Contributions of cortical feedback to sensory processing in primary visual cortex

Closing the structure-function divide is more challenging in the brain than in any other organ (Lichtman and Denk, 2011). For example, in early visual cortex, feedback projections to V1 can be quantified (e.g., Budd, 1998) but the understanding of feedback function is comparatively rudimentary (Muckli and Petro, 2013). Focusing on the function of feedback, we discuss how textbook descriptions mask the complexity of V1 responses, and how feedback and local activity reflects not only sensory processing but internal brain states

Visual selective behavior can be triggered by a feed-forward process

The ventral visual pathway implements object recognition and categorization in a hierarchy of processing areas with neuronal selectivities of increasing complexity. The presence of massive feedback connections within this hierarchy raises the possibility that normal visual processing relies on the use of computational loops. It is not known, however, whether object recognition can be performed at all without such loops (i.e., in a purely feed-forward mode). By analyzing the time course of reaction times in a masked natural scene categorization paradigm, we show that the human visual system can generate selective motor responses based on a single feed-forward pass. We confirm these results using a more constrained letter discrimination task, in which the rapid succession of a target and mask is actually perceived as a distractor. We show that a masked stimulus presented for only 26 msec—and often not consciously perceived—can fully determine the earliest selective motor responses: The neural representations of the stimulus and mask are thus kept separated during a short period corresponding to the feed-forward "sweep." Therefore, feedback loops do not appear to be "mandatory" for visual processing. Rather, we found that such loops allow the masked stimulus to reverberate in the visual system and affect behavior for nearly 150 msec after the feed-forward sweep

A feedback model of visual attention

Feedback connections are a prominent feature of cortical anatomy and are likely to have 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

Cognitive science and epistemic openness

Recent findings in cognitive science suggest that the epistemic subject is more complex and epistemically porous than is generally pictured. Human knowers are open to the world via multiple channels, each operating for particular purposes and according to its own logic. These findings need to be understood and addressed by the philosophical community. The current essay argues that one consequence of the new findings is to invalidate certain arguments for epistemic anti-realism

Electrophysiological and functional magnetic resonance imaging investigations on the influence of spatial and feature-based attention on the flanker effect

Attention represents an almost ubiquitous field in neuroscientific research. It can be manipulated in many ways including direction, intensity or selectivity of attention. An unanswered question remains concerning the possibility to suppress distracting information through top-down attentional control. The present doctoral thesis addresses this topic and furthermore contrasts two main attention types (spatial and feature-based allocation). For this purpose, both anatomical and temporal data were collected and brought together in a common source analysis

Spatiotemporal dynamics of attention networks revealed by representational similarity analysis of EEG and fMRI

The fronto-parietal attention networks have been extensively studied with functional magnetic resonance imaging (fMRI), but spatiotemporal dynamics of these networks are not well understood. We measured event-related potentials (ERPs) with electroencephalography (EEG) and collected fMRI data from identical experiments where participants performed visual and auditory discrimination tasks separately or simultaneously and with or without distractors. To overcome the low temporal resolution of fMRI, we used a novel ERP-based application of multivariate representational similarity analysis (RSA) to parse time-averaged fMRI pattern activity into distinct spatial maps that each corresponded, in representational structure, to a short temporal ERP segment. Discriminant analysis of ERP-fMRI correlations revealed 8 cortical networks-2 sensory, 3 attention, and 3 other-segregated by 4 orthogonal, temporally multifaceted and spatially distributed functions. We interpret these functions as 4 spatiotemporal components of attention: modality-dependent and stimulus-driven orienting, top-down control, mode transition, and response preparation, selection and execution.Peer reviewe

Interactions between visual and semantic processing during object recognition revealed by modulatory effects of age of acquisition

The age of acquisition (AoA) of objects and their names is a powerful determinant of processing speed in adulthood, with early-acquired objects being recognized and named faster than late-acquired objects. Previous research using fMRI (Ellis et al., 2006. Traces of vocabulary acquisition in the brain: evidence from covert object naming. NeuroImage 33, 958–968) found that AoA modulated the strength of BOLD responses in both occipital and left anterior temporal cortex during object naming. We used magnetoencephalography (MEG) to explore in more detail the nature of the influence of AoA on activity in those two regions. Covert object naming recruited a network within the left hemisphere that is familiar from previous research, including visual, left occipito-temporal, anterior temporal and inferior frontal regions. Region of interest (ROI) analyses found that occipital cortex generated a rapid evoked response (~ 75–200 ms at 0–40 Hz) that peaked at 95 ms but was not modulated by AoA. That response was followed by a complex of later occipital responses that extended from ~ 300 to 850 ms and were stronger to early- than late-acquired items from ~ 325 to 675 ms at 10–20 Hz in the induced rather than the evoked component. Left anterior temporal cortex showed an evoked response that occurred significantly later than the first occipital response (~ 100–400 ms at 0–10 Hz with a peak at 191 ms) and was stronger to early- than late-acquired items from ~ 100 to 300 ms at 2–12 Hz. A later anterior temporal response from ~ 550 to 1050 ms at 5–20 Hz was not modulated by AoA. The results indicate that the initial analysis of object forms in visual cortex is not influenced by AoA. A fastforward sweep of activation from occipital and left anterior temporal cortex then results in stronger activation of semantic representations for early- than late-acquired objects. Top-down re-activation of occipital cortex by semantic representations is then greater for early than late acquired objects resulting in delayed modulation of the visual response

A role for recurrent processing in object completion: neurophysiological, psychophysical and computational"evidence

Recognition of objects from partial information presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. We combined neurophysiological recordings in human cortex with psychophysical measurements and computational modeling to investigate the mechanisms involved in object completion. We recorded intracranial field potentials from 1,699 electrodes in 18 epilepsy patients to measure the timing and selectivity of responses along human visual cortex to whole and partial objects. Responses along the ventral visual stream remained selective despite showing only 9-25% of the object. However, these visually selective signals emerged ~100 ms later for partial versus whole objects. The processing delays were particularly pronounced in higher visual areas within the ventral stream, suggesting the involvement of additional recurrent processing. In separate psychophysics experiments, disrupting this recurrent computation with a backward mask at ~75ms significantly impaired recognition of partial, but not whole, objects. Additionally, computational modeling shows that the performance of a purely bottom-up architecture is impaired by heavy occlusion and that this effect can be partially rescued via the incorporation of top-down connections. These results provide spatiotemporal constraints on theories of object recognition that involve recurrent processing to recognize objects from partial information