Receptive Field Changes Research Articles

Changes in population receptive fields following artificial scotoma; remapping or nonlinear responses?

Changes in population receptive fields following artificial scotoma; remapping or nonlinear responses?

Poster Session I: Gain, not changes in spatial receptive field properties, improves task performance in a neural network attention model.

Attention allows us to focus sensory processing on behaviorally relevant aspects of the visual world. One potential mechanism of attention is a change in the gain of sensory responses. However, changing gain at early stages could have multiple downstream consequences for visual processing. Which, if any, of these effects can account for the benefits of attention for detection and discrimination? Using a model of primate visual cortex we document how a Gaussian-shaped gain modulation results in changes to spatial tuning properties. Forcing the model to use only these changes failed to produce any benefit in task performance. Instead, we found that gain alone was both necessary and sufficient to explain category detection and discrimination during attention. Our results show how gain can give rise to changes in receptive fields which are not necessary for enhancing task performance.

Gain, not concomitant changes in spatial receptive field properties, improves task performance in a neural network attention model.

Attention allows us to focus sensory processing on behaviorally relevant aspects of the visual world. One potential mechanism of attention is a change in the gain of sensory responses. However, changing gain at early stages could have multiple downstream consequences for visual processing. Which, if any, of these effects can account for the benefits of attention for detection and discrimination? Using a model of primate visual cortex we document how a Gaussian-shaped gain modulation results in changes to spatial tuning properties. Forcing the model to use only these changes failed to produce any benefit in task performance. Instead, we found that gain alone was both necessary and sufficient to explain category detection and discrimination during attention. Our results show how gain can give rise to changes in receptive fields which are not necessary for enhancing task performance.

Bilateral increase in MEG planar gradients prior to saccade onset

Every time we move our eyes, the retinal locations of objects change. To distinguish the changes caused by eye movements from actual external motion of the objects, the visual system is thought to anticipate the consequences of eye movements (saccades). Single neuron recordings have indeed demonstrated changes in receptive fields before saccade onset. Although some EEG studies with human participants have also demonstrated a pre-saccadic increased potential over the hemisphere that will process a stimulus after a saccade, results have been mixed. Here, we used magnetoencephalography to investigate the timing and lateralization of visually evoked planar gradients before saccade onset. We modelled the gradients from trials with both a saccade and a stimulus as the linear combination of the gradients from two conditions with either only a saccade or only a stimulus. We reasoned that any residual gradients in the condition with both a saccade and a stimulus must be uniquely linked to visually-evoked neural activity before a saccade. We observed a widespread increase in residual planar gradients. Interestingly, this increase was bilateral, showing activity both contralateral and ipsilateral to the stimulus, i.e. over the hemisphere that would process the stimulus after saccade offset. This pattern of results is consistent with predictive pre-saccadic changes involving both the current and the future receptive fields involved in processing an attended object, well before the start of the eye movement. The active, sensorimotor coupling of vision and the oculomotor system may underlie the seamless subjective experience of stable and continuous perception.

Modelling scotoma-induced changes in population receptive fields using divisive normalisation

Modelling scotoma-induced changes in population receptive fields using divisive normalisation

Pitfalls in post hoc analyses of population receptive field data

Data binning involves grouping observations into bins and calculating bin-wise summary statistics. It can cope with overplotting and noise, making it a versatile tool for comparing many observations. However, data binning goes awry if the same observations are used for binning (selection) and contrasting (selective analysis). This creates circularity, biasing noise components and resulting in artifactual changes in the form of regression towards the mean. Importantly, these artifactual changes are a statistical necessity. Here, we use (null) simulations and empirical repeat data to expose this flaw in the scope of post hoc analyses of population receptive field data. In doing so, we reveal that the type of data analysis, data properties, and circular data cleaning are factors shaping the appearance of such artifactual changes. We furthermore highlight that circular data cleaning and circular sorting of change scores are selection practices that result in artifactual changes even without circular data binning. These pitfalls might have led to erroneous claims about changes in population receptive fields in previous work and can be mitigated by using independent data for selection purposes. Our evaluations highlight the urgency for us researchers to make the validation of analysis pipelines standard practice.

Age-related changes in neuronal receptive fields of primary auditory cortex in frequency, amplitude, and temporal domains

Aging populations often experience difficulties hearing. This phenomenon, known as age-related hearing loss, is associated with decreases in hearing sensitivity and pathophysiological changes in the central auditory system, including the primary auditory cortex (AI). To better understand changes in the central auditory system, this study is designed to compare the receptive fields of AI neurons of young and old C57 mice in frequency, amplitude, and temporal domains by using random-delivery (various interval) of multi-frequency gamma-shaped tone pips and a novel data processing approach known as the intensity-stacked spectrotemporal receptive field (iSTRF). We show that the fundamental changes in the response properties of AI neurons in old mice were in line with the literature. Compared to young mice, AI neurons in old mice tuned to lower frequency and higher amplitude of tones with broader frequency tuning, shorter dB (dynamic) range, longer response duration, as well as a higher firing rate. We further compared the entire iSTRF and core iSTRF (above 50% maximal firing rate) between young and old mice; the core iSTRF represented the AI neuronal responses to sound that fall into the central frequency and amplitude ranges from the auditory periphery. It is remarkable that the difference was significant in the entire iSTRF while little difference was observed in the core iSTRFs between young and old mice. However, the lower best frequency and higher best amplitude were obvious in both iSTRFs that were mostly determined by the deficits in the inner ears of old mice. In the frequency domain, the tuning quality factor of entire iSTRFs was significantly greater in old mice, while that of core iSTRFs was not compared to young mice. In the amplitude domain, significantly shorter dB range in old mice were observed in the entire iSTRF, but not in the core iSTRF. In the temporal domain, the response duration of old AI neurons was significantly longer in entire iSTRFs, but not in core iSTRFs, when compared to young AI neurons. Furthermore, the average firing rate of old AI neurons was significantly higher in entire iSTRF, but not in core iSTRF. It is also interesting that the ratio of the firing rate to background firing rate (signal-noise ratio) were similar between young and old AI neurons. Our data suggests that age-related hearing loss has relatively less impact on auditory information processing when sounds fall into the optimal frequency and amplitude ranges of given AI neurons.

Predictive masking of an artificial scotoma is associated with a system-wide reconfiguration of neural populations in the human visual cortex

The visual brain has the remarkable capacity to complete our percept of the world even when the information extracted from the visual scene is incomplete. This ability to predict missing information based on information from spatially adjacent regions is an intriguing attribute of healthy vision. Yet, it gains particular significance when it masks the perceptual consequences of a retinal lesion, leaving patients unaware of their partial loss of vision and ultimately delaying diagnosis and treatment. At present, our understanding of the neural basis of this masking process is limited which hinders both quantitative modeling as well as translational application. To overcome this, we asked the participants to view visual stimuli with and without superimposed artificial scotoma (AS). We used fMRI to record the associated cortical activity and applied model-based analyzes to track changes in cortical population receptive fields and connectivity in response to the introduction of the AS. We found that throughout the visual field and cortical hierarchy, pRFs shifted their preferred position towards the AS border. Moreover, extrastriate areas biased their sampling of V1 towards sections outside the AS projection zone, thereby effectively masking the AS with signals from spared portions of the visual field. We speculate that the signals that drive these system-wide population modifications originate in extrastriate visual areas and, through feedback, also reconfigure the neural populations in the earlier visual areas.

Complementary Inhibitory Weight Profiles Emerge from Plasticity and Allow Flexible Switching of Receptive Fields.

Cortical areas comprise multiple types of inhibitory interneurons, with stereotypical connectivity motifs that may follow specific plasticity rules. Yet, their combined effect on postsynaptic dynamics has been largely unexplored. Here, we analyze the response of a single postsynaptic model neuron receiving tuned excitatory connections alongside inhibition from two plastic populations. Synapses from each inhibitory population change according to distinct plasticity rules. We tested different combinations of three rules: Hebbian, anti-Hebbian, and homeostatic scaling. Depending on the inhibitory plasticity rule, synapses become unspecific (flat), anticorrelated to, or correlated with excitatory synapses. Crucially, the neuron's receptive field (i.e., its response to presynaptic stimuli) depends on the modulatory state of inhibition. When both inhibitory populations are active, inhibition balances excitation, resulting in uncorrelated postsynaptic responses regardless of the inhibitory tuning profiles. Modulating the activity of a given inhibitory population produces strong correlations to either preferred or nonpreferred inputs, in line with recent experimental findings that show dramatic context-dependent changes of neurons' receptive fields. We thus confirm that a neuron's receptive field does not follow directly from the weight profiles of its presynaptic afferents. Our results show how plasticity rules in various cell types can interact to shape cortical circuit motifs and their dynamics.SIGNIFICANCE STATEMENT Neurons in sensory areas of the cortex are known to respond to specific features of a given input (e.g., specific sound frequencies), but recent experimental studies show that such responses (i.e., their receptive fields) depend on context. Inspired by the cortical connectivity, we built models of excitatory and inhibitory inputs onto a single neuron, to study how receptive fields may change on short and long time scales. We show how various synaptic plasticity rules allow for the emergence of diverse connectivity profiles and, moreover, how their dynamic interaction creates a mechanism by which postsynaptic responses can quickly change. Our work emphasizes multiple roles of inhibition in cortical processing and provides a first mechanistic model for flexible receptive fields.

Synaptic and intrinsic mechanisms underlying development of cortical direction selectivity.

Modifications of synaptic inputs and cell-intrinsic properties both contribute to neuronal plasticity and development. To better understand these mechanisms, we undertook an intracellular analysis of the development of direction selectivity in the ferret visual cortex, which occurs rapidly over a few days after eye opening. We found strong evidence of developmental changes in linear spatiotemporal receptive fields of simple cells, implying alterations in circuit inputs. Further, this receptive field plasticity was accompanied by increases in near-spike-threshold excitability and input-output gain that resulted in dramatically increased spiking responses in the experienced state. Increases in subthreshold membrane responses induced by the receptive field plasticity and the increased input-output spiking gain were both necessary to explain the elevated firing rates in experienced ferrets. These results demonstrate that cortical direction selectivity develops through a combination of plasticity in inputs and in cell-intrinsic properties.

Coding Principles in Adaptation.

Adaptation is a common principle that recurs throughout the nervous system at all stages of processing. This principle manifests in a variety of phenomena, from spike frequency adaptation, to apparent changes in receptive fields with changes in stimulus statistics, to enhanced responses to unexpected stimuli. The ubiquity of adaptation leads naturally to the question: What purpose do these different types of adaptation serve? A diverse set of theories, often highly overlapping, has been proposed to explain the functional role of adaptive phenomena. In this review, we discuss several of these theoretical frameworks, highlighting relationships among them and clarifying distinctions. We summarize observations of the varied manifestations of adaptation, particularly as they relate to these theoretical frameworks, focusing throughout on the visual system and making connections to other sensory systems.

Impact of light-adaptive mechanisms on mammalian retinal visual encoding at high light levels.

A persistent change in illumination causes light-adaptive changes in retinal neurons. Light adaptation improves visual encoding by preventing saturation and by adjusting spatiotemporal integration to increase the signal-to-noise ratio (SNR) and utilize signaling bandwidth efficiently. In dim light, the visual input contains a greater relative amount of quantal noise, and vertebrate receptive fields are extended in space and time to increase SNR. Whereas in bright light, SNR of the visual input is high, the rate of synaptic vesicle release from the photoreceptors is low so that quantal noise in synaptic output may limit SNR postsynaptically. Whether and how reduced synaptic SNR impacts spatiotemporal integration in postsynaptic neurons remains unclear. To address this, we measured spatiotemporal integration in retinal horizontal cells and ganglion cells in the guinea pig retina across a broad illumination range, from low to high photopic levels. In both cell types, the extent of spatial and temporal integration changed according to an inverted U-shaped function consistent with adaptation to low SNR at both low and high light levels. We show how a simple mechanistic model with interacting, opponent filters can generate the observed changes in ganglion cell spatiotemporal receptive fields across light-adaptive states and postulate that retinal neurons postsynaptic to the cones in bright light adopt low-pass spatiotemporal response characteristics to improve visual encoding under conditions of low synaptic SNR.

Influence of behavioral state on auditory processing in the marmoset midbrain

Recent work shows that neurons in the inferior colliculus (IC) undergo receptive field changes during auditory behavior in ferrets (Slee & David, 2015. J. Neurosci.). In this study, we tested for similar effects in the marmoset monkey, a highly vocal primate species. We trained two marmosets to detect a pure tone target embedded in a background of random spectral shape (RSS) distractor stimuli. We recorded single-unit activity in the central nucleus of the IC (ICC). Neural responses to targets and distractors were compared between conditions when the marmoset performed the detection task or listened passively. When target frequency was near the neuronal best frequency (BF), responses to distractors were suppressed in about half of the neurons during behavior. Target responses were modulated in some neurons but suppression or enhancement was equally likely. We also measured effects of task engagement in non-central divisions of the IC (NCIC). There, target responses were strongly enhanced during behavior in about half of neurons in this region (median change = 70%). We also found a subset of NCIC neurons that responded with increased firing following the target sound, possibly encoding a reward-related signal. This study replicates our previous finding that distractor responses are suppressed during auditory behavior in the ferret IC. In addition, we found an area in the NCIC with large enhancement of target responses during behavior, suggesting that task engagement produces distinct effects across subdivisions of the IC.

Spatial Tuning Shifts Increase the Discriminability and Fidelity of Population Codes in Visual Cortex.

Selective visual attention enables organisms to enhance the representation of behaviorally relevant stimuli by altering the encoding properties of single receptive fields (RFs). Yet we know little about how the attentional modulations of single RFs contribute to the encoding of an entire visual scene. Addressing this issue requires (1) measuring a group of RFs that tile a continuous portion of visual space, (2) constructing a population-level measurement of spatial representations based on these RFs, and (3) linking how different types of RF attentional modulations change the population-level representation. To accomplish these aims, we used fMRI to characterize the responses of thousands of voxels in retinotopically organized human cortex. First, we found that the response modulations of voxel RFs (vRFs) depend on the spatial relationship between the RF center and the visual location of the attended target. Second, we used two analyses to assess the spatial encoding quality of a population of voxels. We found that attention increased fine spatial discriminability and representational fidelity near the attended target. Third, we linked these findings by manipulating the observed vRF attentional modulations and recomputing our measures of the fidelity of population codes. Surprisingly, we discovered that attentional enhancements of population-level representations largely depend on position shifts of vRFs, rather than changes in size or gain. Our data suggest that position shifts of single RFs are a principal mechanism by which attention enhances population-level representations in visual cortex.SIGNIFICANCE STATEMENT Although changes in the gain and size of RFs have dominated our view of how attention modulates visual information codes, such hypotheses have largely relied on the extrapolation of single-cell responses to population responses. Here we use fMRI to relate changes in single voxel receptive fields (vRFs) to changes in population-level representations. We find that vRF position shifts contribute more to population-level enhancements of visual information than changes in vRF size or gain. This finding suggests that position shifts are a principal mechanism by which spatial attention enhances population codes for relevant visual information. This poses challenges for labeled line theories of information processing, suggesting that downstream regions likely rely on distributed inputs rather than single neuron-to-neuron mappings.

Internal Cholinergic Regulation of Learning and Recall in a Model of Olfactory Processing.

In the olfactory system, cholinergic modulation has been associated with contrast modulation and changes in receptive fields in the olfactory bulb, as well the learning of odor associations in olfactory cortex. Computational modeling and behavioral studies suggest that cholinergic modulation could improve sensory processing and learning while preventing pro-active interference when task demands are high. However, how sensory inputs and/or learning regulate incoming modulation has not yet been elucidated. We here use a computational model of the olfactory bulb, piriform cortex (PC) and horizontal limb of the diagonal band of Broca (HDB) to explore how olfactory learning could regulate cholinergic inputs to the system in a closed feedback loop. In our model, the novelty of an odor is reflected in firing rates and sparseness of cortical neurons in response to that odor and these firing rates can directly regulate learning in the system by modifying cholinergic inputs to the system. In the model, cholinergic neurons reduce their firing in response to familiar odors—reducing plasticity in the PC, but increase their firing in response to novel odor—increasing PC plasticity. Recordings from HDB neurons in awake behaving rats reflect predictions from the model by showing that a subset of neurons decrease their firing as an odor becomes familiar.

A quantitative neuro-computational model of attentive receptive field changes in area MT

A quantitative neuro-computational model of attentive receptive field changes in area MT

Presaccadic changes in local field potential-derived receptive fields within the frontal eye field

Presaccadic changes in local field potential-derived receptive fields within the frontal eye field

A Probabilistic Approach to Receptive Field Mapping in the Frontal Eye Fields.

Studies of the neuronal mechanisms of perisaccadic vision often lack the resolution needed to determine important changes in receptive field (RF) structure. Such limited analytical power can lead to inaccurate descriptions of visuomotor processing. To address this issue, we developed a precise, probabilistic technique that uses a generalized linear model (GLM) for mapping the visual RFs of frontal eye field (FEF) neurons during stable fixation (Mayo et al., 2015). We previously found that full-field RF maps could be obtained using 1–8 dot stimuli presented at frame rates of 10–150 ms. FEF responses were generally robust to changes in the number of stimuli presented or the rate of presentation, which allowed us to visualize RFs over a range of spatial and temporal resolutions. Here, we compare the quality of RFs obtained over different stimulus and GLM parameters to facilitate future work on the detailed mapping of FEF RFs. We first evaluate the interactions between the number of stimuli presented per trial, the total number of trials, and the quality of RF mapping. Next, we vary the spatial resolution of our approach to illustrate the tradeoff between visualizing RF sub-structure and sampling at high resolutions. We then evaluate local smoothing as a possible correction for situations where under-sampling occurs. Finally, we provide a preliminary demonstration of the usefulness of a probabilistic approach for visualizing full-field perisaccadic RF shifts. Our results present a powerful, and perhaps necessary, framework for studying perisaccadic vision that is applicable to FEF and possibly other visuomotor regions of the brain.

Using the Change Manager Model for the Hippocampal System to Predict Connectivity and Neurophysiological Parameters in the Perirhinal Cortex.

Theoretical arguments demonstrate that practical considerations, including the needs to limit physiological resources and to learn without interference with prior learning, severely constrain the anatomical architecture of the brain. These arguments identify the hippocampal system as the change manager for the cortex, with the role of selecting the most appropriate locations for cortical receptive field changes at each point in time and driving those changes. This role results in the hippocampal system recording the identities of groups of cortical receptive fields that changed at the same time. These types of records can also be used to reactivate the receptive fields active during individual unique past events, providing mechanisms for episodic memory retrieval. Our theoretical arguments identify the perirhinal cortex as one important focal point both for driving changes and for recording and retrieving episodic memories. The retrieval of episodic memories must not drive unnecessary receptive field changes, and this consideration places strong constraints on neuron properties and connectivity within and between the perirhinal cortex and regular cortex. Hence the model predicts a number of such properties and connectivity. Experimental test of these falsifiable predictions would clarify how change is managed in the cortex and how episodic memories are retrieved.

Nonlinear population receptive field changes in human area V5/MT+ of healthy subjects with simulated visual field scotomas

There is extensive controversy over whether the adult visual cortex is able to reorganize following visual field loss (scotoma) as a result of retinal or cortical lesions. Functional magnetic resonance imaging (fMRI) methods provide a useful tool to study the aggregate receptive field properties and assess the capacity of the human visual cortex to reorganize following injury. However, these methods are prone to biases near the boundaries of the scotoma. Retinotopic changes resembling reorganization have been observed in the early visual cortex of normal subjects when the visual stimulus is masked to simulate retinal or cortical scotomas. It is not known how the receptive fields of higher visual areas, like hV5/MT+, are affected by partial stimulus deprivation. We measured population receptive field (pRF) responses in human area V5/MT+ of 5 healthy participants under full stimulation and compared them with responses obtained from the same area while masking the left superior quadrant of the visual field (“artificial scotoma” or AS). We found that pRF estimations in area hV5/MT+ are nonlinearly affected by the AS. Specifically, pRF centers shift towards the AS, while the pRF amplitude increases and the pRF size decreases near the AS border. The observed pRF changes do not reflect reorganization but reveal important properties of normal visual processing under different test-stimulus conditions.