Introduction

Background

LSD-induced visual hallucinations, particularly geometric patterns, have long fascinated researchers in neuroscience and psychology. These hallucinations, often referred to as 'form constants', are subjective visual experiences commonly reported by individuals under the influence of psychedelic substances.

Problem Statement and Study Significance

Despite decades of research, there is a lack of up-to-date, quantitative models explaining the neural mechanisms underlying these visual hallucinations. This study aims to develop a computational model that bridges this gap in our understanding.

Literature Review

Current State of Knowledge

• Geometric patterns in visual hallucinations are well-documented
• Existing literature is largely outdated
• Recent advancements in neuroimaging and computational neuroscience offer new opportunities for modeling

Gap in Current Literature

There is a need for modern, quantitative models that can simulate the neural processes leading to LSD-induced visual hallucinations, particularly the generation of spiral patterns.

Research Objectives and Hypotheses

Primary Objective

To develop a quantitative computational model of cortical activity that can generate patterns similar to those reported in LSD-induced visual hallucinations.

Secondary Objectives

1. Analyze existing theoretical and neural models of visual hallucinations
2. Implement a spiking neural network model with cortex-like properties
3. Investigate the effects of excitatory drive on the model's behavior

Hypothesis