved in spatial orientation. Guiding movements of eyes, head, neck and arms they provide an approximately linear relation between target distance and motor response. This involves especially the superior colliculus in the brainstem and the parietal cortex. There, the natural frame of reference follows from the retinal representation of the environment. A model of navigation is presented that is based on the modulation of activity in those sensory-motor maps. The actual mechanism chosen was gain-field modulation, a process of multimodal integration that has been demonstrated in the parietal cortex and superior colliculus, and was implemented as attraction to visual cues (colour). Dependent on the metric of the sensory-motor map, the relative attraction to these cues implemented as gain field modulation and their position define a fixed point attractor on the plane for locomotive behaviour. The actual implementation used Kohonen-networks in a variant of reinforcement learning that are well suited to generate such topographically organized sensory-motor maps with roughly linear visuo-motor response characteristics. In the following, it was investigated how such an implicit coding of target positions by gain-field parameters might be represented in the hippocampus formation and under what conditions a direction-invariant space representation can arise from such retinotopic representations of multiple cues. Information about the orientation in the plane--as could be provided by head direction cells--appeared to be necessary for unambiguous space representation in our model in agreement with physiological experiments. With this information, Gauss-shaped "place-cells" could be generated, however, the representation of the spatial environment was repetitive and clustered and single cells were always tuned to the gain-field parameters as well.

Neuronal networks: flip-flops in the brain

Neuronal activity can rapidly flip-flop between stable states. Although these semi-stable states can be generated through interactions of neuronal networks, it is now known that they can also occur in vivo through intrinsic ionic currents.

Gain control by concerted changes in I(A) and I(H) conductances

Stability of intrinsic electrical activity and modulation of input-output gain are both important for neuronal information processing. It is therefore of interest to define biologically plausible parameters that allow these two features to coexist. Recent experiments indicate that in some biological neurons, the stability of spontaneous firing can arise from coregulated expression of the electrophysiologically opposing I(A) and I(H) currents. Here, I show that such balanced changes in I(A) and I(H) dramatically alter the slope of the relationship between the firing rate and driving current in a Hodgkin-Huxley-type model neuron. Concerted changes in I(A) and I(H) can thus control neuronal gain while preserving intrinsic activity.

Intercollicular commissural projections modulate neuronal responses in the inferior colliculus

The right and left inferior colliculi (ICs) in the auditory midbrain are connected to one another by a bundle of fibres, the commissure of the IC. Previous studies show that this commissural projection connects corresponding frequency regions in the two sides and originates mainly from excitatory neurons, although some studies suggest a smaller number of GABAergic inhibitory neurons may also project via the commissure. Although the commissure of the IC is a major pathway connecting the most important nuclei of the auditory tectum, little is known about its functional significance. To investigate its role in auditory processing in the rat, we recorded sound-evoked responses of single neurons in one IC while injecting kynurenic acid into a corresponding region of the opposite IC. This procedure enabled us to block reversibly excitation of commissural projections to the recorded IC. The changes in the neural responses when input from the opposite IC was blocked are consistent with the commissural projection exerting both an excitatory and an inhibitory influence. The inhibition could be accounted for by monosynaptic or disynaptic connections. The responses to both monaural and binaural stimulation were affected, and the effects were proportionately greater at near-threshold sound levels. The results suggest that one function of the commissure of the IC may be to modulate the response gain of IC neurons to acoustic stimulation.

A Temporal Stability Approach to Position and Attention-Shift-Invariant Recognition

Incorporation of visual-related self-action signals can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by eye movements and covert attention shifts. Training of the network is controlled by signals associated with eye movements and covert attention shifting. A temporal perceptual stability constraint is used to drive the output of the network toward remaining constant across temporal sequences of saccadicmotions and covert attention shifts. We use a four-layer neural network model to perform the position-invariant extraction of local features and temporal integration of invariant presentations of local features in a bottom-up structure. We present results on both simulated data and real images to demonstrate that our network can acquire both position and attention shift invariance.

A feedback model of visual attention

Feedback connections are a prominent feature of cortical anatomy and are likely to have a significant functional role in neural information processing. We present a neural network model of cortical feedback that successfully simulates neurophysiological data associated with attention. In this domain, our model can be considered a more detailed, and biologically plausible, implementation of the biased competition model of attention. However, our model is more general as it can also explain a variety of other top-down processes in vision, such as figure/ground segmentation and contextual cueing. This model thus suggests that a common mechanism, involving cortical feedback pathways, is responsible for a range of phenomena and provides a unified account of currently disparate areas of research.

Fast remapping of sensory stimuli onto motor actions on the basis of contextual modulation

Higher organisms can establish complex associations between sensory events and motor responses. More remarkable than their complexity, however, is that the resulting sensory-motor maps can be selectively interchanged. For example, a person who speaks English and Spanish can read aloud "con once, sin once," going effortlessly from one language to the other. What is the neural basis of this capacity? Here, a network model is presented in which multiple maps between sensory stimuli and motor actions are possible, but only one of them, depending on behavioral context, is implemented at any given time. The key is a nonlinear representation in which the gain of sensory responses is regulated by context information. Neuronal responses can indeed show variations in gain, as has been documented in the case of proprioceptive signals such as eye and head position, which can modulate visually triggered activity. However, in contrast to these, the contextual cues used here need not bear any relationship to the physical attributes of the stimuli; in particular, spatial location is irrelevant. The model thus postulates the existence of sensory neurons that are nonlinearly modulated by arbitrary context signals, a plausible and testable prediction. The proposed mechanism allows a network of neurons to effectively change the functional connectivity between its inputs and outputs and may partially explain how animals can quickly adapt their behavior to varying environmental conditions.

Regulation of neuromodulator receptor efficacy—implications for whole-neuron and synaptic plasticity

Membrane receptors for neuromodulators (NM) are highly regulated in their distribution and efficacy-a phenomenon which influences the individual cell's response to central signals of NM release. Even though NM receptor regulation is implicated in the pharmacological action of many drugs, and is also known to be influenced by various environmental factors, its functional consequences and modes of action are not well understood. In this paper we summarize relevant experimental evidence on NM receptor regulation (specifically dopamine D1 and D2 receptors) in order to explore its significance for neural and synaptic plasticity. We identify the relevant components of NM receptor regulation (receptor phosphorylation, receptor trafficking and sensitization of second-messenger pathways) gained from studies on cultured cells. Key principles in the regulation and control of short-term plasticity (sensitization) are identified, and a model is presented which employs direct and indirect feedback regulation of receptor efficacy. We also discuss long-term plasticity which involves shifts in receptor sensitivity and loss of responsivity to NM signals. Finally, we discuss the implications of NM receptor regulation for models of brain plasticity and memorization. We emphasize that a realistic model of brain plasticity will have to go beyond Hebbian models of long-term potentiation and depression. Plasticity in the distribution and efficacy of NM receptors may provide another important source of functional plasticity with implications for learning and memory.

Background synaptic activity as a switch between dynamical states in a network

A bright red light may trigger a sudden motor action in a driver crossing an intersection: stepping at once on the brakes. The same red light, however, may be entirely inconsequential if it appears, say, inside a movie theater. Clearly, context determines whether a particular stimulus will trigger a motor response, but what is the neural correlate of this? How does the nervous system enable or disable whole networks so that they are responsive or not to a given sensory signal? Using theoretical models and computer simulations, I show that networks of neurons have a built-in capacity to switch between two types of dynamic state: one in which activity is low and approximately equal for all units, and another in which different activity distributions are possible and may even change dynamically. This property allows whole circuits to be turned on or off by weak, unstructured inputs. These results are illustrated using networks of integrate-and-fire neurons with diverse architectures. In agreement with the analytic calculations, a uniform background input may determine whether a random network has one or two stable firing levels; it may give rise to randomly alternating firing episodes in a circuit with reciprocal inhibition; and it may regulate the capacity of a center-surround circuit to produce either self-sustained activity or traveling waves. Thus, the functional properties of a network may be drastically modified by a simple, weak signal. This mechanism works as long as the network is able to exhibit stable firing states, or attractors.

Correlated neuronal activity and the flow of neural information

For years we have known that cortical neurons collectively have synchronous or oscillatory patterns of activity, the frequencies and temporal dynamics of which are associated with distinct behavioural states. Although the function of these oscillations has remained obscure, recent experimental and theoretical results indicate that correlated fluctuations might be important for cortical processes, such as attention, that control the flow of information in the brain.