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The recent findings from cognitive science – one of the fastest growing disciplines worldwide – presented in the volume will serve as a useful resource for scientists/psychologists working in the area. The book highlights the current trends in major sub-disciplines in cognitive science and contains high quality succinct papers covering current challenges, with cross-linking of different interfacing disciplines like psychology, neuroscience, computer science, linguistics, and philosophy.

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List of Figures

    Chapter 1

  • 1.1 Illustration of behavioural stream and three theories of action of reinforcers. SD = discriminative stimulus, R = response, SR = reinforcer 8
  • 1.2 Illustration of a transfer-of-control procedure 10
  • 1.3 Latency to perform an avoidance response as a function of stimulus type and test day 11
  • 1.4 Illustration of a standard discriminative conditional choice task employing common outcomes, and a similar task employing differential outcomes 12
  • 1.5 Performance in a bi-conditional discrimination task under differential and common outcomes procedures 13
  • 1.6 Illustration of the transfer-of-control procedure employed by Kruse et al. (1983) 14
  • 1.7 Illustration of an experimental design for showing inter-problem transfer of control of choice 16
  • 1.8 Illustration of a stimulus equivalence training procedure similar to that employed in Joseph et al. (1997) 17
  • 1.9 Data on the short-term working memory of normal older men and older men with Korsakoff's disease 20

    Chapter 2

  • 2.1 Examples of map displays used in Experiment 1: The global landmark conditions (global-inside: A, global-outside: B, and without-global landmark: C) 27
  • 2.2 Example sequences of displays used in Experiment 1 (Aligned and Misaligned versions of a global landmark inside two local landmark conditions) 28
  • 2.3 Mean response speed and standard errors for the interaction of the global landmark and Alignment of the test display in Experiment 1 30
  • 2.4 Mean response speed and standard errors for the interaction between local landmark and Alignment test display conditions in Experiment 1 32
  • 2.5 Mean response speed and standard errors for the interaction between the arrangement of landmarks (fixed versus random), number of local landmarks, and the Alignment of the test display in Experiment 1 34
  • 2.6 Example of maps used as stimuli in Experiment 2 36
  • 2.7 Mean response speed and standard errors for the interaction between type of landmark and Alignment of the test display in Experiment 2 38
  • 2.8 Mean response speeds and standard errors between Arrangement and type of landmark conditions in Experiment 2 39

    Chapter 3

  • 3.1 Mean reaction times during the 15 blocks of the SRT task plotted separately for participants trained with a 0 ms or 1000 ms RSI. Block 13 is the transfer block during which another sequence was used. 48
  • 3.2 Mean recognition scores in RSI 0 and RSI 1000 conditions when either a constant (CST) or variable (VAR) RSI was used at test. 50
  • 3.3 RTs recorded for old and new fragments presented in the recognition task to participants trained with a 0 ms or a 1000 ms RSI and plotted separately for fragments presented at test with either a constant (CST) or variable (VAR) RSI 51

    Chapter 4

  • 4.1 Sequence Learning Tasks 58
  • 4.2 Summary snapshot of a subject (AS) from “mild-learning” group of 1 × 12 experiment 62
  • 4.3 Summary snapshot of a subject (AS) from “mild-learning” group of 2 × 6 experiment 63
  • 4.4 Summary snapshot of a subject (ST) from “mild-learning” group of 1 × 12 experiment 65
  • 4.5 Summary snapshot of a subject (JY) from “mild-learning” group of 2 × 6 experiment 66
  • 4.6 Summary snapshot of a subject (BN) from “continued-learning” group of 1 × 12 experiment 67
  • 4.7 Summary snapshot of a subject (BN) from “continued-learning” group of 2 × 6 experiment 68

    Chapter 5

  • 5.1 ACE Architecture 73
  • 5.2 Simple muscle model system 74
  • 5.3 (a) Architecture of the actor network (b) The 2D arm and the targets to be reached 75
  • 5.4 Architecture of the critic network 75
  • 5.5 Architecture of the explorer 76
  • 5.6 (a) STN-GPe neuron pair illustrating the excitatory and inhibitory connections, (b) Network model of STN-GPe loop with lateral connections 78
  • 5.7 Dynamics of the STN-GPe Loop: Three characteristic patterns of activity in the STN-GPe layer - (a) Uncorrelated activity, (b) Travelling waves, and (c) Clustering 79
  • 5.8 Snapshots of STN activity for various values of DNe: (a) DNe = 50; observed E-dim ∼ 96, (b) DNe = 20; observed E-dim ∼ 48, (c) DNe = 5; observed E-dim ∼ 15. There is a consistent decrease in E-dim with decreasing DNe81
  • 5.9 Output of the Critic for different targets, with the x-y plane representing [ga, gb] values and the z-axis representing the Value, Q 83
  • 5.10 (a) The dynamics of the model before learning, E-dim = 93, (b) The dynamics of the model after learning for eight epochs, E-dim = 57, (c) The dynamics of the model at the end of learning, E-dim = 5 85
  • 5.11 The relation between norepinephrine (DNe) in the STN-GPe layer and δ 86
  • 5.12 Changes due to dopamine reduction 87

    Chapter 7

  • 7.1 Typical reflexive spatial attention task used to elicit IOR 106
  • 7.2 Typical behavioural results obtained in a reflexive spatial attention task 107
  • 7.3 Behavioural results of monkeys in a reflexive spatial attention task 109
  • 7.4 Activity of SC neurons during a reflexive spatial attention task 110
  • 7.5 Stimulus repetition suppression effects in the ventral steam during a serial recognition task 112
  • 7.6 Stimulus repetition suppression effects in the ventral steam during delayed match-to-sample tasks 114
  • 7.7 Schematic localization of visual pathways in the macaque brain 115
  • 7.8 Schematic diagram of the fixation task (one location, eight shapes) 116
  • 7.9 Activity of AIT and LIP shape selective neurons during a passive fixation task with repeated stimulus presentations within a trial 117
  • 7.10 Repetition suppression effects in AIT and LIP 118
  • 7.11 Repetition suppression effects in LIP across six blocks of trials 119
  • 7.12 Proposed network model of reflexive spatial attention 120
  • 7.13 Simulated outputs of the model at three different CTOAs during a reflexive attention task 121
  • 7.14 Simulation of reflexive spatial attention and the influence of shape 123

    Chapter 8

  • 8.1 Search times for sad and happy schematic faces in a detection task 136
  • 8.2 Search times for sad and happy schematic faces in a discrimination task 137
  • 8.3 The magnitude of flanker compatibility 143
  • 8.4 N 100 component (90 to 140 ms; frontal sites) depicts increased amplitude for happy target faces compared to threatening target faces 144
  • 8.5 N2 component (220 to 260 ms; central midline sites) is locked to stimulus onset and reflects processing of conflict 144
  • 8.6 ERN component (60 to 90 ms; central midline sites) is locked to onset of response and reflects processing of errors 145

    Chapter 9

  • 9.1 The architecture of the sSoTS model 153
  • 9.2 The mean correct reaction times (RTs, in ms) for the unlesioned (dotted lines) and lesioned versions (solid lines) of sSoTS 160
  • 9.3 The mean percentage miss responses for the lesioned versions of sSoTS (data from Simulation 1) 161
  • 9.4 Example displays from Simulation 2 163
  • 9.5 The mean correct RTs (ms) from Simulation 2 164
  • 9.6 (a) The mean correct RTs (ms) and (b) the mean percentage miss responses for Simulation 3 (variation in the NMDA parameter) 167

    Chapter 10

  • 10.1 Schematic of the experimental task in saccade and control conditions 184
  • 10.2 Time estimation data 186

    Chapter 11

  • 11.1 The debut effect 198
  • 11.2 Repeated stimuli subjectively proliferate less than random stimuli 201
  • 11.3 Proposed repetition suppression diagnostic tool 203

    Chapter 12

  • 12.1 SOA 209
  • 12.2 Polyrhythmic Sequence 211
  • 12.3 Mean Stop-RT (ms) averaged across 20 participants in a bimodal single SOA experiment from our lab 212
  • 12.4 Performance on two SOA Polyrhythmic Sequence 214
  • 12.5 Examples of typical passive oddball paradigms used in mismatch negativity (MMN) studies of interval timing 217

    Chapter 13

  • 13.1 Contingent Negative Variation (CNV) 226
  • 13.2 Generalization gradients 227
  • 13.3 Peak latency 228
  • 13.4 Mean CNVs 229
  • 13.5 Three hypothetical models of the neural mechanisms for timing 230
  • 13.6 Attention conditions 231
  • 13.7 Estimation of Activations due to length of duration 233
  • 13.8 Waveforms 235
  • 13.9 Time course activity 236
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