Towards a Unified Theory of Neocortex: Laminar Cortical Circuits for Vision and Cognition

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of pre-attentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

Nonassociative learning as gated neural integrator and differentiator in stimulus-response pathways

Nonassociative learning is a basic neuroadaptive behavior exhibited across animal phyla and sensory modalities but its role in brain intelligence is unclear. Current literature on habituation and sensitization, the classic "dual process" of nonassociative learning, gives highly incongruous accounts between varying experimental paradigms. Here we propose a general theory of nonassociative learning featuring four base modes: habituation/primary sensitization in primary stimulus-response pathways, and desensitization/secondary sensitization in secondary stimulus-response pathways. Primary and secondary modes of nonassociative learning are distinguished by corresponding activity-dependent recall, or nonassociative gating, of neurotransmission memory. From the perspective of brain computation, nonassociative learning is a form of integral-differential calculus whereas nonassociative gating is a form of Boolean logic operator – both dynamically transforming the stimulus-response relationship. From the perspective of sensory integration, nonassociative gating provides temporal filtering whereas nonassociative learning affords low-pass, high-pass or band-pass/band-stop frequency filtering – effectively creating an intelligent sensory firewall that screens all stimuli for attention and resultant internal model adaptation and reaction. This unified framework ties together many salient characteristics of nonassociative learning and nonassociative gating and suggests a common kernel that correlates with a wide variety of sensorimotor integration behaviors such as central resetting and self-organization of sensory inputs, fail-safe sensorimotor compensation, integral-differential and gated modulation of sensorimotor feedbacks, alarm reaction, novelty detection and selective attention, as well as a variety of mental and neurological disorders such as sensorimotor instability, attention deficit hyperactivity, sensory defensiveness, autism, nonassociative fear and anxiety, schizophrenia, addiction and craving, pain sensitization and phantom sensations, etc

Nonassociative learning as gated neural integrator and differentiator in stimulus-response pathways

Nonassociative learning is a basic neuroadaptive behavior exhibited across animal phyla and sensory modalities but its role in brain intelligence is unclear. Current literature on habituation and sensitization, the classic "dual process" of nonassociative learning, gives highly incongruous accounts between varying experimental paradigms. Here we propose a general theory of nonassociative learning featuring four base modes: habituation/primary sensitization in primary stimulus-response pathways, and desensitization/secondary sensitization in secondary stimulus-response pathways. Primary and secondary modes of nonassociative learning are distinguished by corresponding activity-dependent recall, or nonassociative gating, of neurotransmission memory. From the perspective of brain computation, nonassociative learning is a form of integral-differential calculus whereas nonassociative gating is a form of Boolean logic operator – both dynamically transforming the stimulus-response relationship. From the perspective of sensory integration, nonassociative gating provides temporal filtering whereas nonassociative learning affords low-pass, high-pass or band-pass/band-stop frequency filtering – effectively creating an intelligent sensory firewall that screens all stimuli for attention and resultant internal model adaptation and reaction. This unified framework ties together many salient characteristics of nonassociative learning and nonassociative gating and suggests a common kernel that correlates with a wide variety of sensorimotor integration behaviors such as central resetting and self-organization of sensory inputs, fail-safe sensorimotor compensation, integral-differential and gated modulation of sensorimotor feedbacks, alarm reaction, novelty detection and selective attention, as well as a variety of mental and neurological disorders such as sensorimotor instability, attention deficit hyperactivity, sensory defensiveness, autism, nonassociative fear and anxiety, schizophrenia, addiction and craving, pain sensitization and phantom sensations, etc

Neural Models of Seeing and Thinking

Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624

Behavioural and neuronal correlates of visual saliency in mouse

While early parts of the brain’s sensory pathways convey signals about the entire environment, animal behaviour is usually devoted to one or just a few potential objects of interest at any given time. Objects that are more salient (more distinct) are usually prioritised, particularly if they are potential threats, but how and where salience is represented in the brain is not known. Here I examine how salience may be constructed in the visual pathways of mice. To highlight the importance of vision in mice I first show that vision can guide the selection of distinct defence behaviours in response to potential threats - freeze and flight. I then characterise potential neural mechanisms for salience, by making recordings from neurons in the superficial layers of the mouse superior colliculus, an area important in orienting behaviour towards- or away from objects and likely to be part of the salience circuit. I show that many of these neurons are sensitive to visual discontinuities in both the spatial and the temporal domain, and that this sensitivity is more pronounced in awake animals than in anesthetized animals. These results suggest that neurons in the mouse superior colliculus can highlight parts of the environment that are distinct from the spatial and temporal context that they are embedded in, and thus may help in directing animal behaviour with respect to salient objects

When robots weep : a computational approach to affective learning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 245-262).This thesis presents a unified computational framework for the study of emotion that integrates several concepts and mechanisms which have been traditionally deemed to be integral components of intelligent behavior. We introduce the notion of affect programs as the primary theoretical constructs for investigating the function and the mechanisms of emotion, and instantiate these in a variety of embodied agents, including physical and simulated robots. Each of these affect programs establishes a functionally distinct mode of operation for the robots, that is activated when specific environmental contingencies are appraised. These modes involve the coordinated adjustment and entrainment of several different systems-including those governing perception, attention, motivation regulation, action selection, learning, and motor control-as part of the implementation of specialized solutions that take advantage of the regularities found in highly recurrent and prototypical environmental contingencies. We demonstrate this framework through multiple experimental scenarios that explore important features of the affect program abstraction and its function, including the demonstration of affective behavior, evaluative conditioning, incentive salience, and affective learning.by Juan David Velásquez.Ph.D

Dopaminergic modulation of entorhinal cortex function

The neurotransmitter dopamine has been shown to play an important role in the mnemonic functions of the prefrontal cortex, but it is unclear how dopamine may affect sensory and mnemonic processing in the entorhinal cortex. Midbrain dopamine neurons project to the superficial layers of the lateral entorhinal cortex and may modulate olfactory inputs that also terminate in this area. In awake rats, increasing extracellular dopamine levels in the entorhinal cortex with a selective dopamine reuptake inhibitor facilitated basal synaptic transmission in piriform cortex inputs to layer II. Experiments in slices of the entorhinal cortex maintained in vitro demonstrated concentration-dependent, bidirectional effects of dopamine on synaptic responses; a low 10 oM concentration of dopamine enhanced synaptic responses and higher concentrations of 50 and 100 oM dopamine suppressed responses. The facilitation of responses was dependent on activation of D 1 receptors and the suppression was dependent on D 2 receptors. Intracellular recordings of mixed and isolated synaptic responses demonstrated that the dopaminergic suppression is mediated by a D 2 receptor-dependent reduction in glutamate release and a D 1 -dependent drop in cellular input resistance. The drop in input resistance was mediated by a D 1 receptor-dependent K + conductance. In additional experiments, patterned stimulation of the piriform cortex that induces persistent changes in synaptic strength in the entorhinal cortex was used to assess the effects of dopamine on mechanisms of synaptic plasticity in awake rats. Long-term potentiation and depression were successfully induced in control animals, but the same stimulation protocols failed to alter synaptic function in animals treated with a dopamine reuptake inhibitor. The effects of depleting dopamine in the entorhinal cortex on olfactory memory were also assessed using an olfactory non-match-to-sample task. Rats with 6-OHDA lesions of the entorhinal cortex made more errors and took nearly twice as long to reacquire criterion performance relative to control animals during post-surgical retraining. However, once criterion performance was re-attained, the behavior of lesioned animals was indistinguishable from controls on a version of the task involving longer delay periods. These findings point to multiple mechanisms through which exposure to different concentrations of dopamine may modulate sensory and mnemonic processing by modulating synaptic transmission within the lateral entorhinal cortex

Inhibitory mechanisms for visual learning in the human brain

Identifying targets in cluttered scenes is critical for our interactions in complex environments. Our visual system is challenged to both detect elusive targets that we may want to avoid or chase and discriminate between targets that are highly similar. These tasks require our visual system to become an expert at detecting distinctive features that help us differentiate between indistinguishable targets. As the human brain is trained on this type of visual tasks, we observe changes in its function that correspond to improved performance. We use functional brain imaging, to measure learning-dependent modulations of brain activation and investigate the processes that mediate functional brain plasticity. I propose that dissociable brain mechanisms are engaged when detecting targets in clutter vs. discriminating between highly similar targets: for the former, background clutter needs to be suppressed for the target to be recognised, whereas for the latter, neurons are tuned to respond to fine differences. Although GABAergic inhibition is known to suppress redundant neuronal populations and tune neuronal representations, its role in visual learning remains largely unexplored. Here, I propose that GABAergic inhibition plays an important role in visual plasticity through training on these tasks. The purpose of my PhD is to investigate the inhibitory mechanisms that mediate visual perceptual learning; in particular, learning to detect patterns in visual clutter and discriminate between highly similar patterns. I show that BOLD signals as measured by functional Magnetic Resonance Imaging (fMRI) do not differentiate between the two proposed mechanisms. In contrast, Magnetic Resonance Spectroscopy (MRS) provides strong evidence for the distinct involvement of GABAergic inhibition in visual plasticity. Further, my findings show GABA changes during the time-course of learning providing evidence for a distinct role of GABA in learning-dependent plasticity across different brain regions involved in visual learning. Finally, I test the causal link between inhibitory contributions and visual plasticity using a brain stimulation intervention that perturbs the excitation-inhibition balance in the visual cortex and facilitates learning

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task