Feature-based gating of cortical information transmission

In highly developed visual systems, spatial- and feature-based attentional modulation interact to prioritize relevant information and suppress irrelevant details. We investigated the specific role and integration of these two attentional mechanisms in visual cortical area MST of rhesus monkeys. We show that spatial attention acts as a gate for information processing by providing unimpeded high-gain pass-through processing for all sensory information from attended visual locations. Feature-based attentional enhancement does not only show the known dependency on a match between the attended feature and a given cells selectivity, but surprisingly is restricted to those features for which a given cell contributes to perception. This necessitates a refinement of the feature-similarity gain model of attention and documents highly optimized attentional gating of sensory information for cortical processing. This gating is shaped by neuronal sensory preferences, behavioral relevance, and the causal link to perception of neurons that process this visual input.

Laminar microcircuitry of visual cortex producing attention-associated electric fields

Cognitive operations are widely studied by measuring electric fields through EEG and ECoG. However, despite their widespread use, the component neural circuitry giving rise to these signals remains unknown. Specifically, the functional architecture of cortical columns which results in attention-associated electric fields has not been explored. Here we detail the laminar cortical circuitry underlying an attention-associated electric field often measured over posterior regions of the brain in humans and monkeys. First, we identified visual cortical area V4 as one plausible contributor to this attention-associated electric field through inverse modeling of cranial EEG in macaque monkeys performing a visual attention task. Next, we performed laminar neurophysiological recordings on the prelunate gyrus and identified the electric-field-producing dipoles as synaptic activity in distinct cortical layers of area V4. Specifically, activation in the extragranular layers of cortex resulted in the generation of the attention-associated dipole. Feature selectivity of a given cortical column determined the overall contribution to this electric field. Columns selective for the attended feature contributed more to the electric field than columns selective for a different feature. Lastly, the laminar profile of synaptic activity generated by V4 was sufficient to produce an attention-associated signal measurable outside of the column. These findings suggest that the top-down recipient cortical layers produce an attention-associated electric field capable of being measured extracranially and the relative contribution of each column depends upon the underlying functional architecture.

Multimodal Neuroimaging Study of Visual Plasticity in Schizophrenia

Schizophrenia is a severe mental illness with visual learning and memory deficits, and reduced long term potentiation (LTP) may underlie these impairments. Recent human fMRI and EEG studies have assessed visual plasticity that was induced with high frequency visual stimulation, which is thought to mimic an LTP-like phenomenon. This study investigated the differences in visual plasticity in participants with schizophrenia and healthy controls. An fMRI visual plasticity paradigm was implemented, and proton magnetic resonance spectroscopy data were acquired to determine whether baseline resting levels of glutamatergic and GABA metabolites were related to visual plasticity response. Adults with schizophrenia did not demonstrate visual plasticity after family-wise error correction; whereas, the healthy control group did. There was a significant regional difference in visual plasticity in the left visual cortical area V2 when assessing group differences, and baseline GABA levels were associated with this specific ROI in the SZ group only. Overall, this study suggests that visual plasticity is altered in schizophrenia and related to basal GABA levels.

Visual Cortical Area MT is Required for Development of the Dorsal Stream and Associated Visuomotor Behaviours

The middle temporal (MT) area of the extrastriate visual cortex has long been studied in adulthood for its distinctive physiological properties and function as a part of the dorsal stream, yet interestingly possesses a similar maturation profile as the primary visual cortex (V1). Here we examined whether an early-life lesion of MT altered the dorsal stream development and the behavioural precision of reaching to grasp sequences. We observed permanent changes in the anatomy of cortices associated with both reaching (PE and MIP) and grasping (AIP), as well as in reaching and grasping behaviours. In addition, we observed a significant impact on the anatomy of V1 and the direction sensitivity of V1 neurons in the lesion projection zone. These findings indicate that area MT is a crucial node for the development of the primate vision, impacting both V1 and areas in the dorsal visual pathway known to mediate visually guided manual behaviours.TeaserThe early life loss of visual area MT leads to significant anatomical, physiological and behavioural changes.

Strong information-limiting correlations in early visual areas

If the brain processes incoming data efficiently, information should degrade little between early and later neural processing stages, and so information in early stages should match behavioral performance. For instance, if there is enough information in a visual cortical area to determine the orientation of a grating to within 1 degree, and the code is simple enough to be read out by downstream circuits, then animals should be able to achieve that performance behaviourally. Despite over 30 years of research, it is still not known how efficient the brain is. For tasks involving a large number of neurons, the amount of information encoded by neural circuits is limited by differential correlations. Therefore, determining how much information is encoded requires quantifying the strength of differential correlations. Detecting them, however, is difficult. We report here a new method, which requires on the order of 100s of neurons and trials. This method relies on computing the alignment of the neural stimulus encoding direction, f′, with the eigenvectors of the noise covariance matrix, Σ. In the presence of strong differential correlations, f′ must be spanned by a small number of the eigenvectors with largest eigenvalues. Using simulations with a leaky-integrate-and-fire neuron model of the LGN-V1 circuit, we confirmed that this method can indeed detect differential correlations consistent with those that would limit orientation discrimination thresholds to 0.5-3 degrees. We applied this technique to V1 recordings in awake monkeys and found signatures of differential correlations, consistent with a discrimination threshold of 0.47-1.20 degrees, which is not far from typical discrimination thresholds (1-2 deg). These results suggest that, at least in macaque monkeys, V1 contains about as much information as is seen in behaviour, implying that downstream circuits are efficient at extracting the information available in V1.

Multiplicative modulations in hue-selective cells enhance unique hue representation

There is still much to understand about the color processing mechanisms in the brain and the transformation from cone-opponent representations to perceptual hues. Moreover, it is unclear which areas(s) in the brain represent unique hues. We propose a hierarchical model inspired by the neuronal mechanisms in the brain for local hue representation, which reveals the contributions of each visual cortical area in hue representation. Local hue encoding is achieved through incrementally increasing processing nonlinearities beginning with cone input. Besides employing nonlinear rectifications, we propose multiplicative modulations as a form of nonlinearity. Our simulation results indicate that multiplicative modulations have significant contributions in encoding of hues along intermediate directions in the MacLeod-Boynton diagram and that model V4 neurons have the capacity to encode unique hues. Additionally, responses of our model neurons resemble those of biological color cells, suggesting that our model provides a novel formulation of the brain’s color processing pathway.

Modeling diverse responses to filled and outline shapes in macaque V4

Visual area V4 is an important midlevel cortical processing stage that subserves object recognition in primates. Studies investigating shape coding in V4 have largely probed neuronal responses with filled shapes, i.e., shapes defined by both a boundary and an interior fill. As a result, we do not know whether form-selective V4 responses are dictated by boundary features alone or if interior fill is also important. We studied 43 V4 neurons in two male macaque monkeys ( Macaca mulatta) with a set of 362 filled shapes and their corresponding outlines to determine how interior fill modulates neuronal responses in shape-selective neurons. Only a minority of neurons exhibited similar response strength and shape preferences for filled and outline stimuli. A majority responded preferentially to one stimulus category (either filled or outline shapes) and poorly to the other. Our findings are inconsistent with predictions of the hierarchical-max (HMax) V4 model that builds form selectivity from oriented boundary features and takes little account of attributes related to object surface, such as the phase of the boundary edge. We modified the V4 HMax model to include sensitivity to interior fill by either removing phase-pooling or introducing unoriented units at the V1 level; both modifications better explained our data without increasing the number of free parameters. Overall, our results suggest that boundary orientation and interior surface information are both maintained until at least the midlevel visual representation, consistent with the idea that object fill is important for recognition and perception in natural vision. NEW & NOTEWORTHY The shape of an object’s boundary is critical for identification; consistent with this idea, models of object recognition predict that filled and outline versions of a shape are encoded similarly. We report that many neurons in a midlevel visual cortical area respond differently to filled and outline shapes and modify a biologically plausible model to account for our data. Our results suggest that representations of boundary shape and surface fill are interrelated in visual cortex.

A collicular visual cortex: Neocortical space for an ancient midbrain visual structure

Visual responses in the cerebral cortex are believed to rely on the geniculate input to the primary visual cortex (V1). Indeed, V1 lesions substantially reduce visual responses throughout the cortex. Visual information enters the cortex also through the superior colliculus (SC), but the function of this input on visual responses in the cortex is less clear. SC lesions affect cortical visual responses less than V1 lesions, and no visual cortical area appears to entirely rely on SC inputs. We show that visual responses in a mouse lateral visual cortical area called the postrhinal cortex are independent of V1 and are abolished upon silencing of the SC. This area outperforms V1 in discriminating moving objects. We thus identify a collicular primary visual cortex that is independent of the geniculo-cortical pathway and is capable of motion discrimination.