Introduction [for chapter on Consciousness]

No abstract

Time course of target recognition in visual search

Visual search is a ubiquitous task of great importance: it allows us to quickly find the objects that we are looking for. During active search for an object (target), eye movements are made to different parts of the scene. Fixation locations are chosen based on a combination of information about the target and the visual input. At the end of a successful search, the eyes typically fixate on the target. But does this imply that target identification occurs while looking at it? The duration of a typical fixation (~170ms) and neuronal latencies of both the oculomotor system and the visual stream indicate that there might not be enough time to do so. Previous studies have suggested the following solution to this dilemma: the target is identified extrafoveally and this event will trigger a saccade towards the target location. However this has not been experimentally verified. Here we test the hypothesis that subjects recognize the target before they look at it using a search display of oriented colored bars. Using a gaze-contingent real-time technique, we prematurely stopped search shortly after subjects fixated the target. Afterwards, we asked subjects to identify the target location. We find that subjects can identify the target location even when fixating on the target for less than 10ms. Longer fixations on the target do not increase detection performance but increase confidence. In contrast, subjects cannot perform this task if they are not allowed to move their eyes. Thus, information about the target during conjunction search for colored oriented bars can, in some circumstances, be acquired at least one fixation ahead of reaching the target. The final fixation serves to increase confidence rather then performance, illustrating a distinct role of the final fixation for the subjective judgment of confidence rather than accuracy

Detecting and Estimating Signals in Noisy Cable Structures, II: Information Theoretical Analysis

This is the second in a series of articles that seek to recast classical single-neuron biophysics in information-theoretical terms. Classical cable theory focuses on analyzing the voltage or current attenuation of a synaptic signal as it propagates from its dendritic input location to the spike initiation zone. On the other hand, we are interested in analyzing the amount of information lost about the signal in this process due to the presence of various noise sources distributed throughout the neuronal membrane. We use a stochastic version of the linear one-dimensional cable equation to derive closed-form expressions for the second-order moments of the fluctuations of the membrane potential associated with different membrane current noise sources: thermal noise, noise due to the random opening and closing of sodium and potassium channels, and noise due to the presence of “spontaneous” synaptic input. We consider two different scenarios. In the signal estimation paradigm, the time course of the membrane potential at a location on the cable is used to reconstruct the detailed time course of a random, band-limited current injected some distance away. Estimation performance is characterized in terms of the coding fraction and the mutual information. In the signal detection paradigm, the membrane potential is used to determine whether a distant synaptic event occurred within a given observation interval. In the light of our analytical results, we speculate that the length of weakly active apical dendrites might be limited by the information loss due to the accumulated noise between distal synaptic input sites and the soma and that the presence of dendritic nonlinearities probably serves to increase dendritic information transfer

Probabilistic modeling of eye movement data during conjunction search via feature-based attention

Where the eyes fixate during search is not random; rather, gaze reflects the combination of information about the target and the visual input. It is not clear, however, what information about a target is used to bias the underlying neuronal responses. We here engage subjects in a variety of simple conjunction search tasks while tracking their eye movements. We derive a generative model that reproduces these eye movements and calculate the conditional probabilities that observers fixate, given the target, on or near an item in the display sharing a specific feature with the target. We use these probabilities to infer which features were biased by top-down attention: Color seems to be the dominant stimulus dimension for guiding search, followed by object size, and lastly orientation. We use the number of fixations it took to find the target as a measure of task difficulty. We find that only a model that biases multiple feature dimensions in a hierarchical manner can account for the data. Contrary to common assumptions, memory plays almost no role in search performance. Our model can be fit to average data of multiple subjects or to individual subjects. Small variations of a few key parameters account well for the intersubject differences. The model is compatible with neurophysiological findings of V4 and frontal eye fields (FEF) neurons and predicts the gain modulation of these cells

Detecting and Estimating Signals over Noisy and Unreliable Synapses: Information-Theoretic Analysis

The temporal precision with which neurons respond to synaptic inputs has a direct bearing on the nature of the neural code. A characterization of the neuronal noise sources associated with different sub-cellular components (synapse, dendrite, soma, axon, and so on) is needed to understand the relationship between noise and information transfer. Here we study the effect of the unreliable, probabilistic nature of synaptic transmission on information transfer in the absence of interaction among presynaptic inputs. We derive theoretical lower bounds on the capacity of a simple model of a cortical synapse under two different paradigms. In signal estimation, the signal is assumed to be encoded in the mean firing rate of the presynaptic neuron, and the objective is to estimate the continuous input signal from the postsynaptic voltage. In signal detection, the input is binary, and the presence or absence of a presynaptic action potential is to be detected from the postsynaptic voltage. The efficacy of information transfer in synaptic transmission is characterized by deriving optimal strategies under these two paradigms. On the basis of parameter values derived from neocortex, we find that single cortical synapses cannot transmit information reliably, but redundancy obtained using a small number of multiple synapses leads to a significant improvement in the information capacity of synaptic transmission

Linking Linear Threshold Units with Quadratic Models of Motion Perception

Behavioral experiments on insects (Hassenstein and Reichardt 1956; Poggio and Reichardt 1976) as well as psychophysical evidence from human studies (Van Santen and Sperling 1985; Adelson and Bergen 1985; Watson and Ahumada 1985) support the notion that short-range motion perception is mediated by a system with a quadratic type of nonlinearity, as in correlation (Hassenstein and Reichardt 1956), multiplication (Torre and Poggio 1978), or squaring (Adelson and Bergen 1985). However, there is little physiological evidence for quadratic nonlinearities in directionally selective cells. For instance, the response of cortical simple cells to a moving sine grating is half-wave instead of full-wave rectified as it should be for a quadratic nonlinearity (Movshon ef al. 1978; Holub and Morton-Gibson 1981) and is linear for low contrast (Holub and Morton-Gibson 1981). Complex cells have full-wave rectified responses, but are also linear in contrast. Moreover, a detailed theoretical analysis of possible biophysical mechanisms underlying direction selectivity concludes that most do not have quadratic properties except under very limited conditions (Grzywacz and Koch 1987). Thus, it is presently mysterious how a system can show quadratic properties while its individual components do not. We briefly discuss here a simple population encoding scheme offering a possible solution to this problem

Phenomenology without conscious access is a form of consciousness without top-down attention

We agree with Block's basic hypothesis postulating the existence of phenomenal consciousness without cognitive access. We explain such states in terms of consciousness without top-down, endogenous attention and speculate that their correlates may be a coalition of neurons that are consigned to the back of cortex, without access to working memory and planning in frontal cortex

Detecting and Estimating Signals in Noisy Cable Structures, I: Neuronal Noise Sources

In recent theoretical approaches addressing the problem of neural coding, tools from statistical estimation and information theory have been applied to quantify the ability of neurons to transmit information through their spike outputs. These techniques, though fairly general, ignore the specific nature of neuronal processing in terms of its known biophysical properties. However, a systematic study of processing at various stages in a biophysically faithful model of a single neuron can identify the role of each stage in information transfer. Toward this end, we carry out a theoretical analysis of the information loss of a synaptic signal propagating along a linear, one-dimensional, weakly active cable due to neuronal noise sources along the way, using both a signal reconstruction and a signal detection paradigm. Here we begin such an analysis by quantitatively characterizing three sources of membrane noise: (1) thermal noise due to the passive membrane resistance, (2) noise due to stochastic openings and closings of voltage-gated membrane channels (Na^+ and K^+), and (3) noise due to random, background synaptic activity. Using analytical expressions for the power spectral densities of these noise sources, we compare their magnitudes in the case of a patch of membrane from a cortical pyramidal cell and explore their dependence on different biophysical parameters