December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 1 Some YouTube movies: The Neocognitron Part I:

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December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 1 Some YouTube movies: The Neocognitron Part I: The Neocognitron Part II: Automatic license plate recognition: Evolution of neural network robotic controllers:

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 2 Review of Neural Network Facts In biological systems, neurons of similar functionality are usually organized in separate areas (or layers).In biological systems, neurons of similar functionality are usually organized in separate areas (or layers). Often, there is a hierarchy of interconnected layers with the lowest layer receiving sensory input and neurons in higher layers computing more complex functions.Often, there is a hierarchy of interconnected layers with the lowest layer receiving sensory input and neurons in higher layers computing more complex functions. For example, neurons in macaque visual cortex have been identified that are activated only when there is a face (monkey, human, or drawing) in the macaque’s visual field.For example, neurons in macaque visual cortex have been identified that are activated only when there is a face (monkey, human, or drawing) in the macaque’s visual field.

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 3 “Data Flow Diagram” of Visual Areas in Macaque Brain Blue: motion perception pathway Green: object recognition pathway

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 4 Receptive Fields in Hierarchical Neural Networks neuron A receptive field of A

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 5 Receptive Fields in Hierarchical Neural Networks receptive field of A in input layer neuron A in top layer

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 6 Visual Attention The attentional cueing task introduced by Michael Posner gives insight into the dynamics of visual attention. Subjects are instructed to fixate on the central cross. One of the two boxes flashes to capture the subject’s attention (an automatic, involuntary response). After some a short delay (stimulus onset asynchrony - SOA) an asterisk appears in one of the boxes. The subject has to report as quickly as possible in which box the asterisk appeared.

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 7 The Posner Attention Task x

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 8 The Posner Attention Task x

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 9 The Posner Attention Task x

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 10 The Posner Attention Task * x

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 11 The Posner Attention Task x

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 12 The Posner Attention Task For short SOAs (< 200 ms), subjects respond faster if flash and asterisk appear on the same side.  Cueing of attention to relevant location allows faster response. For longer SOAs, subjects respond more slowly if flash and asterisk appear on the same side.  Inhibition-of-Return mechanism makes attention less likely to remain on the side of the flash until the asterisk appears.

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 13 The Fröhlich Effect The Fröhlich effect is a localization error that occurs when observers are asked to indicate the initial position of a fast moving stimulus. Compared to the actual starting location, the perceived starting location is shifted in the direction of motion. This perceptual illusion was named after Friedrich Fröhlich, a German physiologist who discovered the phenomenon more than 80 years ago.

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 14 The Fröhlich Effect Today the most widely accepted explanation of this effect is given by the “Asynchronous Updating Model” (Scharlau & Neumann, 2003). This model states that the stimulus onset triggers an attention shift towards its location. During the shift the stimulus changes its location, and because the conscious perception depends on the stimulus being attended, a later position is consciously perceived as being the first position.

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 15 The Fröhlich Effect We tried to build a quantitative, neural model of the relevant parts of the visual system to explain this effect. This model includes a vision hierarchy (simple features and small receptive fields in lower layers, complex features and large receptive fields in higher layers). In this hierarchy, processing of visual input is done in bottom-up direction, and attentional modulation (selective enhancement of processing) works in a top- down fashion.

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 16 The Fröhlich Effect Model

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 17 The Fröhlich Effect - Results

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 18 The Fröhlich Effect - Results

December 1, 2009Introduction to Cognitive Science Lecture 22: Neural Models of Mental Processes 19 The Fröhlich Effect - Results