Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

This protocol outlines large-scale reconstructions of neurons combined with the use of independent and unbiased clustering analyses to create a ...

Geisel School of Medicine at Dartmouth

A shrewd insight for vision.

Layer 5 neurons in primary visual cortex make putative reciprocal feedback connections to the superficial layers. To test this hypothesis, we employed scanning laser photostimulation combined with intracellular dye injection to examine local functional excitatory inputs to and axonal projections from individual layer 5 neurons in brain slices from monkey V1. In contrast with previous studies of other V1 neurons, layer 5 neurons received significant input from nearly all of the cortical layers, suggesting individual layer 5 cells integrate information from a broad range of input sources. Nevertheless relative strengths of laminar inputs varied across neurons. Cluster analysis of relative strength of laminar inputs to individual layer 5 neurons revealed four discrete clusters representing recurring input patterns; each cluster included both excitatory and inhibitory neurons. Twenty-five of 40 layer 5 neurons fell into two clusters, both characterized by very strong input from superficial layers. These input patterns are consistent with layer 5 neurons providing feedback to superficial layers. The remaining 15 neurons received stronger input from deep layers. Differences in input from layer 4Calpha versus 4Cbeta also suggest specific associations of the magnocellular and parvocellular visual pathways, with populations receiving stronger input from deep versus superficial cortical layers.

Laminar patterns of local excitatory input to layer 5 neurons in macaque primary visual cortex.

Neurons in the lateral geniculate nucleus (LGN) not only provide feedforward input to primary visual cortex (V1), but also receive robust feedback from the cortex. Accordingly, visual processing in the LGN is continuously influenced by previous patterns of activity. This study examines the temporal properties of feedforward and feedback pathways between the LGN and V1 in the macaque monkey to provide a lower bound on how quickly the cortex can influence the LGN. In so doing, we identified a subclass of corticogeniculate neurons that receives direct, suprathreshold input from the LGN that is similar in latency to that directed to other recipient neurons (4.2 +/- 0.4 vs 4.0 +/- 0.2 ms). These neurons also provide feedback to the LGN that is significantly shorter in latency than that supplied by corticogeniculate neurons lacking LGN input (5.1 +/- 1.3 vs 11.1 +/- 2.3 ms, respectively). Across our sample of corticogeniculate neurons, the shortest combined visual response latency and feedback latency was 37 ms (mean, 52.5 +/- 3.8 ms), indicating that visual signals can rapidly travel from the periphery to the cortex and back to the LGN.

A fast, reciprocal pathway between the lateral geniculate nucleus and visual cortex in the macaque monkey.

This study examines the temporal properties of geniculocortical and corticogeniculate (CG) pathways that link the lateral geniculate nucleus (LGN) and primary visual cortex in the ferret. Using electrical stimulation in the LGN to evoke action potentials in geniculocortical and CG axons, results show that conduction latencies are significantly faster in geniculocortical neurons than in CG neurons. Within each pathway, axonal latency and visual physiology support the view of sub-classes of neurons. By examining the timing of visual responses and the latency of CG feedback, estimates indicate that visual information can reach the cortex and return to the LGN as early as 60 msec following the onset of a visual stimulus. These findings place constraints on the functional role of corticogeniculate feedback for visual processing.

Temporal properties of feedforward and feedback pathways between the thalamus and visual cortex in the ferret.

Although it is now generally accepted that the thalamus is more than a simple relay of sensory signals to the cortex, we are just beginning to gain an understanding of how corticothalamic feedback influences sensory processing. Results from an increasing number of studies across sensory systems and different species reveal effects of feedback both on the receptive fields of thalamic neurons and on the transmission of sensory information between the thalamus and cortex. Importantly, these studies demonstrate that the cortico-thalamic projection cannot be viewed in isolation, but must be considered as an integral part of a thalamo-corticothalamic circuit which intimately interconnects the thalamus and cortex for sensory processing.

Emerging views of corticothalamic function.

Thalamocortical communication is a dynamic process influenced by both presynaptic and postsynaptic mechanisms. In this study, we recorded single-unit responses from cortical neurons that received direct input from the lateral geniculate nucleus (LGN) to address the question of whether prior patterns of cortical activity affect the ability of LGN inputs to drive cortical responses. By examining the ongoing activity that preceded the arrival of electrically evoked spikes from the LGN, we identified a number of activity patterns that were predictive of suprathreshold communication. Namely, cortical neurons were more likely to respond to LGN stimulation when their activity levels increased to 30-40Hz and/or their activity displayed rhythmic patterns (30 ms intervals) with increased power in the gamma frequency band. Cortical neurons were also more likely to respond to LGN stimulation when their activity increased 30-40 ms prior to stimulation, suggesting that the phase of gamma activity also contributes to geniculocortical communication. Based on these results, we conclude that ongoing activity in the cortex is not random, but rather organized in a manner that can influence the dynamics of thalamocortical communication.

Cortical activity influences geniculocortical spike efficacy in the macaque monkey.

Although corticothalamic feedback is ubiquitous across species and modalities, its role in sensory processing is unclear. This study provides a detailed description of the visual physiology of corticogeniculate neurons in the primate. Using electrical stimulation to identify corticogeniculate neurons, we distinguish three groups of neurons with response properties that closely resemble those of neurons in the magnocellular, parvocellular, and koniocellular layers of their target structure, the lateral geniculate nucleus (LGN) of the thalamus. Our results indicate that corticogeniculate feedback in the primate is stream specific, and provide strong evidence in support of the view that corticothalamic feedback can influence the transmission of sensory information from the thalamus to the cortex in a stream-selective manner.

Parallel processing in the corticogeniculate pathway of the macaque monkey.

Periodic activity patterns or oscillations within the gamma frequency band (20-80 Hz) have been implicated in sensory processing and cognition in many areas of the cerebral cortex, including primary visual cortex (V1). Although periodic activity appears to be a hallmark of cortical neurons, little is known about the dynamics of these activity patterns as signals progress within local cortical circuits. This study compares the strength of periodic activity between neurons in the input and output stages of cortical processing - neurons in layers 4 and 6 - of V1 in the alert macaque monkey. Our results demonstrate that while both populations of neurons display significant gamma-band activity, this activity increases from the input to output layers of the cortex. These data suggest that local cortical circuits enhance periodic activity within a cortical area.

Modulation of gamma-band activity across local cortical circuits.

Neurons in the deepest layer of mammalian cerebral cortex are morphologically and physiological diverse and are situated in a strategic position to modulate neuronal activity locally and in other structures. The variety of neuronal circuits within which layer 6 neurons participate differs across species and cortical regions. However even amidst this diversity, common organizational features emerge. Examination of the anatomical and physiological characteristics of different classes of layer 6 neuron, each specialized to participate in distinct circuits, provides insight into the functional contributions of layer 6 neurons toward cortical information processing.

Organizing principles of cortical layer 6.

Corticogeniculate neurones make more synapses in the lateral geniculate nucleus (LGN) than retinal ganglion cells, yet we know relatively little about the functions of corticogeniculate feedback for visual processing. In primates, feedforward projections from the retina to the LGN and from the LGN to primary visual cortex are organized into anatomically and physiologically distinct parallel pathways. Recent work demonstrates a close relationship between these parallel streams of feedforward projections and the corticogeniculate feedback pathway. Here, we review the evidence for stream-specific feedback in the primate and consider the implications of parallel streams of feedback for vision.

Corticogeniculate feedback and visual processing in the primate.

The cerebral cortex is a vastly complex structure consisting of multiple distinct populations of neurons residing in functionally specialized cortical compartments. A fundamental goal in systems neuroscience is to understand the interactions among cortical neurons and their relationship to behavior. It is hypothesized that dynamic activity patterns, such as oscillations in global neuronal activity, could span large, heterogeneous populations of cortical neurons in such a manner as to bind together the activity of otherwise disparate cortical networks. Little is known about the mechanisms by which such global oscillatory patterns entrain cortical networks, or the contribution of such activity patterns to cortical function. An important step toward elucidating the role of such patterned activity in cortical information processing is understanding these interactions at the local circuit level. Here, we highlight recent findings that provide insight into how dynamic activity patterns affect specific neuronal populations and circuits.

Patterned Activity within the Local Cortical Architecture.

Most neurons in primary visual cortex (V1) are selective for stimulus size, a property with important implications for salient feature detection. Size selectivity involves dynamic interactions between neuronal circuits that establish the classical (center) and extraclassical (surround) of a neuron's receptive field. Although much is known about the tuning properties and stimulus selectivity of the center and surround subunits, relatively little is known about how these subunits interact to achieve size selectivity. To address this question, we examined the temporal dynamics of size selectivity in two classes of pyramidal neurons at similar hierarchical processing stages in V1 of alert monkeys. These two classes were comprised of neurons in cortical layer 6 with identified projections to the lateral geniculate nucleus. While both neuronal groups displayed comparable levels of size selectivity, the temporal dynamics of their tuning differed significantly. We compared the size tuning profiles of each cell type with a series of sum-of-Gaussian models and discovered that the receptive fields of neurons with fast-conducting axons contained an excitatory center and a suppressive surround with similar onset timing. In contrast, neurons with slow-conducting axons used two center components-an early wide-field component and a delayed narrow-field component that increased activity-in addition to the surround component. The early, wide-field component represents a novel mechanism for cortical neurons to integrate contextual information. These results demonstrate that size tuning in cortical neurons is established via multiple unique mechanisms, dictated by the rich circuit architecture in which neurons are embedded.

Distinct mechanisms for size tuning in primate visual cortex.

Attention is a critical component of perception. However, the mechanisms by which attention modulates neuronal communication to guide behaviour are poorly understood. To elucidate the synaptic mechanisms of attention, we developed a sensitive assay of attentional modulation of neuronal communication. In alert monkeys performing a visual spatial attention task, we probed thalamocortical communication by electrically stimulating neurons in the lateral geniculate nucleus of the thalamus while simultaneously recording shock-evoked responses from monosynaptically connected neurons in primary visual cortex. We found that attention enhances neuronal communication by increasing the efficacy of presynaptic input in driving postsynaptic responses, by increasing synchronous responses among ensembles of postsynaptic neurons receiving independent input, and by decreasing redundant signals between postsynaptic neurons receiving common input. The results demonstrate that attention finely tunes neuronal communication at the synaptic level by selectively altering synaptic weights, enabling enhanced detection of salient events in the noisy sensory environment.

Attention enhances synaptic efficacy and the signal-to-noise ratio in neural circuits.

Oscillatory synchronization of neuronal activity has been proposed as a mechanism to modulate effective connectivity between interacting neuronal populations. In the visual system, oscillations in the gamma-frequency range (30-100 Hz) are thought to subserve corticocortical communication. To test whether a similar mechanism might influence subcortical-cortical communication, we recorded local field potential activity from retinotopically aligned regions in the lateral geniculate nucleus (LGN) and primary visual cortex (V1) of alert macaque monkeys viewing stimuli known to produce strong cortical gamma-band oscillations. As predicted, we found robust gamma-band power in V1. In contrast, visual stimulation did not evoke gamma-band activity in the LGN. Interestingly, an analysis of oscillatory phase synchronization of LGN and V1 activity identified synchronization in the alpha (8-14 Hz) and beta (15-30 Hz) frequency bands. Further analysis of directed connectivity revealed that alpha-band interactions mediated corticogeniculate feedback processing, whereas beta-band interactions mediated geniculocortical feedforward processing. These results demonstrate that although the LGN and V1 display functional interactions in the lower frequency bands, gamma-band activity in the alert monkey is largely an emergent property of cortex.

Simultaneous recordings from the primary visual cortex and lateral geniculate nucleus reveal rhythmic interactions and a cortical source for γ-band oscillations.

Corticothalamic circuits are essential for reciprocal information exchange between the thalamus and cerebral cortex. Nevertheless, the role of corticothalamic circuits in sensory processing remains a mystery. In the visual system, afferents from retina to the lateral geniculate nucleus (LGN) and from LGN to primary visual cortex (V1) are organized into functionally distinct parallel processing streams. Physiological evidence suggests corticogeniculate feedback may be organized into parallel streams; however, little is known about the diversity of corticogeniculate neurons, their local computations, or the structure-function relationship among corticogeniculate neurons. We used a virus-mediated approach to label and reconstruct the complete dendritic and local axonal arbors of identified corticogeniculate neurons in the macaque monkey. Our results reveal morphological substrates for parallel streams of corticogeniculate feedback based on distinct classes of neurons in V1 and V2. These results support the hypothesis that distinct populations of feedback neurons provide independent and unique information to the LGN.

Morphological Substrates for Parallel Streams of Corticogeniculate Feedback Originating in Both V1 and V2 of the Macaque Monkey.

The thalamic reticular nucleus (TRN) is a unique brain structure at the interface between the thalamus and the cortex. Because the TRN receives bottom-up sensory input and top-down cortical input, it could serve as an integration hub for sensory and cognitive signals. Functional evidence supports broad roles for the TRN in arousal, attention, and sensory selection. How specific circuits connecting the TRN with sensory thalamic structures implement these functions is not known. The structural organization and function of the TRN is particularly interesting in the context of highly organized sensory systems, such as the primate visual system, where neurons in the retina and dorsal lateral geniculate nucleus of the thalamus (dLGN) are morphologically and physiologically distinct and also specialized for processing particular features of the visual environment. To gain insight into the functional relationship between the visual sector of the TRN and the dLGN, we reconstructed a large number of TRN neurons that were retrogradely labeled following injections of rabies virus expressing enhanced green fluorescent protein (EGFP) into the dLGN. An independent cluster analysis, based on 10 morphological metrics measured for each reconstructed neuron, revealed three clusters of TRN neurons that differed in cell body shape and size, dendritic arborization patterns, and medial-lateral position within the TRN. TRN dendritic and axonal morphologies are inconsistent with visual stream-specific projections to the dLGN. Instead, TRN neuronal organization could facilitate transmission of global arousal and/or cognitive signals to the dLGN with retinotopic precision that preserves specialized processing of foveal versus peripheral visual information. J. Comp. Neurol. 525:1273-1290, 2017. © 2016 Wiley Periodicals, Inc.

Morphology of visual sector thalamic reticular neurons in the macaque monkey suggests retinotopically specialized, parallel stream-mixed input to the lateral geniculate nucleus.

Farran Briggs

Physiology & Neurobiology

Geisel School of Medicine at Dartmouth

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Farran Briggs

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Physiology & Neurobiology

Geisel School of Medicine at Dartmouth

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Physiology & Neurobiology